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Sample records for building clinical decision

  1. Information management to enable personalized medicine: stakeholder roles in building clinical decision support.

    Science.gov (United States)

    Downing, Gregory J; Boyle, Scott N; Brinner, Kristin M; Osheroff, Jerome A

    2009-10-08

    Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures), and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In addition, to represent meaningful benefits to personalized

  2. Information management to enable personalized medicine: stakeholder roles in building clinical decision support

    Directory of Open Access Journals (Sweden)

    Brinner Kristin M

    2009-10-01

    Full Text Available Abstract Background Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Discussion Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures, and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. Summary This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In

  3. Combining data and meta-analysis to build Bayesian networks for clinical decision support.

    Science.gov (United States)

    Yet, Barbaros; Perkins, Zane B; Rasmussen, Todd E; Tai, Nigel R M; Marsh, D William R

    2014-12-01

    Complex clinical decisions require the decision maker to evaluate multiple factors that may interact with each other. Many clinical studies, however, report 'univariate' relations between a single factor and outcome. Such univariate statistics are often insufficient to provide useful support for complex clinical decisions even when they are pooled using meta-analysis. More useful decision support could be provided by evidence-based models that take the interaction between factors into account. In this paper, we propose a method of integrating the univariate results of a meta-analysis with a clinical dataset and expert knowledge to construct multivariate Bayesian network (BN) models. The technique reduces the size of the dataset needed to learn the parameters of a model of a given complexity. Supplementing the data with the meta-analysis results avoids the need to either simplify the model - ignoring some complexities of the problem - or to gather more data. The method is illustrated by a clinical case study into the prediction of the viability of severely injured lower extremities. The case study illustrates the advantages of integrating combined evidence into BN development: the BN developed using our method outperformed four different data-driven structure learning methods, and a well-known scoring model (MESS) in this domain. Copyright © 2014 Elsevier Inc. All rights reserved.

  4. Building a normative decision support system for clinical and operational risk management in hemodialysis.

    Science.gov (United States)

    Cornalba, Chiara; Bellazzi, Roberto G; Bellazzi, Riccardo

    2008-09-01

    This paper describes the design and implementation of a decision support system for risk management in hemodialysis (HD) departments. The proposed system exploits a domain ontology to formalize the problem as a Bayesian network. It also relies on a software tool, able to automatically collect HD data, to learn the network conditional probabilities. By merging prior knowledge and the available data, the system allows to estimate risk profiles both for patients and HD departments. The risk management process is completed by an influence diagram that enables scenario analysis to choose the optimal decisions that mitigate a patient's risk. The methods and design of the decision support tool are described in detail, and the derived decision model is presented. Examples and case studies are also shown. The tool is one of the few examples of normative system explicitly conceived to manage operational and clinical risks in health care environments.

  5. A Temporal Mining Framework for Classifying Un-Evenly Spaced Clinical Data: An Approach for Building Effective Clinical Decision-Making System.

    Science.gov (United States)

    Jane, Nancy Yesudhas; Nehemiah, Khanna Harichandran; Arputharaj, Kannan

    2016-01-01

    Clinical time-series data acquired from electronic health records (EHR) are liable to temporal complexities such as irregular observations, missing values and time constrained attributes that make the knowledge discovery process challenging. This paper presents a temporal rough set induced neuro-fuzzy (TRiNF) mining framework that handles these complexities and builds an effective clinical decision-making system. TRiNF provides two functionalities namely temporal data acquisition (TDA) and temporal classification. In TDA, a time-series forecasting model is constructed by adopting an improved double exponential smoothing method. The forecasting model is used in missing value imputation and temporal pattern extraction. The relevant attributes are selected using a temporal pattern based rough set approach. In temporal classification, a classification model is built with the selected attributes using a temporal pattern induced neuro-fuzzy classifier. For experimentation, this work uses two clinical time series dataset of hepatitis and thrombosis patients. The experimental result shows that with the proposed TRiNF framework, there is a significant reduction in the error rate, thereby obtaining the classification accuracy on an average of 92.59% for hepatitis and 91.69% for thrombosis dataset. The obtained classification results prove the efficiency of the proposed framework in terms of its improved classification accuracy.

  6. Analysing clinical decision analyses

    NARCIS (Netherlands)

    Habbema, J. D.; Bossuyt, P. M.; Dippel, D. W.; Marshall, S.; Hilden, J.

    1990-01-01

    We present a critical review of aspects of clinical decision analysis which uses an application to screening for familial intracranial aneurysms. The analysis is reported together with methods for assessing decision trees. These methods appear to be powerful checks on the usually rather intuitive

  7. Decision time for clinical decision support systems.

    Science.gov (United States)

    O'Sullivan, Dympna; Fraccaro, Paolo; Carson, Ewart; Weller, Peter

    2014-08-01

    Clinical decision support systems are interactive software systems designed to help clinicians with decision-making tasks, such as determining a diagnosis or recommending a treatment for a patient. Clinical decision support systems are a widely researched topic in the computer science community, but their inner workings are less well understood by, and known to, clinicians. This article provides a brief explanation of clinical decision support systems and some examples of real-world systems. It also describes some of the challenges to implementing these systems in clinical environments and posits some reasons for the limited adoption of decision-support systems in practice. It aims to engage clinicians in the development of decision support systems that can meaningfully help with their decision-making tasks and to open a discussion about the future of automated clinical decision support as a part of healthcare delivery. © 2014 Royal College of Physicians.

  8. Clinical decision modeling system

    Directory of Open Access Journals (Sweden)

    Lyons-Weiler James

    2007-08-01

    Full Text Available Abstract Background Decision analysis techniques can be applied in complex situations involving uncertainty and the consideration of multiple objectives. Classical decision modeling techniques require elicitation of too many parameter estimates and their conditional (joint probabilities, and have not therefore been applied to the problem of identifying high-performance, cost-effective combinations of clinical options for diagnosis or treatments where many of the objectives are unknown or even unspecified. Methods We designed a Java-based software resource, the Clinical Decision Modeling System (CDMS, to implement Naïve Decision Modeling, and provide a use case based on published performance evaluation measures of various strategies for breast and lung cancer detection. Because cost estimates for many of the newer methods are not yet available, we assume equal cost. Our use case reveals numerous potentially high-performance combinations of clinical options for the detection of breast and lung cancer. Results Naïve Decision Modeling is a highly practical applied strategy which guides investigators through the process of establishing evidence-based integrative translational clinical research priorities. CDMS is not designed for clinical decision support. Inputs include performance evaluation measures and costs of various clinical options. The software finds trees with expected emergent performance characteristics and average cost per patient that meet stated filtering criteria. Key to the utility of the software is sophisticated graphical elements, including a tree browser, a receiver-operator characteristic surface plot, and a histogram of expected average cost per patient. The analysis pinpoints the potentially most relevant pairs of clinical options ('critical pairs' for which empirical estimates of conditional dependence may be critical. The assumption of independence can be tested with retrospective studies prior to the initiation of

  9. Decision analysis using decision trees for a simple clinical decision.

    Science.gov (United States)

    Blakley, Brian

    2012-10-01

    To illustrate the use of decision trees with a utility index in clinical decision making. A decision tree was created related to whether or not to perform a tonsillectomy. Data from the literature were applied to a common hypothetical clinical scenario. A decision tree graphically represents the typical decision-making process that many clinicians use. The addition of utility functions permitted consideration of the adverse or beneficial effects of outcomes, altering the treatment decision. Quantitative tools such as decision trees may quantify outcome preferences and aid in clinical decision making, but the proper tool and background data are essential.

  10. Clinical decision support systems.

    Science.gov (United States)

    Beeler, Patrick Emanuel; Bates, David Westfall; Hug, Balthasar Luzius

    2014-01-01

    Clinical decision support (CDS) systems link patient data with an electronic knowledge base in order to improve decision-making and computerised physician order entry (CPOE) is a requirement to set up electronic CDS. The medical informatics literature suggests categorising CDS tools into medication dosing support, order facilitators, point-of-care alerts and reminders, relevant information display, expert systems and workflow support. To date, CDS has particularly been recognised for improving processes. CDS successfully fostered prevention of deep-vein thrombosis, improved adherence to guidelines, increased the use of vaccinations, and decreased the rate of serious medication errors. However, CDS may introduce errors, and therefore the term "e-iatrogenesis" has been proposed to address unintended consequences. At least two studies reported severe treatment delays due to CPOE and CDS. In addition, the phenomenon of "alert fatigue" - arising from a high number of CDS alerts of low clinical significance - may facilitate overriding of potentially critical notifications. The implementation of CDS needs to be carefully planned, CDS interventions should be thoroughly examined in pilot wards only, and then stepwise introduced. A crucial feature of CPOE in combination with CDS is speed, since time consumption has been found to be a major factor determining failure. In the near future, the specificity of alerts will be improved, notifications will be prioritised and offer detailed advice, customisation of CDS will play an increasing role, and finally, CDS is heading for patient-centred decision support. The most important research question remains whether CDS is able to improve patient outcomes beyond processes.

  11. Clinical Decision Support (CDS) Inventory

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Clinical Decision Support (CDS) Inventory contains descriptions of past and present CDS projects across the Federal Government. It includes Federal projects,...

  12. Integrating clinical research into clinical decision making

    Directory of Open Access Journals (Sweden)

    Mark R Tonelli

    2011-01-01

    Full Text Available Evidence-based medicine has placed a general priority on knowledge gained from clinical research for clinical decision making. However, knowledge derived from empiric, population-based research, while valued for its ability to limit bias, is not directly applicable to the care of individual patients. The gap between clinical research and individual patient care centers on the fact that empiric research is not generally designed to answer questions of direct relevance to individual patients. Clinicians must utilize other forms of medical knowledge, including pathophysiologic rationale and clinical experience, in order to arrive at the best medical decision for a particular patient. In addition, clinicians must also elucidate and account for the goals and values of individual patients as well as barriers and facilitators of care inherent in the system in which they practice. Evidence-based guidelines and protocols, then, can never be prescriptive. Clinicians must continue to rely on clinical judgment, negotiating potentially conflicting warrants for action, in an effort to arrive at the best decision for a particular patient.

  13. Multi-criteria decision-making process for buildings

    Energy Technology Data Exchange (ETDEWEB)

    Balcomb, J. D.; Curtner, A.

    2000-06-20

    This paper focuses on a process designed to facilitate two key decisions early in the building design process that are critical to a building's sustainability. As vital decisions are made during the building's design, the process and accompanying tools assist the design team in prioritizing their goals, setting performance targets, and evaluating design options to ensure that the most important issues affecting building sustainability are considered.

  14. Dialogic Consensus In Clinical Decision-Making.

    Science.gov (United States)

    Walker, Paul; Lovat, Terry

    2016-12-01

    This paper is predicated on the understanding that clinical encounters between clinicians and patients should be seen primarily as inter-relations among persons and, as such, are necessarily moral encounters. It aims to relocate the discussion to be had in challenging medical decision-making situations, including, for example, as the end of life comes into view, onto a more robust moral philosophical footing than is currently commonplace. In our contemporary era, those making moral decisions must be cognizant of the existence of perspectives other than their own, and be attuned to the demands of inter-subjectivity. Applicable to clinical practice, we propose and justify a Habermasian approach as one useful means of achieving what can be described as dialogic consensus. The Habermasian approach builds around, first, his discourse theory of morality as universalizable to all and, second, communicative action as a cooperative search for truth. It is a concrete way to ground the discourse which must be held in complex medical decision-making situations, in its actual reality. Considerations about the theoretical underpinnings of the application of dialogic consensus to clinical practice, and potential difficulties, are explored.

  15. Primer on medical decision analysis: Part 2--Building a tree.

    Science.gov (United States)

    Detsky, A S; Naglie, G; Krahn, M D; Redelmeier, D A; Naimark, D

    1997-01-01

    This part of a five-part series covering practical issues in the performance of decision analysis outlines the basic strategies for building decision trees. The authors offer six recommendations for building and programming decision trees. Following these six recommendations will facilitate performance of the sensitivity analyses required to achieve two goals. The first is to find modeling or programming errors, a process known as "debugging" the tree. The second is to determine the robustness of the qualitative conclusions drawn from the analysis.

  16. On algorithm for building of optimal α-decision trees

    KAUST Repository

    Alkhalid, Abdulaziz

    2010-01-01

    The paper describes an algorithm that constructs approximate decision trees (α-decision trees), which are optimal relatively to one of the following complexity measures: depth, total path length or number of nodes. The algorithm uses dynamic programming and extends methods described in [4] to constructing approximate decision trees. Adjustable approximation rate allows controlling algorithm complexity. The algorithm is applied to build optimal α-decision trees for two data sets from UCI Machine Learning Repository [1]. © 2010 Springer-Verlag Berlin Heidelberg.

  17. Building effective clinical teams in healthcare.

    Science.gov (United States)

    Ezziane, Zoheir; Maruthappu, Mahiben; Gawn, Lynsey; Thompson, Emily A; Athanasiou, Thanos; Warren, Oliver J

    2012-01-01

    This article aims to review teamwork and the creation of effective teams within healthcare. By combining research material found in management, psychology and health services research the article explores the drivers increasing the importance of teamwork, reviews the current knowledge base on how to build a team and focuses on some of the barriers to effective team performance. The simultaneous inflation of healthcare costs and necessity to improve quality of care has generated a demand for novel solutions in policy, strategy, commissioning and provider organisations. A critical, but commonly undervalued means by which quality can be improved is through structured, formalised incentivisation and development of teams, and the ability of individuals to work collectively and in collaboration. Several factors appear to contribute to the development of successful teams, including effective communication, comprehensive decision making, safety awareness and the ability to resolve conflict. Not only is strong leadership important if teams are to function effectively but the concept and importance of followership is also vital. Building effective clinical teams is difficult. The research in this area is currently limited, as is the authors' understanding of the different requirements faced by those working in different areas of the health and social care environment. This article provides a starting place for those interested in leading and developing teams of clinicians.

  18. Building models for marketing decisions : Past, present and future

    NARCIS (Netherlands)

    Leeflang, PSH; Wittink, DR

    We review five eras of model building in marketing, with special emphasis on the fourth and the fifth eras, the present and the future. At many firms managers now routinely use model-based results for marketing decisions. Given an increasing number of successful applications, the demand for models

  19. Building models for marketing decisions : past, present and future

    NARCIS (Netherlands)

    Leeflang, P.S.H.; Wittink, Dick R.

    2000-01-01

    We review five eras of model building in marketing, with special emphasis on the fourth and the fifth eras, the present and the future. At many firms managers now routinely use model-based results for marketing decisions. Given an increasing number of successful applications, the demand for models

  20. A distributed clinical decision support system architecture

    OpenAIRE

    Shaker H. El-Sappagh; El-Masri, Samir

    2014-01-01

    This paper proposes an open and distributed clinical decision support system architecture. This technical architecture takes advantage of Electronic Health Record (EHR), data mining techniques, clinical databases, domain expert knowledge bases, available technologies and standards to provide decision-making support for healthcare professionals. The architecture will work extremely well in distributed EHR environments in which each hospital has its own local EHR, and it satisfies the compatibi...

  1. Towards standardising building rural clinics: energy requirements

    CSIR Research Space (South Africa)

    Szewczuk, S

    2015-03-01

    Full Text Available (brick and mortar) and Innovative Building Technologies (IBTs) and alternative off-grid services technologies (energy, water, and sanitation). The paper discusses the energy requirements of a conceptual design for a generic, basic rural clinic....

  2. Multi-criteria decision model for retrofitting existing buildings

    Science.gov (United States)

    Bostenaru Dan, M. D.

    2004-08-01

    Decision is an element in the risk management process. In this paper the way how science can help in decision making and implementation for retrofitting buildings in earthquake prone urban areas is investigated. In such interventions actors from various spheres are involved. Their interests range among minimising the intervention for maximal preservation or increasing it for seismic safety. Research was conducted to see how to facilitate collaboration between these actors. A particular attention was given to the role of time in actors' preferences. For this reason, on decision level, both the processural and the personal dimension of risk management, the later seen as a task, were considered. A systematic approach was employed to determine the functional structure of a participative decision model. Three layers on which actors implied in this multi-criteria decision problem interact were identified: town, building and element. So-called 'retrofit elements' are characteristic bearers in the architectural survey, engineering simulations, costs estimation and define the realms perceived by the inhabitants. This way they represent an interaction basis for the interest groups considered in a deeper study. Such orientation means for actors' interaction were designed on other levels of intervention as well. Finally, an 'experiment' for the implementation of the decision model is presented: a strategic plan for an urban intervention towards reduction of earthquake hazard impact through retrofitting. A systematic approach proves thus to be a very good communication basis among the participants in the seismic risk management process. Nevertheless, it can only be applied in later phases (decision, implementation, control) only, since it serves verifying and improving solution and not developing the concept. The 'retrofit elements' are a typical example of the detailing degree reached in the retrofit design plans in these phases.

  3. Multi-criteria decision model for retrofitting existing buildings

    Directory of Open Access Journals (Sweden)

    M. D. Bostenaru Dan

    2004-01-01

    Full Text Available Decision is an element in the risk management process. In this paper the way how science can help in decision making and implementation for retrofitting buildings in earthquake prone urban areas is investigated. In such interventions actors from various spheres are involved. Their interests range among minimising the intervention for maximal preservation or increasing it for seismic safety. Research was conducted to see how to facilitate collaboration between these actors. A particular attention was given to the role of time in actors' preferences. For this reason, on decision level, both the processural and the personal dimension of risk management, the later seen as a task, were considered. A systematic approach was employed to determine the functional structure of a participative decision model. Three layers on which actors implied in this multi-criteria decision problem interact were identified: town, building and element. So-called 'retrofit elements' are characteristic bearers in the architectural survey, engineering simulations, costs estimation and define the realms perceived by the inhabitants. This way they represent an interaction basis for the interest groups considered in a deeper study. Such orientation means for actors' interaction were designed on other levels of intervention as well. Finally, an 'experiment' for the implementation of the decision model is presented: a strategic plan for an urban intervention towards reduction of earthquake hazard impact through retrofitting. A systematic approach proves thus to be a very good communication basis among the participants in the seismic risk management process. Nevertheless, it can only be applied in later phases (decision, implementation, control only, since it serves verifying and improving solution and not developing the concept. The 'retrofit elements' are a typical example of the detailing degree reached in the retrofit design plans in these phases.

  4. Smart Building: Decision Making Architecture for Thermal Energy Management

    OpenAIRE

    Oscar Hernández Uribe; Juan Pablo San Martin; María C. Garcia-Alegre; Matilde Santos; Domingo Guinea

    2015-01-01

    Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks, soft computing methodologies, machine intelligence algorithms and pervasive sensors are some of the basics of energy optimization strategies developed for the benefit of environmental sustainability and user comfort. This work presents a distributed sensor-processor-communication decision-making architecture to improve the acquisition, stora...

  5. Sustainability focused Decision-making in Building Renovation

    DEFF Research Database (Denmark)

    Kamari, Aliakbar; Corrao, Rossella; Kirkegaard, Poul Henning

    2017-01-01

    An overview of recent research related to building renovation has revealed that efforts to date do not address sustainability issues comprehensively. The question then arises in regard to the holistic sustainability objectives within building renovation context. In order to deal with this question...... sustainability objectives have been collected and structured, and subsequently verified using a Delphi study. A sustainability framework was developed in cooperation with University of Palermo and Aarhus University to audit, develop and assess building renovation performance, and support decision-making during...... the project’s lifecycle. The paper represents the results of research aiming at addressing sustainability of the entire renovation effort including new categories, criteria, and indicators. The developed framework can be applied during different project stages and to assist in the consideration...

  6. Anesthesia information management: clinical decision support.

    Science.gov (United States)

    Freundlich, Robert E; Ehrenfeld, Jesse M

    2017-12-01

    Perioperative informatics tools continue to be developed at a rapid pace and offer clinicians the potential to greatly enhance clinical decision making. The goal of this review is to bring the reader updates on perioperative information management and discuss future research directions in the field. Clinical decision support tools become more timely, accurate, and, in some instances, have been shown to improve patient outcomes. When correctly implemented, they are critical tools for optimization of perioperative care. Perioperative informaticians continue to test new and innovative ways to enhance the delivery of anesthesia care, improving the safety and efficacy of perioperative management. Future work will continue to refine tools to ensure that perioperative informatics provides clinicians timely and accurate feedback, with demonstrable evidence that a decision support system improves patient outcomes.

  7. Modelling and Decision Support of Clinical Pathways

    Science.gov (United States)

    Gabriel, Roland; Lux, Thomas

    The German health care market is under a rapid rate of change, forcing especially hospitals to provide high-quality services at low costs. Appropriate measures for more effective and efficient service provision are process orientation and decision support by information technology of clinical pathway of a patient. The essential requirements are adequate modelling of clinical pathways as well as usage of adequate systems, which are capable of assisting the complete path of a patient within a hospital, and preferably also outside of it, in a digital way. To fulfil these specifications the authors present a suitable concept, which meets the challenges of well-structured clinical pathways as well as rather poorly structured diagnostic and therapeutic decisions, by interplay of process-oriented and knowledge-based hospital information systems.

  8. Building the Clinical Bridge: An Australian Success

    Directory of Open Access Journals (Sweden)

    Marianne Wallis

    2012-01-01

    Full Text Available Nursing effectiveness science includes primary, secondary, and translational, clinically focused research activities which aim to improve patient or client outcomes. It is imperative, for the successful conduct of a program of nursing effectiveness science, that a clinical bridge is established between academic and healthcare service facilities. An Australian example of the development of a robust clinical bridge through the use of jointly funded positions at the professorial level is outlined. In addition, an analysis of the practical application of Lewin’s model of change management and the contribution of both servant and transformational leadership styles to the bridge building process is provided.

  9. Smart Building: Decision Making Architecture for Thermal Energy Management

    Directory of Open Access Journals (Sweden)

    Oscar Hernández Uribe

    2015-10-01

    Full Text Available Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks, soft computing methodologies, machine intelligence algorithms and pervasive sensors are some of the basics of energy optimization strategies developed for the benefit of environmental sustainability and user comfort. This work presents a distributed sensor-processor-communication decision-making architecture to improve the acquisition, storage and transfer of thermal energy in buildings. The developed system is implemented in a near Zero-Energy Building (nZEB prototype equipped with a built-in thermal solar collector, where optical properties are analysed; a low enthalpy geothermal accumulation system, segmented in different temperature zones; and an envelope that includes a dynamic thermal barrier. An intelligent control of this dynamic thermal barrier is applied to reduce the thermal energy demand (heating and cooling caused by daily and seasonal weather variations. Simulations and experimental results are presented to highlight the nZEB thermal energy reduction.

  10. Smart Building: Decision Making Architecture for Thermal Energy Management.

    Science.gov (United States)

    Uribe, Oscar Hernández; Martin, Juan Pablo San; Garcia-Alegre, María C; Santos, Matilde; Guinea, Domingo

    2015-10-30

    Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks, soft computing methodologies, machine intelligence algorithms and pervasive sensors are some of the basics of energy optimization strategies developed for the benefit of environmental sustainability and user comfort. This work presents a distributed sensor-processor-communication decision-making architecture to improve the acquisition, storage and transfer of thermal energy in buildings. The developed system is implemented in a near Zero-Energy Building (nZEB) prototype equipped with a built-in thermal solar collector, where optical properties are analysed; a low enthalpy geothermal accumulation system, segmented in different temperature zones; and an envelope that includes a dynamic thermal barrier. An intelligent control of this dynamic thermal barrier is applied to reduce the thermal energy demand (heating and cooling) caused by daily and seasonal weather variations. Simulations and experimental results are presented to highlight the nZEB thermal energy reduction.

  11. Smart Building: Decision Making Architecture for Thermal Energy Management

    Science.gov (United States)

    Hernández Uribe, Oscar; San Martin, Juan Pablo; Garcia-Alegre, María C.; Santos, Matilde; Guinea, Domingo

    2015-01-01

    Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks, soft computing methodologies, machine intelligence algorithms and pervasive sensors are some of the basics of energy optimization strategies developed for the benefit of environmental sustainability and user comfort. This work presents a distributed sensor-processor-communication decision-making architecture to improve the acquisition, storage and transfer of thermal energy in buildings. The developed system is implemented in a near Zero-Energy Building (nZEB) prototype equipped with a built-in thermal solar collector, where optical properties are analysed; a low enthalpy geothermal accumulation system, segmented in different temperature zones; and an envelope that includes a dynamic thermal barrier. An intelligent control of this dynamic thermal barrier is applied to reduce the thermal energy demand (heating and cooling) caused by daily and seasonal weather variations. Simulations and experimental results are presented to highlight the nZEB thermal energy reduction. PMID:26528978

  12. Personalized Clinical Decision Making in Gastrointestinal Malignancies

    DEFF Research Database (Denmark)

    Hess, Søren; Bjerring, Ole Steen; Pfeiffer, Per

    2016-01-01

    and initial stages. This article outlines the potential use of fluorodeoxyglucose-PET/CT in clinical decision making with special regard to preoperative evaluation and response assessment in gastric cancer (including the gastroesophageal junction), pancreatic cancer (excluding neuroendocrine tumors......Gastrointestinal malignancies comprise a heterogeneous group of diseases that include both common and rare diseases with very different presentations and prognoses. The mainstay of treatment is surgery in combination with preoperative and adjuvant chemotherapy depending on clinical presentation......), colorectal cancer, and gastrointestinal stromal tumors....

  13. Nurses' Clinical Decision Making on Adopting a Wound Clinical Decision Support System.

    Science.gov (United States)

    Khong, Peck Chui Betty; Hoi, Shu Yin; Holroyd, Eleanor; Wang, Wenru

    2015-07-01

    Healthcare information technology systems are considered the ideal tool to inculcate evidence-based nursing practices. The wound clinical decision support system was built locally to support nurses to manage pressure ulcer wounds in their daily practice. However, its adoption rate is not optimal. The study's objective was to discover the concepts that informed the RNs' decisions to adopt the wound clinical decision support system as an evidence-based technology in their nursing practice. This was an exploratory, descriptive, and qualitative design using face-to-face interviews, individual interviews, and active participatory observation. A purposive, theoretical sample of 14 RNs was recruited from one of the largest public tertiary hospitals in Singapore after obtaining ethics approval. After consenting, the nurses were interviewed and observed separately. Recruitment stopped when data saturation was reached. All transcribed interview data underwent a concurrent thematic analysis, whereas observational data were content analyzed independently and subsequently triangulated with the interview data. Eight emerging themes were identified, namely, use of the wound clinical decision support system, beliefs in the wound clinical decision support system, influences of the workplace culture, extent of the benefits, professional control over nursing practices, use of knowledge, gut feelings, and emotions (fear, doubt, and frustration). These themes represented the nurses' mental outlook as they made decisions on adopting the wound clinical decision support system in light of the complexities of their roles and workloads. This research has provided insight on the nurses' thoughts regarding their decision to interact with the computer environment in a Singapore context. It captured the nurses' complex thoughts when deciding whether to adopt or reject information technology as they practice in a clinical setting.

  14. A distributed clinical decision support system architecture

    Directory of Open Access Journals (Sweden)

    Shaker H. El-Sappagh

    2014-01-01

    Full Text Available This paper proposes an open and distributed clinical decision support system architecture. This technical architecture takes advantage of Electronic Health Record (EHR, data mining techniques, clinical databases, domain expert knowledge bases, available technologies and standards to provide decision-making support for healthcare professionals. The architecture will work extremely well in distributed EHR environments in which each hospital has its own local EHR, and it satisfies the compatibility, interoperability and scalability objectives of an EHR. The system will also have a set of distributed knowledge bases. Each knowledge base will be specialized in a specific domain (i.e., heart disease, and the model achieves cooperation, integration and interoperability between these knowledge bases. Moreover, the model ensures that all knowledge bases are up-to-date by connecting data mining engines to each local knowledge base. These data mining engines continuously mine EHR databases to extract the most recent knowledge, to standardize it and to add it to the knowledge bases. This framework is expected to improve the quality of healthcare, reducing medical errors and guaranteeing the safety of patients by helping clinicians to make correct, accurate, knowledgeable and timely decisions.

  15. Intervention strategies for energy efficient municipal buildings: Influencing energy decisions throughout buildings` lifetimes

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1993-12-31

    The current energy-related decisionmaking processes that take place during the lifetimes of municipal buildings in San Francisco do not reflect our ideal picture of energy efficiency as a part of staff awareness and standard practice. Two key problems that undermine the success of energy efficiency programs are lost opportunities and incomplete actions. These problems can be caused by technology-related issues, but often the causes are institutional barriers (organizational or procedural {open_quotes}people problems{close_quotes}). Energy efficient decisions are not being made because of a lack of awareness or policy mandate, or because financial resources are not available to decisionmakers. The Bureau of Energy Conservation (BEC) is working to solve such problems in the City & County of San Francisco through the Intervention Strategies project. In the first phase of the project, using the framework of the building lifetime, we learned how energy efficiency in San Francisco municipal buildings can be influenced through delivering services to support decisionmakers; at key points in the process of funding, designing, constructing and maintaining them. The second phase of the project involved choosing and implementing five pilot projects. Through staff interviews, we learned how decisions that impact energy use are made at various levels. We compiled information about city staff and their needs, and resources available to meet those needs. We then designed actions to deliver appropriate services to staff at these key access points. BEC implemented five pilot projects corresponding to various stages in the building`s lifetime. These were: Bond Guidelines, Energy Efficient Design Practices, Commissioning, Motor Efficiency, and Facilities Condition Monitoring Program.

  16. Building sustainable multi-functional prospective electronic clinical data systems.

    Science.gov (United States)

    Randhawa, Gurvaneet S; Slutsky, Jean R

    2012-07-01

    A better alignment in the goals of the biomedical research enterprise and the health care delivery system can help fill the large gaps in our knowledge of the impact of clinical interventions on patient outcomes in the real world. There are several initiatives underway to align the research priorities of patients, providers, researchers, and policy makers. These include Agency for Healthcare Research and Quality (AHRQ)-supported projects to build flexible prospective clinical electronic data infrastructure that meet the needs of these diverse users. AHRQ has previously supported the creation of 2 distributed research networks as a new approach to conduct comparative effectiveness research (CER) while protecting a patient's confidential information and the proprietary needs of a clinical organization. It has applied its experience in building these networks in directing the American Recovery and Reinvestment Act funds for CER to support new clinical electronic infrastructure projects that can be used for several purposes including CER, quality improvement, clinical decision support, and disease surveillance. In addition, AHRQ has funded a new Electronic Data Methods forum to advance the methods in clinical informatics, research analytics, and governance by actively engaging investigators from the American Recovery and Reinvestment Act-funded projects and external stakeholders.

  17. Best Practices in Clinical Decision Support

    Science.gov (United States)

    Wright, Adam; Phansalkar, Shobha; Bloomrosen, Meryl; Jenders, Robert A.; Bobb, Anne M.; Halamka, John D.; Kuperman, Gilad; Payne, Thomas H.; Teasdale, S.; Vaida, A. J.; Bates, D. W.

    2010-01-01

    Background Evidence demonstrates that clinical decision support (CDS) is a powerful tool for improving healthcare quality and ensuring patient safety. However, implementing and maintaining effective decision support interventions presents multiple technical and organizational challenges. Purpose To identify best practices for CDS, using the domain of preventive care reminders as an example. Methods We assembled a panel of experts in CDS and held a series of facilitated online and inperson discussions. We analyzed the results of these discussions using a grounded theory method to elicit themes and best practices. Results Eight best practice themes were identified as important: deliver CDS in the most appropriate ways, develop effective governance structures, consider use of incentives, be aware of workflow, keep content current, monitor and evaluate impact, maintain high quality data, and consider sharing content. Keys themes within each of these areas were also described. Conclusion Successful implementation of CDS requires consideration of both technical and socio-technical factors. The themes identified in this study provide guidance on crucial factors that need consideration when CDS is implemented across healthcare settings. These best practice themes may be useful for developers, implementers, and users of decision support. PMID:21991299

  18. Considerations for a successful clinical decision support system.

    Science.gov (United States)

    Castillo, Ranielle S; Kelemen, Arpad

    2013-07-01

    Clinical decision support systems have the potential to improve patient care in a multitude of ways. Clinical decision support systems can aid in the reduction of medical errors and reduction in adverse drug events, ensure comprehensive treatment of patient illnesses and conditions, encourage the adherence to guidelines, shorten patient length of stay, and decrease expenses over time. A clinical decision support system is one of the key components for reaching compliance for Meaningful Use. In this article, the advantages, potential drawbacks, and clinical decision support system adoption barriers are discussed, followed by an in-depth review of the characteristics that make a clinical decision support system successful. The legal and ethical issues that come with the implementation of a clinical decision support system within an organization and the future expectations of clinical decision support system are reviewed.

  19. Conceptualising a system for quality clinical decision-making in ...

    African Journals Online (AJOL)

    Quality clinical decision-making in nursing is the essence of quality nursing care delivery. The purpose of this article is to conceptualise a system for quality clinical decision-making in nursing. A system for quality clinical decisionmaking in nursing was conceptualised based on a review of the literature pertaining to clinical ...

  20. Decision making for cancer clinical trial participation: a systematic review.

    Science.gov (United States)

    Biedrzycki, Barbara A

    2010-11-01

    To describe what is known about the factors that influence cancer clinical trial decision making. PubMed database and reference lists of identified articles. Variations in research design and methods, including sample characteristics, instrumentation, time between decision made and measurement of decision making, and response rates, have effects on what is known about decision making for cancer clinical trial participation. Communication, whether in the form of education about a cancer clinical trial or as a personal invitation to join, is an important factor influencing decision making. Personal and system factors influence the outcomes of decision making for cancer clinical trials. The process of decision making for cancer clinical trials is understudied. Nevertheless, the currently available cancer clinical trial decision-making literature suggests a multitude of factors that influence the outcomes of the decision to accept or decline clinical trial participation, as well as the psychosocial consequences of decisional regret, pressures, and satisfaction. The decision-making process of cancer clinical trials is a fertile area for research and, subsequently, evidence-based interventions. Oncology nurses are in a position to facilitate the process and to relieve the pressures patients perceive regarding decision making for cancer clinical trials that will benefit individuals and, ultimately, society.

  1. Clinical Decision Support Tools: The Evolution of a Revolution

    NARCIS (Netherlands)

    Mould, D. R.; D'Haens, G.; Upton, R. N.

    2016-01-01

    Dashboard systems for clinical decision support integrate data from multiple sources. These systems, the newest in a long line of dose calculators and other decision support tools, utilize Bayesian approaches to fully individualize dosing using information gathered through therapeutic drug

  2. Evidence-Based Clinical Decision: Key to Improved Patients Care ...

    African Journals Online (AJOL)

    religious acts of the prehistoric era to empirical-rational decisions of the Egyptian civilization, to modern day evidence-based medicine. Evidence-based medicine requires that clinical decisions and health policies on the prevention, diagnosis and ...

  3. The prefabricated building risk decision research of DM technology on the basis of Rough Set

    Science.gov (United States)

    Guo, Z. L.; Zhang, W. B.; Ma, L. H.

    2017-08-01

    With the resources crises and more serious pollution, the green building has been strongly advocated by most countries and become a new building style in the construction field. Compared with traditional building, the prefabricated building has its own irreplaceable advantages but is influenced by many uncertainties. So far, a majority of scholars have been studying based on qualitative researches from all of the word. This paper profoundly expounds its significance about the prefabricated building. On the premise of the existing research methods, combined with rough set theory, this paper redefines the factors which affect the prefabricated building risk. Moreover, it quantifies risk factors and establish an expert knowledge base through assessing. And then reduced risk factors about the redundant attributes and attribute values, finally form the simplest decision rule. This simplest decision rule, which is based on the DM technology of rough set theory, provides prefabricated building with a controllable new decision-making method.

  4. How to make the best decision. Philosophical aspects of clinical decision theory.

    Science.gov (United States)

    Wulff, H R

    1981-01-01

    An attempt is made to discuss some of the philosophical implications of the use of decision-analytic techniques. The probabilities of a decision analysis are subjective measures of belief, and it is concluded that clinicians base their subjective beliefs on both recorded observations and theoretical knowledge. The clinical decision maker also evaluates the consequences of his actions, and therefore clinical decision theory transcends medical science. A number of different schools of normative ethics are mentioned to illustrate the complexity of everyday decision making. The philosophical terminology is useful for the analysis of clinical problems, and it is argued that clinical decision making has both a teleological and a deontological component. The results of decision-analytic studies depend on such factors as the wealth of the country, the organization of the health service, and cultural norms.

  5. An online infertility clinical decision support system

    Directory of Open Access Journals (Sweden)

    Fabio Diniz de Souza

    2017-09-01

    Full Text Available Objective: To explore some possibilities of computer applications in medicine, and to discuss an online infertility clinical decision support system. Methods: Retrospective data were obtained from 52 couples, and then entered into the online tool. Both its results and the initial diagnoses obtained by the treating physicians were compared with the final diagnoses established by laparoscopy and other diagnostic tests (semen analysis, hormone analysis, endometrial biopsy, ultrasound and hysteroscopy. The initial hypothesis of the research was that the online tool’s output was statistically associated with the final diagnoses. In order to verify that hypothesis, a chi-square (氈2 test with Yates’ correction for continuity (P<0.05 was performed to verify if the online tool’s and the doctor’s diagnoses were statistically associated with the final diagnoses. Results: Four etiological factors were present in more than 50% of the couples (ovarian, tubal-peritoneal, uterine, and endometriosis. The statistical results confirmed the research hypothesis for eight out of the nine etiological factors (ovarian, tubal-peritoneal, uterine, cervical, male, vaginal, psychosomatic, and endometriosis; P<0.05. Since there were no cases related to the immune factor in the sample, further clinical data are necessary in order to assess the online tool’s performance for that factor. Conclusions: The online tool tends to present more false-positives than false negatives, whereas the expert physician tends to present more false-negatives than false-positives. Therefore, the online tool and the doctor seem to complement each other. Finally, the obtained results suggest that the infertility online tool discussed herein might be a useful research and instructional tool.

  6. Early stage decision support for sustainable building renovation – A review

    DEFF Research Database (Denmark)

    Nielsen, Anne Nørkjær; Jensen, Rasmus Lund; Larsen, Tine Steen

    2016-01-01

    Decision support tools for building renovation are important as assistance to professional building owners when setting goals for sustainability, and for making sure that the objectives are met throughout the design process, both when renovating a single building or choosing renovation actions...... of the applicability of the tools in the corresponding areas of the renovation process. The study presents perspectives on the future development of decision support tools in renovation projects, including the aspect of renovating multiple buildings. Areas for future research are suggested, such as emphasizing...... within a building portfolio. Existing literature on decision support tools applicable in the pre-design and design phase of renovation projects have been reviewed, with the aim of providing a state-of-the-art overview. The paper categorizes the tools into six areas in which they can support the decision...

  7. Clinical decision-making and secondary findings in systems medicine.

    Science.gov (United States)

    Fischer, T; Brothers, K B; Erdmann, P; Langanke, M

    2016-05-21

    Systems medicine is the name for an assemblage of scientific strategies and practices that include bioinformatics approaches to human biology (especially systems biology); "big data" statistical analysis; and medical informatics tools. Whereas personalized and precision medicine involve similar analytical methods applied to genomic and medical record data, systems medicine draws on these as well as other sources of data. Given this distinction, the clinical translation of systems medicine poses a number of important ethical and epistemological challenges for researchers working to generate systems medicine knowledge and clinicians working to apply it. This article focuses on three key challenges: First, we will discuss the conflicts in decision-making that can arise when healthcare providers committed to principles of experimental medicine or evidence-based medicine encounter individualized recommendations derived from computer algorithms. We will explore in particular whether controlled experiments, such as comparative effectiveness trials, should mediate the translation of systems medicine, or if instead individualized findings generated through "big data" approaches can be applied directly in clinical decision-making. Second, we will examine the case of the Riyadh Intensive Care Program Mortality Prediction Algorithm, pejoratively referred to as the "death computer," to demonstrate the ethical challenges that can arise when big-data-driven scoring systems are applied in clinical contexts. We argue that the uncritical use of predictive clinical algorithms, including those envisioned for systems medicine, challenge basic understandings of the doctor-patient relationship. Third, we will build on the recent discourse on secondary findings in genomics and imaging to draw attention to the important implications of secondary findings derived from the joint analysis of data from diverse sources, including data recorded by patients in an attempt to realize their

  8. Building simulations supporting decision making in early design – A review

    DEFF Research Database (Denmark)

    Østergård, Torben; Jensen, Rasmus Lund; Maagaard, Steffen

    2016-01-01

    The building design community is challenged by continuously increasing energy demands, which are often combined with ambitious goals for indoor environment, for environmental impact, and for building costs. To aid decision-making, building simulation is widely used in the late design stages......, but its application is still limited in the early stages in which design decisions have a major impact on final building performance and costs. The early integration of simulation software faces several challenges, which include time-consuming modeling, rapid change of the design, conflicting requirements......, input uncertainties, and large design variability. In addition, building design is a multi-collaborator discipline, where design decisions are influenced by architects, engineers, contractors, and building owners. This review covers developments in both academia and in commercial software industry...

  9. Decision analysis in the clinical neurosciences

    NARCIS (Netherlands)

    D.W.J. Dippel (Diederik)

    1994-01-01

    textabstractDiagnostic and therapeutic choice in neurology can fortunately be made without formal decision support in the majority of cases. in many patients a diagnosis and treatment choice are relatively easy to establish. This study however, concerns the application of a decision support

  10. Clinical models of decision making in addiction.

    Science.gov (United States)

    Koffarnus, Mikhail N; Kaplan, Brent A

    2018-01-01

    As research on decision making in addiction accumulates, it is increasingly clear that decision-making processes are dysfunctional in addiction and that this dysfunction may be fundamental to the initiation and maintenance of addictive behavior. How drug-dependent individuals value and choose among drug and nondrug rewards is consistently different from non-dependent individuals. The present review focuses on the assessment of decision-making in addiction. We cover the common behavioral tasks that have shown to be fruitful in decision-making research and highlight analytical and graphical considerations, when available, to facilitate comparisons within and among studies. Delay discounting tasks, drug demand tasks, drug choice tasks, the Iowa Gambling Task, and the Balloon Analogue Risk Task are included. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Patient decision-making for clinical genetics.

    Science.gov (United States)

    Anderson, Gwen

    2007-03-01

    Medicine is incorporating genetic services into all avenues of health-care, ranging from the rarest to the most common diseases. Cognitive theories of decision-making still dominate professionals' understanding of patient decision-making about how to use genetic information and whether to have testing. I discovered a conceptual model of decision-making while carrying out a phenomenological-hermeneutic descriptive study of a convenience sample of 12 couples who were interviewed while deciding whether to undergo prenatal genetic testing. Thirty-two interviews were conducted with 12 men and 12 women separately. Interviews were transcribed verbatim and all data were analyzed using three levels of coding that were sorted into 30 categories and then abstracted into three emergent meta-themes that described men's and women's attempts to make sense and find meaning in how to best use prenatal genetic technology. Their descriptions of how they thought about, communicated, and coped with their decision were so detailed it was possible to discern nine different types of thinking they engaged in while deciding to accept or decline testing. They believed that decision-making is a process of working through your own personal style of thinking. This might include only one or any combination of the following types of thinking: analytical, ethical, moral, reflective, practical, hypothetical, judgmental, scary, and second sight, as described in detail by these 12 couples.

  12. Clinical decision support alert malfunctions: analysis and empirically derived taxonomy.

    Science.gov (United States)

    Wright, Adam; Ai, Angela; Ash, Joan; Wiesen, Jane F; Hickman, Thu-Trang T; Aaron, Skye; McEvoy, Dustin; Borkowsky, Shane; Dissanayake, Pavithra I; Embi, Peter; Galanter, William; Harper, Jeremy; Kassakian, Steve Z; Ramoni, Rachel; Schreiber, Richard; Sirajuddin, Anwar; Bates, David W; Sittig, Dean F

    2017-10-16

    To develop an empirically derived taxonomy of clinical decision support (CDS) alert malfunctions. We identified CDS alert malfunctions using a mix of qualitative and quantitative methods: (1) site visits with interviews of chief medical informatics officers, CDS developers, clinical leaders, and CDS end users; (2) surveys of chief medical informatics officers; (3) analysis of CDS firing rates; and (4) analysis of CDS overrides. We used a multi-round, manual, iterative card sort to develop a multi-axial, empirically derived taxonomy of CDS malfunctions. We analyzed 68 CDS alert malfunction cases from 14 sites across the United States with diverse electronic health record systems. Four primary axes emerged: the cause of the malfunction, its mode of discovery, when it began, and how it affected rule firing. Build errors, conceptualization errors, and the introduction of new concepts or terms were the most frequent causes. User reports were the predominant mode of discovery. Many malfunctions within our database caused rules to fire for patients for whom they should not have (false positives), but the reverse (false negatives) was also common. Across organizations and electronic health record systems, similar malfunction patterns recurred. Challenges included updates to code sets and values, software issues at the time of system upgrades, difficulties with migration of CDS content between computing environments, and the challenge of correctly conceptualizing and building CDS. CDS alert malfunctions are frequent. The empirically derived taxonomy formalizes the common recurring issues that cause these malfunctions, helping CDS developers anticipate and prevent CDS malfunctions before they occur or detect and resolve them expediently.

  13. Energy Signal Tool for Decision Support in Building Energy Systems

    Energy Technology Data Exchange (ETDEWEB)

    Henze, G. P.; Pavlak, G. S.; Florita, A. R.; Dodier, R. H.; Hirsch, A. I.

    2014-12-01

    A prototype energy signal tool is demonstrated for operational whole-building and system-level energy use evaluation. The purpose of the tool is to give a summary of building energy use which allows a building operator to quickly distinguish normal and abnormal energy use. Toward that end, energy use status is displayed as a traffic light, which is a visual metaphor for energy use that is either substantially different from expected (red and yellow lights) or approximately the same as expected (green light). Which light to display for a given energy end use is determined by comparing expected to actual energy use. As expected, energy use is necessarily uncertain; we cannot choose the appropriate light with certainty. Instead, the energy signal tool chooses the light by minimizing the expected cost of displaying the wrong light. The expected energy use is represented by a probability distribution. Energy use is modeled by a low-order lumped parameter model. Uncertainty in energy use is quantified by a Monte Carlo exploration of the influence of model parameters on energy use. Distributions over model parameters are updated over time via Bayes' theorem. The simulation study was devised to assess whole-building energy signal accuracy in the presence of uncertainty and faults at the submetered level, which may lead to tradeoffs at the whole-building level that are not detectable without submetering.

  14. African Researchers and Decision-Makers: Building Synergy for ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    2009-01-01

    Jan 1, 2009 ... This short and accessible book is essential reading for anyone interested in … the importance of synergy between researchers and decision-makers in Africa and how this can contribute to development. It highlights the key constraints why research is not used in policy development but also presents ...

  15. Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems.

    Science.gov (United States)

    DesAutels, Spencer J; Fox, Zachary E; Giuse, Dario A; Williams, Annette M; Kou, Qing-Hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

    2016-01-01

    Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.

  16. Clinical decision-making: physicians' preferences and experiences

    Directory of Open Access Journals (Sweden)

    White Martha

    2007-03-01

    Full Text Available Abstract Background Shared decision-making has been advocated; however there are relatively few studies on physician preferences for, and experiences of, different styles of clinical decision-making as most research has focused on patient preferences and experiences. The objectives of this study were to determine 1 physician preferences for different styles of clinical decision-making; 2 styles of clinical decision-making physicians perceive themselves as practicing; and 3 the congruence between preferred and perceived style. In addition we sought to determine physician perceptions of the availability of time in visits, and their role in encouraging patients to look for health information. Methods Cross-sectional survey of a nationally representative sample of U.S. physicians. Results 1,050 (53% response rate physicians responded to the survey. Of these, 780 (75% preferred to share decision-making with their patients, 142 (14% preferred paternalism, and 118 (11% preferred consumerism. 87% of physicians perceived themselves as practicing their preferred style. Physicians who preferred their patients to play an active role in decision-making were more likely to report encouraging patients to look for information, and to report having enough time in visits. Conclusion Physicians tend to perceive themselves as practicing their preferred role in clinical decision-making. The direction of the association cannot be inferred from these data; however, we suggest that interventions aimed at promoting shared decision-making need to target physicians as well as patients.

  17. Building a Decision Support Tool for Adaptation to Extreme Heat

    Science.gov (United States)

    Steinberg, N.

    2016-12-01

    Human vulnerability to extreme heat can be a difficult measure to assess and effectively "operationalize" for key decision-makers. Existing heat alerts are sensitive to scale and context, often leaving public officials with insufficient forecast data, lack of coherent guidance, and an absence of tools that can accurately represent local heat-health risks. While local forecast data and extreme weather outlooks continue to improve, stakeholders are asking for decision support about interoperability and appropriate interventions to reduce heat-health risks for vulnerable populations. This presentation will discuss the information needs determined by public health officials in California with funding from California's Fourth Climate Change Assessment. Findings from a user needs assessment will be followed by a discussion of methods for communicating heat vulnerability and developing user-centric tools that can help public health professionals and planners prepare their communities for extreme heat.

  18. The reliability of an epilepsy treatment clinical decision support system.

    Science.gov (United States)

    Standridge, Shannon; Faist, Robert; Pestian, John; Glauser, Tracy; Ittenbach, Richard

    2014-10-01

    We developed a content validated computerized epilepsy treatment clinical decision support system to assist clinicians with selecting the best antiepilepsy treatments. Before disseminating our computerized epilepsy treatment clinical decision support system, further rigorous validation testing was necessary. As reliability is a precondition of validity, we verified proof of reliability first. We evaluated the consistency of the epilepsy treatment clinical decision support system in three areas including the preferred antiepilepsy drug choice, the top three recommended choices, and the rank order of the three choices. We demonstrated 100% reliability on 15,000 executions involving a three-step process on five different common pediatric epilepsy syndromes. Evidence for the reliability of the epilepsy treatment clinical decision support system was essential for the long-term viability of the system, and served as a crucial component for the next phase of system validation.

  19. The impact of simulation sequencing on perceived clinical decision making.

    Science.gov (United States)

    Woda, Aimee; Hansen, Jamie; Paquette, Mary; Topp, Robert

    2017-09-01

    An emerging nursing education trend is to utilize simulated learning experiences as a means to optimize competency and decision making skills. The purpose of this study was to examine differences in students' perception of clinical decision making and clinical decision making-related self-confidence and anxiety based on the sequence (order) in which they participated in a block of simulated versus hospital-based learning experiences. A quasi-experimental crossover design was used. Between and within group differences were found relative to self-confidence with the decision making process. When comparing groups, at baseline the simulation followed by hospital group had significantly higher self-confidence scores, however, at 14-weeks both groups were not significantly different. Significant within group differences were found in the simulation followed by hospital group only, demonstrating a significant decrease in clinical decision making related anxiety across the semester. Finally, there were no significant difference in; perceived clinical decision making within or between the groups at the two measurement points. Preliminary findings suggest that simulated learning experiences can be offered with alternating sequences without impacting the process, anxiety or confidence with clinical decision making. This study provides beginning evidence to guide curriculum development and allow flexibility based on student needs and available resources. Copyright © 2017. Published by Elsevier Ltd.

  20. Decision-making for UBC High Performance Buildings: Multi-criteria Analysis for Integrated Life Cycle Models

    OpenAIRE

    Storey, S.

    2010-01-01

    The current paradigm of building design is evolving rapidly and building developers are beginning to dopt sustainable building practices across Canada. Attaining a sustainable built environment is challenged by the complexity of decision-making and stakeholders need to examine a large number of sustainability metrics to support a 'good decision'. Each sustainable building development has a design path unique to the values of the building stakeholders.This project outlines a framework that as...

  1. An introduction to clinical decision analysis in ophthalmology

    Directory of Open Access Journals (Sweden)

    Korah Sanita

    1999-01-01

    Full Text Available Ophthalmologists are often confronted with difficult clinical management problems. In such cases, even published experience may be limited; consequently multiple, generally unproven management options are usually available. When placed in such situations, most of us decide on the most appropriate course of action based on intuition or (limited previous experience. In this article, we use examples to introduce the concept of decision analysis, a method of generating objective decisions for complex clinical problems.

  2. Clinical decision-making support systema in renal failure

    OpenAIRE

    E. Martínez Bernabé; G. Paluzie-Ávila; S. Terre Ohme; D. Ruiz Poza; M. A. Parada Aradilla; J. González Martínez; R. Albertí Valmaña; M. Castellvi Gordo

    2014-01-01

    Introduction: Support systems in clinical decision-making use individual characteristicsof the patient to generate recommendations to the clinician. Objective: To assess the impact of a tool for adjusting drug dosing in renal failure asa support system in clinical decision-making regarding the level of acceptance of theinterventions as well as the time invested by the pharmacist. Method: Non-randomized, prospective and hospital interventional study comparingpre- and post-implementation ...

  3. The energy investment decision in the nonresidential building sector: Research into the areas of influence

    Energy Technology Data Exchange (ETDEWEB)

    Harkreader, S.A.; Ivey, D.L.

    1987-04-01

    The purpose of this report is to describe and to characterize the decision process in the nonresidential building sector as well as the variables influencing energy investment decisions, both of which impact the development of R and D agendas for the Office of Building and Community Systems (BCS). The report reviews the available information on the factors that influence energy investment decisions and identifies information gaps where additional research is needed. This report focuses on variables and combinations of these variables (descriptive states) that influence the non residential energy investment decision maker. Economic and demographic descriptors, energy investment decision maker characteristics, and variables affecting energy investments are identified. This response examines the physical characteristics of buildings, characteristics of the legal environment surrounding buildings, demographic factors, economic factors, and decision processes, all of which impact the nonresidential energy investment market. The emphasis of the report is on providing possible methodologies for projecting the future of the nonresidential energy investment market, as well as, collecting the data necessary for such projections. The use of alternate scenarios is suggested as a projection tool and suggestions for collecting the appropriate data are made in the recommendations.

  4. Commercial building to low energy standards. Crucial decisions at building shell; Geschaeftsbau nach Passivhaus-Standard. Entscheidende Weichenstellungen beim Rohbau

    Energy Technology Data Exchange (ETDEWEB)

    Brenckle, R.

    2007-07-01

    This article describes the Customer Care Centre of the IWB utility in Basel, Switzerland, which was built to the Minergie-P extremely low energy consumption standard. In particular, the importance of crucial decisions made before the start of the construction of the building's shell is stressed. The optimal co-ordination of statics, insulation and permeability is discussed, as are aspects concerning the positioning of windows, waste-heat recovery and air-conditioning. The project and its background are discussed. The heating and ventilation concept, heat gains and losses and the associated ideas used in the building are looked at in detail.

  5. Cognitive Elements in Clinical Decision-Making

    Science.gov (United States)

    Dunphy, Bruce C.; Cantwell, Robert; Bourke, Sid; Fleming, Mark; Smith, Bruce; Joseph, K. S.; Dunphy, Stacey L

    2010-01-01

    Physician cognition, metacognition and affect may have an impact upon the quality of clinical reasoning. The purpose of this study was to examine the relationship between measures of physician metacognition and affect and patient outcomes in obstetric practice. Reflective coping (RC), proactive coping, need for cognition (NFC), tolerance for…

  6. The Feasibility of Sophisticated Multicriteria Support for Clinical Decisions.

    Science.gov (United States)

    Dolan, James G; Veazie, Peter J

    2017-10-01

    Multicriteria decision-making (MCDM) methods are well-suited to serve as the foundation for clinical decision support systems. To do so, however, they need to be appropriate for use in busy clinical settings. We compared decision-making processes and outcomes of patient-level analyses done with a range of multicriteria methods that vary in ease of use and intensity of decision support, 2 factors that could affect their ease of implementation into practice. We conducted a series of Internet surveys to compare the effects of 5 multicriteria methods that differ in user interface and required user input format on decisions regarding selection of a preferred method for lowering the risk of cardiovascular disease. The study sample consisted of members of an online Internet panel maintained by Fluidsurveys, an Internet survey company. Study outcomes were changes in preferred option, decision confidence, preparation for decision making, the Values Clarification and Decisional Uncertainty subscales of the Decisional Conflict Scale, and method ease of use. The frequency of changes in the preferred option ranged from 9% to 38%, P MCDM method increased. The proportion of respondents who rated the method as easy ranged from 57% to 79% and differed significantly among MCDM methods, P = 0.003, but was not consistently related to intensity of decision support or ease of use. Decision support based on MCDM methods is not necessarily limited by decreases in ease of use. This result suggests that it is possible to develop decision support tools using sophisticated multicriteria techniques suitable for use in routine clinical care settings.

  7. Building an engaged workforce at Cleveland Clinic

    Directory of Open Access Journals (Sweden)

    Patrnchak JM

    2013-05-01

    Full Text Available Joseph M PatrnchakCleveland Clinic, Cleveland, OH, USAAbstract: Employee engagement is widely recognized as a critical factor in organizational performance. This article examines an ongoing cultural development initiative at Cleveland Clinic designed to significantly increase employee engagement. Key components of this initiative include the introduction of serving leadership, new caregiver wellness and recognition programs, “Cleveland Clinic Experience” training focused on the institution’s core mission, and changes in the institutional vocabulary. Since 2008, the results include a dramatic improvement in engagement, as measured by the Gallup Q12 survey, with parallel improvements in patient satisfaction, as measured by the clinic's scores on the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS survey. In addition to a discussion of the key components of the clinic’s engagement initiative, the article provides a partial review of the literature focused on employee engagement as well as a summary of “lessons learned” that may serve as a guide for others facing the challenge of increasing employee engagement in large, mature health care institutions.Keywords: health care, employee engagement, culture change, hospital performance, patient satisfaction

  8. Sustainable Decision-Making in Civil Engineering, Construction and Building Technology

    OpenAIRE

    Edmundas Kazimieras Zavadskas; Jurgita Antucheviciene; Tatjana Vilutiene; Hojjat Adeli

    2017-01-01

    Sustainable decision-making in civil engineering, construction and building technology can be supported by fundamental scientific achievements and multiple-criteria decision-making (MCDM) theories. The current paper aims at overviewing the state of the art in terms of published papers related to theoretical methods that are applied to support sustainable evaluation and selection processes in civil engineering. The review is limited solely to papers referred to in the Clarivate Analytic Web of...

  9. Decision process for the retrofit of municipal buildings with solar energy systems: a technical guide

    Energy Technology Data Exchange (ETDEWEB)

    Licciardello, Michael R.; Wood, Brian; Dozier, Warner; Braly, Mark; Yates, Alan

    1980-11-01

    As a background for solar applications, the following topics are covered: solar systems and components for retrofit installations; cost, performance, and quality considerations; and financing alternatives for local government. The retrofit decision process is discussed as follows: pre-screening of buildings, building data requirements, the energy conservation audit, solar system sizing and economics, comparison of alternatives, and implementation. Sample studies are presented for the West Valley Animal Shelter and the Hollywood Police Station. (MHR)

  10. Implementing an integrative multi-agent clinical decision support system with open source software.

    Science.gov (United States)

    Sayyad Shirabad, Jelber; Wilk, Szymon; Michalowski, Wojtek; Farion, Ken

    2012-02-01

    Clinical decision making is a complex multi-stage process. Decision support can play an important role at each stage of this process. At present, the majority of clinical decision support systems have been focused on supporting only certain stages. In this paper we present the design and implementation of MET3-a prototype multi-agent system providing an integrative decision support that spans over the entire decision making process. The system helps physicians with data collection, diagnosis formulation, treatment planning and finding supporting evidence. MET3 integrates with external hospital information systems via HL7 messages and runs on various computing platforms available at the point of care (e.g., tablet computers, mobile phones). Building MET3 required sophisticated and reliable software technologies. In the past decade the open source software movement has produced mature, stable, industrial strength software systems with a large user base. Therefore, one of the decisions that should be considered before developing or acquiring a decision support system is whether or not one could use open source technologies instead of proprietary ones. We believe MET3 shows that the answer to this question is positive.

  11. Decision Making Process for Constructing Low-Energy Buildings in the Public Housing Sector in Sweden

    Directory of Open Access Journals (Sweden)

    Åsa Wahlström

    2016-10-01

    Full Text Available The built environment accounts for a significant share of energy consumption and energy efficiency in this sector is important for the Swedish environmental objectives. Only a limited share of the total new construction of multifamily houses are constructed as low-energy buildings. Current building regulations lay down requirements for energy efficiency for new construction, and these will be tightened further in the future. Public housing companies often aim to be at the forefront, and the public housing sector has now built half of Sweden’s low-energy blocks of flats. Many public housing companies have tried, but it is uncertain if they will, or have, the possibilities to construct low-energy buildings on a large scale. Twenty public housing companies around Sweden have been interviewed with the aim of identifying obstacles and possibilities to be forerunners and build better than required by the building regulations. The study shows that the public housing companies build better than the law demands and intend to continue doing so. Low-energy buildings are particularly suitable in central locations where land is attractive and the required returns lower. The driving motivation is to be at the forefront and to build green. The new pressure to increase house building can lead to a risk of energy and quality issues being passed over. For the increase in the construction of low-energy buildings to continue, extended, shared and comparable decision making support for the public housing companies is needed.

  12. Decision Aids Can Support Cancer Clinical Trials Decisions: Results of a Randomized Trial.

    Science.gov (United States)

    Politi, Mary C; Kuzemchak, Marie D; Kaphingst, Kimberly A; Perkins, Hannah; Liu, Jingxia; Byrne, Margaret M

    2016-12-01

    Cancer patients often do not make informed decisions regarding clinical trial participation. This study evaluated whether a web-based decision aid (DA) could support trial decisions compared with our cancer center's website. Adults diagnosed with cancer in the past 6 months who had not previously participated in a cancer clinical trial were eligible. Participants were randomized to view the DA or our cancer center's website (enhanced usual care [UC]). Controlling for whether participants had heard of cancer clinical trials and educational attainment, multivariable linear regression examined group on knowledge, self-efficacy for finding trial information, decisional conflict (values clarity and uncertainty), intent to participate, decision readiness, and trial perceptions. Two hundred patients (86%) consented between May 2014 and April 2015. One hundred were randomized to each group. Surveys were completed by 87 in the DA group and 90 in the UC group. DA group participants reported clearer values regarding trial participation than UC group participants reported (least squares [LS] mean = 15.8 vs. 32, p trial participation among cancer patients facing this preference-sensitive choice. Although better informing patients before trial participation could improve retention, more work is needed to examine DA impact on enrollment and retention. This paper describes evidence regarding a decision tool to support patients' decisions about trial participation. By improving knowledge, helping patients clarify preferences for participation, and facilitating conversations about trials, decision aids could lead to decisions about participation that better match patients' preferences, promoting patient-centered care and the ethical conduct of clinical research. ©AlphaMed Press.

  13. Development of Decision Support Process for Building Energy Conservation Measures and Economic Analysis

    Directory of Open Access Journals (Sweden)

    Bo-Eun Choi

    2017-03-01

    Full Text Available As policies for energy efficiency of buildings are being actively implemented, building energy performance improvement is urgently required. However, in Korea, information on measures and technologies for building energy efficiency is dispersed and concrete methods are not established, making it difficult to apply effective measures. Therefore, it is required to apply and evaluate energy efficiency measures through database construction integrating diverse information. In this study, the energy efficiency measures in the architectural sector that satisfy domestic legal standards are built. Because of the economic evaluation is necessary for the constructed alternatives, an economic efficiency database was established. The target building was set up, and energy efficiency measures were derived. In addition, a methodology that can induce energy efficient decision making of buildings was proposed, and the energy use evaluation and the economic analysis for each of the alternatives derived from applying the methodology to the target building were carried out. Furthermore, the optimal energy efficiency measures for the target building were suggested through the application of the decision-making process.

  14. Supporting Decision-Making in the Building Life-Cycle Using Linked Building Data

    Directory of Open Access Journals (Sweden)

    Pieter Pauwels

    2014-09-01

    Full Text Available The interoperability challenge is a long-standing challenge in the domain of architecture, engineering and construction (AEC. Diverse approaches have already been presented for addressing this challenge. This article will look into the possibility of addressing the interoperability challenge in the building life-cycle with a linked data approach. An outline is given of how linked data technologies tend to be deployed, thereby working towards a “more holistic” perspective on the building, or towards a large-scale web of “linked building data”. From this overview, and the associated use case scenarios, we conclude that the interoperability challenge cannot be “solved” using linked data technologies, but that it can be addressed. In other words, information exchange and management can be improved, but a pragmatic usage of technologies is still required in practice. Finally, we give an initial outline of some anticipated use cases in the building life-cycle in which the usage of linked data technologies may generate advantages over existing technologies and methods.

  15. Supporting Building Portfolio Investment and Policy Decision Making through an Integrated Building Utility Data Platform

    Energy Technology Data Exchange (ETDEWEB)

    Aziz, Azizan [Carnegie Mellon Univ., Pittsburgh, PA (United States); Lasternas, Bertrand [Carnegie Mellon Univ., Pittsburgh, PA (United States); Alschuler, Elena [US DOE; View Inc; Loftness, Vivian [Carnegie Mellon Univ., Pittsburgh, PA (United States); Wang, Haopeng [Carnegie Mellon Univ., Pittsburgh, PA (United States); Mo, Yunjeong [Carnegie Mellon Univ., Pittsburgh, PA (United States); Wang, Ting [Carnegie Mellon Univ., Pittsburgh, PA (United States); Zhang, Chenlu [Carnegie Mellon Univ., Pittsburgh, PA (United States); Sharma, Shilpi [Carnegie Mellon; Stevens, Ivana [Carnegie Mellon Univ., Pittsburgh, PA (United States)

    2016-03-18

    The American Recovery and Reinvestment Act stimulus funding of 2009 for smart grid projects resulted in the tripling of smart meters deployment. In 2012, the Green Button initiative provided utility customers with access to their real-time1 energy usage. The availability of finely granular data provides an enormous potential for energy data analytics and energy benchmarking. The sheer volume of time-series utility data from a large number of buildings also poses challenges in data collection, quality control, and database management for rigorous and meaningful analyses. In this paper, we will describe a building portfolio-level data analytics tool for operational optimization, business investment and policy assessment using 15-minute to monthly intervals utility data. The analytics tool is developed on top of the U.S. Department of Energy’s Standard Energy Efficiency Data (SEED) platform, an open source software application that manages energy performance data of large groups of buildings. To support the significantly large volume of granular interval data, we integrated a parallel time-series database to the existing relational database. The time-series database improves on the current utility data input, focusing on real-time data collection, storage, analytics and data quality control. The fully integrated data platform supports APIs for utility apps development by third party software developers. These apps will provide actionable intelligence for building owners and facilities managers. Unlike a commercial system, this platform is an open source platform funded by the U.S. Government, accessible to the public, researchers and other developers, to support initiatives in reducing building energy consumption.

  16. Consumer decision and behavior research agenda for the Office of Building and Community Systems

    Energy Technology Data Exchange (ETDEWEB)

    Mohler, B.L.; Scheer, R.M.; Barnes, V.

    1985-12-01

    This report presents a research agenda of Consumer Decision and Behavior Projects related to improving, facilitating and planning Building and Community Systems, (BCS) research and development activities. Information for developing this agenda was gathered through focus group and depth interviews with BCS staff, directors and program managers.

  17. Build, Buy, Open Source, or Web 2.0?: Making an Informed Decision for Your Library

    Science.gov (United States)

    Fagan, Jody Condit; Keach, Jennifer A.

    2010-01-01

    When improving a web presence, today's libraries have a choice: using a free Web 2.0 application, opting for open source, buying a product, or building a web application. This article discusses how to make an informed decision for one's library. The authors stress that deciding whether to use a free Web 2.0 application, to choose open source, to…

  18. Gamification as a Means to User Involvement in Decision-making Processes for Sustainable Buildings

    DEFF Research Database (Denmark)

    Hansen, Hanne Tine Ring; Knudstrup, Mary-Ann; Skøtt, Stine

    2017-01-01

    was developed by a multidisciplinary group of stakeholders and actors from the Danish building and housing industry. The paper presents how gamification can be used to make complex and academic issues of sustainability available to decision-makers in housing organisations who are typically people from all walks...

  19. Sustainable Decision-Making in Civil Engineering, Construction and Building Technology

    Directory of Open Access Journals (Sweden)

    Edmundas Kazimieras Zavadskas

    2017-12-01

    Full Text Available Sustainable decision-making in civil engineering, construction and building technology can be supported by fundamental scientific achievements and multiple-criteria decision-making (MCDM theories. The current paper aims at overviewing the state of the art in terms of published papers related to theoretical methods that are applied to support sustainable evaluation and selection processes in civil engineering. The review is limited solely to papers referred to in the Clarivate Analytic Web of Science core collection database. As the focus is on multiple-criteria decision-making, it aims at reviewing how the papers on MCDM developments and applications have been distributed by period of publishing, by author countries and institutions, and by journals. Detailed analysis of 2015–2017 journal articles from two Web of Science categories (engineering civil and construction building technology is presented. The articles are grouped by research domains, problems analyzed and the decision-making approaches used. The findings of the current review paper show that MCDM applications have been constantly growing and particularly increased in the last three years, confirming the great potential and prospects of applying MCDM methods for sustainable decision-making in civil engineering, construction and building technology.

  20. Value based building renovation - A tool for decision-making and evaluation

    DEFF Research Database (Denmark)

    Jensen, Per Anker; Maslesa, Esmir

    2015-01-01

    Research on the barriers for building renovation in Denmark has revealed that an important obstacle is a lack of simple and holistic tools that can assist stakeholders in prioritisation and decision-making during the early stages of building renovation projects. The purpose of this article...... is to present a tool - RENO-EVALUE, which can be used as decision support for sustainable renovation projects, and for evaluation, during and after building renovations. The tool is a result from the European Eracobuild project ACES - "A concept for promotion of sustainable retrofitting and renovation in early...... stages". This article presents the main result of a work package concerning benefits of renovation. RENO-EVALUE has been developed from four case studies on renovation projects in Denmark, tested and validated on the cases and in a Delphi study. The tool is value based by focusing on the different...

  1. Sustainability-Related Decision Making in Industrial Buildings: An AHP Analysis

    Directory of Open Access Journals (Sweden)

    Jesús Cuadrado

    2015-01-01

    Full Text Available Few other sectors have such a great impact on sustainability as the construction industry, in which concerns over the environmental dimension have been growing for some time. The sustainability assessment methodology presented in this paper is an AHP (Analytic Hierarchy Process based on Multicriteria Decision Making (MCDM and includes the main sustainability factors for consideration in the construction of an industrial building (environmental, economic, and social, as well as other factors that greatly influence the conceptual design of the building (employee safety, corporate image. Its simplicity is well adapted to its main objective, to serve as a sustainability-related decision making tool in industrial building projects, during the design stage. Accompanied by an economic valuation of the actions to be undertaken, this tool means that the most cost-effective solution may be selected from among the various options.

  2. Building clinical trial priorities at the University of Rwanda.

    Science.gov (United States)

    Condo, Jeanine; Kateera, Brenda; Mutimura, Eugene; Birungi, Francine; Ndagijimana, Albert; Jansen, Stefan; Kamwesiga, Julius; Forrest, Jamie I; Mills, Edward J; Binagwaho, Agnes

    2014-11-27

    After the genocide in Rwanda, the country's healthcare system collapsed. Remarkable gains have since been made by the state to provide greater clinical service capacity and expand health policies that are grounded on locally relevant evidence. This commentary explores the challenges faced by Rwanda in building an infrastructure for clinical trials. Through local examples, we discuss how a clinical trial infrastructure can be constructed by (1) building educational capacity; (2) encouraging the testing of relevant interventions using appropriate and cost-effective designs; and, (3) promoting ethical and regulatory standards. The future is bright for clinical research in Rwanda and with a renewed appetite for locally generated evidence it is necessary that we discuss the challenges and opportunities in drawing up a clinical trials agenda.

  3. Unsatisfactory colposcopy: clinical decision-making in conditions of uncertainty.

    Science.gov (United States)

    Manley, Kristyn M; Simms, Rebecca A; Platt, Sarah; Patel, Amit; Bahl, Rachna

    2017-08-22

    Unsatisfactory colposcopy, where the cells of interest are not visible in women with a positive cervical screening test, is a common area of clinical uncertainty due to the lack of clear evidence and guidance. Colposcopists' opinions and experiences are likely to have a significant influence on service provision and the development of national policy. The aim of this study was to analyse decision-making when applied to women with unsatisfactory colposcopy. A multi-centre qualitative study utilizing a series of focus groups in an English healthcare region. Sampling aimed to ensure heterogeneity of experience and healthcare provider demographics. A topic guide covered a range of clinical and cytological variables and was compiled by the researchers and three expert Colposcopists. Using an iterative approach, thematic analysis was selected as the most appropriate method to identify factors affecting decision-making. Twenty-three Colposcopists from four units participated. The decision to treat was easier in women with high-grade cytology and high risk women with low-grade cytology such as heavy smokers, poor attenders, older women, those who had completed their families and women opting for treatment. Where decision-making was more complex, intuition and a multi-disciplinary approach were used to guide management. Areas of dissonance, which are affected by paucity of evidence and emotive factors, included cytological collection device, clinical setting and length of conservative follow-up and depth of excision in women at high risk of treatment-related morbidity. Anxiety of missing a cancer deters long-term cytological follow-up, resulting in heterogeneity of care and higher than anticipated excisional treatments in women with low-grade screening and unsatisfactory colposcopy. In areas of clinical uncertainty when decisions are dominated by affect, clinical guidance can reduce the difficulty and anxiety of decision-making.

  4. The role of emotions in clinical reasoning and decision making.

    Science.gov (United States)

    Marcum, James A

    2013-10-01

    What role, if any, should emotions play in clinical reasoning and decision making? Traditionally, emotions have been excluded from clinical reasoning and decision making, but with recent advances in cognitive neuropsychology they are now considered an important component of them. Today, cognition is thought to be a set of complex processes relying on multiple types of intelligences. The role of mathematical logic (hypothetico-deductive thinking) or verbal linguistic intelligence in cognition, for example, is well documented and accepted; however, the role of emotional intelligence has received less attention-especially because its nature and function are not well understood. In this paper, I argue for the inclusion of emotions in clinical reasoning and decision making. To that end, developments in contemporary cognitive neuropsychology are initially examined and analyzed, followed by a review of the medical literature discussing the role of emotions in clinical practice. Next, a published clinical case is reconstructed and used to illustrate the recognition and regulation of emotions played during a series of clinical consultations, which resulted in a positive medical outcome. The paper's main thesis is that emotions, particularly in terms of emotional intelligence as a practical form of intelligence, afford clinical practitioners a robust cognitive resource for providing quality medical care.

  5. Risk perception and clinical decision making in primary care

    DEFF Research Database (Denmark)

    Barfoed, Benedicte Marie Lind

    2015-01-01

    Objectives We aim to present new knowledge about different perspectives of health care professionals’ risk perceptions and clinical decision making. Furthermore, we intend to discuss differences between professional and personal risk perceptions and the impact on decisions in terms of both short...... and long-term outcomes. Background Insight into healthcare professionals’ perception of risk is a cornerstone for understanding their strategies for practising preventive care. The way people perceive risk can be seen as part of a general personality trait influenced by a mixture of individual...... considerations and the specific context. Most research has been focused on understanding of the concepts of risk. However healthcare professionals’ risk perception and personal attitudes also affect their clinical decision-making and risk communication. The differences between health care professionals’ personal...

  6. Implications of caries diagnostic strategies for clinical management decisions

    DEFF Research Database (Denmark)

    Bælum, Vibeke; Hintze, Hanne; Wenzel, Ann

    2012-01-01

    OBJECTIVES: In clinical practice, a visual-tactile caries examination is frequently supplemented by bitewing radiography. This study evaluated strategies for combining visual-tactile and radiographic caries detection methods and determined their implications for clinical management decisions...... in a low-caries population. METHODS: Each of four examiners independently examined preselected contacting interproximal surfaces in 53 dental students aged 20-37 years using a visual-tactile examination and bitewing radiography. The visual-tactile examination distinguished between noncavitated...

  7. Impact of Medical Library Services on Clinical Decision-Making ...

    African Journals Online (AJOL)

    ... the Doctors' clinical decision-making despite its huge limitations enumerated by the Doctors. Recommendations were made towards a balanced collection development of both print and non-print materials, aggressive re-sensitization and reorientation to the use of handheld digital devices for evidence-based medicine.

  8. Using Clinical Decision Support Software in Health Insurance Company

    Science.gov (United States)

    Konovalov, R.; Kumlander, Deniss

    This paper proposes the idea to use Clinical Decision Support software in Health Insurance Company as a tool to reduce the expenses related to Medication Errors. As a prove that this class of software will help insurance companies reducing the expenses, the research was conducted in eight hospitals in United Arab Emirates to analyze the amount of preventable common Medication Errors in drug prescription.

  9. Competence and decision-making: Ethics and clinical psychiatric ...

    African Journals Online (AJOL)

    The making of decisions pertaining to health and personal issues is dependent on the ability of the patient to function in various areas. The concept of competence is viewed differently from the clinical as opposed to the legal viewpoint. Some jurisdictions have introduced into legislation more specific legal guidelines for ...

  10. Decision making in clinical veterinary practice | Anene | Nigerian ...

    African Journals Online (AJOL)

    Decision making in clinical veterinary practice. BM Anene. Abstract. No Abstract. Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD FULL TEXT · AJOL African Journals Online. HOW TO USE AJOL... for Researchers · for Librarians · for Authors · FAQ's · More about AJOL ...

  11. The impact of an electronic clinical decision support for pulmonary ...

    African Journals Online (AJOL)

    Computed tomography pulmonary angiography (CTPA) is sensitive and specific for PE and is the investigation of choice. Inappropriate CTPA utilisation results in unnecessary high radiation exposure and is costly. State-of-the-art electronic radiology workflow can provide clinical decision support (CDS) for specialised ...

  12. Hubble: Linked Data Hub for Clinical Decision Support

    NARCIS (Netherlands)

    Hoekstra, R.; Magliacane, S.; Rietveld, L.; de Vries, G.; Wibisono, A.; Schlobach, S.; Simperl, E.; Norton, B.; Mladenic, D.; Della Valle, E.; Fundulaki, I.; Passant, A.; Troncy, R.

    2015-01-01

    The AERS datasets is one of the few remaining, large publicly available medical data sets that until now have not been published as Linked Data. It is uniquely positioned amidst other medical datasets. This paper describes the Hubble prototype system for clinical decision support that demonstrates

  13. Application of Multiple Criteria Decision Making to Renovation of Multi-Residential Historic Buildings

    DEFF Research Database (Denmark)

    Galiotto, Nicolas; Flourentzou, Flourentzos; Thalmann, Philippe

    2013-01-01

    project, which fulfills simultaneously and optimally all three pillars of sustainability. Multiple criteria decision making methodologies can help to improve the decision environment and handle the whole space of constraints. It therefore leads the stakeholders to find consensual solutions. In this paper...... countries, incentives have so far not had sufficient impact on the rate and depth of the renovations. A very common obstacle in the decision process for building renovation is the conflict between multiple goals. In an early stage of the decision process, stakeholders have the possibility to block...... the indoor environment quality and the comfort of use, questionnaires were distributed to the tenants. Finally, so as to provide the stakeholders with a comprehensive comparison between different possible scenarios, a synthesis of the evaluation of all criteria was made with HERMIONE multiple criteria...

  14. Gamification as a Means to User Involvement in Decision-making Processes for Sustainable Buildings

    DEFF Research Database (Denmark)

    Hansen, Hanne Tine Ring; Knudstrup, Mary-Ann; Skøtt, Stine

    2017-01-01

    User ownership, actors’ and stakeholders’ lack of knowledge is often identified as critical success parameters and barriers when evaluating how well sustainable buildings perform. Recognising that it is impossible to drive sustainable development without the people who pay for sustainable buildings...... was developed by a multidisciplinary group of stakeholders and actors from the Danish building and housing industry. The paper presents how gamification can be used to make complex and academic issues of sustainability available to decision-makers in housing organisations who are typically people from all walks...... of life. Design thinking was used as method to develop a tool that focuses on how to make sustainable strategy development accessible to non-specialists during those critical stages of building design processes when goals and prioritisations are set. The tool is based on an open and editable platform...

  15. Constructing diagnostic likelihood: clinical decisions using subjective versus statistical probability.

    Science.gov (United States)

    Kinnear, John; Jackson, Ruth

    2017-07-01

    Although physicians are highly trained in the application of evidence-based medicine, and are assumed to make rational decisions, there is evidence that their decision making is prone to biases. One of the biases that has been shown to affect accuracy of judgements is that of representativeness and base-rate neglect, where the saliency of a person's features leads to overestimation of their likelihood of belonging to a group. This results in the substitution of 'subjective' probability for statistical probability. This study examines clinicians' propensity to make estimations of subjective probability when presented with clinical information that is considered typical of a medical condition. The strength of the representativeness bias is tested by presenting choices in textual and graphic form. Understanding of statistical probability is also tested by omitting all clinical information. For the questions that included clinical information, 46.7% and 45.5% of clinicians made judgements of statistical probability, respectively. Where the question omitted clinical information, 79.9% of clinicians made a judgement consistent with statistical probability. There was a statistically significant difference in responses to the questions with and without representativeness information (χ2 (1, n=254)=54.45, pprobability. One of the causes for this representativeness bias may be the way clinical medicine is taught where stereotypic presentations are emphasised in diagnostic decision making. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  16. Diagnostic functional MRI: illustrated clinical applications and decision-making.

    Science.gov (United States)

    Bartsch, Andreas Joachim; Homola, György; Biller, Armin; Solymosi, László; Bendszus, Martin

    2006-06-01

    Functional magnetic resonance imaging (fMRI) has become a popular research tool, yet its use for diagnostic purposes and actual treatment planning has remained less widespread. The literature yields rather sparse evidence-based data on clinical fMRI applications and accordant decision-making. Notwithstanding, blood oxygenation level dependent (BOLD)- and arterial spin labeling (ASL)-fMRI can be judiciously combined with perfusion measurements, electroencephalographic (EEG) recordings, diffusion-weighted imaging (DWI), and fiber tractographies to assist clinical decisions. In this article we provide an overview of clinical fMRI applications based on illustrative examples. Assessment of cochlear implant candidates by fMRI is covered in some detail, and distinct reference is made to particular challenges imposed by brain tumors, other space-occupying lesions, cortical dysplasias, seizure disorders, and vascular malformations. Specific strategies, merits, and pitfalls of analyzing and interpreting diagnostic fMRI studies in individual patients are highlighted. Copyright 2006 Wiley-Liss, Inc.

  17. A health examination system integrated with clinical decision support system.

    Science.gov (United States)

    Kuo, Kuan-Liang; Fuh, Chiou-Shann

    2010-10-01

    Health examinations play a key role in preventive medicine. We propose a health examination system named Health Examination Automatic Logic System (HEALS) to assist clinical workers in improving the total quality of health examinations. Quality of automated inference is confirmed by the zero inference error where during 6 months and 14,773 cases. Automated inference time is less than one second per case in contrast to 2 to 5 min for physicians. The most significant result of efficiency evaluation is that 3,494 of 4,356 (80.2%) cases take less than 3 min per case for producing a report summary. In the evaluation of effectiveness, novice physicians got 18% improvement in making decisions with the assistance of our system. We conclude that a health examination system with a clinical decision system can greatly reduce the mundane burden on clinical workers and markedly improve the quality and efficiency of health examination tasks.

  18. A Theory of Change for Capacity Building for the Use of Research Evidence by Decision Makers in Southern Africa

    Science.gov (United States)

    Stewart, Ruth

    2015-01-01

    The effective use of public policy to reduce poverty and inequality in southern Africa requires an increased use of research evidence to inform decision making. There is an absence of clear evidence as to how best to encourage evidence-informed decision making, and how to build capacity among decision makers in the use of research. This paper…

  19. The Relationship Between the Clinical Orientation of Substance Abuse Professionals and Their Clinical Decisions

    Science.gov (United States)

    Toriello, Paul J.; Leierer, Stephen J.

    2005-01-01

    In this study, the authors examined the relationship between the clinical orientations of substance abuse professionals (SAPs) and their clinical decisions. Cluster analysis grouped a sample of 245 SAPs on two clinical orientations that differed in their relative endorsement of traditional versus contemporary substance abuse counseling processes…

  20. Asheville, North Carolina: Reducing Electricity Demand through Building Programs & Policies (City Energy: From Data to Decisions)

    Energy Technology Data Exchange (ETDEWEB)

    Office of Strategic Programs, Strategic Priorities and Impact Analysis Team

    2017-09-29

    This fact sheet "Asheville, North Carolina: Reducing Electricity Demand through Building Programs & Policies" explains how the City of Asheville used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

  1. Building consensus in strategic decision-making : system dynamics as a group support system

    OpenAIRE

    Vennix, J.A.M.

    1995-01-01

    System dynamics was originally founded as a method for modeling and simulating the behavior of industrial systems. In recent years it is increasingly employed as a Group Support System for strategic decision-making groups. The model is constructed in direct interaction with a management team, and the procedure is generally referred to as group model-building. The model can be conceptual (qualitative) or a full-blown (quantitative) computer simulation model. In this article, a case is describe...

  2. Software Tools For Building Decision-support Models For Flood Emergency Situations

    Science.gov (United States)

    Garrote, L.; Molina, M.; Ruiz, J. M.; Mosquera, J. C.

    The SAIDA decision-support system was developed by the Spanish Ministry of the Environment to provide assistance to decision-makers during flood situations. SAIDA has been tentatively implemented in two test basins: Jucar and Guadalhorce, and the Ministry is currently planning to have it implemented in all major Spanish basins in a few years' time. During the development cycle of SAIDA, the need for providing as- sistance to end-users in model definition and calibration was clearly identified. System developers usually emphasise abstraction and generality with the goal of providing a versatile software environment. End users, on the other hand, require concretion and specificity to adapt the general model to their local basins. As decision-support models become more complex, the gap between model developers and users gets wider: Who takes care of model definition, calibration and validation?. Initially, model developers perform these tasks, but the scope is usually limited to a few small test basins. Before the model enters operational stage, end users must get involved in model construction and calibration, in order to gain confidence in the model recommendations. However, getting the users involved in these activities is a difficult task. The goal of this re- search is to develop representation techniques for simulation and management models in order to define, develop and validate a mechanism, supported by a software envi- ronment, oriented to provide assistance to the end-user in building decision models for the prediction and management of river floods in real time. The system is based on three main building blocks: A library of simulators of the physical system, an editor to assist the user in building simulation models, and a machine learning method to calibrate decision models based on the simulation models provided by the user.

  3. Shared clinical decision making. A Saudi Arabian perspective

    Directory of Open Access Journals (Sweden)

    Ali I. AlHaqwi

    2015-12-01

    Full Text Available Objectives: To determine preferences of patients regarding their involvement in the clinical decision making process and the related factors in Saudi Arabia. Methods: This cross-sectional study was conducted in a major family practice center in King Abdulaziz Medical City, Riyadh, Saudi Arabia, between March and May 2012. Multivariate multinomial regression models were fitted to identify factors associated with patients preferences. Results: The study included 236 participants. The most preferred decision-making style was shared decision-making (57%, followed by paternalistic (28%, and informed consumerism (14%. The preference for shared clinical decision making was significantly higher among male patients and those with higher level of education, whereas paternalism was significantly higher among older patients and those with chronic health conditions, and consumerism was significantly higher in younger age groups. In multivariate multinomial regression analysis, compared with the shared group, the consumerism group were more likely to be female [adjusted odds ratio (AOR =2.87, 95% confidence interval [CI] 1.31-6.27, p=0.008] and non-dyslipidemic (AOR=2.90, 95% CI: 1.03-8.09, p=0.04, and the paternalism group were more likely to be older (AOR=1.03, 95% CI: 1.01-1.05, p=0.04, and female (AOR=2.47, 95% CI: 1.32-4.06, p=0.008. Conclusion: Preferences of patients for involvement in the clinical decision-making varied considerably. In our setting, underlying factors that influence these preferences identified in this study should be considered and tailored individually to achieve optimal treatment outcomes.

  4. IBM’s Health Analytics and Clinical Decision Support

    Science.gov (United States)

    Sun, J.; Knoop, S.; Shabo, A.; Carmeli, B.; Sow, D.; Syed-Mahmood, T.; Rapp, W.

    2014-01-01

    Summary Objectives This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Methods Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. Results There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Conclusion Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation. PMID:25123736

  5. Clinical Decision Making of Nurses Working in Hospital Settings

    Directory of Open Access Journals (Sweden)

    Ida Torunn Bjørk

    2011-01-01

    Full Text Available This study analyzed nurses' perceptions of clinical decision making (CDM in their clinical practice and compared differences in decision making related to nurse demographic and contextual variables. A cross-sectional survey was carried out with 2095 nurses in four hospitals in Norway. A 24-item Nursing Decision Making Instrument based on cognitive continuum theory was used to explore how nurses perceived their CDM when meeting an elective patient for the first time. Data were analyzed with descriptive frequencies, t-tests, Chi-Square test, and linear regression. Nurses' decision making was categorized into analytic-systematic, intuitive-interpretive, and quasi-rational models of CDM. Most nurses reported the use of quasi-rational models during CDM thereby supporting the tenet that cognition most often includes properties of both analysis and intuition. Increased use of intuitive-interpretive models of CDM was associated with years in present job, further education, male gender, higher age, and working in predominantly surgical units.

  6. Nurses’ Use of Race in Clinical Decision Making

    Science.gov (United States)

    Sellers, Sherrill L.; Moss, Melissa E.; Calzone, Kathleen; Abdallah, Khadijah E.; Jenkins, Jean F.; Bonham, Vence L.

    2017-01-01

    Purpose To examine nurses’ self-reported use of race in clinical evaluation. Design This cross-sectional study analyzed data collected from three separate studies using the Genetics and Genomics in Nursing Practice Survey, which includes items about use of race and genomic information in nursing practice. The Racial Attributes in Clinical Evaluation (RACE) scale was used to measure explicit clinical use of race among nurses from across the United States. Methods Multivariate regression analysis was used to examine associations between RACE score and individual-level characteristics and beliefs in 5,733 registered nurses. Findings Analysis revealed significant relationships between RACE score and nurses’ race and ethnicity, educational level, and views on the clinical importance of patient demographic characteristics. Asian nurses reported RACE scores 1.41 points higher than White nurses (p nurses reported RACE scores 0.55 points higher than White nurses (p nurses, the baccalaureate-level nurses reported 0.69 points higher RACE scores (p nurses reported 1.63 points higher RACE scores (p nurses reported 1.77 points higher RACE scores (p nurses may be due, in part, to differential levels of racial self-awareness. A relatively linear positive relationship between level of nursing degree nursing education and use of race suggests that a stronger foundation of knowledge about genetic ancestry, population genetics and the concept “race” and genetic ancestry may increase in clinical decision making could allow nurses to more appropriately use of race in clinical care. Integrating patient demographic characteristics into clinical decisions is an important component of nursing practice. Clinical Relevance Registered nurses provide care for diverse racial and ethnic patient populations and stand on the front line of clinical care, making them essential for reducing racial and ethnic disparities in healthcare delivery. Exploring registered nurses’ individual

  7. A Conceptual Framework for Occupant-Centered Building Management Decision Support System

    DEFF Research Database (Denmark)

    Lazarova-Molnar, Sanja; Shaker, Hamid Reza

    2016-01-01

    and organizations. The critical factor for achieving these goals are employees, who are also usually occupants of these buildings and, thus, hold one of the keys to reduced energy consumption. It has been shown that energy-conscious behaviour of building occupants presents a significant opportunity to save energy....... Human behaviour is, however, very complex and hard to predict, and there needs to be a set of conditions satisfied for occupants to cooperate on the energy efficiency level. Majority of commercial buildings’ occupants are not directly affected by their energy-consumption related behaviour due to the non......-obvious/-direct incentive to reduce energy use and no access to their levels of consumption. In this paper we present a framework for a building energy management decision support system that is motivated by these findings, and therefore, centres the occupants and motivates them to both achieve business-wise and improve...

  8. Engineering of a Clinical Decision Support Framework for the Point of Care Use

    Science.gov (United States)

    Wilk, Szymon; Michalowski, Wojtek; O’Sullivan, Dympna; Farion, Ken; Matwin, Stan

    2008-01-01

    Computerized decision support for use at the point of care has to be comprehensive. It means that clinical information stored in electronic health records needs to be integrated with various forms of clinical knowledge (elicited from experts, discovered from data or summarized in systematic reviews of clinical trials). In order to provide such comprehensive support we created the MET-A3Support framework for constructing clinical applications aimed at various medical conditions. We employed the multiagent system paradigm and the O-MaSE methodology to define an engineering process involving three main activities: requirements engineering, analysis and design. Then we applied the process to build MET-A3Support. The paper describes the engineering process and its results, including models representing selected elements of our framework. PMID:18999068

  9. LAMDA at TREC CDS track 2015: Clinical Decision Support Track

    Science.gov (United States)

    2015-11-20

    In TREC 2015 Clinical Decision Support Track, our goal is to retrieve the relevant medical articles for the questions about medical statement. We...its semantic type. Query expansion is executed by extracting the semantic type from the description of the question , and appending words in the...Science Research Program through the National Research Foundation (NRF) of Korea funded by the Ministry of Science, ICT , and Future Planning (MSIP

  10. Unsatisfactory colposcopy: clinical decision-making in conditions of uncertainty

    OpenAIRE

    Manley, Kristyn M.; Simms, Rebecca A.; Platt, Sarah; Patel, Amit; Bahl, Rachna

    2017-01-01

    Background Unsatisfactory colposcopy, where the cells of interest are not visible in women with a positive cervical screening test, is a common area of clinical uncertainty due to the lack of clear evidence and guidance. Colposcopists? opinions and experiences are likely to have a significant influence on service provision and the development of national policy. The aim of this study was to analyse decision-making when applied to women with unsatisfactory colposcopy. Methods A multi-centre qu...

  11. Immediate implant placement: clinical decisions, advantages, and disadvantages.

    Science.gov (United States)

    Bhola, Monish; Neely, Anthony L; Kolhatkar, Shilpa

    2008-10-01

    Implant placement in fresh extraction sockets in conjunction with appropriate guided bone regeneration is well documented. The decision to extract teeth and replace them with immediate implants is determined by many factors, which ultimately affect the total treatment plan. The goal of this article is to review some of the important clinical considerations when selecting patients for immediate implant placement, and to discuss the advantages and disadvantages of this mode of therapy.

  12. Implications of caries diagnostic strategies for clinical management decisions.

    Science.gov (United States)

    Baelum, Vibeke; Hintze, Hanne; Wenzel, Ann; Danielsen, Bo; Nyvad, Bente

    2012-06-01

    In clinical practice, a visual-tactile caries examination is frequently supplemented by bitewing radiography. This study evaluated strategies for combining visual-tactile and radiographic caries detection methods and determined their implications for clinical management decisions in a low-caries population. Each of four examiners independently examined preselected contacting interproximal surfaces in 53 dental students aged 20-37 years using a visual-tactile examination and bitewing radiography. The visual-tactile examination distinguished between noncavitated and cavitated lesions while the radiographic examination determined lesion depth. Direct inspection of the surfaces following tooth separation for the presence of cavitated or noncavitated lesions was the validation method. The true-positive rate (i.e. the sensitivity) and the false-positive rate (i.e. 1-specificity) were calculated for each diagnostic strategy. Visual-tactile examination provided a true-positive rate of 34.2% and a false-positive rate of 1.5% for the detection of a cavity. The combination of a visual-tactile and a radiographic examination using the lesion in dentin threshold for assuming cavitation had a true-positive rate of 76.3% and a false-positive rate of 8.2%. When diagnostic observations were translated into clinical management decisions using the rule that a noncavitated lesion should be treated nonoperatively and a cavitated lesion operatively, our results showed that the visual-tactile method alone was the superior strategy, resulting in most correct clinical management decisions and most correct decisions regarding the choice of treatment. © 2011 John Wiley & Sons A/S.

  13. Nurses' Use of Race in Clinical Decision Making.

    Science.gov (United States)

    Sellers, Sherrill L; Moss, Melissa E; Calzone, Kathleen; Abdallah, Khadijah E; Jenkins, Jean F; Bonham, Vence L

    2016-11-01

    To examine nurses' self-reported use of race in clinical evaluation. This cross-sectional study analyzed data collected from three separate studies using the Genetics and Genomics in Nursing Practice Survey, which includes items about use of race and genomic information in nursing practice. The Racial Attributes in Clinical Evaluation (RACE) scale was used to measure explicit clinical use of race among nurses from across the United States. Multivariate regression analysis was used to examine associations between RACE score and individual-level characteristics and beliefs in 5,733 registered nurses. Analysis revealed significant relationships between RACE score and nurses' race and ethnicity, educational level, and views on the clinical importance of patient demographic characteristics. Asian nurses reported RACE scores 1.41 points higher than White nurses (p RACE scores 0.55 points higher than White nurses (p RACE scores (p RACE scores (p RACE scores (p race and ethnicity corresponded to a 0.54-point increase in RACE score (p RACE score (p RACE score (p RACE score (p race among minority nurses may be due, in part, to differential levels of racial self-awareness. A relatively linear positive relationship between level of nursing degree nursing education and use of race suggests that a stronger foundation of knowledge about genetic ancestry, population genetics and the concept "race" and genetic ancestry may increase in clinical decision making could allow nurses to more appropriately use of race in clinical care. Integrating patient demographic characteristics into clinical decisions is an important component of nursing practice. Registered nurses provide care for diverse racial and ethnic patient populations and stand on the front line of clinical care, making them essential for reducing racial and ethnic disparities in healthcare delivery. Exploring registered nurses' individual-level characteristics and clinical use of race may provide a more comprehensive

  14. A Visual Analytics Based Decision Support Methodology For Evaluating Low Energy Building Design Alternatives

    Science.gov (United States)

    Dutta, Ranojoy

    The ability to design high performance buildings has acquired great importance in recent years due to numerous federal, societal and environmental initiatives. However, this endeavor is much more demanding in terms of designer expertise and time. It requires a whole new level of synergy between automated performance prediction with the human capabilities to perceive, evaluate and ultimately select a suitable solution. While performance prediction can be highly automated through the use of computers, performance evaluation cannot, unless it is with respect to a single criterion. The need to address multi-criteria requirements makes it more valuable for a designer to know the "latitude" or "degrees of freedom" he has in changing certain design variables while achieving preset criteria such as energy performance, life cycle cost, environmental impacts etc. This requirement can be met by a decision support framework based on near-optimal "satisficing" as opposed to purely optimal decision making techniques. Currently, such a comprehensive design framework is lacking, which is the basis for undertaking this research. The primary objective of this research is to facilitate a complementary relationship between designers and computers for Multi-Criterion Decision Making (MCDM) during high performance building design. It is based on the application of Monte Carlo approaches to create a database of solutions using deterministic whole building energy simulations, along with data mining methods to rank variable importance and reduce the multi-dimensionality of the problem. A novel interactive visualization approach is then proposed which uses regression based models to create dynamic interplays of how varying these important variables affect the multiple criteria, while providing a visual range or band of variation of the different design parameters. The MCDM process has been incorporated into an alternative methodology for high performance building design referred to as

  15. Clinical decision-making of rural novice nurses.

    Science.gov (United States)

    Seright, T J

    2011-01-01

    Nurses in rural settings are often the first to assess and interpret the patient's clinical presentations. Therefore, an understanding of how nurses experience decision-making is important in terms of educational preparation, resource allocation to rural areas, institutional cultures, and patient outcomes. Theory development was based on the in-depth investigation of 12 novice nurses practicing in rural critical access hospitals in a north central state. This grounded theory study consisted of face-to-face interviews with 12 registered nurses, nine of whom were observed during their work day. The participants were interviewed a second time, as a method of member checking, and during this interview they reviewed their transcripts, the emerging themes and categories. Directors of nursing from both the research sites and rural hospitals not involved in the study, experienced researchers, and nurse educators facilitated triangulation of the findings. 'Sociocentric rationalizing' emerged as the central phenomenon and referred to the sense of belonging and agency which impacted the decision-making in this small group of novice nurses in rural critical access hospitals. The observed consequences, which were conceptualized during the axial coding process and were derived from observations and interviews of the 12 novice nurses in this study include: (1) gathering information before making a decision included assessment of: the credibility of co-workers, patients' subjective and objective data, and one's own past and current experiences; (2) conferring with co-workers as a direct method of confirming/denying decisions being made was considered more realistic and expedient than policy books and decision trees; (3) rural practicum clinical experiences, along with support after orientation, provide for transition to the rural nurse role; (4) involved directors of nursing served as both models and protectors of novice nurses placed in high accountability positions early in

  16. Mechanistic biomarkers for clinical decision making in rheumatic diseases

    Science.gov (United States)

    Robinson, William H.; Lindstrom, Tamsin M.; Cheung, Regina K.; Sokolove, Jeremy

    2013-01-01

    The use of biomarkers is becoming increasingly intrinsic to the practice of medicine and holds great promise for transforming the practice of rheumatology. Biomarkers have the potential to aid clinical diagnosis when symptoms are present or to provide a means of detecting early signs of disease when they are not. Some biomarkers can serve as early surrogates of eventual clinical outcomes or guide therapeutic decision making by enabling identification of individuals likely to respond to a specific therapy. Using biomarkers might reduce the costs of drug development by enabling individuals most likely to respond to be enrolled in clinical trials, thereby minimizing the number of participants required. In this Review, we discuss the current use and the potential of biomarkers in rheumatology and in select fields at the forefront of biomarker research. We emphasize the value of different types of biomarkers, addressing the concept of ‘actionable’ biomarkers, which can be used to guide clinical decision making, and ‘mechanistic’ biomarkers, a subtype of actionable biomarker that is embedded in disease pathogenesis and, therefore, represents a superior biomarker. We provide examples of actionable and mechanistic biomarkers currently available, and discuss how development of such biomarkers could revolutionize clinical practice and drug development. PMID:23419428

  17. Real-Time Clinical Decision Support Decreases Inappropriate Plasma Transfusion.

    Science.gov (United States)

    Shah, Neil; Baker, Steven A; Spain, David; Shieh, Lisa; Shepard, John; Hadhazy, Eric; Maggio, Paul; Goodnough, Lawrence T

    2017-08-01

    To curtail inappropriate plasma transfusions, we instituted clinical decision support as an alert upon order entry if the patient's recent international normalized ratio (INR) was 1.7 or less. The alert was suppressed for massive transfusion and within operative or apheresis settings. The plasma order was automatically removed upon alert acceptance while clinical exception reasons allowed for continued transfusion. Alert impact was studied comparing a 7-month control period with a 4-month intervention period. Monthly plasma utilization decreased 17.4%, from a mean ± SD of 3.40 ± 0.48 to 2.82 ± 0.6 plasma units per hundred patient days (95% confidence interval [CI] of difference, -0.1 to 1.3). Plasma transfused below an INR of 1.7 or less decreased from 47.6% to 41.6% (P = .0002; odds ratio, 0.78; 95% CI, 0.69-0.89). The alert recommendation was accepted 33% of the time while clinical exceptions were chosen in the remaining cases (active bleeding, 31%; other clinical indication, 33%; and apheresis, 2%). Alert acceptance rate varied significantly among different provider specialties. Clinical decision support can help curtail inappropriate plasma use but needs to be part of a comprehensive strategy including audit and feedback for comprehensive, long-term changes.

  18. Clinical decision making in exercise prescription for fall prevention.

    Science.gov (United States)

    Haas, Romi; Maloney, Stephen; Pausenberger, Eva; Keating, Jennifer L; Sims, Jane; Molloy, Elizabeth; Jolly, Brian; Morgan, Prue; Haines, Terry

    2012-05-01

    Physical therapists often prescribe exercises for fall prevention. Understanding the factors influencing the clinical decision-making processes used by expert physical therapists working in specialist fall and balance clinics may assist other therapists in prescribing exercises for fall prevention with greater efficacy. The objective of this study was to describe the factors influencing the clinical decision-making processes used by expert physical therapists to prescribe exercises for fall prevention. This investigation was a qualitative study from a phenomenological perspective. Semistructured telephone interviews were conducted with 24 expert physical therapists recruited primarily from the Victorian Falls Clinic Coalition. Interviews focused on 3 exercise prescription contexts: face-to-face individual therapy, group exercise programs, and home exercise programs. Interviews elicited information about therapist practices and the therapist, patient, and environmental factors influencing the clinical decision-making processes for the selection of exercise setting, type, dosage (intensity, quantity, rest periods, duration, and frequency), and progression. Strategies for promoting adherence and safety were also discussed. Data were analyzed with a framework approach by 3 investigators. Participants described highly individualized exercise prescription approaches tailored to address key findings from physical assessments. Dissonance between prescribing a program that was theoretically correct on the basis of physiological considerations and prescribing one that a client would adhere to was evident. Safety considerations also were highly influential on the exercise type and setting prescribed. Terminology for describing the intensity of balance exercises was vague relative to terminology for describing the intensity of strength exercises. Physical therapists with expertise in fall prevention adopted an individualized approach to exercise prescription that was based on

  19. The comparison of the energy performance of hotel buildings using PROMETHEE decision-making method

    Directory of Open Access Journals (Sweden)

    Vujosevic Milica L.

    2016-01-01

    Full Text Available Annual energy performance of the atrium type hotel buildings in Belgrade climate conditions are analysed in this paper. The objective is to examine the impact of the atrium on the hotel building’s energy needs for space heating and cooling, thus establishing the best design among four proposed alternatives of the hotels with atrium. The energy performance results are obtained using EnergyPlus simulation engine, taking into account Belgrade climate data and thermal comfort parameters. The selected results are compared and the hotels are ranked according to certain criteria. Decision-making process that resulted in the ranking of the proposed alternatives is conducted using PROMETHEE method and Borda model. The methodological approach in this research includes the creation of a hypothetical model of an atrium type hotel building, numerical simulation of energy performances of four design alternatives of the hotel building with an atrium, comparative analysis of the obtained results and ranking of the proposed alternatives from the building’s energy performance perspective. The main task of the analysis is to examine the influence of the atrium, with both its shape and position, on the energy performance of the hotel building. Based on the results of the research it can be to determine the most energy efficient model of the hotel building with atrium for Belgrade climate condition areas. [Projekat Ministarstva nauke Republike Srbije: Spatial, Environmental, Energy and Social aspects of the Developing Settlements and Climate Change - Mutual Impacts

  20. A qualitative study: Clinical decision making in low back pain.

    Science.gov (United States)

    Davies, Claire; Howell, Dana

    2012-02-01

    Classification systems are available to subgroup patients with acute/nonspecific low back pain (LBP) to determine interventions. The use of classification systems by physical therapists (PT) has little published evidence. The aims of this study were to understand the process PTs use when assessing and determining interventions for patients with acute/nonspecific LBP in outpatient settings and what classification systems, if any, are used in clinical practice. Qualitative methods were used to investigate the decision-making process PTs use when managing patients with LBP. Semi-structured interviews focused on the decision-making process of examination and intervention selection for patients with LBP. Findings were verified through member checking, triangulation, and audit trail. Thirteen PTs were included in the study. Four decision-making preferences emerged from the data: (1) identifying the root cause, (2) eclectic approach, (3) experience-based management, and (4) evidence-based management. Experience, education, and other aspects of the PTs' backgrounds influenced their preferred decision-making style, and use of resources, such as classification systems, varied broadly.

  1. A DFuzzy-DAHP Decision-Making Model for Evaluating Energy-Saving Design Strategies for Residential Buildings

    Directory of Open Access Journals (Sweden)

    Yu-Lung Chen

    2012-11-01

    Full Text Available The construction industry is a high-pollution and high-energy-consumption industry. Energy-saving designs for residential buildings not only reduce the energy consumed during construction, but also reduce long-term energy consumption in completed residential buildings. Because building design affects investment costs, designs are often influenced by investors’ decisions. A set of appropriate decision-support tools for residential buildings are required to examine how building design influences corporations externally and internally. From the perspective of energy savings and environmental protection, we combined three methods to develop a unique model for evaluating the energy-saving design of residential buildings. Among these methods, the Delphi group decision-making method provides a co-design feature, the analytical hierarchy process (AHP includes multi-criteria decision-making techniques, and fuzzy logic theory can simplify complex internal and external factors into easy-to-understand numbers or ratios that facilitate decisions. The results of this study show that incorporating solar building materials, double-skin facades, and green roof designs can effectively provide high energy-saving building designs.

  2. A highly scalable, interoperable clinical decision support service.

    Science.gov (United States)

    Goldberg, Howard S; Paterno, Marilyn D; Rocha, Beatriz H; Schaeffer, Molly; Wright, Adam; Erickson, Jessica L; Middleton, Blackford

    2014-02-01

    To create a clinical decision support (CDS) system that is shareable across healthcare delivery systems and settings over large geographic regions. The enterprise clinical rules service (ECRS) realizes nine design principles through a series of enterprise java beans and leverages off-the-shelf rules management systems in order to provide consistent, maintainable, and scalable decision support in a variety of settings. The ECRS is deployed at Partners HealthCare System (PHS) and is in use for a series of trials by members of the CDS consortium, including internally developed systems at PHS, the Regenstrief Institute, and vendor-based systems deployed at locations in Oregon and New Jersey. Performance measures indicate that the ECRS provides sub-second response time when measured apart from services required to retrieve data and assemble the continuity of care document used as input. We consider related work, design decisions, comparisons with emerging national standards, and discuss uses and limitations of the ECRS. ECRS design, implementation, and use in CDS consortium trials indicate that it provides the flexibility and modularity needed for broad use and performs adequately. Future work will investigate additional CDS patterns, alternative methods of data passing, and further optimizations in ECRS performance.

  3. Using concept mapping to build clinical judgment skills.

    Science.gov (United States)

    Gerdeman, Jaime L; Lux, Kathleen; Jacko, Jean

    2013-01-01

    This article is a description of educational innovation that utilizes concept mapping as a teaching strategy in the development of critical thinking skills of undergraduate nursing students. A concept mapping rubric was designed using Tanner's Clinical Judgment Model to guide students (n = 8) in the construction of clinical cases for the development of appropriate clinical judgment skills. Each student evaluated the concept mapping exercise and provided feedback regarding the rubric, their understanding of the clinical situation, and the development of clinical judgment skills. The students expressed that the concept mapping activity and rubric lead them to make better clinical decisions and increased clinical judgment skills. Content analysis is the research method used to make inferences from qualitative data, with the purpose of providing new insights and clinical knowledge regarding this teaching strategy. Future recommendations for the use of this teaching strategy include shortening the wording and descriptions for each stage of evaluation to promote ease of use for the student in the growth of critical thinking skills. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. Towards the Significance of Decision Aid in Building Information Modeling (BIM Software Selection Process

    Directory of Open Access Journals (Sweden)

    Omar Mohd Faizal

    2014-01-01

    Full Text Available Building Information Modeling (BIM has been considered as a solution in construction industry to numerous problems such as delays, increased lead in times and increased costs. This is due to the concept and characteristic of BIM that will reshaped the way construction project teams work together to increase productivity and improve the final project outcomes (cost, time, quality, safety, functionality, maintainability, etc.. As a result, the construction industry has witnesses numerous of BIM software available in market. Each of this software has offers different function, features. Furthermore, the adoption of BIM required high investment on software, hardware and also training expenses. Thus, there is indentified that there is a need of decision aid for appropriated BIM software selection that fulfill the project needs. However, research indicates that there is limited study attempt to guide decision in BIM software selection problem. Thus, this paper highlight the importance of decision making and support for BIM software selection as it is vital to increase productivity, construction project throughout building lifecycle.

  5. Using attribute behavior diversity to build accurate decision tree committees for microarray data.

    Science.gov (United States)

    Han, Qian; Dong, Guozhu

    2012-08-01

    DNA microarrays (gene chips), frequently used in biological and medical studies, measure the expressions of thousands of genes per sample. Using microarray data to build accurate classifiers for diseases is an important task. This paper introduces an algorithm, called Committee of Decision Trees by Attribute Behavior Diversity (CABD), to build highly accurate ensembles of decision trees for such data. Since a committee's accuracy is greatly influenced by the diversity among its member classifiers, CABD uses two new ideas to "optimize" that diversity, namely (1) the concept of attribute behavior-based similarity between attributes, and (2) the concept of attribute usage diversity among trees. The ideas are effective for microarray data, since such data have many features and behavior similarity between genes can be high. Experiments on microarray data for six cancers show that CABD outperforms previous ensemble methods significantly and outperforms SVM, and show that the diversified features used by CABD's decision tree committee can be used to improve performance of other classifiers such as SVM. CABD has potential for other high-dimensional data, and its ideas may apply to ensembles of other classifier types.

  6. A Decision Support Tool for Building Integrated Renewable Energy Microgrids Connected to a Smart Grid

    Directory of Open Access Journals (Sweden)

    Damilola A. Asaleye

    2017-11-01

    Full Text Available The objective of this study was to create a tool that will enable renewable energy microgrid (REμG facility users to make informed decisions on the utilization of electrical power output from a building integrated REμG connected to a smart grid. A decision support tool for renewable energy microgrids (DSTREM capable of predicting photovoltaic array and wind turbine power outputs was developed. The tool simulated users’ daily electricity consumption costs, avoided CO2 emissions and incurred monetary income relative to the usage of the building integrated REμG connected to the national electricity smart grid. DSTREM forecasted climate variables, which were used to predict REμG power output over a period of seven days. Control logic was used to prioritize supply of electricity to consumers from the renewable energy sources and the national smart grid. Across the evaluated REμG electricity supply options and during working days, electricity exported by the REμG to the national smart grid ranged from 0% to 61% of total daily generation. The results demonstrated that both monetary saving and CO2 offsets can be substantially improved through the application of DSTREM to a REμG connected to a building.

  7. Medical students, clinical preventive services, and shared decision-making.

    Science.gov (United States)

    Keefe, Carole W; Thompson, Margaret E; Noel, Mary Margaret

    2002-11-01

    Improving access to preventive care requires addressing patient, provider, and systems barriers. Patients often lack knowledge or are skeptical about the importance of prevention. Physicians feel that they have too little time, are not trained to deliver preventive services, and are concerned about the effectiveness of prevention. We have implemented an educational module in the required family practice clerkship (1) to enhance medical student learning about common clinical preventive services and (2) to teach students how to inform and involve patients in shared decision making about those services. Students are asked to examine available evidence-based information for preventive screening services. They are encouraged to look at the recommendations of various organizations and use such resources as reports from the U.S. Preventive Services Task Force to determine recommendations they want to be knowledgeable about in talking with their patients. For learning shared decision making, students are trained to use a model adapted from Braddock and colleagues(1) to discuss specific screening services and to engage patients in the process of making informed decisions about what is best for their own health. The shared decision making is presented and modeled by faculty, discussed in small groups, and students practice using Web-based cases and simulations. The students are evaluated using formative and summative performance-based assessments as they interact with simulated patients about (1) screening for high blood cholesterol and other lipid abnormalities, (2) screening for colorectal cancer, (3) screening for prostate cancer, and (4) screening for breast cancer. The final student evaluation is a ten-minute, videotaped discussion with a simulated patient about screening for colorectal cancer that is graded against a checklist that focuses primarily on the elements of shared decision making. Our medical students appear quite willing to accept shared decision making as

  8. How do small groups make decisions? : A theoretical framework to inform the implementation and study of clinical competency committees.

    Science.gov (United States)

    Chahine, Saad; Cristancho, Sayra; Padgett, Jessica; Lingard, Lorelei

    2017-06-01

    In the competency-based medical education (CBME) approach, clinical competency committees are responsible for making decisions about trainees' competence. However, we currently lack a theoretical model for group decision-making to inform this emerging assessment phenomenon. This paper proposes an organizing framework to study and guide the decision-making processes of clinical competency committees.This is an explanatory, non-exhaustive review, tailored to identify relevant theoretical and evidence-based papers related to small group decision-making. The search was conducted using Google Scholar, Web of Science, MEDLINE, ERIC, and PsycINFO for relevant literature. Using a thematic analysis, two researchers (SC & JP) met four times between April-June 2016 to consolidate the literature included in this review.Three theoretical orientations towards group decision-making emerged from the review: schema, constructivist, and social influence. Schema orientations focus on how groups use algorithms for decision-making. Constructivist orientations focus on how groups construct their shared understanding. Social influence orientations focus on how individual members influence the group's perspective on a decision. Moderators of decision-making relevant to all orientations include: guidelines, stressors, authority, and leadership.Clinical competency committees are the mechanisms by which groups of clinicians will be in charge of interpreting multiple assessment data points and coming to a shared decision about trainee competence. The way in which these committees make decisions can have huge implications for trainee progression and, ultimately, patient care. Therefore, there is a pressing need to build the science of how such group decision-making works in practice. This synthesis suggests a preliminary organizing framework that can be used in the implementation and study of clinical competency committees.

  9. A Clinical Decision Support System for Breast Cancer Patients

    Science.gov (United States)

    Fernandes, Ana S.; Alves, Pedro; Jarman, Ian H.; Etchells, Terence A.; Fonseca, José M.; Lisboa, Paulo J. G.

    This paper proposes a Web clinical decision support system for clinical oncologists and for breast cancer patients making prognostic assessments, using the particular characteristics of the individual patient. This system comprises three different prognostic modelling methodologies: the clinically widely used Nottingham prognostic index (NPI); the Cox regression modelling and a partial logistic artificial neural network with automatic relevance determination (PLANN-ARD). All three models yield a different prognostic index that can be analysed together in order to obtain a more accurate prognostic assessment of the patient. Missing data is incorporated in the mentioned models, a common issue in medical data that was overcome using multiple imputation techniques. Risk group assignments are also provided through a methodology based on regression trees, where Boolean rules can be obtained expressed with patient characteristics.

  10. Clinical decision making for caries management in children.

    Science.gov (United States)

    Tinanoff, Norman; Douglass, Joanna M

    2002-01-01

    The aim of this review of clinical decision making for caries management in children is to integrate current knowledge in the field of cariology into clinically usable concepts and procedures. Current evidence regarding the carious process and caries risk assessment allows the practitioner to go beyond traditional surgical management of dental caries. Therapy should focus on patient-specific approaches that include disease monitoring and preventive therapies supplemented when necessary by restorative care. The type and intensity of these therapies should be determined utilizing clinical data as well as knowledge of the caries process for that child. Changes in the management of dental caries will require health organizations and dental schools to educate students, practitioners, and patients in evidence- and risk-based care.

  11. Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design.

    Science.gov (United States)

    Islam, Roosan; Weir, Charlene R; Jones, Makoto; Del Fiol, Guilherme; Samore, Matthew H

    2015-11-30

    Clinical experts' cognitive mechanisms for managing complexity have implications for the design of future innovative healthcare systems. The purpose of the study is to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt to their information environment. We used Cognitive Task Analysis (CTA) methods to interview 10 Infectious Disease (ID) experts at the University of Utah and Salt Lake City Veterans Administration Medical Center. Participants were asked to recall a complex, critical and vivid antibiotic-prescribing incident using the Critical Decision Method (CDM), a type of Cognitive Task Analysis (CTA). Using the four iterations of the Critical Decision Method, questions were posed to fully explore the incident, focusing in depth on the clinical components underlying the complexity. Probes were included to assess cognitive and decision strategies used by participants. The following three themes emerged as the constituents of decision complexity experienced by the Infectious Diseases experts: 1) the overall clinical picture does not match the pattern, 2) a lack of comprehension of the situation and 3) dealing with social and emotional pressures such as fear and anxiety. All these factors contribute to decision complexity. These factors almost always occurred together, creating unexpected events and uncertainty in clinical reasoning. Five themes emerged in the analyses of how experts deal with the complexity. Expert clinicians frequently used 1) watchful waiting instead of over- prescribing antibiotics, engaged in 2) theory of mind to project and simulate other practitioners' perspectives, reduced very complex cases into simple 3) heuristics, employed 4) anticipatory thinking to plan and re-plan events and consulted with peers to share knowledge, solicit opinions and 5) seek help on patient cases. The cognitive strategies to deal with decision complexity found in this study have important

  12. Multicriteria Decision Analysis of Material Selection of High Energy Performance Residential Building

    Science.gov (United States)

    Čuláková, Monika; Vilčeková, Silvia; Katunská, Jana; Krídlová Burdová, Eva

    2013-11-01

    In world with limited amount of energy sources and with serious environmental pollution, interest in comparing the environmental embodied impacts of buildings using different structure systems and alternative building materials will be increased. This paper shows the significance of life cycle energy and carbon perspective and the material selection in reducing energy consumption and emissions production in the built environment. The study evaluates embodied environmental impacts of nearly zero energy residential structures. The environmental assessment uses framework of LCA within boundary: cradle to gate. Designed alternative scenarios of material compositions are also assessed in terms of energy effectiveness through selected thermal-physical parameters. This study uses multi-criteria decision analysis for making clearer selection between alternative scenarios. The results of MCDA show that alternative E from materials on nature plant base (wood, straw bales, massive wood panel) present possible way to sustainable perspective of nearly zero energy houses in Slovak republic

  13. Providers' Response to Clinical Decision Support for QT Prolonging Drugs.

    Science.gov (United States)

    Sharma, Sunita; Martijn Bos, J; Tarrell, Robert F; Simon, Gyorgy J; Morlan, Bruce W; Ackerman, Michael J; Caraballo, Pedro J

    2017-09-02

    Commonly used drugs in hospital setting can cause QT prolongation and trigger life-threatening arrhythmias. We evaluate changes in prescribing behavior after the implementation of a clinical decision support system to prevent the use of QT prolonging medications in the hospital setting. We conducted a quasi-experimental study, before and after the implementation of a clinical decision support system integrated in the electronic medical record (QT-alert system). This system detects patients at risk of significant QT prolongation (QTc>500ms) and alerts providers ordering QT prolonging drugs. We reviewed the electronic health record to assess the provider's responses which were classified as "action taken" (QT drug avoided, QT drug changed, other QT drug(s) avoided, ECG monitoring, electrolytes monitoring, QT issue acknowledged, other actions) or "no action taken". Approximately, 15.5% (95/612) of the alerts were followed by a provider's action in the pre-intervention phase compared with 21% (228/1085) in the post-intervention phase (p=0.006). The most common type of actions taken during pre-intervention phase compared to post-intervention phase were ECG monitoring (8% vs. 13%, p=0.002) and QT issue acknowledgment (2.1% vs. 4.1%, p=0.03). Notably, there was no significant difference for other actions including QT drug avoided (p=0.8), QT drug changed (p=0.06) and other QT drug(s) avoided (p=0.3). Our study demonstrated that the QT alert system prompted a higher proportion of providers to take action on patients at risk of complications. However, the overall impact was modest underscoring the need for educating providers and optimizing clinical decision support to further reduce drug-induced QT prolongation.

  14. Research utilization in the building industry: decision model and preliminary assessment

    Energy Technology Data Exchange (ETDEWEB)

    Watts, R.L.; Johnson, D.R.; Smith, S.A.; Westergard, E.J.

    1985-10-01

    The Research Utilization Program was conceived as a far-reaching means for managing the interactions of the private sector and the federal research sector as they deal with energy conservation in buildings. The program emphasizes a private-public partnership in planning a research agenda and in applying the results of ongoing and completed research. The results of this task support the hypothesis that the transfer of R and D results to the buildings industry can be accomplished more efficiently and quickly by a systematic approach to technology transfer. This systematic approach involves targeting decision makers, assessing research and information needs, properly formating information, and then transmitting the information through trusted channels. The purpose of this report is to introduce elements of a market-oriented knowledge base, which would be useful to the Building Systems Division, the Office of Buildings and Community Systems and their associated laboratories in managing a private-public research partnership on a rational systematic basis. This report presents conceptual models and data bases that can be used in formulating a technology transfer strategy and in planning technology transfer programs.

  15. Guideline Formalization and Knowledge Representation for Clinical Decision Support

    Directory of Open Access Journals (Sweden)

    Tiago OLIVEIRA

    2012-09-01

    Full Text Available Normal 0 21 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} The prevalence of situations of medical error and defensive medicine in healthcare institutions is a great concern of the medical community. Clinical Practice Guidelines are regarded by most researchers as a way to mitigate theseoccurrences; however, there is a need to make them interactive, easier to update and to deploy. This paper provides a model for Computer-Interpretable Guidelines based on the generic tasks of the clinical process, devised to be included in the framework of a Clinical Decision Support System. Aiming to represent medical recommendations in a simple and intuitive way. Hence, this work proposes a knowledge representation formalism that uses an Extension to Logic Programming to handle incomplete information. This model is used to represent different cases of missing, conflicting and inexact information with the aid of a method to quantify its quality. The integration of the guideline model with the knowledge representation formalism yields a clinical decision model that relies on the development of multiple information scenarios and the exploration of different clinical hypotheses.

  16. Guideline Formalization and Knowledge Representation for Clinical Decision Support

    Directory of Open Access Journals (Sweden)

    Paulo NOVAIS

    2013-07-01

    Full Text Available Normal 0 21 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} The prevalence of situations of medical error and defensive medicine in healthcare institutions is a great concern of the medical community. Clinical Practice Guidelines are regarded by most researchers as a way to mitigate these occurrences; however, there is a need to make them interactive, easier to update and to deploy. This paper provides a model for Computer-Interpretable Guidelines based on the generic tasks of the clinical process, devised to be included in the framework of a Clinical Decision Support System. Aiming to represent medical recommendations in a simple and intuitive way. Hence, this work proposes a knowledge representation formalism that uses an Extension to Logic Programming to handle incomplete information. This model is used to represent different cases of missing, conflicting and inexact information with the aid of a method to quantify its quality. The integration of the guideline model with the knowledge representation formalism yields a clinical decision model that relies on the development of multiple information scenarios and the exploration of different clinical hypotheses.

  17. Is it the time to rethink clinical decision-making strategies? From a single clinical outcome evaluation to a Clinical Multi-criteria Decision Assessment (CMDA).

    Science.gov (United States)

    Migliore, Alberto; Integlia, Davide; Bizzi, Emanuele; Piaggio, Tomaso

    2015-10-01

    There are plenty of different clinical, organizational and economic parameters to consider in order having a complete assessment of the total impact of a pharmaceutical treatment. In the attempt to follow, a holistic approach aimed to provide an evaluation embracing all clinical parameters in order to choose the best treatments, it is necessary to compare and weight multiple criteria. Therefore, a change is required: we need to move from a decision-making context based on the assessment of one single criteria towards a transparent and systematic framework enabling decision makers to assess all relevant parameters simultaneously in order to choose the best treatment to use. In order to apply the MCDA methodology to clinical decision making the best pharmaceutical treatment (or medical devices) to use to treat a specific pathology, we suggest a specific application of the Multiple Criteria Decision Analysis for the purpose, like a Clinical Multi-criteria Decision Assessment CMDA. In CMDA, results from both meta-analysis and observational studies are used by a clinical consensus after attributing weights to specific domains and related parameters. The decision will result from a related comparison of all consequences (i.e., efficacy, safety, adherence, administration route) existing behind the choice to use a specific pharmacological treatment. The match will yield a score (in absolute value) that link each parameter with a specific intervention, and then a final score for each treatment. The higher is the final score; the most appropriate is the intervention to treat disease considering all criteria (domain an parameters). The results will allow the physician to evaluate the best clinical treatment for his patients considering at the same time all relevant criteria such as clinical effectiveness for all parameters and administration route. The use of CMDA model will yield a clear and complete indication of the best pharmaceutical treatment to use for patients

  18. Appreciative inquiry enhances cardiology nurses’ clinical decision making when using a clinical guideline on delirium

    DEFF Research Database (Denmark)

    Vedsegaard, Helle; Schrader, Anne-Marie; Rom, Gitte

    2016-01-01

    The current study responds to implementation challenges with translating evidence-based knowledge into practice. We explore how appreciative inquiry can be used in in-house learning sessions for nurses to enhance their knowledge in using a guideline on delirium as part of clinical decision making...... and axial coding drawing on the principles of grounded theory. The study shows that appreciative inquiry was meaningful to cardiology nurses in providing them with knowledge of using a guideline on delirium in clinical decision making, the main reasons being a) data on a current patient were included, b...

  19. Artificial intelligence framework for simulating clinical decision-making: a Markov decision process approach.

    Science.gov (United States)

    Bennett, Casey C; Hauser, Kris

    2013-01-01

    In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This framework serves two potential functions: (1) a simulation environment for exploring various healthcare policies, payment methodologies, etc., and (2) the basis for clinical artificial intelligence - an AI that can "think like a doctor". This approach combines Markov decision processes and dynamic decision networks to learn from clinical data and develop complex plans via simulation of alternative sequential decision paths while capturing the sometimes conflicting, sometimes synergistic interactions of various components in the healthcare system. It can operate in partially observable environments (in the case of missing observations or data) by maintaining belief states about patient health status and functions as an online agent that plans and re-plans as actions are performed and new observations are obtained. This framework was evaluated using real patient data from an electronic health record. The results demonstrate the feasibility of this approach; such an AI framework easily outperforms the current treatment-as-usual (TAU) case-rate/fee-for-service models of healthcare. The cost per unit of outcome change (CPUC) was $189 vs. $497 for AI vs. TAU (where lower is considered optimal) - while at the same time the AI approach could obtain a 30-35% increase in patient outcomes. Tweaking certain AI model parameters could further enhance this advantage, obtaining approximately 50% more improvement (outcome change) for roughly half the costs. Given careful design and problem formulation, an AI simulation framework can approximate optimal

  20. Decision Support for Diabetes in Scotland: Implementation and Evaluation of a Clinical Decision Support System.

    Science.gov (United States)

    Conway, Nicholas; Adamson, Karen A; Cunningham, Scott G; Emslie Smith, Alistair; Nyberg, Peter; Smith, Blair H; Wales, Ann; Wake, Deborah J

    2017-09-01

    Automated clinical decision support systems (CDSS) are associated with improvements in health care delivery to those with long-term conditions, including diabetes. A CDSS was introduced to two Scottish regions (combined diabetes population ~30 000) via a national diabetes electronic health record. This study aims to describe users' reactions to the CDSS and to quantify impact on clinical processes and outcomes over two improvement cycles: December 2013 to February 2014 and August 2014 to November 2014. Feedback was sought via patient questionnaires, health care professional (HCP) focus groups, and questionnaires. Multivariable regression was used to analyze HCP SCI-Diabetes usage (with respect to CDSS message presence/absence) and case-control comparison of clinical processes/outcomes. Cases were patients whose HCP received a CDSS messages during the study period. Closely matched controls were selected from regions outside the study, following similar clinical practice (without CDSS). Clinical process measures were screening rates for diabetes-related complications. Clinical outcomes included HbA1c at 1 year. The CDSS had no adverse impact on consultations. HCPs were generally positive toward CDSS and used it within normal clinical workflow. CDSS messages were generated for 5692 cases, matched to 10 667 controls. Following clinic, the probability of patients being appropriately screened for complications more than doubled for most measures. Mean HbA1c improved in cases and controls but more so in cases (-2.3 mmol/mol [-0.2%] versus -1.1 [-0.1%], P = .003). The CDSS was well received; associated with improved efficiencies in working practices; and large improvements in guideline adherence. These evidence-based, early interventions can significantly reduce costly and devastating complications.

  1. Clinical Decision Support Knowledge Management: Strategies for Success.

    Science.gov (United States)

    Khalifa, Mohamed; Alswailem, Osama

    2015-01-01

    Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital.

  2. Evaluate the ability of clinical decision support systems (CDSSs) to improve clinical practice.

    Science.gov (United States)

    Ajami, Sima; Amini, Fatemeh

    2013-01-01

    Prevalence of new diseases, medical science promotion and increase of referring to health care centers, provide a good situation for medical errors growth. Errors can involve medicines, surgery, diagnosis, equipment, or lab reports. Medical errors can occur anywhere in the health care system: In hospitals, clinics, surgery centers, doctors' offices, nursing homes, pharmacies, and patients' homes. According to the Institute of Medicine (IOM), 98,000 people die every year from preventable medical errors. In 2010 from all referred medical error records to Iran Legal Medicine Organization, 46/5% physician and medical team members were known as delinquent. One of new technologies that can reduce medical errors is clinical decision support systems (CDSSs). This study was unsystematic-review study. The literature was searched on evaluate the "ability of clinical decision support systems to improve clinical practice" with the help of library, books, conference proceedings, data bank, and also searches engines available at Google, Google scholar. For our searches, we employed the following keywords and their combinations: medical error, clinical decision support systems, Computer-Based Clinical Decision Support Systems, information technology, information system, health care quality, computer systems in the searching areas of title, keywords, abstract, and full text. In this study, more than 100 articles and reports were collected and 38 of them were selected based on their relevancy. The CDSSs are computer programs, designed for help to health care careers. These systems as a knowledge-based tool could help health care manager in analyze evaluation, improvement and selection of effective solutions in clinical decisions. Therefore, it has a main role in medical errors reduction. The aim of this study was to express ability of the CDSSs to improve

  3. Clinical genomics information management software linking cancer genome sequence and clinical decisions.

    Science.gov (United States)

    Watt, Stuart; Jiao, Wei; Brown, Andrew M K; Petrocelli, Teresa; Tran, Ben; Zhang, Tong; McPherson, John D; Kamel-Reid, Suzanne; Bedard, Philippe L; Onetto, Nicole; Hudson, Thomas J; Dancey, Janet; Siu, Lillian L; Stein, Lincoln; Ferretti, Vincent

    2013-09-01

    Using sequencing information to guide clinical decision-making requires coordination of a diverse set of people and activities. In clinical genomics, the process typically includes sample acquisition, template preparation, genome data generation, analysis to identify and confirm variant alleles, interpretation of clinical significance, and reporting to clinicians. We describe a software application developed within a clinical genomics study, to support this entire process. The software application tracks patients, samples, genomic results, decisions and reports across the cohort, monitors progress and sends reminders, and works alongside an electronic data capture system for the trial's clinical and genomic data. It incorporates systems to read, store, analyze and consolidate sequencing results from multiple technologies, and provides a curated knowledge base of tumor mutation frequency (from the COSMIC database) annotated with clinical significance and drug sensitivity to generate reports for clinicians. By supporting the entire process, the application provides deep support for clinical decision making, enabling the generation of relevant guidance in reports for verification by an expert panel prior to forwarding to the treating physician. Copyright © 2013 Elsevier Inc. All rights reserved.

  4. How to Reach Decision Makers: Build a network of educators and practitioners with common goals

    Science.gov (United States)

    Boudrias, M. A.; Estrada, M.; Anders, S.; Silva-Send, N. J.; Gershunov, A.

    2013-12-01

    In San Diego County, the Climate Education Partners (CEP) includes climate scientists, science educators, behavioral scientists, environmental practitioners and community organizations that are dedicated to providing local decision makers (elected officials, business leaders, community leaders) with sound climate science learning opportunities and resources that promote informed decision making. Their work over the past three years has found that effective climate education programs are designed for specific audiences with tailored information that is relevant to them, while simultaneously building community efficacy, identity and values. An integrated approach that blends rigorous scientific facts, local climate change impact, and social science education theory is contributing towards the development of a cadre of engaged leaders and communities. To track project progress and to inform the project strategy, local Key Influentials are being interviewed to gauge their current understanding of climate change and their interest in either becoming messengers to their community or becoming the portal to their constituency. Innovation comes from productive collaboration. For this reason, CEP has been working with leading scientists (climatologists, hydrologists, meteorologists, ecologists), environmental groups, museums and zoos, media experts and government agencies (Water Authority, CalFire) to develop and refine a program of learning activities and resources geared specifically for Key Influentials. For example, a water tour has been designed to bring 25 key influential leaders in San Diego County to a dam, a pumping station and a reservoir and provide climate change facts, impacts and potential solutions to the critical issue of water supply for the San Diego Region. While learning local facts about the causes and impacts of climate change, participants also learn about what they can do (increasing efficacy), that they can be a part of a solution centered community

  5. Building capacity for evidence informed decision making in public health: a case study of organizational change.

    Science.gov (United States)

    Peirson, Leslea; Ciliska, Donna; Dobbins, Maureen; Mowat, David

    2012-02-20

    Core competencies for public health in Canada require proficiency in evidence informed decision making (EIDM). However, decision makers often lack access to information, many workers lack knowledge and skills to conduct systematic literature reviews, and public health settings typically lack infrastructure to support EIDM activities. This research was conducted to explore and describe critical factors and dynamics in the early implementation of one public health unit's strategic initiative to develop capacity to make EIDM standard practice. This qualitative case study was conducted in one public health unit in Ontario, Canada between 2008 and 2010. In-depth information was gathered from two sets of semi-structured interviews and focus groups (n = 27) with 70 members of the health unit, and through a review of 137 documents. Thematic analysis was used to code the key informant and document data. The critical factors and dynamics for building EIDM capacity at an organizational level included: clear vision and strong leadership, workforce and skills development, ability to access research (library services), fiscal investments, acquisition and development of technological resources, a knowledge management strategy, effective communication, a receptive organizational culture, and a focus on change management. With leadership, planning, commitment and substantial investments, a public health department has made significant progress, within the first two years of a 10-year initiative, towards achieving its goal of becoming an evidence informed decision making organization.

  6. Can patient decision aids help people make good decisions about participating in clinical trials? A study protocol

    Directory of Open Access Journals (Sweden)

    Fergusson Dean A

    2008-07-01

    Full Text Available Abstract Background Evidence shows that the standard process for obtaining informed consent in clinical trials can be inadequate, with study participants frequently not understanding even basic information fundamental to giving informed consent. Patient decision aids are effective decision support tools originally designed to help patients make difficult treatment or screening decisions. We propose that incorporating decision aids into the informed consent process will improve the extent to which participants make decisions that are informed and consistent with their preferences. A mixed methods study will test this proposal. Methods Phase one of this project will involve assessment of a stratified random sample of 50 consent documents from recently completed investigator-initiated clinical trials, according to existing standards for supporting good decision making. Phase two will involve interviews of a purposive sample of 50 trial participants (10 participants from each of five different clinical areas about their experience of the informed consent process, and how it could be improved. In phase three, we will convert consent forms for two completed clinical trials into decision aids and pilot test these new tools using a user-centered design approach, an iterative development process commonly employed in computer usability literature. In phase four, we will conduct a pilot observational study comparing the new tools to standard consent forms, with potential recruits to two hypothetical clinical trials. Outcomes will include knowledge of key aspects of the decision, knowledge of the probabilities of different outcomes, decisional conflict, the hypothetical participation decision, and qualitative impressions of the experience. Discussion This work will provide initial evidence about whether a patient decision aid can improve the informed consent process. The larger goal of this work is to examine whether study recruitment can be improved from

  7. Peripheral Exophytic Oral Lesions: A Clinical Decision Tree

    Directory of Open Access Journals (Sweden)

    Hamed Mortazavi

    2017-01-01

    Full Text Available Diagnosis of peripheral oral exophytic lesions might be quite challenging. This review article aimed to introduce a decision tree for oral exophytic lesions according to their clinical features. General search engines and specialized databases including PubMed, PubMed Central, Medline Plus, EBSCO, Science Direct, Scopus, Embase, and authenticated textbooks were used to find relevant topics by means of keywords such as “oral soft tissue lesion,” “oral tumor like lesion,” “oral mucosal enlargement,” and “oral exophytic lesion.” Related English-language articles published since 1988 to 2016 in both medical and dental journals were appraised. Upon compilation of data, peripheral oral exophytic lesions were categorized into two major groups according to their surface texture: smooth (mesenchymal or nonsquamous epithelium-originated and rough (squamous epithelium-originated. Lesions with smooth surface were also categorized into three subgroups according to their general frequency: reactive hyperplastic lesions/inflammatory hyperplasia, salivary gland lesions (nonneoplastic and neoplastic, and mesenchymal lesions (benign and malignant neoplasms. In addition, lesions with rough surface were summarized in six more common lesions. In total, 29 entities were organized in the form of a decision tree in order to help clinicians establish a logical diagnosis by a stepwise progression method.

  8. Clinical implementation of RNA signatures for pharmacogenomic decision-making

    Directory of Open Access Journals (Sweden)

    Tang W

    2011-09-01

    Full Text Available Weihua Tang1, Zhiyuan Hu2, Hind Muallem1, Margaret L Gulley1,21Department of Pathology and Laboratory Medicine, 2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, North Carolina, NC, USAAbstract: RNA profiling is increasingly used to predict drug response, dose, or toxicity based on analysis of drug pharmacokinetic or pharmacodynamic pathways. Before implementing multiplexed RNA arrays in clinical practice, validation studies are carried out to demonstrate sufficient evidence of analytic and clinical performance, and to establish an assay protocol with quality assurance measures. Pathologists assure quality by selecting input tissue and by interpreting results in the context of the input tissue as well as the technologies that were used and the clinical setting in which the test was ordered. A strength of RNA profiling is the array-based measurement of tens to thousands of RNAs at once, including redundant tests for critical analytes or pathways to promote confidence in test results. Instrument and reagent manufacturers are crucial for supplying reliable components of the test system. Strategies for quality assurance include careful attention to RNA preservation and quality checks at pertinent steps in the assay protocol, beginning with specimen collection and proceeding through the various phases of transport, processing, storage, analysis, interpretation, and reporting. Specimen quality is checked by probing housekeeping transcripts, while spiked and exogenous controls serve as a check on analytic performance of the test system. Software is required to manipulate abundant array data and present it for interpretation by a laboratory physician who reports results in a manner facilitating therapeutic decision-making. Maintenance of the assay requires periodic documentation of personnel competency and laboratory proficiency. These strategies are shepherding genomic arrays into clinical settings to provide added

  9. Building for change: university hospital design for future clinical learning.

    Science.gov (United States)

    Nordenström, Jörgen; Kiessling, Anna; Nordquist, Jonas

    2013-09-01

    Recent developments in the way health care is organized and delivered have rendered many old hospital structures obsolete. The creation of an entire new university hospital for tertiary health care, clinical research and education has made it necessary to discuss and define what pedagogical strategies should be used in this new setting and how physical structures can support learning. Contemporary health care is per se interprofessionally team-based, but most health care education is still performed in silos, separated for each profession. When building a new hospital new possibilities arise to create an interprofessional and learner-centered environment with an adjusted physical infrastructure and spaces for learning. The old hospital conserved highly discipline-based (and professionally isolated) curriculas and didactically oriented; all manifested in the physical environments. However, the New Karolinska University Hospital presents a shift towards a pedagogy characterized by learning centeredness, interprofessionalism clearly expressed in the architecture, design and allocation of spaces within the new buildings. The aim of this article is to highlight the considerations that have been made during the process to design and plan for the new university hospital.

  10. Exploration Clinical Decision Support System: Medical Data Architecture

    Science.gov (United States)

    Lindsey, Tony; Shetye, Sandeep; Shaw, Tianna (Editor)

    2016-01-01

    The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear

  11. Robot decisions: on the importance of virtuous judgment in clinical decision making.

    Science.gov (United States)

    Gelhaus, Petra

    2011-10-01

    The aim of this article is to argue for the necessity of emotional professional virtues in the understanding of good clinical practice. This understanding is required for a proper balance of capacities in medical education and further education of physicians. For this reason an ideal physician, incarnating the required virtues, skills and knowledge is compared with a non-emotional robot that is bound to moral rules. This fictive confrontation is meant to clarify why certain demands on the personality of the physician are justified, in addition to a rule- and principle-based moral orientation and biomedical knowledge and skills. Philosophical analysis of thought experiments inspired by science fiction literature by Isaac Asimov. Although prima facie a rule-oriented robot seems more reliable and trustworthy, the complexity of clinical judgment is not met by an encompassing and never contradictory set of rules from which one could logically derive decisions. There are different ways how the robot could still work, but at the cost of the predictability of its behaviour and its moral orientation. In comparison, a virtuous human doctor who is also bound to these rules, although less strictly, will more reliably keep at moral objectives, be understandable, be more flexible in case the rules come to their limits, and will be more predictable in these critical situations. Apart from these advantages of the virtuous human doctor referring to her own person, the most problematic deficit of the robot is its lacking deeper understanding of the inner mental events of patients which makes good contact, good communication and good influence impossible. Although an infallibly rule-oriented robot seems more reliable at first view, in situations that require complex decisions like clinical practice the agency of a moral human person is more trustworthy. Furthermore, the understanding of the patient's emotions must remain insufficient for a non-emotional, non-human being. Because

  12. Neuroplasticity and Clinical Practice: Building Brain Power for Health

    Directory of Open Access Journals (Sweden)

    Joyce Shaffer

    2016-07-01

    Full Text Available The focus of this review is on driving neuroplasticity in a positive direction using evidence-based interventions that also have the potential to improve general health. One goal is to provide an overview of the many ways new neuroscience can inform treatment protocols to empower and motivate clients to make the lifestyle choices that could help build brain power and could increase adherence to healthy lifestyle changes that have also been associated with simultaneously enhancing vigorous longevity, health, happiness and wellness. Another goal is to explore the use of a focus in clinical practice on helping clients appreciate this new evidence and use evolving neuroscience in establishing individualized goals, designing strategies for achieving them and increasing treatment compliance. The timing is urgent for such interventions with goals of enhancing brain health across the lifespan and improving statistics on dementia worldwide.

  13. Factors and Drivers Effecting the Decision of Using Off-Site Manufacturing (OSM Systems in House Building Industry

    Directory of Open Access Journals (Sweden)

    Hussein Elnaas

    2014-01-01

    Full Text Available Much has been written on Off-site Manufacturing (OSM in construction, particularly regarding the perceived benefits and barriers to implementation. However, there seems to be a wide misunderstanding of the state of OSM associated with the concept of decision by many of those involved in decision making process within the house building industry. This has led to a demand for guidance’s on decision making process for construction project leaders particularly at early project stages. Choosing a construction method for a project will require an optimum decision strategy which involves careful understanding, measurement and evaluation of a number of decision factors that can have the most influence on successful decision action. This paper, therefore, aims to identify the key decision factors to be considered at evaluation stage when choosing to use Off-Site Manufacturing (OSM as a construction strategy in house building projects. This will reveal the key drivers for change in the industry towards the use of OSM in house building.

  14. A clinical decision-making algorithm for penicillin allergy.

    Science.gov (United States)

    Soria, Angèle; Autegarden, Elodie; Amsler, Emmanuelle; Gaouar, Hafida; Vial, Amandine; Francès, Camille; Autegarden, Jean-Eric

    2017-12-01

    About 10% of subjects report suspected penicillin allergy, but 85-90% of these patients are not truly allergic and could safely receive beta-lactam antibiotics Objective: To design and validate a clinical decision-making algorithm, based on anamnesis (chronology, severity, and duration of the suspected allergic reactions) and reaching a 100% sensitivity and negative predictive value, to assess allergy risk related to a penicillin prescription in general practise. All patients were included prospectively and explorated based on ENDA/EAACI recommendations. Results of penicillin allergy work-up (gold standard) were compared with results of the algorithm. Allergological work-up diagnosed penicillin hypersensitivity in 41/259 patients (15.8%) [95% CI: 11.5-20.3]. Three of these patients were diagnosed as having immediate-type hypersensitivity to penicillin, but had been misdiagnosed as low risk patients using the clinical algorithm. Thus, the sensitivity and negative predictive value of the algorithm were 92.7% [95% CI: 80.1-98.5] and 96.3% [95% CI: 89.6-99.2], respectively, and the probability that a patient with true penicillin allergy had been misclassified was 3.7% [95% CI: 0.8-10.4]. Although the risk of misclassification is low, we cannot recommend the use of this algorithm in general practice. However, the algorithm can be useful in emergency situations in hospital settings. Key messages True penicillin allergy is considerably lower than alleged penicillin allergy (15.8%; 41 of the 259 patients with suspected penicillin allergy). A clinical algorithm based on the patient's clinical history of the supposed allergic event to penicillin misclassified 3/41 (3.7%) truly allergic patients.

  15. SANDS: an architecture for clinical decision support in a National Health Information Network.

    Science.gov (United States)

    Wright, Adam; Sittig, Dean F

    2007-10-11

    A new architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support) is introduced and its performance evaluated. The architecture provides a method for performing clinical decision support across a network, as in a health information exchange. Using the prototype we demonstrated that, first, a number of useful types of decision support can be carried out using our architecture; and, second, that the architecture exhibits desirable reliability and performance characteristics.

  16. A Scalable Architecture for Rule Engine Based Clinical Decision Support Systems.

    Science.gov (United States)

    Chattopadhyay, Soumi; Banerjee, Ansuman; Banerjee, Nilanjan

    2015-01-01

    Clinical Decision Support systems (CDSS) have reached a fair level of sophistication and have emerged as the popular system of choice for their aid in clinical decision making. These decision support systems are based on rule engines navigate through a repertoire of clinical rules and multitudes of facts to assist a clinical expert to decide on the set of actuations in response to a medical situation. In this paper, we present the design of a scalable architecture for a rule engine based clinical decision system.

  17. Building Capacity to Use Earth Observations in Decision Making for Climate, Health, Agriculture and Natural Disasters

    Science.gov (United States)

    Robertson, A. W.; Ceccato, P.

    2015-12-01

    In order to fill the gaps existing in climate and public health, agriculture, natural disasters knowledge and practices, the International Research Institute for Climate and Society (IRI) has developed a Curriculum for Best Practices in Climate Information. This Curriculum builds on the experience of 10 years courses on 'Climate Information' and captures lessons and experiences from different tailored trainings that have been implemented in many countries in Africa, Asia and Latin America. In this presentation, we will provide examples of training activities we have developed to bring remote sensing products to monitor climatic and environmental information into decision processes that benefited users such as the World Health Organization, Ministries of Health, Ministries of Agriculture, Universities, Research Centers such as CIFOR and FIOCRUZ. The framework developed by IRI to provide capacity building is based on the IDEAS framework: Innovation (research) Around climate impacts, evaluation of interventions, and the value of climate information in reducing risks and maximizing opportunities Demonstration E.g. in-country GFCS projects in Tanzania and Malawi - or El Nino work in Ethiopia Education Academic and professional training efforts Advocacy This might focus on communication of variability and change? We are WHO collaborating center so are engaged through RBM/Global Malaria Programme Service ENACTS and Data library key to this. Country data better quality than NASA as incorporates all relevant station data and NASA products. This presentation will demonstrate how the IDEAS framework has been implemented and lessons learned.

  18. Interoperability of clinical decision-support systems and electronic health records using archetypes: a case study in clinical trial eligibility.

    Science.gov (United States)

    Marcos, Mar; Maldonado, Jose A; Martínez-Salvador, Begoña; Boscá, Diego; Robles, Montserrat

    2013-08-01

    Clinical decision-support systems (CDSSs) comprise systems as diverse as sophisticated platforms to store and manage clinical data, tools to alert clinicians of problematic situations, or decision-making tools to assist clinicians. Irrespective of the kind of decision-support task CDSSs should be smoothly integrated within the clinical information system, interacting with other components, in particular with the electronic health record (EHR). However, despite decades of developments, most CDSSs lack interoperability features. We deal with the interoperability problem of CDSSs and EHRs by exploiting the dual-model methodology. This methodology distinguishes a reference model and archetypes. A reference model is represented by a stable and small object-oriented model that describes the generic properties of health record information. For their part, archetypes are reusable and domain-specific definitions of clinical concepts in the form of structured and constrained combinations of the entities of the reference model. We rely on archetypes to make the CDSS compatible with EHRs from different institutions. Concretely, we use archetypes for modelling the clinical concepts that the CDSS requires, in conjunction with a series of knowledge-intensive mappings relating the archetypes to the data sources (EHR and/or other archetypes) they depend on. We introduce a comprehensive approach, including a set of tools as well as methodological guidelines, to deal with the interoperability of CDSSs and EHRs based on archetypes. Archetypes are used to build a conceptual layer of the kind of a virtual health record (VHR) over the EHR whose contents need to be integrated and used in the CDSS, associating them with structural and terminology-based semantics. Subsequently, the archetypes are mapped to the EHR by means of an expressive mapping language and specific-purpose tools. We also describe a case study where the tools and methodology have been employed in a CDSS to support

  19. Translating shared decision-making into health care clinical practices: Proof of concepts

    Directory of Open Access Journals (Sweden)

    St-Jacques Sylvie

    2008-01-01

    Full Text Available Abstract Background There is considerable interest today in shared decision-making (SDM, defined as a decision-making process jointly shared by patients and their health care provider. However, the data show that SDM has not been broadly adopted yet. Consequently, the main goal of this proposal is to bring together the resources and the expertise needed to develop an interdisciplinary and international research team on the implementation of SDM in clinical practice using a theory-based dyadic perspective. Methods Participants include researchers from Canada, US, UK, and Netherlands, representing medicine, nursing, psychology, community health and epidemiology. In order to develop a collaborative research network that takes advantage of the expertise of the team members, the following research activities are planned: 1 establish networking and on-going communication through internet-based forum, conference calls, and a bi-weekly e-bulletin; 2 hold a two-day workshop with two key experts (one in theoretical underpinnings of behavioral change, and a second in dyadic data analysis, and invite all investigators to present their views on the challenges related to the implementation of SDM in clinical practices; 3 conduct a secondary analyses of existing dyadic datasets to ensure that discussion among team members is grounded in empirical data; 4 build capacity with involvement of graduate students in the workshop and online forum; and 5 elaborate a position paper and an international multi-site study protocol. Discussion This study protocol aims to inform researchers, educators, and clinicians interested in improving their understanding of effective strategies to implement shared decision-making in clinical practice using a theory-based dyadic perspective.

  20. Energy conservation standards for new federal residential buildings: A decision analysis study using relative value discounting

    Energy Technology Data Exchange (ETDEWEB)

    Harvey, C. (Houston Univ., TX (USA). Coll. of Business Administration); Merkhofer, M.M.; Hamm, G.L. (Applied Decision Analysis, Inc., Menlo Park, CA (USA))

    1990-07-02

    This report presents a reassessment of the proposed standard for energy conservation in new federal residential buildings. The analysis uses the data presented in the report, Economic Analysis: In Support of Interim Energy Conservation Standards for New Federal Residential Buildings (June 1988)-to be referred to as the EASIECS report. The reassessment differs from that report in several respects. In modeling factual information, it uses more recent forecasts of future energy prices and it uses data from the Bureau of the Census in order to estimate the distribution of lifetimes of residential buildings rather than assuming a hypothetical 25-year lifetime. In modeling social preferences decision analysis techniques are used in order to examine issues of public values that often are not included in traditional cost-benefit analyses. The present report concludes that the public would benefit from the proposed standard. Several issues of public values regarding energy use are illustrated with methods to include them in a formal analysis of a proposed energy policy. The first issue places a value on costs and benefits that will occur in the future as an irreversible consequence of current policy choices. This report discusses an alternative method, called relative value discounting which permits flexible discounting of future events-and the possibility of placing greater values on future events. The second issue places a value on the indirect benefits of energy savings so that benefits accrue to everyone rather than only to the person who saves the energy. This report includes non-zero estimates of the indirect benefits. The third issue is how the costs and benefits discussed in a public policy evaluation should be compared. In summary, selection of individual projects with larger benefit to cost ratios leads to a portfolio of projects with the maximum benefit to cost difference. 30 refs., 6 figs., 16 tabs. (JF)

  1. Referral criteria and clinical decision support: radiological protection aspects for justification.

    Science.gov (United States)

    Pérez, M del Rosario

    2015-06-01

    Advanced imaging technology has opened new horizons for medical diagnostics and improved patient care. However, many procedures are unjustified and do not provide a net benefit. An area of particular concern is the unnecessary use of radiation when clinical evaluation or other imaging modalities could provide an accurate diagnosis. Referral criteria for medical imaging are consensus statements based on the best-available evidence to assist the decision-making process when choosing the best imaging procedure for a given patient. Although they are advisory rather than compulsory, physicians should have good reasons for deviation from these criteria. Voluntary use of referral criteria has shown limited success compared with integration into clinical decision support systems. These systems support good medical practice, can improve health service delivery, and foster safer, more efficient, fair, cost-effective care, thus contributing to the strengthening of health systems. Justification of procedures and optimisation of protection, the two pillars of radiological protection in health care, are implicit in the notion of good medical practice. However, some health professionals are not familiar with these principles, and have low awareness of radiological protection aspects of justification. A stronger collaboration between radiation protection and healthcare communities could contribute to improve the radiation protection culture in medical practice. © The Chartered Institution of Building Services Engineers 2014.

  2. By-person factor analysis in clinical ethical decision making: Q methodology in end-of-life care decisions.

    Science.gov (United States)

    Wong, William; Eiser, Arnold R; Mrtek, Robert G; Heckerling, Paul S

    2004-01-01

    To determine the usefulness of Q methodology to locate and describe shared subjective influences on clinical decision making among participant physicians using hypothetical cases containing common ethical issues. Qualitative study using by-person factor analysis of subjective Q sort data matrix. University medical center. Convenience sample of internal medicine attending physicians and house staff (n = 35) at one midwestern academic health sciences center. Presented with four hypothetical cases involving urgent decision making near the end of life, participants selected one of three specific clinical actions offered for each case. Immediately afterward and while considering their decision, each respondent sorted twenty-five subjective self-referent items in terms of the influence of each statement on their decision-making process. By-person factor analysis, where participants are defined as variates, yielded information about the attitudinal background the physicians brought to their consideration of each hypothetical case. We performed a second-order factor analysis on all of the subjective viewpoints to determine if a smaller core of shared attitudes existed across some or all of the four case vignettes. Factor scores for each item and post-sort comments from interviews conducted individually with each respondent guided the interpretation of ethical perspective used by these respondents in making clinical decisions about the cases. Second-order factor analysis on seventeen viewpoints used by physicians in the four hypothetical urgent decision cases revealed three moderately correlated (r2 person factor analysis are useful qualitative methodological tools to study the complex structure of subjective attitudes that influence physicians in making medical decisions. This study revealed the subjective viewpoints used by our physician participants as they made ethically challenging treatment decisions. The three second-order factors identified here are grounded in

  3. Creating and sharing clinical decision support content with Web 2.0: Issues and examples.

    Science.gov (United States)

    Wright, Adam; Bates, David W; Middleton, Blackford; Hongsermeier, Tonya; Kashyap, Vipul; Thomas, Sean M; Sittig, Dean F

    2009-04-01

    Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

  4. Optimal Decision Model for Sustainable Hospital Building Renovation-A Case Study of a Vacant School Building Converting into a Community Public Hospital.

    Science.gov (United States)

    Juan, Yi-Kai; Cheng, Yu-Ching; Perng, Yeng-Horng; Castro-Lacouture, Daniel

    2016-06-24

    Much attention has been paid to hospitals environments since modern pandemics have emerged. The building sector is considered to be the largest world energy consumer, so many global organizations are attempting to create a sustainable environment in building construction by reducing energy consumption. Therefore, maintaining high standards of hygiene while reducing energy consumption has become a major task for hospitals. This study develops a decision model based on genetic algorithms and A* graph search algorithms to evaluate existing hospital environmental conditions and to recommend an optimal scheme of sustainable renovation strategies, considering trade-offs among minimal renovation cost, maximum quality improvement, and low environmental impact. Reusing vacant buildings is a global and sustainable trend. In Taiwan, for example, more and more school space will be unoccupied due to a rapidly declining birth rate. Integrating medical care with local community elder-care efforts becomes important because of the aging population. This research introduces a model that converts a simulated vacant school building into a community public hospital renovation project in order to validate the solutions made by hospital managers and suggested by the system. The result reveals that the system performs well and its solutions are more successful than the actions undertaken by decision-makers. This system can improve traditional hospital building condition assessment while making it more effective and efficient.

  5. Digital technology and clinical decision making in depression treatment: Current findings and future opportunities.

    Science.gov (United States)

    Hallgren, Kevin A; Bauer, Amy M; Atkins, David C

    2017-06-01

    Clinical decision making encompasses a broad set of processes that contribute to the effectiveness of depression treatments. There is emerging interest in using digital technologies to support effective and efficient clinical decision making. In this paper, we provide "snapshots" of research and current directions on ways that digital technologies can support clinical decision making in depression treatment. Practical facets of clinical decision making are reviewed, then research, design, and implementation opportunities where technology can potentially enhance clinical decision making are outlined. Discussions of these opportunities are organized around three established movements designed to enhance clinical decision making for depression treatment, including measurement-based care, integrated care, and personalized medicine. Research, design, and implementation efforts may support clinical decision making for depression by (1) improving tools to incorporate depression symptom data into existing electronic health record systems, (2) enhancing measurement of treatment fidelity and treatment processes, (3) harnessing smartphone and biosensor data to inform clinical decision making, (4) enhancing tools that support communication and care coordination between patients and providers and within provider teams, and (5) leveraging treatment and outcome data from electronic health record systems to support personalized depression treatment. The current climate of rapid changes in both healthcare and digital technologies facilitates an urgent need for research, design, and implementation of digital technologies that explicitly support clinical decision making. Ensuring that such tools are efficient, effective, and usable in frontline treatment settings will be essential for their success and will require engagement of stakeholders from multiple domains. © 2017 Wiley Periodicals, Inc.

  6. Clinical Decision Support for Early Recognition of Sepsis.

    Science.gov (United States)

    Amland, Robert C; Hahn-Cover, Kristin E

    2016-01-01

    Sepsis is an inflammatory response triggered by infection, with a high in-hospital mortality rate. Early recognition and treatment can reverse the inflammatory response, with evidence of improved patient outcomes. One challenge clinicians face is identifying the inflammatory syndrome against the background of the patient's infectious illness and comorbidities. An approach to this problem is implementation of computerized early warning tools for sepsis. This multicenter retrospective study sought to determine clinimetric performance of a cloud-based computerized sepsis clinical decision support system (CDS), understand the epidemiology of sepsis, and identify opportunities for quality improvement. Data encompassed 6200 adult hospitalizations from 2012 through 2013. Of 13% patients screened-in, 51% were already suspected to have an infection when the system activated. This study focused on a patient cohort screened-in before infection was suspected; median time from arrival to CDS activation was 3.5 hours, and system activation to diagnostic collect was another 8.6 hours. © The Author(s) 2014.

  7. Building

    OpenAIRE

    Seavy, Ryan

    2014-01-01

    Building for concrete is temporary. The building of wood and steel stands against the concrete to give form and then gives way, leaving a trace of its existence behind. Concrete is not a building material. One does not build with concrete. One builds for concrete. MARCH

  8. Modeling the green building (GB) investment decisions of developers and end-users with transaction costs (TCs) considerations

    NARCIS (Netherlands)

    Qian, Q.K.; Chan, E.H.W.; Visscher, H.J.; Lehmann, S.

    2015-01-01

    The paper, through a “regenerative” lens, has focused upon a new conceptual game system involving transaction costs (TCs) for creating a more accessible green buildings (GB) market. Individual stakeholders steadfastly guard their own interests in any investment decision, which seldom considers any

  9. Applying a family systems lens to proxy decision making in clinical practice and research.

    Science.gov (United States)

    Rolland, John S; Emanuel, Linda L; Torke, Alexia M

    2017-03-01

    When patients are incapacitated and face serious illness, family members must make medical decisions for the patient. Medical decision sciences give only modest attention to the relationships among patients and their family members, including impact that these relationships have on the decision-making process. A review of the literature reveals little effort to systematically apply a theoretical framework to the role of family interactions in proxy decision making. A family systems perspective can provide a useful lens through which to understand the dynamics of proxy decision making. This article considers the mutual impact of family systems on the processes and outcomes of proxy decision making. The article first reviews medical decision science's evolution and focus on proxy decision making and then reviews a family systems approach, giving particular attention to Rolland's Family Systems Illness Model. A case illustrates how clinical practice and how research would benefit from bringing family systems thinking to proxy decisions. We recommend including a family systems approach in medical decision science research and clinical practices around proxy decisions making. We propose that clinical decisions could be less conflicted and less emotionally troubling for families and clinicians if family systems approaches were included. This perspective opens new directions for research and novel approaches to clinical care. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  10. Parametric vs. Nonparametric Regression Modelling within Clinical Decision Support

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan; Zvárová, Jana

    2017-01-01

    Roč. 5, č. 1 (2017), s. 21-27 ISSN 1805-8698 R&D Projects: GA ČR GA17-01251S Institutional support: RVO:67985807 Keywords : decision support systems * decision rules * statistical analysis * nonparametric regression Subject RIV: IN - Informatics, Computer Science OBOR OECD: Statistics and probability

  11. Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets.

    Science.gov (United States)

    Chen, Jonathan H; Alagappan, Muthuraman; Goldstein, Mary K; Asch, Steven M; Altman, Russ B

    2017-06-01

    Determine how varying longitudinal historical training data can impact prediction of future clinical decisions. Estimate the "decay rate" of clinical data source relevance. We trained a clinical order recommender system, analogous to Netflix or Amazon's "Customers who bought A also bought B..." product recommenders, based on a tertiary academic hospital's structured electronic health record data. We used this system to predict future (2013) admission orders based on different subsets of historical training data (2009 through 2012), relative to existing human-authored order sets. Predicting future (2013) inpatient orders is more accurate with models trained on just one month of recent (2012) data than with 12 months of older (2009) data (ROC AUC 0.91 vs. 0.88, precision 27% vs. 22%, recall 52% vs. 43%, all P<10 -10 ). Algorithmically learned models from even the older (2009) data was still more effective than existing human-authored order sets (ROC AUC 0.81, precision 16% recall 35%). Training with more longitudinal data (2009-2012) was no better than using only the most recent (2012) data, unless applying a decaying weighting scheme with a "half-life" of data relevance about 4 months. Clinical practice patterns (automatically) learned from electronic health record data can vary substantially across years. Gold standards for clinical decision support are elusive moving targets, reinforcing the need for automated methods that can adapt to evolving information. Prioritizing small amounts of recent data is more effective than using larger amounts of older data towards future clinical predictions. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  12. Integrating Simplified and Full Life Cycle Approaches in Decision Making for Building Energy Refurbishment: Benefits and Barriers

    Directory of Open Access Journals (Sweden)

    Xabat Oregi

    2015-05-01

    Full Text Available The life cycle assessment (LCA method is a powerful tool that can serve to aid decision making regarding the environmental benefits of refurbishment projects. However, due to the relative complexity of LCA studies, simplified LCA methodologies are frequently used, focusing on just some of the building life cycle phases or a reduced number of indicators. The most common and widespread simplification is to only evaluate the differences a refurbishment project makes on the operational energy use of the building. This paper compares the results of applying full LCA, simplified LCA and operational energy use assessment in a refurbishment case study. Results show that simplified LCA methodologies including building use phase and product manufacturing phase can generally be sufficiently accurate to aid decision making for building energy refurbishment, as other building life cycle phases related to transport of products, on site construction, deconstruction or end of life represent a generally negligible part of the total life cycle impacts, both in terms of resource use or environmental impacts. Barriers and benefits of applying simplified LCA approaches to building energy refurbishment projects are subsequently discussed.

  13. Computer-based Monitoring for Decision Support Systems and Disaster Preparedness in Buildings

    Directory of Open Access Journals (Sweden)

    Alan Vinh

    2009-04-01

    Full Text Available The operation of modern buildings can support a vast amount of static and real-time data. Static information such as building schematics is vital for security and rescue purposes. There is a need for building managers and for first responders to be notified of designated building alerts in real-time so that actions can be performed promptly. The capability to monitor building devices and to keep the first responder community updated with the latest building information during emergency situations, as well as the ability to remotely control certain building devices and processes, can be realized today. This paper describes the various challenges encountered in the research area of building interoperability and proposes methods and insights for developing a standards framework to enable communication between building information systems and first responder information systems. Having a standards framework in place will assist in the development and deployment of commercial products in support of building interoperability.

  14. Factors influencing the clinical decision-making of midwives: a qualitative study.

    Science.gov (United States)

    Daemers, Darie O A; van Limbeek, Evelien B M; Wijnen, Hennie A A; Nieuwenhuijze, Marianne J; de Vries, Raymond G

    2017-10-06

    Although midwives make clinical decisions that have an impact on the health and well-being of mothers and babies, little is known about how they make those decisions. Wide variation in intrapartum decisions to refer women to obstetrician-led care suggests that midwives' decisions are based on more than the evidence based medicine (EBM) model - i.e. clinical evidence, midwife's expertise, and woman's values - alone. With this study we aimed to explore the factors that influence clinical decision-making of midwives who work independently. We used a qualitative approach, conducting in-depth interviews with a purposive sample of 11 Dutch primary care midwives. Data collection took place between May and September 2015. The interviews were semi-structured, using written vignettes to solicit midwives' clinical decision-making processes (Think Aloud method). We performed thematic analysis on the transcripts. We identified five themes that influenced clinical decision-making: the pregnant woman as a whole person, sources of knowledge, the midwife as a whole person, the collaboration between maternity care professionals, and the organisation of care. Regarding the midwife, her decisions were shaped not only by her experience, intuition, and personal circumstances, but also by her attitudes about physiology, woman-centredness, shared decision-making, and collaboration with other professionals. The nature of the local collaboration between maternity care professionals and locally-developed protocols dominated midwives' clinical decision-making. When midwives and obstetricians had different philosophies of care and different practice styles, their collaborative efforts were challenged. Midwives' clinical decision-making is a more varied and complex process than the EBM framework suggests. If midwives are to succeed in their role as promoters and protectors of physiological pregnancy and birth, they need to understand how clinical decisions in a multidisciplinary context are

  15. External validation of clinical decision rules for children with wrist trauma

    NARCIS (Netherlands)

    Mulders, Marjolein A. M.; Walenkamp, Monique M. J.; Dubois, Bente F. H.; Slaar, Annelie; Goslings, J. Carel; Schep, Niels W. L.

    2017-01-01

    Clinical decision rules help to avoid potentially unnecessary radiographs of the wrist, reduce waiting times and save costs. The primary aim of this study was to provide an overview of all existing non-validated clinical decision rules for wrist trauma in children and to externally validate these

  16. External validation of clinical decision rules for children with wrist trauma

    NARCIS (Netherlands)

    M.A.M. Mulders (Marjolein A. M.); M.M.J. Walenkamp (Monique); B.F.H. Dubois (Bente F. H.); A. Slaar (Annelie); J.C. Goslings (Carel); N.W.L. Schep (Niels)

    2017-01-01

    textabstractBackground: Clinical decision rules help to avoid potentially unnecessary radiographs of the wrist, reduce waiting times and save costs. Objective: The primary aim of this study was to provide an overview of all existing non-validated clinical decision rules for wrist trauma in children

  17. Clinical decision-making among new graduate nurses attending residency programs in Saudi Arabia.

    Science.gov (United States)

    Al-Dossary, Reem Nassar; Kitsantas, Panagiota; Maddox, P J

    2016-02-01

    This study examined the impact of residency programs on clinical decision-making of new Saudi graduate nurses who completed a residency program compared to new Saudi graduate nurses who did not participate in residency programs. This descriptive study employed a convenience sample (N=98) of new graduate nurses from three hospitals in Saudi Arabia. A self-administered questionnaire was used to collect data. Clinical decision-making skills were measured using the Clinical Decision Making in Nursing Scale. Descriptive statistics, independent t-tests, and multiple linear regression analysis were utilized to examine the effect of residency programs on new graduate nurses' clinical decision-making skills. On average, resident nurses had significantly higher levels of clinical decision-making skills than non-residents (t=23.25, p=0.000). Enrollment in a residency program explained 86.9% of the variance in total clinical decision making controlling for age and overall grade point average. The findings of this study support evidence in the nursing literature conducted primarily in the US and Europe that residency programs have a positive influence on new graduate nurses' clinical decision-making skills. This is the first study to examine the impact of residency programs on clinical decision-making among new Saudi graduate nurses who completed a residency program. The findings of this study underscore the need for the development and implementation of residency programs for all new nurses. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Implementation of a scalable, web-based, automated clinical decision support risk-prediction tool for chronic kidney disease using C-CDA and application programming interfaces.

    Science.gov (United States)

    Samal, Lipika; D'Amore, John D; Bates, David W; Wright, Adam

    2017-11-01

    Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry so are rarely used. Due to new data interoperability standards for electronic health records (EHRs), other options are available. As a clinical case study, we sought to build a scalable, web-based system that would automate calculation of kidney failure risk and display clinical decision support to users in primary care practices. We developed a single-page application, web server, database, and application programming interface to calculate and display kidney failure risk. Data were extracted from the EHR using the Consolidated Clinical Document Architecture interoperability standard for Continuity of Care Documents (CCDs). EHR users were presented with a noninterruptive alert on the patient's summary screen and a hyperlink to details and recommendations provided through a web application. Clinic schedules and CCDs were retrieved using existing application programming interfaces to the EHR, and we provided a clinical decision support hyperlink to the EHR as a service. We debugged a series of terminology and technical issues. The application was validated with data from 255 patients and subsequently deployed to 10 primary care clinics where, over the course of 1 year, 569 533 CCD documents were processed. We validated the use of interoperable documents and open-source components to develop a low-cost tool for automated clinical decision support. Since Consolidated Clinical Document Architecture-based data extraction extends to any certified EHR, this demonstrates a successful modular approach to clinical decision support.

  19. SANDS: a service-oriented architecture for clinical decision support in a National Health Information Network.

    Science.gov (United States)

    Wright, Adam; Sittig, Dean F

    2008-12-01

    In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are:

  20. What can natural language processing do for clinical decision support?

    National Research Council Canada - National Science Library

    Demner-Fushman, Dina; Chapman, Wendy W; McDonald, Clement J

    2009-01-01

    .... natural language processing (NLP) is instrumental in using free-text information to drive CDS, representing clinical knowledge and CDS interventions in standardized formats, and leveraging clinical narrative...

  1. Integrating computerized clinical decision support systems into clinical work: A meta-synthesis of qualitative research.

    Science.gov (United States)

    Miller, Anne; Moon, Brian; Anders, Shilo; Walden, Rachel; Brown, Steven; Montella, Diane

    2015-12-01

    Computerized clinical decision support systems (CDSS) are an emerging means for improving healthcare safety, quality and efficiency, but meta-analyses findings are mixed. This meta-synthesis aggregates qualitative research findings as possible explanations for variable quantitative research outcomes. Qualitative studies published between 2000 and 2013 in English, involving physicians, registered and advanced practice nurses' experience of CDSS use in clinical practice were included. PubMed and CINAHL databases were searched. Study titles and abstracts were screened against inclusion criteria. Retained studies were appraised against quality criteria. Findings were extracted iteratively from studies in the 4th quartile of quality scores. Two reviewers constructed themes inductively. A third reviewer applied the defined themes deductively achieving 92% agreement. 3798 unique records were returned; 56 met inclusion criteria and were reviewed against quality criteria. 9 studies were of sufficiently high quality for synthetic analysis. Five major themes (clinician-patient-system integration; user interface usability; the need for better 'algorithms'; system maturity; patient safety) were defined. Despite ongoing development, CDSS remains an emerging technology. Lack of understanding about and lack of consideration for the interaction between human decision makers and CDSS is a major reason for poor system adoption and use. Further high-quality qualitative research is needed to better understand human-system interaction issues. These issues may continue to confound quantitative study results if not addressed. Copyright © 2015. Published by Elsevier Ireland Ltd.

  2. [International outcomes from attempts to implement a clinical decision support system in gastroenterology].

    Science.gov (United States)

    Tenório, Josceli Maria; Hummel, Anderson Diniz; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

    2011-01-01

    This study aimed at describing the recent experience acquired with the implementation and use of clinical decision support system in gastroenterology in order to determine the level of development, tests used and advantages that such a system can offer to the medical practice. A search in the PubMed, LILACS and ISI Web of Knowledge databases for studies in decision-making support systems in gastroenterology including original papers produced from 2005 to 2010 was performed. A total of 104 scientific papers were retrieved initially. These were analyzed using inclusion and exclusion criteria, thus yielding nine studies for further analysis. The clinical decision support system analyzed in the present study showed a great variety of clinical problems regarding the investigation of a disease and the determination of a diagnosis. Eighty-nine per cent of the studies showed experimental models for clinical decision support system development. Seventy-eight per cent of the studies described the outcomes obtained with artificial intelligence technique. Two studies compared the clinical decision support system performance with that of a doctor, and only one research work described a controlled study evidencing improvements in the medical practice. The studies analyzed showed evidence of potential benefits that clinical decision support system can bring to the clinical practice. However, further controlled studies performed in medical day-to-day conditions and environment should be performed in order to provide more clear evidence of the usefulness of clinical decision support system in the medical practice.

  3. A kernel-based integration of genome-wide data for clinical decision support.

    Science.gov (United States)

    Daemen, Anneleen; Gevaert, Olivier; Ojeda, Fabian; Debucquoy, Annelies; Suykens, Johan Ak; Sempoux, Christine; Machiels, Jean-Pascal; Haustermans, Karin; De Moor, Bart

    2009-04-03

    Although microarray technology allows the investigation of the transcriptomic make-up of a tumor in one experiment, the transcriptome does not completely reflect the underlying biology due to alternative splicing, post-translational modifications, as well as the influence of pathological conditions (for example, cancer) on transcription and translation. This increases the importance of fusing more than one source of genome-wide data, such as the genome, transcriptome, proteome, and epigenome. The current increase in the amount of available omics data emphasizes the need for a methodological integration framework. We propose a kernel-based approach for clinical decision support in which many genome-wide data sources are combined. Integration occurs within the patient domain at the level of kernel matrices before building the classifier. As supervised classification algorithm, a weighted least squares support vector machine is used. We apply this framework to two cancer cases, namely, a rectal cancer data set containing microarray and proteomics data and a prostate cancer data set containing microarray and genomics data. For both cases, multiple outcomes are predicted. For the rectal cancer outcomes, the highest leave-one-out (LOO) areas under the receiver operating characteristic curves (AUC) were obtained when combining microarray and proteomics data gathered during therapy and ranged from 0.927 to 0.987. For prostate cancer, all four outcomes had a better LOO AUC when combining microarray and genomics data, ranging from 0.786 for recurrence to 0.987 for metastasis. For both cancer sites the prediction of all outcomes improved when more than one genome-wide data set was considered. This suggests that integrating multiple genome-wide data sources increases the predictive performance of clinical decision support models. This emphasizes the need for comprehensive multi-modal data. We acknowledge that, in a first phase, this will substantially increase costs; however

  4. Preprocessing structured clinical data for predictive modeling and decision support. A roadmap to tackle the challenges.

    Science.gov (United States)

    Ferrão, José Carlos; Oliveira, Mónica Duarte; Janela, Filipe; Martins, Henrique M G

    2016-12-07

    EHR systems have high potential to improve healthcare delivery and management. Although structured EHR data generates information in machine-readable formats, their use for decision support still poses technical challenges for researchers due to the need to preprocess and convert data into a matrix format. During our research, we observed that clinical informatics literature does not provide guidance for researchers on how to build this matrix while avoiding potential pitfalls. This article aims to provide researchers a roadmap of the main technical challenges of preprocessing structured EHR data and possible strategies to overcome them. Along standard data processing stages - extracting database entries, defining features, processing data, assessing feature values and integrating data elements, within an EDPAI framework -, we identified the main challenges faced by researchers and reflect on how to address those challenges based on lessons learned from our research experience and on best practices from related literature. We highlight the main potential sources of error, present strategies to approach those challenges and discuss implications of these strategies. Following the EDPAI framework, researchers face five key challenges: (1) gathering and integrating data, (2) identifying and handling different feature types, (3) combining features to handle redundancy and granularity, (4) addressing data missingness, and (5) handling multiple feature values. Strategies to address these challenges include: cross-checking identifiers for robust data retrieval and integration; applying clinical knowledge in identifying feature types, in addressing redundancy and granularity, and in accommodating multiple feature values; and investigating missing patterns adequately. This article contributes to literature by providing a roadmap to inform structured EHR data preprocessing. It may advise researchers on potential pitfalls and implications of methodological decisions in

  5. Merging clinical chemistry biomarker data with a COPD database - building a clinical infrastructure for proteomic studies.

    Science.gov (United States)

    Eriksson, Jonatan; Andersson, Simone; Appelqvist, Roger; Wieslander, Elisabet; Truedsson, Mikael; Bugge, May; Malm, Johan; Dahlbäck, Magnus; Andersson, Bo; Fehniger, Thomas E; Marko-Varga, György

    2016-01-01

    Data from biological samples and medical evaluations plays an essential part in clinical decision making. This data is equally important in clinical studies and it is critical to have an infrastructure that ensures that its quality is preserved throughout its entire lifetime. We are running a 5-year longitudinal clinical study, KOL-Örestad, with the objective to identify new COPD (Chronic Obstructive Pulmonary Disease) biomarkers in blood. In the study, clinical data and blood samples are collected from both private and public health-care institutions and stored at our research center in databases and biobanks, respectively. The blood is analyzed by Mass Spectrometry and the results from this analysis then linked to the clinical data. We built an infrastructure that allows us to efficiently collect and analyze the data. We chose to use REDCap as the EDC (Electronic Data Capture) tool for the study due to its short setup-time, ease of use, and flexibility. REDCap allows users to easily design data collection modules based on existing templates. In addition, it provides two functions that allow users to import batches of data; through a web API (Application Programming Interface) as well as by uploading CSV-files (Comma Separated Values). We created a software, DART (Data Rapid Translation), that translates our biomarker data into a format that fits REDCap's CSV-templates. In addition, DART is configurable to work with many other data formats as well. We use DART to import our clinical chemistry data to the REDCap database. We have shown that a powerful and internationally adopted EDC tool such as REDCap can be extended so that it can be used efficiently in proteomic studies. In our study, we accomplish this by using DART to translate our clinical chemistry data to a format that fits the templates of REDCap.

  6. The changing nature of clinical decision support systems: a focus on consumers, genomics, public health and decision safety.

    Science.gov (United States)

    Coiera, E; Lau, A Y S; Tsafnat, G; Sintchenko, V; Magrabi, F

    2009-01-01

    To review the recent research literature in clinical decision support systems (CDSS). A review of recent literature was undertaken, focussing on CDSS evaluation, consumers and public health, the impact of translational bioinformatics on CDSS design, and CDSS safety. In recent years, researchers have concentrated much less on the development of decision technologies, and have focussed more on the impact of CDSS in the clinical world. Recent work highlights that traditional process measures of CDSS effectiveness, such as document relevance are poor proxy measures for decision outcomes. Measuring the dynamics of decision making, for example via decision velocity, may produce a more accurate picture of effectiveness. Another trend is the broadening of user base for CDSS beyond front line clinicians. Consumers are now a major focus for biomedical informatics, as are public health officials, tasked with detecting and managing disease outbreaks at a health system, rather than individual patient level. Bioinformatics is also changing the nature of CDSS. Apart from personalisation of therapy recommendations, translational bioinformatics is creating new challenges in the interpretation of the meaning of genetic data. Finally, there is much recent interest in the safety and effectiveness of computerised physician order entry (CPOE) systems, given that prescribing and administration errors are a significant cause of morbidity and mortality. Of note, there is still much controversy surrounding the contention that poorly designed, implemented or used CDSS may actually lead to harm. CDSS research remains an active and evolving area of research, as CDSS penetrate more widely beyond their traditional domain into consumer decision support, and as decisions become more complex, for example by involving sequence level genetic data.

  7. Clinical decision making in dermatology: observation of consultations and the patients' perspectives.

    Science.gov (United States)

    Hajjaj, F M; Salek, M S; Basra, M K A; Finlay, A Y

    2010-01-01

    Clinical decision making is a complex process and might be influenced by a wide range of clinical and non-clinical factors. Little is known about this process in dermatology. The aim of this study was to explore the different types of management decisions made in dermatology and to identify factors influencing those decisions from observation of consultations and interviews with the patients. 61 patient consultations were observed by a physician with experience in dermatology. The patients were interviewed immediately after each consultation. Consultations and interviews were audio recorded, transcribed and their content analysed using thematic content analysis. The most common management decisions made during the consultations included: follow-up, carrying out laboratory investigation, starting new topical treatment, renewal of systemic treatment, renewal of topical treatment, discharging patients and starting new systemic treatment. Common influences on those decisions included: clinical factors such as ineffectiveness of previous therapy, adherence to prescribing guidelines, side-effects of medications, previous experience with the treatment, deterioration or improvement in the skin condition, and chronicity of skin condition. Non-clinical factors included: patient's quality of life, patient's friends or relatives, patient's time commitment, travel or transportation difficulties, treatment-related costs, availability of consultant, and availability of treatment. The study has shown that patients are aware that management decisions in dermatology are influenced by a wide range of clinical and non-clinical factors. Education programmes should be developed to improve the quality of decision making. Copyright © 2010 S. Karger AG, Basel.

  8. Review of Current Data Exchange Practices: Providing Descriptive Data to Assist with Building Operations Decisions

    Energy Technology Data Exchange (ETDEWEB)

    Livingood, W.; Stein, J.; Considine, T.; Sloup, C.

    2011-05-01

    Retailers who participate in the U.S. Department of Energy Commercial Building Energy Alliances (CBEA) identified the need to enhance communication standards. The means are available to collect massive numbers of buildings operational data, but CBEA members have difficulty transforming the data into usable information and energy-saving actions. Implementing algorithms for automated fault detection and diagnostics and linking building operational data to computerized maintenance management systems are important steps in the right direction, but have limited scalability for large building portfolios because the algorithms must be configured for each building.

  9. Multigenerational Challenges: Team-Building for Positive Clinical Workforce Outcomes

    Science.gov (United States)

    Moore, Jill M; Everly, Marcee; Bauer, Renee

    2016-05-31

    Patient acuity in hospital settings continues to increase, and there is greater emphasis on patient outcomes. The current nursing workforce is comprised of four distinct generational cohorts that include veterans, baby boomers, millennials, and generation Xers. Each group has unique characteristics that add complexity to the workforce and this can add challenges to providing optimal patient care. Team building is one strategy to increase mutual understanding, communication, and respect, and thus potentially improve patient outcomes. In this article, we first briefly define generational cohorts by characteristics, and discuss differing expectations for work/life balance and potential negative outcomes. Our discussion offers team building strategies for positive outcomes, a case scenario, and concludes with resources for team building and organizational opportunities.

  10. A Model of Cancer Clinical Trial Decision-making Informed by African-American Cancer Patients.

    Science.gov (United States)

    Wenzel, Jennifer A; Mbah, Olive; Xu, Jiayun; Moscou-Jackson, Gyasi; Saleem, Haneefa; Sakyi, Kwame; Ford, Jean G

    2015-06-01

    Clinical trials are critical to advancing cancer treatment. Minority populations are underrepresented among trial participants, and there is limited understanding of their decision-making process and key determinants of decision outcomes regarding trial participation. To understand research decision-making among clinical trial-eligible African-American cancer patients at Johns Hopkins, we conducted seven focus groups (n=32) with trial-offered patients ≥ 18 years diagnosed with lung, breast, prostate, or colorectal cancer ≤ 5 years. Three "acceptor" and four "decliner" focus groups were conducted. Questions addressed: attitudes towards clinical trials, reasons for accepting or declining participation, and recommendations to improve minority recruitment and enrollment. Data were transcribed and analyzed using traditional approaches to content and thematic analysis in NVivo 9.0. Data coding resulted in themes that supported model construction. Participant experiences revealed the following themes when describing the decision-making process: Information gathering, Intrapersonal perspectives, and Interpersonal influences. Decision outcomes included the presence or absence of decision regret and satisfaction. From these themes, we generated a Model of Cancer Clinical Trial Decision-making. Our model should be tested in hypothesis-driven research to elucidate factors and processes influencing decision balance and outcomes of trial-related decision-making. The model should also be tested in other disparities populations and for diagnoses other than cancer.

  11. Why cancer patients enter randomized clinical trials: exploring the factors that influence their decision.

    Science.gov (United States)

    Wright, James R; Whelan, Timothy J; Schiff, Susan; Dubois, Sacha; Crooks, Dauna; Haines, Patricia T; DeRosa, Diane; Roberts, Robin S; Gafni, Amiram; Pritchard, Kathleen; Levine, Mark N

    2004-11-01

    Few interventions have been designed and tested to improve recruitment to clinical trials in oncology. The multiple factors influencing patients' decisions have made the prioritization of specific interventions challenging. The present study was undertaken to identify the independent predictors of a cancer patient's decision to enter a randomized clinical trial. A list of factors from the medical literature was augmented with a series of focus groups involving cancer patients, physicians, and clinical research associates (CRAs). A series of questionnaires was developed with items based on these factors and were administered concurrently to 189 cancer patients, their physicians, and CRAs following the patient's decision regarding trial entry. Forward logistic regression modeling was performed using the items significantly correlated (by univariate analysis) with the decision to enter a clinical trial. A number of items were significantly correlated with the patient's decision. In the multivariate logistic regression model, the patient's perception of personal benefit was the most important, with an odds ratio (OR) of 3.08 (P decision-making process were also important. These included whether the CRA helped with the decision (OR = 1.71; P decision was hard for the patient to make (OR = 0.52; P decision-making process while respecting the need for information and patient autonomy may also lead to meaningful improvements in accrual.

  12. A medical informatics perspective on clinical decision support systems. Findings from the yearbook 2013 section on decision support.

    Science.gov (United States)

    Bouaud, J; Lamy, J-B

    2013-01-01

    To summarize excellent research and to select best papers published in 2012 in the field of computer-based decision support in healthcare. A bibliographic search focused on clinical decision support systems (CDSSs) and computer provider order entry was performed, followed by a double-blind literature review. The review process yielded six papers, illustrating various aspects of clinical decision support. The first paper is a systematic review of CDSS intervention trials in real settings, and considers different types of possible outcomes. It emphasizes the heterogeneity of studies and confirms that CDSSs can improve process measures but that evidence lacks for other types of outcomes, especially clinical or economic. Four other papers tackle the safety of drug prescribing and show that CDSSs can be efficient in reducing prescription errors. The sixth paper exemplifies the growing role of ontological resources which can be used for several applications including decision support. CDSS research has to be continuously developed and assessed. The wide variety of systems and of interventions limits the understanding of factors of success of CDSS implementations. A standardization in the characterization of CDSSs and of intervention trial reporting will help to overcome this obstacle.

  13. Clinical decision support must be useful, functional is not enough

    DEFF Research Database (Denmark)

    Kortteisto, Tiina; Komulainen, Jorma; Mäkelä, Marjukka

    2012-01-01

    ABSTRACT: BACKGROUND: Health information technology, particularly electronic decision support systems, can reduce the existing gap between evidence-based knowledge and health care practice but professionals have to accept and use this information. Evidence is scant on which features influence the...

  14. Clinical decision-making in functional and hyperkinetic movement disorders

    NARCIS (Netherlands)

    van der Salm, Sandra M. A.; van Rootselaar, Anne-Fleur; Cath, Danielle C.; de Haan, Rob J.; Koelman, Johannes H. T. M.; Tijssen, Marina A. J.

    2017-01-01

    Objective: Functional or psychogenic movement disorders (FMD) present a diagnostic challenge. To diagnose FMD, clinicians must have experience with signs typical of FMD and distinguishing features from other hyperkinetic disorders. The aim of this study was to clarify the decision-making process of

  15. Implementation of workflow engine technology to deliver basic clinical decision support functionality.

    Science.gov (United States)

    Huser, Vojtech; Rasmussen, Luke V; Oberg, Ryan; Starren, Justin B

    2011-04-10

    Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. We describe an implementation of a free workflow technology

  16. Implementation of workflow engine technology to deliver basic clinical decision support functionality

    Directory of Open Access Journals (Sweden)

    Oberg Ryan

    2011-04-01

    Full Text Available Abstract Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language process definition language (XPDL. The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent. We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We

  17. Implementation of workflow engine technology to deliver basic clinical decision support functionality

    Science.gov (United States)

    2011-01-01

    Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of

  18. Carrboro, North Carolina: Achieving Building Efficiencies for Low-Income Households (City Energy: From Data to Decisions)

    Energy Technology Data Exchange (ETDEWEB)

    Office of Strategic Programs, Strategic Priorities and Impact Analysis Team

    2017-09-29

    This fact sheet "Carrboro, North Carolina: Achieving Building Efficiencies for Low-Income Households" explains how the Town of Carrboro used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

  19. South Lake Tahoe, California: Using Energy Data to Partner on Building Energy Efficiency Actions (City Energy: From Data to Decisions)

    Energy Technology Data Exchange (ETDEWEB)

    Strategic Priorities and Impact Analysis Team, Office of Strategic Programs

    2017-11-01

    This fact sheet "South Lake Tahoe, California: Using Energy Data to Partner on Building Energy Efficiency Actions" explains how the City of South Lake Tahoe used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

  20. Moab, Utah: Using Energy Data to Target Carbon Reductions from Building Energy Efficiency (City Energy: From Data to Decisions)

    Energy Technology Data Exchange (ETDEWEB)

    Strategic Priorities and Impact Analysis Team, Office of Strategic Programs

    2017-11-01

    This fact sheet "Moab, Utah: Using Energy Data to Target Carbon Reductions from Building Energy Efficiency" explains how the City of Moab used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

  1. [Clinical decision making and critical thinking in the nursing diagnostic process].

    Science.gov (United States)

    Müller-Staub, Maria

    2006-10-01

    The daily routine requires complex thinking processes of nurses, but clinical decision making and critical thinking are underestimated in nursing. A great demand for educational measures in clinical judgement related with the diagnostic process was found in nurses. The German literature hardly describes nursing diagnoses as clinical judgements about human reactions on health problems / life processes. Critical thinking is described as an intellectual, disciplined process of active conceptualisation, application and synthesis of information. It is gained through observation, experience, reflection and communication and leads thinking and action. Critical thinking influences the aspects of clinical decision making a) diagnostic judgement, b) therapeutic reasoning and c) ethical decision making. Human reactions are complex processes and in their course, human behavior is interpreted in the focus of health. Therefore, more attention should be given to the nursing diagnostic process. This article presents the theoretical framework of the paper "Clinical decision making: Fostering critical thinking in the nursing diagnostic process through case studies".

  2. Clinical decision support systems for patient safety: a focus group needs assessment with Korean ICU nurses.

    Science.gov (United States)

    Choi, Mona; Choi, Ran; Bae, Young-Ran; Lee, Sun-Mi

    2011-11-01

    An ICU is known as a data-rich environment, and information technology can improve the quality of care by utilizing stored clinical data and providing decision support effectively and in a timely manner to clinicians. The necessity of clinical decision support systems is emphasized now more than ever because patient safety and nursing-sensitive outcomes in the clinical setting have become a critical issue. The purpose of this study was to explore nursing-sensitive outcomes issues related to patient safety in critical care and to understand the types and contents of clinical decision support systems that nurses desire in a clinical practice setting. Focus group interviews were conducted with 37 nurses who worked in one university hospital system in Korea. Our findings are summarized into threats to patient safety, nursing-sensitive outcomes, and the types and contents of clinical decision support systems, which are categorized into the following groups: (1) reminders, notification, alert, and warning systems; (2) point-of-care guidelines; and (3) references for information/guidelines. Nurses consistently stated that clinical decision support systems can help improve nursing outcomes by applying standardized nursing care. Our study is expected to provide a practical suggestion for developing and designing a new clinical decision support system or for refining an existing one.

  3. User-centered design to improve clinical decision support in primary care.

    Science.gov (United States)

    Brunner, Julian; Chuang, Emmeline; Goldzweig, Caroline; Cain, Cindy L; Sugar, Catherine; Yano, Elizabeth M

    2017-08-01

    A growing literature has demonstrated the ability of user-centered design to make clinical decision support systems more effective and easier to use. However, studies of user-centered design have rarely examined more than a handful of sites at a time, and have frequently neglected the implementation climate and organizational resources that influence clinical decision support. The inclusion of such factors was identified by a systematic review as "the most important improvement that can be made in health IT evaluations." (1) Identify the prevalence of four user-centered design practices at United States Veterans Affairs (VA) primary care clinics and assess the perceived utility of clinical decision support at those clinics; (2) Evaluate the association between those user-centered design practices and the perceived utility of clinical decision support. We analyzed clinic-level survey data collected in 2006-2007 from 170 VA primary care clinics. We examined four user-centered design practices: 1) pilot testing, 2) provider satisfaction assessment, 3) formal usability assessment, and 4) analysis of impact on performance improvement. We used a regression model to evaluate the association between user-centered design practices and the perceived utility of clinical decision support, while accounting for other important factors at those clinics, including implementation climate, available resources, and structural characteristics. We also examined associations separately at community-based clinics and at hospital-based clinics. User-centered design practices for clinical decision support varied across clinics: 74% conducted pilot testing, 62% conducted provider satisfaction assessment, 36% conducted a formal usability assessment, and 79% conducted an analysis of impact on performance improvement. Overall perceived utility of clinical decision support was high, with a mean rating of 4.17 (±.67) out of 5 on a composite measure. "Analysis of impact on performance

  4. Uncertainty and objectivity in clinical decision making: a clinical case in emergency medicine.

    Science.gov (United States)

    Engebretsen, Eivind; Heggen, Kristin; Wieringa, Sietse; Greenhalgh, Trisha

    2016-12-01

    The evidence-based practice and evidence-based medicine (EBM) movements have promoted standardization through guideline development methodologies based on systematic reviews and meta-analyses of best available research. EBM has challenged clinicians to question their reliance on practical reasoning and clinical judgement. In this paper, we argue that the protagonists of EBM position their mission as reducing uncertainty through the use of standardized methods for knowledge evaluation and use. With this drive towards uniformity, standardization and control comes a suspicion towards intuition, creativity and uncertainty as integral parts of medical practice. We question the appropriateness of attempts to standardize professional practice through a discussion of the importance of uncertainty. Greenhalgh's taxonomy of uncertainty is used to inform an analysis of the clinical reasoning occurring in a potentially life threatening emergency situation with a young patient. The case analysis is further developed by the use of the Canadian philosopher Bernard Lonergan's theory about understanding and objective knowing. According to Lonergan it is not by getting rid of or even by reducing uncertainty, but by attending systematically to it and by relating to it in a self-conscious way, that objective knowledge can be obtained. The paper concludes that uncertainty is not a regrettable and unavoidable aspect of decision making but a productive component of clinical reasoning.

  5. Clinical data warehousing for evidence based decision making.

    Science.gov (United States)

    Narra, Lekha; Sahama, Tony; Stapleton, Peta

    2015-01-01

    Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.

  6. FDUMedSearch at TREC 2015 Clinical Decision Support Track

    Science.gov (United States)

    2015-11-20

    expansion using Medical Subject Headings ( MeSH ), pseudo relevance feedback and classification were used to enhance the retrieval performance. We...Decision Support track 2015 (CDS2015) focuses on linking PubMed Central (PMC) articles to the medical cases for patient care. There are 30 topics...a doctor to help us to extract important keywords in the description of each topic in manual setting. 2.3 MeSH Terms Query Expansion MeSH has

  7. Artificial Intelligence Framework for Simulating Clinical Decision-Making: A Markov Decision Process Approach

    OpenAIRE

    Bennett, Casey C.; Hauser, Kris

    2013-01-01

    In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This serves two potential functions: 1) a simulation environment for expl...

  8. An Examination of Accelerated and Basic Baccalaureate Nursing Students' Perceptions of Clinical Decision Making

    Science.gov (United States)

    Krumwiede, Kelly A.

    2010-01-01

    Developing decision-making skills is essential in education in order to be a competent nurse. The purpose of this study was to examine and compare the perceptions of clinical decision-making skills of students enrolled in accelerated and basic baccalaureate nursing programs. A comparative descriptive research design was used for this study.…

  9. Complexity perspectives on clinical decision making in an intensive care unit

    NARCIS (Netherlands)

    De Bock, Ben A.; Willems, Dick L.; Weinstein, Henry C.

    2017-01-01

    How to clarify the implications of complexity thinking for decision making in the intensive care unit (ICU)? Retrospective qualitative empirical research. Practitioners in an ICU were interviewed on how their decisions were made regarding a particular patient in a difficult, clinical situation.

  10. mHealth for Clinical Decision-Making in Sub-Saharan Africa : A Scoping Review

    NARCIS (Netherlands)

    Adepoju, Ibukun-Oluwa Omolade; Albersen, Bregje Joanna Antonia; De Brouwere, Vincent; van Roosmalen, Jos; Zweekhorst, M.B.M.

    2017-01-01

    BACKGROUND: In a bid to deliver quality health services in resource-poor settings, mobile health (mHealth) is increasingly being adopted. The role of mHealth in facilitating evidence-based clinical decision-making through data collection, decision algorithms, and evidence-based guidelines, for

  11. Factors Predicting Oncology Care Providers' Behavioral Intention to Adopt Clinical Decision Support Systems

    Science.gov (United States)

    Wolfenden, Andrew

    2012-01-01

    The purpose of this quantitative correlation study was to examine the predictors of user behavioral intention on the decision of oncology care providers to adopt or reject the clinical decision support system. The Unified Theory of Acceptance and Use of Technology (UTAUT) formed the foundation of the research model and survey instrument. The…

  12. Can computerized clinical decision support systems improve diabetes management? A systematic review and meta-analysis.

    Science.gov (United States)

    Jeffery, R; Iserman, E; Haynes, R B

    2013-06-01

    To systematically review randomized trials that assessed the effects of computerized clinical decision support systems in ambulatory diabetes management compared with a non-computerized clinical decision support system control. We included all diabetes trials from a comprehensive computerized clinical decision support system overview completed in January 2010, and searched EMBASE, MEDLINE, INSPEC/COMPENDEX and Evidence-Based Medicine Reviews (EBMR) from January 2010 to April 2012. Reference lists of related reviews, included articles and Clinicaltrials.gov were also searched. Randomized controlled trials of patients with diabetes in ambulatory care settings comparing a computerized clinical decision support system intervention with a non-computerized clinical decision support system control, measuring either a process of care or a patient outcome, were included. Screening of studies, data extraction, risk of bias and quality of evidence assessments were carried out independently by two reviewers, and discrepancies were resolved through consensus or third-party arbitration. Authors were contacted for any missing data. Fifteen trials were included (13 from the previous review and two from the current search). Only one study was at low risk of bias, while the others were of moderate to high risk of bias because of methodological limitations. HbA1c (3 months' follow-up), quality of life and hospitalization (12 months' follow-up) were pooled and all favoured the computerized clinical decision support systems over the control, although none were statistically significant. Triglycerides and practitioner performance tended to favour computerized clinical decision support systems although results were too heterogeneous to pool. Computerized clinical decision support systems in diabetes management may marginally improve clinical outcomes, but confidence in the evidence is low because of risk of bias, inconsistency and imprecision. © 2012 The Authors. Diabetic Medicine

  13. Lessons learned from implementing service-oriented clinical decision support at four sites: A qualitative study.

    Science.gov (United States)

    Wright, Adam; Sittig, Dean F; Ash, Joan S; Erickson, Jessica L; Hickman, Trang T; Paterno, Marilyn; Gebhardt, Eric; McMullen, Carmit; Tsurikova, Ruslana; Dixon, Brian E; Fraser, Greg; Simonaitis, Linas; Sonnenberg, Frank A; Middleton, Blackford

    2015-11-01

    To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  14. Need for a clinical decision rule for the management of pharyngitis ...

    African Journals Online (AJOL)

    While it is desirable to do throat culture to guide the physician's management of each case, the required laboratory skill is unavailable in most clinical settings in Nigeria. A clinical decision rule (CDR) which is a clinical tool that helps guide physicians in the management of conditions such as pharyngitis, have been shown to ...

  15. Building bridges between perceptual and economic decision-making: neural and computational mechanisms

    Directory of Open Access Journals (Sweden)

    Christopher eSummerfield

    2012-05-01

    Full Text Available Investigation into the neural and computational bases of decision-making has proceeded in two parallel but distinct streams. Perceptual decision making (PDM is concerned with how observers detect, discriminate and categorise noisy sensory information. Economic decision making (EDM explores how options are selected on the basis of their reinforcement history. Traditionally, the subfields of PDM and EDM have employed different paradigms, proposed different mechanistic models, explored different brain regions, disagreed about whether decisions approach optimality. Nevertheless, we argue that there is a common framework for understanding decisions made in both domains, under which an agent has to combine sensory information (what is the stimulus with value information (what is it worth. We review computational models of the decision process typically used in PDM, based around the idea that decisions involve a serial integration of evidence, and assess their applicability to decisions between good and gambles. Subsequently, we consider the contribution of three key brain regions – the parietal cortex, the basal ganglia, and the orbitofrontal cortex – to perceptual and economic decision-making, with a focus on the mechanisms by which sensory and reward information are integrated during choice. We find that although the parietal cortex is often implicated in the integration of sensory evidence, there is evidence for its role in encoding the expected value of a decision. Similarly, although much research has emphasised the role of the striatum and orbitofrontal cortex in value-guided choices, they may play an important role in categorisation of perceptual information. In conclusion, we consider how findings from the two fields might be brought together, in order to move towards a general framework for understanding decision-making in humans and other primates.

  16. Sexuality Education: Building an Evidence- and Rights-Based Approach to Healthy Decision-Making

    Science.gov (United States)

    Bridges, Emily; Hauser, Debra

    2014-01-01

    As they grow up, young people face important decisions about relationships, sexuality, and sexual behavior. The decisions they make can impact their health and well-being for the rest of their lives. Young people have the right to lead healthy lives, and society has the responsibility to prepare youth by providing them with comprehensive sexual…

  17. Decision rules and associated sample size planning for regional approval utilizing multiregional clinical trials.

    Science.gov (United States)

    Chen, Xiaoyuan; Lu, Nelson; Nair, Rajesh; Xu, Yunling; Kang, Cailian; Huang, Qin; Li, Ning; Chen, Hongzhuan

    2012-09-01

    Multiregional clinical trials provide the potential to make safe and effective medical products simultaneously available to patients globally. As regulatory decisions are always made in a local context, this poses huge regulatory challenges. In this article we propose two conditional decision rules that can be used for medical product approval by local regulatory agencies based on the results of a multiregional clinical trial. We also illustrate sample size planning for such trials.

  18. Helping Health Care Providers and Clinical Scientists Understand Apparently Irrational Policy Decisions.

    Science.gov (United States)

    Demeter, Sandor J

    2016-12-21

    Health care providers (HCP) and clinical scientists (CS) are generally most comfortable using evidence-based rational decision-making models. They become very frustrated when policymakers make decisions that, on the surface, seem irrational and unreasonable. However, such decisions usually make sense when analysed properly. The goal of this paper to provide a basic theoretical understanding of major policy models, to illustrate which models are most prevalent in publicly funded health care systems, and to propose a policy analysis framework to better understand the elements that drive policy decision-making. The proposed policy framework will also assist HCP and CS achieve greater success with their own proposals.

  19. Clinical comparison of various esthetic restorative options for coronal build-up of primary anterior teeth

    National Research Council Canada - National Science Library

    Duhan, Himanshu; Pandit, Inder Kumar; Srivastava, Nikhil; Gugnani, Neeraj; Gupta, Monika; Kochhar, Gulsheen Kaur

    2015-01-01

    This study was designed to compare the clinical performance of composite, strip crowns, biological restoration, and composite with stainless steel band when used for the coronal build-up of anterior teeth...

  20. Building trust and diversity in patient-centered oncology clinical trials: An integrated model.

    Science.gov (United States)

    Hurd, Thelma C; Kaplan, Charles D; Cook, Elise D; Chilton, Janice A; Lytton, Jay S; Hawk, Ernest T; Jones, Lovell A

    2017-04-01

    Trust is the cornerstone of clinical trial recruitment and retention. Efforts to decrease barriers and increase clinical trial participation among diverse populations have yielded modest results. There is an urgent need to better understand the complex interactions between trust and clinical trial participation. The process of trust-building has been a focus of intense research in the business community. Yet, little has been published about trust in oncology clinical trials or the process of building trust in clinical trials. Both clinical trials and business share common dimensions. Business strategies for building trust may be transferable to the clinical trial setting. This study was conducted to understand and utilize contemporary thinking about building trust to develop an Integrated Model of Trust that incorporates both clinical and business perspectives. A key word-directed literature search of the PubMed, Medline, Cochrane, and Google Search databases for entries dated between 1 January 1985 and 1 September 2015 was conducted to obtain information from which to develop an Integrated Model of Trust. Successful trial participation requires both participants and clinical trial team members to build distinctly different types of interpersonal trust to effect recruitment and retention. They are built under conditions of significant emotional stress and time constraints among people who do not know each other and have never worked together before. Swift Trust and Traditional Trust are sequentially built during the clinical trial process. Swift trust operates during the recruitment and very early active treatment phases of the clinical trial process. Traditional trust is built over time and operates during the active treatment and surveillance stages of clinical trials. The Psychological Contract frames the participants' and clinical trial team members' interpersonal trust relationship. The "terms" of interpersonal trust are negotiated through the psychological

  1. Selecting the Optimal Building System Using Multiple Criteria Decision Making Emphasising on Three Methods of TOPSIS , SAW, AHP

    Directory of Open Access Journals (Sweden)

    Alireza Rezaiean

    2015-09-01

    Full Text Available Nowadays, various factors complicate the decision making process and the need to make decisions that consider all the factors in question, they are more than ever before. The internal and external researchers, have shown interest in the multi-criteria decision making. In our study, the method includes a multi-criteria decision making method such as Analytical Hierarchy Process, Simple additive weighting and TOPSIS Technique for order-prefrence by similarity to ideal solution(  to solve the selection problem of building efficient systems we have used. Systems that have been evaluated in this issue include: Lightweight Steel Frames, Insulating concrete formwork, 3D-PANEL and Prefabricated reinforced concrete systems. Required data using the questionnaire sample (n = 150 were examined. Questionnaires among the mass of experts, academic institutions and conferences were distributed. According to the research results, using different methods of decision making, the results will yield fairly similar, so that all three methods, Prefabricated reinforced concrete systems in the first place, and the Lightweight Steel Frames system was in the Second place. The Prefabricated reinforced concrete systems, in terms of administrative and economic criterias, in the first place, and the system Lightweight Steel Frames, ranked first in terms of environmental criteria accounted for.

  2. Accuracy of intuition in clinical decision-making among novice clinicians.

    Science.gov (United States)

    Price, Amanda; Zulkosky, Kristen; White, Krista; Pretz, Jean

    2017-05-01

    To assess the reliance on intuitive and analytical approaches during clinical decision-making among novice clinicians and whether that reliance is associated with accurate decision-making. Nurse educators and managers tend to emphasize analysis over intuition during clinical decision-making though nurses typically report some reliance on intuition in their practice. We hypothesized that under certain conditions, reliance on intuition would support accurate decision-making, even among novices. This study utilized an experimental design with clinical complication (familiar vs. novel) and decision phase (cue acquisition, diagnosis and action) as within-subjects' factors, and simulation role (observer, family, auxiliary nurse and primary nurse) as between-subjects' factor. We examined clinical decision-making accuracy among final semester pre-licensure nursing students in a simulation experience. Students recorded their reasoning about emerging clinical complications with their patient during two distinct points in the simulation; one point involved a familiar complication and the other a relatively novel complication. All data were collected during Spring 2015. Although most participants relied more heavily on analysis than on intuition, use of intuition during the familiar complication was associated with more accurate decision-making, particularly in guiding attention to relevant cues. With the novel complication, use of intuition appeared to hamper decision-making, particularly for those in an observer role. Novice clinicians should be supported by educators and nurse managers to note when their intuitions are likely to be valid. Our findings emphasize the integrated nature of intuition and analysis in clinical decision-making. © 2016 John Wiley & Sons Ltd.

  3. Development and evaluation of learning module on clinical decision-making in Prosthodontics.

    Science.gov (United States)

    Deshpande, Saee; Lambade, Dipti; Chahande, Jayashree

    2015-01-01

    Best practice strategies for helping students learn the reasoning skills of problem solving and critical thinking (CT) remain a source of conjecture, particularly with regard to CT. The dental education literature is fundamentally devoid of research on the cognitive components of clinical decision-making. This study was aimed to develop and evaluate the impact of blended learning module on clinical decision-making skills of dental graduates for planning prosthodontics rehabilitation. An interactive teaching module consisting of didactic lectures on clinical decision-making and a computer-assisted case-based treatment planning software was developed Its impact on cognitive knowledge gain in clinical decision-making was evaluated using an assessment involving problem-based multiple choice questions and paper-based case scenarios. Mean test scores were: Pretest (17 ± 1), posttest 1 (21 ± 2) and posttest 2 (43 ± 3). Comparison of mean scores was done with one-way ANOVA test. There was overall significant difference in between mean scores at all the three points (P posttest 1 > pretest. Blended teaching methods employing didactic lectures on the clinical decision-making as well as computer assisted case-based learning can be used to improve quality of clinical decision-making in prosthodontic rehabilitation for dental graduates.

  4. Unsatisfactory colposcopy: clinical decision-making in conditions of uncertainty

    National Research Council Canada - National Science Library

    Kristyn M Manley; Rebecca A Simms; Sarah Platt; Amit Patel; Rachna Bahl

    2017-01-01

    Background Unsatisfactory colposcopy, where the cells of interest are not visible in women with a positive cervical screening test, is a common area of clinical uncertainty due to the lack of clear evidence and guidance. Colposcopists...

  5. Physician understanding and application of surrogate decision-making laws in clinical practice.

    Science.gov (United States)

    Comer, Amber Rose; Gaffney, Margaret; Stone, Cynthia L; Torke, Alexia

    2017-01-01

    Although state surrogate laws are the most common way surrogate decision makers are identified, no studies have been conducted to determine physician understanding of these laws or how these laws are utilized during clinical practice. The purpose of this study is to better understand how surrogate decision-making laws function in practice. A cross-sectional survey of 412 physicians working in Indiana hospitals was conducted between November 2014 and January 2015 to determine physicians' knowledge of Indiana's surrogate decision-making law and physicians' approaches to hypothetical cases using the law in clinical practice. Fewer than half of physicians (48%) were able to correctly identify all legally allowable surrogate decision makers. Of those physicians who knew the law, nearly all of them (98%) indicated that they would violate the law during clinical practice by allowing nonlegal surrogates such as grandchildren to make medical decisions. A majority of physicians endorse relying on surrogates who have strong ties to the patient but are not legally allowable in Indiana. It is possible that these decisions reflect sound ethical reasoning even though they are illegal. Due to the narrow construction of some state surrogate decision laws, physicians may be placed in the position where they must either choose to follow medical ethical principles or the law. To alleviate these issues, state surrogate decision laws need to be amended to include a broader list of surrogates, such as extended family and close friends.

  6. Features of computerized clinical decision support systems supportive of nursing practice: a literature review.

    Science.gov (United States)

    Lee, Seonah

    2013-10-01

    This study aimed to organize the system features of decision support technologies targeted at nursing practice into assessment, problem identification, care plans, implementation, and outcome evaluation. It also aimed to identify the range of the five stage-related sequential decision supports that computerized clinical decision support systems provided. MEDLINE, CINAHL, and EMBASE were searched. A total of 27 studies were reviewed. The system features collected represented the characteristics of each category from patient assessment to outcome evaluation. Several features were common across the reviewed systems. For the sequential decision support, all of the reviewed systems provided decision support in sequence for patient assessment and care plans. Fewer than half of the systems included problem identification. There were only three systems operating in an implementation stage and four systems in outcome evaluation. Consequently, the key steps for sequential decision support functions were initial patient assessment, problem identification, care plan, and outcome evaluation. Providing decision support in such a full scope will effectively help nurses' clinical decision making. By organizing the system features, a comprehensive picture of nursing practice-oriented computerized decision support systems was obtained; however, the development of a guideline for better systems should go beyond the scope of a literature review.

  7. The DEVELOP National Program: Building Dual Capacity in Decision Makers and Young Professionals Through NASA Earth Observations

    Science.gov (United States)

    Childs, L. M.; Rogers, L.; Favors, J.; Ruiz, M.

    2012-12-01

    Through the years, NASA has played a distinct/important/vital role in advancing Earth System Science to meet the challenges of environmental management and policy decision making. Within NASA's Earth Science Division's Applied Sciences' Program, the DEVELOP National Program seeks to extend NASA Earth Science for societal benefit. DEVELOP is a capacity building program providing young professionals and students the opportunity to utilize NASA Earth observations and model output to demonstrate practical applications of those resources to society. Under the guidance of science advisors, DEVELOP teams work in alignment with local, regional, national and international partner organizations to identify the widest array of practical uses for NASA data to enhance related management decisions. The program's structure facilitates a two-fold approach to capacity building by fostering an environment of scientific and professional development opportunities for young professionals and students, while also providing end-user organizations enhanced management and decision making tools for issues impacting their communities. With the competitive nature and growing societal role of science and technology in today's global workplace, DEVELOP is building capacity in the next generation of scientists and leaders by fostering a learning and growing environment where young professionals possess an increased understanding of teamwork, personal development, and scientific/professional development and NASA's Earth Observation System. DEVELOP young professionals are partnered with end user organizations to conduct 10 week feasibility studies that demonstrate the use of NASA Earth science data for enhanced decision making. As a result of the partnership, end user organizations are introduced to NASA Earth Science technologies and capabilities, new methods to augment current practices, hands-on training with practical applications of remote sensing and NASA Earth science, improved remote

  8. A Decision Making Tool for a Comprehensive Evaluation of Building Retrofitting Actions at the Regional Scale

    Directory of Open Access Journals (Sweden)

    Rossano Albatici

    2016-09-01

    Full Text Available Buildings in Europe account for 40% of total primary energy consumption and 36% of CO2 emissions. Nearly one-half of the building stock was built before modern energy efficiency standards and need urgent renovation. Urban retrofitting has emerged as a crucial factor for bringing about a radical change, the new construction rate being lower than 1%. Nevertheless, an accepted and consolidated methodology for refurbishing the existing housing stock is still lacking. The study presents an operating methodology for the optimization of the retrofitting process, based on energy efficiency and cost-effectiveness, as well as users’ comfort, in the building asset of ITEA SpA, the social housing institute for the Province of Trento (Italy, which manages more than 600 buildings. The research consists of the following stages: (1 definition of building classes, similar in age, dimension, typology, construction system and location; (2 analysis of plant systems and recognition of cases significant for classifying buildings in term of energy class; (3 identification of possible improvements and related cost-benefits; and (4 extension of the results to the whole building class. A tool is here proposed, intended for use by ITEA in order to set medium- and long-term plans. The tool does not consider only the effective sustainability of the controlling body intervention but also the final users’ full satisfaction.

  9. Complexity perspectives on clinical decision making in an intensive care unit.

    Science.gov (United States)

    de Bock, Ben A; Willems, Dick L; Weinstein, Henry C

    2017-08-01

    How to clarify the implications of complexity thinking for decision making in the intensive care unit (ICU)? Retrospective qualitative empirical research. Practitioners in an ICU were interviewed on how their decisions were made regarding a particular patient in a difficult, clinical situation. Transcriptions of these interviews were coded and retrieved in Maxqda, a software program. Assisted by complexity thinking, researchers focused on the decision-making process and the shift from analytic approaches to complex approaches. Originally, practitioners took their decisions with negligible transdisciplinary interactivity, drawing on analytical knowledge. Later on, they shifted to transdisciplinary practices, paying attention to more participation in their decision-making processes within their complex environment. Complexity thinking demonstrates that this is a better model towards understanding transdisciplinary decision making then most analytical methodologies. © 2017 John Wiley & Sons, Ltd.

  10. An Agent-Based Framework for Building Decision Support System in Supply Chain Management

    Science.gov (United States)

    Kazemi, A.; Fazel Zarandi, M. H.

    In this study, two scenarios are presented for solving Production-Distribution Panning Problem (PDPP) in a Decision Support System (DSS) framework. In the first scenario, a Traditional Decision Support System (TDSS) is presented for PDPP and a Genetic Algorithm (GA) is used for solving it. In the second scenario, a Multi-agent Decision Support System (MADSS) is considered for PDPP and three algorithms are used for solving it: Genetic Algorithm (GA), Tabu Search (TS) and Simulated Annealing (SA). Then an algorithm is suggested by using multi-agent system and A Teams concept. The obtained results reveal that the use of MADSS delivers better solutions to us.

  11. Building the graph of medicine from millions of clinical narratives.

    Science.gov (United States)

    Finlayson, Samuel G; LePendu, Paea; Shah, Nigam H

    2014-01-01

    Electronic health records (EHR) represent a rich and relatively untapped resource for characterizing the true nature of clinical practice and for quantifying the degree of inter-relatedness of medical entities such as drugs, diseases, procedures and devices. We provide a unique set of co-occurrence matrices, quantifying the pairwise mentions of 3 million terms mapped onto 1 million clinical concepts, calculated from the raw text of 20 million clinical notes spanning 19 years of data. Co-frequencies were computed by means of a parallelized annotation, hashing, and counting pipeline that was applied over clinical notes from Stanford Hospitals and Clinics. The co-occurrence matrix quantifies the relatedness among medical concepts which can serve as the basis for many statistical tests, and can be used to directly compute Bayesian conditional probabilities, association rules, as well as a range of test statistics such as relative risks and odds ratios. This dataset can be leveraged to quantitatively assess comorbidity, drug-drug, and drug-disease patterns for a range of clinical, epidemiological, and financial applications.

  12. Patient-Centered Decision Support: Formative Usability Evaluation of Integrated Clinical Decision Support With a Patient Decision Aid for Minor Head Injury in the Emergency Department.

    Science.gov (United States)

    Melnick, Edward R; Hess, Erik P; Guo, George; Breslin, Maggie; Lopez, Kevin; Pavlo, Anthony J; Abujarad, Fuad; Powsner, Seth M; Post, Lori A

    2017-05-19

    The Canadian Computed Tomography (CT) Head Rule, a clinical decision rule designed to safely reduce imaging in minor head injury, has been rigorously validated and implemented, and yet expected decreases in CT were unsuccessful. Recent work has identified empathic care as a key component in decreasing CT overuse. Health information technology can hinder the clinician-patient relationship. Patient-centered decision tools to support the clinician-patient relationship are needed to promote evidence-based decisions. Our objective is to formatively evaluate an electronic tool that not only helps clinicians at the bedside to determine the need for CT use based on the Canadian CT Head Rule but also promotes evidence-based conversations between patients and clinicians regarding patient-specific risk and patients' specific concerns. User-centered design with practice-based and participatory decision aid development was used to design, develop, and evaluate patient-centered decision support regarding CT use in minor head injury in the emergency department. User experience and user interface (UX/UI) development involved successive iterations with incremental refinement in 4 phases: (1) initial prototype development, (2) usability assessment, (3) field testing, and (4) beta testing. This qualitative approach involved input from patients, emergency care clinicians, health services researchers, designers, and clinical informaticists at every stage. The Concussion or Brain Bleed app is the product of 16 successive iterative revisions in accordance with UX/UI industry design standards. This useful and usable final product integrates clinical decision support with a patient decision aid. It promotes shared use by emergency clinicians and patients at the point of care within the emergency department context. This tablet computer app facilitates evidence-based conversations regarding CT in minor head injury. It is adaptable to individual clinician practice styles. The resultant tool

  13. A study to explore if dentists' anxiety affects their clinical decision-making.

    Science.gov (United States)

    Chipchase, S Y; Chapman, H R; Bretherton, R

    2017-02-24

    Aims To develop a measure of dentists' anxiety in clinical situations; to establish if dentists' anxiety in clinical situations affected their self-reported clinical decision-making; to establish if occupational stress, as demonstrated by burnout, is associated with anxiety in clinical situations and clinical decision-making; and to explore the relationship between decision-making style and the clinical decisions which are influenced by anxiety.Design Cross-sectional study.Setting Primary Dental Care.Subjects and methods A questionnaire battery [Maslach Burnout Inventory, measuring burnout; Melbourne Decision Making Questionnaire, measuring decision-making style; Dealing with Uncertainty Questionnaire (DUQ), measuring coping with diagnostic uncertainty; and a newly designed Dentists' Anxieties in Clinical Situations Scale, measuring dentists' anxiety (DACSS-R) and change of treatment (DACSS-C)] was distributed to dentists practicing in Nottinghamshire and Lincolnshire. Demographic data were collected and dentists gave examples of anxiety-provoking situations and their responses to them.Main outcome measure Respondents' self-reported anxiety in various clinical situations on a 11-point Likert Scale (DACSS-R) and self-reported changes in clinical procedures (Yes/No; DACSS-C). The DACSS was validated using multiple t-tests and a principal component analysis. Differences in DACSS-R ratings and burnout, decision-making and dealing with uncertainty were explored using Pearson correlations and multiple regression analysis. Qualitative data was subject to a thematic analysis.Results The DACSS-R revealed a four-factor structure and had high internal reliability (Cronbach's α = 0.94). Those with higher DACSS-R scores of anxiety were more likely to report changes in clinical procedures (DACSS-C scores). DACSS-R scores were associated with decision-making self-esteem and style as measured by the MDMQ and all burnout subscales, though not with scores on the DUQ scale

  14. An integrated, ethically driven environmental model of clinical decision making in emergency settings.

    Science.gov (United States)

    Wolf, Lisa

    2013-02-01

    To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.

  15. Clinical decision-making described by Swedish prehospital emergency care nurse students - An exploratory study.

    Science.gov (United States)

    Nilsson, Tomas; Lindström, Veronica

    2016-07-01

    The purpose of this study was to explore the PECN students' clinical decision-making during a seven-week clinical rotation in the ambulance services. Developing expertise in prehospital emergency care practices requires both theoretical and empirical learning. A prehospital emergency care nurse (PECN) is a Registered Nurse (RN) with one year of additional training in emergency care. There has been little investigation of how PECN students describe their decision-making during a clinical rotation. A qualitative study design was used, and 12 logbooks written by the Swedish PECN students were analysed using content analysis. The students wrote about 997 patient encounters - ambulance assignments during their clinical rotation. Four themes emerged as crucial for the students' decision-making: knowing the patient, the context-situation awareness in the ambulance service, collaboration, and evaluation. Based on the themes, students made decisions on how to respond to patients' illnesses. The PECN students used several variables in their decision-making. The decision- making was an on-going process during the whole ambulance assignment. The university has the responsibility to guide the students during their transition from an RN to a PECN. The findings of the study can support the educators and clinical supervisors in developing the programme of study for becoming a PECN. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. A Decision Support Tool for Sustainable Land Use, Transportation, Buildings/Infrastructure, and Materials Management

    Science.gov (United States)

    One issue for community groups, local and regional planners, and politicians, is that they require relevant information to develop programs and initiatives for incorporating sustainability principles into their physical infrastructure, operations, and decision-making processes. T...

  17. Building a maintenance policy through a multi-criterion decision-making model

    Science.gov (United States)

    Faghihinia, Elahe; Mollaverdi, Naser

    2012-08-01

    A major competitive advantage of production and service systems is establishing a proper maintenance policy. Therefore, maintenance managers should make maintenance decisions that best fit their systems. Multi-criterion decision-making methods can take into account a number of aspects associated with the competitiveness factors of a system. This paper presents a multi-criterion decision-aided maintenance model with three criteria that have more influence on decision making: reliability, maintenance cost, and maintenance downtime. The Bayesian approach has been applied to confront maintenance failure data shortage. Therefore, the model seeks to make the best compromise between these three criteria and establish replacement intervals using Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II), integrating the Bayesian approach with regard to the preference of the decision maker to the problem. Finally, using a numerical application, the model has been illustrated, and for a visual realization and an illustrative sensitivity analysis, PROMETHEE GAIA (the visual interactive module) has been used. Use of PROMETHEE II and PROMETHEE GAIA has been made with Decision Lab software. A sensitivity analysis has been made to verify the robustness of certain parameters of the model.

  18. Fuzzy decision approach for selection of most suitable construction method of Green Buildings

    Directory of Open Access Journals (Sweden)

    Sunita Bansal

    2017-06-01

    Full Text Available A big challenge in sustainable projects is selection of appropriate construction method and is considered to be the decisive factor for its success. Many environment friendly prefabricated elements are entering into the market at an increasing pace. This has increased the workload and inquisitiveness of the stakeholders who will need information about their environmental, technical and esthetic aspects. The use of prefabrication in sustainable construction is advantageous but appropriate decision criteria and their weightage for applicability assessments for a project from every stakeholder’s perspective is found to be deficient. Decisions to use prefabricated elements are still largely based on anecdotal evidence or cost-based evaluation rather than holistic sustainable performance. But authenticated information is seldom available and suitability within the project requirements is always debatable. Environmental decisions, being closely coupled with society’s built-in uncertainties and risks, are uncertain since ecological systems as well as social systems change in the future. Thus the selection of a suitable construction method has been perceived as a multi-criteria decision-making problem highly intensive in knowledge with partial information and uncertainty. This knowledge or perception base from the minds of experts has to be collected and processed for a decision. Fuzzy synthetic evaluation method using analytic hierarchy process by Saaty has been adopted to provide an analytical tool to evaluate the applicability of prefabricated or on-site construction method.

  19. A fuzzy decision making system for building damage map creation using high resolution satellite imagery

    Science.gov (United States)

    Rastiveis, H.; Samadzadegan, F.; Reinartz, P.

    2013-02-01

    Recent studies have shown high resolution satellite imagery to be a powerful data source for post-earthquake damage assessment of buildings. Manual interpretation of these images, while being a reliable method for finding damaged buildings, is a subjective and time-consuming endeavor, rendering it unviable at times of emergency. The present research, proposes a new state-of-the-art method for automatic damage assessment of buildings using high resolution satellite imagery. In this method, at the first step a set of pre-processing algorithms are performed on the images. Then, extracting a candidate building from both pre- and post-event images, the intact roof part after an earthquake is found. Afterwards, by considering the shape and other structural properties of this roof part with its pre-event condition in a fuzzy inference system, the rate of damage for each candidate building is estimated. The results obtained from evaluation of this algorithm using QuickBird images of the December 2003 Bam, Iran, earthquake prove the ability of this method for post-earthquake damage assessment of buildings.

  20. New design decisions of prefabricated girderless floors of multi-storeyed buildings

    Directory of Open Access Journals (Sweden)

    Storozhenko Leonid

    2017-01-01

    Full Text Available Nowadays new trends are clearly manifested in building structures for buildings of various appointment and specific characteristics of their long-term operation. The priority in the construction industry takes place construction of high-rise residential and office buildings. Numerous studies in Ukraine and abroad proved that the construction of the frame with girderless floor provides resistance to both vertical and horizontal loads. It makes it possible to improve the traditional methods of frame building design. However, in the monolithic building of girderless floors there are a number of unresolved problems of structural, technological and organizational character. The authors have developed the construction of prefabricate reinforced concrete girderless floor that includes column drops, intercolumn slabs, span slabs. Column drops have bevelled lateral edges around the perimeter, forming a platform to support intercolumn slabs. Mounting of slabs occurs in the definite order. In the capacity of the columns it can be used as traditional prefabricated reinforced concrete structures as concrete filled steel tube ones. The advantage is that, comparing to modern reinforced concrete girderless floor, additional supporting equipment is not used during mounting slabs and scaffolding. The proposed girderless floors can be recommended for use in the construction of residential and public buildings for various purposes.

  1. The impact of an electronic clinical decision support for pulmonary ...

    African Journals Online (AJOL)

    1 Division of Radiodiagnosis, Department of Medical Imaging and Clinical Oncology, Faculty of Medicine and Health Sciences,. Stellenbosch ... 3, 82.6% v. 69.3%; p=0.015) During phases 2 and 3, no CTPAs were requested for patients with a modified Wells score of ≤4 ..... Snope JD, et al. Safety of excluding acute.

  2. [Knowledge management system for laboratory work and clinical decision support].

    Science.gov (United States)

    Inada, Masanori; Sato, Mayumi; Yoneyama, Akiko

    2011-05-01

    This paper discusses a knowledge management system for clinical laboratories. In the clinical laboratory of Toranomon Hospital, we receive about 20 questions relevant to laboratory tests per day from medical doctors or co-medical staff. These questions mostly involve the essence to appropriately accomplish laboratory tests. We have to answer them carefully and suitably because an incorrect answer may cause a medical accident. Up to now, no method has been in place to achieve a rapid response and standardized answers. For this reason, the laboratory staff have responded to various questions based on their individual knowledge. We began to develop a knowledge management system to promote the knowledge of staff working for the laboratory. This system is a type of knowledge base for assisting the work, such as inquiry management, laboratory consultation, process management, and clinical support. It consists of several functions: guiding laboratory test information, managing inquiries from medical staff, reporting results of patient consultation, distributing laboratory staffs notes, and recording guidelines for laboratory medicine. The laboratory test information guide has 2,000 records of medical test information registered in the database with flexible retrieval. The inquiry management tool provides a methos to record all questions, answer easily, and retrieve cases. It helps staff to respond appropriately in a short period of time. The consulting report system treats patients' claims regarding medical tests. The laboratory staffs notes enter a file management system so they can be accessed to aid in clinical support. Knowledge sharing using this function can achieve the transition from individual to organizational learning. Storing guidelines for laboratory medicine will support EBM. Finally, it is expected that this system will support intellectual activity concerning laboratory work and contribute to the practice of knowledge management for clinical work support.

  3. External validation of clinical decision rules for children with wrist trauma.

    Science.gov (United States)

    Mulders, Marjolein A M; Walenkamp, Monique M J; Dubois, Bente F H; Slaar, Annelie; Goslings, J Carel; Schep, Niels W L

    2017-05-01

    Clinical decision rules help to avoid potentially unnecessary radiographs of the wrist, reduce waiting times and save costs. The primary aim of this study was to provide an overview of all existing non-validated clinical decision rules for wrist trauma in children and to externally validate these rules in a different cohort of patients. Secondarily, we aimed to compare the performance of these rules with the validated Amsterdam Pediatric Wrist Rules. We included all studies that proposed a clinical prediction or decision rule in children presenting at the emergency department with acute wrist trauma. We performed external validation within a cohort of 379 children. We also calculated the sensitivity, specificity, negative predictive value and positive predictive value of each decision rule. We included three clinical decision rules. The sensitivity and specificity of all clinical decision rules after external validation were between 94% and 99%, and 11% and 26%, respectively. After external validation 7% to 17% less radiographs would be ordered and 1.4% to 5.7% of all fractures would be missed. Compared to the Amsterdam Pediatric Wrist Rules only one of the three other rules had a higher sensitivity; however both the specificity and the reduction in requested radiographs were lower in the other three rules. The sensitivity of the three non-validated clinical decision rules is high. However the specificity and the reduction in number of requested radiographs are low. In contrast, the validated Amsterdam Pediatric Wrist Rules has an acceptable sensitivity and the greatest reduction in radiographs, at 22%, without missing any clinically relevant fractures.

  4. Clinical decision-making and therapeutic approaches in osteopathy - a qualitative grounded theory study.

    Science.gov (United States)

    Thomson, Oliver P; Petty, Nicola J; Moore, Ann P

    2014-02-01

    There is limited understanding of how osteopaths make decisions in relation to clinical practice. The aim of this research was to construct an explanatory theory of the clinical decision-making and therapeutic approaches of experienced osteopaths in the UK. Twelve UK registered osteopaths participated in this constructivist grounded theory qualitative study. Purposive and theoretical sampling was used to select participants. Data was collected using semi-structured interviews which were audio-recorded and transcribed. As the study approached theoretical sufficiency, participants were observed and video-recorded during a patient appointment, which was followed by a video-prompted interview. Constant comparative analysis was used to analyse and code data. Data analysis resulted in the construction of three qualitatively different therapeutic approaches which characterised participants and their clinical practice, termed; Treater, Communicator and Educator. Participants' therapeutic approach influenced their approach to clinical decision-making, the level of patient involvement, their interaction with patients, and therapeutic goals. Participants' overall conception of practice lay on a continuum ranging from technical rationality to professional artistry, and contributed to their therapeutic approach. A range of factors were identified which influenced participants' conception of practice. The findings indicate that there is variation in osteopaths' therapeutic approaches to practice and clinical decision-making, which are influenced by their overall conception of practice. This study provides the first explanatory theory of the clinical decision-making and therapeutic approaches of osteopaths. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. Barriers for Hospital-Based Nurse Practitioners Utilizing Clinical Decision Support Systems: A Systematic Review.

    Science.gov (United States)

    Borum, Cindy

    2018-01-23

    There is a national focus on the adoption of healthcare technology to improve the delivery of safe, efficient, and high-quality patient care. Nurse practitioners fulfill an emerging strategic role in the hospital setting. A comprehensive literature review focused on the question: What are the barriers for nurse practitioners utilizing clinical decision support in the hospital setting? Nine studies conducted from 2011 to 2017 were the basis for this review, which identified 13 barriers for nurse practitioners utilizing clinical decision support in the hospital. Having the right information, including up-to-date evidence-based practice guidelines, accurate clinical pathways, and current clinical algorithms, was the most common barrier. Providing reliable clinical decision support is crucial as nurse practitioners become more dependent on hospital technology systems in the delivery of safe patient care. Eliminating barriers to the use of clinical decision support is important for informaticists and nurse practitioners because both groups concentrate on acceptance of decision support systems in the hospital to meet the goal of safe and high-quality patient care.

  6. The Effects of Computerized Clinical Decision Support Systems on Laboratory Test Ordering: A Systematic Review.

    Science.gov (United States)

    Delvaux, Nicolas; Van Thienen, Katrien; Heselmans, Annemie; de Velde, Stijn Van; Ramaekers, Dirk; Aertgeerts, Bert

    2017-04-01

    - Inappropriate laboratory test ordering has been shown to be as high as 30%. This can have an important impact on quality of care and costs because of downstream consequences such as additional diagnostics, repeat testing, imaging, prescriptions, surgeries, or hospital stays. - To evaluate the effect of computerized clinical decision support systems on appropriateness of laboratory test ordering. - We used MEDLINE, Embase, CINAHL, MEDLINE In-Process and Other Non-Indexed Citations, Clinicaltrials.gov, Cochrane Library, and Inspec through December 2015. Investigators independently screened articles to identify randomized trials that assessed a computerized clinical decision support system aimed at improving laboratory test ordering by providing patient-specific information, delivered in the form of an on-screen management option, reminder, or suggestion through a computerized physician order entry using a rule-based or algorithm-based system relying on an evidence-based knowledge resource. Investigators extracted data from 30 papers about study design, various study characteristics, study setting, various intervention characteristics, involvement of the software developers in the evaluation of the computerized clinical decision support system, outcome types, and various outcome characteristics. - Because of heterogeneity of systems and settings, pooled estimates of effect could not be made. Data showed that computerized clinical decision support systems had little or no effect on clinical outcomes but some effect on compliance. Computerized clinical decision support systems targeted at laboratory test ordering for multiple conditions appear to be more effective than those targeted at a single condition.

  7. Experimental verification of an energy consumption signal tool for operational decision support in an office building

    Energy Technology Data Exchange (ETDEWEB)

    Pavlak, Gregory S.; Henze, Gregor P.; Hirsch, Adam I.; Florita, Anthony R.; Dodier, Robert H.

    2016-12-01

    This paper demonstrates an energy signal tool to assess the system-level and whole-building energy use of an office building in downtown Denver, Colorado. The energy signal tool uses a traffic light visualization to alert a building operator to energy use which is substantially different from expected. The tool selects which light to display for a given energy end-use by comparing measured energy use to expected energy use, accounting for uncertainty. A red light is only displayed when a fault is likely enough, and abnormal operation costly enough, that taking action will yield the lowest cost result. While the theoretical advances and tool development were reported previously, it has only been tested using a basic building model and has not, until now, been experimentally verified. Expected energy use for the field demonstration is provided by a compact reduced-order representation of the Alliance Center, generated from a detailed DOE-2.2 energy model. Actual building energy consumption data is taken from the summer of 2014 for the office building immediately after a significant renovation project. The purpose of this paper is to demonstrate a first look at the building following its major renovation compared to the design intent. The tool indicated strong under-consumption in lighting and plug loads and strong over-consumption in HVAC energy consumption, which prompted several focused actions for follow-up investigation. In addition, this paper illustrates the application of Bayesian inference to the estimation of posterior parameter probability distributions to measured data. Practical discussion of the application is provided, along with additional findings from further investigating the significant difference between expected and actual energy consumption.

  8. Building a learning health system using clinical registers: a non-technical introduction.

    Science.gov (United States)

    Ovretveit, John; Nelson, Eugene; James, Brent

    2016-10-10

    Purpose The purpose of this paper is to describe how clinical registers were designed and used to serve multiple purposes in three health systems, in order to contribute practical experience for building learning healthcare systems. Design/methodology/approach Case description and comparison of the development and use of clinical registries, drawing on participants' experience and published and unpublished research. Findings Clinical registers and new software systems enable fact-based decisions by patients, clinicians, and managers about better care, as well as new and more economical research. Designing systems to present the data for users' daily work appears to be the key to effective use of the potential afforded by digital data. Research limitations/implications The case descriptions draw on the experience of the authors who were involved in the development of the registers, as well as on published and unpublished research. There is limited data about outcomes for patients or cost-effectiveness. Practical implications The cases show the significant investments which are needed to make effective use of clinical register data. There are limited skills to design and apply the digital systems to make the best use of the systems and to reduce their disadvantages. More use can be made of digital data for quality improvement, patient empowerment and support, and for research. Social implications Patients can use their data combined with other data to self-manage their chronic conditions. There are challenges in designing and using systems so that those with lower health and computer literacy and incomes also benefit from these systems, otherwise the digital revolution may increase health inequalities. Originality/value The paper shows three real examples of clinical registers which have been developed as part of their host health systems' strategies to develop learning healthcare systems. The paper gives a simple non-technical introduction and overview for

  9. Building consensus on clinical procedural skills for South African ...

    African Journals Online (AJOL)

    Background: The development of registrar training as part of the newly created speciality of family medicine in South Africa requires the development of a national consensus on the clinical procedural skills outcomes that should be expected of training programmes. Methods: This study utilized a Delphi technique to ...

  10. Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

    Science.gov (United States)

    Dolan, James G

    2010-01-01

    Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

  11. Building a Bridge or Digging a Pipeline? Clinical Data Mining in Evidence-Informed Knowledge Building

    Science.gov (United States)

    Epstein, Irwin

    2015-01-01

    Challenging the "bridge metaphor" theme of this conference, this article contends that current practice-research integration strategies are more like research-to-practice "pipelines." The purpose of this article is to demonstrate the potential of clinical data-mining studies conducted by practitioners, practitioner-oriented PhD…

  12. Evaluating the use of a computerized clinical decision support system for asthma by pediatric pulmonologists.

    Science.gov (United States)

    Lomotan, Edwin A; Hoeksema, Laura J; Edmonds, Diana E; Ramírez-Garnica, Gabriela; Shiffman, Richard N; Horwitz, Leora I

    2012-03-01

    To investigate use of a new guideline-based, computerized clinical decision support (CCDS) system for asthma in a pediatric pulmonology clinic of a large academic medical center. We conducted a qualitative evaluation including review of electronic data, direct observation, and interviews with all nine pediatric pulmonologists in the clinic. Outcome measures included patterns of computer use in relation to patient care, and themes surrounding the relationship between asthma care and computer use. The pediatric pulmonologists entered enough data to trigger the decision support system in 397/445 (89.2%) of all asthma visits from January 2009 to May 2009. However, interviews and direct observations revealed use of the decision support system was limited to documentation activities after clinic sessions ended. Reasons for delayed use reflected barriers common to general medical care and barriers specific to subspecialty care. Subspecialist-specific barriers included the perceived high complexity of patients, the impact of subject matter expertise on the types of decision support needed, and unique workflow concerns such as the need to create letters to referring physicians. Pediatric pulmonologists demonstrated low use of a computerized decision support system for asthma care because of a combination of general and subspecialist-specific factors. Subspecialist-specific factors should not be underestimated when designing guideline-based, computerized decision support systems for the subspecialty setting. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  13. Knowledge bases, clinical decision support systems, and rapid learning in oncology.

    Science.gov (United States)

    Yu, Peter Paul

    2015-03-01

    One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care. Copyright © 2015 by American Society of Clinical Oncology.

  14. Clinical decision making in seizures and status epilepticus.

    Science.gov (United States)

    Teran, Felipe; Harper-Kirksey, Katrina; Jagoda, Andy

    2015-01-01

    Seizures and status epilepticus are frequent neurologic emergencies in the emergency department, accounting for 1% of all emergency department visits. The management of this time-sensitive and potentially life-threatening condition is challenging for both prehospital providers and emergency clinicians. The approach to seizing patients begins with differentiating seizure activity from mimics and follows with identifying potential secondary etiologies, such as alcohol-related seizures. The approach to the patient in status epilepticus and the patient with nonconvulsive status epilepticus constitutes a special clinical challenge. This review summarizes the best available evidence and recommendations regarding diagnosis and resuscitation of the seizing patient in the emergency setting.

  15. MR-Tree - A Scalable MapReduce Algorithm for Building Decision Trees

    Directory of Open Access Journals (Sweden)

    Vasile PURDILĂ

    2014-03-01

    Full Text Available Learning decision trees against very large amounts of data is not practical on single node computers due to the huge amount of calculations required by this process. Apache Hadoop is a large scale distributed computing platform that runs on commodity hardware clusters and can be used successfully for data mining task against very large datasets. This work presents a parallel decision tree learning algorithm expressed in MapReduce programming model that runs on Apache Hadoop platform and has a very good scalability with dataset size.

  16. Framework for securing personal health data in clinical decision support systems.

    Science.gov (United States)

    Sandell, Protik

    2007-01-01

    If appropriate security mechanisms aren't in place, individuals and groups can get unauthorized access to personal health data residing in clinical decision support systems (CDSS). These concerns are well founded; there has been a dramatic increase in reports of security incidents. The paper provides a framework for securing personal health data in CDSS. The framework breaks down CDSS into data gathering, data management and data delivery functions. It then provides the vulnerabilities that can occur in clinical decision support activities and the measures that need to be taken to protect the data. The framework is applied to protect the confidentiality, integrity and availability of personal health data in a decision support system. Using the framework, project managers and architects can assess the potential risk of unauthorized data access in their decision support system. Moreover they can design systems and procedures to effectively secure personal health data.

  17. Genetics in the Clinical Decision of Antiplatelet Treatment.

    Science.gov (United States)

    Siasos, Gerasimos; Zaromitidou, Marina; Oikonomou, Evangelos; Vavuranakis, Manolis; Tsigkou, Vicky; Papageorgiou, Nikolaos; Chaniotis, Dimitrios; Vrachatis, Dimitrios A; Stefanadis, Christodoulos; Papavassiliou, Athanasios G; Tousoulis, Dimitrios

    2017-01-01

    Coronary artery disease remains the leading cause of death globally. Dual antiplatelet treatment with aspirin and aP2Y12 receptor significantly reduces thrombotic events. However, antiplatelet drug response displays considerable interindividual variability. Genetic factors account for up to 70% of impaired drug response. A number of genes encoding proteins involved in the pharmacokinetic pathway have been found to alter drug response. According to most studies, CYP2C19 gene is the strongest genetic determinant. The novel antiplatelet agents prasugrel and ticagrelor, seem to overcome genetic restrictions but in expense of increased bleeding rates. Achieving a balance between adequate platelet inhibition and bleeding complications is challenging. Genetic screening may provide valuable guidance towards an efficient antiplatelet treatment. However, the lack of randomized controls trials testing the effect of a genotype-guided therapy, forbids the implementation of genetic testing into clinical practice. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  18. Quantitative ultrasound texture analysis for clinical decision making support

    Science.gov (United States)

    Wu, Jie Ying; Beland, Michael; Konrad, Joseph; Tuomi, Adam; Glidden, David; Grand, David; Merck, Derek

    2015-03-01

    We propose a general ultrasound (US) texture-analysis and machine-learning framework for detecting the presence of disease that is suitable for clinical application across clinicians, disease types, devices, and operators. Its stages are image selection, image filtering, ROI selection, feature parameterization, and classification. Each stage is modular and can be replaced with alternate methods. Thus, this framework is adaptable to a wide range of tasks. Our two preliminary clinical targets are hepatic steatosis and adenomyosis diagnosis. For steatosis, we collected US images from 288 patients and their pathology-determined values of steatosis (%) from biopsies. Two radiologists independently reviewed all images and identified the region of interest (ROI) most representative of the hepatic echotexture for each patient. To parameterize the images into comparable quantities, we filter the US images at multiple scales for various texture responses. For each response, we collect a histogram of pixel features within the ROI, and parameterize it as a Gaussian function using its mean, standard deviation, kurtosis, and skew to create a 36-feature vector. Our algorithm uses a support vector machine (SVM) for classification. Using a threshold of 10%, we achieved 72.81% overall accuracy, 76.18% sensitivity, and 65.96% specificity in identifying steatosis with leave-ten-out cross-validation (p<0.0001). Extending this framework to adenomyosis, we identified 38 patients with MR-confirmed findings of adenomyosis and previous US studies and 50 controls. A single rater picked the best US-image and ROI for each case. Using the same processing pipeline, we obtained 76.14% accuracy, 86.00% sensitivity, and 63.16% specificity with leave-one-out cross-validation (p<0.0001).

  19. Building consensus in strategic decision-making : system dynamics as a group support system

    NARCIS (Netherlands)

    Vennix, J.A.M.

    1995-01-01

    System dynamics was originally founded as a method for modeling and simulating the behavior of industrial systems. In recent years it is increasingly employed as a Group Support System for strategic decision-making groups. The model is constructed in direct interaction with a management team, and

  20. The Role of Scientific Studies in Building Consensus in Environmental Decision Making: a Coral Reef Example

    Science.gov (United States)

    We present a new approach for characterizing the potential of scientific studies to reduce conflict among stakeholders in an analytic-deliberative environmental decision-making process. The approach computes a normalized metric, the Expected Consensus Index of New Research (ECINR...

  1. Learning by Doing: Teaching Decision Making through Building a Code of Ethics.

    Science.gov (United States)

    Hawthorne, Mark D.

    2001-01-01

    Notes that applying abstract ethical principles to the practical business of building a code of applied ethics for a technical communication department teaches students that they share certain unarticulated or unconscious values that they can translate into ethical principles. Suggests that combining abstract theory with practical policy writing…

  2. A Conceptual Framework for Occupant-Centered Building Management Decision Support System

    DEFF Research Database (Denmark)

    Lazarova-Molnar, Sanja; Shaker, Hamid Reza

    2016-01-01

    Buildings’ energy consumption makes the largest portion of the overall energy consumption. Commercial buildings are specific and their energy efficiency should not be viewed as a standalone issue. On the contrary, it needs to be viewed in function of the goals of the hosted businesses and organiz......Buildings’ energy consumption makes the largest portion of the overall energy consumption. Commercial buildings are specific and their energy efficiency should not be viewed as a standalone issue. On the contrary, it needs to be viewed in function of the goals of the hosted businesses...... and organizations. The critical factor for achieving these goals are employees, who are also usually occupants of these buildings and, thus, hold one of the keys to reduced energy consumption. It has been shown that energy-conscious behaviour of building occupants presents a significant opportunity to save energy....... Human behaviour is, however, very complex and hard to predict, and there needs to be a set of conditions satisfied for occupants to cooperate on the energy efficiency level. Majority of commercial buildings’ occupants are not directly affected by their energy-consumption related behaviour due to the non...

  3. Extracting Buildings from True Color Stereo Aerial Images Using a Decision Making Strategy

    Directory of Open Access Journals (Sweden)

    Eufemia Tarantino

    2011-07-01

    Full Text Available The automatic extraction of buildings from true color stereo aerial imagery in a dense built-up area is the main focus of this paper. Our approach strategy aimed at reducing the complexity of the image content by means of a three-step procedure combining reliable geospatial image analysis techniques. Even if it is a rudimentary first step towards a more general approach, the method presented proved useful in urban sprawl studies for rapid map production in flat area by retrieving indispensable information on buildings from scanned historic aerial photography. After the preliminary creation of a photogrammetric model to manage Digital Surface Model and orthophotos, five intermediate mask-layers data (Elevation, Slope, Vegetation, Shadow, Canny, Shadow, Edges were processed through the combined use of remote sensing image processing and GIS software environments. Lastly, a rectangular building block model without roof structures (Level of Detail, LoD1 was automatically generated. System performance was evaluated with objective criteria, showing good results in a complex urban area featuring various types of building objects.

  4. Decision-making in the Pre-design Stage of Sustainable Building Renovation Projects

    DEFF Research Database (Denmark)

    Nielsen, Anne Nørkjær; Steen Larsen, Tine; Jensen, Rasmus Lund

    2017-01-01

    There is a great potential in renovating our existing building stock, in terms of improving environmental, economic and social qualities. Meeting the increasing performance requirements for sustainable construction entails an increasing level of complexity in the design process of both new...

  5. Clinical decision making on the use of physical restraint in intensive care units

    Directory of Open Access Journals (Sweden)

    Xinqian Li

    2014-12-01

    Full Text Available Physical restraint is a common nursing intervention in intensive care units and nurses often use it to ensure patients' safety and to prevent unexpected accidents. However, existing literature indicated that the use of physical restraint is a complex one because of inadequate rationales, the negative physical and emotional effects on patients, but the lack of perceived alternatives. This paper is aimed to interpret the clinical decision-making theories related to the use of physical restraint in intensive care units in order to facilitate our understanding on the use of physical restraint and to evaluate the quality of decisions made by nurses. By reviewing the literature, intuition and heuristics are the main decision-making strategies related to the use of physical restraint in intensive care units because the rapid and reflexive nature of intuition and heuristics allow nurses to have a rapid response to urgent and emergent cases. However, it is problematic if nurses simply count their decision-making on experience rather than incorporate research evidence into clinical practice because of inadequate evidence to support the use of physical restraint. Besides that, such a rapid response may lead nurses to make decisions without adequate assessment and thinking and therefore biases and errors may be generated. Therefore, despite the importance of intuition and heuristics in decision-making in acute settings on the use of physical restraint, it is recommended that nurses should incorporate research evidence with their experience to make decisions and adequate assessment before implementing physical restraint is also necessary.

  6. A social-technological epistemology of clinical decision-making as mediated by imaging.

    Science.gov (United States)

    van Baalen, Sophie; Carusi, Annamaria; Sabroe, Ian; Kiely, David G

    2017-10-01

    In recent years there has been growing attention to the epistemology of clinical decision-making, but most studies have taken the individual physicians as the central object of analysis. In this paper we argue that knowing in current medical practice has an inherently social character and that imaging plays a mediating role in these practices. We have analyzed clinical decision-making within a medical expert team involved in diagnosis and treatment of patients with pulmonary hypertension (PH), a rare disease requiring multidisciplinary team involvement in diagnosis and management. Within our field study, we conducted observations, interviews, video tasks, and a panel discussion. Decision-making in the PH clinic involves combining evidence from heterogeneous sources into a cohesive framing of a patient, in which interpretations of the different sources can be made consistent with each other. Because pieces of evidence are generated by people with different expertise and interpretation and adjustments take place in interaction between different experts, we argue that this process is socially distributed. Multidisciplinary team meetings are an important place where information is shared, discussed, interpreted, and adjusted, allowing for a collective way of seeing and a shared language to be developed. We demonstrate this with an example of image processing in the PH service, an instance in which knowledge is distributed over multiple people who play a crucial role in generating an evaluation of right heart function. Finally, we argue that images fulfill a mediating role in distributed knowing in 3 ways: first, as enablers or tools in acquiring information; second, as communication facilitators; and third, as pervasively framing the epistemic domain. With this study of clinical decision-making in diagnosis and treatment of PH, we have shown that clinical decision-making is highly social and mediated by technologies. The epistemology of clinical decision-making needs

  7. Building Capacity for Data-Driven Decision Making in African HIV Testing Programs: Field Perspectives on Data Use Workshops.

    Science.gov (United States)

    Courtenay-Quirk, Cari; Spindler, Hilary; Leidich, Aimee; Bachanas, Pam

    2016-12-01

    Strategic, high quality HIV testing services (HTS) delivery is an essential step towards reaching the end of AIDS by 2030. We conducted HTS Data Use workshops in five African countries to increase data use for strategic program decision-making. Feedback was collected on the extent to which workshop skills and tools were applied in practice and to identify future capacity-building needs. We later conducted six semistructured phone interviews with workshop planning teams and sent a web-based survey to 92 past participants. The HTS Data Use workshops provided accessible tools that were readily learned by most respondents. While most respondents reported increased confidence in interpreting data and frequency of using such tools over time, planning team representatives indicated ongoing needs for more automated tools that can function across data systems. To achieve ambitious global HIV/AIDS targets, national decision makers may continue to seek tools and skill-building opportunities to monitor programs and identify opportunities to refine strategies.

  8. An exploratory study on baccalaureate-prepared nurses' perceptions regarding clinical decision-making in mainland China.

    Science.gov (United States)

    Wang, Yue; Chien, Wai-Tong; Twinn, Sheila

    2012-06-01

    To explore Chinese baccalaureate-prepared nurses' perceptions of the concept and practices of clinical decision-making. Clinical decision-making is an integral part of nursing practice. Several studies have explored the experiences and factors which influence nurses' clinical decisions and these have recognised the cultural impact. However, little is known about the experience of clinical decision-making from the perspective of Chinese baccalaureate-prepared nurses. A qualitative, exploratory study. Data were obtained through in-depth, semi-structured interview with a convenience sample of 12 baccalaureate-prepared registered nurses. Interviews focused on registered nurses' understanding and perceptions of clinical decision-making in clinical practice. They were tape-recorded, transcribed verbatim and content analysed. Two major themes were identified, namely, functional perspectives of clinical decision-making and perceived autonomy in clinical decision-making. There were two sub-themes for the first theme: emphasising a full understanding of the patient's health status and undertaking appropriate nursing judgements and problem-solving. Three sub-themes emerged for perceived autonomy in clinical decision-making: relying on a doctor's instructions, making judgements on a doctor's orders and making decisions independently in emergency care. The findings indicate that Chinese nurses understand the essence of clinical decision-making, but they have low autonomy in such decisions in their daily practice. More importantly, the results also reveal the importance of social and cultural factors in nurses' perceptions of this topic. A better understanding of the perceptions and concepts of clinical decision-making among nurses in mainland China and other countries as well, can help in establishing nurses' roles and responsibilities in participating in making effective decisions for patient care. The findings can also inform us of potential strategies which may be adopted to

  9. A pilot study of distributed knowledge management and clinical decision support in the cloud.

    Science.gov (United States)

    Dixon, Brian E; Simonaitis, Linas; Goldberg, Howard S; Paterno, Marilyn D; Schaeffer, Molly; Hongsermeier, Tonya; Wright, Adam; Middleton, Blackford

    2013-09-01

    Implement and perform pilot testing of web-based clinical decision support services using a novel framework for creating and managing clinical knowledge in a distributed fashion using the cloud. The pilot sought to (1) develop and test connectivity to an external clinical decision support (CDS) service, (2) assess the exchange of data to and knowledge from the external CDS service, and (3) capture lessons to guide expansion to more practice sites and users. The Clinical Decision Support Consortium created a repository of shared CDS knowledge for managing hypertension, diabetes, and coronary artery disease in a community cloud hosted by Partners HealthCare. A limited data set for primary care patients at a separate health system was securely transmitted to a CDS rules engine hosted in the cloud. Preventive care reminders triggered by the limited data set were returned for display to clinician end users for review and display. During a pilot study, we (1) monitored connectivity and system performance, (2) studied the exchange of data and decision support reminders between the two health systems, and (3) captured lessons. During the six month pilot study, there were 1339 patient encounters in which information was successfully exchanged. Preventive care reminders were displayed during 57% of patient visits, most often reminding physicians to monitor blood pressure for hypertensive patients (29%) and order eye exams for patients with diabetes (28%). Lessons learned were grouped into five themes: performance, governance, semantic interoperability, ongoing adjustments, and usability. Remote, asynchronous cloud-based decision support performed reasonably well, although issues concerning governance, semantic interoperability, and usability remain key challenges for successful adoption and use of cloud-based CDS that will require collaboration between biomedical informatics and computer science disciplines. Decision support in the cloud is feasible and may be a reasonable

  10. Expediting the transfer of evidence into practice: building clinical partnerships*

    Science.gov (United States)

    Rader, Tamara; Gagnon, Anita J.

    2000-01-01

    A librarian/clinician partnership was fostered in one hospital through the formation of the Evidence-based Practice Committee, with an ulterior goal of facilitating the transfer of evidence into practice. The paper will describe barriers to evidence-based practice and outline the committee's strategies for overcoming these barriers, including the development and promotion of a Web-based guide to evidence-based practice specifically designed for clinicians (health professionals). Educational strategies for use of the Web-based guide will also be addressed. Advantages of this partnership are that the skills of librarians in meeting the needs of clinicians are maximized. The evidence-based practice skills of clinicians are honed and librarians make a valuable contribution to the knowledgebase of the clinical staff. The knowledge acquired through the partnership by both clinicians and librarians will increase the sophistication of the dialogue between the two groups and in turn will expedite the transfer of evidence into practice. PMID:10928710

  11. Proposed Clinical Decision Rules to Diagnose Acute Rhinosinusitis Among Adults in Primary Care

    DEFF Research Database (Denmark)

    Ebell, Mark H.; Hansen, Jens Georg

    2017-01-01

    PURPOSE To reduce inappropriate antibiotic prescribing, we sought to develop a clinical decision rule for the diagnosis of acute rhinosinusitis and acute bacterial rhinosinusitis. METHODS Multivariate analysis and classification and regression tree (CART) analysis were used to develop clinical...... decision rules for the diagnosis of acute rhinosinusitis, defined using 3 different reference standards (purulent antral puncture fluid or abnormal finding on a computed tomographic (CT) scan; for acute bacterial rhinosinusitis, we used a positive bacterial culture of antral fluid). Signs, symptoms, C......-reactive protein (CRP), and reference standard tests were prospectively recorded in 175 Danish patients aged 18 to 65 years seeking care for suspected acute rhinosinusitis. For each reference standard, we developed 2 clinical decision rules: a point score based on a logistic regression model and an algorithm based...

  12. Optimal data systems: the future of clinical predictions and decision support.

    Science.gov (United States)

    Celi, Leo A; Csete, Marie; Stone, David

    2014-10-01

    The purpose of the review is to describe the evolving concept and role of data as it relates to clinical predictions and decision-making. Critical care medicine is, as an especially data-rich specialty, becoming acutely cognizant not only of its historic deficits in data utilization but also of its enormous potential for capturing, mining, and leveraging such data into well-designed decision support modalities as well as the formulation of robust best practices. Modern electronic medical records create an opportunity to design complete and functional data systems that can support clinical care to a degree never seen before. Such systems are often referred to as 'data-driven,' but a better term is 'optimal data systems' (ODS). Here we discuss basic features of an ODS and its benefits, including the potential to transform clinical prediction and decision support.

  13. Reproductive Ethics in Commercial Surrogacy: Decision-Making in IVF Clinics in New Delhi, India

    DEFF Research Database (Denmark)

    Tanderup, Malene; Reddy, Sunita; Patel, Tulsi

    2015-01-01

    Research are somewhat vague and contradictory, resulting in self-regulated practices of fertility clinics. This paper broadly looks at clinical ethics in reproduction in the practice of surrogacy and decision-making in various procedures. Through empirical research in New Delhi, the capital of India, from...... December 2011 to November 2012, issues of decision-making on embryo transfer, fetal reduction, and mode of delivery were identified. Interviews were carried out with doctors in eighteen ART clinics, agents from four agencies, and fourteen surrogates. In aiming to fulfil the commissioning parents’ demands......, doctors were willing to go to the greatest extent possible in their medical practice. Autonomy and decision-making regarding choice of the number of embryos to transfer and the mode of delivery lay neither with commissioning parents nor surrogate mothers but mostly with doctors. In order to ensure higher...

  14. Computerized clinical decision support systems for chronic disease management: a decision-maker-researcher partnership systematic review.

    Science.gov (United States)

    Roshanov, Pavel S; Misra, Shikha; Gerstein, Hertzel C; Garg, Amit X; Sebaldt, Rolf J; Mackay, Jean A; Weise-Kelly, Lorraine; Navarro, Tamara; Wilczynski, Nancy L; Haynes, R Brian

    2011-08-03

    The use of computerized clinical decision support systems (CCDSSs) may improve chronic disease management, which requires recurrent visits to multiple health professionals, ongoing disease and treatment monitoring, and patient behavior modification. The objective of this review was to determine if CCDSSs improve the processes of chronic care (such as diagnosis, treatment, and monitoring of disease) and associated patient outcomes (such as effects on biomarkers and clinical exacerbations). We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for potentially eligible articles published up to January 2010. We included randomized controlled trials that compared the use of CCDSSs to usual practice or non-CCDSS controls. Trials were eligible if at least one component of the CCDSS was designed to support chronic disease management. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of relevant outcomes. Of 55 included trials, 87% (n = 48) measured system impact on the process of care and 52% (n = 25) of those demonstrated statistically significant improvements. Sixty-five percent (36/55) of trials measured impact on, typically, non-major (surrogate) patient outcomes, and 31% (n = 11) of those demonstrated benefits. Factors of interest to decision makers, such as cost, user satisfaction, system interface and feature sets, unique design and deployment characteristics, and effects on user workflow were rarely investigated or reported. A small majority (just over half) of CCDSSs improved care processes in chronic disease management and some improved patient health. Policy makers, healthcare administrators, and practitioners should be aware that the evidence of CCDSS effectiveness is limited, especially with respect to the small number and size of studies measuring patient outcomes.

  15. Clinical decision on pit and fissure sealing according to the occlusal morphology. A descriptive study.

    Science.gov (United States)

    Courson, F; Velly, A M; Droz, D; Lupi-Pégurier, L; Muller-Bolla, M

    2011-03-01

    The objective of this descriptive study was to evaluate the clinical decision on sealing pits and fissures according to the occlusal morphology in patients with low individual caries risk (ICR). A total of 222 dentists, 86 affiliated to the French Society of Paediatric Odontology (SFOP) and 136 general practice dentists (GPs), answered the same questionnaire with illustrations of 4 occlusal surfaces of permanent molars: they indicated firstly if these were at risk and secondly the corresponding decision regarding sealing. This questionnaire assessed the decision on widening pits and fissures before sealing and the type of sealant material used. Multivariate logistic regression analyses were performed to identify the factors associated with the clinical decision to widen pits and fissures. Sealing of at-risk teeth was indicated by 89% of dentists, whereas sealing of not at-risk occlusal surfaces was recommended by 46%. SFOP dentists were more prone to recommend pit and fissures sealants. The multivariate analyses demonstrated that only the type of material was associated with the clinical decision to widen pits and fissures. Forty eight percent of dentists choose the same material in all clinical situations. The wide variations in sealant use and placement technique implies there is no apparent consensus among GP and SFOP dentists. Although the criteria are similar in numerous scientific societies, not all dentists are acting upon these recommendations.

  16. Potential Role of Methylation Marker in Glioma Supporting Clinical Decisions

    Directory of Open Access Journals (Sweden)

    Krzysztof Roszkowski

    2016-11-01

    Full Text Available The IDH1/2 gene mutations, ATRX loss/mutation, 1p/19q status, and MGMT promoter methylation are increasingly used as prognostic or predictive biomarkers of gliomas. However, the effect of their combination on radiation therapy outcome is discussable. Previously, we demonstrated that the IDH1 c.G395A; p.R132H mutation was associated with longer survival in grade II astrocytoma and GBM (Glioblastoma. Here we analyzed the MGMT promoter methylation status in patients with a known mutation status in codon 132 of IDH1, followed by clinical and genetic data analysis based on the two statuses. After a subtotal tumor resection, the patients were treated using IMRT (Intensity-Modulated Radiation Therapy with 6 MeV photons. The total dose was: 54 Gy for astrocytoma II, 60 Gy for astrocytoma III, 60 Gy for glioblastoma, 2 Gy per day, with 24 h intervals, five days per week. The patients with MGMT promoter methylation and IDH1 somatic mutation (OS = 40 months had a better prognosis than those with MGMT methylation alone (OS = 18 months. In patients with astrocytoma anaplasticum (n = 7 with the IDH1 p.R132H mutation and hypermethylated MGMT, the prognosis was particularly favorable (median OS = 47 months. In patients with astrocytoma II meeting the above criteria, the prognosis was also better than in those not meeting those criteria. The IDH1 mutation appears more relevant for the prognosis than MGMT methylation. The IDH1 p.R132H mutation combined with MGMT hypermethylation seems to be the most advantageous for treatment success. Patients not meeting those criteria may require more aggressive treatments.

  17. Sensitivity of a Clinical Decision Rule and Early Computed Tomography in Aneurysmal Subarachnoid Hemorrhage

    Directory of Open Access Journals (Sweden)

    Dustin G. Mark

    2015-10-01

    Full Text Available Introduction: Application of a clinical decision rule for subarachnoid hemorrhage, in combination with cranial computed tomography (CT performed within six hours of ictus (early cranial CT, may be able to reasonably exclude a diagnosis of aneurysmal subarachnoid hemorrhage (aSAH. This study’s objective was to examine the sensitivity of both early cranial CT and a previously validated clinical decision rule among emergency department (ED patients with aSAH and a normal mental status. Methods: Patients were evaluated in the 21 EDs of an integrated health delivery system between January 2007 and June 2013. We identified by chart review a retrospective cohort of patients diagnosed with aSAH in the setting of a normal mental status and performance of early cranial CT. Variables comprising the SAH clinical decision rule (age >40, presence of neck pain or stiffness, headache onset with exertion, loss of consciousness at headache onset were abstracted from the chart and assessed for inter-rater reliability. Results: One hundred fifty-five patients with aSAH met study inclusion criteria. The sensitivity of early cranial CT was 95.5% (95% CI [90.9-98.2]. The sensitivity of the SAH clinical decision rule was also 95.5% (95% CI [90.9-98.2]. Since all false negative cases for each diagnostic modality were mutually independent, the combined use of both early cranial CT and the clinical decision rule improved sensitivity to 100% (95% CI [97.6-100.0]. Conclusion: Neither early cranial CT nor the SAH clinical decision rule demonstrated ideal sensitivity for aSAH in this retrospective cohort. However, the combination of both strategies might optimize sensitivity for this life-threatening disease.

  18. We can work it out: Group decision-making builds social identity and enhances the cognitive performance of care residents.

    Science.gov (United States)

    Haslam, Catherine; Alexander Haslam, S; Knight, Craig; Gleibs, Ilka; Ysseldyk, Renate; McCloskey, Lauren-Grace

    2014-02-01

    Group-based interventions have been argued to slow the cognitive decline of older people residing in care by building social identification and thereby increasing motivation and engagement. The present study explored the identity-cognition association further by investigating the impact of a group decision-making intervention on cognition. Thirty-six care home residents were assigned to one of three conditions: an Intervention in which they made decisions about lounge refurbishment as a group, a Comparison condition in which staff made these decisions, or a no-treatment Control. Cognitive function, social identification, home satisfaction, and lounge use were measured before and after the intervention. Participants in the Intervention condition showed significant increases on all measures, and greater improvement than participants in both Comparison and Control conditions. Consistent with social identity theorizing, these findings point to the role of group activity and social identification in promoting cognitive integrity and well-being among care residents. © 2012 The British Psychological Society.

  19. Decision Analysis with Value Focused Thinking as a Methodology to Select Buildings for Deconstruction

    Science.gov (United States)

    2007-03-01

    of non-load bearing components of a building such as windows, doors, appliances, sanitary ware, cabinets, electrical fixtures, etc. Structural...War II. High value specialty items such as hardwood flooring, architectural moldings and unique doors or electrical fixtures can be very valuable...wood is not necessarily suitable for reuse or recycling (Franklin Associates, 1998). However, new tools such as 25 pneumatic de- nailers and

  20. A Survey of Standard Information Models for Clinical Decision Support Systems.

    Science.gov (United States)

    Mussavi Rizi, Seyed Ali; Roudsari, Abdul

    2017-01-01

    HL7 CDA, vMR, and openEHR archetypes have been utilized as standard information models for clinical decision support systems. Compared to openEHR archetypes, vMR typically requires less time to develop and extend which makes it a good fit for rapid prototyping and pilot projects, while openEHR archetypes handle the data and semantic specification better. Using CDA for clinical decision support systems is discouraged due to its complexity, steep learning curve, and potential safety issues.

  1. Many faces of rationality: Implications of the great rationality debate for clinical decision-making.

    Science.gov (United States)

    Djulbegovic, Benjamin; Elqayam, Shira

    2017-10-01

    Given that more than 30% of healthcare costs are wasted on inappropriate care, suboptimal care is increasingly connected to the quality of medical decisions. It has been argued that personal decisions are the leading cause of death, and 80% of healthcare expenditures result from physicians' decisions. Therefore, improving healthcare necessitates improving medical decisions, ie, making decisions (more) rational. Drawing on writings from The Great Rationality Debate from the fields of philosophy, economics, and psychology, we identify core ingredients of rationality commonly encountered across various theoretical models. Rationality is typically classified under umbrella of normative (addressing the question how people "should" or "ought to" make their decisions) and descriptive theories of decision-making (which portray how people actually make their decisions). Normative theories of rational thought of relevance to medicine include epistemic theories that direct practice of evidence-based medicine and expected utility theory, which provides the basis for widely used clinical decision analyses. Descriptive theories of rationality of direct relevance to medical decision-making include bounded rationality, argumentative theory of reasoning, adaptive rationality, dual processing model of rationality, regret-based rationality, pragmatic/substantive rationality, and meta-rationality. For the first time, we provide a review of wide range of theories and models of rationality. We showed that what is "rational" behaviour under one rationality theory may be irrational under the other theory. We also showed that context is of paramount importance to rationality and that no one model of rationality can possibly fit all contexts. We suggest that in context-poor situations, such as policy decision-making, normative theories based on expected utility informed by best research evidence may provide the optimal approach to medical decision-making, whereas in the context

  2. A clinical decision support needs assessment of community-based physicians.

    Science.gov (United States)

    Richardson, Joshua E; Ash, Joan S

    2011-12-01

    To conduct a grounded needs assessment to elicit community-based physicians' current views on clinical decision support (CDS) and its desired capabilities that may assist future CDS design and development for community-based practices. To gain insight into community-based physicians' goals, environments, tasks, and desired support tools, we used a human-computer interaction model that was based in grounded theory. We conducted 30 recorded interviews with, and 25 observations of, primary care providers within 15 urban and rural community-based clinics across Oregon. Participants were members of three healthcare organizations with different commercial electronic health record systems. We used a grounded theory approach to analyze data and develop a user-centered definition of CDS and themes related to desired CDS functionalities. Physicians viewed CDS as a set of software tools that provide alerts, prompts, and reference tools, but not tools to support patient management, clinical operations, or workflow, which they would like. They want CDS to enhance physician-patient relationships, redirect work among staff, and provide time-saving tools. Participants were generally dissatisfied with current CDS capabilities and overall electronic health record usability. Physicians identified different aspects of decision-making in need of support: clinical decision-making such as medication administration and treatment, and cognitive decision-making that enhances relationships and interactions with patients and staff. Physicians expressed a need for decision support that extended beyond their own current definitions. To meet this requirement, decision support tools must integrate functions that align time and resources in ways that assist providers in a broad range of decisions.

  3. Exploring a clinically friendly web-based approach to clinical decision support linked to the electronic health record: design philosophy, prototype implementation, and framework for assessment.

    Science.gov (United States)

    Miller, Perry; Phipps, Michael; Chatterjee, Sharmila; Rajeevan, Nallakkandi; Levin, Forrest; Frawley, Sandra; Tokuno, Hajime

    2014-07-01

    Computer-based clinical decision support (CDS) is an important component of the electronic health record (EHR). As an increasing amount of CDS is implemented, it will be important that this be accomplished in a fashion that assists in clinical decision making without imposing unacceptable demands and burdens upon the provider's practice. The objective of our study was to explore an approach that allows CDS to be clinician-friendly from a variety of perspectives, to build a prototype implementation that illustrates features of the approach, and to gain experience with a pilot framework for assessment. The paper first discusses the project's design philosophy and goals. It then describes a prototype implementation (Neuropath/CDS) that explores the approach in the domain of neuropathic pain and in the context of the US Veterans Administration EHR. Finally, the paper discusses a framework for assessing the approach, illustrated by a pilot assessment of Neuropath/CDS. The paper describes the operation and technical design of Neuropath/CDS, as well as the results of the pilot assessment, which emphasize the four areas of focus, scope, content, and presentation. The work to date has allowed us to explore various design and implementation issues relating to the approach illustrated in Neuropath/CDS, as well as the development and pilot application of a framework for assessment.

  4. Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

    Science.gov (United States)

    Hargrave, C.; Moores, M.; Deegan, T.; Gibbs, A.; Poulsen, M.; Harden, F.; Mengersen, K.

    2014-03-01

    A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific subregions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

  5. Hemispheric activation differences in novice and expert clinicians during clinical decision making.

    Science.gov (United States)

    Hruska, Pam; Hecker, Kent G; Coderre, Sylvain; McLaughlin, Kevin; Cortese, Filomeno; Doig, Christopher; Beran, Tanya; Wright, Bruce; Krigolson, Olav

    2016-12-01

    Clinical decision making requires knowledge, experience and analytical/non-analytical types of decision processes. As clinicians progress from novice to expert, research indicates decision-making becomes less reliant on foundational biomedical knowledge and more on previous experience. In this study, we investigated how knowledge and experience were reflected in terms of differences in neural areas of activation. Novice and expert clinicians diagnosed simple or complex (easy, hard) cases while functional magnetic resonance imaging (fMRI) data were collected. Our results highlight key differences in the neural areas activated in novices and experts during the clinical decision-making process. fMRI data were collected from ten second year medical students (novices) and ten practicing gastroenterologists (experts) while they diagnosed sixteen (eight easy and eight hard) clinical cases via multiple-choice questions. Behavioral data were collected for diagnostic accuracy (correct/incorrect diagnosis) and time taken to assign a clinical diagnosis. Two analyses were performed with the fMRI data. First, data from easy and hard cases were compared within respective groups (easy > hard, hard > easy). Second, neural differences between novices and experts (novice > expert, expert > novice) were assessed. Experts correctly diagnosed more cases than novices and made their diagnoses faster than novices on both easy and hard cases (all p's decision making process, we identified significant hemispheric activation differences between novice and expert clinicians when diagnosing hard clinical cases. Specifically, novice clinicians had greater activations in the left anterior temporal cortex and left ventral lateral prefrontal cortex whereas expert clinicians had greater activations in the right dorsal lateral, right ventral lateral, and right parietal cortex. Hemispheric differences in activation were not observed between novices and experts while diagnosing easy clinical

  6. Designing an automated clinical decision support system to match clinical practice guidelines for opioid therapy for chronic pain

    Directory of Open Access Journals (Sweden)

    Clark Michael E

    2010-04-01

    Full Text Available Abstract Background Opioid prescribing for chronic pain is common and controversial, but recommended clinical practices are followed inconsistently in many clinical settings. Strategies for increasing adherence to clinical practice guideline recommendations are needed to increase effectiveness and reduce negative consequences of opioid prescribing in chronic pain patients. Methods Here we describe the process and outcomes of a project to operationalize the 2003 VA/DOD Clinical Practice Guideline for Opioid Therapy for Chronic Non-Cancer Pain into a computerized decision support system (DSS to encourage good opioid prescribing practices during primary care visits. We based the DSS on the existing ATHENA-DSS. We used an iterative process of design, testing, and revision of the DSS by a diverse team including guideline authors, medical informatics experts, clinical content experts, and end-users to convert the written clinical practice guideline into a computable algorithm to generate patient-specific recommendations for care based upon existing information in the electronic medical record (EMR, and a set of clinical tools. Results The iterative revision process identified numerous and varied problems with the initially designed system despite diverse expert participation in the design process. The process of operationalizing the guideline identified areas in which the guideline was vague, left decisions to clinical judgment, or required clarification of detail to insure safe clinical implementation. The revisions led to workable solutions to problems, defined the limits of the DSS and its utility in clinical practice, improved integration into clinical workflow, and improved the clarity and accuracy of system recommendations and tools. Conclusions Use of this iterative process led to development of a multifunctional DSS that met the approval of the clinical practice guideline authors, content experts, and clinicians involved in testing. The

  7. Designing an automated clinical decision support system to match clinical practice guidelines for opioid therapy for chronic pain.

    Science.gov (United States)

    Trafton, Jodie A; Martins, Susana B; Michel, Martha C; Wang, Dan; Tu, Samson W; Clark, David J; Elliott, Jan; Vucic, Brigit; Balt, Steve; Clark, Michael E; Sintek, Charles D; Rosenberg, Jack; Daniels, Denise; Goldstein, Mary K

    2010-04-12

    Opioid prescribing for chronic pain is common and controversial, but recommended clinical practices are followed inconsistently in many clinical settings. Strategies for increasing adherence to clinical practice guideline recommendations are needed to increase effectiveness and reduce negative consequences of opioid prescribing in chronic pain patients. Here we describe the process and outcomes of a project to operationalize the 2003 VA/DOD Clinical Practice Guideline for Opioid Therapy for Chronic Non-Cancer Pain into a computerized decision support system (DSS) to encourage good opioid prescribing practices during primary care visits. We based the DSS on the existing ATHENA-DSS. We used an iterative process of design, testing, and revision of the DSS by a diverse team including guideline authors, medical informatics experts, clinical content experts, and end-users to convert the written clinical practice guideline into a computable algorithm to generate patient-specific recommendations for care based upon existing information in the electronic medical record (EMR), and a set of clinical tools. The iterative revision process identified numerous and varied problems with the initially designed system despite diverse expert participation in the design process. The process of operationalizing the guideline identified areas in which the guideline was vague, left decisions to clinical judgment, or required clarification of detail to insure safe clinical implementation. The revisions led to workable solutions to problems, defined the limits of the DSS and its utility in clinical practice, improved integration into clinical workflow, and improved the clarity and accuracy of system recommendations and tools. Use of this iterative process led to development of a multifunctional DSS that met the approval of the clinical practice guideline authors, content experts, and clinicians involved in testing. The process and experiences described provide a model for development of

  8. Questioning assent: how are children's views included as families make decisions about clinical trials?

    Science.gov (United States)

    Madden, L; Shilling, V; Woolfall, K; Sowden, E; Smyth, R L; Williamson, P R; Young, B

    2016-11-01

    Assent is used to take children's wishes into account when they are invited into clinical trials, but the concept has attracted considerable criticism. We investigated children's accounts of decision-making with the aim of informing practice in supporting children when invited to join a clinical trial. We audio-recorded qualitative, semi-structured interviews with 22 children aged 8-16 years about being invited to take part in a clinical trial. Most children were interviewed with their parents. Analysis of the transcribed interviews examined the content of participants' accounts thematically, whilst also drawing on principles of discourse analysis, which examines how individuals use talk to achieve certain effects or social practices. It was not possible to separate children's knowledge of the clinical trial, or their decision-making processes from that of their parents, with parents taking a substantial mediating role in producing their children's decisions. Decision-making gradually unfolded across time and events and was interwoven within the family context, rather than happening in one moment or in the clinical setting. Whilst children valued their parents' role, a case study of child-parent disagreement indicated how children can struggle to be heard. Decisions happen within a process of family dynamics, in contrast to ideas of assent that isolate it from this context. Parents have a substantial role in children's decisions, and thus how families come to provide consent. Reflecting this we argue that assent practices need to focus on supporting parents to support their children in learning and deliberating about trials. However, this needs to be accompanied by practitioners being alert to the possibility of divergence in child and parent views and enabling children's perspectives to be heard. © 2016 The Authors. Child: Care, Health and Development published by John Wiley & Sons Ltd.

  9. A service oriented approach for guidelines-based clinical decision support using BPMN.

    Science.gov (United States)

    Rodriguez-Loya, Salvador; Aziz, Ayesha; Chatwin, Chris

    2014-01-01

    Evidence-based medical practice requires that clinical guidelines need to be documented in such a way that they represent a clinical workflow in its most accessible form. In order to optimize clinical processes to improve clinical outcomes, we propose a Service Oriented Architecture (SOA) based approach for implementing clinical guidelines that can be accessed from an Electronic Health Record (EHR) application with a Web Services enabled communication mechanism with the Enterprise Service Bus. We have used Business Process Modelling Notation (BPMN) for modelling and presenting the clinical pathway in the form of a workflow. The aim of this study is to produce spontaneous alerts in the healthcare workflow in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD). The use of BPMN as a tool to automate clinical guidelines has not been previously employed for providing Clinical Decision Support (CDS).

  10. Weighing Clinical Evidence Using Patient Preferences: An Application of Probabilistic Multi-Criteria Decision Analysis.

    Science.gov (United States)

    Broekhuizen, Henk; IJzerman, Maarten J; Hauber, A Brett; Groothuis-Oudshoorn, Catharina G M

    2017-03-01

    The need for patient engagement has been recognized by regulatory agencies, but there is no consensus about how to operationalize this. One approach is the formal elicitation and use of patient preferences for weighing clinical outcomes. The aim of this study was to demonstrate how patient preferences can be used to weigh clinical outcomes when both preferences and clinical outcomes are uncertain by applying a probabilistic value-based multi-criteria decision analysis (MCDA) method. Probability distributions were used to model random variation and parameter uncertainty in preferences, and parameter uncertainty in clinical outcomes. The posterior value distributions and rank probabilities for each treatment were obtained using Monte-Carlo simulations. The probability of achieving the first rank is the probability that a treatment represents the highest value to patients. We illustrated our methodology for a simplified case on six HIV treatments. Preferences were modeled with normal distributions and clinical outcomes were modeled with beta distributions. The treatment value distributions showed the rank order of treatments according to patients and illustrate the remaining decision uncertainty. This study demonstrated how patient preference data can be used to weigh clinical evidence using MCDA. The model takes into account uncertainty in preferences and clinical outcomes. The model can support decision makers during the aggregation step of the MCDA process and provides a first step toward preference-based personalized medicine, yet requires further testing regarding its appropriate use in real-world settings.

  11. A Stochastic and Holistic Method to Support Decision-Making in Early Building Design

    DEFF Research Database (Denmark)

    Østergaard, Torben; Maagaard, Steffen; Jensen, Rasmus Lund

    2015-01-01

    The use of holistic certification tools is increasing and requirements in legislation are continuously being tightened. This calls for a holistic simulation approach in the early design phase where input uncertainties are large and decisions are crucial to the performance. An iterative parametric...... method is proposed: 1) Assign uniform distributions to uncertain design inputs of interest; 2) Perform sensitivity analysis (SA) by the method of Morris to rank input by relative importance; 3) Run Monte Carlo simulations to explore the entire design domain; 4) Apply Monte Carlo filtering to identify...

  12. Clinical trial or standard treatment? Shared decision making at the department of oncology

    DEFF Research Database (Denmark)

    Gregersen, Trine Ammentorp; Birkelund, Regner; Ammentorp, Jette

    2016-01-01

    Title: Clinical trial or standard treatment? Shared decision making at the department of oncology. Authors: Ph.d. student, Trine A. Gregersen. Trine.gregersen@rsyd.dk. Department of Oncology. Health Services Research Unit Lillebaelt Hospital / IRS University of Southern Denmark. Professor, Regner...... background is a Bachelor and Master of Science in Nursing. This project is my Ph.D. project which is supported by Region of Southern Denmark and Lillebaelt Hospital. The project started January 2016 and will be carried out at Department of Oncology at Vejle Hospital. Background Most cancer patients...... that they are participating in a trial. This place great demand on the healthcare providers’ ability to involve and advise patients in the decisions. The aim of this study is to investigate the characteristics of the communication when decisions about participation in clinical oncology trial are made and the patients...

  13. Mobile clinical decision support systems and applications: a literature and commercial review.

    Science.gov (United States)

    Martínez-Pérez, Borja; de la Torre-Díez, Isabel; López-Coronado, Miguel; Sainz-de-Abajo, Beatriz; Robles, Montserrat; García-Gómez, Juan Miguel

    2014-01-01

    The latest advances in eHealth and mHealth have propitiated the rapidly creation and expansion of mobile applications for health care. One of these types of applications are the clinical decision support systems, which nowadays are being implemented in mobile apps to facilitate the access to health care professionals in their daily clinical decisions. The aim of this paper is twofold. Firstly, to make a review of the current systems available in the literature and in commercial stores. Secondly, to analyze a sample of applications in order to obtain some conclusions and recommendations. Two reviews have been done: a literature review on Scopus, IEEE Xplore, Web of Knowledge and PubMed and a commercial review on Google play and the App Store. Five applications from each review have been selected to develop an in-depth analysis and to obtain more information about the mobile clinical decision support systems. Ninety-two relevant papers and 192 commercial apps were found. Forty-four papers were focused only on mobile clinical decision support systems. One hundred seventy-one apps were available on Google play and 21 on the App Store. The apps are designed for general medicine and 37 different specialties, with some features common in all of them despite of the different medical fields objective. The number of mobile clinical decision support applications and their inclusion in clinical practices has risen in the last years. However, developers must be careful with their interface or the easiness of use, which can impoverish the experience of the users.

  14. The role of emotion in clinical decision making: an integrative literature review.

    Science.gov (United States)

    Kozlowski, Desirée; Hutchinson, Marie; Hurley, John; Rowley, Joanne; Sutherland, Joanna

    2017-12-15

    Traditionally, clinical decision making has been perceived as a purely rational and cognitive process. Recently, a number of authors have linked emotional intelligence (EI) to clinical decision making (CDM) and calls have been made for an increased focus on EI skills for clinicians. The objective of this integrative literature review was to identify and synthesise the empirical evidence for a role of emotion in CDM. A systematic search of the bibliographic databases PubMed, PsychINFO, and CINAHL (EBSCO) was conducted to identify empirical studies of clinician populations. Search terms were focused to identify studies reporting clinician emotion OR clinician emotional intelligence OR emotional competence AND clinical decision making OR clinical reasoning. Twenty three papers were retained for synthesis. These represented empirical work from qualitative, quantitative, and mixed-methods approaches and comprised work with a focus on experienced emotion and on skills associated with emotional intelligence. The studies examined nurses (10), physicians (7), occupational therapists (1), physiotherapists (1), mixed clinician samples (3), and unspecified infectious disease experts (1). We identified two main themes in the context of clinical decision making: the subjective experience of emotion; and, the application of emotion and cognition in CDM. Sub-themes under the subjective experience of emotion were: emotional response to contextual pressures; emotional responses to others; and, intentional exclusion of emotion from CDM. Under the application of emotion and cognition in CDM, sub-themes were: compassionate emotional labour - responsiveness to patient emotion within CDM; interdisciplinary tension regarding the significance and meaning of emotion in CDM; and, emotion and moral judgement. Clinicians' experienced emotions can and do affect clinical decision making, although acknowledgement of that is far from universal. Importantly, this occurs in the in the absence of a

  15. GOFC-GOLD/LCLUC/START Regional Networking: building capacity for science and decision-making.

    Science.gov (United States)

    Justice, C. O.; Vadrevu, K.; Gutman, G.

    2016-12-01

    Over the past 20 years, the international GOFC-GOLD Program and START, with core funding from the NASA LCLUC program and ESA have been developing regional networks of scientists and data users for scientific capacity building and sharing experience in the use and application of Earth Observation data. Regional networks connect scientists from countries with similar environmental and social issues and often with shared water and airsheds. Through periodic regional workshops, regional and national projects are showcased and national priorities and policy drivers are articulated. The workshops encourage both north-south and south-south exchange and collaboration. The workshops are multi-sponsored and each include a training component, targeting early career scientists and data users from the region. The workshops provide an opportunity for regional scientists to publish in peer-reviewed special editions focused on regional issues. Currently, the NASA LCLUC program funded "South and Southeast Asia Regional Initiative (SARI)" team is working closely with the USAID/NASA SERVIR program to implement some capacity building and training activities jointly in south/southeast Asian countries to achieve maximum benefit.

  16. Improving Emergency Department Triage Classification with Computerized Clinical Decision Support at a Pediatric Hospital

    Science.gov (United States)

    Kunisch, Joseph Martin

    2012-01-01

    Background: The Emergency Severity Index (ESI) is an emergency department (ED) triage classification system based on estimated patient-specific resource utilization. Rules for a computerized clinical decision support (CDS) system based on a patient's chief complaint were developed and tested using a stochastic model for predicting ESI scores.…

  17. Teaching metacognition in clinical decision-making using a novel mnemonic checklist: an exploratory study.

    Science.gov (United States)

    Chew, Keng Sheng; Durning, Steven J; van Merriënboer, Jeroen Jg

    2016-12-01

    Metacognition is a cognitive debiasing strategy that clinicians can use to deliberately detach themselves from the immediate context of a clinical decision, which allows them to reflect upon the thinking process. However, cognitive debiasing strategies are often most needed when the clinician cannot afford the time to use them. A mnemonic checklist known as TWED (T = threat, W = what else, E = evidence and D = dispositional factors) was recently created to facilitate metacognition. This study explores the hypothesis that the TWED checklist improves the ability of medical students to make better clinical decisions. Two groups of final-year medical students from Universiti Sains Malaysia, Malaysia, were recruited to participate in this quasi-experimental study. The intervention group (n = 21) received educational intervention that introduced the TWED checklist, while the control group (n = 19) received a tutorial on basic electrocardiography. Post-intervention, both groups received a similar assessment on clinical decision-making based on five case scenarios. The mean score of the intervention group was significantly higher than that of the control group (18.50 ± 4.45 marks vs. 12.50 ± 2.84 marks, p < 0.001). In three of the five case scenarios, students in the intervention group obtained higher scores than those in the control group. The results of this study support the use of the TWED checklist to facilitate metacognition in clinical decision-making.

  18. Competencies in nursing students for organized forms of clinical moral deliberation and decision-making

    NARCIS (Netherlands)

    dr. Bart Cusveller; Jeanette den Uil-Westerlaken

    2014-01-01

    Bachelor-prepared nurses are expected to be competent in moral deliberation and decision-making (MDD) in clinical practice. It is unclear, however, how this competence develops in nursing students. This study explores the development of nursing students’ competence for participating in organized

  19. Forms of Knowledge Incorporated in Clinical Decision-making among Newly-Graduated Nurses: A Metasynthesis

    DEFF Research Database (Denmark)

    Voldbjerg, Siri; Elgaard Sørensen, Erik; Grønkjær, Mette

    2014-01-01

    the knowledge that informs clinical decision-making among newly-graduated nurses. Qualitative studies were retrieved from CINAHL, PubMed, SCOPE, ERIC and GOOGLE-Scholar and subsequently selected by pre-defined inclusion criteria and critically appraised using CASP. Metaphors identified in the analytical process...

  20. Decision-tree induction to detect clinical mastitis with automatic milking

    NARCIS (Netherlands)

    Kamphuis, C.; Mollenhorst, H.; Feelders, A.; Pietersma, D.; Hogeveen, H.

    2010-01-01

    a b s t r a c t This study explored the potential of using decision-tree induction to develop models for the detection of clinical mastitis with automatic milking. Sensor data (including electrical conductivity and colour) of over 711,000 quarter milkings were collected from December 2006 till

  1. Clinical decision-making to facilitate appropriate patient management in chiropractic practice: 'the 3-questions model'

    Directory of Open Access Journals (Sweden)

    Amorin-Woods Lyndon G

    2012-03-01

    Full Text Available Abstract Background A definitive diagnosis in chiropractic clinical practice is frequently elusive, yet decisions around management are still necessary. Often, a clinical impression is made after the exclusion of serious illness or injury, and care provided within the context of diagnostic uncertainty. Rather than focussing on labelling the condition, the clinician may choose to develop a defendable management plan since the response to treatment often clarifies the diagnosis. Discussion This paper explores the concept and elements of defensive problem-solving practice, with a view to developing a model of agile, pragmatic decision-making amenable to real-world application. A theoretical framework that reflects the elements of this approach will be offered in order to validate the potential of a so called '3-Questions Model'; Summary Clinical decision-making is considered to be a key characteristic of any modern healthcare practitioner. It is, thus, prudent for chiropractors to re-visit the concept of defensible practice with a view to facilitate capable clinical decision-making and competent patient examination skills. In turn, the perception of competence and trustworthiness of chiropractors within the wider healthcare community helps integration of chiropractic services into broader healthcare settings.

  2. Competencies in nursing students for organized forms of clinical moral deliberation and decision-making

    NARCIS (Netherlands)

    Jeanette den Uil-Westerlaken; dr. Bart Cusveller

    2013-01-01

    Bachelor-prepared nurses are expected to be competent in moral deliberation and decision-making (MDD) in clinical practice. It is unclear, however, how this competence develops in nursing students. This study explores the development of nursing students’ competence for participating in organized

  3. Clinical Decision Support Tools for Selecting Interventions for Patients with Disabling Musculoskeletal Disorders

    DEFF Research Database (Denmark)

    Gross, Douglas P; Armijo-Olivo, Susan; Shaw, William S

    2016-01-01

    Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders. Methods We used Arksey and O'Malley's scoping review framework which progresses through five stages: (1) identifyin...

  4. Computer-based clinical decision aids. A review of methods and assessment of systems

    NARCIS (Netherlands)

    Reisman, Y

    1996-01-01

    During the last three decades a great deal of research has been devoted to the development of integrated clinical decision support systems. This report aims to give a basic understanding of what is required for such a system. By means of a large literature study a survey is given of the major

  5. Knowledge of risk factors and the periodontal disease-systemic link in dental students' clinical decisions.

    Science.gov (United States)

    Friesen, Lynn Roosa; Walker, Mary P; Kisling, Rebecca E; Liu, Ying; Williams, Karen B

    2014-09-01

    This study evaluated second-, third-, and fourth-year dental students' ability to identify systemic conditions associated with periodontal disease, risk factors most important for referral, and medications with an effect on the periodontium and their ability to apply this knowledge to make clinical decisions regarding treatment and referral of periodontal patients. A twenty-one question survey was administered at one U.S. dental school in the spring semester of 2012 to elicit the students' knowledge and confidence regarding clinical reasoning. The response rate was 86 percent. Periodontal risk factors were accurately selected by at least 50 percent of students in all three classes; these were poorly controlled diabetes, ≥6 mm pockets posteriorly, and lack of response to previous non-surgical therapy. Confidence in knowledge, knowledge of risk factors, and knowledge of medications with an effect on the periodontium improved with training and were predictive of better referral decision making. The greatest impact of training was seen on the students' ability to make correct decisions about referral and treatment for seven clinical scenarios. Although the study found a large increase in the students' abilities from the second through fourth years, the mean of 4.6 (out of 7) for the fourth-year students shows that, on average, those students missed correct treatment or referral on more than two of seven clinical cases. These results suggest that dental curricula should emphasize more critical decision making with respect to referral and treatment criteria in managing the periodontal patient.

  6. Advances in Clinical Decision Support: Highlights of Practice and the Literature 2015-2016.

    Science.gov (United States)

    Jenders, R A

    2017-08-01

    Introduction: Advances in clinical decision support (CDS) continue to evolve to support the goals of clinicians, policymakers, patients and professional organizations to improve clinical practice, patient safety, and the quality of care. Objectives: Identify key thematic areas or foci in research and practice involving clinical decision support during the 2015-2016 time period. Methods: Thematic analysis consistent with a grounded theory approach was applied in a targeted review of journal publications, the proceedings of key scientific conferences as well as activities in standards development organizations in order to identify the key themes underlying work related to CDS. Results: Ten key thematic areas were identified, including: 1) an emphasis on knowledge representation, with a focus on clinical practice guidelines; 2) various aspects of precision medicine, including the use of sensor and genomic data as well as big data; 3) efforts in quality improvement; 4) innovative uses of computer-based provider order entry (CPOE) systems, including relevant data displays; 5) expansion of CDS in various clinical settings; 6) patient-directed CDS; 7) understanding the potential negative impact of CDS; 8) obtaining structured data to drive CDS interventions; 9) the use of diagnostic decision support; and 10) the development and use of standards for CDS. Conclusions: Active research and practice in 2015-2016 continue to underscore the importance and broad utility of CDS for effecting change and improving the quality and outcome of clinical care. Georg Thieme Verlag KG Stuttgart.

  7. Strengthening national decision-making on immunization by building capacity for economic evaluation: Implementing ProVac in Europe.

    Science.gov (United States)

    Blau, Julia; Hoestlandt, Céline; D Clark, Andrew; Baxter, Louise; Felix Garcia, Ana Gabriela; Mounaud, Bérénice; Mosina, Liudmila

    2015-05-07

    -vaccine economic analysis, review of local evidence, recommending key data inputs, and support in presenting results to national decision makers. National cost-effectiveness studies were conducted in four countries: Albania (rotavirus vaccine [RV]), Azerbaijan (pneumococcal conjugate vaccine [PCV]), Croatia (PCV), and Georgia (PCV). All four countries improved their estimates of the burden of disease preventable by the new vaccines. National advisory bodies and ministries of health obtained economic evidence that helped Albania and Croatia to make decisions on introducing the new vaccines. Azerbaijan and Georgia used economic evidence to confirm previously made preliminary decisions to introduce PCV and make corresponding financial commitments. The study helped Albania to obtain access to affordable prices for rotavirus vaccines through participation in the UNICEF procurement mechanism for middle-income countries. Croatia was able to define the PCV price that would make its introduction cost-effective, and can use this figure as a basis for price negotiations. Despite some challenges due to competing national priorities, tight budgets for immunization, and lack of available national data, the ProVac IWG helped to build capacity of national health professionals, support decision-making for the introduction of new vaccines, and promote utilization of economic evidence for making decisions on immunization. This type of strong collaboration among international partners and countries should be scaled up, given that many other countries in the WHO European Region have expressed interest in receiving assistance from the ProVac IWG. Copyright © 2015. Published by Elsevier Ltd.

  8. Building of Reusable Reverse Logistics Model and its Optimization Considering the Decision of Backorder or Next Arrival of Goods

    Science.gov (United States)

    Lee, Jeong-Eun; Gen, Mitsuo; Rhee, Kyong-Gu; Lee, Hee-Hyol

    This paper deals with the building of the reusable reverse logistics model considering the decision of the backorder or the next arrival of goods. The optimization method to minimize the transportation cost and to minimize the volume of the backorder or the next arrival of goods occurred by the Just in Time delivery of the final delivery stage between the manufacturer and the processing center is proposed. Through the optimization algorithms using the priority-based genetic algorithm and the hybrid genetic algorithm, the sub-optimal delivery routes are determined. Based on the case study of a distilling and sale company in Busan in Korea, the new model of the reusable reverse logistics of empty bottles is built and the effectiveness of the proposed method is verified.

  9. Integrating individual trip planning in energy efficiency – Building decision tree models for Danish fisheries

    DEFF Research Database (Denmark)

    Bastardie, Francois; Nielsen, J. Rasmus; Andersen, Bo Sølgaard

    2013-01-01

    Danish fishermen have provided information on dynamics in their fuel consumption, running costs, and fishing patterns through a web-based questionnaire. This detailed documentation of the fishing practices is used in spatial modelling tools to improve advice and research for fisheries. The tools...... integrate detailed information on vessel distribution, catch and fuel consumption for different fisheries with a detailed resource distribution of targeted stocks from research surveys to evaluate the optimum consumption and efficiency to reduce fuel costs and the costs of displacement of effort. The energy...... efficiency for the value of catch per unit of fuel consumed is analysed by merging the questionnaire, logbook and VMS (vessel monitoring system) information. Logic decision trees and conditional behaviour probabilities are established from the responses of fishermen regarding a range of sequential...

  10. Actionable knowledge and strategic decision making for bio- and agroterrorism threats: building a collaborative early warning culture.

    Science.gov (United States)

    Mårtensson, Per-Åke; Hedström, Lars; Sundelius, Bengt; Skiby, Jeffrey E; Elbers, Armin; Knutsson, Rickard

    2013-09-01

    Current trends in biosecurity and cybersecurity include (1) the wide availability of technology and specialized knowledge that previously were available only to governments; (2) the global economic recession, which may increase the spread of radical non-state actors; and (3) recent US and EU commission reports that reflect concerns about non-state actors in asymmetric threats. The intersectoral and international nature of bioterrorism and agroterrorism threats requires collaboration across several sectors including intelligence, police, forensics, customs, and other law enforcement organizations who must work together with public and animal health organizations as well as environmental and social science organizations. This requires coordinated decision making among these organizations, based on actionable knowledge and information sharing. The risk of not sharing information among organizations compared to the benefit of sharing information can be considered in an "information sharing risk-benefit analysis" to prevent a terrorism incident from occurring and to build a rapid response capability. In the EU project AniBioThreat, early warning is the main topic in work package 3 (WP 3). A strategy has been generated based on an iterative approach to bring law enforcement agencies and human and animal health institutes together. Workshops and exercises have taken place during the first half of the project, and spin-off activities include new preparedness plans for institutes and the formation of a legal adviser network for decision making. In addition, a seminar on actionable knowledge was held in Stockholm, Sweden, in 2012, which identified the need to bring various agency cultures together to work on developing a resilient capability to identify early signs of bio- and agroterrorism threats. The seminar concluded that there are a number of challenges in building a collaborative culture, including developing an education program that supports collaboration and shared

  11. Life Cycle Assessment and Optimization-Based Decision Analysis of Construction Waste Recycling for a LEED-Certified University Building

    Directory of Open Access Journals (Sweden)

    Murat Kucukvar

    2016-01-01

    Full Text Available The current waste management literature lacks a comprehensive LCA of the recycling of construction materials that considers both process and supply chain-related impacts as a whole. Furthermore, an optimization-based decision support framework has not been also addressed in any work, which provides a quantifiable understanding about the potential savings and implications associated with recycling of construction materials from a life cycle perspective. The aim of this research is to present a multi-criteria optimization model, which is developed to propose economically-sound and environmentally-benign construction waste management strategies for a LEED-certified university building. First, an economic input-output-based hybrid life cycle assessment model is built to quantify the total environmental impacts of various waste management options: recycling, conventional landfilling and incineration. After quantifying the net environmental pressures associated with these waste treatment alternatives, a compromise programming model is utilized to determine the optimal recycling strategy considering environmental and economic impacts, simultaneously. The analysis results show that recycling of ferrous and non-ferrous metals significantly contributed to reductions in the total carbon footprint of waste management. On the other hand, recycling of asphalt and concrete increased the overall carbon footprint due to high fuel consumption and emissions during the crushing process. Based on the multi-criteria optimization results, 100% recycling of ferrous and non-ferrous metals, cardboard, plastic and glass is suggested to maximize the environmental and economic savings, simultaneously. We believe that the results of this research will facilitate better decision making in treating construction and debris waste for LEED-certified green buildings by combining the results of environmental LCA with multi-objective optimization modeling.

  12. Biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics.

    Science.gov (United States)

    Kuru, Kaya; Niranjan, Mahesan; Tunca, Yusuf; Osvank, Erhan; Azim, Tayyaba

    2014-10-01

    In general, medical geneticists aim to pre-diagnose underlying syndromes based on facial features before performing cytological or molecular analyses where a genotype-phenotype interrelation is possible. However, determining correct genotype-phenotype interrelationships among many syndromes is tedious and labor-intensive, especially for extremely rare syndromes. Thus, a computer-aided system for pre-diagnosis can facilitate effective and efficient decision support, particularly when few similar cases are available, or in remote rural districts where diagnostic knowledge of syndromes is not readily available. The proposed methodology, visual diagnostic decision support system (visual diagnostic DSS), employs machine learning (ML) algorithms and digital image processing techniques in a hybrid approach for automated diagnosis in medical genetics. This approach uses facial features in reference images of disorders to identify visual genotype-phenotype interrelationships. Our statistical method describes facial image data as principal component features and diagnoses syndromes using these features. The proposed system was trained using a real dataset of previously published face images of subjects with syndromes, which provided accurate diagnostic information. The method was tested using a leave-one-out cross-validation scheme with 15 different syndromes, each of comprised 5-9 cases, i.e., 92 cases in total. An accuracy rate of 83% was achieved using this automated diagnosis technique, which was statistically significant (p<0.01). Furthermore, the sensitivity and specificity values were 0.857 and 0.870, respectively. Our results show that the accurate classification of syndromes is feasible using ML techniques. Thus, a large number of syndromes with characteristic facial anomaly patterns could be diagnosed with similar diagnostic DSSs to that described in the present study, i.e., visual diagnostic DSS, thereby demonstrating the benefits of using hybrid image processing

  13. A deliberative framework to identify the need for real-life evidence building of new cancer drugs after interim funding decision.

    Science.gov (United States)

    Leung, Leanne; de Lemos, Mário L; Kovacic, Laurel

    2017-01-01

    Background With the rising cost of new oncology treatments, it is no longer sustainable to base initial drug funding decisions primarily on prospective clinical trials as their performance in real-life populations are often difficult to determine. In British Columbia, an approach in evidence building is to retrospectively analyse patient outcomes using observational research on an ad hoc basis. Methods The deliberative framework was constructed in three stages: framework design, framework validation and treatment programme characterization, and key informant interview. Framework design was informed through a literature review and analyses of provincial and national decision-making processes. Treatment programmes funded between 2010 and 2013 were used for framework validation. A selection concordance rate of 80% amongst three reviewers was considered to be a validation of the framework. Key informant interviews were conducted to determine the utility of this deliberative framework. Results A multi-domain deliberative framework with 15 assessment parameters was developed. A selection concordance rate of 84.2% was achieved for content validation of the framework. Nine treatment programmes from five different tumour groups were selected for retrospective outcomes analysis. Five contributory factors to funding uncertainties were identified. Key informants agreed that the framework is a comprehensive tool that targets the key areas involved in the funding decision-making process. Conclusions The oncology-based deliberative framework can be routinely used to assess treatment programmes from the major tumour sites for retrospective outcomes analysis. Key informants indicate this is a value-added tool and will provide insight to the current prospective funding model.

  14. Clinical Decision Support Reduces Overuse of Red Blood Cell Transfusions: Interrupted Time Series Analysis.

    Science.gov (United States)

    Kassakian, Steven Z; Yackel, Thomas R; Deloughery, Thomas; Dorr, David A

    2016-06-01

    Red blood cell transfusion is the most common procedure in hospitalized patients in the US. Growing evidence suggests that a sizeable percentage of these transfusions are inappropriate, putting patients at significant risk and increasing costs to the health care system. We performed a retrospective quasi-experimental study from November 2008 until November 2014 in a 576-bed tertiary care hospital. The intervention consisted of an interruptive clinical decision support alert shown to a provider when a red blood cell transfusion was ordered in a patient whose most recent hematocrit was ≥21%. We used interrupted time series analysis to determine whether our primary outcome of interest, rate of red blood cell transfusion in patients with hematocrit ≥21% per 100 patient (pt) days, was reduced by the implementation of the clinical decision support tool. The rate of platelet transfusions was used as a nonequivalent dependent control variable. A total of 143,000 hospital admissions were included in our analysis. Red blood cell transfusions decreased from 9.4 to 7.8 per 100 pt days after the clinical decision support intervention was implemented. Interrupted time series analysis showed that significant decline of 0.05 (95% confidence interval [CI], 0.03-0.07; P clinical decision support tool. There was no statistical change in the rate of platelet transfusion resulting from the intervention. The implementation of an evidence-based clinical decision support tool was associated with a significant decline in the overuse of red blood cell transfusion. We believe this intervention could be easily replicated in other hospitals using commercial electronic health records and a similar reduction in overuse of red blood cell transfusions achieved. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Clinical decision support must be useful, functional is not enough: a qualitative study of computer-based clinical decision support in primary care.

    Science.gov (United States)

    Kortteisto, Tiina; Komulainen, Jorma; Mäkelä, Marjukka; Kunnamo, Ilkka; Kaila, Minna

    2012-10-08

    Health information technology, particularly electronic decision support systems, can reduce the existing gap between evidence-based knowledge and health care practice but professionals have to accept and use this information. Evidence is scant on which features influence the use of computer-based clinical decision support (eCDS) in primary care and how different professional groups experience it. Our aim was to describe specific reasons for using or not using eCDS among primary care professionals. The setting was a Finnish primary health care organization with 48 professionals receiving patient-specific guidance at the point of care. Multiple data (focus groups, questionnaire and spontaneous feedback) were analyzed using deductive content analysis and descriptive statistics. The content of the guidance is a significant feature of the primary care professional's intention to use eCDS. The decisive reason for using or not using the eCDS is its perceived usefulness. Functional characteristics such as speed and ease of use are important but alone these are not enough. Specific information technology, professional, patient and environment features can help or hinder the use. Primary care professionals have to perceive eCDS guidance useful for their work before they use it.

  16. Understanding clinical work practices for cross-boundary decision support in e-health.

    Science.gov (United States)

    Tawfik, Hissam; Anya, Obinna; Nagar, Atulya K

    2012-07-01

    One of the major concerns of research in integrated healthcare information systems is to enable decision support among clinicians across boundaries of organizations and regional workgroups. A necessary precursor, however, is to facilitate the construction of appropriate awareness of local clinical practices, including a clinician's actual cognitive capabilities, peculiar workplace circumstances, and specific patient-centered needs based on real-world clinical contexts across work settings. In this paper, a user-centered study aimed to investigate clinical practices across three different geographical areas-the U.K., the UAE and Nigeria-is presented. The findings indicate that differences in clinical practices among clinicians are associated with differences in local work contexts across work settings, but are moderated by adherence to best practice guidelines and the need for patient-centered care. The study further reveals that an awareness especially of the ontological, stereotypical, and situated practices plays a crucial role in adapting knowledge for cross-boundary decision support. The paper then outlines a set of design guidelines for the development of enterprise information systems for e-health. Based on the guidelines, the paper proposes the conceptual design of CaDHealth, a practice-centered framework for making sense of clinical practices across work settings for effective cross-boundary e-health decision support.

  17. Advancing clinical decision support using lessons from outside of healthcare: an interdisciplinary systematic review

    Directory of Open Access Journals (Sweden)

    Wu Helen W

    2012-08-01

    Full Text Available Abstract Background Greater use of computerized decision support (DS systems could address continuing safety and quality problems in healthcare, but the healthcare field has struggled to implement DS technology. This study surveys DS experience across multiple non-healthcare disciplines for new insights that are generalizable to healthcare provider decisions. In particular, it sought design principles and lessons learned from the other disciplines that could inform efforts to accelerate the adoption of clinical decision support (CDS. Methods Our systematic review drew broadly from non-healthcare databases in the basic sciences, social sciences, humanities, engineering, business, and defense: PsychINFO, BusinessSource Premier, Social Sciences Abstracts, Web of Science, and Defense Technical Information Center. Because our interest was in DS that could apply to clinical decisions, we selected articles that (1 provided a review, overview, discussion of lessons learned, or an evaluation of design or implementation aspects of DS within a non-healthcare discipline and (2 involved an element of human judgment at the individual level, as opposed to decisions that can be fully automated or that are made at the organizational level. Results Clinical decisions share some similarities with decisions made by military commanders, business managers, and other leaders: they involve assessing new situations and choosing courses of action with major consequences, under time pressure, and with incomplete information. We identified seven high-level DS system design features from the non-healthcare literature that could be applied to CDS: providing broad, system-level perspectives; customizing interfaces to specific users and roles; making the DS reasoning transparent; presenting data effectively; generating multiple scenarios covering disparate outcomes (e.g., effective; effective with side effects; ineffective; allowing for contingent adaptations; and facilitating

  18. Advancing clinical decision support using lessons from outside of healthcare: an interdisciplinary systematic review.

    Science.gov (United States)

    Wu, Helen W; Davis, Paul K; Bell, Douglas S

    2012-08-17

    Greater use of computerized decision support (DS) systems could address continuing safety and quality problems in healthcare, but the healthcare field has struggled to implement DS technology. This study surveys DS experience across multiple non-healthcare disciplines for new insights that are generalizable to healthcare provider decisions. In particular, it sought design principles and lessons learned from the other disciplines that could inform efforts to accelerate the adoption of clinical decision support (CDS). Our systematic review drew broadly from non-healthcare databases in the basic sciences, social sciences, humanities, engineering, business, and defense: PsychINFO, BusinessSource Premier, Social Sciences Abstracts, Web of Science, and Defense Technical Information Center. Because our interest was in DS that could apply to clinical decisions, we selected articles that (1) provided a review, overview, discussion of lessons learned, or an evaluation of design or implementation aspects of DS within a non-healthcare discipline and (2) involved an element of human judgment at the individual level, as opposed to decisions that can be fully automated or that are made at the organizational level. Clinical decisions share some similarities with decisions made by military commanders, business managers, and other leaders: they involve assessing new situations and choosing courses of action with major consequences, under time pressure, and with incomplete information. We identified seven high-level DS system design features from the non-healthcare literature that could be applied to CDS: providing broad, system-level perspectives; customizing interfaces to specific users and roles; making the DS reasoning transparent; presenting data effectively; generating multiple scenarios covering disparate outcomes (e.g., effective; effective with side effects; ineffective); allowing for contingent adaptations; and facilitating collaboration. The article provides examples of

  19. Neighborhood graph and learning discriminative distance functions for clinical decision support.

    Science.gov (United States)

    Tsymbal, Alexey; Zhou, Shaohua Kevin; Huber, Martin

    2009-01-01

    There are two essential reasons for the slow progress in the acceptance of clinical case retrieval and similarity search-based decision support systems; the especial complexity of clinical data making it difficult to define a meaningful and effective distance function on them and the lack of transparency and explanation ability in many existing clinical case retrieval decision support systems. In this paper, we try to address these two problems by introducing a novel technique for visualizing inter-patient similarity based on a node-link representation with neighborhood graphs and by considering two techniques for learning discriminative distance function that help to combine the power of strong "black box" learners with the transparency of case retrieval and nearest neighbor classification.

  20. Factors associated with clinical decision-making in relation to treatment need for temporomandibular disorders.

    Science.gov (United States)

    Yekkalam, Negin; Wänman, Anders

    2016-01-01

    The aim of this study was to analyze dentist's clinical decision-making related to treatment need for temporomandibular disorders (TMD) in an adult population. The study population comprised 779 randomly selected 35, 50, 65 and 75 year old individuals living in the county of Västerbotten, Sweden. The participants filled out a questionnaire and were examined clinically according to a structured protocol. The four examiners (two men, two women) were experienced dentists and were calibrated before the start of the study. After examination they individually assessed the need of treatment owing to TMD. In total, 15% of the study population was considered to have a treatment need owing to TMD. The highest estimate was noted for 35 and 50 years old women and the lowest for 65 and 75 years old men. Overall, 21% of the women and 8% of the men were considered to have a treatment need owing to TMD, with statistically significant differences between men and women for the 35 and 50 years old groups. Inter-individual variations in dentists' decisions were observed. In a multivariate analysis, female gender, signs and symptoms of TMD pain, signs and symptoms of TMD dysfunction and smoking were associated with estimated treatment need. The prevalence of estimated treatment need owing to TMD was fairly high, but the dentists' clinical decision-making process showed large inter-individual variability. The observation calls for further research on the factors affecting the decision-making process in care providers.

  1. Consensus Recommendations for Systematic Evaluation of Drug-Drug Interaction Evidence for Clinical Decision Support

    Science.gov (United States)

    Scheife, Richard T.; Hines, Lisa E.; Boyce, Richard D.; Chung, Sophie P.; Momper, Jeremiah; Sommer, Christine D.; Abernethy, Darrell R.; Horn, John; Sklar, Stephen J.; Wong, Samantha K.; Jones, Gretchen; Brown, Mary; Grizzle, Amy J.; Comes, Susan; Wilkins, Tricia Lee; Borst, Clarissa; Wittie, Michael A.; Rich, Alissa; Malone, Daniel C.

    2015-01-01

    Background Healthcare organizations, compendia, and drug knowledgebase vendors use varying methods to evaluate and synthesize evidence on drug-drug interactions (DDIs). This situation has a negative effect on electronic prescribing and medication information systems that warn clinicians of potentially harmful medication combinations. Objective To provide recommendations for systematic evaluation of evidence from the scientific literature, drug product labeling, and regulatory documents with respect to DDIs for clinical decision support. Methods A conference series was conducted to develop a structured process to improve the quality of DDI alerting systems. Three expert workgroups were assembled to address the goals of the conference. The Evidence Workgroup consisted of 15 individuals with expertise in pharmacology, drug information, biomedical informatics, and clinical decision support. Workgroup members met via webinar from January 2013 to February 2014. Two in-person meetings were conducted in May and September 2013 to reach consensus on recommendations. Results We developed expert-consensus answers to three key questions: 1) What is the best approach to evaluate DDI evidence?; 2) What evidence is required for a DDI to be applicable to an entire class of drugs?; and 3) How should a structured evaluation process be vetted and validated? Conclusion Evidence-based decision support for DDIs requires consistent application of transparent and systematic methods to evaluate the evidence. Drug information systems that implement these recommendations should be able to provide higher quality information about DDIs in drug compendia and clinical decision support tools. PMID:25556085

  2. Factors that influence the clinical decision making of physical therapists in choosing a balance assessment approach.

    Science.gov (United States)

    McGinnis, Patricia Q; Hack, Laurita M; Nixon-Cave, Kim; Michlovitz, Susan L

    2009-03-01

    Many methods for examining patients with balance deficits are supported by the literature. How or why therapists choose specific balance assessment methods during examination of patients remains unclear. The aims of this study were: (1) to explore decision making during examination of patients with balance deficits, (2) to understand the selection and use of assessment methods from the clinician's perspective, and (3) to explore why specific methods were selected. A qualitative design using a grounded theory approach permitted exploration of clinical decision making. Eleven therapists were purposefully selected (6 from outpatient offices, 5 from inpatient rehabilitation settings) to participate in repeated interviews. Credibility of the findings was established through low-inference data, member check, and triangulation among participants and multiple data sources. A highly individualized approach to patient examination based on therapists' practical knowledge emerged from the data, with limited influence of the literature. Movement observation was the primary assessment and diagnostic tool. When selecting assessment approaches for specific patients, the perceived value of information gathered mattered more than testing time. A 3-stage model of assessment decision making portrayed both the process and reasons influencing therapists' choices. In the context of the complex and busy nature of clinical practice, therapists gathered data that they considered meaningful during patient examination. The findings provide insight into factors influencing assessment decisions and suggest mechanisms to foster translation of research into clinical practice.

  3. Optimizing Clinical Decision Support in the Electronic Health Record. Clinical Characteristics Associated with the Use of a Decision Tool for Disposition of ED Patients with Pulmonary Embolism.

    Science.gov (United States)

    Ballard, Dustin W; Vemula, Ridhima; Chettipally, Uli K; Kene, Mamata V; Mark, Dustin G; Elms, Andrew K; Lin, James S; Reed, Mary E; Huang, Jie; Rauchwerger, Adina S; Vinson, David R

    2016-09-21

    Adoption of clinical decision support (CDS) tools by clinicians is often limited by workflow barriers. We sought to assess characteristics associated with clinician use of an electronic health record-embedded clinical decision support system (CDSS). In a prospective study on emergency department (ED) activation of a CDSS tool across 14 hospitals between 9/1/14 to 4/30/15, the CDSS was deployed at 10 active sites with an on-site champion, education sessions, iterative feedback, and up to 3 gift cards/clinician as an incentive. The tool was also deployed at 4 passive sites that received only an introductory educational session. Activation of the CDSS - which calculated the Pulmonary Embolism Severity Index (PESI) score and provided guidance - and associated clinical data were collected prospectively. We used multivariable logistic regression with random effects at provider/facility levels to assess the association between activation of the CDSS tool and characteristics at: 1) patient level (PESI score), 2) provider level (demographics and clinical load at time of activation opportunity), and 3) facility level (active vs. passive site, facility ED volume, and ED acuity at time of activation opportunity). Out of 662 eligible patient encounters, the CDSS was activated in 55%: active sites: 68% (346/512); passive sites 13% (20/150). In bivariate analysis, active sites had an increase in activation rates based on the number of prior gift cards the physician had received (96% if 3 prior cards versus 60% if 0, pscores I or II (compared to III or higher) were associated with higher likelihood of CDSS activation. Performing on-site tool promotion significantly increased odds of CDSS activation. Optimizing CDSS adoption requires active education.

  4. A method of building of decision trees based on data from wearable device during a rehabilitation of patients with tibia fractures

    Science.gov (United States)

    Kupriyanov, M. S.; Shukeilo, E. Y.; Shichkina, J. A.

    2015-11-01

    Nowadays technologies which are used in traumatology are a combination of mechanical, electronic, calculating and programming tools. Relevance of development of mobile applications for an expeditious data processing which are received from medical devices (in particular, wearable devices), and formulation of management decisions increases. Using of a mathematical method of building of decision trees for an assessment of a patient's health condition using data from a wearable device considers in this article.

  5. A method of building of decision trees based on data from wearable device during a rehabilitation of patients with tibia fractures

    Energy Technology Data Exchange (ETDEWEB)

    Kupriyanov, M. S., E-mail: mikhail.kupriyanov@gmail.com; Shukeilo, E. Y., E-mail: eyshukeylo@gmail.com; Shichkina, J. A., E-mail: strange.y@mail.ru [Saint Petersburg Electrotechnical University “LETI” (Russian Federation)

    2015-11-17

    Nowadays technologies which are used in traumatology are a combination of mechanical, electronic, calculating and programming tools. Relevance of development of mobile applications for an expeditious data processing which are received from medical devices (in particular, wearable devices), and formulation of management decisions increases. Using of a mathematical method of building of decision trees for an assessment of a patient’s health condition using data from a wearable device considers in this article.

  6. [A computerised clinical decision-support system for the management of depression in Primary Care].

    Science.gov (United States)

    Aragonès, Enric; Comín, Eva; Cavero, Myriam; Pérez, Víctor; Molina, Cristina; Palao, Diego

    Despite its clinical relevance and its importance as a public health problem, there are major gaps in the management of depression. Evidence-based clinical guidelines are useful to improve processes and clinical outcomes. In order to make their implementation easier these guidelines have been transformed into computerised clinical decision support systems. In this article, a description is presented on the basics and characteristics of a new computerised clinical guideline for the management of major depression, developed in the public health system in Catalonia. This tool helps the clinician to establish reliable and accurate diagnoses of depression, to choose the best treatment a priori according to the disease and the patient characteristics. It also emphasises the importance of systematic monitoring to assess the clinical course, and to adjust therapeutic interventions to the patient's needs at all times. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

  7. The utility of clinical decision tools for diagnosing osteoporosis in postmenopausal women with rheumatoid arthritis

    Directory of Open Access Journals (Sweden)

    Brand Caroline

    2008-01-01

    Full Text Available Abstract Background Patients with rheumatoid arthritis have a higher risk of low bone mineral density than normal age matched populations. There is limited evidence to support cost effectiveness of population screening in rheumatoid arthritis and case finding strategies have been proposed as a means to increase cost effectiveness of diagnostic screening for osteoporosis. This study aimed to assess the performance attributes of generic and rheumatoid arthritis specific clinical decision tools for diagnosing osteoporosis in a postmenopausal population with rheumatoid arthritis who attend ambulatory specialist rheumatology clinics. Methods A cross-sectional study of 127 ambulatory post-menopausal women with rheumatoid arthritis was performed. Patients currently receiving or who had previously received bone active therapy were excluded. Eligible women underwent clinical assessment and dual-energy-xray absorptiometry (DXA bone mineral density assessment. Clinical decision tools, including those specific for rheumatoid arthritis, were compared to seven generic post-menopausal tools to predict osteoporosis (defined as T score Results One hundred and twenty seven women participated. The median age was 62 (IQR 56–71 years. Median disease duration was 108 (60–168 months. Seventy two (57% women had no record of a previous DXA examination. Eighty (63% women had T scores at femoral neck or lumbar spine less than -1. The area under the ROC curve for clinical decision tool prediction of T score Conclusion There was limited utility of clinical decision tools for predicting osteoporosis in this patient population. Fracture prediction tools that include risk factors independent of BMD are needed.

  8. Using Life Cycle Assessment to Inform Decision-Making for Sustainable Buildings

    Directory of Open Access Journals (Sweden)

    Mieke Vandenbroucke

    2015-05-01

    Full Text Available Because the student residences of the Vrije Universiteit Brussel built in 1973 are not adapted to current comfort standards, the university decided to construct new accommodation facilities at the border of the campus. However, besides demolition, there was no strategy on how to deal with the existing ones. In the search for a more sustainable strategy, the university’s administration assigned the TRANSFORM research team to define various design strategies and to assess the long-term environmental consequences in order to select the best strategy by the use of Life Cycle Environmental Assessment. Current Life Cycle Environmental Assessments generally include maintenance, repair, replacement and operational energy consumption during use, but do not include future refurbishments. However, it is likely that their impact cannot be neglected either. Therefore, this article offers a framework which takes future refurbishments into account, in addition to the standard use impacts: initial and end-of-life impact. We report on the construction assemblies, the results of the assessments conducted and the advice provided. The results confirm that the impact of future refurbishments cannot be neglected. In addition, we observed that there were significant environmental savings when transforming the residences compared to new construction, and long-term benefits of a design enabling the reuse of building elements.

  9. Improving Decision Making about Genetic Testing in the Clinic: An Overview of Effective Knowledge Translation Interventions.

    Directory of Open Access Journals (Sweden)

    France Légaré

    Full Text Available Knowledge translation (KT interventions are attempts to change behavior in keeping with scientific evidence. While genetic tests are increasingly available to healthcare consumers in the clinic, evidence about their benefits is unclear and decisions about genetic testing are thus difficult for all parties.We sought to identify KT interventions that involved decisions about genetic testing in the clinical context and to assess their effectiveness for improving decision making in terms of behavior change, increased knowledge and wellbeing.We searched for trials assessing KT interventions in the context of genetic testing up to March 2014 in all systematic reviews (n = 153 published by two Cochrane review groups: Effective Practice and Organisation of Care (EPOC and Consumers and Communication.We retrieved 2473 unique trials of which we retained only 28 (1%. Two EPOC reviews yielded two trials of KT interventions: audit and feedback (n = 1 and educational outreach (n = 1. Both targeted health professionals and the KT intervention they assessed was found to be effective. Four Consumers and Communication reviews yielded 26 trials: decision aids (n = 15, communication of DNA-based disease risk estimates (n = 7, personalized risk communication (n = 3 and mobile phone messaging (n = 1. Among these, 25 trials targeted only health consumers or patients and the KT interventions were found to be effective in four trials, partly effective in seven, and ineffective in four. Lastly, only one trial targeted both physicians and patients and was found to be effective.More research on the effectiveness of KT interventions regarding genetic testing in the clinical context may contribute to patients making informed value-based decisions and drawing the maximum benefit from clinical applications of genetic and genomic innovations.

  10. Newly graduated nurses' use of knowledge sources in clinical decision-making: an ethnographic study.

    Science.gov (United States)

    Voldbjerg, Siri Lygum; Grønkjaer, Mette; Wiechula, Rick; Sørensen, Erik Elgaard

    2017-05-01

    To explore which knowledge sources newly graduated nurses' use in clinical decision-making and why and how they are used. In spite of an increased educational focus on skills and competencies within evidence-based practice, newly graduated nurses' ability to use components within evidence-based practice with a conscious and reflective use of research evidence has been described as being poor. To understand why, it is relevant to explore which other knowledge sources are used. This may shed light on why research evidence is sparsely used and ultimately inform approaches to strengthen the knowledgebase used in clinical decision-making. Ethnographic study using participant-observation and individual semistructured interviews of nine Danish newly graduated nurses in medical and surgical hospital settings. Newly graduates use of knowledge sources was described within three main structures: 'other', 'oneself' and 'gut feeling'. Educational preparation, transition into clinical practice and the culture of the setting influenced the knowledge sources used. The sources ranged from overt easily articulated knowledge sources to covert sources that were difficult to articulate. The limited articulation of certain sources inhibited the critical reflection on the reasoning behind decisions. Reflection is a prerequisite for an evidence-based practice where decisions should be transparent in order to consider if other evidentiary sources could be used. Although there is a complexity and variety to knowledge sources used, there is an imbalance with the experienced nurse playing a key role, functioning both as predominant source and a role model as to which sources are valued and used in clinical decision-making. If newly graduates are to be supported in an articulate and reflective use of a variety of sources, they have to be allocated to experienced nurses who model a reflective, articulate and balanced use of knowledge sources. © 2016 John Wiley & Sons Ltd.

  11. Development of a clinical decision support system for diabetes care: A pilot study.

    Directory of Open Access Journals (Sweden)

    Livvi Li Wei Sim

    Full Text Available Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard interface for displaying glycemic, lipid and renal function results, in an integrated form with decision support capabilities, based on local clinical practice guidelines. The clinical decision support system included a dashboard feature that graphically summarized all relevant laboratory results and displayed them in a color-coded system that allowed quick interpretation of the metabolic control of the patients. An alert module informs the user of tests that are due for repeat testing. An interactive graph module was also developed for better visual appreciation of the trends of the laboratory results of the patient. In a pilot study involving case scenarios administered via an electronic questionnaire, the Diabetes Dashboard, compared to the existing laboratory reporting interface, significantly improved the identification of abnormal laboratory results, of the long-term trend of the laboratory tests and of tests due for repeat testing. However, the Diabetes Dashboard did not significantly improve the identification of patients requiring treatment adjustment or the amount of time spent on each case scenario. In conclusion, we have developed and shown that the use of the Diabetes Dashboard, which incorporates several decision support features, can improve the management of diabetes. It is anticipated that this dashboard will be most helpful when deployed in an outpatient setting, where physicians can quickly make clinical decisions based on summarized information and be alerted to pertinent areas of care that require

  12. Development of a clinical decision support system for diabetes care: A pilot study.

    Science.gov (United States)

    Sim, Livvi Li Wei; Ban, Kenneth Hon Kim; Tan, Tin Wee; Sethi, Sunil Kumar; Loh, Tze Ping

    2017-01-01

    Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard) interface for displaying glycemic, lipid and renal function results, in an integrated form with decision support capabilities, based on local clinical practice guidelines. The clinical decision support system included a dashboard feature that graphically summarized all relevant laboratory results and displayed them in a color-coded system that allowed quick interpretation of the metabolic control of the patients. An alert module informs the user of tests that are due for repeat testing. An interactive graph module was also developed for better visual appreciation of the trends of the laboratory results of the patient. In a pilot study involving case scenarios administered via an electronic questionnaire, the Diabetes Dashboard, compared to the existing laboratory reporting interface, significantly improved the identification of abnormal laboratory results, of the long-term trend of the laboratory tests and of tests due for repeat testing. However, the Diabetes Dashboard did not significantly improve the identification of patients requiring treatment adjustment or the amount of time spent on each case scenario. In conclusion, we have developed and shown that the use of the Diabetes Dashboard, which incorporates several decision support features, can improve the management of diabetes. It is anticipated that this dashboard will be most helpful when deployed in an outpatient setting, where physicians can quickly make clinical decisions based on summarized information and be alerted to pertinent areas of care that require additional attention.

  13. Clinical Decision Support Systems (CDSS) for preventive management of COPD patients.

    Science.gov (United States)

    Velickovski, Filip; Ceccaroni, Luigi; Roca, Josep; Burgos, Felip; Galdiz, Juan B; Marina, Nuria; Lluch-Ariet, Magí

    2014-11-28

    The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems.

  14. Clinical decision support systems differ in their ability to identify clinically relevant drug interactions of immunosuppressants in kidney transplant patients.

    Science.gov (United States)

    Amkreutz, J; Koch, A; Buendgens, L; Trautwein, C; Eisert, A

    2017-06-01

    In kidney transplant patients, clinically relevant drug-drug interactions (DDIs) with immunosuppressants potentially lead to serious adverse drug events (ADEs). The aim of this study was (i) to show that five clinical decision support systems (CDSSs) differ in their ability to identify clinically relevant potential DDIs (pDDIs) of immunosuppressants in kidney transplant patients and (ii) to compare CDSSs in terms of their ability to identify clinically relevant pDDIs in this context. All pDDIs being possible between nine immunosuppressants and 234 comedication drugs were identified for 264 intensive care unit (ICU) kidney transplant patients from 1999 to 2010. For pDDI identification, five CDSSs were used: DRUG-REAX® , ID PHARMA CHECK® , Lexi-Interact, mediQ and Meona. PDDIs from high severity categories were defined as clinically relevant. Classification of pDDIs as clinically relevant/non-clinically relevant by a clinical pharmacist using Stockley's Drug Interactions was employed as benchmark. We analysed inter-rater agreement, sensitivity, specificity, positive predictive value and negative predictive value. Clinical decision support systems generated a total of 759 pDDI alerts. A total of 240 pDDI alerts were in high severity categories. A total of 391 different pDDIs were identified. Only 5% (n = 35) of different pDDIs were identified by all CDSSs. A total of 49 pDDIs were classified as clinically relevant by clinical pharmacists' rating using Stockley's Drug Interactions. Meona (0·72) has the highest inter-rater agreement with the benchmark for clinically relevant pDDIs. ID PHARMA CHECK® and mediQ show highest sensitivities (0·74, respectively). Meona has the highest specificity (0·99) and positive predictive value (0·89). Five CDSSs differ in their ability to identify clinically relevant pDDIs of immunosuppressants in kidney transplant patients. Data may assist in selecting CDSSs for kidney transplant patients in the ICU. Using CDSSs to identify

  15. Professional autonomy in 21st century healthcare: Nurses' accounts of clinical decision-making

    DEFF Research Database (Denmark)

    Traynor, Michael; Boland, Maggie; Buus, Niels

    2010-01-01

    profession for reasons including history, gender and a traditional subservience to medicine. This paper reports on a focus group study of UK nurses participating in post-qualifying professional development in 2008. Three groups of nurses in different specialist areas comprised a total of 26 participants....... The study uses accounts of decision-making to gain insight into contemporary professional nursing. The study also aims to explore the usefulness of a theory of professional work set out by Jamous and Peloille (1970). The analysis draws on notions of interpretive repertoires and elements of narrative...... analysis. We identified two interpretive repertoires: 'clinical judgement' which was used to describe the different grounds for making judgements; and 'decision-making' which was used to describe organisational circumstances influencing decision-making. Jamous and Peloille's theory proved useful...

  16. Feminist poststructuralism: a methodological paradigm for examining clinical decision-making.

    Science.gov (United States)

    Arslanian-Engoren, Cynthia

    2002-03-01

    To present the philosophical framework of feminist poststructuralism, discuss its use as an innovative research approach and its implications for nursing knowledge development and practice. This perspective examines the construction of meaning, power relationships, and the importance of language as it affects contemporary healthcare decisions. It seeks to identify and expose biases that marginalize the healthcare needs of women and contribute to healthcare disparities for this population. Additionally, a feminist poststructuralist perspective seeks to develop new knowledge for understanding gender differences. A feminist poststructuralist perspective represents an alternative paradigm for studying the phenomenon of clinical decision-making. An empirical application example of a feminist poststructuralist perspective is provided. This exemplar investigated emergency department registered nurses' triage decisions for men and women with symptoms suggestive of coronary heart disease.

  17. KQA: A Knowledge Quality Assessment Model for Clinical Decision Support Systems.

    Science.gov (United States)

    Zolhavarieh, Seyedjamal; Parry, Dave

    2017-01-01

    Informatics researchers have developed many methods for using computers to utilize knowledge in decision making in the form of clinical decision support systems (CDSSs). These systems can enhance human decision making in the healthcare domain. The knowledge acquisition bottleneck is one of the well-known issues in developing knowledge-based systems such as CDSS. It can be considered as a flow of knowledge from different knowledge sources to the main system. Most existing methods for extracting knowledge from knowledge resources suffer from the lack of a proper mechanism for extracting high-quality knowledge. In this paper, we propose a framework to discover high-quality knowledge by utilizing Semantic Web technologies.

  18. Model for prediction of pediatric OSA: Proposal for a clinical decision rule.

    Science.gov (United States)

    Certal, Victor; Silva, Hélder; Carvalho, Carlos; Costa-Pereira, Altamiro; Azevedo, Inês; Winck, João; Capasso, Robson; Camacho, Macario

    2015-12-01

    Obstructive sleep apnea (OSA) is a syndrome frequently diagnosed in children; however, it lacks optimal diagnostic methods. This study aimed to provide a clinical decision rule for predicting pediatric OSA using commonly available clinical information. A prospective cohort study. Children between the ages of 3 to 6 years-old, referred for an otorhinolaryngology consultation due to clinical suspicion of OSA, were recruited from January to June 2014. At baseline age, weight, height, gender, body mass index, Pediatric Sleep Questionnaire (PSQ) scores, tonsil size, and oxygen desaturation index (ODI) were assessed. A logistic regression modeling was used with backward stepwise elimination to develop a prediction model. Sixty-seven children were included with a mean age of 4.51 years. Of the 67 children included in this study, 25 (37.3%) subjects were diagnosed with pediatric OSA. Significant predictors of pediatric OSA in the final model (odds ratio, 95% confidence interval) included PSQ score (5.12; 3.3-6.5), ODI (1.34; 1.0-1.79) and tonsil size (6.7; 3.22-9.75). The final decision rule had a sensitivity of 88% and a specificity of 86%. The area under the receiver operating characteristic curve was 0.897. The proposed clinical decision rule, based on three readily available variables, is a promising discriminating instrument for prediction of OSA among children between 3 and 6 years. 2b. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

  19. Clinical decision support software for diabetic foot risk stratification: development and formative evaluation.

    Science.gov (United States)

    Schoen, Deborah E; Glance, David G; Thompson, Sandra C

    2015-01-01

    Identifying people at risk of developing diabetic foot complications is a vital step in prevention programs in primary healthcare settings. Diabetic foot risk stratification systems predict foot ulceration. The aim of this study was to explore the views and experiences of potential end users during development and formative evaluations of an electronic diabetic foot risk stratification tool based on evidence-based guidelines and determine the accuracy of the tool. Formative evaluation of the risk tool occurred in five stages over an eight-month period and employed a mixed methods research design consisting of semi-structured interviews, focus group and participant observation, online survey, expert review, comparison to the Australian Guidelines and clinical testing. A total of 43 healthcare practitioners trialled the computerised clinical decision support system during development, with multiple software changes made as a result of feedback. Individual and focus group participants exposed critical design flaws. Live testing revealed risk stratification errors and functional limitations providing the basis for practical improvements. In the final product, all risk calculations and recommendations made by the clinical decision support system reflect current Australian Guidelines. Development of the computerised clinical decision support system using evidence-based guidelines can be optimised by a multidisciplinary iterative process of feedback, testing and software adaptation by experts in modern development technologies.

  20. Clinical decision support systems in child and adolescent psychiatry: a systematic review.

    Science.gov (United States)

    Koposov, Roman; Fossum, Sturla; Frodl, Thomas; Nytrø, Øystein; Leventhal, Bennett; Sourander, Andre; Quaglini, Silvana; Molteni, Massimo; de la Iglesia Vayá, María; Prokosch, Hans-Ulrich; Barbarini, Nicola; Milham, Michael Peter; Castellanos, Francisco Xavier; Skokauskas, Norbert

    2017-11-01

    Psychiatric disorders are amongst the most prevalent and impairing conditions in childhood and adolescence. Unfortunately, it is well known that general practitioners (GPs) and other frontline health providers (i.e., child protection workers, public health nurses, and pediatricians) are not adequately trained to address these ubiquitous problems (Braddick et al. Child and Adolescent mental health in Europe: infrastructures, policy and programmes, European Communities, 2009; Levav et al. Eur Child Adolesc Psychiatry 13:395-401, 2004). Advances in technology may offer a solution to this problem with clinical decision support systems (CDSS) that are designed to help professionals make sound clinical decisions in real time. This paper offers a systematic review of currently available CDSS for child and adolescent mental health disorders prepared according to the PRISMA-Protocols (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols). Applying strict eligibility criteria, the identified studies (n = 5048) were screened. Ten studies, describing eight original clinical decision support systems for child and adolescent psychiatric disorders, fulfilled inclusion criteria. Based on this systematic review, there appears to be a need for a new, readily available CDSS for child neuropsychiatric disorder which promotes evidence-based, best practices, while enabling consideration of national variation in practices by leveraging data-reuse to generate predictions regarding treatment outcome, addressing a broader cluster of clinical disorders, and targeting frontline practice environments.

  1. Pharmacists' awareness of clinical decision support in pharmacy information systems: an exploratory evaluation.

    Science.gov (United States)

    Hines, Lisa E; Saverno, Kim R; Warholak, Terri L; Taylor, Ann; Grizzle, Amy J; Murphy, John E; Malone, Daniel C

    2011-12-01

    Clinical decision support (CDS), such as drug-drug interaction (DDI) and drug-allergy checking, has been used in pharmacy information systems for several decades; however, there has been limited research on CDS use by practicing pharmacists. The purpose of this study was to document pharmacists' awareness of DDI and other medication-related CDS features available within pharmacy information systems. Researchers conducted on-site interviews with pharmacists throughout the state of Arizona from December 2008 to November 2009 regarding their pharmacy information systems features. Pharmacists were asked to provide information about DDI and other medication-related decision support features of the pharmacy software at their practice site. Descriptive statistics were used to summarize interview responses. Sixty-one pharmacists from a variety of practice settings completed the interview. All respondents indicated that their pharmacy system provided drug-allergy and DDI alerts. Approximately 60% of the pharmacists reported that their DDI decision support systems included recommendations for managing drug interactions. Two-thirds of respondents reported that their pharmacy's computer system permitted the addition of medications from other pharmacies and/or over-the-counter products to a patient's profile. Approximately 40% of the pharmacists reported that some drugs entered into the pharmacy computer system were not included in (or linked to) the electronic DDI checking. Most pharmacists indicated the presence of other medication-related decision support features, such as drug-disease (78%), drug-age precautions (67%), and inappropriate dosage alerts (79%). However, fewer pharmacists reported more advanced functionality, such as laboratory recommendations (34%) and pediatric dosing (39%). Overall, pharmacists' awareness regarding the many decision support functionalities of their systems was limited. Based on the study findings, it appears that there are a number of

  2. How meta-analytic evidence impacts clinical decision making in oral implantology: a Delphi opinion poll.

    Science.gov (United States)

    Pommer, Bernhard; Becker, Kathrin; Arnhart, Christoph; Fabian, Ferenc; Rathe, Florian; Stigler, Robert G

    2016-03-01

    To investigate the impact of meta-analytic evidence in scientific literature on clinical decision making in the field of oral implantology. A Delphi opinion poll was performed at the meeting of the "Next Generation" Committees of the Austrian, German and Swiss Societies for Implantology (ÖGI, DGI and SGI). First, the experts gave their opinion on 20 questions regarding routine implant treatment (uninformed decisions), then they were confronted with up-to-date Level I evidence from scientific literature on these topics and again asked to give their opinion (informed decisions) as well as to rate the available evidence as satisfactory or insufficient. Topics involved surgical issues, such as immediate implant placement, flapless surgery, tilted and short implants and bone substitute materials, as well as opinions on prosthodontic paradigms, such as immediate loading, abutment materials and platform switching. Compared to their uninformed decisions prior to confrontation with recent scientific literature, on average, 37% of experts (range: 15-50%) changed their opinion on the topic. When originally favoring one treatment alternative, less than half were still convinced after review of meta-analytic evidence. Discrepancy between uninformed and informed decisions was significantly associated with insufficient evidence (P = 0.014, 49% change of opinion vs. 26% on topics rated as sufficiently backed with evidence). Agreement regarding strength of evidence could be reached for eight topics (40%), in three issues toward sufficiency and in five issues toward lack of evidence. Confrontation with literature results significantly changes clinical decisions of implantologists, particularly in cases of ambiguous or lacking meta-analytic evidence. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  3. Clinical decision support for whole genome sequence information leveraging a service-oriented architecture: a prototype.

    Science.gov (United States)

    Welch, Brandon M; Rodriguez-Loya, Salvador; Eilbeck, Karen; Kawamoto, Kensaku

    2014-01-01

    Whole genome sequence (WGS) information could soon be routinely available to clinicians to support the personalized care of their patients. At such time, clinical decision support (CDS) integrated into the clinical workflow will likely be necessary to support genome-guided clinical care. Nevertheless, developing CDS capabilities for WGS information presents many unique challenges that need to be overcome for such approaches to be effective. In this manuscript, we describe the development of a prototype CDS system that is capable of providing genome-guided CDS at the point of care and within the clinical workflow. To demonstrate the functionality of this prototype, we implemented a clinical scenario of a hypothetical patient at high risk for Lynch Syndrome based on his genomic information. We demonstrate that this system can effectively use service-oriented architecture principles and standards-based components to deliver point of care CDS for WGS information in real-time.

  4. Changes in patient satisfaction related to hospital renovation: experience with a new clinical building.

    Science.gov (United States)

    Siddiqui, Zishan K; Zuccarelli, Rebecca; Durkin, Nowella; Wu, Albert W; Brotman, Daniel J

    2015-03-01

    There is an increasing trend toward designing hospitals with patient-centered features like reduced noise, improved natural light, visitor friendly facilities, well-decorated rooms, and hotel-like amenities. It has also been suggested that because patients cannot reliably distinguish positive experiences with the physical environment from positive experience with care, an improved hospital environment leads to higher satisfaction with physicians, nursing, food service, housekeeping, and higher overall satisfaction. To characterize changes in patient satisfaction that occurred when clinical services (comprised of stable nursing, physician, and unit teams) were relocated to a new clinical building with patient-centered features. We hypothesized that new building features would positively impact provider, ancillary staff, and overall satisfaction, as well as improved satisfaction with the facility. Natural experiment utilizing a pre-post design with concurrent controls. Academic tertiary care hospital. We included all patients discharged from 12 clinical units that relocated to the new clinical building who returned surveys in the 7.5-month period following the move. Premove baseline data were captured from the year prior to the move. Patients on unmoved clinical units who returned satisfaction surveys served as concurrent controls. Patient-centered design features incorporated into the new clinical building. All patients during the baseline period and control patients during the study period were located in usual patient rooms with standard hospital amenities. The primary outcome was satisfaction scores on the Press Ganey and Hospital Consumer Assessment of Healthcare Providers and Systems survey, dichotomized at highest category versus lower categories. We performed logistic regression to identify predictors of "top-box" scores. The move was associated with improved room- and visitor-related satisfaction without significant improvement in satisfaction with clinical

  5. [Preferences, satisfaction level of patient participation in making decisions in health centre nursing clinics].

    Science.gov (United States)

    Ruiz Moral, Roger; Alba Dios, Antonia; Dios Guerra, Caridad; Jiménez García, Celia; González Neubauer, Valeria; Pérula de Torres, Luis Ángel; Barrios Blasco, Luciano

    2011-01-01

    To assess patient preferences their satisfaction level and their participation in decision making with nurses. Cross-sectional and mixed quantitative-qualitative study carried out in people attending the nursing services of 9 Health Centres in Andalusia. Patients were interviewed immediately after receiving nursing treatment using two different questionnaires for assessing their opinions, satisfaction and perception of involvement in the decisional process. A descriptive analysis using the χ(2) test (Popen-ended questions. Qualitative analysis: Open-ended questions were grouped into categories by a process involving three researchers independently. A total of 235 patients took part, of whom 59% (138) preferred a collaborative role with the nurse when making decisions. In the closed questions, 96.2% (228) of the surveyed patients declared to be satisfied or very satisfied with the decision making process; nevertheless 17.4% (41) made specific suggestions for improving this process. For them the main improvement areas were related to: general communication skills or a more specific one such as: strategies for helping them make decisions, reaching common ground or giving advice. Nurses should be aware that most patients wish to be involved in decision making and in clinical practice this participation can be improved by obtaining specific communicational skills. Surveys that include open-ended questions are more useful to assess the quality of care. Copyright © 2010 Elsevier España, S.L. All rights reserved.

  6. Clinical decision support systems in hospital care using ubiquitous devices: Current issues and challenges.

    Science.gov (United States)

    Baig, Mirza Mansoor; GholamHosseini, Hamid; Moqeem, Aasia A; Mirza, Farhaan; Lindén, Maria

    2017-11-01

    Supporting clinicians in decision making using advanced technologies has been an active research area in biomedical engineering during the past years. Among a wide range of ubiquitous systems, smartphone applications have been increasingly developed in healthcare settings to help clinicians as well as patients. Today, many smartphone applications, from basic data analysis to advanced patient monitoring, are available to clinicians and patients. Such applications are now increasingly integrating into healthcare for clinical decision support, and therefore, concerns around accuracy, stability, and dependency of these applications are rising. In addition, lack of attention to the clinicians' acceptability, as well as the low impact on the medical professionals' decision making, are posing more serious issues on the acceptability of smartphone applications. This article reviews smartphone-based decision support applications, focusing on hospital care settings and their overall impact of these applications on the wider clinical workflow. Additionally, key challenges and barriers of the current ubiquitous device-based healthcare applications are identified. Finally, this article addresses current challenges, future directions, and the adoption of mobile healthcare applications.

  7. Replacing the mercury manometer with an oscillometric device in a hypertension clinic: implications for clinical decision making.

    Science.gov (United States)

    Stergiou, G S; Lourida, P; Tzamouranis, D

    2011-11-01

    Oscillometric devices are being widely used for ambulatory, home and office blood pressure (BP) measurement, and several of them have been validated using established protocols. This cross-sectional study assessed the impact on antihypertensive treatment decisions of replacing the mercury sphygmomanometer by a validated oscillometric device. Consecutive subjects attending a hypertension clinic had triplicate simultaneous same-arm BP measurements using a mercury sphygmomanometer and a validated professional oscillometric device. For each device, uncontrolled hypertension was defined as average BP ≥140/90 mm Hg (systolic/diastolic). A total of 5108 simultaneous BP measurements were obtained from 763 subjects in 1717 clinic visits. In 24% of all visits, the mercury and the oscillometric BP measurements led to different conclusion regarding the diagnosis of uncontrolled hypertension. In 4.9% of the visits, the diagnostic disagreement was considered as 'clinically important' (BP exceeding the diagnostic threshold by >5 mm Hg). These data suggest that the replacement of the mercury sphygmomanometer by a validated professional oscillometric device will result into different treatment decisions in about 5% of the cases. Therefore, and because of the known problems when using mercury devices and the auscultatory technique in clinical practise, the oscillometric devices are regarded as reliable alternatives to the mercury sphygmomanometer for office use.

  8. Ethnic bias and clinical decision-making among New Zealand medical students: an observational study.

    Science.gov (United States)

    Harris, Ricci; Cormack, Donna; Stanley, James; Curtis, Elana; Jones, Rhys; Lacey, Cameron

    2018-01-23

    Health professional racial/ethnic bias may impact on clinical decision-making and contribute to subsequent ethnic health inequities. However, limited research has been undertaken among medical students. This paper presents findings from the Bias and Decision-Making in Medicine (BDMM) study, which sought to examine ethnic bias (Māori (indigenous peoples) compared with New Zealand European) among medical students and associations with clinical decision-making. All final year New Zealand (NZ) medical students in 2014 and 2015 (n = 888) were invited to participate in a cross-sectional online study. Key components included: two chronic disease vignettes (cardiovascular disease (CVD) and depression) with randomized patient ethnicity (Māori or NZ European) and questions on patient management; implicit bias measures (an ethnicity preference Implicit Association Test (IAT) and an ethnicity and compliant patient IAT); and, explicit ethnic bias questions. Associations between ethnic bias and clinical decision-making responses to vignettes were tested using linear regression. Three hundred and two students participated (34% response rate). Implicit and explicit ethnic bias favoring NZ Europeans was apparent among medical students. In the CVD vignette, no significant differences in clinical decision-making by patient ethnicity were observed. There were also no differential associations by patient ethnicity between any measures of ethnic bias (implicit or explicit) and patient management responses in the CVD vignette. In the depression vignette, some differences in the ranking of recommended treatment options were observed by patient ethnicity and explicit preference for NZ Europeans was associated with increased reporting that NZ European patients would benefit from treatment but not Māori (slope difference 0.34, 95% CI 0.08, 0.60; p = 0.011), although this was the only significant finding in these analyses. NZ medical students demonstrated ethnic bias, although

  9. Distributing knowledge maintenance for clinical decision-support systems: the "knowledge library" model.

    Science.gov (United States)

    Geissbuhler, A; Miller, R A

    1999-01-01

    The maintenance of knowledge-rich clinical decision-support systems is challenging, in particular in the complex setting of a large academic medical center. Distributing the maintenance tasks to the source of expertise can address scalability, accuracy and currency issues. It also helps to foster a more global sense of ownership among the system users. The knowledge maintenance model must provide processes and tools to deal with a wide range of stakeholders (resident and attending physicians, consulting specialists, other care providers, case managers, ancillary departments), with knowledge embedded in legacy departmental systems, and with the continuous evolution of the content and form of the knowledge base. We describe and illustrate the "knowledge library" model in use at Vanderbilt University Medical Center for the distributed maintenance of the integrated knowledge base that drives the WizOrder clinical decision-support, physician order entry, and notes capture system.

  10. Conflicts of interest in research: is clinical decision-making compromised? An opinion paper.

    Science.gov (United States)

    Adibi, Shawn; Abidi, Shawn; Bebermeyer, Richard D

    2010-08-01

    Lack of transparency in funded research can compromise clinical decision-making in an evidence-based practice. Transparency can be defined as full disclosure of all financial assistance and support to authors and investigators. There is a perception that ethical principles are eroding and that research data can be biased due to conflicts of interest. These research outcomes biased or not, are used for clinical decision-making in the evidence-based practice. One suggested solution to this common ethical dilemma is to continue the dialogue on transparency in research and to create oversight bodies which include representatives from business and industry, private practice, academia, and research. There is increasing evidence of the need for more ethics education at all levels.

  11. How Qualitative Research Informs Clinical and Policy Decision Making in Transplantation: A Review.

    Science.gov (United States)

    Tong, Allison; Morton, Rachael L; Webster, Angela C

    2016-09-01

    Patient-centered care is no longer just a buzzword. It is now widely touted as a cornerstone in delivering quality care across all fields of medicine. However, patient-centered strategies and interventions necessitate evidence about patients' decision-making processes, values, priorities, and needs. Qualitative research is particularly well suited to understanding the experience and perspective of patients, donors, clinicians, and policy makers on a wide range of transplantation-related topics including organ donation and allocation, adherence to prescribed therapy, pretransplant and posttransplant care, implementation of clinical guidelines, and doctor-patient communication. In transplantation, evidence derived from qualitative research has been integrated into strategies for shared decision-making, patient educational resources, process evaluations of trials, clinical guidelines, and policies. The aim of this article is to outline key concepts and methods used in qualitative research, guide the appraisal of qualitative studies, and assist clinicians to understand how qualitative research may inform their practice and policy.

  12. The perils of meta-regression to identify clinical decision support system success factors.

    Science.gov (United States)

    Fillmore, Christopher L; Rommel, Casey A; Welch, Brandon M; Zhang, Mingyuan; Kawamoto, Kensaku

    2015-08-01

    Clinical decision support interventions are typically heterogeneous in nature, making it difficult to identify why some interventions succeed while others do not. One approach to identify factors important to the success of health information systems is the use of meta-regression techniques, in which potential explanatory factors are correlated with the outcome of interest. This approach, however, can result in misleading conclusions due to several issues. In this manuscript, we present a cautionary case study in the context of clinical decision support systems to illustrate the limitations of this type of analysis. We then discuss implications and recommendations for future work aimed at identifying success factors of medical informatics interventions. In particular, we identify the need for head-to-head trials in which the importance of system features is directly evaluated in a prospective manner. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. What We Can Learn from Amazon for Clinical Decision Support Systems.

    Science.gov (United States)

    Abid, Sidra; Keshavjee, Karim; Karim, Arsalan; Guergachi, Aziz

    2017-01-01

    Health care continue to lag behind other industries, such as retail and financial services, in the use of decision-support-like tools. Amazon is particularly prolific in the use of advanced predictive and prescriptive analytics to assist its customers to purchase more, while increasing satisfaction, retention, repeat-purchases and loyalty. How can we do the same in health care? In this paper, we explore various elements of the Amazon website and Amazon's data science and big data practices to gather inspiration for re-designing clinical decision support in the health care sector. For each Amazon element we identified, we present one or more clinical applications to help us better understand where Amazon's.

  14. Relationships Between Clinical Decision-Making Patterns and Self-Efficacy and Nursing Professionalism in Korean Pediatric Nurses.

    Science.gov (United States)

    Choi, Miyoung; Kim, Jisoo

    2015-01-01

    As pediatric nurses must make decisions on a regular basis when caring for hospitalized children, clinical decision-making abilities are necessary in this profession. In the present study, we explored clinical decision-making patterns and their association with self-efficacy and nursing professionalism in pediatric nurses. We surveyed 173 pediatric nurses and analyzed the relationships between their clinical decision-making patterns and self-efficacy and nursing professionalism. Factor analysis identified 5 clinical decision-making patterns: patient-family-nurse collaborative (PNC), individual patient-oriented (IP), nurse model-oriented (NM), pattern-oriented intuitive (PI), and nursing knowledge-oriented (NK). The most frequently observed clinical decision-making pattern was the PNC. The self-efficacy and nursing professionalism were found to be higher in pediatric nurses using the IP and NM, and were lower for those using the PNC. Thus, the present results suggest that pediatric nurses' clinical decision-making patterns are influenced by nursing professionalism and self-efficacy. Therefore, intervention programs focusing on these variables might improve clinical decision-making in pediatric nurses. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Development of a clinical decision support system for diabetes care: A pilot study

    OpenAIRE

    Sim, Livvi Li Wei; Ban, Kenneth Hon Kim; Tan, Tin Wee; Sethi, Sunil Kumar; Loh, Tze Ping

    2017-01-01

    Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard) interface for displaying glycemic, lipid and renal function results,...

  16. Access to augmentative and alternative communication: new technologies and clinical decision-making.

    Science.gov (United States)

    Fager, Susan; Bardach, Lisa; Russell, Susanne; Higginbotham, Jeff

    2012-01-01

    Children with severe physical impairments require a variety of access options to augmentative and alternative communication (AAC) and computer technology. Access technologies have continued to develop, allowing children with severe motor control impairments greater independence and access to communication. This article will highlight new advances in access technology, including eye and head tracking, scanning, and access to mainstream technology, as well as discuss future advances. Considerations for clinical decision-making and implementation of these technologies will be presented along with case illustrations.

  17. Evaluation of Symptoms and Characteristic Features of Lead Poisoning and their Assistance in Clinical Decision Making

    OpenAIRE

    D'souza HS; Menezes G; Dsouza SA; Venkatesh T

    2015-01-01

    Aim of the present study is to evaluate the symptoms and characteristics features in lead based industrial workers and accessing their reliability in clinical decision making and diagnosing lead toxicity. Study involves 15 industrial workers (exposed) and 15 non-exposed individuals, matched for age, sex and nationality selected from Bangalore, India. Association of various symptoms and characteristic features in exposed and non-exposed groups were evaluated and their association with high ...

  18. Mobile learning app: A novel method to teach clinical decision making in prosthodontics.

    Science.gov (United States)

    Deshpande, Saee; Chahande, Jaishree; Rathi, Akhil

    2017-01-01

    Prosthodontics involves replacing lost dentofacial structures using artificial substitutes. Due to availability of many materials and techniques, clinician's clinical decision-making regarding appropriate selection of prosthesis requires critical thinking abilities and is demanding. Especially during graduate training years, learners do not receive the exposure to a variety of cases, thus their clinical reasoning skills are not developed optimally. Therefore, using the trend of incorporating technology in education, we developed a mobile learning app for this purpose. The aim of this study was to evaluate learners' perceptions of this app's utility and impact on their clinical decision-making skills. After taking informed consent, interns of the Department of Prosthodontics of VSPM Dental College, Nagpur, India, during the academic year May 2015-May 2016 were sent the link for the app to be installed in their Android smartphones. Their perceptions were recorded on a feedback questionnaire using 5-point Likert scale. The script concordance test (SCT) was used to check for changes in clinical reasoning abilities. Out of 120 students who were sent the link, 102 downloaded the link and 92 completed the feedback questionnaire and appeared for the SCT (response rate: 76%). The overall response to the app was positive for more than two-thirds of interns, who reported a greater confidence in their clinical decision-making around prostheses through this app and 94% of the students felt that this app should be regularly used along with conventional teaching techniques. Mean SCT scores were pretest 41.5 (±1.7) and posttest 63 (±2.4) (P learning app, is an effective way to improve clinical reasoning skills for planning prosthodontic rehabilitation. It is well received by students.

  19. Ending the technology paradox: healthcare management technologies for clinical decision making.

    Science.gov (United States)

    Karys, A

    1998-01-01

    As this article has shown, advances are beginning to put an end to the technology paradox that has hindered the industry's efforts to manage care better. Whereas in the past the management side of the healthcare industry has been slow to adopt new technologies, recent years have seen an explosion in the development and use of new tools for managing care. Most of these tools have traditionally focused on managing the administrative and financial aspects of providing care; however, that has also begun to change. Software systems incorporating clinical decision support criteria permit healthcare professionals to make clinical decision-making part of the care management process conveniently and efficiently. Clinical decision support criteria are also helping to change the focus of managed care. At the beginning of the managed care era, insurers and managed care companies concentrated primarily on reigning in costs, in many cases by restricting the types and duration of care provided to their members. Although these restrictions succeeded in conserving resources, they also helped foster an uneasy atmosphere between payers and providers, many of whom felt that their clinical judgment was too often overruled by the "bean counters." At the same time, many healthcare consumers grew to distrust both managed care professionals and providers, feeling that medical decisions were often made for the wrong reasons. However, as managed care companies have acknowledged that the most efficient way to provide care is to provide appropriate care, the focus has begun to move toward the clinical side of healthcare. Although healthcare organizations are still relying on financial management tools, they are also looking for systems that can make the clinical decision-making process more efficient and effective. The end result is that the healthcare industry is able to assure the best, most appropriate treatment while conserving resources. With the constant stream of new technologies into

  20. A programmable rules engine to provide clinical decision support using HTML forms.

    Science.gov (United States)

    Heusinkveld, J; Geissbuhler, A; Sheshelidze, D; Miller, R

    1999-01-01

    The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser.

  1. Clinical decision-making: heuristics and cognitive biases for the ophthalmologist.

    Science.gov (United States)

    Hussain, Ahsen; Oestreicher, James

    Diagnostic errors have a significant impact on health care outcomes and patient care. The underlying causes and development of diagnostic error are complex with flaws in health care systems, as well as human error, playing a role. Cognitive biases and a failure of decision-making shortcuts (heuristics) are human factors that can compromise the diagnostic process. We describe these mechanisms, their role with the clinician, and provide clinical scenarios to highlight the various points at which biases may emerge. We discuss strategies to modify the development and influence of these processes and the vulnerability of heuristics to provide insight and improve clinical outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Clinical decision support improves quality of telephone triage documentation - an analysis of triage documentation before and after computerized clinical decision support

    Science.gov (United States)

    2014-01-01

    Background Clinical decision support (CDS) has been shown to be effective in improving medical safety and quality but there is little information on how telephone triage benefits from CDS. The aim of our study was to compare triage documentation quality associated with the use of a clinical decision support tool, ExpertRN©. Methods We examined 50 triage documents before and after a CDS tool was used in nursing triage. To control for the effects of CDS training we had an additional control group of triage documents created by nurses who were trained in the CDS tool, but who did not use it in selected notes. The CDS intervention cohort of triage notes was compared to both the pre-CDS notes and the CDS trained (but not using CDS) cohort. Cohorts were compared using the documentation standards of the American Academy of Ambulatory Care Nursing (AAACN). We also compared triage note content (documentation of associated positive and negative features relating to the symptoms, self-care instructions, and warning signs to watch for), and documentation defects pertinent to triage safety. Results Three of five AAACN documentation standards were significantly improved with CDS. There was a mean of 36.7 symptom features documented in triage notes for the CDS group but only 10.7 symptom features in the pre-CDS cohort (p triage note documentation quality. CDS-aided triage notes had significantly more information about symptoms, warning signs and self-care. The changes in triage documentation appeared to be the result of the CDS alone and not due to any CDS training that came with the CDS intervention. Although this study shows that CDS can improve documentation, further study is needed to determine if it results in improved care. PMID:24645674

  3. The Group Objective Structured Clinical Experience: building communication skills in the clinical reasoning context.

    Science.gov (United States)

    Konopasek, Lyuba; Kelly, Kevin V; Bylund, Carma L; Wenderoth, Suzanne; Storey-Johnson, Carol

    2014-07-01

    Students are rarely taught communication skills in the context of clinical reasoning training. The purpose of this project was to combine the teaching of communication skills using SPs with clinical reasoning exercises in a Group Objective Structured Clinical Experience (GOSCE) to study feasibility of the approach, the effect on learners' self-efficacy and attitude toward learning communication skills, and the effect of providing multiple sources of immediate, collaborative feedback. GOSCE sessions were piloted in Pediatrics and Medicine clerkships with students assessing their own performance and receiving formative feedback on communication skills from peers, standardized patients (SPs), and faculty. The sessions were evaluated using a retrospective pre/post-training questionnaire rating changes in self-efficacy and attitudes, and the value of the feedback. Results indicate a positive impact on attitudes toward learning communication skills and self-efficacy regarding communication in the clinical setting. Also, learners considered feedback by peers, SPs, and faculty valuable in each GOSCE. The GOSCE is an efficient and learner-centered method to attend to multiple goals of teaching communication skills, clinical reasoning, self-assessment, and giving feedback in a formative setting. The GOSCE is a low-resource, feasible strategy for experiential learning in communication skills and clinical reasoning. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  4. Development of traditional Chinese medicine clinical data warehouse for medical knowledge discovery and decision support.

    Science.gov (United States)

    Zhou, Xuezhong; Chen, Shibo; Liu, Baoyan; Zhang, Runsun; Wang, Yinghui; Li, Ping; Guo, Yufeng; Zhang, Hua; Gao, Zhuye; Yan, Xiufeng

    2010-01-01

    Traditional Chinese medicine (TCM) is a scientific discipline, which develops the related theories from the long-term clinical practices. The large-scale clinical data are the core empirical knowledge source for TCM research. This paper introduces a clinical data warehouse (CDW) system, which incorporates the structured electronic medical record (SEMR) data for medical knowledge discovery and TCM clinical decision support (CDS). We have developed the clinical reference information model (RIM) and physical data model to manage the various information entities and their relationships in TCM clinical data. An extraction-transformation-loading (ETL) tool is implemented to integrate and normalize the clinical data from different operational data sources. The CDW includes online analytical processing (OLAP) and complex network analysis (CNA) components to explore the various clinical relationships. Furthermore, the data mining and CNA methods are used to discover the valuable clinical knowledge from the data. The CDW has integrated 20,000 TCM inpatient data and 20,000 outpatient data, which contains manifestations (e.g. symptoms, physical examinations and laboratory test results), diagnoses and prescriptions as the main information components. We propose a practical solution to accomplish the large-scale clinical data integration and preprocessing tasks. Meanwhile, we have developed over 400 OLAP reports to enable the multidimensional analysis of clinical data and the case-based CDS. We have successfully conducted several interesting data mining applications. Particularly, we use various classification methods, namely support vector machine, decision tree and Bayesian network, to discover the knowledge of syndrome differentiation. Furthermore, we have applied association rule and CNA to extract the useful acupuncture point and herb combination patterns from the clinical prescriptions. A CDW system consisting of TCM clinical RIM, ETL, OLAP and data mining as the core

  5. Designing a Clinical Framework to Guide Gross Motor Intervention Decisions for Infants and Young Children with Hypotonia

    Science.gov (United States)

    Darrah, Johanna; O'Donnell, Maureen; Lam, Joyce; Story, Maureen; Wickenheiser, Diane; Xu, Kaishou; Jin, Xiaokun

    2013-01-01

    Clinical practice frameworks are a valuable component of clinical education, promoting informed clinical decision making based on the best available evidence and/or clinical experience. They encourage standardized intervention approaches and evaluation of practice. Based on an international project to support the development of an enhanced service…

  6. Barriers and decisions when answering clinical questions at the point of care: a grounded theory study.

    Science.gov (United States)

    Cook, David A; Sorensen, Kristi J; Wilkinson, John M; Berger, Richard A

    2013-11-25

    Answering clinical questions affects patient-care decisions and is important to continuous professional development. The process of point-of-care learning is incompletely understood. To understand what barriers and enabling factors influence physician point-of-care learning and what decisions physicians face during this process. Focus groups with grounded theory analysis. Focus group discussions were transcribed and then analyzed using a constant comparative approach to identify barriers, enabling factors, and key decisions related to physician information-seeking activities. Academic medical center and outlying community sites. Purposive sample of 50 primary care and subspecialist internal medicine and family medicine physicians, interviewed in 11 focus groups. Insufficient time was the main barrier to point-of-care learning. Other barriers included the patient comorbidities and contexts, the volume of available information, not knowing which resource to search, doubt that the search would yield an answer, difficulty remembering questions for later study, and inconvenient access to computers. Key decisions were whether to search (reasons to search included infrequently seen conditions, practice updates, complex questions, and patient education), when to search (before, during, or after the clinical encounter), where to search (with the patient present or in a separate room), what type of resource to use (colleague or computer), what specific resource to use (influenced first by efficiency and second by credibility), and when to stop. Participants noted that key features of efficiency (completeness, brevity, and searchability) are often in conflict. Physicians perceive that insufficient time is the greatest barrier to point-of-care learning, and efficiency is the most important determinant in selecting an information source. Designing knowledge resources and systems to target key decisions may improve learning and patient care.

  7. Clinical performance of an interactive clinical decision support system for assessment of plasma lactate in hospitalized patients with organ dysfunction

    Directory of Open Access Journals (Sweden)

    Raschke RA

    2017-05-01

    Full Text Available Purpose: Elevated plasma lactate concentration can be a useful measure of tissue hypo-perfusion in acutely deteriorating patients, focusing attention on the need for urgent resuscitation. But lactate is not always assessed in a timely fashion in patients who have deteriorating vital signs. We hypothesized that an electronic medical record (EMR-based decision support system could interact with clinicians to prompt assessment of plasma lactate in appropriate clinical situations in order to risk stratify a population of inpatients and identify those who are acutely deteriorating in real-time. Methods: All adult patients admitted to our hospital over a three month period were monitored by an EMR-based lactate decision support system (lactate DSS programmed to detect patients exhibiting acute organ dysfunction and engage the clinician in the decision to order a plasma lactate concentration. Inpatient mortality was determined for the five risk categories that this system generated, and chart review was performed on a high-risk subgroup to describe the spectrum of bedside events that triggered the system logic. Results: The lactate DSS segregated inpatients into five strata with mortality rates of 0.8% (95%CI:0.6-1.0%; 2.7% (95%CI:1.0-4.4%; 7.9% (95%CI: 6.0-10.1%, 13.0% (95%CI: 9.0-17.8% and 42.1% (95%CI: 32.0-52.4%, achieving a discriminant accuracy of 80% (95%CI:76-84% by AUROC for predicting inpatient mortality. Classification into the two highest risk strata had a positive predictive value for detecting acute life-threatening clinical events of 54% (95%CI: 41.5-66.5%. Conclusions: Our lactate decision support system is different than previously-described computerized “early warning systems”, because it engages the clinician in decision-making and incorporates clinical judgment in risk stratification. Our system has favorable operating characteristics for the prediction of inpatient mortality and real-time detection of acute life

  8. Advances In Infection Surveillance and Clinical Decision Support With Fuzzy Sets and Fuzzy Logic.

    Science.gov (United States)

    Koller, Walter; de Bruin, Jeroen S; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

    2015-01-01

    By the use of extended intelligent information technology tools for fully automated healthcare-associated infection (HAI) surveillance, clinicians can be informed and alerted about the emergence of infection-related conditions in their patients. Moni--a system for monitoring nosocomial infections in intensive care units for adult and neonatal patients--employs knowledge bases that were written with extensive use of fuzzy sets and fuzzy logic, allowing the inherent un-sharpness of clinical terms and the inherent uncertainty of clinical conclusions to be a part of Moni's output. Thus, linguistic as well as propositional uncertainty became a part of Moni, which can now report retrospectively on HAIs according to traditional crisp HAI surveillance definitions, as well as support clinical bedside work by more complex crisp and fuzzy alerts and reminders. This improved approach can bridge the gap between classical retrospective surveillance of HAIs and ongoing prospective clinical-decision-oriented HAI support.

  9. Patient factors that influence clinicians' decision making in self-management support: A clinical vignette study.

    Science.gov (United States)

    Bos-Touwen, Irene D; Trappenburg, Jaap C A; van der Wulp, Ineke; Schuurmans, Marieke J; de Wit, Niek J

    2017-01-01

    Self-management support is an integral part of current chronic care guidelines. The success of self-management interventions varies between individual patients, suggesting a need for tailored self-management support. Understanding the role of patient factors in the current decision making of health professionals can support future tailoring of self-management interventions. The aim of this study is to identify the relative importance of patient factors in health professionals' decision making regarding self-management support. A factorial survey was presented to primary care physicians and nurses. The survey consisted of clinical vignettes (case descriptions), in which 11 patient factors were systematically varied. Each care provider received a set of 12 vignettes. For each vignette, they decided whether they would give this patient self-management support and whether they expected this support to be successful. The associations between respondent decisions and patient factors were explored using ordered logit regression. The survey was completed by 60 general practitioners and 80 nurses. Self-management support was unlikely to be provided in a third of the vignettes. The most important patient factor in the decision to provide self-management support as well as in the expectation that self-management support would be successful was motivation, followed by patient-provider relationship and illness perception. Other factors, such as depression or anxiety, education level, self-efficacy and social support, had a small impact on decisions. Disease, disease severity, knowledge of disease, and age were relatively unimportant factors. This is the first study to explore the relative importance of patient factors in decision making and the expectations regarding the provision of self-management support to chronic disease patients. By far, the most important factor considered was patient's motivation; unmotivated patients were less likely to receive self-management support

  10. Computerized clinical decision support systems for therapeutic drug monitoring and dosing: A decision-maker-researcher partnership systematic review

    Directory of Open Access Journals (Sweden)

    Weise-Kelly Lorraine

    2011-08-01

    Full Text Available Abstract Background Some drugs have a narrow therapeutic range and require monitoring and dose adjustments to optimize their efficacy and safety. Computerized clinical decision support systems (CCDSSs may improve the net benefit of these drugs. The objective of this review was to determine if CCDSSs improve processes of care or patient outcomes for therapeutic drug monitoring and dosing. Methods We conducted a decision-maker-researcher partnership systematic review. Studies from our previous review were included, and new studies were sought until January 2010 in MEDLINE, EMBASE, Evidence-Based Medicine Reviews, and Inspec databases. Randomized controlled trials assessing the effect of a CCDSS on process of care or patient outcomes were selected by pairs of independent reviewers. A study was considered to have a positive effect (i.e., CCDSS showed improvement if at least 50% of the relevant study outcomes were statistically significantly positive. Results Thirty-three randomized controlled trials were identified, assessing the effect of a CCDSS on management of vitamin K antagonists (14, insulin (6, theophylline/aminophylline (4, aminoglycosides (3, digoxin (2, lidocaine (1, or as part of a multifaceted approach (3. Cluster randomization was rarely used (18% and CCDSSs were usually stand-alone systems (76% primarily used by physicians (85%. Overall, 18 of 30 studies (60% showed an improvement in the process of care and 4 of 19 (21% an improvement in patient outcomes. All evaluable studies assessing insulin dosing for glycaemic control showed an improvement. In meta-analysis, CCDSSs for vitamin K antagonist dosing significantly improved time in therapeutic range. Conclusions CCDSSs have potential for improving process of care for therapeutic drug monitoring and dosing, specifically insulin and vitamin K antagonist dosing. However, studies were small and generally of modest quality, and effects on patient outcomes were uncertain, with no convincing

  11. Enabling health care decisionmaking through clinical decision support and knowledge management.

    Science.gov (United States)

    Lobach, David; Sanders, Gillian D; Bright, Tiffani J; Wong, Anthony; Dhurjati, Ravi; Bristow, Erin; Bastian, Lori; Coeytaux, Remy; Samsa, Gregory; Hasselblad, Vic; Williams, John W; Wing, Liz; Musty, Michael; Kendrick, Amy S

    2012-04-01

    To catalogue study designs used to assess the clinical effectiveness of CDSSs and KMSs, to identify features that impact the success of CDSSs/KMSs, to document the impact of CDSSs/KMSs on outcomes, and to identify knowledge types that can be integrated into CDSSs/KMSs. MEDLINE(®), CINAHL(®), PsycINFO(®), and Web of Science(®). We included studies published in English from January 1976 through December 2010. After screening titles and abstracts, full-text versions of articles were reviewed by two independent reviewers. Included articles were abstracted to evidence tables by two reviewers. Meta-analyses were performed for seven domains in which sufficient studies with common outcomes were included. We identified 15,176 articles, from which 323 articles describing 311 unique studies including 160 reports on 148 randomized control trials (RCTs) were selected for inclusion. RCTs comprised 47.5 percent of the comparative studies on CDSSs/KMSs. Both commercially and locally developed CDSSs effectively improved health care process measures related to performing preventive services (n = 25; OR 1.42, 95% confidence interval [CI] 1.27 to 1.58), ordering clinical studies (n = 20; OR 1.72, 95% CI 1.47 to 2.00), and prescribing therapies (n = 46; OR 1.57, 95% CI 1.35 to 1.82). Fourteen CDSS/KMS features were assessed for correlation with success of CDSSs/KMSs across all endpoints. Meta-analyses identified six new success features: Integration with charting or order entry system. Promotion of action rather than inaction. No need for additional clinician data entry. Justification of decision support via research evidence. Local user involvement. Provision of decision support results to patients as well as providers. Three previously identified success features were confirmed: Automatic provision of decision support as part of clinician workflow. Provision of decision support at time and location of decisionmaking. Provision of a recommendation, not just an assessment. Only 29

  12. Reproductive Ethics in Commercial Surrogacy: Decision-Making in IVF Clinics in New Delhi, India.

    Science.gov (United States)

    Tanderup, Malene; Reddy, Sunita; Patel, Tulsi; Nielsen, Birgitte Bruun

    2015-09-01

    As a neo-liberal economy, India has become one of the new health tourism destinations, with commercial gestational surrogacy as an expanding market. Yet the Indian Assisted Reproductive Technology (ART) Bill has been pending for five years, and the guidelines issued by the Indian Council of Medical Research are somewhat vague and contradictory, resulting in self-regulated practices of fertility clinics. This paper broadly looks at clinical ethics in reproduction in the practice of surrogacy and decision-making in various procedures. Through empirical research in New Delhi, the capital of India, from December 2011 to November 2012, issues of decision-making on embryo transfer, fetal reduction, and mode of delivery were identified. Interviews were carried out with doctors in eighteen ART clinics, agents from four agencies, and fourteen surrogates. In aiming to fulfil the commissioning parents' demands, doctors were willing to go to the greatest extent possible in their medical practice. Autonomy and decision-making regarding choice of the number of embryos to transfer and the mode of delivery lay neither with commissioning parents nor surrogate mothers but mostly with doctors. In order to ensure higher success rates, surrogates faced the risk of multiple pregnancy and fetal reduction with little information regarding the risks involved. In the globalized market of commercial surrogacy in India, and with clinics compromising on ethics, there is an urgent need for formulation of regulative law for the clinical practice and maintenance of principles of reproductive ethics in order to ensure that the interests of surrogate mothers are safeguarded.

  13. Clinical decision support tools for osteoporosis disease management: a systematic review of randomized controlled trials.

    Science.gov (United States)

    Kastner, Monika; Straus, Sharon E

    2008-12-01

    Studies indicate a gap between evidence and clinical practice in osteoporosis management. Tools that facilitate clinical decision making at the point of care are promising strategies for closing these practice gaps. To systematically review the literature to identify and describe the effectiveness of tools that support clinical decision making in osteoporosis disease management. Medline, EMBASE, CINAHL, and EBM Reviews (CDSR, DARE, CCTR, and ACP J Club), and contact with experts in the field. Randomized controlled trials (RCTs) in any language from 1966 to July 2006 investigating disease management interventions in patients at risk for osteoporosis. Outcomes included fractures and bone mineral density (BMD) testing. Two investigators independently assessed articles for relevance and study quality, and extracted data using standardized forms. Of 1,246 citations that were screened for relevance, 13 RCTs met the inclusion criteria. Reported study quality was generally poor. Meta-analysis was not done because of methodological and clinical heterogeneity; 77% of studies included a reminder or education as a component of their intervention. Three studies of reminders plus education targeted to physicians and patients showed increased BMD testing (RR range 1.43 to 8.67) and osteoporosis medication use (RR range 1.60 to 8.67). A physician reminder plus a patient risk assessment strategy found reduced fractures [RR 0.58, 95% confidence interval (CI) 0.37 to 0.90] and increased osteoporosis therapy (RR 2.44, CI 1.43 to 4.17). Multi-component tools that are targeted to physicians and patients may be effective for supporting clinical decision making in osteoporosis disease management.

  14. Virtual clinics in glaucoma care: face-to-face versus remote decision-making.

    Science.gov (United States)

    Clarke, Jonathan; Puertas, Renata; Kotecha, Aachal; Foster, Paul J; Barton, Keith

    2017-07-01

    To examine the agreement in clinical decisions of glaucoma status made in a virtual glaucoma clinic with those made during a face-to-face consultation. A trained nurse and technicians entered data prospectively for 204 patients into a proforma. A subsequent face-to-face clinical assessment was completed by either a glaucoma consultant or fellow. Proformas were reviewed remotely by one of two additional glaucoma consultants, and 12 months later, by the clinicians who had undertaken the original clinical examination. The interobserver and intraobserver decision-making agreements of virtual assessment versus standard care were calculated. We identified adverse disagreement between face-to-face and virtual review in 7/204 (3.4%, 95% CI 0.9% to 5.9%) patients, where virtual review failed to predict a need to accelerated follow-up identified in face-to-face review. Misclassification events were rare, occurring in 1.9% (95% CI 0.3% to 3.8%) of assessments. Interobserver κ (95% CI) showed only fair agreement (0.24 (0.04 to 0.43)); this improved to moderate agreement when only consultant decisions were compared against each other (κ=0.41 (0.16 to 0.65)). The intraobserver agreement κ (95% CI) for the consultant was 0.274 (0.073 to 0.476), and that for the fellow was 0.264 (0.031 to 0.497). The low rate of adverse misclassification, combined with the slowly progressive nature of most glaucoma, and the fact that patients will all be regularly reassessed, suggests that virtual clinics offer a safe, logistically viable option for selected patients with glaucoma. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  15. Physician's expectations regarding prescribing clinical decision support systems in a Belgian hospital.

    Science.gov (United States)

    Cornu, P; Steurbaut, S; De Beukeleer, M; Putman, K; van de Velde, R; Dupont, A G

    2014-06-01

    Developing and implementing clinical decision support systems (CDSSs) is time-consuming and costly. Therefore, prioritization of the most relevant systems is warranted. The physician's perceived usefulness has been identified as a decisive reason for using CDSSs. The objective of this study was to investigate the physician's perceived usefulness of different types of CDSSs and to identify the user needs and expectations regarding future CDSSs. Cross-sectional single-centre survey among physicians with a clinical assignment in a university hospital. Physicians were questioned about their current experiences with drug prescribing and the perceived usefulness and desired features of future CDSSs. One hundred and sixty-four physicians completed the survey (52·6%). The majority acknowledged that it is very difficult to take all relevant information into account when prescribing drugs. Drug-drug interaction checking, drug-allergy checking, and dosing guidance were considered as most useful. Automated clinical guidelines and adverse drug event monitoring were considered as least useful. The user-friendliness of the systems, clinical relevance of the alerts, and prevention of alert fatigue were perceived as important aspects for a successful implementation. From the physicians' perspective drug-drug interaction checking, drug-allergy checking, and dosing guidance should receive the highest priority for development and implementation. Because the perceived usefulness has been identified as a decisive reason for using CDSSs, it seems feasible to take into account this prioritization when developing and implementing CDSSs. In order to overcome the physicians' perceived disadvantages, attention should go to the development of user-friendly systems that deliver clinical relevant alerts.

  16. Earthquake Vulnerability Assessment for Hospital Buildings Using a Gis-Based Group Multi Criteria Decision Making Approach: a Case Study of Tehran, Iran

    Science.gov (United States)

    Delavar, M. R.; Moradi, M.; Moshiri, B.

    2015-12-01

    Nowadays, urban areas are threatened by a number of natural hazards such as flood, landslide and earthquake. They can cause huge damages to buildings and human beings which necessitates disaster mitigation and preparation. One of the most important steps in disaster management is to understand all impacts and effects of disaster on urban facilities. Given that hospitals take care of vulnerable people reaction of hospital buildings against earthquake is vital. In this research, the vulnerability of hospital buildings against earthquake is analysed. The vulnerability of buildings is related to a number of criteria including age of building, number of floors, the quality of materials and intensity of the earthquake. Therefore, the problem of seismic vulnerability assessment is a multi-criteria assessment problem and multi criteria decision making methods can be used to address the problem. In this paper a group multi criteria decision making model is applied because using only one expert's judgments can cause biased vulnerability maps. Sugeno integral which is able to take into account the interaction among criteria is employed to assess the vulnerability degree of buildings. Fuzzy capacities which are similar to layer weights in weighted linear averaging operator are calculated using particle swarm optimization. Then, calculated fuzzy capacities are included into the model to compute a vulnerability degree for each hospital.

  17. Geo-portal as a planning instrument: supporting decision making and fostering market potential of Energy efficiency in buildings

    Science.gov (United States)

    Cuca, Branka; Brumana, Raffaella; Oreni, Daniela; Iannaccone, Giuliana; Sesana, Marta

    2014-03-01

    Steady technological progress has led to a noticeable advancement in disciplines associated with Earth observation. This has enabled information transition regarding changing scenarios, both natural and urban, to occur in (almost) real time. In particular, the need for integration on a local scale with the wider territorial framework has occurred in analysis and monitoring of built environments over the last few decades. The progress of Geographic Information (GI) science has provided significant advancements when it comes to spatial analysis, while the almost free availability of the internet has ensured a fast and constant exchange of geo-information, even for everyday users' requirements. Due to its descriptive and semantic nature, geo-spatial information is capable of providing a complete overview of a certain phenomenon and of predicting the implications within the natural, social and economic context. However, in order to integrate geospatial data into decision making processes, it is necessary to provide a specific context, which is well supported by verified data. This paper investigates the potentials of geo-portals as planning instruments developed to share multi-temporal/multi-scale spatial data, responding to specific end-users' demands in the case of Energy efficiency in Buildings (EeB) across European countries. The case study regards the GeoCluster geo-portal and mapping tool (Project GE2O, FP7), built upon a GeoClustering methodology for mapping of indicators relevant for energy efficiency technologies in the construction sector.

  18. Net-zero Building Cluster Simulations and On-line Energy Forecasting for Adaptive and Real-Time Control and Decisions

    Science.gov (United States)

    Li, Xiwang

    Buildings consume about 41.1% of primary energy and 74% of the electricity in the U.S. Moreover, it is estimated by the National Energy Technology Laboratory that more than 1/4 of the 713 GW of U.S. electricity demand in 2010 could be dispatchable if only buildings could respond to that dispatch through advanced building energy control and operation strategies and smart grid infrastructure. In this study, it is envisioned that neighboring buildings will have the tendency to form a cluster, an open cyber-physical system to exploit the economic opportunities provided by a smart grid, distributed power generation, and storage devices. Through optimized demand management, these building clusters will then reduce overall primary energy consumption and peak time electricity consumption, and be more resilient to power disruptions. Therefore, this project seeks to develop a Net-zero building cluster simulation testbed and high fidelity energy forecasting models for adaptive and real-time control and decision making strategy development that can be used in a Net-zero building cluster. The following research activities are summarized in this thesis: 1) Development of a building cluster emulator for building cluster control and operation strategy assessment. 2) Development of a novel building energy forecasting methodology using active system identification and data fusion techniques. In this methodology, a systematic approach for building energy system characteristic evaluation, system excitation and model adaptation is included. The developed methodology is compared with other literature-reported building energy forecasting methods; 3) Development of the high fidelity on-line building cluster energy forecasting models, which includes energy forecasting models for buildings, PV panels, batteries and ice tank thermal storage systems 4) Small scale real building validation study to verify the performance of the developed building energy forecasting methodology. The outcomes of

  19. Sick building syndrome (SBS) and exposure to water-damaged buildings: time series study, clinical trial and mechanisms.

    Science.gov (United States)

    Shoemaker, Ritchie C; House, Dennis E

    2006-01-01

    Occupants of water-damaged buildings (WDBs) with evidence of microbial amplification often describe a syndrome involving multiple organ systems, commonly referred to as "sick building syndrome" (SBS), following chronic exposure to the indoor air. Studies have demonstrated that the indoor air of WDBs often contains a complex mixture of fungi, mycotoxins, bacteria, endotoxins, antigens, lipopolysaccharides, and biologically produced volatile compounds. A case-series study with medical assessments at five time points was conducted to characterize the syndrome after a double-blinded, placebo-controlled clinical trial conducted among a group of study participants investigated the efficacy of cholestyramine (CSM) therapy. The general hypothesis of the time series study was that chronic exposure to the indoor air of WDBs is associated with SBS. Consecutive clinical patients were screened for diagnosis of SBS using criteria of exposure potential, symptoms involving at least five organ systems, and the absence of confounding factors. Twenty-eight cases signed voluntary consent forms for participation in the time-series study and provided samples of microbial contaminants from water-damaged areas in the buildings they occupied. Twenty-six participants with a group-mean duration of illness of 11 months completed examinations at all five study time points. Thirteen of those participants also agreed to complete a double-blinded, placebo-controlled clinical trial. Data from Time Point 1 indicated a group-mean of 23 out of 37 symptoms evaluated; and visual contrast sensitivity (VCS), an indicator of neurological function, was abnormally low in all participants. Measurements of matrix metalloproteinase 9 (MMP9), leptin, alpha melanocyte stimulating hormone (MSH), vascular endothelial growth factor (VEGF), immunoglobulin E (IgE), and pulmonary function were abnormal in 22, 13, 25, 14, 1, and 7 participants, respectively. Following 2 weeks of CSM therapy to enhance toxin elimination

  20. Which criteria considered in healthcare decisions? Insights from an international survey of policy and clinical decision makers

    NARCIS (Netherlands)

    Tanios, Nataly; Wagner, Monika; Tony, Michele; Baltussen, Rob; van Til, Janine Astrid; Rindress, Donna; Kind, Paul; Goetghebeur, Mireille M.

    2013-01-01

    Objectives: The aim of this study was to gather qualitative and quantitative data on criteria considered by healthcare decision makers. Methods: Using snowball sampling and an online questionnaire with forty-three criteria organized into ten clusters, decision makers were invited by an international

  1. Which criteria are considered in healthcare decisions? Insights from an international survey of policy and clinical decision makers

    NARCIS (Netherlands)

    Tanios, N.; Wagner, M.; Tony, M.; Baltussen, R.M.; Til, J. van; Rindress, D.; Kind, P.; Goetghebeur, M.M.; Decision, C. International T

    2013-01-01

    Objectives: The aim of this study was to gather qualitative and quantitative data on criteria considered by healthcare decision makers. Methods: Using snowball sampling and an online questionnaire with forty-three criteria organized into ten clusters, decision makers were invited by an international

  2. [Human body meridian spatial decision support system for clinical treatment and teaching of acupuncture and moxibustion].

    Science.gov (United States)

    Wu, Dehua

    2016-01-01

    The spatial position and distribution of human body meridian are expressed limitedly in the decision support system (DSS) of acupuncture and moxibustion at present, which leads to the failure to give the effective quantitative analysis on the spatial range and the difficulty for the decision-maker to provide a realistic spatial decision environment. Focusing on the limit spatial expression in DSS of acupuncture and moxibustion, it was proposed that on the basis of the geographic information system, in association of DSS technology, the design idea was developed on the human body meridian spatial DSS. With the 4-layer service-oriented architecture adopted, the data center integrated development platform was taken as the system development environment. The hierarchical organization was done for the spatial data of human body meridian via the directory tree. The structured query language (SQL) server was used to achieve the unified management of spatial data and attribute data. The technologies of architecture, configuration and plug-in development model were integrated to achieve the data inquiry, buffer analysis and program evaluation of the human body meridian spatial DSS. The research results show that the human body meridian spatial DSS could reflect realistically the spatial characteristics of the spatial position and distribution of human body meridian and met the constantly changeable demand of users. It has the powerful spatial analysis function and assists with the scientific decision in clinical treatment and teaching of acupuncture and moxibustion. It is the new attempt to the informatization research of human body meridian.

  3. Patient Perceptions of Illness Identity in Cancer Clinical Trial Decision-Making.

    Science.gov (United States)

    Palmer-Wackerly, Angela L; Dailey, Phokeng M; Krok-Schoen, Jessica L; Rhodes, Nancy D; Krieger, Janice L

    2017-06-16

    When patients are diagnosed with cancer, they begin to negotiate their illness identity in relation to their past and future selves, their relationships, and their group memberships. Thus, how patients view their cancer in relation to their other identities may affect how and why they make particular decisions about treatment options. Using the Communication Theory of Identity (CTI), the current study explores: (1) how and why illness identity is framed across identity layers in relation to one particular cancer treatment: participation in a cancer clinical trial (CT); and (2) how and why patients experience identity conflicts while making their treatment decisions. Semi-structured, in-depth interviews were analyzed for 46 cancer patients who were offered a CT. Results of a grounded theory analysis indicated that patients expressed separate identity frames (e.g., personal, relational, and communal), aligned identity frames (e.g., personal and communal), and identity conflicts (e.g., personal-personal). This study theoretically shows how and why patient illness identity relates to cancer treatment decision-making as well as how and why patients relate (and conflict) with the cancer communal identity frame. Practical implications include how healthcare providers and family members can support patient decision-making through awareness of and accommodating to identity shifts.

  4. Development of a formal structure for clinical management decisions: a mathematical analysis.

    Science.gov (United States)

    Card, W I

    1975-01-01

    Decision theory and the calculating power of the computer now enables us to contemplate the development of formal methods for making decisions about clinical management. In the simplest model, it is first necessary to define all treatment decisions as an exhaustive and mutually exclusive set and similarly to define the set of consequences or outcomes of treatment. The probability of each outcome conditional on treatment has to be estimated and this consequent state of health has to be quantified as a utility. Possible methods of estimating utilities of states of health are discussed and the construction of a unidimensional utility function based on a sequence of wagers. The states of health consequent on severe brain damage can only be described multidimensionally and the model has to be extended to include this case. While such a model would allow simple treatment decisions to be formalized, it could not decide whether the cost of treatment was worth while nor whether it would pay to carry out further investigative tests and thus buy more evidence. If these additional variables are to be included in the model, it is necessary to introduce the motion of an equivalence between monetary values and utilities. This implies attaching a monetary value to any given state of health.

  5. Formative evaluation of the accuracy of a clinical decision support system for cervical cancer screening.

    Science.gov (United States)

    Wagholikar, Kavishwar Balwant; MacLaughlin, Kathy L; Kastner, Thomas M; Casey, Petra M; Henry, Michael; Greenes, Robert A; Liu, Hongfang; Chaudhry, Rajeev

    2013-01-01

    We previously developed and reported on a prototype clinical decision support system (CDSS) for cervical cancer screening. However, the system is complex as it is based on multiple guidelines and free-text processing. Therefore, the system is susceptible to failures. This report describes a formative evaluation of the system, which is a necessary step to ensure deployment readiness of the system. Care providers who are potential end-users of the CDSS were invited to provide their recommendations for a random set of patients that represented diverse decision scenarios. The recommendations of the care providers and those generated by the CDSS were compared. Mismatched recommendations were reviewed by two independent experts. A total of 25 users participated in this study and provided recommendations for 175 cases. The CDSS had an accuracy of 87% and 12 types of CDSS errors were identified, which were mainly due to deficiencies in the system's guideline rules. When the deficiencies were rectified, the CDSS generated optimal recommendations for all failure cases, except one with incomplete documentation. The crowd-sourcing approach for construction of the reference set, coupled with the expert review of mismatched recommendations, facilitated an effective evaluation and enhancement of the system, by identifying decision scenarios that were missed by the system's developers. The described methodology will be useful for other researchers who seek rapidly to evaluate and enhance the deployment readiness of complex decision support systems.

  6. Clinical decision velocity is increased when meta-search filters enhance an evidence retrieval system.

    Science.gov (United States)

    Coiera, Enrico; Westbrook, Johanna I; Rogers, Kris

    2008-01-01

    To test whether the use of an evidence retrieval system that uses clinically targeted meta-search filters can enhance the rate at which clinicians make correct decisions, reduce the effort involved in locating evidence, and provide an intuitive match between clinical tasks and search filters. A laboratory experiment under controlled conditions asked 75 clinicians to answer eight randomly sequenced clinical questions, using one of two randomly assigned search engines. The first search engine Quick Clinical (QC) was equipped with meta-search filters (the combined use of meta-search and search filters) designed to answer typical clinical questions e.g., treatment, diagnosis, and the second 'library model' system (LM) offered free access to an identical evidence set with no filter support. Changes in clinical decision making were measured by the proportion of correct post-search answers provided to questions, the time taken to answer questions, and the number of searches and links to documents followed in a search session. The intuitive match between meta-search filters and clinical tasks was measured by the proportion and distribution of filters selected for individual clinical questions. Clinicians in the two groups performed equally well pre-search. Post search answers improved overall by 21%, with 52.2% of answers correct with QC and 54.7% with LM (chi(2) = 0.33, df = 1, p > 0.05). Users of QC obtained a significantly greater percentage of their correct answers within the first two minutes of searching compared to LM users (QC 58.2%; LM 32.9%; chi(2) = 19.203, df = 1, p searches per scenario (m = 3.0 SD = 1.15 versus m = 5.5 SD1.97, t = 6.63, df = 72, p = 0.0001). Clinicians using the QC system followed fewer document links than did those who used LM (respectively 3.9 links SD = 1.20 versus 4.7 links SD = 1.79, t = 2.13, df = 72, p = 0.0368). In 6 of the 8 questions, two meta-search filters accounted for 89% or more of clinicians' first choice, suggesting the

  7. Is there a "magic" hemoglobin number? Clinical decision support promoting restrictive blood transfusion practices.

    Science.gov (United States)

    Goodnough, Lawrence Tim; Shah, Neil

    2015-10-01

    Blood transfusion has been identified as one of the most frequently performed therapeutic procedures, with a significant percentage of transfusions identified to be inappropriate. Recent key clinical trials in adults have provided Level 1 evidence to support restrictive red blood cell (RBC) transfusion practices. However, some advocates have attempted to identify a "correct" Hb threshold for RBC transfusion; whereas others assert that management of anemia, including transfusion decisions, must take into account clinical patient variables, rather than simply one diagnostic laboratory test. The heterogeneity of guidelines for blood transfusion by a number of medical societies reflects this controversy. Clinical decision support (CDS) uses a Hb threshold number in a smart Best Practices Alert (BPA) upon physician order, to trigger a concurrent utilization self-review for whether blood transfusion therapy is appropriate. This review summarizes Level 1 evidence in seven key clinical trials in adults that support restrictive transfusion practices, along strategies made possible by CDS that have demonstrated value in improving blood utilization by promoting restrictive transfusion practices. © 2015 Wiley Periodicals, Inc.

  8. Cervical spine degenerative diseases: An evaluation of clinical and imaging features in surgical decisions

    Energy Technology Data Exchange (ETDEWEB)

    Soo, M.; Tran-Dinh, H.D.; Quach, T.; Downey, J.; Pohlmann, S. [Westmead Hospital, Westmead, NSW (Australia). Department of Radiology; Dorsch, N.W.C. [Westmead Hospital, Westmead, NSW (Australia). Department of Neurosurgery

    1997-11-01

    In clinically severe cervical spondylosis, imaging plays a vital role in surgical decisions. A prime factor is acquired canal stenosis with cord compression. To validate this concept, the clinical and imaging features of 20 patients with spondylitic myelopathy and 24 with radiculopathy were retrospectively reviewed. All had computed tomographic myelography (CTM) as part of their clinical work-up. The patients` clinical severity was graded as mild, moderate and severe; the age, length of illness and a history of eventual surgery or otherwise were recorded. At the level of maximum compression the following parameters were obtained from the axial CTM images: surface area and ratio of the anteroposterior to the transverse diameter of the cord; subarachnoid space and vertebral canal areas. Data were statistically analysed. A significant association exists between surgery and increasing severity of symptoms (P=0.04), and advancing age (P=0.01). These associations hold true for myelopathy and radiculopathy. A strong association is present between surgery and the surface area of the cord (P=0.01), being applicable to myelopathy only. The other parameters show no association with surgical decisions. It is concluded that with myelopathy a narrow cord area at the level of maximum compression, and moderate-severe functional impairment are indicators for surgical intervention. (authors). 22 refs., 3 tabs., 3 figs.

  9. Trail Blazing or Jam Session? Towards a New Concept of Clinical Decision-making.

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    Risør, Torsten

    2017-04-01

    Clinical decision-making (CDM) is key in learning to be a doctor as the defining activity in their clinical work. CDM is often portrayed in the literature as similar to 'trail blazing'; the doctor as the core agent, clearing away obstacles on the path towards diagnosis and treatment. However, in a fieldwork of young doctors in Denmark, it was difficult connect their practice to this image. This paper presents the exploration of this discrepancy in the heart of medical practice and how an alternative image emerged; that of a 'jam session'. The exploration is represented as a case-based hypothesis-testing: first, a theoretically and empirically informed hypothesis (H0) of how doctors perform CDM is developed. In H0, CDM is a stepwise process of reasoning about clinical data, often influenced by outside contextual factors. Then, H0 is tested against a case from ethnographic fieldwork with doctors going through internship. Although the case is chosen for characteristics that make it 'most likely' to verify the hypothesis, verification proves difficult. The case challenges preconceptions in CDM literature about chronology, context, objectivity, cognition, agency, and practice. The young doctor is found not to make decisions, but rather to participate in CDM; an activity akin to the dynamics found in a jam session. Their participation circles in and through four concurrent interrelated constructions that suggest a new conceptualization of CDM; a starting point for a deeper understanding of actual practice in a changing clinical environment.

  10. Patient exposure in the basic science classroom enhances differential diagnosis formation and clinical decision-making

    Directory of Open Access Journals (Sweden)

    Justin G. Peacock

    2015-02-01

    Full Text Available Purpose. The authors proposed that introducing real patients into a pathology classroom early in medical education would help integrate fundamental principles and disease pathology with clinical presentation and medical history.Methods. Three patients with different pathologies described their history and presentation without revealing their diagnosis. Students were required to submit a differential diagnosis in writing, and then were able to ask questions to arrive at the correct diagnosis. Students were surveyed on the efficacy of patient-based learning.Results. Average student scores on the differential diagnosis assignments significantly improved 32% during the course. From the survey, 72% of students felt that patient encounters should be included in the pathology course next year. Seventy-four percent felt that the differential diagnosis assignments helped them develop clinical decision-making skills. Seventy-three percent felt that the experience helped them know what questions to ask patients. Eighty-six percent felt that they obtained a better understanding of patients’ social and emotional challenges.Discussion. Having students work through the process of differential diagnosis formulation when encountering a real patient and their clinical presentation improved clinical decision-making skills and integrated fundamental concepts with disease pathology during a basic science pathology course.

  11. Clinical reasoning and population health: decision making for an emerging paradigm of health care.

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    Edwards, Ian; Richardson, Barbara

    2008-01-01

    Chronic conditions now provide the major disease and disability burden facing humanity. This development has necessitated a reorientation in the practice skills of health care professions away from hospital-based inpatient and outpatient care toward community-based management of patients with chronic conditions. Part of this reorientation toward community-based management of chronic conditions involves practitioners' understanding and adoption of a concept of population health management based on appropriate theoretical models of health care. Drawing on recent studies of expertise in physiotherapy, this article proposes a clinical reasoning and decision-making framework to meet these challenges. The challenge of population and community-based management of chronic conditions also provides an opportunity for physiotherapists to further clarify a professional epistemology of practice that embraces the kinds of knowledge and clinical reasoning processes used in physiotherapy practice. Three case studies related to the management of chronic musculoskeletal pain in different populations are used to exemplify the range of epistemological perspectives that underpin community-based practice. They illustrate the link between conceptualizations of practice problems and knowledge sources that are used as a basis for clinical reasoning and decision making as practitioners are increasingly required to move between the clinic and the community.

  12. The integration of surface electromyography in the clinical decision making process: a case report

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    Nicholson, W Reg

    1998-01-01

    Objective: To demonstrate how the findings of surface electromyography (S.E.M.G.) were integrated into the clinical decision-making process. Clinical Features: This is a retrospective review of the file of a 27-year-old male suffering from mechanical low back pain. He was evaluated on 3 separate occasions over a 3 year period. History, radiography, functional outcome studies, visual-numerical pain score, pain drawing, physical examination and surface electromyography were utilized in evaluating this patient. Intervention and Outcome: The two clinical interventions of spinal manipulative therapy (S.M.T.) had positive results in that the patient achieved an asymptomatic state and returned to his position of employment. The S.E.M.G. data collected during the industrial assessment, did not provide the outcome that the patient had anticipated. Conclusion: Surface electromyography is a useful clinical tool in the author’s decision-making process for the treatment of mechanical lower back pain. Therapeutic intervention by S.M.T., therapeutic exercises and rating risk factors were influenced by the S.E.M.G. findings.

  13. The role of clinical decision support in pharmacist response to drug-interaction alerts.

    Science.gov (United States)

    Miller, Luke; Steinmetz Pater, Karen; Corman, Shelby

    2015-01-01

    With over 100,000 different types of drug-drug interactions health care professionals rely heavily on automated drug-interaction alerts. Substantial variance in drug-interaction alerts yields opportunities for the use of clinical decision support (CDS) as a potential benefit to pharmacists. The purpose of this research was to determine whether decision support during dispensing impacts pharmacist response to drug-interaction alerts. A brief survey was administered to pharmacists in the community consisting of three patient cases, each containing three drug-drug interactions of varying severity. For each interaction, pharmacists were asked how they would respond, one group of pharmacists was randomly assigned to receive CDS while the other group did not. There were no significant differences in pharmacist response to alerts between the two groups. The control group did appear to be more likely to consult a drug reference, but this difference was not significant. While this study did not demonstrate a significant difference, drug-interaction alerts are still an area where improvements could be made. Advancements have the potential to reduce risk to patients and limit unnecessary hospital admissions. This study suggests that this level of clinical decision support has limited impact, but may prove beneficial by reducing the need to consult additional references. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Cancer Multidisciplinary Team Meetings: Evidence, Challenges, and the Role of Clinical Decision Support Technology

    Science.gov (United States)

    Patkar, Vivek; Acosta, Dionisio; Davidson, Tim; Jones, Alison; Fox, John; Keshtgar, Mohammad

    2011-01-01

    Multidisciplinary team (MDT) model in cancer care was introduced and endorsed to ensure that care delivery is consistent with the best available evidence. Over the last few years, regular MDT meetings have become a standard practice in oncology and gained the status of the key decision-making forum for patient management. Despite the fact that cancer MDT meetings are well accepted by clinicians, concerns are raised over the paucity of good-quality evidence on their overall impact. There are also concerns over lack of the appropriate support for this important but overburdened decision-making platform. The growing acceptance by clinical community of the health information technology in recent years has created new opportunities and possibilities of using advanced clinical decision support (CDS) systems to realise full potential of cancer MDT meetings. In this paper, we present targeted summary of the available evidence on the impact of cancer MDT meetings, discuss the reported challenges, and explore the role that a CDS technology could play in addressing some of these challenges. PMID:22295234

  15. Cancer Multidisciplinary Team Meetings: Evidence, Challenges, and the Role of Clinical Decision Support Technology

    Directory of Open Access Journals (Sweden)

    Vivek Patkar

    2011-01-01

    Full Text Available Multidisciplinary team (MDT model in cancer care was introduced and endorsed to ensure that care delivery is consistent with the best available evidence. Over the last few years, regular MDT meetings have become a standard practice in oncology and gained the status of the key decision-making forum for patient management. Despite the fact that cancer MDT meetings are well accepted by clinicians, concerns are raised over the paucity of good-quality evidence on their overall impact. There are also concerns over lack of the appropriate support for this important but overburdened decision-making platform. The growing acceptance by clinical community of the health information technology in recent years has created new opportunities and possibilities of using advanced clinical decision support (CDS systems to realise full potential of cancer MDT meetings. In this paper, we present targeted summary of the available evidence on the impact of cancer MDT meetings, discuss the reported challenges, and explore the role that a CDS technology could play in addressing some of these challenges.

  16. Formative Evaluation of Clinician Experience with Integrating Family History-Based Clinical Decision Support into Clinical Practice

    Directory of Open Access Journals (Sweden)

    Megan Doerr

    2014-03-01

    Full Text Available Family health history is a leading predictor of disease risk. Nonetheless, it is underutilized to guide care and, therefore, is ripe for health information technology intervention. To fill the family health history practice gap, Cleveland Clinic has developed a family health history collection and clinical decision support tool, MyFamily. This report describes the impact and process of implementing MyFamily into primary care, cancer survivorship and cancer genetics clinics. Ten providers participated in semi-structured interviews that were analyzed to identify opportunities for process improvement. Participants universally noted positive effects on patient care, including increases in quality, personalization of care and patient engagement. The impact on clinical workflow varied by practice setting, with differences observed in the ease of integration and the use of specific report elements. Tension between the length of the report and desired detail was appreciated. Barriers and facilitators to the process of implementation were noted, dominated by the theme of increased integration with the electronic medical record. These results fed real-time improvement cycles to reinforce clinician use. This model will be applied in future institutional efforts to integrate clinical genomic applications into practice and may be useful for other institutions considering the implementation of tools for personalizing medical management.

  17. Evaluation of clinical rules in a standalone pharmacy based clinical decision support system for hospitalized and nursing home patients.

    Science.gov (United States)

    de Wit, Hugo A J M; Mestres Gonzalvo, Carlota; Cardenas, Jenny; Derijks, Hieronymus J; Janknegt, Rob; van der Kuy, Paul-Hugo M; Winkens, Bjorn; Schols, Jos M G A

    2015-06-01

    To improve the current standalone pharmacy clinical decision support system (CDSS) by identifying and quantifying the benefits and limitations of the system. Alerts and handling of the executed clinical rules were extracted from the CDSS from the period September 2011 to December 2011. The number of executed clinical rule alerts, number of actions on alerts, and the reason why alerts were classified as not relevant were analyzed. The alerts where considered clinically relevant when the pharmacist needed to contact the physician. The 4065 alerts have been separated into: 1137 (28.0%) new alerts, 2797 (68.8%) repeat alerts and 131 (3.2%) double alerts. When the alerts were analyzed, only 3.6% were considered clinically relevant. Reasons why alerts were considered as not to be relevant were: (a) the dosage was correct or already adjusted, (b) the drug was (temporarily) stopped and (c) the monitored laboratory value or drug dosage had already reverted to be within the reference limits. The reasons for no action were linked to three categorical limitations of the used system: 'algorithm alert criteria', 'CDSS optimization', and 'data delivery'. This study highlighted a number of ways in which the CDSS could be improved. These different aspects have been identified as important for developing an efficient CDSS. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  18. Interim analysis: A rational approach of decision making in clinical trial.

    Science.gov (United States)

    Kumar, Amal; Chakraborty, Bhaswat S

    2016-01-01

    Interim analysis of especially sizeable trials keeps the decision process free of conflict of interest while considering cost, resources, and meaningfulness of the project. Whenever necessary, such interim analysis can also call for potential termination or appropriate modification in sample size, study design, and even an early declaration of success. Given the extraordinary size and complexity today, this rational approach helps to analyze and predict the outcomes of a clinical trial that incorporate what is learned during the course of a study or a clinical development program. Such approach can also fill the gap by directing the resources toward relevant and optimized clinical trials between unmet medical needs and interventions being tested currently rather than fulfilling only business and profit goals.

  19. Clinical Decision-making for Caries Management in Children: An Update.

    Science.gov (United States)

    Slayton, Rebecca L

    2015-01-01

    Dental caries continues to be one of the most common chronic diseases of childhood. Medical management of this disease has the potential to decrease the burden of disease in the most vulnerable children and delay the need for surgical intervention. Effective medical management requires early and effective risk assessment to identify individuals at risk prior to disease occurrence. The purpose of this review of clinical decision-making for caries management in children was to translate current knowledge of cariology into clinically relevant concepts and procedures. Patient-specific approaches, such as individual risk assessment, active surveillance, and preventive therapies-supplemented, when necessary, by restorative care-should be emphasized. Clinical findings should inform the type and frequency of therapy recommended on an individual basis. As more is learned about this common complex disorder, it is anticipated that educational strategies for students, practitioners, and families will change to reflect new evidence and risk-based care.

  20. Sharing clinical decisions for multimorbidity case management using social network and open-source tools.

    Science.gov (United States)

    Martínez-García, Alicia; Moreno-Conde, Alberto; Jódar-Sánchez, Francisco; Leal, Sandra; Parra, Carlos

    2013-12-01

    Social networks applied through Web 2.0 tools have gained importance in health domain, because they produce improvements on the communication and coordination capabilities among health professionals. This is highly relevant for multimorbidity patients care because there is a large number of health professionals in charge of patient care, and this requires to obtain clinical consensus in their decisions. Our objective is to develop a tool for collaborative work among health professionals for multimorbidity patient care. We describe the architecture to incorporate decision support functionalities in a social network tool to enable the adoption of shared decisions among health professionals from different care levels. As part of the first stage of the project, this paper describes the results obtained in a pilot study about acceptance and use of the social network component in our healthcare setting. At Virgen del Rocío University Hospital we have designed and developed the Shared Care Platform (SCP) to provide support in the continuity of care for multimorbidity patients. The SCP has two consecutively developed components: social network component, called Clinical Wall, and Clinical Decision Support (CDS) system. The Clinical Wall contains a record where health professionals are able to debate and define shared decisions. We conducted a pilot study to assess the use and acceptance of the SCP by healthcare professionals through questionnaire based on the theory of the Technology Acceptance Model. In March 2012 we released and deployed the SCP, but only with the social network component. The pilot project lasted 6 months in the hospital and 2 primary care centers. From March to September 2012 we created 16 records in the Clinical Wall, all with a high priority. A total of 10 professionals took part in the exchange of messages: 3 internists and 7 general practitioners generated 33 messages. 12 of the 16 record (75%) were answered by the destination health professionals

  1. Untapped Potential of Observational Research to Inform Clinical Decision Making: American Society of Clinical Oncology Research Statement.

    Science.gov (United States)

    Visvanathan, Kala; Levit, Laura A; Raghavan, Derek; Hudis, Clifford A; Wong, Sandra; Dueck, Amylou; Lyman, Gary H

    2017-06-01

    ASCO believes that high-quality observational studies can advance evidence-based practice for cancer care and are complementary to randomized controlled trials (RCTs). Observational studies can generate hypotheses by evaluating novel exposures or biomarkers and by revealing patterns of care and relationships that might not otherwise be discovered. Researchers can then test these hypotheses in RCTs. Observational studies can also answer or inform questions that either have not been or cannot be answered by RCTs. In addition, observational studies can be used for postmarketing surveillance of new cancer treatments, particularly in vulnerable populations. The incorporation of observational research as part of clinical decision making is consistent with the position of many leading institutions. ASCO identified five overarching recommendations to enhance the role of observational research in clinical decision making: (1) improve the quality of electronic health data available for research, (2) improve interoperability and the exchange of electronic health information, (3) ensure the use of rigorous observational research methodologies, (4) promote transparent reporting of observational research studies, and (5) protect patient privacy.

  2. Clinical decision aids for chest pain in the emergency department: identifying low-risk patients

    Directory of Open Access Journals (Sweden)

    Alley W

    2015-11-01

    Full Text Available William Alley, Simon A Mahler Department of Emergency Medicine, Wake Forest Baptist Medical Center, Winston-Salem, NC, USA Abstract: Chest pain is one of the most common presenting complaints in the emergency department, though only a small minority of patients are subsequently diagnosed with acute coronary syndrome (ACS. However, missing the diagnosis has potential for significant morbidity and mortality. ACS presentations can be atypical, and their workups are often prolonged and costly. In order to risk-stratify patients and better direct the workup and care given, many decision aids have been developed. While each may have merit in certain clinical settings, the most useful aid in the emergency department is one that finds all cases of ACS while also identifying a substantial subset of patients at low risk who can be discharged without stress testing or coronary angiography. This review describes several of the chest pain decision aids developed and studied through the recent past, starting with the thrombolysis in myocardial infarction (TIMI risk score and Global Registry of Acute Coronary Events (GRACE scores, which were developed as prognostic aids for patients already diagnosed with ACS, then subsequently validated in the undifferentiated chest pain population. Asia-Pacific Evaluation of Chest Pain Trial (ASPECT; Accelerated Diagnostic Protocol to Assess Patients With Chest Pain Symptoms Using Contemporary Troponins (ADAPT; North American Chest Pain Rule (NACPR; and History, Electrocardiogram, Age, Risk factors, Troponin (HEART score have been developed exclusively for use in the undifferentiated chest pain population as well, with improved performance compared to their predecessors. This review describes the relative merits and limitations of these decision aids so that providers can determine which tool fits the needs of their clinical practice setting. Keywords: chest pain, decision aid, risk score, acute coronary syndrome

  3. Comparison of Computer-based Clinical Decision Support Systems and Content for Diabetes Mellitus.

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    Kantor, M; Wright, A; Burton, M; Fraser, G; Krall, M; Maviglia, S; Mohammed-Rajput, N; Simonaitis, L; Sonnenberg, F; Middleton, B

    2011-01-01

    Computer-based clinical decision support (CDS) systems have been shown to improve quality of care and workflow efficiency, and health care reform legislation relies on electronic health records and CDS systems to improve the cost and quality of health care in the United States; however, the heterogeneity of CDS content and infrastructure of CDS systems across sites is not well known. We aimed to determine the scope of CDS content in diabetes care at six sites, assess the capabilities of CDS in use at these sites, characterize the scope of CDS infrastructure at these sites, and determine how the sites use CDS beyond individual patient care in order to identify characteristics of CDS systems and content that have been successfully implemented in diabetes care. We compared CDS systems in six collaborating sites of the Clinical Decision Support Consortium. We gathered CDS content on care for patients with diabetes mellitus and surveyed institutions on characteristics of their site, the infrastructure of CDS at these sites, and the capabilities of CDS at these sites. The approach to CDS and the characteristics of CDS content varied among sites. Some commonalities included providing customizability by role or user, applying sophisticated exclusion criteria, and using CDS automatically at the time of decision-making. Many messages were actionable recommendations. Most sites had monitoring rules (e.g. assessing hemoglobin A1c), but few had rules to diagnose diabetes or suggest specific treatments. All sites had numerous prevention rules including reminders for providing eye examinations, influenza vaccines, lipid screenings, nephropathy screenings, and pneumococcal vaccines. Computer-based CDS systems vary widely across sites in content and scope, but both institution-created and purchased systems had many similar features and functionality, such as integration of alerts and reminders into the decision-making workflow of the provider and providing messages that are

  4. mHealth for Clinical Decision-Making in Sub-Saharan Africa: A Scoping Review.

    Science.gov (United States)

    Adepoju, Ibukun-Oluwa Omolade; Albersen, Bregje Joanna Antonia; De Brouwere, Vincent; van Roosmalen, Jos; Zweekhorst, Marjolein

    2017-03-23

    In a bid to deliver quality health services in resource-poor settings, mobile health (mHealth) is increasingly being adopted. The role of mHealth in facilitating evidence-based clinical decision-making through data collection, decision algorithms, and evidence-based guidelines, for example, is established in resource-rich settings. However, the extent to which mobile clinical decision support systems (mCDSS) have been adopted specifically in resource-poor settings such as Africa and the lessons learned about their use in such settings are yet to be established. The aim of this study was to synthesize evidence on the use of mHealth for point-of-care decision support and improved quality of care by health care workers in Africa. A scoping review of 4 peer-reviewed and 1 grey literature databases was conducted. No date limits were applied, but only articles in English language were selected. Using pre-established criteria, 2 reviewers screened articles and extracted data. Articles were analyzed using Microsoft Excel and MAXQDA. We retained 22 articles representing 11 different studies in 7 sub-Saharan African countries. Interventions were mainly in the domain of maternal health and ranged from simple text messaging (short message service, SMS) to complex multicomponent interventions. Although health workers are generally supportive of mCDSS and perceive them as useful, concerns about increased workload and altered workflow hinder sustainability. Facilitators and barriers to use of mCDSS include technical and infrastructural support, ownership, health system challenges, and training. The use of mCDSS in sub-Saharan Africa is an indication of progress in mHealth, although their effect on quality of service delivery is yet to be fully explored. Lessons learned are useful for informing future research, policy, and practice for technologically supported health care delivery, especially in resource-poor settings.

  5. Integration of Hospital Information and Clinical Decision Support Systems to Enable the Reuse of Electronic Health Record Data.

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    Kopanitsa, Georgy

    2017-05-18

    The efficiency and acceptance of clinical decision support systems (CDSS) can increase if they reuse medical data captured during health care delivery. High heterogeneity of the existing legacy data formats has become the main barrier for the reuse of data. Thus, we need to apply data modeling mechanisms that provide standardization, transformation, accumulation and querying medical data to allow its reuse. In this paper, we focus on the interoperability issues of the hospital information systems (HIS) and CDSS data integration. Our study is based on the approach proposed by Marcos et al. where archetypes are used as a standardized mechanism for the interaction of a CDSS with an electronic health record (EHR). We build an integration tool to enable CDSSs collect data from various institutions without a need for modifications in the implementation. The approach implies development of a conceptual level as a set of archetypes representing concepts required by a CDSS. Treatment case data from Regional Clinical Hospital in Tomsk, Russia was extracted, transformed and loaded to the archetype database of a clinical decision support system. Test records' normalization has been performed by defining transformation and aggregation rules between the EHR data and the archetypes. These mapping rules were used to automatically generate openEHR compliant data. After the transformation, archetype data instances were loaded into the CDSS archetype based data storage. The performance times showed acceptable performance for the extraction stage with a mean of 17.428 s per year (3436 case records). The transformation times were also acceptable with 136.954 s per year (0.039 s per one instance). The accuracy evaluation showed the correctness and applicability of the method for the wide range of HISes. These operations were performed without interrupting the HIS workflow to prevent the HISes from disturbing the service provision to the users. The project results have proven that

  6. Development of a Model of Interprofessional Shared Clinical Decision Making in the ICU: A Mixed-Methods Study.

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    DeKeyser Ganz, Freda; Engelberg, Ruth; Torres, Nicole; Curtis, Jared Randall

    2016-04-01

    To develop a model to describe ICU interprofessional shared clinical decision making and the factors associated with its implementation. Ethnographic (observations and interviews) and survey designs. Three ICUs (two in Israel and one in the United States). A convenience sample of nurses and physicians. None. Observations and interviews were analyzed using ethnographic and grounded theory methodologies. Questionnaires included a demographic information sheet and the Jefferson Scale of Attitudes toward Physician-Nurse Collaboration. From observations and interviews, we developed a conceptual model of the process of shared clinical decision making that involves four stepped levels, proceeding from the lowest to the highest levels of collaboration: individual decision, information exchange, deliberation, and shared decision. This process is influenced by individual, dyadic, and system factors. Most decisions were made at the lower two levels. Levels of perceived collaboration were moderate with no statistically significant differences between physicians and nurses or between units. Both qualitative and quantitative data corroborated that physicians and nurses from all units were similarly and moderately satisfied with their level of collaboration and shared decision making. However, most ICU clinical decision making continues to take place independently, where there is some sharing of information but rarely are decisions made collectively. System factors, such as interdisciplinary rounds and unit culture, seem to have a strong impact on this process. This study provides a model for further study and improvement of interprofessional shared decision making.

  7. PredicT-ML: a tool for automating machine learning model building with big clinical data.

    Science.gov (United States)

    Luo, Gang

    2016-01-01

    Predictive modeling is fundamental to transforming large clinical data sets, or "big clinical data," into actionable knowledge for various healthcare applications. Machine learning is a major predictive modeling approach, but two barriers make its use in healthcare challenging. First, a machine learning tool user must choose an algorithm and assign one or more model parameters called hyper-parameters before model training. The algorithm and hyper-parameter values used typically impact model accuracy by over 40 %, but their selection requires many labor-intensive manual iterations that can be difficult even for computer scientists. Second, many clinical attributes are repeatedly recorded over time, requiring temporal aggregation before predictive modeling can be performed. Many labor-intensive manual iterations are required to identify a good pair of aggregation period and operator for each clinical attribute. Both barriers result in time and human resource bottlenecks, and preclude healthcare administrators and researchers from asking a series of what-if questions when probing opportunities to use predictive models to improve outcomes and reduce costs. This paper describes our design of and vision for PredicT-ML (prediction tool using machine learning), a software system that aims to overcome these barriers and automate machine learning model building with big clinical data. The paper presents the detailed design of PredicT-ML. PredicT-ML will open the use of big clinical data to thousands of healthcare administrators and researchers and increase the ability to advance clinical research and improve healthcare.

  8. A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial.

    Science.gov (United States)

    Kannry, Joseph; McCullagh, Lauren; Kushniruk, Andre; Mann, Devin; Edonyabo, Daniel; McGinn, Thomas

    2015-01-01

    The promise of Clinical Decision Support (CDS) has always been to transform patient care and improve patient outcomes through the delivery of timely and appropriate recommendations that are patient specific and, more often than not, are appropriately actionable. However, the users of CDS-providers-are frequently bombarded with inappropriate and inapplicable CDS that often are not informational, not integrated into the workflow, not patient specific, and that may present out of date and irrelevant recommendations. The integrated clinical prediction rule (iCPR) project was a randomized clinical trial (RCT) conducted to determine if a novel form of CDS, i.e., clinical prediction rules (CPRs), could be efficiently integrated into workflow and result in changes in outcomes (e.g., antibiotic ordering) when embedded within a commercial electronic health record (EHR). We use the lessons learned from the iCPR project to illustrate a framework for constructing usable, useful, and effective actionable CDS while employing off-the-shelf functionality in a production system. Innovations that make up the framework combine the following: (1) active and actionable decision support, (2) multiple rounds of usability testing with iterative development for user acceptance, (3) numerous context sensitive triggers, (4) dedicated training and support for users of the CDS tool for user adoption, and (5) support from clinical and administrative leadership. We define "context sensitive triggers" as being workflow events (i.e., context) that result in a CDS intervention. Success of the framework can be measured by CDS adoption (i.e., intervention is being used), acceptance (compliance with recommendations), and clinical outcomes (where appropriate). This framework may have broader implications for the deployment of Health Information Technology (HIT). iCPR was well adopted(57.4% of users) and accepted (42.7% of users). Usability testing identified and fixed many issues before the iCPR RCT

  9. Building Situation Awareness on the Move: Staff Monitoring Behavior in Clinic Corridors.

    Science.gov (United States)

    González-Martínez, Esther; Bangerter, Adrian; Lê Van, Kim

    2017-12-01

    We conducted a workplace research project on staff mobility in a Swiss hospital outpatient clinic that involved extensive fieldwork and video recordings. The article describes monitoring practices and routines that staff engage in as they walk through the corridors and in and out of the clinic's rooms. The staff perform checks on on-going activity, share their observations with colleagues, and take responsive action while engaged in away-oriented walk or in specific roaming, action-seeking, rallying, and patrolling walk. We argue that these behaviors are closely associated with building and sustaining situation awareness (SA) with regard to the status of the clinic's functioning. They contribute to the coordination of a spatially distributed team that rapidly accomplishes consequential and closely interrelated activities in constantly changing circumstances.

  10. A study of diverse clinical decision support rule authoring environments and requirements for integration

    Directory of Open Access Journals (Sweden)

    Zhou Li

    2012-11-01

    Full Text Available Abstract Background Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs, Software Engineers (SEs, and Subject Matter Experts (SMEs to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. Methods The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. Results While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. Conclusions A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR systems, testing, and reporting.

  11. Clinical Decision Support System for Diabetes Based on Ontology Reasoning and TOPSIS Analysis

    Directory of Open Access Journals (Sweden)

    Rung-Ching Chen

    2017-01-01

    Full Text Available Introduction. Although a number of researchers have considered the positive potential of Clinical Decision Support System (CDSS, they did not consider that patients’ attitude which leads to active treatment strategies or HbA1c targets. Materials and Methods. We adopted the American Diabetes Association (ADA and the European Association for the Study of Diabetes (EASD published to propose an HbA1c target and antidiabetic medication recommendation system for patients. Based on the antidiabetic medication profiles, which were presented by the American Association of Clinical Endocrinologists (AACE and American College of Endocrinology (ACE, we use TOPSIS to calculate the ranking of antidiabetic medications. Results. The endocrinologist set up ten virtual patients’ medical data to evaluate a decision support system. The system indicates that the CDSS performs well and is useful to 87%, and the recommendation system is suitable for outpatients. The evaluation results of the antidiabetic medications show that the system has 85% satisfaction degree which can assist clinicians to manage T2DM while selecting antidiabetic medications. Conclusions. In addition to aiding doctors’ clinical diagnosis, the system not only can serve as a guide for specialty physicians but also can help nonspecialty doctors and young doctors with their drug prescriptions.

  12. Measurement of Fibrosis in Crohn's Disease Strictures with Imaging and Blood Biomarkers to Inform Clinical Decisions.

    Science.gov (United States)

    Higgins, Peter D R

    2017-01-01

    Distinguishing fibrosis from inflammation in an intestinal stricture in Crohn's disease is quite difficult. The absence of signs of inflammation on CT or MRI does not prove the absence of inflammation, as most strictures have a mix of fibrosis and inflammation. Identifying refractory fibrosis and distinguishing the patients who will respond to anti-inflammatory therapy from those who will require surgery are important clinical requirements, and several new technologies in imaging and serum biomarkers are being applied to this problem. Key Messages: Delayed gadolinium enhancement of a Crohn's disease stricture on MRI can reliably identify severe fibrosis, and may be helpful in deciding which patients will require surgery. However, this approach does not appear to be able to identify patients with mild or moderate fibrosis. New imaging technologies, including T2/magnetization transfer MRI, shear wave velocity ultrasound, and photoacoustic imaging, offer promising animal data that could prove to accurately assist clinical decision making. Glyoproteomics has identified hepatic growth factor alpha and cartilage oligomeric matrix protein as possible serum biomarkers to detect and measure intestinal fibrosis. The presence of upstream small bowel dilation >3.5 cm or a platelet/albumin ratio >150 helps in identifying Crohn's disease patients at high risk of stricture resection in the next 2 years. Imaging and biomarker technologies to measure intestinal fibrosis are rapidly evolving, and could soon provide valuable information for clinical decision making for patients with intestinal strictures from Crohn's disease. © 2017 S. Karger AG, Basel.

  13. A study of diverse clinical decision support rule authoring environments and requirements for integration.

    Science.gov (United States)

    Zhou, Li; Karipineni, Neelima; Lewis, Janet; Maviglia, Saverio M; Fairbanks, Amanda; Hongsermeier, Tonya; Middleton, Blackford; Rocha, Roberto A

    2012-11-12

    Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs), Software Engineers (SEs), and Subject Matter Experts (SMEs) to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE) in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS) interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR) systems, testing, and reporting.

  14. Development and impact of computerised decision support systems for clinical management of depression: A systematic review.

    Science.gov (United States)

    Triñanes, Yolanda; Atienza, Gerardo; Louro-González, Arturo; de-las-Heras-Liñero, Elena; Alvarez-Ariza, María; Palao, Diego J

    2015-01-01

    One of the proposals for improving clinical practice is to introduce computerised decision support systems (CDSS) and integrate these with electronic medical records. Accordingly, this study sought to systematically review evidence on the effectiveness of CDSS in the management of depression. A search was performed in Medline, EMBASE and PsycInfo, in order to do this. The quality of quantitative studies was assessed using the SIGN method, and qualitative studies using the CASPe checklist. Seven studies were identified (3 randomised clinical trials, 3 non-randomised trials, and one qualitative study). The CDSS assessed incorporated content drawn from guidelines and other evidence-based products. In general, the CDSS had a positive impact on different aspects, such as the screening and diagnosis, treatment, improvement in depressive symptoms and quality of life, and referral of patients. The use of CDSS could thus serve to optimise care of depression in various scenarios by providing recommendations based on the best evidence available and facilitating decision-making in clinical practice. Copyright © 2014 SEP y SEPB. Published by Elsevier España. All rights reserved.

  15. The Research of Clinical Decision Support System Based on Three-Layer Knowledge Base Model

    Directory of Open Access Journals (Sweden)

    Yicheng Jiang

    2017-01-01

    Full Text Available In many clinical decision support systems, a two-layer knowledge base model (disease-symptom of rule reasoning is used. This model often does not express knowledge very well since it simply infers disease from the presence of certain symptoms. In this study, we propose a three-layer knowledge base model (disease-symptom-property to utilize more useful information in inference. The system iteratively calculates the probability of patients who may suffer from diseases based on a multisymptom naive Bayes algorithm, in which the specificity of these disease symptoms is weighted by the estimation of the degree of contribution to diagnose the disease. It significantly reduces the dependencies between attributes to apply the naive Bayes algorithm more properly. Then, the online learning process for parameter optimization of the inference engine was completed. At last, our decision support system utilizing the three-layer model was formally evaluated by two experienced doctors. By comparisons between prediction results and clinical results, our system can provide effective clinical recommendations to doctors. Moreover, we found that the three-layer model can improve the accuracy of predictions compared with the two-layer model. In light of some of the limitations of this study, we also identify and discuss several areas that need continued improvement.

  16. The Utilization of a Clinical Decision Support System to Manage Adult Type 2 Diabetes: A Correlational Study

    Science.gov (United States)

    Faught, I. Charie

    2012-01-01

    While the Institute of Medicine (2001) has promoted health information technology to improve the process of care such as compliance with clinical practice guidelines and quicker access to clinical information, diagnostic tests, and treatment results, very little was known about how a clinical decision support system can contribute to diabetes…

  17. A Critical Review of the Theoretical Frameworks and the Conceptual Factors in the Adoption of Clinical Decision Support Systems.

    Science.gov (United States)

    Khong, Peck Chui Betty; Holroyd, Eleanor; Wang, Wenru

    2015-12-01

    The clinical decision support system is utilized to translate knowledge into evidence-based practice in clinical settings. Many studies have been conducted to understand users' adoption of the clinical decision support system. A critical review was conducted to understand the theoretical or conceptual frameworks used to inform the studies on the adoption of the clinical decision support system. The review identified 15 theoretical and conceptual frameworks using multiple hybrids of theories and concepts. The Technology Acceptance Model was the most frequently used baseline framework combined with frameworks such as the diffusion of innovation, social theory, longitudinal theory, and so on. The results from these articles yielded multiple concepts influencing the adoption of the clinical decision support system. These concepts can be recategorized into nine major concepts, namely, the information system, person (user or patient), social, organization, perceived benefits, emotions, trustability, relevance (fitness), and professionalism. None of the studies found all the nine concepts. That said, most of them have identified the information system, organization, and person concepts as three of its concepts affecting the use of the clinical decision support system. Within each of the concepts, its subconcepts were noted to be very varied. Yet each of these subconcepts has significantly contributed toward the different facets of the concepts. A pluralistic framework was built using the concepts and subconcepts to provide an overall framework construct for future study on the adoption of the clinical decision support system.

  18. A diagnosis-based clinical decision rule for spinal pain part 2: review of the literature

    Directory of Open Access Journals (Sweden)

    Hurwitz Eric L

    2008-08-01

    Full Text Available Abstract Background Spinal pain is a common and often disabling problem. The research on various treatments for spinal pain has, for the most part, suggested that while several interventions have demonstrated mild to moderate short-term benefit, no single treatment has a major impact on either pain or disability. There is great need for more accurate diagnosis in patients with spinal pain. In a previous paper, the theoretical model of a diagnosis-based clinical decision rule was presented. The approach is designed to provide the clinician with a strategy for arriving at a specific working diagnosis from which treatment decisions can be made. It is based on three questions of diagnosis. In the current paper, the literature on the reliability and validity of the assessment procedures that are included in the diagnosis-based clinical decision rule is presented. Methods The databases of Medline, Cinahl, Embase and MANTIS were searched for studies that evaluated the reliability and validity of clinic-based diagnostic procedures for patients with spinal pain that have relevance for questions 2 (which investigates characteristics of the pain source and 3 (which investigates perpetuating factors of the pain experience. In addition, the reference list of identified papers and authors' libraries were searched. Results A total of 1769 articles were retrieved, of which 138 were deemed relevant. Fifty-one studies related to reliability and 76 related to validity. One study evaluated both reliability and validity. Conclusion Regarding some aspects of the DBCDR, there are a number of studies that allow the clinician to have a reasonable degree of confidence in his or her findings. This is particularly true for centralization signs, neurodynamic signs and psychological perpetuating factors. There are other aspects of the DBCDR in which a lesser degree of confidence is warranted, and in which further research is needed.

  19. Emergency nurses' knowledge, attitude and clinical decision making skills about pain.

    Science.gov (United States)

    Ucuzal, Meral; Doğan, Runida

    2015-04-01

    Pain is the most common reason that patients come to the emergency department. Emergency nurses have an indispensable role in the management of this pain. The aim of this study was to examine emergency nurses' knowledge, attitude and clinical decision-making skills about pain. This descriptive study was conducted in a state and a university hospital between September and October 2012 in Malatya, Turkey. Of 98 nurses working in the emergency departments of these two hospitals, 57 returned the questionnaires. The response rate was 58%. Data were collected using the Demographic Information Questionnaire, Knowledge and Attitude Questionnaire about Pain and Clinical Decision Making Survey. Frequency, percentage, mean and standard deviation were used to evaluate data. 75.4% of participant nurses knew that patients' own statement about their pain was the most reliable indicator during pain assessment. Almost half of the nurses believed that patients should be encouraged to endure the pain as much as possible before resorting to a pain relief method. The results also indicate that most of nurses think that a sleeping patient does not have any pain and pain relief should be postponed as it can influence the diagnosis negatively. It is determined that the pain scale was not used frequently. Only 35.1% of nurses reported keeping records of pain. Despite all the recommendations of substantial past research the results of this study indicate that emergency nurses continue to demonstrate inadequate knowledge, clinical decision-making skills and negative attitudes about pain. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. Physicians' Compliance with a Clinical Decision Support System Alerting during the Prescribing Process.

    Science.gov (United States)

    Baypinar, Fatih; Kingma, Hylke Jan; van der Hoeven, Ruud T M; Becker, Matthijs L

    2017-06-01

    Clinical decision support systems have been shown to improve practitioner performance. Most systems designed to prevent medication errors generate lists with patients who fulfill the criteria of the algorithm. These lists are reviewed by a pharmacist and physicians are contacted by telephone. Presenting pop-up alerts as part of the workflow with a clear recommendation is a feature critical to success. Therefore we implemented three algorithms in a clinical decision support system alerting during the medication ordering process. We analyzed whether the recommendations in these alerts were followed. We evaluated 1. whether folic or folinic acid was co-prescribed more frequently within 48 h after ordering methotrexate, 2. whether vitamin D or analogues were co-prescribed more frequently within 48 h after ordering bisphophonates and 3. whether sodium lowering drugs were stopped more frequently within one hour in patients with hyponatremia. We analyzed the difference in the 48 days before implementation and the 43 days after implementation, using Pearson's Chi2 test. Co-prescription of folic or folinic acid increased from 54 to 91% (p = 0.014), co-prescription of vitamin D or analogues increased from 11 to 40% (p = 0.001) and the number of stopped orders for sodium lowering drugs increased from 3 to 14% (p = 0.002). This clinical decision support system that alerts physicians for preventable medication errors during the medication ordering process is an effective approach to improve prescribing behavior.

  1. GLASS Clinical Decision Rule Applied to Thoracolumbar Spinal Fractures in Patients Involved in Motor Vehicle Crashes

    Science.gov (United States)

    Althoff, Seth; Overberger, Ryan; Sochor, Mark; Bose, Dipan; Werner, Joshua

    2017-01-01

    Introduction There are established and validated clinical decision tools for cervical spine clearance. Almost all the rules include spinal tenderness on exam as an indication for imaging. Our goal was to apply GLASS, a previously derived clinical decision tool for cervical spine clearance, to thoracolumbar injuries. GLass intact Assures Safe Spine (GLASS) is a simple, objective method to evaluate those patients involved in motor vehicle collisions and determine which are at low risk for thoracolumbar injuries. Methods We performed a retrospective cohort study using the National Accident Sampling System-Crashworthiness Data System (NASS-CDS) over an 11-year period (1998–2008). Sampled occupant cases selected in this study included patients age 16–60 who were belt-restrained, front- seat occupants involved in a crash with no airbag deployment, and no glass damage prior to the crash. Results We evaluated 14,191 occupants involved in motor vehicle collisions in this analysis. GLASS had a sensitivity of 94.4% (95% CI [86.3–98.4%]), specificity of 54.1% (95% CI [53.2–54.9%]), and negative predictive value of 99.9% (95% CI [99.8–99.9%]) for thoracic injuries, and a sensitivity of 90.3% (95% CI [82.8–95.2%]), specificity of 54.2% (95% CI [53.3–54.9%]), and negative predictive value of 99.9% (95% CI [99.7–99.9%]) for lumbar injuries. Conclusion The GLASS rule represents the possibility of a novel, more-objective thoracolumbar spine clearance tool. Prospective evaluation would be required to further evaluate the validity of this clinical decision rule. PMID:29085544

  2. Recommendations for Selecting Drug-Drug Interactions for Clinical Decision Support

    Science.gov (United States)

    Tilson, Hugh; Hines, Lisa E.; McEvoy, Gerald; Weinstein, David M.; Hansten, Philip D.; Matuszewski, Karl; le Comte, Marianne; Higby-Baker, Stefanie; Hanlon, Joseph T.; Pezzullo, Lynn; Vieson, Kathleen; Helwig, Amy L.; Huang, Shiew-Mei; Perre, Anthony; Bates, David W.; Poikonen, John; Wittie, Michael A.; Grizzle, Amy J.; Brown, Mary; Malone, Daniel C.

    2016-01-01

    Purpose To recommend principles for including drug-drug interactions (DDIs) in clinical decision support. Methods A conference series was conducted to improve clinical decision support (CDS) for DDIs. The Content Workgroup met monthly by webinar from January 2013 to February 2014, with two in-person meetings to reach consensus. The workgroup consisted of 20 experts in pharmacology, drug information, and CDS from academia, government agencies, health information (IT) vendors, and healthcare organizations. Workgroup members addressed four key questions: (1) What process should be used to develop and maintain a standard set of DDIs?; (2) What information should be included in a knowledgebase of standard DDIs?; (3) Can/should a list of contraindicated drug pairs be established?; and (4) How can DDI alerts be more intelligently filtered? Results To develop and maintain a standard set of DDIs for CDS in the United States, we recommend a transparent, systematic, and evidence-driven process with graded recommendations by a consensus panel of experts and oversight by a national organization. We outline key DDI information needed to help guide clinician decision-making. We recommend judicious classification of DDIs as contraindicated, as only a small set of drug combinations are truly contraindicated. Finally, we recommend more research to identify methods to safely reduce repetitive and less relevant alerts. Conclusion A systematic ongoing process is necessary to select DDIs for alerting clinicians. We anticipate that our recommendations can lead to consistent and clinically relevant content for interruptive DDIs, and thus reduce alert fatigue and improve patient safety. PMID:27045070

  3. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: methods of a decision-maker-researcher partnership systematic review.

    Science.gov (United States)

    Haynes, R Brian; Wilczynski, Nancy L

    2010-02-05

    Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this research was to form a partnership of healthcare providers, managers, and researchers to review randomized controlled trials assessing the effects of computerized decision support for six clinical application areas: primary preventive care, therapeutic drug monitoring and dosing, drug prescribing, chronic disease management, diagnostic test ordering and interpretation, and acute care management; and to identify study characteristics that predict benefit. The review was undertaken by the Health Information Research Unit, McMaster University, in partnership with Hamilton Health Sciences, the Hamilton, Niagara, Haldimand, and Brant Local Health Integration Network, and pertinent healthcare service teams. Following agreement on information needs and interests with decision-makers, our earlier systematic review was updated by searching Medline, EMBASE, EBM Review databases, and Inspec, and reviewing reference lists through 6 January 2010. Data extraction items were expanded according to input from decision-makers. Authors of primary studies were contacted to confirm data and to provide additional information. Eligible trials were organized according to clinical area of application. We included randomized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a computerized clinical decision support system compared with patient care without such a system. Data will be summarized using descriptive summary measures, including proportions

  4. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: Methods of a decision-maker-researcher partnership systematic review

    Directory of Open Access Journals (Sweden)

    Wilczynski Nancy L

    2010-02-01

    Full Text Available Abstract Background Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this research was to form a partnership of healthcare providers, managers, and researchers to review randomized controlled trials assessing the effects of computerized decision support for six clinical application areas: primary preventive care, therapeutic drug monitoring and dosing, drug prescribing, chronic disease management, diagnostic test ordering and interpretation, and acute care management; and to identify study characteristics that predict benefit. Methods The review was undertaken by the Health Information Research Unit, McMaster University, in partnership with Hamilton Health Sciences, the Hamilton, Niagara, Haldimand, and Brant Local Health Integration Network, and pertinent healthcare service teams. Following agreement on information needs and interests with decision-makers, our earlier systematic review was updated by searching Medline, EMBASE, EBM Review databases, and Inspec, and reviewing reference lists through 6 January 2010. Data extraction items were expanded according to input from decision-makers. Authors of primary studies were contacted to confirm data and to provide additional information. Eligible trials were organized according to clinical area of application. We included randomized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a computerized clinical decision support system compared with patient care without such a system. Results Data will be summarized

  5. Together, slowly but surely: the role of social interaction and feedback in the build-up of benefit in collective decision-making

    DEFF Research Database (Denmark)

    Bahrami, Bahador; Olsen, Karsten; Bang, Dan

    2011-01-01

    in a significant collective benefit in perceptual decisions. When feedback was not available a collective benefit was not initially obtained but emerged through practice to the extent that in the second half of the experiments, collective benefits obtained with (Experiment 1) and without (Experiment 2) feedback...... were robust and statistically indistinguishable. Taken together, this work demonstrates that social interaction was necessary for build-up of reliable collaborative benefit, whereas objective reference only accelerated the process but-given enough opportunity for practice-was not necessary for building...

  6. 'PICO-D Management'; a decision-aid for evidence-based chiropractic education and clinical practice.

    Science.gov (United States)

    Amorin-Woods, Lyndon G; Losco, Barrett E

    2016-01-01

    Various models and decision-making aids exist for chiropractic clinical practice. "PICO-D Man" (Patient-Intervention-Comparator-Outcome-Duration Management) is a decision-aid developed in an educational setting which field practitioners may also find useful for applying defensible evidence-based practice. Clinical decision-making involves understanding and evaluating both the proposed clinicalintervention(s) and the relevant and available management options with respect to describing the patient and their problem, clinical and cost effectiveness, safety, feasibility and time-frame. For people consulting chiropractors this decision-aid usually requires the practitioner to consider a comparison of usual chiropractic care, (clinical management including a combination of active care and passive manual interventions), to usual medical care usually including medications, or other allied healthmanagement options while being mindful of the natural history of the persons' condition.

  7. Evaluation of the validity of the Psychology Experiment Building Language tests of vigilance, auditory memory, and decision making

    Directory of Open Access Journals (Sweden)

    Brian Piper

    2016-03-01

    Full Text Available Background. The Psychology Experimental Building Language (PEBL test battery (http://pebl.sourceforge.net/ is a popular application for neurobehavioral investigations. This study evaluated the correspondence between the PEBL and the non-PEBL versions of four executive function tests. Methods. In one cohort, young-adults (N = 44 completed both the Conner’s Continuous Performance Test (CCPT and the PEBL CPT (PCPT with the order counter-balanced. In a second cohort, participants (N = 47 completed a non-computerized (Wechsler and a computerized (PEBL Digit Span (WDS or PDS both Forward and Backward. Participants also completed the Psychological Assessment Resources or the PEBL versions of the Iowa Gambling Task (PARIGT or PEBLIGT. Results. The between-test correlations were moderately high (reaction time r = 0.78, omission errors r = 0.65, commission errors r = 0.66 on the CPT. DS Forward was significantly greater than DS Backward on the WDS (p < .0005 and the PDS (p < .0005. The total WDS score was moderately correlated with the PDS (r = 0.56. The PARIGT and the PEBLIGTs showed a very similar pattern for response times across blocks, development of preference for Advantageous over Disadvantageous Decks, and Deck selections. However, the amount of money earned (score–loan was significantly higher in the PEBLIGT during the last Block. Conclusions. These findings are broadly supportive of the criterion validity of the PEBL measures of sustained attention, short-term memory, and decision making. Select differences between workalike versions of the same test highlight how detailed aspects of implementation may have more important consequences for computerized testing than has been previously acknowledged.

  8. Uncertainty Analysis of Coupled Socioeconomic-Cropping Models: Building Confidence in Climate Change Decision-Support Tools for Local Stakeholders

    Science.gov (United States)

    Malard, J. J.; Rojas, M.; Adamowski, J. F.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

    2015-12-01

    While cropping models represent the biophysical aspects of agricultural systems, system dynamics modelling offers the possibility of representing the socioeconomic (including social and cultural) aspects of these systems. The two types of models can then be coupled in order to include the socioeconomic dimensions of climate change adaptation in the predictions of cropping models.We develop a dynamically coupled socioeconomic-biophysical model of agricultural production and its repercussions on food security in two case studies from Guatemala (a market-based, intensive agricultural system and a low-input, subsistence crop-based system). Through the specification of the climate inputs to the cropping model, the impacts of climate change on the entire system can be analysed, and the participatory nature of the system dynamics model-building process, in which stakeholders from NGOs to local governmental extension workers were included, helps ensure local trust in and use of the model.However, the analysis of climate variability's impacts on agroecosystems includes uncertainty, especially in the case of joint physical-socioeconomic modelling, and the explicit representation of this uncertainty in the participatory development of the models is important to ensure appropriate use of the models by the end users. In addition, standard model calibration, validation, and uncertainty interval estimation techniques used for physically-based models are impractical in the case of socioeconomic modelling. We present a methodology for the calibration and uncertainty analysis of coupled biophysical (cropping) and system dynamics (socioeconomic) agricultural models, using survey data and expert input to calibrate and evaluate the uncertainty of the system dynamics as well as of the overall coupled model. This approach offers an important tool for local decision makers to evaluate the potential impacts of climate change and their feedbacks through the associated socioeconomic system.

  9. Mobile Clinical Decision Support System for Acid-base Balance Diagnosis and Treatment Recommendation.

    Science.gov (United States)

    Mandzuka, Mensur; Begic, Edin; Boskovic, Dusanka; Begic, Zijo; Masic, Izet

    2017-06-01

    This paper presents mobile application implementing a decision support system for acid-base disorder diagnosis and treatment recommendation. The application was developed using the official integrated development environment for the Android platform (to maximize availability and minimize investments in specialized hardware) called Android Studio. The application identifies disorder, based on the blood gas analysis, evaluates whether the disorder has been compensated, and based on additional input related to electrolyte imbalance, provides recommendations for treatment. The application is a tool in the hands of the user, which provides assistance during acid-base disorders treatment. The application will assist the physician in clinical practice and is focused on the treatment in intensive care.

  10. Implementing clinical decision support for primary care professionals – the process

    DEFF Research Database (Denmark)

    Kortteisto, Tiina; Komulainen, Jorma; Kunnamo, Ilkka

    2012-01-01

    the implementation. The actual use was measured by means of a questionnaire and statistical data. The implementation process consisted of three successive training rounds and lasted for 18 months. After 12 months the reported actual use of the eCDS functions was diverse. The study indicates that successful......We describe the process of putting into practice a computer-based clinical decision support (eCDS) service integrated in the electronic patient record, and the actual use of eCDS after one year in a primary care organization with 48 health care professionals. Multiple methods were used to support...

  11. Mobile Clinical Decision Support Systems in Our Hands - Great Potential but also a Concern.

    Science.gov (United States)

    Masic, Izet; Begic, Edin

    2016-01-01

    Due to the powerful computer resources as well as the availability of today's mobile devices, a special field of mobile systems for clinical decision support in medicine has been developed. The benefits of these applications (systems) are: availability of necessary hardware (mobile phones, tablets and phablets are widespread, and can be purchased at a relatively affordable price), availability of mobile applications (free or for a "small" amount of money) and also mobile applications are tailored for easy use and save time of clinicians in their daily work. In these systems lies a huge potential, and certainly a great economic benefit, so this issue must be approached multidisciplinary.

  12. Magnetic resonance imaging of the vagina: an overview for radiologists with emphasis on clinical decision making*

    Science.gov (United States)

    Ferreira, Daian Miranda; Bezerra, Régis Otaviano França; Ortega, Cinthia Denise; Blasbalg, Roberto; Viana, Públio César Cavalcante; de Menezes, Marcos Roberto; Rocha, Manoel de Souza

    2015-01-01

    Magnetic resonance imaging is a method with high contrast resolution widely used in the assessment of pelvic gynecological diseases. However, the potential of such method to diagnose vaginal lesions is still underestimated, probably due to the scarce literature approaching the theme, the poor familiarity of radiologists with vaginal diseases, some of them relatively rare, and to the many peculiarities involved in the assessment of the vagina. Thus, the authors illustrate the role of magnetic resonance imaging in the evaluation of vaginal diseases and the main relevant findings to be considered in the clinical decision making process. PMID:26379324

  13. Impact of cardiovascular magnetic resonance on management and clinical decision-making in heart failure patients

    Science.gov (United States)

    2013-01-01

    Background Cardiovascular magnetic resonance (CMR) can provide important diagnostic and prognostic information in patients with heart failure. However, in the current health care environment, use of a new imaging modality like CMR requires evidence for direct additive impact on clinical management. We sought to evaluate the impact of CMR on clinical management and diagnosis in patients with heart failure. Methods We prospectively studied 150 consecutive patients with heart failure and an ejection fraction ≤50% referred for CMR. Definitions for “significant clinical impact” of CMR were pre-defined and collected directly from medical records and/or from patients. Categories of significant clinical impact included: new diagnosis, medication change, hospital admission/discharge, as well as performance or avoidance of invasive procedures (angiography, revascularization, device therapy or biopsy). Results Overall, CMR had a significant clinical impact in 65% of patients. This included an entirely new diagnosis in 30% of cases and a change in management in 52%. CMR results directly led to angiography in 9% and to the performance of percutaneous coronary intervention in 7%. In a multivariable model that included clinical and imaging parameters, presence of late gadolinium enhancement (LGE) was the only independent predictor of “significant clinical impact” (OR 6.72, 95% CI 2.56-17.60, p=0.0001). Conclusions CMR made a significant additive clinical impact on management, decision-making and diagnosis in 65% of heart failure patients. This additive impact was seen despite universal use of prior echocardiography in this patient group. The presence of LGE was the best independent predictor of significant clinical impact following CMR. PMID:24083836

  14. Automatic identification of high impact articles in PubMed to support clinical decision making.

    Science.gov (United States)

    Bian, Jiantao; Morid, Mohammad Amin; Jonnalagadda, Siddhartha; Luo, Gang; Del Fiol, Guilherme

    2017-09-01

    The practice of evidence-based medicine involves integrating the latest best available evidence into patient care decisions. Yet, critical barriers exist for clinicians' retrieval of evidence that is relevant for a particular patient from primary sources such as randomized controlled trials and meta-analyses. To help address those barriers, we investigated machine learning algorithms that find clinical studies with high clinical impact from PubMed®. Our machine learning algorithms use a variety of features including bibliometric features (e.g., citation count), social media attention, journal impact factors, and citation metadata. The algorithms were developed and evaluated with a gold standard composed of 502 high impact clinical studies that are referenced in 11 clinical evidence-based guidelines on the treatment of various diseases. We tested the following hypotheses: (1) our high impact classifier outperforms a state-of-the-art classifier based on citation metadata and citation terms, and PubMed's® relevance sort algorithm; and (2) the performance of our high impact classifier does not decrease significantly after removing proprietary features such as citation count. The mean top 20 precision of our high impact classifier was 34% versus 11% for the state-of-the-art classifier and 4% for PubMed's® relevance sort (p=0.009); and the performance of our high impact classifier did not decrease significantly after removing proprietary features (mean top 20 precision=34% vs. 36%; p=0.085). The high impact classifier, using features such as bibliometrics, social media attention and MEDLINE® metadata, outperformed previous approaches and is a promising alternative to identifying high impact studies for clinical decision support. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. A nonparametric Bayesian method of translating machine learning scores to probabilities in clinical decision support.

    Science.gov (United States)

    Connolly, Brian; Cohen, K Bretonnel; Santel, Daniel; Bayram, Ulya; Pestian, John

    2017-08-07

    Probabilistic assessments of clinical care are essential for quality care. Yet, machine learning, which supports this care process has been limited to categorical results. To maximize its usefulness, it is important to find novel approaches that calibrate the ML output with a likelihood scale. Current state-of-the-art calibration methods are generally accurate and applicable to many ML models, but improved granularity and accuracy of such methods would increase the information available for clinical decision making. This novel non-parametric Bayesian approach is demonstrated on a variety of data sets, including simulated classifier outputs, biomedical data sets from the University of California, Irvine (UCI) Machine Learning Repository, and a clinical data set built to determine suicide risk from the language of emergency department patients. The method is first demonstrated on support-vector machine (SVM) models, which generally produce well-behaved, well understood scores. The method produces calibrations that are comparable to the state-of-the-art Bayesian Binning in Quantiles (BBQ) method when the SVM models are able to effectively separate cases and controls. However, as the SVM models' ability to discriminate classes decreases, our approach yields more granular and dynamic calibrated probabilities comparing to the BBQ method. Improvements in granularity and range are even more dramatic when the discrimination between the classes is artificially degraded by replacing the SVM model with an ad hoc k-means classifier. The method allows both clinicians and patients to have a more nuanced view of the output of an ML model, allowing better decision making. The method is demonstrated on simulated data, various biomedical data sets and a clinical data set, to which diverse ML methods are applied. Trivially extending the method to (non-ML) clinical scores is also discussed.

  16. Crossing the Evidence Chasm: Building Evidence Bridges from Process Changes to Clinical Outcomes

    Science.gov (United States)

    Kendrick, David C.; Bu, Davis; Pan, Eric; Middleton, Blackford

    2007-01-01

    Objective Although demand for information about the effectiveness and efficiency of health care information technology grows, large-scale resource-intensive randomized controlled trials of health care information technology remain impractical. New methods are needed to translate more commonly available clinical process measures into potential impact on clinical outcomes. Design The authors propose a method for building mathematical models based on published evidence that provides an evidence bridge between process changes and resulting clinical outcomes. This method combines tools from systematic review, influence diagramming, and health care simulations. Measurements The authors apply this method to create an evidence bridge between retinopathy screening rates and incidence of blindness in diabetic patients. Results The resulting model uses changes in eye examination rates and other evidence-based population parameters to generate clinical outcomes and costs in a Markov model. Conclusion This method may serve as an alternative to more expensive study designs and provide useful estimates of the impact of health care information technology on clinical outcomes through changes in clinical process measures. PMID:17329720

  17. Studying abroad: Exploring factors influencing nursing students' decisions to apply for clinical placements in international settings.

    Science.gov (United States)

    Kent-Wilkinson, Arlene; Dietrich Leurer, Marie; Luimes, Janet; Ferguson, Linda; Murray, Lee

    2015-08-01

    For over 15 years the College of Nursing at the University of Saskatchewan has facilitated study abroad clinical placements in a number of countries to enhance student learning. Nursing students often find their study abroad experience to be a defining moment in their educational program, and in their personal and professional growth. The main objective of this research was to explore factors influencing nursing students' decisions to study abroad. A descriptive longitudinal design study was conducted using an online survey. The Study Abroad Survey was distributed to all undergraduate and graduate nursing students, in all years of all programs, at all sites of the College of Nursing, University of Saskatchewan in Saskatchewan, Canada. A total of 1058 nursing students registered in the 2013-2014 academic year were surveyed. The data were collected using an online survey administered by Campus Labs™ (2014). Students indicated that their interest in study abroad international experiences was high (84%), with many perceived benefits, but barriers to participation were also high for these students. Financial barriers topped the list (71%), followed by family responsibilities (30%) and job obligations (23%). The research highlights the factors behind student decision making related to international placements, and provides the basis for improvements to the College of Nursing's International Study Abroad Program (ISAP). Previous travel and international service learning, resulting in increased perceived value of a study abroad experience may prove to be the more significant factor influencing decision making, rather than financial barrier. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Data collection and information presentation for optimal decision making by clinical managers--the Autocontrol Project.

    Science.gov (United States)

    Grant, A M; Richard, Y; Deland, E; Després, N; de Lorenzi, F; Dagenais, A; Buteau, M

    1997-01-01

    The Autocontrol methodology has been developed in order to support the optimisation of decision-making and the use of resources in the context of a clinical unit. The theoretical basis relates to quality assurance and information systems and is influenced by management and cognitive research in the health domain. The methodology uses population rather than individual decision making and because of its dynamic feedback design promises to have rapid and profound effect on practice. Most importantly the health care professional is the principle user of the Autocontrol system. In this methodology we distinguish three types of evidence necessary for practice change: practice based or internal evidence, best evidence derived from the literature or external evidence concerning the practice in question, and process based evidence on how to optimise the process of practice change. The software used by the system is of the executive decision support type which facilitates interrogation of large databases. The Autocontrol system is designed to interrogate the data of the patient medical record however the latter often lacks data on concomitant resource use and this must be supplemented. This paper reviews the Autocontrol methodology and gives examples from current studies.

  19. [The effects of case-based learning using video on clinical decision making and learning motivation in undergraduate nursing students].

    Science.gov (United States)

    Yoo, Moon-Sook; Park, Jin-Hee; Lee, Si-Ra

    2010-12-01

    The purpose of this study was to examine the effects of case-base learning (CBL) using video on clinical decision-making and learning motivation. This research was conducted between June 2009 and April 2010 as a nonequivalent control group non-synchronized design. The study population was 44 third year nursing students who enrolled in a college of nursing, A University in Korea. The nursing students were divided into the CBL and the control group. The intervention was the CBL with three cases using video. The controls attended a traditional live lecture on the same topics. With questionnaires objective clinical decision-making, subjective clinical decision-making, and learning motivation were measured before the intervention, and 10 weeks after the intervention. Significant group differences were observed in clinical decision-making and learning motivation. The post-test scores of clinical decision-making in the CBL group were statistically higher than the control group. Learning motivation was also significantly higher in the CBL group than in the control group. These results indicate that CBL using video is effective in enhancing clinical decision-making and motivating students to learn by encouraging self-directed learning and creating more interest and curiosity in learning.

  20. Cancer patient decision making related to clinical trial participation: an integrative review with implications for patients' relational autonomy.

    Science.gov (United States)

    Bell, Jennifer A H; Balneaves, Lynda G

    2015-04-01

    Oncology clinical trials are necessary for the improvement of patient care as they have the ability to confirm the efficacy and safety of novel cancer treatments and in so doing, contribute to a solid evidence base on which practitioners and patients can make informed treatment decisions. However, only 3-5 % of adult cancer patients enroll in clinical trials. Lack of participation compromises the success of clinical trials and squanders an opportunity for improving patient outcomes. This literature review summarizes the factors and contexts that influence cancer patient decision making related to clinical trial participation. An integrative review was undertaken within PubMed, CINAHL, and EMBASE databases for articles written between 1995 and 2012 and archived under relevant keywords. Articles selected were data-based, written in English, and limited to adult cancer patients. In the 51 articles reviewed, three main types of factors were identified that influence cancer patients' decision making about participation in clinical trials: personal, social, and system factors. Subthemes included patients' trust in their physician and the research process, undue influence within the patient-physician relationship, and systemic social inequalities. How these factors interact and influence patients' decision-making process and relational autonomy, however, is insufficiently understood. Future research is needed to further elucidate the sociopolitical barriers and facilitators of clinical trial participation and to enhance ethical practice within clinical trial enrolment. This research will inform targeted education and support interventions to foster patients' relational autonomy in the decision-making process and potentially improve clinical trial participation rates.

  1. Patient factors that influence clinicians' decision making in self-management support: A clinical vignette study.

    Directory of Open Access Journals (Sweden)

    Irene D Bos-Touwen

    Full Text Available Self-management support is an integral part of current chronic care guidelines. The success of self-management interventions varies between individual patients, suggesting a need for tailored self-management support. Understanding the role of patient factors in the current decision making of health professionals can support future tailoring of self-management interventions. The aim of this study is to identify the relative importance of patient factors in health professionals' decision making regarding self-management support.A factorial survey was presented to primary care physicians and nurses. The survey consisted of clinical vignettes (case descriptions, in which 11 patient factors were systematically varied. Each care provider received a set of 12 vignettes. For each vignette, they decided whether they would give this patient self-management support and whether they expected this support to be successful. The associations between respondent decisions and patient factors were explored using ordered logit regression.The survey was completed by 60 general practitioners and 80 nurses. Self-management support was unlikely to be provided in a third of the vignettes. The most important patient factor in the decision to provide self-management support as well as in the expectation that self-management support would be successful was motivation, followed by patient-provider relationship and illness perception. Other factors, such as depression or anxiety, education level, self-efficacy and social support, had a small impact on decisions. Disease, disease severity, knowledge of disease, and age were relatively unimportant factors.This is the first study to explore the relative importance of patient factors in decision making and the expectations regarding the provision of self-management support to chronic disease patients. By far, the most important factor considered was patient's motivation; unmotivated patients were less likely to receive self

  2. Assigning Robust Default Values in Building Performance Simulation Software for Improved Decision-Making in the Initial Stages of Building Design

    Directory of Open Access Journals (Sweden)

    Kyosuke Hiyama

    2015-01-01

    Full Text Available Applying data mining techniques on a database of BIM models could provide valuable insights in key design patterns implicitly present in these BIM models. The architectural designer would then be able to use previous data from existing building projects as default values in building performance simulation software for the early phases of building design. The author has proposed the method to minimize the magnitude of the variation in these default values in subsequent design stages. This approach maintains the accuracy of the simulation results in the initial stages of building design. In this study, a more convincing argument is presented to demonstrate the significance of the new method. The variation in the ideal default values for different building design conditions is assessed first. Next, the influence of each condition on these variations is investigated. The space depth is found to have a large impact on the ideal default value of the window to wall ratio. In addition, the presence or absence of lighting control and natural ventilation has a significant influence on the ideal default value. These effects can be used to identify the types of building conditions that should be considered to determine the ideal default values.

  3. A Mathematical Model for Interpretable Clinical Decision Support with Applications in Gynecology

    Science.gov (United States)

    Van Belle, Vanya M. C. A.; Van Calster, Ben; Timmerman, Dirk; Bourne, Tom; Bottomley, Cecilia; Valentin, Lil; Neven, Patrick; Van Huffel, Sabine; Suykens, Johan A. K.; Boyd, Stephen

    2012-01-01

    Background Over time, methods for the development of clinical decision support (CDS) systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical models. In order to accomplish effective decision support, CDS systems should provide information on how the model arrives at a certain decision. To address the issue of incompatibility between performance, interpretability and applicability of CDS systems, this paper proposes an innovative model structure, automatically leading to interpretable and easily applicable models. The resulting models can be used to guide clinicians when deciding upon the appropriate treatment, estimating patient-specific risks and to improve communication with patients. Methods and Findings We propose the interval coded scoring (ICS) system, which imposes that the effect of each variable on the estimated risk is constant within consecutive intervals. The number and position of the intervals are automatically obtained by solving an optimization problem, which additionally performs variable selection. The resulting model can be visualised by means of appealing scoring tables and color bars. ICS models can be used within software packages, in smartphone applications, or on paper, which is particularly useful for bedside medicine and home-monitoring. The ICS approach is illustrated on two gynecological problems: diagnosis of malignancy of ovarian tumors using a dataset containing 3,511 patients, and prediction of first trimester viability of pregnancies using a dataset of 1,435 women. Comparison of the performance of the ICS approach with a range of prediction models proposed in the literature illustrates the ability of ICS to combine optimal performance with the interpretability of simple scoring systems. Conclusions The ICS approach can improve patient-clinician communication and will provide additional insights in the importance and influence of available variables. Future challenges

  4. A mathematical model for interpretable clinical decision support with applications in gynecology.

    Directory of Open Access Journals (Sweden)

    Vanya M C A Van Belle

    Full Text Available BACKGROUND: Over time, methods for the development of clinical decision support (CDS systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical models. In order to accomplish effective decision support, CDS systems should provide information on how the model arrives at a certain decision. To address the issue of incompatibility between performance, interpretability and applicability of CDS systems, this paper proposes an innovative model structure, automatically leading to interpretable and easily applicable models. The resulting models can be used to guide clinicians when deciding upon the appropriate treatment, estimating patient-specific risks and to improve communication with patients. METHODS AND FINDINGS: We propose the interval coded scoring (ICS system, which imposes that the effect of each variable on the estimated risk is constant within consecutive intervals. The number and position of the intervals are automatically obtained by solving an optimization problem, which additionally performs variable selection. The resulting model can be visualised by means of appealing scoring tables and color bars. ICS models can be used within software packages, in smartphone applications, or on paper, which is particularly useful for bedside medicine and home-monitoring. The ICS approach is illustrated on two gynecological problems: diagnosis of malignancy of ovarian tumors using a dataset containing 3,511 patients, and prediction of first trimester viability of pregnancies using a dataset of 1,435 women. Comparison of the performance of the ICS approach with a range of prediction models proposed in the literature illustrates the ability of ICS to combine optimal performance with the interpretability of simple scoring systems. CONCLUSIONS: The ICS approach can improve patient-clinician communication and will provide additional insights in the importance and influence of available

  5. Identifying best practices for clinical decision support and knowledge management in the field.

    Science.gov (United States)

    Ash, Joan S; Sittig, Dean F; Dykstra, Richard; Wright, Adam; McMullen, Carmit; Richardson, Joshua; Middleton, Blackford

    2010-01-01

    To investigate best practices for implementing and managing clinical decision support (CDS) in community hospitals and ambulatory settings, we carried out a series of ethnographic studies to gather information from nine diverse organizations. Using the Rapid Assessment Process methodology, we conducted surveys, interviews, and observations over a period of two years in eight different geographic regions of the U.S.A. We first utilized a template organizing method for an expedited analysis of the data, followed by a deeper and more time consuming interpretive approach. We identified five major categories of best practices that require careful consideration while carrying out the planning, implementation, and knowledge management processes related to CDS. As more health care organizations implement clinical systems such as computerized provider order entry with CDS, descriptions of lessons learned by CDS pioneers can provide valuable guidance so that CDS can have optimal impact on health care quality.

  6. Enhancing Worker Health Through Clinical Decision Support (CDS): An Introduction to a Compilation.

    Science.gov (United States)

    Filios, Margaret S; Storey, Eileen; Baron, Sherry; Luensman, Genevieve B; Shiffman, Richard N

    2017-11-01

    This article outlines an approach to developing clinical decision support (CDS) for conditions related to work and health. When incorporated in electronic health records, such CDS will assist primary care providers (PCPs) care for working patients. Three groups of Subject Matter Experts (SMEs) identified relevant clinical practice guidelines, best practices, and reviewed published literature concerning work-related asthma, return-to-work, and management of diabetes at work. SMEs developed one recommendation per topic that could be supported by electronic CDS. Reviews with PCPs, staff, and health information system implementers in five primary care settings confirmed that the approach was important and operationally sound. This compendium is intended to stimulate a dialogue between occupational health specialists and PCPs that will enhance the use of work information about patients in the primary care setting.

  7. Extraction Of Adverse Events From Clinical Documents To Support Decision Making Using Semantic Preprocessing.

    Science.gov (United States)

    Gaebel, Jan; Kolter, Till; Arlt, Felix; Denecke, Kerstin

    2015-01-01

    Clinical documentation is usually stored in unstructured format in electronic health records (EHR). Processing the information is inconvenient and time consuming and should be enhanced by computer systems. In this paper, a rule-based method is introduced that identifies adverse events documented in the EHR that occurred during treatment. For this purpose, clinical documents are transformed into a semantic structure from which adverse events are extracted. The method is evaluated in a user study with neurosurgeons. In comparison to a bag of word classification using support vector machines, our approach achieved comparably good results of 65% recall and 78% precision. In conclusion, the rule-based method generates promising results that can support physicians' decision making. Because of the structured format the data can be reused for other purposes as well.

  8. A Clinical Decision Support System for Monitoring Post-Colonoscopy Patient Follow-Up and Scheduling.

    Science.gov (United States)

    Wadia, Roxanne; Shifman, Mark; Levin, Forrest L; Marenco, Luis; Brandt, Cynthia A; Cheung, Kei-Hoi; Taddei, Tamar; Krauthammer, Michael

    2017-01-01

    This paper describes a natural language processing (NLP)-based clinical decision support (CDS) system that is geared towards colon cancer care coordinators as the end users. The system is implemented using a metadata- driven Structured Query Language (SQL) function (discriminant function). For our pilot study, we have developed a training corpus consisting of 2,085 pathology reports from the VA Connecticut Health Care System (VACHS). We categorized reports as "actionable"- requiring close follow up, or "non-actionable"- requiring standard or no follow up. We then used 600 distinct pathology reports from 6 different VA sites as our test corpus. Analysis of our test corpus shows that our NLP approach yields 98.5% accuracy in identifying cases that required close clinical follow up. By integrating this into our cancer care tracking system, our goal is to ensure that patients with worrisome pathology receive appropriate and timely follow-up and care.

  9. Reasoning, evidence, and clinical decision-making: The great debate moves forward.

    Science.gov (United States)

    Loughlin, Michael; Bluhm, Robyn; Buetow, Stephen; Borgerson, Kirstin; Fuller, Jonathan

    2017-10-01

    When the editorial to the first philosophy thematic edition of this journal was published in 2010, critical questioning of underlying assumptions, regarding such crucial issues as clinical decision making, practical reasoning, and the nature of evidence in health care, was still derided by some prominent contributors to the literature on medical practice. Things have changed dramatically. Far from being derided or dismissed as a distraction from practical concerns, the discussion of such fundamental questions, and their implications for matters of practical import, is currently the preoccupation of some of the most influential and insightful contributors to the on-going evidence-based medicine debate. Discussions focus on practical wisdom, evidence, and value and the relationship between rationality and context. In the debate about clinical practice, we are going to have to be more explicit and rigorous in future in developing and defending our views about what is valuable in human life. © 2017 John Wiley & Sons, Ltd.

  10. Usability Testing of a Complex Clinical Decision Support Tool in the Emergency Department: Lessons Learned.

    Science.gov (United States)

    Press, Anne; McCullagh, Lauren; Khan, Sundas; Schachter, Andy; Pardo, Salvatore; McGinn, Thomas

    2015-09-10

    As the electronic health record (EHR) becomes the preferred documentation tool across medical practices, health care organizations are pushing for clinical decision support systems (CDSS) to help bring clinical decision support (CDS) tools to the forefront of patient-physician interactions. A CDSS is integrated into the EHR and allows physicians to easily utilize CDS tools. However, often CDSS are integrated into the EHR without an initial phase of usability testing, resulting in poor adoption rates. Usability testing is important because it evaluates a CDSS by testing it on actual users. This paper outlines the usability phase of a study, which will test the impact of integration of the Wells CDSS for pulmonary embolism (PE) diagnosis into a large urban emergency department, where workflow is often chaotic and high stakes decisions are frequently made. We hypothesize that conducting usability testing prior to integration of the Wells score into an emergency room EHR will result in increased adoption rates by physicians. The objective of the study was to conduct usability testing for the integration of the Wells clinical prediction rule into a tertiary care center's emergency department EHR. We conducted usability testing of a CDS tool in the emergency department EHR. The CDS tool consisted of the Wells rule for PE in the form of a calculator and was triggered off computed tomography (CT) orders or patients' chief complaint. The study was conducted at a tertiary hospital in Queens, New York. There were seven residents that were recruited and participated in two phases of usability testing. The usability testing employed a "think aloud" method and "near-live" clinical simulation, where care providers interacted with standardized patients enacting a clinical scenario. Both phases were audiotaped, video-taped, and had screen-capture software activated for onscreen recordings. Phase I: Data from the "think-aloud" phase of the study showed an overall positive outlook on

  11. Incorporating INTERACT II Clinical Decision Support Tools into Nursing Home Health Information Technology

    Science.gov (United States)

    Handler, Steven M.; Sharkey, Siobhan S.; Hudak, Sandra; Ouslander, Joseph G.

    2012-01-01

    A substantial reduction in hospitalization rates has been associated with the implementation of the Interventions to Reduce Acute Care Transfers (INTERACT) quality improvement intervention using the accompanying paper-based clinical practice tools (INTERACT II). There is significant potential to further increase the impact of INTERACT by integrating INTERACT II tools into nursing home (NH) health information technology (HIT) via standalone or integrated clinical decision support (CDS) systems. This article highlights the process of translating INTERACT II tools from paper to NH HIT. The authors believe that widespread dissemination and integration of INTERACT II CDS tools into various NH HIT products could lead to sustainable improvement in resident and clinician process and outcome measures, including enhanced interclinician communication and a reduction in potentially avoidable hospitalizations. PMID:22267955

  12. Integrating Social Media and Mobile Sensor Data for Clinical Decision Support: Concept and Requirements.

    Science.gov (United States)

    Denecke, Kerstin

    2016-01-01

    Social media are increasingly used by individuals for the purpose of collecting data and reporting on the personal health status, on health issues, symptoms and experiences with treatments. Beyond, fitness trackers are more used by individuals to monitor their fitness and health. The health data that is becoming available due to these developments could provide a valuable source for continuous health monitoring, prevention of unexpected health events and clinical decision making since it gives insights into behavior and life habits. However, an integration of the data is challenging. This paper aims triggering the discussion about this current topic. We present a concept for integrating social media data with mobile sensor data and clinical data using digital patient modelling. Further, we collect requirements and challenges for a possible realization of the concept. Challenges include the data volume, reliability and semantic interoperability.

  13. Paying for treatments? Influences on negotiating clinical need and decision-making for dental implant treatment.

    Science.gov (United States)

    Exley, Catherine E; Rousseau, Nikki S; Steele, Jimmy; Finch, Tracy; Field, James; Donaldson, Cam; Thomason, J Mark; May, Carl R; Ellis, Janice S

    2009-01-12

    The aim of this study is to examine how clinicians and patients negotiate clinical need and treatment decisions within a context of finite resources. Dental implant treatment is an effective treatment for missing teeth, but is only available via the NHS in some specific clinical circumstances. The majority of people who receive this treatment therefore pay privately, often at substantial cost to themselves. People are used to paying towards dental treatment costs. However, dental implant treatment is much more expensive than existing treatments--such as removable dentures. We know very little about how dentists make decisions about whether to offer such treatments, or what patients consider when deciding whether or not to pay for them. Mixed methods will be employed to provide insight and understanding into how clinical need is determined, and what influences people's decision making processes when deciding whether or not to pursue a dental implant treatment. Phase 1 will use a structured scoping questionnaire with all the General dental practitioners (GDPs) in three Primary Care Trust areas (n = 300) to provide base-line data about existing practice in relation to dental implant treatment, and to provide data to develop a systematic sampling procedure for Phase 2. Phases 2 (GDPs) and 3 (patients) use qualitative focused one to one interviews with a sample of these practitioners (up to 30) and their patients (up to 60) to examine their views and experiences of decision making in relation to dental implant treatment. Purposive sampling for phases 2 and 3 will be carried out to ensure participants represent a range of socio-economic circumstances, and choices made. Most dental implant treatment is conducted in primary care. Very little information was available prior to this study about the quantity and type of treatment carried out privately. It became apparent during phase 2 that ISOD treatment was an unusual treatment in primary care. We thus extended our sample

  14. Application of a diagnosis-based clinical decision guide in patients with neck pain

    Science.gov (United States)

    2011-01-01

    Background Neck pain (NP) is a common cause of disability. Accurate and efficacious methods of diagnosis and treatment have been elusive. A diagnosis-based clinical decision guide (DBCDG; previously referred to as a diagnosis-based clinical decision rule) has been proposed which attempts to provide the clinician with a systematic, evidence-based guide in applying the biopsychosocial model of care. The approach is based on three questions of diagnosis. The purpose of this study is to present the prevalence of findings using the DBCDG in consecutive patients with NP. Methods Demographic, diagnostic and baseline outcome measure data were gathered on a cohort of NP patients examined by one of three examiners trained in the application of the DBCDG. Results Data were gathered on 95 patients. Signs of visceral disease or potentially serious illness were found in 1%. Centralization signs were found in 27%, segmental pain provocation signs were found in 69% and radicular signs were found in 19%. Clinically relevant myofascial signs were found in 22%. Dynamic instability was found in 40%, oculomotor dysfunction in 11.6%, fear beliefs in 31.6%, central pain hypersensitivity in 4%, passive coping in 5% and depression in 2%. Conclusion The DBCDG can be applied in a busy private practice environment. Further studies are needed to investigate clinically relevant means to identify central pain hypersensitivity, oculomotor dysfunction, poor coping and depression, correlations and patterns among the diagnostic components of the DBCDG as well as inter-examiner reliability, validity and efficacy of treatment based on the DBCDG. PMID:21871119

  15. Using data mining to explore complex clinical decisions: A study of hospitalization after a suicide attempt.

    Science.gov (United States)

    Baca-García, Enrique; Perez-Rodriguez, M Mercedes; Basurte-Villamor, Ignacio; Saiz-Ruiz, Jeronimo; Leiva-Murillo, José M; de Prado-Cumplido, Mario; Santiago-Mozos, Ricardo; Artés-Rodríguez, Antonio; de Leon, Jose

    2006-07-01

    Medical education is moving toward developing guidelines using the evidence-based approach; however, controlled data are missing for answering complex treatment decisions such as those made during suicide attempts. A new set of statistical techniques called data mining (or machine learning) is being used by different industries to explore complex databases and can be used to explore large clinical databases. The study goal was to reanalyze, using data mining techniques, a published study of which variables predicted psychiatrists' decisions to hospitalize in 509 suicide attempters over the age of 18 years who were assessed in the emergency department. Patients were recruited for the study between 1996 and 1998. Traditional multivariate statistics were compared with data mining techniques to determine variables predicting hospitalization. Five analyses done by psychiatric researchers using traditional statistical techniques classified 72% to 88% of patients correctly. The model developed by researchers with no psychiatric knowledge and employing data mining techniques used 5 variables (drug consumption during the attempt, relief that the attempt was not effective, lack of family support, being a housewife, and family history of suicide attempts) and classified 99% of patients correctly (99% sensitivity and 100% specificity). This reanalysis of a published study fundamentally tries to make the point that these new multivariate techniques, called data mining, can be used to study large clinical databases in psychiatry. Data mining techniques may be used to explore important treatment questions and outcomes in large clinical databases and to help develop guidelines for problems where controlled data are difficult to obtain. New opportunities for good clinical research may be developed by using data mining analyses.

  16. Application of a diagnosis-based clinical decision guide in patients with low back pain

    Directory of Open Access Journals (Sweden)

    Murphy Donald R

    2011-10-01

    Full Text Available Abstract Background Low back pain (LBP is common and costly. Development of accurate and efficacious methods of diagnosis and treatment has been identified as a research priority. A diagnosis-based clinical decision guide (DBCDG; previously referred to as a diagnosis-based clinical decision rule has been proposed which attempts to provide the clinician with a systematic, evidence-based means to apply the biopsychosocial model of care. The approach is based on three questions of diagnosis. The purpose of this study is to present the prevalence of findings using the DBCDG in consecutive patients with LBP. Methods Demographic, diagnostic and baseline outcome measure data were gathered on a cohort of LBP patients examined by one of three examiners trained in the application of the DBCDG. Results Data were gathered on 264 patients. Signs of visceral disease or potentially serious illness were found in 2.7%. Centralization signs were found in 41%, lumbar and sacroiliac segmental signs in 23% and 27%, respectively and radicular signs were found in 24%. Clinically relevant myofascial signs were diagnosed in 10%. Dynamic instability was diagnosed in 63%, fear beliefs in 40%, central pain hypersensitivity in 5%, passive coping in 3% and depression in 3%. Conclusion The DBCDG can be applied in a busy private practice environment. Further studies are needed to investigate clinically relevant means to identify central pain hypersensitivity, poor coping and depression, correlations and patterns among the diagnostic components of the DBCDG as well as inter-examiner reliability and efficacy of treatment based on the DBCDG.

  17. Application of a diagnosis-based clinical decision guide in patients with neck pain

    Directory of Open Access Journals (Sweden)

    Murphy Donald R

    2011-08-01

    Full Text Available Abstract Background Neck pain (NP is a common cause of disability. Accurate and efficacious methods of diagnosis and treatment have been elusive. A diagnosis-based clinical decision guide (DBCDG; previously referred to as a diagnosis-based clinical decision rule has been proposed which attempts to provide the clinician with a systematic, evidence-based guide in applying the biopsychosocial model of care. The approach is based on three questions of diagnosis. The purpose of this study is to present the prevalence of findings using the DBCDG in consecutive patients with NP. Methods Demographic, diagnostic and baseline outcome measure data were gathered on a cohort of NP patients examined by one of three examiners trained in the application of the DBCDG. Results Data were gathered on 95 patients. Signs of visceral disease or potentially serious illness were found in 1%. Centralization signs were found in 27%, segmental pain provocation signs were found in 69% and radicular signs were found in 19%. Clinically relevant myofascial signs were found in 22%. Dynamic instability was found in 40%, oculomotor dysfunction in 11.6%, fear beliefs in 31.6%, central pain hypersensitivity in 4%, passive coping in 5% and depression in 2%. Conclusion The DBCDG can be applied in a busy private practice environment. Further studies are needed to investigate clinically relevant means to identify central pain hypersensitivity, oculomotor dysfunction, poor coping and depression, correlations and patterns among the diagnostic components of the DBCDG as well as inter-examiner reliability, validity and efficacy of treatment based on the DBCDG.

  18. Knowledge discovery in clinical decision support systems for pain management: a systematic review.

    Science.gov (United States)

    Pombo, Nuno; Araújo, Pedro; Viana, Joaquim

    2014-01-01

    The occurrence of pain accounts for billions of dollars in annual medical expenditures; loss of quality of life and decreased worker productivity contribute to indirect costs. As pain is highly subjective, clinical decision support systems (CDSSs) can be critical for improving the accuracy of pain assessment and offering better support for clinical decision-making. This review is focused on computer technologies for pain management that allow CDSSs to obtain knowledge from the clinical data produced by either patients or health care professionals. A comprehensive literature search was conducted in several electronic databases to identify relevant articles focused on computerised systems that constituted CDSSs and include data or results related to pain symptoms from patients with acute or chronic pain, published between 1992 and 2011 in the English language. In total, thirty-nine studies were analysed; thirty-two were selected from 1245 citations, and seven were obtained from reference tracking. The results highlighted the following clusters of computer technologies: rule-based algorithms, artificial neural networks, nonstandard set theory, and statistical learning algorithms. In addition, several methodologies were found for content processing such as terminologies, questionnaires, and scores. The median accuracy ranged from 53% to 87.5%. Computer technologies that have been applied in CDSSs are important but not determinant in improving the systems' accuracy and the clinical practice, as evidenced by the moderate correlation among the studies. However, these systems play an important role in the design of computerised systems oriented to a patient's symptoms as is required for pain management. Several limitations related to CDSSs were observed: the lack of integration with mobile devices, the reduced use of web-based interfaces, and scarce capabilities for data to be inserted by patients. Copyright © 2013 Elsevier B.V. All rights reserved.

  19. Integrative review of clinical decision support for registered nurses in acute care settings.

    Science.gov (United States)

    Dunn Lopez, Karen; Gephart, Sheila M; Raszewski, Rebecca; Sousa, Vanessa; Shehorn, Lauren E; Abraham, Joanna

    2017-03-01

    To report on the state of the science of clinical decision support (CDS) for hospital bedside nurses. We performed an integrative review of qualitative and quantitative peer-reviewed original research studies using a structured search of PubMed, Embase, Cumulative Index to Nursing and Applied Health Literature (CINAHL), Scopus, Web of Science, and IEEE Xplore (Institute of Electrical and Electronics Engineers Xplore Digital Library). We included articles that reported on CDS targeting bedside nurses and excluded in stages based on rules for titles, abstracts, and full articles. We extracted research design and methods, CDS purpose, electronic health record integration, usability, and process and patient outcomes. Our search yielded 3157 articles. After removing duplicates and applying exclusion rules, 28 articles met the inclusion criteria. The majority of studies were single-site, descriptive or qualitative (43%) or quasi-experimental (36%). There was only 1 randomized controlled trial. The purpose of most CDS was to support diagnostic decision-making (36%), guideline adherence (32%), medication management (29%), and situational awareness (25%). All the studies that included process outcomes (7) and usability outcomes (4) and also had analytic procedures to detect changes in outcomes demonstrated statistically significant improvements. Three of 4 studies that included patient outcomes and also had analytic procedures to detect change showed statistically significant improvements. No negative effects of CDS were found on process, usability, or patient outcomes. Clinical support systems targeting bedside nurses have positive effects on outcomes and hold promise for improving care quality; however, this research is lagging behind studies of CDS targeting medical decision-making in both volume and level of evidence.

  20. Clinical decision aids for chest pain in the emergency department: identifying low-risk patients

    Science.gov (United States)

    Alley, William; Mahler, Simon A

    2015-01-01

    Chest pain is one of the most common presenting complaints in the emergency department, though only a small minority of patients are subsequently diagnosed with acute coronary syndrome (ACS). However, missing the diagnosis has potential for significant morbidity and mortality. ACS presentations can be atypical, and their workups are often prolonged and costly. In order to risk-stratify patients and better direct the workup and care given, many decision aids have been developed. While each may have merit in certain clinical settings, the most useful aid in the emergency department is one that finds all cases of ACS while also identifying a substantial subset of patients at low risk who can be discharged without stress testing or coronary angiography. This review describes several of the chest pain decision aids developed and studied through the recent past, starting with the thrombolysis in myocardial infarction (TIMI) risk score and Global Registry of Acute Coronary Events (GRACE) scores, which were developed as prognostic aids for patients already diagnosed with ACS, then subsequently validated in the undifferentiated chest pain population. Asia-Pacific Evaluation of Chest Pain Trial (ASPECT); Accelerated Diagnostic Protocol to Assess Patients With Chest Pain Symptoms Using Contemporary Troponins (ADAPT); North American Chest Pain Rule (NACPR); and History, Electrocardiogram, Age, Risk factors, Troponin (HEART) score have been developed exclusively for use in the undifferentiated chest pain population as well, with improved performance compared to their predecessors. This review describes the relative merits and limitations of these decision aids so that providers can determine which tool fits the needs of their clinical practice setting. PMID:27147894

  1. Knowledge of Fecal Calprotectin and Infliximab Trough Levels Alters Clinical Decision-making for IBD Outpatients on Maintenance Infliximab Therapy

    Science.gov (United States)

    Prosser, Connie; Kroeker, Karen I.; Wang, Haili; Shalapay, Carol; Dhami, Neil; Fedorak, Darryl K.; Halloran, Brendan; Dieleman, Levinus A.; Goodman, Karen J.; Fedorak, Richard N.

    2015-01-01

    Background: Infliximab is an effective therapy for inflammatory bowel disease (IBD). However, more than 50% of patients lose response. Empiric dose intensification is not effective for all patients because not all patients have objective disease activity or subtherapeutic drug level. The aim was to determine how an objective marker of disease activity or therapeutic drug monitoring affects clinical decisions regarding maintenance infliximab therapy in outpatients with IBD. Methods: Consecutive patients with IBD on maintenance infliximab therapy were invited to participate by providing preinfusion stool and blood samples. Fecal calprotectin (FCP) and infliximab trough levels (ITLs) were measured by enzyme linked immunosorbent assay. Three decisions were compared: (1) actual clinical decision, (2) algorithmic FCP or ITL decisions, and (3) expert panel decision based on (a) clinical data, (b) clinical data plus FCP, and (c) clinical data plus FCP plus ITL. In secondary analysis, Receiver-operating curves were used to assess the ability of FCP and ITL in predicting clinical disease activity or remission. Results: A total of 36 sets of blood and stool were available for analysis; median FCP 191.5 μg/g, median ITLs 7.3 μg/mL. The actual clinical decision differed from the hypothetical decision in 47.2% (FCP algorithm); 69.4% (ITL algorithm); 25.0% (expert panel clinical decision); 44.4% (expert panel clinical plus FCP); 58.3% (expert panel clinical plus FCP plus ITL) cases. FCP predicted clinical relapse (area under the curve [AUC] = 0.417; 95% confidence interval [CI], 0.197–0.641) and subtherapeutic ITL (AUC = 0.774; 95% CI, 0.536–1.000). ITL predicted clinical remission (AUC = 0.498; 95% CI, 0.254–0.742) and objective remission (AUC = 0.773; 95% CI, 0.622–0.924). Conclusions: Using FCP and ITLs in addition to clinical data results in an increased number of decisions to optimize management in outpatients with IBD on stable maintenance infliximab therapy. PMID

  2. Anticoagulation manager: development of a clinical decision support mobile application for management of anticoagulants.

    Science.gov (United States)

    Chih-Wen Cheng; Hang Wu; Thompson, Pamela J; Taylor, Julie R; Zehnbauer, Barbara A; Wilson, Karlyn K; Wang, May D

    2016-08-01

    Patients with certain clotting disorders or conditions have a greater risk of developing arterial or venous clots and downstream embolisms, strokes, and arterial insufficiency. These patients need prescription anticoagulant drugs to reduce the possibility of clot formation. However, historically, the clinical decision making workflow in determining the correct type and dosage of anticoagulant(s) is part science and part art. To address this problem, we developed Anticoagulation Manager, an intelligent clinical decision workflow management system on iOS-based mobile devices to help clinicians effectively choose the most appropriate and helpful follow-up clotting tests for patients with a common clotting profile. The app can provide physicians guidance to prescribe the most appropriate medication for patients in need of anticoagulant drugs. This intelligent app was jointly designed and developed by medical professionals in CDC and engineers at Georgia Tech, and will be evaluated by physicians for ease-of-use, robustness, flexibility, and scalability. Eventually, it will be deployed and shared in both physician community and developer community.

  3. Clinical decision making in a patient with secondary hip-spine syndrome.

    Science.gov (United States)

    Burns, Scott A; Mintken, Paul E; Austin, Gary P

    2011-07-01

    The prevalence of lumbar and hip pathology is on the rise; however, treatment outcomes have not improved, highlighting the difficulty in identifying and treating the correct impairments. The purpose of this case report is to describe the clinical decision making in the examination and treatment of an individual with secondary hip-spine syndrome. Our case study was a 62-year-old male with low back pain with concomitant right hip pain. His Oswestry Disability Index (ODI) was 18%, back numeric pain rating scale (NPRS) was 4/10, fear avoidance beliefs questionnaire (FABQ) work subscale was 0, FABQ physical activity subscale was 18, and patient specific functional scale (PSFS) was 7.33. Physical examination revealed findings consistent with secondary hip-spine syndrome. He was treated for four visits with joint mobilization/manipulation and strengthening exercises directed at the hip. At discharge, all standardized outcome measures achieved full resolution. Clinical decision making in the presence of lumbopelvic-hip pain is often difficult. Previous literature has shown that some patients with lumbopelvic-hip pain respond favorably to manual therapy and exercise targeting regions adjacent to the lumbar spine. The findings of this case report suggest that individuals with a primary complaint of LBP with hip impairments may benefit from interventions to reduce hip impairments.

  4. Futility: clinical decisions at the end-of-life in women with ovarian cancer.

    Science.gov (United States)

    von Gruenigen, Vivian E; Daly, Barbara J

    2005-05-01

    The purpose of this article is to provide a review of the clinical meaning of futility, discuss current normative uses of futility assessments and propose guidelines for clinicians to use in dialogue regarding treatment decisions for patients with advanced ovarian cancers. We performed a MEDLINE literature search of relevant clinical articles for this review that discussed futility and the application to women with ovarian cancer. Medical futility refers to treatments that serve no physiologic, quantitative or qualitative meaningful purpose. Despite the growth in options focused on symptom management rather than disease eradication, including hospice programs and the more recent development of palliative care programs, there is evidence that many patients continue to receive aggressive interventions, including chemotherapy, until days before their death. While the legal and moral acceptability of treatment limitation is well established, clarity in establishing goals of care, timing of the transition from cure to palliation and communication of specific decisions to withhold further aggressive interventions remain problematic for both patients and clinicians. There continues to be a distinct need for both better understanding of the dynamics of patient choice and increased education of physicians in addressing end-of-life care planning. It is essential that we continue to test specific communication and supportive interventions that will improve our ability to help patients avoid the burden of futile therapy while maintaining hope.

  5. Derivation of a clinical decision rule for predictive factors for the development of pharyngocutaneous fistula postlaryngectomy

    Directory of Open Access Journals (Sweden)

    Suzana Boltes Cecatto

    2015-08-01

    Full Text Available INTRODUCTION: Pharyngocutaneous fistula after lary