Sample records for clinical decision support

  1. Decision time for clinical decision support systems

    O'Sullivan, D.; Fraccaro, P.; Carson, E; Weller, P


    Clinical decision support systems are interactive software systems designed to assist 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. In this article we provide a brief explanation of clinical decision support systems and provide some examples of real wor...

  2. Clinical Decision Support (CDS) Inventory

    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,...

  3. Grand challenges in clinical decision support.

    Sittig, Dean F; Wright, Adam; Osheroff, Jerome A; Middleton, Blackford; Teich, Jonathan M; Ash, Joan S; Campbell, Emily; Bates, David W


    There is a pressing need for high-quality, effective means of designing, developing, presenting, implementing, evaluating, and maintaining all types of clinical decision support capabilities for clinicians, patients and consumers. Using an iterative, consensus-building process we identified a rank-ordered list of the top 10 grand challenges in clinical decision support. This list was created to educate and inspire researchers, developers, funders, and policy-makers. The list of challenges in order of importance that they be solved if patients and organizations are to begin realizing the fullest benefits possible of these systems consists of: improve the human-computer interface; disseminate best practices in CDS design, development, and implementation; summarize patient-level information; prioritize and filter recommendations to the user; create an architecture for sharing executable CDS modules and services; combine recommendations for patients with co-morbidities; prioritize CDS content development and implementation; create internet-accessible clinical decision support repositories; use freetext information to drive clinical decision support; mine large clinical databases to create new CDS. Identification of solutions to these challenges is critical if clinical decision support is to achieve its potential and improve the quality, safety and efficiency of healthcare. PMID:18029232

  4. Clinical Productivity System - A Decision Support Model

    Bennett, Casey C


    Purpose: This goal of this study was to evaluate the effects of a data-driven clinical productivity system that leverages Electronic Health Record (EHR) data to provide productivity decision support functionality in a real-world clinical setting. The system was implemented for a large behavioral health care provider seeing over 75,000 distinct clients a year. Design/methodology/approach: The key metric in this system is a "VPU", which simultaneously optimizes multiple aspects of clinical care. The resulting mathematical value of clinical productivity was hypothesized to tightly link the organization's performance to its expectations and, through transparency and decision support tools at the clinician level, affect significant changes in productivity, quality, and consistency relative to traditional models of clinical productivity. Findings: In only 3 months, every single variable integrated into the VPU system showed significant improvement, including a 30% rise in revenue, 10% rise in clinical percentage, a...

  5. Information theory models for clinical decision support

    Vajda, Igor

    Praha : Ústav informatiky AV ČR, v.v.i, 2009 - (Z. Valenta). s. 117-117 [Výroční konference Mezinárodní společnosti pro klinickou biostatistiku /30./. 23.08.2009-27.08.2009, Praha] R&D Projects: GA MŠk 1M06014; GA MŠk(CZ) 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : Information * decision error * decision risk * ROC curve * information bounds Subject RIV: BD - Theory of Information theory models for clinical decision support.doc

  6. Clinical decision support system in dental implantology

    Alexandra Polášková; Jitka Feberová; Taťjána Dostálová; Pavel Kříž; Michaela Seydlová


    Implantology is rapidly developing interdisciplinary field providing enormous amounts of data to be classified, evaluated and interpreted. The analysis of clinical data remains a big challenge, because each new system has specific requirements. The aim of study was prepare specific tool for treatment planning. Decision support system is built on Expert system. It is interactive software which provides clinical recommendations and treatment planning. Expert systems are knowledge-based computer...

  7. ClinicalAccess: a clinical decision support tool.

    Crowell, Karen; Vardell, Emily


    ClinicalAccess is a new clinical decision support tool that uses a question-and-answer format to mirror clinical decision-making strategies. The unique format of ClinicalAccess delivers concise, authoritative answers to more than 120,000 clinical questions. This column presents a review of the product, a sample search, and a comparison with other point-of-care search engines. PMID:25927513

  8. Clinical Decision Support Systems: A Useful Tool in Clinical Practice

    Kolostoumpis G.


    Full Text Available The possibility of supporting in decision – making shows an increase in recent years. Based on mathematic simulation tools, knowledge databases, processing methods, medical data and methods, artificial intelligence for coding of the available knowledge and for resolving complex problems arising into clinical practice. Aim: the aim of this review is to present the development of new methods and modern services, in clinical practice and the emergence in their implementation. Data and methods: the methodology that was followed included research of articles that referred to health sector and modern technologies, at the electronic data bases “pubmed” and “medline”. Results: Is a useful tool for medical experts using characteristics and medical data used by the doctors. Constitute innovation for the medical community, and ensure the support of clinical decisions with an overall way by providing a comprehensive solution in the light of the integration of computational decision support systems into clinical practice. Conclusions: Decision Support Systems contribute to improving the quality of health services with simultaneous impoundment of costs (i.e. avoid medical errors

  9. Clinical Decision Support: Statistical Hopes and Challenges

    Kalina, Jan; Zvárová, Jana


    Roč. 4, č. 1 (2016), s. 30-34. ISSN 1805-8698 Grant ostatní: Nadační fond na opdporu vědy(CZ) Neuron Institutional support: RVO:67985807 Keywords : decision support * data mining * multivariate statistics * psychiatry * information based medicine Subject RIV: BB - Applied Statistics, Operational Research

  10. Outpatient diabetes clinical decision support: current status and future directions.

    O'Connor, P J; Sperl-Hillen, J M; Fazio, C J; Averbeck, B M; Rank, B H; Margolis, K L


    Outpatient clinical decision support systems have had an inconsistent impact on key aspects of diabetes care. A principal barrier to success has been low use rates in many settings. Here, we identify key aspects of clinical decision support system design, content and implementation that are related to sustained high use rates and positive impacts on glucose, blood pressure and lipid management. Current diabetes clinical decision support systems may be improved by prioritizing care recommendations, improving communication of treatment-relevant information to patients, using such systems for care coordination and case management and integrating patient-reported information and data from remote devices into clinical decision algorithms and interfaces. PMID:27194173

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

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


    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. PMID:26066306

  12. Grand Challenges in Clinical Decision Support v10

    Sittig, Dean F.; Wright, Adam; Osheroff, Jerome A; Middleton, Blackford; Teich, Jonathan M.; Ash, Joan S.; Campbell, Emily; Bates, David W.


    There is a pressing need for high-quality, effective means of designing, developing, presenting, implementing, evaluating, and maintaining all types of clinical decision support capabilities for clinicians, patients and consumers. Using an iterative, consensus-building process we identified a rank-ordered list of the top 10 grand challenges in clinical decision support. This list was created to educate and inspire researchers, developers, funders, and policy-makers. The list of challenges in ...

  13. Reducing Diagnostic Error with Computer-Based Clinical Decision Support

    Greenes, Robert A.


    Information technology approaches to delivering diagnostic clinical decision support (CDS) are the subject of the papers to follow in the proceedings. These will address the history of CDS and present day approaches (Miller), evaluation of diagnostic CDS methods (Friedman), and the role of clinical documentation in supporting diagnostic decision…

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

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


    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 monitoring. In the treatment of inflammatory bowel disease patients with infliximab, dashboards may reduce therapeutic failures and treatment costs. The history and future development of modern Bayesian dashboard systems is described. PMID:26785109

  15. Improving clinical decision support using data mining techniques

    Burn-Thornton, Kath E.; Thorpe, Simon I.


    Physicians, in their ever-demanding jobs, are looking to decision support systems for aid in clinical diagnosis. However, clinical decision support systems need to be of sufficiently high accuracy that they help, rather than hinder, the physician in his/her diagnosis. Decision support systems with accuracies, of patient state determination, of greater than 80 percent, are generally perceived to be sufficiently accurate to fulfill the role of helping the physician. We have previously shown that data mining techniques have the potential to provide the underpinning technology for clinical decision support systems. In this paper, an extension of the work in reverence 2, we describe how changes in data mining methodologies, for the analysis of 12-lead ECG data, improve the accuracy by which data mining algorithms determine which patients are suffering from heart disease. We show that the accuracy of patient state prediction, for all the algorithms, which we investigated, can be increased by up to 6 percent, using the combination of appropriate test training ratios and 5-fold cross-validation. The use of cross-validation greater than 5-fold, appears to reduce the improvement in algorithm classification accuracy gained by the use of this validation method. The accuracy of 84 percent in patient state predictions, obtained using the algorithm OCI, suggests that this algorithm will be capable of providing the required accuracy for clinical decision support systems.

  16. Fuzzy Logic in Clinical Practice Decision Support Systems

    Warren, Jim; Beliakov, Gleb; Zwaag, van der, B.J.


    Computerized clinical guidelines can provide significant benefits to health outcomes and costs, however, their effective implementation presents significant problems. Vagueness and ambiguity inherent in natural (textual) clinical guidelines is not readily amenable to formulating automated alerts or advice. Fuzzy logic allows us to formalize the treatment of vagueness in a decision support architecture. This paper discusses sources of fuzziness in clinical practice guidelines. We consider how ...

  17. Dynamic clinical data mining: search engine-based decision support.

    Celi, Leo Anthony; Zimolzak, Andrew J; Stone, David J


    The research world is undergoing a transformation into one in which data, on massive levels, is freely shared. In the clinical world, the capture of data on a consistent basis has only recently begun. We propose an operational vision for a digitally based care system that incorporates data-based clinical decision making. The system would aggregate individual patient electronic medical data in the course of care; query a universal, de-identified clinical database using modified search engine technology in real time; identify prior cases of sufficient similarity as to be instructive to the case at hand; and populate the individual patient's electronic medical record with pertinent decision support material such as suggested interventions and prognosis, based on prior outcomes. Every individual's course, including subsequent outcomes, would then further populate the population database to create a feedback loop to benefit the care of future patients. PMID:25600664

  18. A Clinical Decision Support System for Breast Cancer Patients

    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.

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

    Khalifa, Mohamed; Alswailem, Osama


    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. PMID:26152955

  20. Clinical decision support for perioperative information management systems.

    Wanderer, Jonathan P; Ehrenfeld, Jesse M


    Clinical decision support (CDS) systems are being used to optimize the increasingly complex care that our health care system delivers. These systems have become increasingly important in the delivery of perioperative care for patients undergoing cardiac, thoracic, and vascular procedures. The adoption of perioperative information management systems (PIMS) has allowed these technologies to enter the operating room and support the clinical work flow of anesthesiologists and operational processes. Constructing effective CDS systems necessitates an understanding of operative work flow and technical considerations as well as achieving integration with existing information systems. In this review, we describe published examples of CDS for PIMS, including support for cardiopulmonary bypass separation physiological alarms, β-blocker guideline adherence, enhanced revenue capture for arterial line placement, and detection of hemodynamic monitoring gaps. Although these and other areas are amenable to CDS systems, the challenges of latency and data reliability represent fundamental limitations on the potential application of these tools to specific types of clinical issues. Ultimately, we expect that CDS will remain an important tool in our efforts to optimize the quality of care delivered. PMID:23690340

  1. Guideline Formalization and Knowledge Representation for Clinical Decision Support

    Tiago OLIVEIRA


    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.

  2. Details of a Successful Clinical Decision Support System

    Friedlin, Jeff; Dexter, Paul R.; Overhage, J. Marc


    Computerized physician order entry (CPOE) with clinical decision support (CDS) is regarded as one of the most effective ways to improve the quality of health care and increase patient safety. As electronic medical records become more available, such systems will increasingly become the method of choice to achieve these goals. Creating a CPOE/CDS system is a complex task, and some fail despite time consuming and expensive development. The CPOE system at the Regenstrief Institute incorporates sophisticated CDS and is one of the oldest and most successful in the U.S. Many years in development, it is currently used by hundreds of providers. Our well established, successful system can serve as a template or model for the future development of similar systems. We recently completed a full analysis of our CPOE/CDS system and present details of its structure, functionality and contents. PMID:18693837

  3. Dynamic Clinical Data Mining: Search Engine-Based Decision Support

    Celi, Leo Anthony; Zimolzak, Andrew J; Stone, David J


    The research world is undergoing a transformation into one in which data, on massive levels, is freely shared. In the clinical world, the capture of data on a consistent basis has only recently begun. We propose an operational vision for a digitally based care system that incorporates data-based clinical decision making. The system would aggregate individual patient electronic medical data in the course of care; query a universal, de-identified clinical database using modified search engine t...

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

    Kuo, Kuan-Liang; Fuh, Chiou-Shann


    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. PMID:20703626

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

    Kortteisto, Tiina; Komulainen, Jorma; Mäkelä, Marjukka;


    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...... 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. RESULTS: 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...

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

    Wright, Adam; Sittig, Dean F


    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: PMID:18434256

  7. Quantitative ultrasound texture analysis for clinical decision making support

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


    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 (padenomyosis, 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).

  8. Fuzzy Logic in Clinical Practice Decision Support Systems

    Warren, Jim; Beliakov, Gleb; Zwaag, van der Berend


    Computerized clinical guidelines can provide significant benefits to health outcomes and costs, however, their effective implementation presents significant problems. Vagueness and ambiguity inherent in natural (textual) clinical guidelines is not readily amenable to formulating automated alerts or

  9. A proposed clinical decision support architecture capable of supporting whole genome sequence information.

    Welch, Brandon M; Loya, Salvador Rodriguez; Eilbeck, Karen; Kawamoto, Kensaku


    Whole genome sequence (WGS) information may soon be widely available to help clinicians personalize the care and treatment of patients. However, considerable barriers exist, which may hinder the effective utilization of WGS information in a routine clinical care setting. Clinical decision support (CDS) offers a potential solution to overcome such barriers and to facilitate the effective use of WGS information in the clinic. However, genomic information is complex and will require significant considerations when developing CDS capabilities. As such, this manuscript lays out a conceptual framework for a CDS architecture designed to deliver WGS-guided CDS within the clinical workflow. To handle the complexity and breadth of WGS information, the proposed CDS framework leverages service-oriented capabilities and orchestrates the interaction of several independently-managed components. These independently-managed components include the genome variant knowledge base, the genome database, the CDS knowledge base, a CDS controller and the electronic health record (EHR). A key design feature is that genome data can be stored separately from the EHR. This paper describes in detail: (1) each component of the architecture; (2) the interaction of the components; and (3) how the architecture attempts to overcome the challenges associated with WGS information. We believe that service-oriented CDS capabilities will be essential to using WGS information for personalized medicine. PMID:25411644

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

    Wolfenden, Andrew


    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…

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

    Brinner Kristin M


    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

  12. Feasibility of incorporating genomic knowledge into electronic medical records for pharmacogenomic clinical decision support

    Hoath James I


    Full Text Available Abstract In pursuing personalized medicine, pharmacogenomic (PGx knowledge may help guide prescribing drugs based on a person’s genotype. Here we evaluate the feasibility of incorporating PGx knowledge, combined with clinical data, to support clinical decision-making by: 1 analyzing clinically relevant knowledge contained in PGx knowledge resources; 2 evaluating the feasibility of a rule-based framework to support formal representation of clinically relevant knowledge contained in PGx knowledge resources; and, 3 evaluating the ability of an electronic medical record/electronic health record (EMR/EHR to provide computable forms of clinical data needed for PGx clinical decision support. Findings suggest that the PharmGKB is a good source for PGx knowledge to supplement information contained in FDA approved drug labels. Furthermore, we found that with supporting knowledge (e.g. IF age

  13. Visual cluster analysis in support of clinical decision intelligence.

    Gotz, David; Sun, Jimeng; Cao, Nan; Ebadollahi, Shahram


    Electronic health records (EHRs) contain a wealth of information about patients. In addition to providing efficient and accurate records for individual patients, large databases of EHRs contain valuable information about overall patient populations. While statistical insights describing an overall population are beneficial, they are often not specific enough to use as the basis for individualized patient-centric decisions. To address this challenge, we describe an approach based on patient similarity which analyzes an EHR database to extract a cohort of patient records most similar to a specific target patient. Clusters of similar patients are then visualized to allow interactive visual refinement by human experts. Statistics are then extracted from the refined patient clusters and displayed to users. The statistical insights taken from these refined clusters provide personalized guidance for complex decisions. This paper focuses on the cluster refinement stage where an expert user must interactively (a) judge the quality and contents of automatically generated similar patient clusters, and (b) refine the clusters based on his/her expertise. We describe the DICON visualization tool which allows users to interactively view and refine multidimensional similar patient clusters. We also present results from a preliminary evaluation where two medical doctors provided feedback on our approach. PMID:22195102

  14. LERM (Logical Elements Rule Method): A method for assessing and formalizing clinical rules for decision support

    S. Medlock; D. Opondo; S. Eslami; M. Askari; P. Wierenga; S.E. de Rooij; A. Abu-Hanna


    Purpose: The aim of this study was to create a step-by-step method for transforming clinical rules for use in decision support, and to validate this method for usability and reliability. Methods: A sample set of clinical rules was identified from the relevant literature. Using an iterative approach

  15. Clinical application of the UMLS in a computerized order entry and decision-support system.

    Geissbuhler, A.; Miller, R A


    Vanderbilt University Medical Center uses the UMLS as a dictionary, an interlingua, and a knowledge source within the WizOrder system. WizOrder provides direct care-provider order entry and integrated clinical decision-support capabilities. Linking the two functions enables efficient decision-support during the "normal" workflow of care providers, at the point where decisions are made. WizOrder uses the UMLS as a dictionary to encode free-text entries into controlled vocabularies such as ICD9...

  16. On Implementing Clinical Decision Support: Achieving Scalability and Maintainability by Combining Business Rules and Ontologies.

    Kashyap, Vipul; Morales, Alfredo; Hongsermeier, Tonya


    We present an approach and architecture for implementing scalable and maintainable clinical decision support at the Partners HealthCare System. The architecture integrates a business rules engine that executes declarative if-then rules stored in a rule-base referencing objects and methods in a business object model. The rules engine executes object methods by invoking services implemented on the clinical data repository. Specialized inferences that support classification of data and instances...

  17. Measuring the Impact of Diagnostic Decision Support on the Quality of Clinical Decision Making: Development of a Reliable and Valid Composite Score

    Ramnarayan, Padmanabhan; Kapoor, Ritika R; Coren, Michael; Nanduri, Vasantha; Tomlinson, Amanda L.; Taylor, Paul M.; Wyatt, Jeremy C; Britto, Joseph F.


    Objective: Few previous studies evaluating the benefits of diagnostic decision support systems have simultaneously measured changes in diagnostic quality and clinical management prompted by use of the system. This report describes a reliable and valid scoring technique to measure the quality of clinical decision plans in an acute medical setting, where diagnostic decision support tools might prove most useful.

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

    Kunisch, Joseph Martin


    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.…

  19. Long-term follow-up of childhood cancer survivors: clinical decision support and research participation

    Kilsdonk, E.


    The aim of the research in this thesis was twofold. Part 1 aimed to provide insights into how the use of a (paper-based) clinical guideline for follow-up care of childhood cancer survivors could be improved (CCS) by communicating the guideline through a computerized clinical decision support system (CDSS). We first investigated factors that could facilitate a successful CDSS implementation through a systematic literature review. Subsequently, we investigated whether the use of an established ...

  20. A programmable rules engine to provide clinical decision support using HTML forms.

    Heusinkveld, J.; Geissbuhler, A.; Sheshelidze, D.; Miller, R.


    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 te...

  1. Development of Clinical Decision Support Systems based on Mathematical Models of Physiological Systems

    Giannessi, Massimo


    In the last years of research, I focused my studies on different physiological problems. Together with my supervisors, I developed/improved different mathematical models in order to create valid tools useful for a better understanding of important clinical issues. The aim of all this work is to develop tools for learning and understanding cardiac and cerebrovascular physiology as well as pathology, generating research questions and developing clinical decision support systems useful for in...

  2. Incorporating INTERACT II Clinical Decision Support Tools into Nursing Home Health Information Technology

    Handler, Steven M.; Sharkey, Siobhan S.; Hudak, Sandra; Ouslander, Joseph G.


    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...

  3. Development of a Workflow Integration Survey (WIS) for Implementing Computerized Clinical Decision Support

    Flanagan, Mindy; Arbuckle, Nicole; Saleem, Jason J; Militello, Laura G.; Haggstrom, David A.; Doebbeling, Bradley N


    Interventions that focus on improving computerized clinical decision support (CDS) demonstrate that successful workflow integration can increase the adoption and use of CDS. However, metrics for assessing workflow integration in clinical settings are not well established. The goal of this study was to develop and validate a survey to assess the extent to which CDS is integrated into workflow. Qualitative data on CDS design, usability, and integration from four sites was collected by direct ob...

  4. Group Decision Process Support

    Gøtze, John; Hijikata, Masao


    Introducing the notion of Group Decision Process Support Systems (GDPSS) to traditional decision-support theorists.......Introducing the notion of Group Decision Process Support Systems (GDPSS) to traditional decision-support theorists....

  5. Clinical decision support for whole genome sequence information leveraging a service-oriented architecture: a prototype.

    Welch, Brandon M; Rodriguez-Loya, Salvador; Eilbeck, Karen; Kawamoto, Kensaku


    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. PMID:25954430

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

    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.


    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

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

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


    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). PMID:25160142

  8. Fuzzy-Arden-Syntax-based, Vendor-agnostic, Scalable Clinical Decision Support and Monitoring Platform.

    Adlassnig, Klaus-Peter; Fehre, Karsten; Rappelsberger, Andrea


    This study's objective is to develop and use a scalable genuine technology platform for clinical decision support based on Arden Syntax, which was extended by fuzzy set theory and fuzzy logic. Arden Syntax is a widely recognized formal language for representing clinical and scientific knowledge in an executable format, and is maintained by Health Level Seven (HL7) International and approved by the American National Standards Institute (ANSI). Fuzzy set theory and logic permit the representation of knowledge and automated reasoning under linguistic and propositional uncertainty. These forms of uncertainty are a common feature of patients' medical data, the body of medical knowledge, and deductive clinical reasoning. PMID:26262410

  9. Evaluating a Clinical Decision Support Interface for End-of-Life Nurse Care

    Febretti, Alessandro; Stifter, Janet; Keenan, Gail M; Lopez, Karen D; Johnson, Andrew; Wilkie, Diana J


    Clinical Decision Support Systems (CDSS) are tools that assist healthcare personnel in the decision-making process for patient care. Although CDSSs have been successfully deployed in the clinical setting to assist physicians, few CDSS have been targeted at professional nurses, the largest group of health providers. We present our experience in designing and testing a CDSS interface embedded within a nurse care planning and documentation tool. We developed four prototypes based on different CDSS feature designs, and tested them in simulated end-of-life patient handoff sessions with a group of 40 nurse clinicians. We show how our prototypes directed nurses towards an optimal care decision that was rarely performed in unassisted practice. We also discuss the effect of CDSS layout and interface navigation in a nurse’s acceptance of suggested actions. These findings provide insights into effective nursing CDSS design that are generalizable to care scenarios different than end-of-life.

  10. Multi-site evaluation of a clinical decision support system for radiation therapy

    Deshpande, Ruchi; DeMarco, John; Kessel, Kerstin; Liu, Brent J.


    We have developed an imaging informatics based decision support system that learns from retrospective treatment plans to provide recommendations for healthy tissue sparing to prospective incoming patients. This system incorporates a model of best practices from previous cases, specific to tumor anatomy. Ultimately, our hope is to improve clinical workflow efficiency, patient outcomes and to increase clinician confidence in decision-making. The success of such a system depends greatly on the training dataset, which in this case, is the knowledge base that the data-mining algorithm employs. The size and heterogeneity of the database is essential for good performance. Since most institutions employ standard protocols and practices for treatment planning, the diversity of this database can be greatly increased by including data from different institutions. This work presents the results of incorporating cross-country, multi-institutional data into our decision support system for evaluation and testing.

  11. The Morningside Initiative: Collaborative Development of a Knowledge Repository to Accelerate Adoption of Clinical Decision Support

    Greenes, Robert; Bloomrosen, Meryl; Brown-Connolly, Nancy E.; Curtis, Clayton; Detmer, Don E.; Enberg, Robert; Fridsma, Douglas; Fry, Emory; Goldstein, Mary K.; Haug, Peter; Hulse, Nathan; Hongsermeier, Tonya; Maviglia, Saverio; Robbins, Craig W; Shah, Hemant


    The Morningside Initiative is a public-private activity that has evolved from an August, 2007, meeting at the Morningside Inn, in Frederick, MD, sponsored by the Telemedicine and Advanced Technology Research Center (TATRC) of the US Army Medical Research Materiel Command. Participants were subject matter experts in clinical decision support (CDS) and included representatives from the Department of Defense, Veterans Health Administration, Kaiser Permanente, Partners Healthcare System, Henry Fo...

  12. Overview of the second workshop on medical content–based retrieval for clinical decision support

    Depeursinge A.; Greenspan H.; Syeda T.; Muller H.


    The second workshop on Medical Content–Based Retrieval for Clinical Decision Support took place at the MICCAI conference in Toronto, Canada on September 22, 2011. The workshop brought together more than 40 registered researchers interested in the field of medical content–based retrieval. Eleven papers were accepted and presented at the workshop. Two invited speakers gave overviews on state–of–the–art academic research and industrial perspectives. The program was completed with a panel discuss...

  13. Use of Clinical Decision Support to Increase Influenza Vaccination: Multi-year Evolution of the System

    Gerard, Mary N.; Trick, William E.; Das, Krishna; Charles-Damte, Marjorie; Murphy, Gregory A.; Benson, Irene M.


    Despite recognition that clinical decision support (CDS) can improve patient care, there has been poor penetration of this technology into healthcare settings. We used CDS to increase inpatient influenza vaccination during implementation of an electronic medical record, in which pharmacy and nursing transactions increasingly became electronic. Over three influenza seasons we evaluated standing orders, provider reminders, and pre-selected physician orders. A pre-intervention cross-sectional su...

  14. Improving Appropriateness of Acid-Suppressive Medication Use Via Computerized Clinical Decision Support

    Herzig, Shoshana J.; Guess, Jamey R.; Feinbloom, David B.; Adra, May; Afonso, Kevin A.; Howell, Michael D.; Edward R. Marcantonio


    As part of the Choosing Wisely Campaign, the Society of Hospital Medicine identified reducing inappropriate use of acid-suppressive medication for stress ulcer prophylaxis as one of 5 key opportunities to improve the value of care for hospitalized patients. We designed a computerized clinical decision support intervention to reduce use of acid-suppressive medication for stress ulcer prophylaxis in hospitalized patients outside of the intensive care unit at an academic medical center. Using qu...

  15. Can computerized clinical decision support systems improve practitioners' diagnostic test ordering behavior? A decision-maker-researcher partnership systematic review

    Weise-Kelly Lorraine


    Full Text Available Abstract Background Underuse and overuse of diagnostic tests have important implications for health outcomes and costs. Decision support technology purports to optimize the use of diagnostic tests in clinical practice. The objective of this review was to assess whether computerized clinical decision support systems (CCDSSs are effective at improving ordering of tests for diagnosis, monitoring of disease, or monitoring of treatment. The outcome of interest was effect on the diagnostic test-ordering behavior of practitioners. Methods We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for eligible articles published up to January 2010. We included randomized controlled trials comparing the use of CCDSSs to usual practice or non-CCDSS controls in clinical care settings. Trials were eligible if at least one component of the CCDSS gave suggestions for ordering or performing a diagnostic procedure. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of test ordering outcomes. Results Thirty-five studies were identified, with significantly higher methodological quality in those published after the year 2000 (p = 0.002. Thirty-three trials reported evaluable data on diagnostic test ordering, and 55% (18/33 of CCDSSs improved testing behavior overall, including 83% (5/6 for diagnosis, 63% (5/8 for treatment monitoring, 35% (6/17 for disease monitoring, and 100% (3/3 for other purposes. Four of the systems explicitly attempted to reduce test ordering rates and all succeeded. Factors of particular interest to decision makers include costs, user satisfaction, and impact on workflow but were rarely investigated or reported. Conclusions Some CCDSSs can modify practitioner test-ordering behavior. To better inform development and implementation efforts, studies should describe in more detail potentially

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

    Wu Helen W


    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

  17. Physician Attitudes toward Adopting Genome-Guided Prescribing through Clinical Decision Support

    Casey Lynnette Overby


    Full Text Available This study assessed physician attitudes toward adopting genome-guided prescribing through clinical decision support (CDS, prior to enlisting in the Clinical Implementation of Personalized Medicine through Electronic Health Records and Genomics pilot pharmacogenomics project (CLIPMERGE PGx. We developed a survey instrument that includes the Evidence Based Practice Attitude Scale, adapted to measure attitudes toward adopting genome-informed interventions (EBPAS-GII. The survey also includes items to measure physicians’ characteristics (awareness, experience, and perceived usefulness, attitudes about personal genome testing (PGT services, and comfort using technology. We surveyed 101 General Internal Medicine physicians from the Icahn School of Medicine at Mount Sinai (ISMMS. The majority were residency program trainees (~88%. Prior to enlisting into CLIPMERGE PGx, most physicians were aware of and had used decision support aids. Few physicians, however, were aware of and had used genome-guided prescribing. The majority of physicians viewed decision support aids and genotype data as being useful for making prescribing decisions. Most physicians had not heard of, but were willing to use, PGT services and felt comfortable interpreting PGT results. Most physicians were comfortable with technology. Physicians who perceived genotype data to be useful in making prescribing decisions, had more positive attitudes toward adopting genome-guided prescribing through CDS. Our findings suggest that internal medicine physicians have a deficit in their familiarity and comfort interpreting and using genomic information. This has reinforced the importance of gathering feedback and guidance from our enrolled physicians when designing genome-guided CDS and the importance of prioritizing genomic medicine education at our institutions.

  18. EHRs Connect Research and Practice: Where Predictive Modeling, Artificial Intelligence, and Clinical Decision Support Intersect

    Bennett, Casey; Selove, Rebecca


    Objectives: Electronic health records (EHRs) are only a first step in capturing and utilizing health-related data - the challenge is turning that data into useful information. Furthermore, EHRs are increasingly likely to include data relating to patient outcomes, functionality such as clinical decision support, and genetic information as well, and, as such, can be seen as repositories of increasingly valuable information about patients' health conditions and responses to treatment over time. Methods: We describe a case study of 423 patients treated by Centerstone within Tennessee and Indiana in which we utilized electronic health record data to generate predictive algorithms of individual patient treatment response. Multiple models were constructed using predictor variables derived from clinical, financial and geographic data. Results: For the 423 patients, 101 deteriorated, 223 improved and in 99 there was no change in clinical condition. Based on modeling of various clinical indicators at baseline, the high...

  19. A study of diverse clinical decision support rule authoring environments and requirements for integration

    Zhou Li


    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.

  20. Enabling cross-platform clinical decision support through Web-based decision support in commercial electronic health record systems: proposal and evaluation of initial prototype implementations.

    Zhang, Mingyuan; Velasco, Ferdinand T; Musser, R Clayton; Kawamoto, Kensaku


    Enabling clinical decision support (CDS) across multiple electronic health record (EHR) systems has been a desired but largely unattained aim of clinical informatics, especially in commercial EHR systems. A potential opportunity for enabling such scalable CDS is to leverage vendor-supported, Web-based CDS development platforms along with vendor-supported application programming interfaces (APIs). Here, we propose a potential staged approach for enabling such scalable CDS, starting with the use of custom EHR APIs and moving towards standardized EHR APIs to facilitate interoperability. We analyzed three commercial EHR systems for their capabilities to support the proposed approach, and we implemented prototypes in all three systems. Based on these analyses and prototype implementations, we conclude that the approach proposed is feasible, already supported by several major commercial EHR vendors, and potentially capable of enabling cross-platform CDS at scale. PMID:24551426

  1. Cancer Multidisciplinary Team Meetings: Evidence, Challenges, and the Role of Clinical Decision Support Technology

    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

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

    Clark Michael E


    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

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

    Navarro Tamara


    Full Text Available Abstract Background 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. Methods 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. Results 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. Conclusions 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

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

    Gross, Douglas P; Armijo-Olivo, Susan; Shaw, William S; Williams-Whitt, Kelly; Shaw, Nicola T; Hartvigsen, Jan; Qin, Ziling; Ha, Christine; Woodhouse, Linda J; Steenstra, Ivan A


    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) identifying...... the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research...

  5. Clinical decision support, systems methodology, and telemedicine: their role in the management of chronic disease.

    Carson, E R; Cramp, D G; Morgan, A; Roudsari, A V


    In this paper, the design and evaluation of decision support systems, including those incorporating a telematic component, are considered. It is argued that effective design and evaluation are dependent upon the adoption of appropriate methodology set firmly within a systemic framework. Systems modeling is proposed as an approach to system design, with evaluation adopting an approach incorporating evaluability analysis and formative and summative evaluation, including the use of stakeholder matrix analysis. The relevance of such systemic methodology is demonstrated in the context of diabetes and end-stage renal disease as examples of the generic clinical problem of the management of chronic disease. PMID:10719517

  6. Performance of online drug information databases as clinical decision support tools in infectious disease medication management.

    Polen, Hyla H; Zapantis, Antonia; Clauson, Kevin A; Clauson, Kevin Alan; Jebrock, Jennifer; Paris, Mark


    Infectious disease (ID) medication management is complex and clinical decision support tools (CDSTs) can provide valuable assistance. This study evaluated scope and completeness of ID drug information found in online databases by evaluating their ability to answer 147 question/answer pairs. Scope scores produced highest rankings (%) for: Micromedex (82.3), Lexi-Comp/American Hospital Formulary Service (81.0), and Medscape Drug Reference (81.0); lowest includes: Epocrates Online Premium (47.0), Johns Hopkins ABX Guide (45.6), and PEPID PDC (40.8). PMID:18999059

  7. Recurrent Neural Networks in Computer-Based Clinical Decision Support for Laryngopathies: An Experimental Study

    Jan Warchoł; Jarosław Szkoła; Krzysztof Pancerz


    The main goal of this paper is to give the basis for creating a computer-based clinical decision support (CDS) system for laryngopathies. One of approaches which can be used in the proposed CDS is based on the speech signal analysis using recurrent neural networks (RNNs). RNNs can be used for pattern recognition in time series data due to their ability of memorizing some information from the past. The Elman networks (ENs) are a classical representative of RNNs. To improve learning ability of ...

  8. Genetic Stratification in Myeloid Diseases: From Risk Assessment to Clinical Decision Support Tool

    Yishai Ofran


    Full Text Available Genetic aberrations have become a dominant factor in the stratification of myeloid malignancies. Cytogenetic and a few mutation studies are the backbone of risk assessment models of myeloid malignancies which are a major consideration in clinical decisions, especially patient assignment for allogeneic stem cell transplantation. Progress in our understanding of the genetic basis of the pathogenesis of myeloid malignancies and the growing capabilities of mass sequencing may add new roles for the clinical usage of genetic data. A few recently identified mutations recognized to be associated with specific diseases or clinical scenarios may soon become part of the diagnostic criteria of such conditions. Mutational studies may also advance our capabilities for a more efficient patient selection process, assigning the most effective therapy at the best timing for each patient. The clinical utility of genetic data is anticipated to advance further with the adoption of deep sequencing and next-generation sequencing techniques. We herein suggest some future potential applications of sequential genetic data to identify pending deteriorations at time points which are the best for aggressive interventions such as allogeneic stem cell transplantation. Genetics is moving from being mostly a prognostic factor to becoming a multitasking decision support tool for hematologists. Physicians must pay attention to advances in molecular hematology as it will soon be accessible and influential for most of our patients.

  9. A Critical Review of the Theoretical Frameworks and the Conceptual Factors in the Adoption of Clinical Decision Support Systems.

    Khong, Peck Chui Betty; Holroyd, Eleanor; Wang, Wenru


    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. PMID:26535769

  10. [Human body meridian spatial decision support system for clinical treatment and teaching of acupuncture and moxibustion].

    Wu, Dehua


    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. PMID:26946752

  11. Multidisciplinary Modelling of Symptoms and Signs with Archetypes and SNOMED-CT for Clinical Decision Support.

    Marco-Ruiz, Luis; Maldonado, J Alberto; Karlsen, Randi; Bellika, Johan G


    Clinical Decision Support Systems (CDSS) help to improve health care and reduce costs. However, the lack of knowledge management and modelling hampers their maintenance and reuse. Current EHR standards and terminologies can allow the semantic representation of the data and knowledge of CDSS systems boosting their interoperability, reuse and maintenance. This paper presents the modelling process of respiratory conditions' symptoms and signs by a multidisciplinary team of clinicians and information architects with the help of openEHR, SNOMED and clinical information modelling tools for a CDSS. The information model of the CDSS was defined by means of an archetype and the knowledge model was implemented by means of an SNOMED-CT based ontology. PMID:25991115

  12. Recommended practices for computerized clinical decision support and knowledge management in community settings: a qualitative study

    Ash Joan S


    Full Text Available Abstract Background The purpose of this study was to identify recommended practices for computerized clinical decision support (CDS development and implementation and for knowledge management (KM processes in ambulatory clinics and community hospitals using commercial or locally developed systems in the U.S. Methods Guided by the Multiple Perspectives Framework, the authors conducted ethnographic field studies at two community hospitals and five ambulatory clinic organizations across the U.S. Using a Rapid Assessment Process, a multidisciplinary research team: gathered preliminary assessment data; conducted on-site interviews, observations, and field surveys; analyzed data using both template and grounded methods; and developed universal themes. A panel of experts produced recommended practices. Results The team identified ten themes related to CDS and KM. These include: 1 workflow; 2 knowledge management; 3 data as a foundation for CDS; 4 user computer interaction; 5 measurement and metrics; 6 governance; 7 translation for collaboration; 8 the meaning of CDS; 9 roles of special, essential people; and 10 communication, training, and support. Experts developed recommendations about each theme. The original Multiple Perspectives framework was modified to make explicit a new theoretical construct, that of Translational Interaction. Conclusions These ten themes represent areas that need attention if a clinic or community hospital plans to implement and successfully utilize CDS. In addition, they have implications for workforce education, research, and national-level policy development. The Translational Interaction construct could guide future applied informatics research endeavors.

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

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


    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

  14. Service oriented architecture for clinical decision support: a systematic review and future directions.

    Loya, Salvador Rodriguez; Kawamoto, Kensaku; Chatwin, Chris; Huser, Vojtech


    The use of a service-oriented architecture (SOA) has been identified as a promising approach for improving health care by facilitating reliable clinical decision support (CDS). A review of the literature through October 2013 identified 44 articles on this topic. The review suggests that SOA related technologies such as Business Process Model and Notation (BPMN) and Service Component Architecture (SCA) have not been generally adopted to impact health IT systems' performance for better care solutions. Additionally, technologies such as Enterprise Service Bus (ESB) and architectural approaches like Service Choreography have not been generally exploited among researchers and developers. Based on the experience of other industries and our observation of the evolution of SOA, we found that the greater use of these approaches have the potential to significantly impact SOA implementations for CDS. PMID:25325996

  15. Using clinical decision support as a means of implementing a universal postpartum depression screening program.

    Loudon, Holly; Nentin, Farida; Silverman, Michael E


    A major barrier to the diagnosis of postpartum depression (PPD) includes symptom detection. The lack of awareness and understanding of PPD among new mothers, the variability in clinical presentation, and the various diagnostic strategies can increase this further. The purpose of this study was to test the feasibility of adding clinical decision support (CDS) to the electronic health record (EHR) as a means of implementing a universal standardized PPD screening program within a large, at high risk, population. All women returning to the Mount Sinai Hospital OB/GYN Ambulatory Practice for postpartum care between 2010 and 2013 were presented with the Edinburgh Postnatal Depression Scale (EPDS) in response to a CDS "hard stop" built into the EHR. Of the 2102 women who presented for postpartum care, 2092 women (99.5 %) were screened for PPD in response to a CDS hard stop module. Screens were missing on ten records (0.5 %) secondary to refusal, language barrier, or lack of clarity in the EHR. Technology is becoming increasingly important in addressing the challenges faced by health care providers. While the identification of PPD has become the recent focus of public health concerns secondary to the significant social burden, numerous barriers to screening still exist within the clinical setting. The utility of adding CDS in the form of a hard stop, requiring clinicians to enter a standardized PPD mood assessment score to the patient EHR, offers a sufficient way to address a primary barrier to PPD symptom identification at the practitioner level. PMID:26669601

  16. icuARM-An ICU Clinical Decision Support System Using Association Rule Mining

    Chanani, Nikhil; Venugopalan, Janani; Maher, Kevin; Wang, May Dongmei


    The rapid development of biomedical monitoring technologies has enabled modern intensive care units (ICUs) to gather vast amounts of multimodal measurement data about their patients. However, processing large volumes of complex data in real-time has become a big challenge. Together with ICU physicians, we have designed and developed an ICU clinical decision support system icuARM based on associate rule mining (ARM), and a publicly available research database MIMIC-II (Multi-parameter Intelligent Monitoring in Intensive Care II) that contains more than 40,000 ICU records for 30,000+patients. icuARM is constructed with multiple association rules and an easy-to-use graphical user interface (GUI) for care providers to perform real-time data and information mining in the ICU setting. To validate icuARM, we have investigated the associations between patients' conditions such as comorbidities, demographics, and medications and their ICU outcomes such as ICU length of stay. Coagulopathy surfaced as the most dangerous co-morbidity that leads to the highest possibility (54.1%) of prolonged ICU stay. In addition, women who are older than 50 years have the highest possibility (38.8%) of prolonged ICU stay. For clinical conditions treatable with multiple drugs, icuARM suggests that medication choice can be optimized based on patient-specific characteristics. Overall, icuARM can provide valuable insights for ICU physicians to tailor a patient's treatment based on his or her clinical status in real time.

  17. Electronic clinical decision support systems attitudes and barriers to use in the oncology setting.

    Collins, I M


    BACKGROUND: There is little evidence regarding attitudes to clinical decision support systems (CDSS) in oncology. AIMS: We examined the current usage, awareness, and concerns of Irish medical oncologists and oncology pharmacists in this area. METHODS: A questionnaire was sent to 27 medical oncologists and 34 oncology pharmacists, identified through professional interest groups. Respondents ranked concerns regarding their use of a CDSS on a scale from 1 to 4, with 4 being most important. RESULTS: Overall, 67% (41\\/61) responded, 48% (13\\/27) of oncologists and 82% (28\\/34) of pharmacists surveyed. Concerns included "difficulty defining complex clinical situations with a set of rules" (mean ± SD) (3.2 ± 0.9), "ensuring evidence base is up to date and relevant" (3.2 ± 0.9) and "lack of clinically relevant suggestions" (2.9 ± 0.9). Ninety-three percent reported using a CDSS but 54% were unaware of this. CONCLUSION: While there are benefits to using a CDSS, concerns must be addressed through user education. This may be a starting point for a user-centred design approach to the development of future local systems through a consultative process.

  18. The 2013 symposium on pathology data integration and clinical decision support and the current state of field

    Jason M Baron


    Full Text Available Background: Pathologists and informaticians are becoming increasingly interested in electronic clinical decision support for pathology, laboratory medicine and clinical diagnosis. Improved decision support may optimize laboratory test selection, improve test result interpretation and permit the extraction of enhanced diagnostic information from existing laboratory data. Nonetheless, the field of pathology decision support is still developing. To facilitate the exchange of ideas and preliminary studies, we convened a symposium entitled: Pathology data integration and clinical decision support. Methods: The symposium was held at the Massachusetts General Hospital, on May 10, 2013. Participants were selected to represent diverse backgrounds and interests and were from nine different institutions in eight different states. Results: The day included 16 plenary talks and three panel discussions, together covering four broad areas. Summaries of each presentation are included in this manuscript. Conclusions: A number of recurrent themes emerged from the symposium. Among the most pervasive was the dichotomy between diagnostic data and diagnostic information, including the opportunities that laboratories may have to use electronic systems and algorithms to convert the data they generate into more useful information. Differences between human talents and computer abilities were described; well-designed symbioses between humans and computers may ultimately optimize diagnosis. Another key theme related to the unique needs and challenges in providing decision support for genomics and other emerging diagnostic modalities. Finally, many talks relayed how the barriers to bringing decision support toward reality are primarily personnel, political, infrastructural and administrative challenges rather than technological limitations.

  19. Formative Evaluation of Clinician Experience with Integrating Family History-Based Clinical Decision Support into Clinical Practice

    Megan Doerr


    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.

  20. Clinical information system services and capabilities desired for scalable, standards-based, service-oriented decision support: consensus assessment of the Health Level 7 clinical decision support Work Group.

    Kawamoto, Kensaku; Jacobs, Jason; Welch, Brandon M; Huser, Vojtech; Paterno, Marilyn D; Del Fiol, Guilherme; Shields, David; Strasberg, Howard R; Haug, Peter J; Liu, Zhijing; Jenders, Robert A; Rowed, David W; Chertcoff, Daryl; Fehre, Karsten; Adlassnig, Klaus-Peter; Curtis, A Clayton


    A standards-based, service-oriented architecture for clinical decision support (CDS) has the potential to significantly enhance CDS scalability and robustness. To enable such a CDS architecture, the Health Level 7 CDS Work Group reviewed the literature, hosted multi-stakeholder discussions, and consulted domain experts to identify and prioritize the services and capabilities required from clinical information systems (CISs) to enable service-oriented CDS. In addition, relevant available standards were identified. Through this process, ten CIS services and eight CIS capabilities were identified as being important for enabling scalable, service-oriented CDS. In particular, through a survey of 46 domain experts, five services and capabilities were identified as being especially critical: 1) the use of standard information models and terminologies; 2) the ability to leverage a Decision Support Service (DSS); 3) support for a clinical data query service; 4) support for an event subscription and notification service; and 5) support for a user communication service. PMID:23304315

  1. Clinical Decision Support for the Classification of Diabetic Retinopathy: A Comparison of Manual and Automated Results.

    Mitsch, Christoph; Fehre, Karsten; Prager, Sonja; Scholda, Christoph; Kriechbaum, Katharina; Wrba, Thomas; Schmidt-Erfurth, Ursula


    The management of diabetic retinopathy, a frequent ophthalmological manifestation of diabetes mellitus, consists of regular examinations and a standardized, manual classification of disease severity, which is used to recommend re-examination intervals. To evaluate the feasibility and safety of implementing automated, guideline-based diabetic retinopathy (DR) grading into clinical routine by applying established clinical decision support (CDS) technology. We compared manual with automated classification that was generated using medical documentation and an Arden server with a specific medical logic module. Of 7169 included eyes, 47% (n=3373) showed inter-method classification agreement, specifically 29.4% in mild DR, 38.3% in moderate DR, 27.6% in severe DR, and 65.7% in proliferative DR. We demonstrate that the implementation of a CDS system for automated disease severity classification in diabetic retinopathy is feasible but also that, due to the highly individual nature of medical documentation, certain important criteria for the used electronic health record system need to be met in order to achieve reliable results. PMID:27139380

  2. Clinical decision modeling system

    Lyons-Weiler James


    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

  3. Clinical Decision Support Tools for Selecting Interventions for Patients with Disabling Musculoskeletal Disorders: A Scoping Review.

    Gross, Douglas P; Armijo-Olivo, Susan; Shaw, William S; Williams-Whitt, Kelly; Shaw, Nicola T; Hartvigsen, Jan; Qin, Ziling; Ha, Christine; Woodhouse, Linda J; Steenstra, Ivan A


    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) identifying the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses multiple disciplines, we searched health care, computing science and business databases. Results Our search resulted in 4605 manuscripts. Titles and abstracts were screened for relevance. The reliability of the screening process was high with an average percentage of agreement of 92.3 %. Of the located articles, 123 were considered relevant. Within this literature, there were 43 CDS tools located. These were classified into 3 main areas: computer-based tools/questionnaires (n = 8, 19 %), treatment algorithms/models (n = 14, 33 %), and clinical prediction rules/classification systems (n = 21, 49 %). Each of these areas and the associated evidence are described. The state of evidentiary support for CDS tools is still preliminary and lacks external validation, head-to-head comparisons, or evidence of generalizability across different populations and settings. Conclusions CDS tools, especially those employing rapidly advancing computer technologies, are under development and of potential interest to health care providers, case management organizations and funders of care. Based on the results of this scoping review, we conclude that these tools, models and systems should be subjected to further validation before they can be recommended for large-scale implementation for managing patients with MSK disorders. PMID:26667939

  4. The integrated decision support system

    This paper has introduced development history, present situation, popular decision support technology of decision support system, and discussed the integrated decision support system form with technical foundation. (authors)

  5. Privacy-Preserving Patient-Centric Clinical Decision Support System on Naïve Bayesian Classification.

    Liu, Ximeng; Lu, Rongxing; Ma, Jianfeng; Chen, Le; Qin, Baodong


    Clinical decision support system, which uses advanced data mining techniques to help clinician make proper decisions, has received considerable attention recently. The advantages of clinical decision support system include not only improving diagnosis accuracy but also reducing diagnosis time. Specifically, with large amounts of clinical data generated everyday, naïve Bayesian classification can be utilized to excavate valuable information to improve a clinical decision support system. Although the clinical decision support system is quite promising, the flourish of the system still faces many challenges including information security and privacy concerns. In this paper, we propose a new privacy-preserving patient-centric clinical decision support system, which helps clinician complementary to diagnose the risk of patients' disease in a privacy-preserving way. In the proposed system, the past patients' historical data are stored in cloud and can be used to train the naïve Bayesian classifier without leaking any individual patient medical data, and then the trained classifier can be applied to compute the disease risk for new coming patients and also allow these patients to retrieve the top- k disease names according to their own preferences. Specifically, to protect the privacy of past patients' historical data, a new cryptographic tool called additive homomorphic proxy aggregation scheme is designed. Moreover, to leverage the leakage of naïve Bayesian classifier, we introduce a privacy-preserving top- k disease names retrieval protocol in our system. Detailed privacy analysis ensures that patient's information is private and will not be leaked out during the disease diagnosis phase. In addition, performance evaluation via extensive simulations also demonstrates that our system can efficiently calculate patient's disease risk with high accuracy in a privacy-preserving way. PMID:26960216

  6. Computerized clinical decision support systems for therapeutic drug monitoring and dosing: A decision-maker-researcher partnership systematic review

    Weise-Kelly Lorraine


    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

  7. Design and implementation of a decision support system for breast cancer treatment based on clinical practice guidelines

    Evidence based medicine is the clinical practice that uses medical data and proof in order to make efficient clinical decisions. Information technology (IT) can play a crucial role in exploiting the huge size of raw medical data involved. In an attempt to improve clinical efficacy, health care society nowadays also utilizes a new assistant, clinical guidelines. Our research concerns the medical domain of the breast cancer disease. Our research's focus is twofold; our primary goal is to ensure consistency in clinical practice by importing clinical guidelines in an IT driven decision support system (DSS). Furthermore, we seek to improve visualization of disease specific, clinical data, providing for it's faster and more efficient use. (orig.)

  8. Decision support basics

    Power, Daniel J


    This book is targeted to busy managers and MBA students who need to grasp the basics of computerized decision support. Some of the topics covered include: What is a DSS? What do managers need to know about computerized decision support? And how can managers identify opportunities to create innovative DSS? Overall the book addresses 35 fundamental questions that are relevant to understanding computerized decision support.

  9. A decision-support system for the analysis of clinical practice patterns.

    Balas, E A; Li, Z. R.; Mitchell, J. A.; Spencer, D. C.; Brent, E; Ewigman, B G


    Several studies documented substantial variation in medical practice patterns, but physicians often do not have adequate information on the cumulative clinical and financial effects of their decisions. The purpose of developing an expert system for the analysis of clinical practice patterns was to assist providers in analyzing and improving the process and outcome of patient care. The developed QFES (Quality Feedback Expert System) helps users in the definition and evaluation of measurable qu...

  10. Four Principles for User Interface Design of Computerised Clinical Decision Support Systems

    Kanstrup, Anne Marie; Christiansen, Marion Berg; Nøhr, Christian


    Abstract.  The paper presents results from design of a user interface for a Computerised Clinical Decision Support System (CSSS). The ambition has been to design Human-Computer Interaction that can minimise medication errors. Through an iterative design process a digital prototype for prescriptio...... four interaction principles are integrated in the design of user interfaces for CDSS, i.e. the model is an integrated model which we suggest as a guide for interaction design when working with preventing medication errors....... of medicine has been developed. This paper presents results from the formative evaluation of the prototype conducted in a simulation laboratory with ten participating physicians. Data from the simulation is analysed by use of theory on how users perceive information. The conclusion is a model, which...... emphasises a focus on how users interact with the system, a focus on how information is provided by the system, and four principles of interaction. The four principles for design of user interfaces for CDSS are summarised as four A’s: All in one, At a glance, At hand and Attention. It is recommended that all...

  11. A fuzzy logic decision support system for assessing clinical nutritional risk

    Ali Mohammad Hadianfard


    Full Text Available Introduction: Studies have indicated a global high prevalence of hospital malnutrition on admission and during hospitalization. Clinical Nutritional Risk Screen (CNRS is a way to identify malnutrition and manage nutritional interventions. Several traditional and non-computer based tools have been suggested for screening nutritional risk levels. The present study was an attempt to employ a computer based fuzzy model decision support system as a nutrition-screening tool for inpatients. Method: This is an applied modeling study. The system architecture was designed based on the fuzzy logic model including input data, inference engine, and output. A clinical nutritionist entered nineteen input variables using a windows-based graphical user interface. The inference engine was involved with knowledge obtained from literature and the construction of ‘IF-THEN’ rules. The output of the system was stratification of patients into four risk levels from ‘No’ to ‘High’ where a number was also allocated to them as a nutritional risk grade. All patients (121 people admitted during implementing the system participated in testing the model. The classification tests were used to measure the CNRS fuzzy model performance. IBM SPSS version 21 was utilized as a tool for data analysis with α = 0.05 as a significance level. Results: Results showed that sensitivity, specificity, accuracy, and precision of the fuzzy model performance were 91.67% (±4.92, 76% (±7.6, 88.43% (±5.7, and 93.62% (±4.32, respectively. Instant performance on admission and very low probability of mistake in predicting malnutrition risk level may justify using the model in hospitals. Conclusion: To conclude, the fuzzy model-screening tool is based on multiple nutritional risk factors, having the capability of classifying inpatients into several nutritional risk levels and identifying the level of required nutritional intervention.

  12. An HL7-CDA wrapper for facilitating semantic interoperability to rule-based Clinical Decision Support Systems

    Sáez Silvestre, Carlos; BRESÓ GUARDADO, ADRIÁN; Vicente Robledo, Javier; Robles Viejo, Montserrat; García Gómez, Juan Miguel


    The success of Clinical Decision Support Systems (CDSS) greatly depends on its capability of being integrated in Health Information Systems (HIS). Several proposals have been published up to date to permit CDSS gathering patient data from HIS. Some base the CDSS data input on the HL7 reference model, however, they are tailored to specific CDSS or clinical guidelines technologies, or do not focus on standardizing the CDSS resultant knowledge. We propose a solution for facilitating semantic int...

  13. Construction of a Clinical Decision Support System for Undergoing Surgery Based on Domain Ontology and Rules Reasoning

    Bau, Cho-Tsan; Chen, Rung-Ching; Huang, Chung-Yi


    Objective: To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. Materials and Methods: The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé–Web Ontology Language editor was used to implement the ontology. Embedded clinical knowle...

  14. A UMLS-based knowledge acquisition tool for rule-based clinical decision support system development.

    Achour, Soumeya,; Dojat, Michel; Rieux, Claire; Bierling, Philippe; Lepage, Eric


    International audience Decision support systems in the medical field have to be easily modified by medical experts themselves. The authors have designed a knowledge acquisition tool to facilitate the creation and maintenance of a knowledge base by the domain expert and its sharing and reuse by other institutions. The Unified Medical Language System (UMLS) contains the domain entities and constitutes the relations repository from which the expert builds, through a specific browser, the expl...

  15. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: Methods of a decision-maker-researcher partnership systematic review

    Wilczynski Nancy L


    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

  16. Depression and Anxiety During Pregnancy: Evaluating the Literature in Support of Clinical Risk-Benefit Decision-Making.

    Dalke, Katharine Baratz; Wenzel, Amy; Kim, Deborah R


    Depression and anxiety during pregnancy are common, and patients and providers are faced with complex decisions regarding various treatment modalities. A structured discussion of the risks and benefits of options with the patient and her support team is recommended to facilitate the decision-making process. This clinically focused review, with emphasis on the last 3 years of published study data, evaluates the major risk categories of medication treatments, namely pregnancy loss, physical malformations, growth impairment, behavioral teratogenicity, and neonatal toxicity. Nonpharmacological treatment options, including neuromodulation and psychotherapy, are also briefly reviewed. Specific recommendations, drawn from the literature and the authors' clinical experience, are also offered to help guide the clinician in decision-making. PMID:27091646

  17. Using a service oriented architecture approach to clinical decision support: performance results from two CDS Consortium demonstrations.

    Paterno, Marilyn D; Goldberg, Howard S; Simonaitis, Linas; Dixon, Brian E; Wright, Adam; Rocha, Beatriz H; Ramelson, Harley Z; Middleton, Blackford


    The Clinical Decision Support Consortium has completed two demonstration trials involving a web service for the execution of clinical decision support (CDS) rules in one or more electronic health record (EHR) systems. The initial trial ran in a local EHR at Partners HealthCare. A second EHR site, associated with Wishard Memorial Hospital, Indianapolis, IN, was added in the second trial. Data were gathered during each 6 month period and analyzed to assess performance, reliability, and response time in the form of means and standard deviations for all technical components of the service, including assembling and preparation of input data. The mean service call time for each period was just over 2 seconds. In this paper we report on the findings and analysis to date while describing the areas for further analysis and optimization as we continue to expand our use of a Services Oriented Architecture approach for CDS across multiple institutions. PMID:23304342

  18. Evaluating a Web-Based Clinical Decision Support System for Language Disorders Screening in a Nursery School

    Martín Ruiz, María Luisa; Valero Duboy, Miguel Angel; Torcal Loriente, Carmen; Pau de la Cruz, Iván


    Background: Early and effective identification of developmental disorders during childhood remains a critical task for the international community. The second highest prevalence of common developmental disorders in children are language delays, which are frequently the first symptoms of a possible disorder. Objective: This paper evaluates a Web-based Clinical Decision Support System (CDSS) whose aim is to enhance the screening of language disorders at a nursery school. The common lack of earl...

  19. Randomised controlled trial of clinical decision support tools to improve learning of evidence based medicine in medical students

    Leung, Gabriel M; Johnston, Janice M; Tin, Keith Y K; Wong, Irene O. L.; Ho, Lai-Ming; Lam, Wendy W.T.; Lam, Tai-hing


    Objective: To assess the educational effectiveness on learning evidence based medicine of a handheld computer clinical decision support tool compared with a pocket card containing guidelines and a control. Design: Randomised controlled trial. Setting University of Hong Kong, 2001. Participants: 169 fourth year medical students. Main outcome measures: Factor and individual item scores from a validated questionnaire on five key self reported measures: personal application and current use of evi...

  20. Documentation-based clinical decision support to improve antibiotic prescribing for acute respiratory infections in primary care: a cluster randomised controlled trial

    Jeffrey Linder; Jeffrey Schnipper; Ruslana Tsurikova; Tony Yu; Lynn Volk; Andrea Melnikas; Matvey Palchuk; Maya Olsha-Yehiav; Blackford Middleton


    Background and objective Clinical guidelines discourage antibiotic prescribing for many acute respiratory infections (ARIs), especially for non-antibiotic appropriate diagnoses. Electronic health record (EHR)-based clinical decision support has the potential to improve antibiotic prescribing for ARIs. Methods We randomly assigned 27 primary care clinics to receive an EHR-integrated, documentation based clinical decision support system for the care of patients with ARIs - the ARI Smart Form...

  1. Support and Assessment for Fall Emergency Referrals (SAFER 1: cluster randomised trial of computerised clinical decision support for paramedics.

    Helen Anne Snooks

    Full Text Available To evaluate effectiveness, safety and cost-effectiveness of Computerised Clinical Decision Support (CCDS for paramedics attending older people who fall.Cluster trial randomised by paramedic; modelling.13 ambulance stations in two UK emergency ambulance services.42 of 409 eligible paramedics, who attended 779 older patients for a reported fall.Intervention paramedics received CCDS on Tablet computers to guide patient care. Control paramedics provided care as usual. One service had already installed electronic data capture.Effectiveness: patients referred to falls service, patient reported quality of life and satisfaction, processes of care.Further emergency contacts or death within one month.Costs and quality of life. We used findings from published Community Falls Prevention Trial to model cost-effectiveness.17 intervention paramedics used CCDS for 54 (12.4% of 436 participants. They referred 42 (9.6% to falls services, compared with 17 (5.0% of 343 participants seen by 19 control paramedics [Odds ratio (OR 2.04, 95% CI 1.12 to 3.72]. No adverse events were related to the intervention. Non-significant differences between groups included: subsequent emergency contacts (34.6% versus 29.1%; OR 1.27, 95% CI 0.93 to 1.72; quality of life (mean SF12 differences: MCS -0.74, 95% CI -2.83 to +1.28; PCS -0.13, 95% CI -1.65 to +1.39 and non-conveyance (42.0% versus 36.7%; OR 1.13, 95% CI 0.84 to 1.52. However ambulance job cycle time was 8.9 minutes longer for intervention patients (95% CI 2.3 to 15.3. Average net cost of implementing CCDS was £208 per patient with existing electronic data capture, and £308 without. Modelling estimated cost per quality-adjusted life-year at £15,000 with existing electronic data capture; and £22,200 without.Intervention paramedics referred twice as many participants to falls services with no difference in safety. CCDS is potentially cost-effective, especially with existing electronic data capture.ISRCTN Register ISRCTN

  2. Real-Time Clinical Decision Support System with Data Stream Mining

    Yang Zhang


    Full Text Available This research aims to describe a new design of data stream mining system that can analyze medical data stream and make real-time prediction. The motivation of the research is due to a growing concern of combining software technology and medical functions for the development of software application that can be used in medical field of chronic disease prognosis and diagnosis, children healthcare, diabetes diagnosis, and so forth. Most of the existing software technologies are case-based data mining systems. They only can analyze finite and structured data set and can only work well in their early years and can hardly meet today's medical requirement. In this paper, we describe a clinical-support-system based data stream mining technology; the design has taken into account all the shortcomings of the existing clinical support systems.

  3. Implementation of Clinical Pharmacogenomics within a Large Health System: From Electronic Health Record Decision Support to Consultation Services.

    Hicks, J Kevin; Stowe, David; Willner, Marc A; Wai, Maya; Daly, Thomas; Gordon, Steven M; Lashner, Bret A; Parikh, Sumit; White, Robert; Teng, Kathryn; Moss, Timothy; Erwin, Angelika; Chalmers, Jeffrey; Eng, Charis; Knoer, Scott


    The number of clinically relevant gene-based guidelines and recommendations pertaining to drug prescribing continues to grow. Incorporating gene-drug interaction information into the drug-prescribing process can help optimize pharmacotherapy outcomes and improve patient safety. However, pharmacogenomic implementation barriers exist such as integration of pharmacogenomic results into electronic health records (EHRs), development and deployment of pharmacogenomic decision support tools to EHRs, and feasible models for establishing ambulatory pharmacogenomic clinics. We describe the development of pharmacist-managed pharmacogenomic services within a large health system. The Clinical Pharmacogenetics Implementation Consortium guidelines for HLA-B*57:01-abacavir, HLA-B*15:02-carbamazepine, and TPMT-thiopurines (i.e., azathioprine, mercaptopurine, and thioguanine) were systematically integrated into patient care. Sixty-three custom rules and alerts (20 for TPMT-thiopurines, 8 for HLA-B*57:01-abacavir, and 35 for HLA-B*15:02-anticonvulsants) were developed and deployed to the EHR for the purpose of providing point-of-care pharmacogenomic decision support. In addition, a pharmacist and physician-geneticist collaboration established a pharmacogenomics ambulatory clinic. This clinic provides genetic testing when warranted, result interpretation along with pharmacotherapy recommendations, and patient education. Our processes for developing these pharmacogenomic services and solutions for addressing implementation barriers are presented. PMID:27312955

  4. Design and Development of a Sharable Clinical Decision Support System Based on a Semantic Web Service Framework.

    Zhang, Yi-Fan; Gou, Ling; Tian, Yu; Li, Tian-Chang; Zhang, Mao; Li, Jing-Song


    Clinical decision support (CDS) systems provide clinicians and other health care stakeholders with patient-specific assessments or recommendations to aid in the clinical decision-making process. Despite their demonstrated potential for improving health care quality, the widespread availability of CDS systems has been limited mainly by the difficulty and cost of sharing CDS knowledge among heterogeneous healthcare information systems. The purpose of this study was to design and develop a sharable clinical decision support (S-CDS) system that meets this challenge. The fundamental knowledge base consists of independent and reusable knowledge modules (KMs) to meet core CDS needs, wherein each KM is semantically well defined based on the standard information model, terminologies, and representation formalisms. A semantic web service framework was developed to identify, access, and leverage these KMs across diverse CDS applications and care settings. The S-CDS system has been validated in two distinct client CDS applications. Model-level evaluation results confirmed coherent knowledge representation. Application-level evaluation results reached an overall accuracy of 98.66 % and a completeness of 96.98 %. The evaluation results demonstrated the technical feasibility and application prospect of our approach. Compared with other CDS engineering efforts, our approach facilitates system development and implementation and improves system maintainability, scalability and efficiency, which contribute to the widespread adoption of effective CDS within the healthcare domain. PMID:27002818

  5. Decision Support for Radiologists

    M. Fatehi


    Full Text Available Introduction & Background: Radiology practice like any other discipline in medicine consists of professional problem solving. A practicing radiologist may face different kinds of problems from pathology finding in im-age, suggestion of appropriate workup in a specific situation, formulating relevant differential diagnosis list for comparison with normal variants and artifacts. When a radiologist has the opportunity to use a computer he/she will also be able to use digital material/technology to solve these problems and make sound decisions. The available methods/materials for digital decision support in radiology may be categorized as follow: A. Image Processing When a radiological image is captured or converted to digital format, techniques like edge enhancement and contrast change may improve the diagnostic value of an image and help in decision making. B. Computer-aided Detection Thoracic imaging and mammography are two fields with promising advances in computer-aided diagnosis (CAD. The ultimate role of CAD is as a second opinion besides radiologists own perception. It is obvious how-ever that when available, CAD may decrease detection errors in radiology practice. C. Decision Support Databases Image Banks: An electronic atlas may be used to compare patients’ image to a predefined classified set of im-ages in order to help radiologist in pattern recognition. This may also be used for anatomic details and variants. Knowledge Bases: A digital differential diagnosis table or algorithmic approach to a specific problem may be helpful in reading room. Digital Textbooks: Classical radiological textbooks may be used in routine practice to remember some definitions, lists or hints, When available, digital version of textbooks are invaluable decision aids. D. Internet resources Online resources can be easily updated, widely used by different users, uniformly applied by different radiolo-gists. Although digital decision support materials and

  6. Use of conditional rule structure to automate clinical decision support: a comparison of artificial intelligence and deterministic programming techniques.

    Friedman, R H; Frank, A D


    A rule-based computer system was developed to perform clinical decision-making support within a medical information system, oncology practice, and clinical research. This rule-based system, which has been programmed using deterministic rules, possesses features of generalizability, modularity of structure, convenience in rule acquisition, explanability, and utility for patient care and teaching, features which have been identified as advantages of artificial intelligence (AI) rule-based systems. Formal rules are primarily represented as conditional statements; common conditions and actions are stored in system dictionaries so that they can be recalled at any time to form new decision rules. Important similarities and differences exist in the structure of this system and clinical computer systems utilizing artificial intelligence (AI) production rule techniques. The non-AI rule-based system possesses advantages in cost and ease of implementation. The degree to which significant medical decision problems can be solved by this technique remains uncertain as does whether the more complex AI methodologies will be required. PMID:6352165

  7. A clinical decision support system for integrating tuberculosis and HIV care in Kenya: a human-centered design approach.

    Caricia Catalani

    Full Text Available With the aim of integrating HIV and tuberculosis care in rural Kenya, a team of researchers, clinicians, and technologists used the human-centered design approach to facilitate design, development, and deployment processes of new patient-specific TB clinical decision support system for medical providers. In Kenya, approximately 1.6 million people are living with HIV and have a 20-times higher risk of dying of tuberculosis. Although tuberculosis prevention and treatment medication is widely available, proven to save lives, and prioritized by the World Health Organization, ensuring that it reaches the most vulnerable communities remains challenging. Human-centered design, used in the fields of industrial design and information technology for decades, is an approach to improving the effectiveness and impact of innovations that has been scarcely used in the health field. Using this approach, our team followed a 3-step process, involving mixed methods assessment to (1 understand the situation through the collection and analysis of site observation sessions and key informant interviews; (2 develop a new clinical decision support system through iterative prototyping, end-user engagement, and usability testing; and, (3 implement and evaluate the system across 24 clinics in rural West Kenya. Through the application of this approach, we found that human-centered design facilitated the process of digital innovation in a complex and resource-constrained context.

  8. A clinical decision support system for integrating tuberculosis and HIV care in Kenya: a human-centered design approach.

    Catalani, Caricia; Green, Eric; Owiti, Philip; Keny, Aggrey; Diero, Lameck; Yeung, Ada; Israelski, Dennis; Biondich, Paul


    With the aim of integrating HIV and tuberculosis care in rural Kenya, a team of researchers, clinicians, and technologists used the human-centered design approach to facilitate design, development, and deployment processes of new patient-specific TB clinical decision support system for medical providers. In Kenya, approximately 1.6 million people are living with HIV and have a 20-times higher risk of dying of tuberculosis. Although tuberculosis prevention and treatment medication is widely available, proven to save lives, and prioritized by the World Health Organization, ensuring that it reaches the most vulnerable communities remains challenging. Human-centered design, used in the fields of industrial design and information technology for decades, is an approach to improving the effectiveness and impact of innovations that has been scarcely used in the health field. Using this approach, our team followed a 3-step process, involving mixed methods assessment to (1) understand the situation through the collection and analysis of site observation sessions and key informant interviews; (2) develop a new clinical decision support system through iterative prototyping, end-user engagement, and usability testing; and, (3) implement and evaluate the system across 24 clinics in rural West Kenya. Through the application of this approach, we found that human-centered design facilitated the process of digital innovation in a complex and resource-constrained context. PMID:25170939

  9. A Clinical Decision Support Framework for Incremental Polyps Classification in Virtual Colonoscopy

    Hiroyuki Yoshida


    Full Text Available We present in this paper a novel dynamic learning method for classifying polyp candidate detections in Computed Tomographic Colonography (CTC using an adaptation of the Least Square Support Vector Machine (LS-SVM. The proposed technique, called Weighted Proximal Support Vector Machines (WP-SVM, extends the offline capabilities of the SVM scheme to address practical CTC applications. Incremental data are incorporated in the WP-SVM as a weighted vector space, and the only storage requirements are the hyperplane parameters. WP-SVM performance evaluation based on 169 clinical CTC cases using a 3D computer-aided diagnosis (CAD scheme for feature reduction comparable favorably with previously published CTC CAD studies that have however involved only binary and offline classification schemes. The experimental results obtained from iteratively applying WP-SVM to improve detection sensitivity demonstrate its viability for incremental learning, thereby motivating further follow on research to address a wider range of true positive subclasses such as pedunculated, sessile, and flat polyps, and over a wider range of false positive subclasses such as folds, stool, and tagged materials.

  10. The process of development of a prioritization tool for a clinical decision support build within a computerized provider order entry system: Experiences from St Luke's Health System.

    Wolf, Matthew; Miller, Suzanne; DeJong, Doug; House, John A; Dirks, Carl; Beasley, Brent


    To establish a process for the development of a prioritization tool for a clinical decision support build within a computerized provider order entry system and concurrently to prioritize alerts for Saint Luke's Health System. The process of prioritizing clinical decision support alerts included (a) consensus sessions to establish a prioritization process and identify clinical decision support alerts through a modified Delphi process and (b) a clinical decision support survey to validate the results. All members of our health system's physician quality organization, Saint Luke's Care as well as clinicians, administrators, and pharmacy staff throughout Saint Luke's Health System, were invited to participate in this confidential survey. The consensus sessions yielded a prioritization process through alert contextualization and associated Likert-type scales. Utilizing this process, the clinical decision support survey polled the opinions of 850 clinicians with a 64.7 percent response rate. Three of the top rated alerts were approved for the pre-implementation build at Saint Luke's Health System: Acute Myocardial Infarction Core Measure Sets, Deep Vein Thrombosis Prophylaxis within 4 h, and Criteria for Sepsis. This study establishes a process for developing a prioritization tool for a clinical decision support build within a computerized provider order entry system that may be applicable to similar institutions. PMID:25814483

  11. An international observational study suggests that artificial intelligence for clinical decision support optimizes anemia management in hemodialysis patients.

    Barbieri, Carlo; Molina, Manuel; Ponce, Pedro; Tothova, Monika; Cattinelli, Isabella; Ion Titapiccolo, Jasmine; Mari, Flavio; Amato, Claudia; Leipold, Frank; Wehmeyer, Wolfgang; Stuard, Stefano; Stopper, Andrea; Canaud, Bernard


    Managing anemia in hemodialysis patients can be challenging because of competing therapeutic targets and individual variability. Because therapy recommendations provided by a decision support system can benefit both patients and doctors, we evaluated the impact of an artificial intelligence decision support system, the Anemia Control Model (ACM), on anemia outcomes. Based on patient profiles, the ACM was built to recommend suitable erythropoietic-stimulating agent doses. Our retrospective study consisted of a 12-month control phase (standard anemia care), followed by a 12-month observation phase (ACM-guided care) encompassing 752 patients undergoing hemodialysis therapy in 3 NephroCare clinics located in separate countries. The percentage of hemoglobin values on target, the median darbepoetin dose, and individual hemoglobin fluctuation (estimated from the intrapatient hemoglobin standard deviation) were deemed primary outcomes. In the observation phase, median darbepoetin consumption significantly decreased from 0.63 to 0.46 μg/kg/month, whereas on-target hemoglobin values significantly increased from 70.6% to 76.6%, reaching 83.2% when the ACM suggestions were implemented. Moreover, ACM introduction led to a significant decrease in hemoglobin fluctuation (intrapatient standard deviation decreased from 0.95 g/dl to 0.83 g/dl). Thus, ACM support helped improve anemia outcomes of hemodialysis patients, minimizing erythropoietic-stimulating agent use with the potential to reduce the cost of treatment. PMID:27262365

  12. An HL7-CDA wrapper for facilitating semantic interoperability to rule-based Clinical Decision Support Systems.

    Sáez, Carlos; Bresó, Adrián; Vicente, Javier; Robles, Montserrat; García-Gómez, Juan Miguel


    The success of Clinical Decision Support Systems (CDSS) greatly depends on its capability of being integrated in Health Information Systems (HIS). Several proposals have been published up to date to permit CDSS gathering patient data from HIS. Some base the CDSS data input on the HL7 reference model, however, they are tailored to specific CDSS or clinical guidelines technologies, or do not focus on standardizing the CDSS resultant knowledge. We propose a solution for facilitating semantic interoperability to rule-based CDSS focusing on standardized input and output documents conforming an HL7-CDA wrapper. We define the HL7-CDA restrictions in a HL7-CDA implementation guide. Patient data and rule inference results are mapped respectively to and from the CDSS by means of a binding method based on an XML binding file. As an independent clinical document, the results of a CDSS can present clinical and legal validity. The proposed solution is being applied in a CDSS for providing patient-specific recommendations for the care management of outpatients with diabetes mellitus. PMID:23199936

  13. Computerized clinical decision support systems for acute care management: A decision-maker-researcher partnership systematic review of effects on process of care and patient outcomes

    Sahota Navdeep


    Full Text Available Abstract Background Acute medical care often demands timely, accurate decisions in complex situations. Computerized clinical decision support systems (CCDSSs have many features that could help. However, as for any medical intervention, claims that CCDSSs improve care processes and patient outcomes need to be rigorously assessed. The objective of this review was to systematically review the effects of CCDSSs on process of care and patient outcomes for acute medical care. Methods We conducted a decision-maker-researcher partnership systematic review. MEDLINE, EMBASE, Evidence-Based Medicine Reviews databases (Cochrane Database of Systematic Reviews, DARE, ACP Journal Club, and others, and the Inspec bibliographic database were searched to January 2010, in all languages, for randomized controlled trials (RCTs of CCDSSs in all clinical areas. We included RCTs that evaluated the effect on process of care or patient outcomes of a CCDSS used for acute medical care compared with care provided without a CCDSS. 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-six studies met our inclusion criteria for acute medical care. The CCDSS improved process of care in 63% (22/35 of studies, including 64% (9/14 of medication dosing assistants, 82% (9/11 of management assistants using alerts/reminders, 38% (3/8 of management assistants using guidelines/algorithms, and 67% (2/3 of diagnostic assistants. Twenty studies evaluated patient outcomes, of which three (15% reported improvements, all of which were medication dosing assistants. Conclusion The majority of CCDSSs demonstrated improvements in process of care, but patient outcomes were less likely to be evaluated and far less likely to show positive results.

  14. A Novel Clinical Decision Support System Using Improved Adaptive Genetic Algorithm for the Assessment of Fetal Well-Being

    Sindhu Ravindran


    Full Text Available A novel clinical decision support system is proposed in this paper for evaluating the fetal well-being from the cardiotocogram (CTG dataset through an Improved Adaptive Genetic Algorithm (IAGA and Extreme Learning Machine (ELM. IAGA employs a new scaling technique (called sigma scaling to avoid premature convergence and applies adaptive crossover and mutation techniques with masking concepts to enhance population diversity. Also, this search algorithm utilizes three different fitness functions (two single objective fitness functions and multi-objective fitness function to assess its performance. The classification results unfold that promising classification accuracy of 94% is obtained with an optimal feature subset using IAGA. Also, the classification results are compared with those of other Feature Reduction techniques to substantiate its exhaustive search towards the global optimum. Besides, five other benchmark datasets are used to gauge the strength of the proposed IAGA algorithm.

  15. Intention to adopt clinical decision support systems in a developing country: effect of Physician’s perceived professional autonomy, involvement and belief: a cross-sectional study

    Sambasivan Murali; Esmaeilzadeh Pouyan; Kumar Naresh; Nezakati Hossein


    Abstract Background Computer-based clinical decision support systems (CDSS) are regarded as a key element to enhance decision-making in a healthcare environment to improve the quality of medical care delivery. The concern of having new CDSS unused is still one of the biggest issues in developing countries for the developers and implementers of clinical IT systems. The main objectives of this study are to determine whether (1) the physician’s perceived professional autonomy, (2) involvement in...

  16. Nurses' Numeracy and Graphical Literacy: Informing Studies of Clinical Decision Support Interfaces.

    Lopez, Karen Dunn; Wilkie, Diana J; Yao, Yingwei; Sousa, Vanessa; Febretti, Alessandro; Stifter, Janet; Johnson, Andrew; Keenan, Gail M


    We present findings of a comparative study of numeracy and graph literacy in a representative group of 60 practicing nurses. This article focuses on a fundamental concern related to the effectiveness of numeric information displayed in various features in the electronic health record during clinical workflow. Our findings suggest the need to consider numeracy and graph literacy when presenting numerical information as well as the potential for tailoring numeric display types to an individual's cognitive strengths. PMID:26323050

  17. Clinical Decision Support System to Enhance Quality Control of Spirometry Using Information and Communication Technologies

    Burgos Rincón, Felip; Melia, Umberto Sergio Pio; Vallverdú Ferrer, Montserrat; Velickovski, Filip; Lluch-Ariet, Magí; Caminal Magrans, Pere; Roca-Torrent, Josep


    Background: We recently demonstrated that quality of spirometry in primary care could markedly improve with remote offline support from specialized professionals. It is hypothesized that implementation of automatic online assessment of quality of spirometry using information and communication technologies may significantly enhance the potential for extensive deployment of a high quality spirometry program in integrated care settings. Objective: The objective of the study was to elaborate a...

  18. Do computerised clinical decision support systems for prescribing change practice? A systematic review of the literature (1990-2007

    Williamson Margaret


    Full Text Available Abstract Background Computerised clinical decision support systems (CDSSs are used widely to improve quality of care and patient outcomes. This systematic review evaluated the impact of CDSSs in targeting specific aspects of prescribing, namely initiating, monitoring and stopping therapy. We also examined the influence of clinical setting (institutional vs ambulatory care, system- or user-initiation of CDSS, multi-faceted vs stand alone CDSS interventions and clinical target on practice changes in line with the intent of the CDSS. Methods We searched Medline, Embase and PsychINFO for publications from 1990-2007 detailing CDSS prescribing interventions. Pairs of independent reviewers extracted the key features and prescribing outcomes of methodologically adequate studies (experiments and strong quasi-experiments. Results 56 studies met our inclusion criteria, 38 addressing initiating, 23 monitoring and three stopping therapy. At the time of initiating therapy, CDSSs appear to be somewhat more effective after, rather than before, drug selection has occurred (7/12 versus 12/26 studies reporting statistically significant improvements in favour of CDSSs on = 50% of prescribing outcomes reported. CDSSs also appeared to be effective for monitoring therapy, particularly using laboratory test reminders (4/7 studies reporting significant improvements in favour of CDSSs on the majority of prescribing outcomes. None of the studies addressing stopping therapy demonstrated impacts in favour of CDSSs over comparators. The most consistently effective approaches used system-initiated advice to fine-tune existing therapy by making recommendations to improve patient safety, adjust the dose, duration or form of prescribed drugs or increase the laboratory testing rates for patients on long-term therapy. CDSSs appeared to perform better in institutional compared to ambulatory settings and when decision support was initiated automatically by the system as opposed to

  19. Computerized Clinical Decision Support to Prevent Venous Thromboembolism Among Hospitalized Patients: Proximal Outcomes from a Multiyear Quality Improvement Project.

    Amland, Robert C; Dean, Bonnie B; Yu, HsingTing; Ryan, Hugh; Orsund, Timothy; Hackman, Jeffrey L; Roberts, Shauna R


    Despite venous thromboembolism (VTE) policy initiatives, gaps exist between guidelines and practice. In response, hospitals implement clinical decision support (CDS) systems to improve VTE prophylaxis. To assess the impact of a VTE CDS on reducing incidence of VTE, this study used a pretest/posttest, longitudinal, cohort design incorporating electronic health record (EHR) data from one urban tertiary and level 1 trauma center, and one suburban hospital. VTE CDS was embedded into the EHR system. The study included 45,046 admissions; 171,753 patient days; and 110 VTE events. The VTE rate declined from 0.954 per 1,000 patient days to 0.434 comparing baseline to full VTE CDS. Compared to baseline, patients benefitting from VTE CDS were 35% less likely to have a VTE. VTE CDS utilization achieved 78.4% patients assessed within 24 hr from admission, 64.0% patients identified at risk, and 47.7% patients at risk for VTE with an initiated VTE interdisciplinary plan of care. CDS systems with embedded algorithms, alerts, and notification capabilities enable physicians at the point of care to utilize guidelines and make impactful decisions to prevent VTE. This study demonstrates a phased-in implementation of VTE CDS as an effective approach toward VTE prevention. Implications for future research and quality improvement are discussed as well. PMID:26151096

  20. Formal Logic and Flowchart for Diagnosis Validity Verification and Inclusion in Clinical Decision Support Systems

    Sosa, M.; Grundel, L.; Simini, F.


    Logical reasoning is part of medical practice since its origins. Modern Medicine has included information-intensive tools to refine diagnostics and treatment protocols. We are introducing formal logic teaching in Medical School prior to Clinical Internship, to foster medical practice. Two simple examples (Acute Myocardial Infarction and Diabetes Mellitus) are given in terms of formal logic expression and truth tables. Flowcharts of both diagnostic processes help understand the procedures and to validate them logically. The particularity of medical information is that it is often accompanied by “missing data” which suggests to adapt formal logic to a “three state” logic in the future. Medical Education must include formal logic to understand complex protocols and best practices, prone to mutual interactions.

  1. Future perspectives toward the early definition of a multivariate decision-support scheme employed in clinical decision making for senior citizens.

    Frantzidis, Christos A; Gilou, Sotiria; Billis, Antonis; Karagianni, Maria; Bratsas, Charalampos D; Bamidis, Panagiotis


    Recent neuroscientific studies focused on the identification of pathological neurophysiological patterns (emotions, geriatric depression, memory impairment and sleep disturbances) through computerised clinical decision-support systems. Almost all these research attempts employed either resting-state condition (e.g. eyes-closed) or event-related potentials extracted during a cognitive task known to be affected by the disease under consideration. This Letter reviews existing data mining techniques and aims to enhance their robustness by proposing a holistic decision framework dealing with comorbidities and early symptoms' identification, while it could be applied in realistic occasions. Multivariate features are elicited and fused in order to be compared with average activities characteristic of each neuropathology group. A proposed model of the specific cognitive function which may be based on previous findings (a priori information) and/or validated by current experimental data should be then formed. So, the proposed scheme facilitates the early identification and prevention of neurodegenerative phenomena. Neurophysiological semantic annotation is hypothesised to enhance the importance of the proposed framework in facilitating the personalised healthcare of the information society and medical informatics research community. PMID:27222732

  2. Shared clinical decision making

    AlHaqwi, Ali I.; AlDrees, Turki M.; AlRumayyan, Ahmad; AlFarhan, Ali I.; Alotaibi, Sultan S.; AlKhashan, Hesham I.; Badri, Motasim


    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. PMID:26620990

  3. Clinical decision support of therapeutic drug monitoring of phenytoin: measured versus adjusted phenytoin plasma concentrations

    Krasowski Matthew D


    Full Text Available Abstract Background Therapeutic drug monitoring of phenytoin by measurement of plasma concentrations is often employed to optimize clinical efficacy while avoiding adverse effects. This is most commonly accomplished by measurement of total phenytoin plasma concentrations. However, total phenytoin levels can be misleading in patients with factors such as low plasma albumin that alter the free (unbound concentrations of phenytoin. Direct measurement of free phenytoin concentrations in plasma is more costly and time-consuming than determination of total phenytoin concentrations. An alternative to direct measurement of free phenytoin concentrations is use of the Sheiner-Tozer equation to calculate an adjusted phenytoin that corrects for the plasma albumin concentration. Innovative medical informatics tools to identify patients who would benefit from adjusted phenytoin calculations or from laboratory measurement of free phenytoin are needed to improve safety and efficacy of phenytoin pharmacotherapy. The electronic medical record for an academic medical center was searched for the time period from August 1, 1996 to November 30, 2010 for patients who had total phenytoin and free phenytoin determined on the same blood draw, and also a plasma albumin measurement within 7 days of the phenytoin measurements. The measured free phenytoin plasma concentration was used as the gold standard. Results In this study, the standard Sheiner-Tozer formula for calculating an estimated (adjusted phenytoin level more frequently underestimates than overestimates the measured free phenytoin relative to the respective therapeutic ranges. Adjusted phenytoin concentrations provided superior classification of patients than total phenytoin measurements, particularly at low albumin concentrations. Albumin plasma concentrations up to 7 days prior to total phenytoin measurements can be used for adjusted phenytoin concentrations. Conclusions The results suggest that a measured

  4. Coupling Clinical Decision Support System with Computerized Prescriber Order Entry and their Dynamic Plugging in the Medical Workflow System

    Bouzguenda, Lotfi


    This work deals with coupling Clinical Decision Support System (CDSS) with Computerized Prescriber Order Entry (CPOE) and their dynamic plugging in the medical Workflow Management System (WfMS). First, in this paper we argue some existing CDSS representative of the state of the art in order to emphasize their inability to deal with coupling with CPOE and medical WfMS. The multi-agent technology is at the basis of our proposition since (i) it provides natural abstractions to deal with distribution, heterogeneity and autonomy which are inherent to the previous systems (CDSS, CPOE and medical WfMS), and (ii) it introduces powerful concepts such as organizations, goals and roles useful to describe in details the coordination of the different components involved in these systems. In this paper, we also propose a Multi-Agent System (MAS) to support the coupling CDSS with CPOE. Finally, we show how we integrate the proposed MAS in the medical workflow management system which is also based on collaborating agents

  5. Examining perceptions of the usefulness and usability of a mobile-based system for pharmacogenomics clinical decision support: a mixed methods study

    Blagec, Kathrin; Romagnoli, Katrina M.; Boyce, Richard D.; Samwald, Matthias


    Background. Pharmacogenomic testing has the potential to improve the safety and efficacy of pharmacotherapy, but clinical application of pharmacogenetic knowledge has remained uncommon. Clinical Decision Support (CDS) systems could help overcome some of the barriers to clinical implementation. The aim of this study was to evaluate the perception and usability of a web- and mobile-enabled CDS system for pharmacogenetics-guided drug therapy–the Medication Safety Code (MSC) system–among potentia...

  6. Computerized clinical decision support systems for primary preventive care: A decision-maker-researcher partnership systematic review of effects on process of care and patient outcomes

    Wilczynski Nancy L


    Full Text Available Abstract Background Computerized clinical decision support systems (CCDSSs are claimed to improve processes and outcomes of primary preventive care (PPC, but their effects, safety, and acceptance must be confirmed. We updated our previous systematic reviews of CCDSSs and integrated a knowledge translation approach in the process. The objective was to review randomized controlled trials (RCTs assessing the effects of CCDSSs for PPC on process of care, patient outcomes, harms, and costs. Methods We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews Database, Inspec, and other databases, as well as reference lists through January 2010. We contacted authors to confirm data or provide additional information. We included RCTs that assessed the effect of a CCDSS for PPC on process of care and patient outcomes compared to care provided without a CCDSS. 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 We added 17 new RCTs to our 2005 review for a total of 41 studies. RCT quality improved over time. CCDSSs improved process of care in 25 of 40 (63% RCTs. Cumulative scientifically strong evidence supports the effectiveness of CCDSSs for screening and management of dyslipidaemia in primary care. There is mixed evidence for effectiveness in screening for cancer and mental health conditions, multiple preventive care activities, vaccination, and other preventive care interventions. Fourteen (34% trials assessed patient outcomes, and four (29% reported improvements with the CCDSS. Most trials were not powered to evaluate patient-important outcomes. CCDSS costs and adverse events were reported in only six (15% and two (5% trials, respectively. Information on study duration was often missing, limiting our ability to assess sustainability of CCDSS effects. Conclusions

  7. Designing Colorectal Cancer Screening Decision Support: A Cognitive Engineering Enterprise

    Militello, Laura G.; Saleem, Jason J; Borders, Morgan R.; Sushereba, Christen E.; Haverkamp, Donald; Steven P. Wolf; Doebbeling, Bradley N.


    Adoption of clinical decision support has been limited. Important barriers include an emphasis on algorithmic approaches to decision support that do not align well with clinical work flow and human decision strategies, and the expense and challenge of developing, implementing, and refining decision support features in existing electronic health records (EHRs). We applied decision-centered design to create a modular software application to support physicians in managing and tracking colorectal...

  8. Design of decision support systems

    The paper is addressing the design of decision support systems to be used in the nuclear industry and the requirements placed on such systems. A general model of the decision-making situation is proposed for the structuring of the different functions provided by the decision support system. The relative merits of different functions of the support systems and their practical implementation are discussed. A proposal for the functions to be included in a decision support system is given as a result fo the discussion. The practical design of decision support system is discussed, and some general remarks on the management of design projects are given. The use of decision support systems and their integration in the every day routines are also discussed. Reference is given to experiments, where a large scale validation of decision support systems have been attempted. One of the findings from the validation experiments, is that it might be difficult or even impossible to prove the benefit of a proposed design of a decision support system in quantitative terms. Present design practices are bringing in the concern for the human as a part of the system comparatively late and in a rather unsystematic way. As a conclusion it is argued that more effort should be spent in building up an understanding of the dynamics of design projects. Such an understanding can be used to create better models for carrying out the design projects and to specify different design tools to be used. (author). 17 refs, 1 fig, 5 tabs

  9. An Organizational Informatics Analysis of Colorectal, Breast, and Cervical Cancer Screening Clinical Decision Support and Information Systems within Community Health Centers

    Carney, Timothy Jay


    A study design has been developed that employs a dual modeling approach to identify factors associated with facility-level cancer screening improvement and how this is mediated by the use of clinical decision support. This dual modeling approach combines principles of (1) Health Informatics, (2) Cancer Prevention and Control, (3) Health Services…

  10. An Electronic Clinical Decision Support Tool to Assist Primary Care Providers in Cardiovascular Disease Risk Management: Development and Mixed Methods Evaluation

    Peiris, David P; Joshi, Rohina; Webster, Ruth J; Groenestein, Patrick; Usherwood, Tim P; Heeley, Emma; Turnbull, Fiona M; Lipman, Alexandra; Patel, Anushka A.


    Background Challenges remain in translating the well-established evidence for management of cardiovascular disease (CVD) risk into clinical practice. Although electronic clinical decision support (CDS) systems are known to improve practitioner performance, their development in Australian primary health care settings is limited. Objectives Study aims were to (1) develop a valid CDS tool that assists Australian general practitioners (GPs) in global CVD risk management, and (2) preliminarily eva...

  11. Pre-Operative Prediction of Advanced Prostatic Cancer Using Clinical Decision Support Systems: Accuracy Comparison between Support Vector Machine and Artificial Neural Network

    The purpose of the current study was to develop support vector machine (SVM) and artificial neural network (ANN) models for the pre-operative prediction of advanced prostate cancer by using the parameters acquired from transrectal ultrasound (TRUS)-guided prostate biopsies, and to compare the accuracies between the two models. Five hundred thirty-two consecutive patients who underwent prostate biopsies and prostatectomies for prostate cancer were divided into the training and test groups (n = 300 versus n 232). From the data in the training group, two clinical decision support systems (CDSSs-[SVM and ANN]) were constructed with input (age, prostate specific antigen level, digital rectal examination, and five biopsy parameters) and output data (the probability for advanced prostate cancer [> pT3a]). From the data of the test group, the accuracy of output data was evaluated. The areas under the receiver operating characteristic (ROC) curve (AUC) were calculated to summarize the overall performances, and a comparison of the ROC curves was performed (p < 0.05). The AUC of SVM and ANN is 0.805 and 0.719, respectively (p = 0.020), in the pre-operative prediction of advanced prostate cancer. Te performance of SVM is superior to ANN in the pre-operative prediction of advanced prostate cancer.

  12. Decision support systems

    Jørgensen, L.N.; Noe, E.; Langvad, A.M.;


    system Crop Protection Online is widely used by advisors and as a learning tool for students. Although the system has been validated in many field trials over the years and has shown reliable results, the number of end-users among farmers has been relatively low during the last 10 years (approximately...... 1000 farmers). A sociological investigation of farmers' decision-making styles in the area of crop protection has shown that arable farmers can be divided into three major groups: (a) system-orientated farmers, (b) experience-based farmers and (c) advisory-orientated farmers. The information required...

  13. Decision support for emergency management

    A short introduction will be given to the Nordic project ''NKA/INF: Information Technology for Accident and Emergency Management'', which is now in its final phase. To perform evaluation of the project, special scenarious have been developed, and experiments based on these will be fulfilled and compared with experiments without use of the decision support system. Furthermore, the succeeding European project, ''IT Support for Emergency Management - ISEM'', with the purpose of developing a decision support system for complex and distributed decision making in emergency management in full scale, will be described and the preliminary conceptual model for the system will be presented. (author)

  14. Development of a real-time clinical decision support system upon the web mvc-based architecture for prostate cancer treatment

    Liang Wen-Miin


    Full Text Available Abstract Background A real-time clinical decision support system (RTCDSS with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC architecture, by which the system can easily be adapted to different diseases and applications. Methods We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. Results The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Conclusions Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital

  15. Clinical Decision Support Using Electronic Medical Records: For the Improvement of Diabetes Care and Proper Use of Insulin for Inpatients.

    Seto, Ryoma; Wakabayashi, Susumu


    The aim of the study is to develop a scheme of a decision support system concerning insulin intervention for inpatients. Transaction data for 32,637 inpatients were collected from the EMR. As a result, antidiabetic agents were not taken by 38.9%-41.7% of patients with a Disease Complicated by DM. It is recommended that the EMR should provide a suggestion about insulin level for diseases with DM as a complicating factor. PMID:26262263

  16. A collaborative framework for contributing DICOM RT PHI (Protected Health Information) to augment data mining in clinical decision support

    Deshpande, Ruchi; Thuptimdang, Wanwara; DeMarco, John; Liu, Brent J.


    We have built a decision support system that provides recommendations for customizing radiation therapy treatment plans, based on patient models generated from a database of retrospective planning data. This database consists of relevant metadata and information derived from the following DICOM objects - CT images, RT Structure Set, RT Dose and RT Plan. The usefulness and accuracy of such patient models partly depends on the sample size of the learning data set. Our current goal is to increase this sample size by expanding our decision support system into a collaborative framework to include contributions from multiple collaborators. Potential collaborators are often reluctant to upload even anonymized patient files to repositories outside their local organizational network in order to avoid any conflicts with HIPAA Privacy and Security Rules. We have circumvented this problem by developing a tool that can parse DICOM files on the client's side and extract de-identified numeric and text data from DICOM RT headers for uploading to a centralized system. As a result, the DICOM files containing PHI remain local to the client side. This is a novel workflow that results in adding only relevant yet valuable data from DICOM files to the centralized decision support knowledge base in such a way that the DICOM files never leave the contributor's local workstation in a cloud-based environment. Such a workflow serves to encourage clinicians to contribute data for research endeavors by ensuring protection of electronic patient data.

  17. Evaluation of Nursing Documentation Completion of Stroke Patients in the Emergency Department: A Pre-Post Analysis Using Flowsheet Templates and Clinical Decision Support.

    Richardson, Karen J; Sengstack, Patricia; Doucette, Jeffrey N; Hammond, William E; Schertz, Matthew; Thompson, Julie; Johnson, Constance


    The primary aim of this performance improvement project was to determine whether the electronic health record implementation of stroke-specific nursing documentation flowsheet templates and clinical decision support alerts improved the nursing documentation of eligible stroke patients in seven stroke-certified emergency departments. Two system enhancements were introduced into the electronic record in an effort to improve nursing documentation: disease-specific documentation flowsheets and clinical decision support alerts. Using a pre-post design, project measures included six stroke management goals as defined by the National Institute of Neurological Disorders and Stroke and three clinical decision support measures based on entry of orders used to trigger documentation reminders for nursing: (1) the National Institutes of Health's Stroke Scale, (2) neurological checks, and (3) dysphagia screening. Data were reviewed 6 months prior (n = 2293) and 6 months following the intervention (n = 2588). Fisher exact test was used for statistical analysis. Statistical significance was found for documentation of five of the six stroke management goals, although effect sizes were small. Customizing flowsheets to meet the needs of nursing workflow showed improvement in the completion of documentation. The effects of the decision support alerts on the completeness of nursing documentation were not statistically significant (likely due to lack of order entry). For example, an order for the National Institutes of Health Stroke Scale was entered only 10.7% of the time, which meant no alert would fire for nursing in the postintervention group. Future work should focus on decision support alerts that trigger reminders for clinicians to place relevant orders for this population. PMID:26679006

  18. Using Clinical Decision Support and Dashboard Technology to Improve Heart Team Efficiency and Accuracy in a Transcatheter Aortic Valve Implantation (TAVI) Program.

    Clarke, Sarah; Wilson, Marisa L; Terhaar, Mary


    Heart Team meetings are becoming the model of care for patients undergoing transcatheter aortic valve implantations (TAVI) worldwide. While Heart Teams have potential to improve the quality of patient care, the volume of patient data processed during the meeting is large, variable, and comes from different sources. Thus, consolidation is difficult. Also, meetings impose substantial time constraints on the members and financial pressure on the institution. We describe a clinical decision support system (CDSS) designed to assist the experts in treatment selection decisions in the Heart Team. Development of the algorithms and visualization strategy required a multifaceted approach and end-user involvement. An innovative feature is its ability to utilize algorithms to consolidate data and provide clinically useful information to inform the treatment decision. The data are integrated using algorithms and rule-based alert systems to improve efficiency, accuracy, and usability. Future research should focus on determining if this CDSS improves patient selection and patient outcomes. PMID:27332170

  19. The design and implementation of an Interactive Computerised Decision Support Framework (ICDSF) as a strategy to improve nursing students' clinical reasoning skills.

    Hoffman, Kerry; Dempsey, Jennifer; Levett-Jones, Tracy; Noble, Danielle; Hickey, Noelene; Jeong, Sarah; Hunter, Sharyn; Norton, Carol


    This paper describes the conceptual design and testing of an Interactive Computerised Decision Support Framework (ICDSF) which was constructed to enable student nurses to "think like a nurse." The ICDSF was based on a model of clinical reasoning. Teaching student nurses to reason clinically is important as poor clinical reasoning skills can lead to "failure-to rescue" of deteriorating patients. The framework of the ICDSF was based on nursing concepts to encourage deep learning and transferability of knowledge. The principles of active student participation, situated cognition to solve problems, authenticity, and cognitive rehearsal were used to develop the ICDSF. The ICDSF was designed in such a way that students moved through it in a step-wise fashion and were required to achieve competency at each step before proceeding to the next. The quality of the ICDSF was evaluated using a questionairre survey, students' written comments and student assessment measures on a pilot and the ICDSF. Overall students were highly satisfied with the clinical scenarios of the ICDSF and believed they were an interesting and useful way to engage in authentic clinical learning. They also believed the ICDSF was useful in developing cognitive skills such as clinical reasoning, problem-solving and decision-making. Some reported issues were the need for good technical support and the lack of face to face contact when using e-learning. Some students also believed the ICDSF was less useful than actual clinical placements. PMID:21074299

  20. Analysis of the process of representing clinical statements for decision-support applications: a comparison of openEHR archetypes and HL7 virtual medical record.

    González-Ferrer, A; Peleg, M; Marcos, M; Maldonado, J A


    Delivering patient-specific decision-support based on computer-interpretable guidelines (CIGs) requires mapping CIG clinical statements (data items, clinical recommendations) into patients' data. This is most effectively done via intermediate data schemas, which enable querying the data according to the semantics of a shared standard intermediate schema. This study aims to evaluate the use of HL7 virtual medical record (vMR) and openEHR archetypes as intermediate schemas for capturing clinical statements from CIGs that are mappable to electronic health records (EHRs) containing patient data and patient-specific recommendations. Using qualitative research methods, we analyzed the encoding of ten representative clinical statements taken from two CIGs used in real decision-support systems into two health information models (openEHR archetypes and HL7 vMR instances) by four experienced informaticians. Discussion among the modelers about each case study example greatly increased our understanding of the capabilities of these standards, which we share in this educational paper. Differing in content and structure, the openEHR archetypes were found to contain a greater level of representational detail and structure while the vMR representations took fewer steps to complete. The use of openEHR in the encoding of CIG clinical statements could potentially facilitate applications other than decision-support, including intelligent data analysis and integration of additional properties of data items from existing EHRs. On the other hand, due to their smaller size and fewer details, the use of vMR potentially supports quicker mapping of EHR data into clinical statements. PMID:27209183

  1. A critical appraisal of the literature on the effects of computer-based clinical decision support systems on clinician performance and patient outcomes.

    Langton, K. B.; Johnston, M. E.; Haynes, R. B.; Mathieu, A


    OBJECTIVE: To review the evaluations of computer-based clinical decision support systems (CDSS's). DATA SOURCES: The literature collected in the MEDLARS, EMBASE, SCISEARCH and INSPEC databases was searched from 1974 to the present. The reference lists of relevant articles were reviewed as were conference proceedings. STUDY SELECTION: Prospective, controlled studies were included. Studies were rated for methodological quality. DATA EXTRACTION: Study quality was assessed and data on study setti...

  2. Which Soft? : decision support software

    Tereso, Anabela Pereira; Macedo, Ricardo; Abreu, Rafael; Brandão, João; Martins, Henrique


    In this project we developed a decision support software that helps to choose the best decision software, but can also be applied to any other problem of selection. It is based on multicriteria methods. With this software we try to give each user the best solution, depending on his preferences. The entire project was planned and outlined in UML, implemented in C# and the database was built with SQL Server. It was a project divided into three main stages: requirements gathering, UML spe...

  3. Decision Strategy Research: Policy Support

    The objective of SCK-CEN's R and D programme on decision strategy research are (1) to support and advise the Belgian authorities on specific problems concerning existing and potential hazards from exposure to ionising radiation, both in normal and emergency situations; (2) to perform research on relevant topics that might have an important impact on decision making related to nuclear applications, including social and economic sciences. Main achievements in this area in 1999 are described

  4. Decision Strategy Research: Policy Support

    Hardeman, F


    The objective of SCK-CEN's R and D programme on decision strategy research are (1) to support and advise the Belgian authorities on specific problems concerning existing and potential hazards from exposure to ionising radiation, both in normal and emergency situations; (2) to perform research on relevant topics that might have an important impact on decision making related to nuclear applications, including social and economic sciences. Main achievements in this area in 1999 are described.

  5. Decision Support for Internet Users:

    Fujimoto, Kazunori; Shimazu, Mitsunobu

    This paper describes availability of personal Web-pages and a prototype development for Decision Support for Internet Users, called DSIU, which is an area of research for decision support by using information on the Internet. The availability of Web-pages concerns usage of formal pages, which are provided by companies and so on, and personal pages, which are provided by private persons. Web-pages are gathered by using an Internet search engine to determine destinations for travel and personal pages are confirmed to provide much subjective information than formal pages. The prototype development concerns a travel recommendation system, which is a kind of decision support systems. The prototype uses subjective and objective information on the Internet to select several destinations for users and to provide explanations the reason why the destinations are recommended. This paper also describes our perspective of DSIU researches.

  6. Development and evaluation of a computerised clinical decision support system for switching drugs at the interface between primary and tertiary care

    Pruszydlo Markus G


    Full Text Available Abstract Background Upon admission to a hospital patients’ medications are frequently switched to alternative drugs compiled in so called hospital drug formularies. This substitution process is a laborious and error-prone task which should be supported by sophisticated electronic tools. We developed a computerised decision support system and evaluated benefit and potential harm associated with its use. Methods Based on a multi-step algorithm we identified drug classes suitable for exchange, defined conversion factors for therapeutic interchange, built a web-based decision support system, and implemented it into the computerised physician order entry of a large university hospital. For evaluation we compared medications manually switched by clinical pharmacists with the results of automated switching by the newly developed computer system and optimised the system in an iterative process. Thereafter the final system was tested in an independent set of prescriptions. Results After iterative optimisation of the logical framework the tool was able to switch drugs to pharmaceutical equivalents and alternatives; in addition, it contained 21 different drug classes for therapeutic substitution. In this final version it switched 91.6% of 202 documented medication consultations (containing 1,333 drugs automatically, leaving 8.4% for manual processing by clinical professionals. No incorrect drug switches were found. Conclusion A large majority (>90% of drug switches performed at the interface between primary and tertiary care can be handled automatically using electronic decision support systems, indicating that medication errors and workload of healthcare professionals can be considerably reduced.

  7. Crisis centre decision maker's support

    Decision makers generally have enormous responsibility and sometimes lack of reliable information. In case of such a serious events like nuclear accidents could be, man is usually under stress and stress, of course, is great potential contributor for making errors. Decision makers are often competent people with general knowledge and skills and they are not deeply concerned in some scientific or technical details. Reliable and realistic recommendation for decision makers provide so called supporting groups, established for this purpose and composed of high level skilled experts. Nevertheless, even experts are only human beings and therefore it is of the first importance that they have as much reliable information, methods and tools as possible to help them to evaluate what happened and to predict what can happen in future. Friendly user's interface of supporting tools is essential for correct interpretation of available data and for avoiding errors (author) (ml)

  8. How clinical decisions are made

    Bate, Louise; Hutchinson, Andrew; Underhill, Jonathan; Maskrey, Neal


    There is much variation in the implementation of the best available evidence into clinical practice. These gaps between evidence and practice are often a result of multiple individual decisions. When making a decision, there is so much potentially relevant information available, it is impossible to know or process it all (so called ‘bounded rationality’). Usually, a limited amount of information is selected to reach a sufficiently satisfactory decision, a process known as satisficing. There a...

  9. Implications of Decision Making Research for Decision Support and Displays

    Morrison, Jeffrey G.; Kelly, Richard T.; Moore, Ronald A.; Hutchins, Susan G.


    To appear in J. A. Cannon-Bowers & E. Salas (Eds.), Decision Making Under Stress: Implications for Training and Simulation. A prototype decision support system (DSS) was developed to enhance Navy tactical decision making based on naturalistic decision processes. Displays were developed to support critical decision making tasks through recognition-primed and explanation-based reasoning processes, and cognitive analysis was conducted of the decision making problems faced by Navy ...




    Effective contaminated land management requires a number of decisions addressing a suite of technical, economic, and social concerns. These concerns include human health risks, ecological risks, economic costs, technical feasibility of proposed remedial actions, and the value society places on clean-up and re-use of formerly contaminated lands. Decision making, in the face of uncertainty and multiple and often conflicting objectives, is a vital and challenging role in environmental management that affects a significant economic activity. Although each environmental remediation problem is unique and requires a site-specific analysis, many of the key decisions are similar in structure. This has led many to attempt to develop standard approaches. As part of the standardization process, attempts have been made to codify specialist expertise into decision support tools. This activity is intended to facilitate reproducible and transparent decision making. The process of codifying procedures has also been found to be a useful activity for establishing and rationalizing management processes. This study will have two primary objectives. The first is to develop taxonomy for Decision Support Tools (DST) to provide a framework for understanding the different tools and what they are designed to address in the context of environmental remediation problems. The taxonomy will have a series of subject areas for the DST. From these subjects, a few key areas will be selected for further study and software in these areas will be identified. The second objective, will be to review the existing DST in the selected areas and develop a screening matrix for each software product.

  11. Cardio Online Reader/COR: A Web 2.0-Based Tool Aimed at Clinical Decision-Making Support in Cardiology

    Papíková, Vendula; Zvolský, Miroslav

    Heidelberg: Springer Science-Business Media, 2012 - (Kostkova, P.; Szomszor, M.; Fowler, D.), s. 122-127. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering . 91). ISBN 978-3-642-29261-3. ISSN 1867-8211. [eHealth 2011. International Conference /4./. Málaga (ES), 21.11.2011-23.11.2011] R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : EBM * Web 2.0 * medical information sources * clinical decision-making support Subject RIV: IN - Informatics, Computer Science

  12. Feasibility of integrating a clinical decision support tool into an existing computerized physician order entry system to increase seasonal influenza vaccination in the emergency department.

    Venkat, Arvind; Chan-Tompkins, Noreen H; Hegde, Gajanan G; Chuirazzi, David M; Hunter, Roger; Szczesiul, Jillian M


    While emergency department (ED) seasonal influenza vaccination programs are feasible, reported implementation barriers include added staffing requirements to identify eligible patients and getting busy ED personnel to order and provide vaccination. We present a prospective, observational trial of integrating a clinical decision support tool into an existing ED computerized physician order entry (CPOE) system to increase ED seasonal influenza vaccination without added staffing resources, the operational barriers identified to program implementation, the revenue generated and data on opportunities for future quality improvement. Compared to the comparable pre-protocol period, ED influenza vaccination rose by 17.5% with a resultant profit margin of 34.5%. PMID:20620167

  13. Developing public health clinical decision support systems (CDSS for the outpatient community in New York City: our experience

    Singer Jesse


    Full Text Available Abstract Background Developing a clinically relevant set of quality measures that can be effectively used by an electronic health record (EHR is difficult. Whether it is achieving internal consensus on relevant priority quality measures, communicating to EHR vendors' whose programmers generally lack clinical contextual knowledge, or encouraging implementation of EHR that meaningfully impacts health outcomes, the path is challenging. However, greater transparency of population health, better accountability, and ultimately improved health outcomes is the goal and EHRs afford us a realistic chance of reaching it in a scalable way. Method In this article, we summarize our experience as a public health government agency with developing measures for a public health oriented EHR in New York City in partnership with a commercial EHR vendor. Results From our experience, there are six key lessons that we share in this article that we believe will dramatically increase the chance of success. First, define the scope and build consensus. Second, get support from executive leadership. Third, find an enthusiastic and competent software partner. Fourth, implement a transparent operational strategy. Fifth, create and test the EHR system with real life scenarios. Last, seek help when you need it. Conclusions Despite the challenges, we encourage public health agencies looking to build a similarly focused public health EHR to create one both for improved individual patient as well as the larger population health.

  14. Barriers to implementation of a computerized decision support system for depression: an observational report on lessons learned in "real world" clinical settings

    Sunderajan Prabha


    Full Text Available Abstract Background Despite wide promotion, clinical practice guidelines have had limited effect in changing physician behavior. Effective implementation strategies to date have included: multifaceted interventions involving audit and feedback, local consensus processes, marketing; reminder systems, either manual or computerized; and interactive educational meetings. In addition, there is now growing evidence that contextual factors affecting implementation must be addressed such as organizational support (leadership procedures and resources for the change and strategies to implement and maintain new systems. Methods To examine the feasibility and effectiveness of implementation of a computerized decision support system for depression (CDSS-D in routine public mental health care in Texas, fifteen study clinicians (thirteen physicians and two advanced nurse practitioners participated across five sites, accruing over 300 outpatient visits on 168 patients. Results Issues regarding computer literacy and hardware/software requirements were identified as initial barriers. Clinicians also reported concerns about negative impact on workflow and the potential need for duplication during the transition from paper to electronic systems of medical record keeping. Conclusion The following narrative report based on observations obtained during the initial testing and use of a CDSS-D in clinical settings further emphasizes the importance of taking into account organizational factors when planning implementation of evidence-based guidelines or decision support within a system.

  15. Computer decision support software safely improves glycemic control in the burn intensive care unit: a randomized controlled clinical study

    Mann, Elizabeth A.; Jones, John A.; Wolf, Steven E.; Wade, Charles E.


    Objective The optimal method for glycemic control in the critically burned patient is unknown. The purpose of this randomized controlled study was to determine the safety and efficacy of computer decision support software (CDSS) to control serum glucose concentration in a burn intensive care unit. Methods Eighteen adult burn/trauma patients receiving continuous insulin infusion were initially randomized to receive glucose management via a traditional paper-based protocol (PP) or a computer protocol (CP) for 72 hours, then crossed over to the alternate method for an additional 72 hours. Results Time in target glucose range (80-110 mg/dl) was higher in the CP group (47 ± 17% versus 41 ± 16.6%; p ≤ 0.05); time over target range was not significantly reduced in the CP group (49 ± 17.8% versus 54 ± 17.1; p = 0.08); and no difference was noted in time under target range of 80 mg/dl (CP 4.5 ± 2.8, PP 4.8 ± 3.3%; p = 0.8), under 60 mg/dl (p = 0.7), and under 40 mg/dl (p = 1.0). Severe hypoglycemic events (< 40 mg/dl) did not differ from the CP group compared to historical controls for patients receiving no insulin (p = 0.6). More glucose measurements were performed in the CP group (p = 0.0003), and nursing staff compliance with CP recommendations was greater (p < 0.0001). Conclusions Glycemic control using CDSS is safe and effective for the critically burned patient. Time in target range improved without increase in hypoglycemic events. CDSS enhanced consistency in practice, providing standardization among nursing staff. PMID:21240001

  16. General practitioners' attitudes and preparedness towards Clinical Decision Support in e-Prescribing (CDS-eP adoption in the West of Ireland: a cross sectional study

    O'Brien Timothy


    Full Text Available Abstract Background Electronic clinical decision support (CDS is increasingly establishing its role in evidence-based clinical practice. Considerable evidence supports its enhancement of efficiency in e-Prescribing, but some controversy remains. This study evaluated the practicality and identified the perceived benefits of, and barriers to, its future adoption in the West of Ireland. Methods This cross sectional study was carried out by means of a 27-part questionnaire sent to 262 registered general practitioners in Counties Galway, Mayo and Roscommon. The survey domains encompassed general information of individual's practice, current use of CDS and the practitioner's attitudes towards adoption of CDS-eP. Descriptive and inferential analyses were performed to analyse the data collected. Results The overall response rate was 37%. Nearly 92% of respondents employed electronic medical records in their practice. The majority acknowledged the value of electronic CDS in improving prescribing quality (71% and reducing prescribing errors (84%. Despite a high degree of unfamiliarity (73%, the practitioners were open to the use of CDS-eP (94% and willing to invest greater resources for its implementation (62%. Lack of a strategic implementation plan (78% is the main perceived barrier to the incorporation of CDS-eP into clinical practice, followed by i lack of financial incentives (70%, ii lack of standardized product software (61%, iii high sensitivity of drug-drug interaction or medication allergy markers (46%, iv concern about overriding physicians' prescribing decisions(44% and v lack of convincing evidence on the systems' effectiveness (22%. Conclusions Despite favourable attitudes towards the adoption of CDS-eP, multiple perceived barriers impede its incorporation into clinical practice. These merit further exploration, taking into consideration the structure of the Irish primary health care system, before CDS-eP can be recommended for routine

  17. Decision Support for Tactical Decision Making Under Stress

    Hutchins, Susan G.; Kelly, Richard T.; Morrison, Jeffrey G.


    A decision support system was designed for naval shipboard command-level decision makers to enhance decision making in a littoral environment or in any short-fused, ambiguous, decision making situation. Design of the prototype DSS was based on (1) an understanding of the cognitive strategies people bring to bear when dealing with the types of decisions required in tactical decision making, (2) applying human-system interface design principles which are expected t...

  18. Development of a clinical decision support system using genetic algorithms and Bayesian classification for improving the personalised management of women attending a colposcopy room.

    Bountris, Panagiotis; Topaka, Elena; Pouliakis, Abraham; Haritou, Maria; Karakitsos, Petros; Koutsouris, Dimitrios


    Cervical cancer (CxCa) is often the result of underestimated abnormalities in the test Papanicolaou (Pap test). The recent advances in the study of the human papillomavirus (HPV) infection (the necessary cause for CxCa development) have guided clinical practice to add HPV related tests alongside the Pap test. In this way, today, HPV DNA testing is well accepted as an ancillary test and it is used for the triage of women with abnormal findings in cytology. However, these tests are either highly sensitive or highly specific, and therefore none of them provides an optimal solution. In this Letter, a clinical decision support system based on a hybrid genetic algorithm - Bayesian classification framework is presented, which combines the results of the Pap test with those of the HPV DNA test in order to exploit the benefits of each method and produce more accurate outcomes. Compared with the medical tests and their combinations (co-testing), the proposed system produced the best receiver operating characteristic curve and the most balanced combination among sensitivity and specificity in detecting high-grade cervical intraepithelial neoplasia and CxCa (CIN2+). This system may support decision-making for the improved management of women who attend a colposcopy room following a positive test result. PMID:27382484

  19. Integrating clinical research into clinical decision making

    Mark R Tonelli


    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.

  20. Data-mining to build a knowledge representation store for clinical decision support. Studies on curation and validation based on machine performance in multiple choice medical licensing examinations.

    Robson, Barry; Boray, Srinidhi


    Extracting medical knowledge by structured data mining of many medical records and from unstructured data mining of natural language source text on the Internet will become increasingly important for clinical decision support. Output from these sources can be transformed into large numbers of elements of knowledge in a Knowledge Representation Store (KRS), here using the notation and to some extent the algebraic principles of the Q-UEL Web-based universal exchange and inference language described previously, rooted in Dirac notation from quantum mechanics and linguistic theory. In a KRS, semantic structures or statements about the world of interest to medicine are analogous to natural language sentences seen as formed from noun phrases separated by verbs, prepositions and other descriptions of relationships. A convenient method of testing and better curating these elements of knowledge is by having the computer use them to take the test of a multiple choice medical licensing examination. It is a venture which perhaps tells us almost as much about the reasoning of students and examiners as it does about the requirements for Artificial Intelligence as employed in clinical decision making. It emphasizes the role of context and of contextual probabilities as opposed to the more familiar intrinsic probabilities, and of a preliminary form of logic that we call presyllogistic reasoning. PMID:27089305

  1. Decision Support for effective production control

    Africa, E.; Nehzati, T.; Strandhagen, J.O.;


    This study aims to identify the actual needs of decision makers for decision support in the production control activity, considering the role and cognitive skills of human decision-makers in the decision-making process. Multiple case studies have been conducted in order to gain practical insights...... from the manufacturing industry. This paper contributes to raise the issues that should be considered for successful implementation of the decision support systems in practice....

  2. The limitations of using the existing TAM in adoption of clinical decision support system in hospitals: An empirical study in Malaysia

    Pouyan Esmaeilzadeh


    Full Text Available The technology acceptance model (TAM has been widely used to study user acceptance of new computer technologies. Previous studies claimed that future technology acceptance research should explore other additional explanatory variables, which may affect the originally proposed constructs of the TAM. The use of information technology in the health care sector and especially in hospitals offers great potential for improving the performance of physicians, increasing the quality of services and also reducing the organizational expenses. However, the main challenge that arises according to the literature is whether healthcare professionals are willing to adopt and use clinical information technology while performing their tasks. Although adoption of various information technologies has been studied using the technology acceptance model (TAM, the study of technology acceptance for professional groups (such as physicians has been limited. Physician adoption of clinical information technology is important for its successful implementation. Therefore, the purpose of this study is to gain a better insight about factors affecting physicians’ acceptance of clinical decision support systems (CDSS in a hospital setting. The results reflect the importance of perceived threat to professional autonomy, perceived interactivity with clinical IT, perceived usefulness and perceived ease of use in determining physicians’ intention to use CDSS.

  3. Developing public health clinical decision support systems (CDSS) for the outpatient community in New York City: our experience

    Singer Jesse; Anane Sheila; Taverna John; Amirfar Sam


    Abstract Background Developing a clinically relevant set of quality measures that can be effectively used by an electronic health record (EHR) is difficult. Whether it is achieving internal consensus on relevant priority quality measures, communicating to EHR vendors' whose programmers generally lack clinical contextual knowledge, or encouraging implementation of EHR that meaningfully impacts health outcomes, the path is challenging. However, greater transparency of population health, better ...

  4. Decision support telemedicine systems: A conceptual model and reusable templates

    B. Nannings; A. Abu-Hanna


    Decision support telemedicine systems (DSTSs) are systems combining elements from telemedicine and clinical decision support systems. Although emerging more, these types of systems have not been given much attention in the literature. Our objective is to define the term DSTS, to propose a general DS

  5. Intention to adopt clinical decision support systems in a developing country: effect of Physician’s perceived professional autonomy, involvement and belief: a cross-sectional study

    Sambasivan Murali


    Full Text Available Abstract Background Computer-based clinical decision support systems (CDSS are regarded as a key element to enhance decision-making in a healthcare environment to improve the quality of medical care delivery. The concern of having new CDSS unused is still one of the biggest issues in developing countries for the developers and implementers of clinical IT systems. The main objectives of this study are to determine whether (1 the physician’s perceived professional autonomy, (2 involvement in the decision to implement CDSS and (3 the belief that CDSS will improve job performance increase the intention to adopt CDSS. Four hypotheses were formulated and tested. Methods A questionnaire-based survey conducted between July 2010 and December 2010. The study was conducted in seven public and five private hospitals in Kuala Lumpur, Malaysia. Before contacting the hospitals, necessary permission was obtained from the Ministry of Health, Malaysia and the questionnaire was vetted by the ethics committee of the ministry. Physicians working in 12 hospitals from 10 different specialties participated in the study. The sampling method used was stratified random sampling and the physicians were stratified based on the specialty. A total of 450 physicians were selected using a random number generator. Each of these physicians was given a questionnaire and out of 450 questionnaires, 335 (response rate – 74% were returned and 309 (69% were deemed usable. Results The hypotheses were tested using Structural Equation Modeling (SEM. Salient results are: (1 Physicians’ perceived threat to professional autonomy lowers the intention to use CDSS (p Conclusion The proposed model with the three main constructs (physician’s professional characteristic, involvement and belief explains 47% of the variance in the intention to use CDSS. This is significantly higher than the models addressed so far. The results will have a major impact in implementing CDSS in developing

  6. Building a web-based tool to support clinical decisions in the control of Chlamydia trachomatis and Neisseria gonorrhoeae infections.

    Zhao, Kun; Qiu, Fasheng; Chen, Guantao


    Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (GC) are the agents of two common, sexually transmitted diseases afflicting women in the United States ( We designed a novel web-based application that offers simple recommendations to help optimize medical outcomes with CT and GC prevention and control programs. This application takes population groups, prevalence rates, parameters for available screening assays and treatment regimens (costs, sensitivity, and specificity), as well as budget limits as inputs. Its output suggests optimal screening and treatment strategies for selected at-risk groups, commensurate with the clinic's budget allocation. Development of this tool illustrates how a clinical informatics application based on rigorous mathematics might have a significant impact on real-world clinical issues. PMID:24564848

  7. Computer support of group decision making

    E.A. Trachtenherz


    In this paper we consider techniques of computer group decision making support. The interrelation of support methods, negotiation process type, and character of problems to be managed is shown. The structure of a computer-aided system supporting group decision making is offered, and some methods to support the course of negotiations using such systems are discussed.

  8. Platform decisions supported by gaming

    Hansen, Poul H. Kyvsgård; Mikkola, Juliana Hsuan


    these decisions can cause a high strategic risk. This paper describes and discusses the complexity of the platform decisions. We argue that new methods have to be introduced in order to create a comprehensive picture of the consequences of the platform decisions. One of the promising new methods is the...... application of on-line games in order to provide training for decision makers and in order to generate overview over the implications of platform decisions. However, games have to be placed in a context with other methods and we argue that a mixture of games, workshops, and simulations can provide improved...

  9. A Service-Oriented Architecture for Integrating Clinical Decision Support in a National E-Health System

    Wang, Jingyi


    With the help of appropriate IT support, health care services can be executed in a more effective and secure way. In Sweden, the NPÖ (National Patients’ Översikt) stands for National Patients’ Overview. It is a platform where authorized health care providers can access comprehensive and continuous information about health care and patients’ situation, based on which care providers can offer safe and qualified services. The NPÖ project is focusing on the information sharing phase. In order to ...

  10. Evaluation of Stream Mining Classifiers for Real-Time Clinical Decision Support System: A Case Study of Blood Glucose Prediction in Diabetes Therapy

    Simon Fong


    Full Text Available Earlier on, a conceptual design on the real-time clinical decision support system (rt-CDSS with data stream mining was proposed and published. The new system is introduced that can analyze medical data streams and can make real-time prediction. This system is based on a stream mining algorithm called VFDT. The VFDT is extended with the capability of using pointers to allow the decision tree to remember the mapping relationship between leaf nodes and the history records. In this paper, which is a sequel to the rt-CDSS design, several popular machine learning algorithms are investigated for their suitability to be a candidate in the implementation of classifier at the rt-CDSS. A classifier essentially needs to accurately map the events inputted to the system into one of the several predefined classes of assessments, such that the rt-CDSS can follow up with the prescribed remedies being recommended to the clinicians. For a real-time system like rt-CDSS, the major technological challenges lie in the capability of the classifier to process, analyze and classify the dynamic input data, quickly and upmost reliably. An experimental comparison is conducted. This paper contributes to the insight of choosing and embedding a stream mining classifier into rt-CDSS with a case study of diabetes therapy.

  11. Customer Decision Support Systems: Resources for Student Decision Making

    Cara Okleshen Peters; David A. Bradbard; Mary C. Martin


    This paper highlights the potential of customer decision support systems (CDSS) to assist students in education-related decision making. Faculty can use these resources to more effectively advise students on various elements of college life, while students can employ them to more actively participate in their own learning and improve their academic experience. This conceptual paper summarizes consumer decision support systems (CDSS) concepts and presents exemplar websites students could utili...

  12. Integration of Rule Based Expert Systems and Case Based Reasoning in an Acute Bacterial Meningitis Clinical Decision Support System

    Cabrera, Mariana Maceiras


    This article presents the results of the research carried out on the development of a medical diagnostic system applied to the Acute Bacterial Meningitis, using the Case Based Reasoning methodology. The research was focused on the implementation of the adaptation stage, from the integration of Case Based Reasoning and Rule Based Expert Systems. In this adaptation stage we use a higher level RBC that stores and allows reutilizing change experiences, combined with a classic rule-based inference engine. In order to take into account the most evident clinical situation, a pre-diagnosis stage is implemented using a rule engine that, given an evident situation, emits the corresponding diagnosis and avoids the complete process.

  13. Treatment process - Clinical decision making

    Full text: Although many aspects of cancer treatment, especially the technical aspects of radiotherapy, are subject to rigorous quality assurance, the quality of actual clinical decision making is rarely scrutinized. There are several developments over the past 10 to 15 years that have driven forward attempts in the UK National Health Service (NHS) to bring such quality assurance into the clinic. This goes back to the work of Dr. Archie Cochrane in the 1970s and his views that clinical practice should be underpinned by research evidence and only treatments that have been shown to be effective should be used. The term clinical effectiveness is now widely used. It refers to the amount by which any treatment actually affects outcomes for patients. For cancer patients this may mean 'cure', improving survival, local control, or symptoms, or minimizing toxicity - or indeed a combination of all of them. But how do we know what is the most effective treatment for a particular patient? How do we assure the quality of the clinical decision? By going to the research evidence and asking questions about whether there is clear evidence which treatment is likely to give the best outcome for this patient. This is 'evidence-based medicine': the application of the best available evidence from clinical care research to the management of individual patients. However this is not just a blind application of this evidence and is not 'cookbook medicine'. Other things need to be considered as well as the evidence, a clinical judgement about the applicability of any treatment to an individual patient and patient preference. When confronted by a patient with a clinical problem, how do we find the 'best' evidence? 1. Refine the clinical question into a standard format: patient, intervention, comparison, and outcomes (PICO) 2. Search for relevant publications in electronic databases, such as Pubmed and Medline, and retrieve them 3. Critically read and appraise them: Are they relevant to this

  14. Uncertainty modeling and decision support

    We first formulate the problem of decision making under uncertainty. The importance of the representation of our knowledge about the uncertainty in formulating a decision process is pointed out. We begin with a brief discussion of the case of probabilistic uncertainty. Next, in considerable detail, we discuss the case of decision making under ignorance. For this case the fundamental role of the attitude of the decision maker is noted and its subjective nature is emphasized. Next the case in which a Dempster-Shafer belief structure is used to model our knowledge of the uncertainty is considered. Here we also emphasize the subjective choices the decision maker must make in formulating a decision function. The case in which the uncertainty is represented by a fuzzy measure (monotonic set function) is then investigated. We then return to the Dempster-Shafer belief structure and show its relationship to the fuzzy measure. This relationship allows us to get a deeper understanding of the formulation the decision function used Dempster- Shafer framework. We discuss how this deeper understanding allows a decision analyst to better make the subjective choices needed in the formulation of the decision function

  15. Physicians’ use of computerized clinical decision supports to improve medication management in the elderly – the Seniors Medication Alert and Review Technology intervention

    Alagiakrishnan K


    Full Text Available Kannayiram Alagiakrishnan,1 Patricia Wilson,2 Cheryl A Sadowski,3 Darryl Rolfson,1 Mark Ballermann,4,5 Allen Ausford,6,7 Karla Vermeer,7 Kunal Mohindra,8 Jacques Romney,9 Robert S Hayward10 1Department of Medicine, Division of Geriatric Medicine, 2Department of Medicine, 3Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, 4Chief Medical Information Office, Alberta Health Services, 5Division of Critical Care, Department of Medicine, University of Alberta, 6Department of Family Medicine, University of Alberta, 7Lynwood Family Physician, 8eClinician EMR, Alberta Health Services-Information Systems, 9Department of Medicine, Division of Endocrinology, 10Division of General Internal Medicine, University of Alberta, Edmonton, AB, Canada Background: Elderly people (aged 65 years or more are at increased risk of polypharmacy (five or more medications, inappropriate medication use, and associated increased health care costs. The use of clinical decision support (CDS within an electronic medical record (EMR could improve medication safety.Methods: Participatory action research methods were applied to preproduction design and development and postproduction optimization of an EMR-embedded CDS implementation of the Beers’ Criteria for medication management and the Cockcroft–Gault formula for estimating glomerular filtration rates (GFR. The “Seniors Medication Alert and Review Technologies” (SMART intervention was used in primary care and geriatrics specialty clinics. Passive (chart messages and active (order-entry alerts prompts exposed potentially inappropriate medications, decreased GFR, and the possible need for medication adjustments. Physician reactions were assessed using surveys, EMR simulations, focus groups, and semi-structured interviews. EMR audit data were used to identify eligible patient encounters, the frequency of CDS events, how alerts were managed, and when evidence links were followed.Results: Analysis of

  16. A Contemplation of Training Decision Support System

    P.Kalpana,; Dr . T . Bhuvaneswari


    This research paper presents a role of decision support system in Human Resource Training Systems. A deep understanding of the knowledge hidden in Human Resource (HR) data is vital to a firm's competitive position and organizational decision making. The HR data is usually treated to answer queries. Training Decision Support System (TDSS) data primarily concerns Transactional process and Executive support system is used to retrieve data from the system, recording it for future purposes. The pa...

  17. Financial Decision Making Support System

    Lobanova, E. N.; Zmitrovich, A. I.; Voshevoz, A. A.; Krivko-Krasko, A. V.


    In this article we consider concepts and components of the Financial Decision Making System that is being developed in the Institute of Business and Management Technology, BSU. Such system can be successfully used either for training experts in financial analytics and financial management or for financial managers and financial directors in an enterprise for the effective financial decision making.

  18. Fertility and contraceptive decision-making and support for HIV infected individuals: client and provider experiences and perceptions at two HIV clinics in Uganda

    Wanyenze Rhoda K


    Full Text Available Abstract Background Some people living with HIV/AIDS (PLHIV want to have children while others want to prevent pregnancies; this calls for comprehensive services to address both needs. This study explored decisions to have or not to have children and contraceptive preferences among PLHIV at two clinics in Uganda. Methods This was a qualitative cross-sectional study. We conducted seventeen focus group discussions and 14 in-depth interviews with sexually active adult men and women and adolescent girls and boys, and eight key informant interviews with providers. Overall, 106 individuals participated in the interviews; including 84 clients through focus group discussions. Qualitative latent content analysis technique was used, guided by key study questions and objectives. A coding system was developed before the transcripts were examined. Codes were grouped into categories and then themes and subthemes further identified. Results In terms of contraceptive preferences, clients had a wide range of preferences; whereas some did not like condoms, pills and injectables, others preferred these methods. Fears of complications were raised mainly about pills and injectables while cost of the methods was a major issue for the injectables, implants and intrauterine devices. Other than HIV sero-discordance and ill health (which was cited as transient, the decision to have children or not was largely influenced by socio-cultural factors. All adult men, women and adolescents noted the need to have children, preferably more than one. The major reasons for wanting more children for those who already had some were; the sex of the children (wanting to have both girls and boys and especially boys, desire for large families, pressure from family, and getting new partners. Providers were supportive of the decision to have children, especially for those who did not have any child at all, but some clients cited negative experiences with providers and information gaps for

  19. Risk-based emergency decision support

    In the present paper we discuss how to assist critical decisions taken under complex, contingent circumstances, with a high degree of uncertainty and short time frames. In such sharp-end decision regimes, standard rule-based decision support systems do not capture the complexity of the situation. At the same time, traditional risk analysis is of little use due to variability in the specific circumstances. How then, can an organisation provide assistance to, e.g. pilots in dealing with such emergencies? A method called 'contingent risk and decision analysis' is presented, to provide decision support for decisions under variable circumstances and short available time scales. The method consists of nine steps of definition, modelling, analysis and criteria definition to be performed 'off-line' by analysts, and procedure generation to transform the analysis result into an operational decision aid. Examples of pilots' decisions in response to sudden vibration in offshore helicopter transport method are used to illustrate the approach


    Boghean Florin


    Full Text Available Generalised uncertainty, a phenomenon that today’s managers are facing as part of their professional experience, makes it impossible to anticipate the way the business environment will evolve or what will be the consequences of the decisions they plan to implement. Any decision making process within the company entails the simultaneous presence of a number of economic, technical, juridical, human and managerial variables. The development and the approval of a decision is the result of decision making activities developed by the decision maker and sometimes by a decision support team or/and a decision support system (DSS. These aspects related to specific applications of decision support systems in risk management will be approached in this research paper. Decisions in general and management decisions in particular are associated with numerous risks, due to their complexity and increasing contextual orientation. In each business entity, there are concerns with the implementation of risk management in order to improve the likelihood of meeting objectives, the trust of the parties involved, increase the operational safety and security as well as the protection of the environment, minimise losses, improve organisational resilience in order to diminish the negative impact on the organisation and provide a solid foundation for decision making. Since any business entity is considered to be a wealth generator, the analysis of their performance should not be restricted to financial efficiency alone, but will also encompass their economic efficiency as well. The type of research developed in this paper entails different dimensions: conceptual, methodological, as well as empirical testing. Subsequently, the conducted research entails a methodological side, since the conducted activities have resulted in the presentation of a simulation model that is useful in decision making processes on the capital market. The research conducted in the present paper

  1. A pragmatic study exploring the prevention of delirium among hospitalized older hip fracture patients: Applying evidence to routine clinical practice using clinical decision support

    Schmaltz Heidi N


    Full Text Available Abstract Delirium occurs in up to 65% of older hip fracture patients. Developing delirium in hospital has been associated with a variety of adverse outcomes. Trials have shown that multi-component preventive interventions can lower delirium rates. The objective of this study was to implement and evaluate the effectiveness of an evidence-based electronic care pathway, which incorporates multi-component delirium strategies, among older hip fracture patients. We conducted a pragmatic study using an interrupted time series design in order to evaluate the use and impact of the intervention. The target population was all consenting patients aged 65 years or older admitted with an acute hip fracture to the orthopedic units at two Calgary, Alberta hospitals. The primary outcome was delirium rates. Secondary outcomes included length of hospital stay, in-hospital falls, in-hospital mortality, new discharges to long-term care, and readmissions. A Durbin Watson test was conducted to test for serial correlation and, because no correlation was found, Chi-square statistics, Wilcoxon test and logistic regression analyses were conducted as appropriate. At study completion, focus groups were conducted at each hospital to explore issues around the use of the order set. During the 40-week study period, 134 patients were enrolled. The intervention had no effect on the overall delirium rate (33% pre versus 31% post; p = 0.84. However, there was a significant interaction between study phase and hospital (p = 0.03. Although one hospital did not experience a decline in delirium rate, the delirium rate at the other hospital declined from 42% to 19% (p = 0.08. This difference by hospital was mirrored in focus group feedback. The hospital that experienced a decline in delirium rates was more supportive of the intervention. Overall, post-intervention there were no significant differences in mean length of stay (12 days post versus 14 days pre; p = 0.74, falls (6% post

  2. Economic aspects of clinical decision making: applications of clinical decision analysis.

    Crane, V S


    Clinical decision analysis as a basic tool for decision making is described, and potential applications of decision analysis in six areas of clinical practice are identified. Clinical decision analysis is a systematic method of describing clinical problems in a quantitative fashion, identifying possible courses of action, assessing the probability and value of outcomes, and then making a calculation to select the ultimate course of action. Clinical decision analysis provides a structure for clinical decision problems, helps clarify medical controversies, and encourages decision makers to speak a common language. Applications of clinical decision analysis in the areas of diagnostic testing, patient management, product and program selection, research and education, patient preferences, and health-care-policy evaluation are described. Decision analysis offers health professionals a tool for making quantifiable, cost-effective clinical decisions, especially in terms of clinical outcomes. PMID:3285672

  3. Implementation pearls from a new guidebook on improving medication use and outcomes with clinical decision support. Effective CDS is essential for addressing healthcare performance improvement imperatives.

    Sirajuddin, Anwar M; Osheroff, Jerome A; Sittig, Dean F; Chuo, John; Velasco, Ferdinand; Collins, David A


    Effective clinical decision support (CDS) is essential for addressing healthcare performance improvement imperatives, but care delivery organizations (CDO) typically struggle with CDS deployment. Ensuring safe and effective medication delivery to patients is a central focus of CDO performance improvement efforts, and this article provides an overview of best-practice strategies for applying CDS to these goals. The strategies discussed are drawn from a new guidebook, co-published and co-sponsored by more than a dozen leading organizations. Developed by scores of CDS implementers and experts, the guidebook outlines key steps and success factors for applying CDS to medication management. A central thesis is that improving outcomes with CDS interventions requires that the CDS five rights be addressed successfully. That is, the interventions must deliver the right information, to the right person, in the right format, through the right channel, at the right point in workflow. This paper provides further details about these CDS five rights, and highlights other important strategies for successful CDS programs. PMID:19894486

  4. Decision support in supervisory control

    It is argued that the supervisory control of complex industrial processes having a potential for serious consequences in case of accidents requires careful consideration of the allocation of decision making between the three main agents of control; namely the designer, the operator and the automatic control system. In particular, it is advocated that instead of continuing their efforts to make their preplanning of responses and countermeasures more and more complete and restricting the operator's initiative, designers should take advantage of modern information technology to make available to the operators their conceptual models and their processing resources so as to allow the operators to function as their extended arm in coping with the plant. Such an interactive decision making activity would thus benefit from this simultaneous availability of the design basis, up-to-date knowledge of plant status and accumualted operational experience. (author)

  5. Using Visualization in Cockpit Decision Support Systems

    Aragon, Cecilia R.


    In order to safely operate their aircraft, pilots must makerapid decisions based on integrating and processing large amounts ofheterogeneous information. Visual displays are often the most efficientmethod of presenting safety-critical data to pilots in real time.However, care must be taken to ensure the pilot is provided with theappropriate amount of information to make effective decisions and notbecome cognitively overloaded. The results of two usability studies of aprototype airflow hazard visualization cockpit decision support systemare summarized. The studies demonstrate that such a system significantlyimproves the performance of helicopter pilots landing under turbulentconditions. Based on these results, design principles and implicationsfor cockpit decision support systems using visualization arepresented.

  6. Decision support, analytics, and business intelligence

    Power, Daniel J


    Competition is becoming more intense and decision makers are encountering increasing complexity, rapid change, and higher levels of risk. In many situations, the solution is more and better computerized decision support, especially analytics and business intelligence. Today managers need to learn about and understand computerized decision support. If a business is to succeed, managers must know much more about information technology solutions. This second edition of a powerful introductory book is targeted at busy managers and MBA students who need to grasp the basics of computerized decision

  7. Indonesian Earthquake Decision Support System

    Warnars, Spits


    Earthquake DSS is an information technology environment which can be used by government to sharpen, make faster and better the earthquake mitigation decision. Earthquake DSS can be delivered as E-government which is not only for government itself but in order to guarantee each citizen's rights for education, training and information about earthquake and how to overcome the earthquake. Knowledge can be managed for future use and would become mining by saving and maintain all the data and infor...

  8. Decision support for utility environmental risk management

    This paper reviews a number of decision support methods developed and applied by Decision Focus Incorporated to help utility personnel manage current environmental problems. This work has been performed for the Environmental Risk Analysis Program of EPRI's Environment Division, and also for a number of electric utilities across the country. These are two distinct types of decision support software tools that have been created: economic risk management and environmental risk analysis. These types differ primarily in the identification of who will make a decision. Economic risk management tools are directed primarily at decisions made by electric utilities. Environmental risk analysis tools are directed primarily at decisions made by legislative or regulatory agencies, about which a utility may wish to comment

  9. General practitioners' and nurses' experiences of using computerised decision support in screening for diabetic foot disease: implementing Scottish Clinical Information - Diabetes Care in routine clinical practice

    Fay Crawford


    Conclusions Adoption of the SCI-DC foot assessment tool in primary care is not perceived as clinically necessary. Although information recorded by specialist services on SCI-DC is helpful, important structural barriers to its implementation mean the potential benefits associated with its use are unlikely to be realised; greater engagement with primary care priorities for diabetes management is needed to assist its successful implementation and adoption.


    Rok Rupnik; Matjaž Kukar


    Traditional techniques of data analysis do not enable the solution of all kind of problems and for that reason they have become insufficient. This caused a newinterdisciplinary field of data mining to arise, encompassing both classical statistical, and modern machine learning techniques to support the data analysis and knowledge discovery from data. Data mining methods are powerful in dealing with large quantities of data, but on the other hand they are difficult to master by business users t...

  11. Examining perceptions of the usefulness and usability of a mobile-based system for pharmacogenomics clinical decision support: a mixed methods study.

    Blagec, Kathrin; Romagnoli, Katrina M; Boyce, Richard D; Samwald, Matthias


    Background. Pharmacogenomic testing has the potential to improve the safety and efficacy of pharmacotherapy, but clinical application of pharmacogenetic knowledge has remained uncommon. Clinical Decision Support (CDS) systems could help overcome some of the barriers to clinical implementation. The aim of this study was to evaluate the perception and usability of a web- and mobile-enabled CDS system for pharmacogenetics-guided drug therapy-the Medication Safety Code (MSC) system-among potential users (i.e., physicians and pharmacists). Furthermore, this study sought to collect data on the practicability and comprehensibility of potential layouts of a proposed personalized pocket card that is intended to not only contain the machine-readable data for use with the MSC system but also human-readable data on the patient's pharmacogenomic profile. Methods. We deployed an emergent mixed methods design encompassing (1) qualitative interviews with pharmacists and pharmacy students, (2) a survey among pharmacogenomics experts that included both qualitative and quantitative elements and (3) a quantitative survey among physicians and pharmacists. The interviews followed a semi-structured guide including a hypothetical patient scenario that had to be solved by using the MSC system. The survey among pharmacogenomics experts focused on what information should be printed on the card and how this information should be arranged. Furthermore, the MSC system was evaluated based on two hypothetical patient scenarios and four follow-up questions on the perceived usability. The second survey assessed physicians' and pharmacists' attitude towards the MSC system. Results. In total, 101 physicians, pharmacists and PGx experts coming from various relevant fields evaluated the MSC system. Overall, the reaction to the MSC system was positive across all investigated parameters and among all user groups. The majority of participants were able to solve the patient scenarios based on the

  12. Evaluation of selected environmental decision support software

    Decision Support Software (DSS) continues to be developed to support analysis of decisions pertaining to environmental management. Decision support systems are computer-based systems that facilitate the use of data, models, and structured decision processes in decision making. The optimal DSS should attempt to integrate, analyze, and present environmental information to remediation project managers in order to select cost-effective cleanup strategies. The optimal system should have a balance between the sophistication needed to address the wide range of complicated sites and site conditions present at DOE facilities, and ease of use (e.g., the system should not require data that is typically unknown and should have robust error checking of problem definition through input, etc.). In the first phase of this study, an extensive review of the literature, the Internet, and discussions with sponsors and developers of DSS led to identification of approximately fifty software packages that met the preceding definition

  13. Geospatial decision support systems for societal decision making

    Bernknopf, R.L.


    While science provides reliable information to describe and understand the earth and its natural processes, it can contribute more. There are many important societal issues in which scientific information can play a critical role. Science can add greatly to policy and management decisions to minimize loss of life and property from natural and man-made disasters, to manage water, biological, energy, and mineral resources, and in general, to enhance and protect our quality of life. However, the link between science and decision-making is often complicated and imperfect. Technical language and methods surround scientific research and the dissemination of its results. Scientific investigations often are conducted under different conditions, with different spatial boundaries, and in different timeframes than those needed to support specific policy and societal decisions. Uncertainty is not uniformly reported in scientific investigations. If society does not know that data exist, what the data mean, where to use the data, or how to include uncertainty when a decision has to be made, then science gets left out -or misused- in a decision making process. This paper is about using Geospatial Decision Support Systems (GDSS) for quantitative policy analysis. Integrated natural -social science methods and tools in a Geographic Information System that respond to decision-making needs can be used to close the gap between science and society. The GDSS has been developed so that nonscientists can pose "what if" scenarios to evaluate hypothetical outcomes of policy and management choices. In this approach decision makers can evaluate the financial and geographic distribution of potential policy options and their societal implications. Actions, based on scientific information, can be taken to mitigate hazards, protect our air and water quality, preserve the planet's biodiversity, promote balanced land use planning, and judiciously exploit natural resources. Applications using the

  14. Indonesian Earthquake Decision Support System

    Warnars, Spits


    Earthquake DSS is an information technology environment which can be used by government to sharpen, make faster and better the earthquake mitigation decision. Earthquake DSS can be delivered as E-government which is not only for government itself but in order to guarantee each citizen's rights for education, training and information about earthquake and how to overcome the earthquake. Knowledge can be managed for future use and would become mining by saving and maintain all the data and information about earthquake and earthquake mitigation in Indonesia. Using Web technology will enhance global access and easy to use. Datawarehouse as unNormalized database for multidimensional analysis will speed the query process and increase reports variation. Link with other Disaster DSS in one national disaster DSS, link with other government information system and international will enhance the knowledge and sharpen the reports.

  15. A Geospatial Decision Support System Toolkit Project

    National Aeronautics and Space Administration — We propose to design a working prototype Geospatial Decision Support Toolkit (GeoKit) that will enable scientists, agencies, and stakeholders to configure and...

  16. Solutions for decision support in university management

    Andrei STANCIU; Mihai FLORIN; Cristina RÃDULESCU; Ofelia ALECA


    The paper proposes an overview of decision support systems in order to define the role of a system to assist decision in university management. The authors present new technologies and the basic concepts of multidimensional data analysis using models of business processes within the universities. Based on information provided by scientific literature and on the authors’ experience, the study aims to define selection criteria in choosing a development environment for designing a support system...

  17. A Marketing Decision Support System for Retailers

    Leonard M. Lodish


    A decision support system for planning marketing strategies and allocating resources for a multi-store retailer is described. This decision support system combines well-known model building and analysis methodology, sophisticated computer software, and attention to management's implementation needs in order to apply management science thinking to messy, high level strategy and forecasting problems. The system consists of a planning model, national campaign evaluation system, experimental anal...

  18. Marketing Decision Support Systemen in kort bestek

    Campen, van, P.F.A.M.; Huizingh, K.R.E.; Oude Ophuis, P.A.M.; Wierenga, Berend


    textabstractVoor u liggen de uitkomsten van een onderzoek over marketing decision support systemen bij Nederlandse bedrijven. Bij marketing decision support systemen worden de mogelijkbeden die de moderne informaticatechnologie biedt, aangewend ten behoeve van het marketing management. Door de toename en internationalisering van de concurrentie, door de snelle veranderingen in distributiekanalen en door het steeds hoger wordende tempo van produktvernieuwing (en veroudering) worden dergelijke ...

  19. Solutions for decision support in university management

    Andrei STANCIU


    Full Text Available The paper proposes an overview of decision support systems in order to define the role of a system to assist decision in university management. The authors present new technologies and the basic concepts of multidimensional data analysis using models of business processes within the universities. Based on information provided by scientific literature and on the authors’ experience, the study aims to define selection criteria in choosing a development environment for designing a support system dedicated to university management. The contributions consist in designing a data warehouse model and models of OLAP analysis to assist decision in university management.

  20. Evaluating Ethical Responsibility in Inverse Decision Support

    Ahmad M. Kabil


    Full Text Available Decision makers have considerable autonomy on how they make decisions and what type of support they receive. This situation places the DSS analyst in a different relationship with the client than his colleagues who support regular MIS applications. This paper addresses an ethical dilemma in “Inverse Decision Support,” when the analyst supports a decision maker who requires justification for a preconceived selection that does not correspond to the best option that resulted from the professional resolution of the problem. An extended application of the AHP model is proposed for evaluating the ethical responsibility in selecting a suboptimal alternative. The extended application is consistent with the Inverse Decision Theory that is used extensively in medical decision making. A survey of decision analysts is used to assess their perspective of using the proposed extended application. The results show that 80% of the respondents felt that the proposed extended application is useful in business practices. 14% of them expanded the usability of the extended application to academic teaching of the ethics theory. The extended application is considered more usable in a country with a higher Transparency International Corruption Perceptions Index (TICPI than in a country with a lower one.

  1. Legal Considerations in Clinical Decision Making.

    Ursu, Samuel C.


    Discussion of legal issues in dental clinical decision making looks at the nature and elements of applicable law, especially malpractice, locus of responsibility, and standards of care. Greater use of formal decision analysis in clinical dentistry and better research on diagnosis and treatment are recommended, particularly in light of increasing…

  2. Group decision support using Toulmin argument structures

    Janssen, T. [Argonne National Lab., IL (United States)]|[George Mason Univ., Fairfax, VA (United States). School of Information Technology and Engineering; Sage, A.P. [George Mason Univ., Fairfax, VA (United States). School of Information Technology and Engineering


    This paper addresses the need for sound science, technology, and management assessment relative to environmental policy decision making through an approach that involves a logical structure for evidence, a framed decision-making process, and an environment that encourages group participation. Toulmin-based logic possesses these characteristics and is used as the basis for development of a group decision support system. This system can support several user groups, such as pesticide policy-making experts, who can use the support system to state arguments for or against an important policy issue, and pest management experts, who can use the system to assist in identifying and evaluating alternatives for controlling pests on agricultural commodities. The resulting decision support system assists in improving the clarity of the lines of reasoning used in specific situations; the warrants, grounds, and backings that are used to support claims and specific lines of reasoning; and the contradictions, rebuttals, and arguments surrounding each step in the reasoning process associated with evaluating a claim or counterclaim. Experts and decisions makers with differing views can better understand each other`s thought processes. The net effect is enhanced communications and understanding of the whole picture and, in many cases, consensus on decisions to be taken.

  3. Designing Colorectal Cancer Screening Decision Support: A Cognitive Engineering Enterprise

    Militello, Laura G.; Saleem, Jason J.; Borders, Morgan R.; Sushereba, Christen E.; Haverkamp, Donald; Wolf, Steven P.; Doebbeling, Bradley N.


    Adoption of clinical decision support has been limited. Important barriers include an emphasis on algorithmic approaches to decision support that do not align well with clinical work flow and human decision strategies, and the expense and challenge of developing, implementing, and refining decision support features in existing electronic health records (EHRs). We applied decision-centered design to create a modular software application to support physicians in managing and tracking colorectal cancer screening. Using decision-centered design facilitates a thorough understanding of cognitive support requirements from an end user perspective as a foundation for design. In this project, we used an iterative design process, including ethnographic observation and cognitive task analysis, to move from an initial design concept to a working modular software application called the Screening & Surveillance App. The beta version is tailored to work with the Veterans Health Administration’s EHR Computerized Patient Record System (CPRS). Primary care providers using the beta version Screening & Surveillance App more accurately answered questions about patients and found relevant information more quickly compared to those using CPRS alone. Primary care providers also reported reduced mental effort and rated the Screening & Surveillance App positively for usability. PMID:26973441

  4. Email recruitment to use web decision support tools for pneumonia.

    Flanagan, James R.; Peterson, Michael; Dayton, Charles; Strommer Pace, Lori; Plank, Andrew; Walker, Kristy; Carlson, William S.


    Application of guidelines to improve clinical decisions for Community Acquired Pneumonia (CAP) patients depends on accurate information about specific facts of each case and on presenting guideline support at the time decisions are being made. We report here on a system designed to solicit information from physicians about their CAP patients in order to classify CAP and present appropriate guidelines for type of care, length of stay, and use of antibiotics. We used elements of three existing ...


    Harmandeep Singh; Nitika Sharma


    A decision support system for precision farming is designed to assist farmers, agricultural experts, research workers or any intellectuals with guidance in making various farming related decisions and help them to access, display and analyze data that have geographic content and meaning. The concept of precision farming is not only related with the use of technologies but it is also about the five R’s that is use of right input (nutrients, water, fertilizer, money, machinery etc.), at the rig...

  6. Biometric and intelligent decision making support

    Kaklauskas, Arturas


    This book presents different methods for analyzing the body language (movement, position, use of personal space, silences, pauses and tone, the eyes, pupil dilation or constriction, smiles, body temperature and the like) for better understanding people’s needs and actions, including biometric data gathering and reading. Different studies described in this book indicate that sufficiently much data, information and knowledge can be gained by utilizing biometric technologies. This is the first, wide-ranging book that is devoted completely to the area of intelligent decision support systems, biometrics technologies and their integrations. This book is designated for scholars, practitioners and doctoral and master’s degree students in various areas and those who are interested in the latest biometric and intelligent decision making support problems and means for their resolutions, biometric and intelligent decision making support systems and the theory and practice of their integration and the opportunities fo...

  7. Decision support for health care: the PROforma evidence base

    John Fox


    Full Text Available Cancer Research UK has developed PROforma, a formal language for modelling clinical processes, along with associated tools for creating decision support, care planning, clinical workflow management and other applications. The PROforma method has been evaluated in a variety of settings: in primary health care (prescribing, referral of suspected cancer patients, genetic risk assessment and in specialist care of patients with breast cancer, leukaemia, HIV infection and other conditions. About nine years of experience have been gained with PROforma technologies. Seven trials of decision support applications have been published or are in preparation. Each of these has shown significant positive effects on a variety of measures of quality and/or outcomes of care. This paper reviews the evidence base for the clinical effectiveness of these PROforma applications, and previews the CREDO project _a multi-centre trial of a complex PROforma application for supporting integrated breast cancer care across primary and secondary care settings.

  8. Clinical Decision Making of Rural Novice Nurses

    Seright, Teresa J.


    The purpose of this study was to develop substantive theory regarding decision making by the novice nurse in a rural hospital setting. Interviews were guided by the following research questions: What cues were used by novice rural registered nurses in order to make clinical decisions? What were the sources of feedback which influenced subsequent…

  9. Transferring Decision Support Concepts to Evaluation.

    Sauter, Vicki L.; Mandell, Marvin B.


    Use of decision support systems (DSS) to increase the utilization of management science models and accounting information is discussed. It is argued that application of the conceptual foundations of DSS to evaluation and other forms of applied social research is an effective means of increasing evaluation utilization by policymakers. (TJH)

  10. Fault Isolation for Shipboard Decision Support

    Lajic, Zoran; Blanke, Mogens; Nielsen, Ulrik Dam


    Fault detection and fault isolation for in-service decision support systems for marine surface vehicles will be presented in this paper. The stochastic wave elevation and the associated ship responses are modeled in the frequency domain. The paper takes as an example fault isolation of a containe...

  11. Text summarization as a decision support aid

    Workman T


    Full Text Available Abstract Background PubMed data potentially can provide decision support information, but PubMed was not exclusively designed to be a point-of-care tool. Natural language processing applications that summarize PubMed citations hold promise for extracting decision support information. The objective of this study was to evaluate the efficiency of a text summarization application called Semantic MEDLINE, enhanced with a novel dynamic summarization method, in identifying decision support data. Methods We downloaded PubMed citations addressing the prevention and drug treatment of four disease topics. We then processed the citations with Semantic MEDLINE, enhanced with the dynamic summarization method. We also processed the citations with a conventional summarization method, as well as with a baseline procedure. We evaluated the results using clinician-vetted reference standards built from recommendations in a commercial decision support product, DynaMed. Results For the drug treatment data, Semantic MEDLINE enhanced with dynamic summarization achieved average recall and precision scores of 0.848 and 0.377, while conventional summarization produced 0.583 average recall and 0.712 average precision, and the baseline method yielded average recall and precision values of 0.252 and 0.277. For the prevention data, Semantic MEDLINE enhanced with dynamic summarization achieved average recall and precision scores of 0.655 and 0.329. The baseline technique resulted in recall and precision scores of 0.269 and 0.247. No conventional Semantic MEDLINE method accommodating summarization for prevention exists. Conclusion Semantic MEDLINE with dynamic summarization outperformed conventional summarization in terms of recall, and outperformed the baseline method in both recall and precision. This new approach to text summarization demonstrates potential in identifying decision support data for multiple needs.

  12. Comparison of Accuracies for Image-based 1.5T and 3T MRI Using a Clinical Decision Support System Driven by a Support Vector Machine to Detect Seminal Vesicle Invasion of Prostate Cancer

    The purpose of this study is to develop image-based clinical decision support systems (CDSSs) using support vector machine models (SVMs) for the detection of seminal vesicle invasion (SVI) of prostate cancer and to compare the accuracies of 1.5T and 3.0T MR CDSSs. A total of 548 prostate cancer patients who underwent a prostatectomy and preoperative MR using 1.5T or 3.0T were enrolled in this study. Each 1.5T and 3.0T group was subdivided into the training group and test group, arbitrarily. Images were analyzed in consensus by two radiologists. CDSS was constructed with input data that has the appearance of a seminal vesicle, PSA level and age in each training group, and with the output data of the probability for SVI using SVMs. The accuracy of the output data were evaluated with data of each test group. After a histopathologic correlation, the sensitivity, specificity and accuracy for the detection of SVI were compared in both 1.5T and 3.0T. For the diagnosis of SVI, the specificity and the accuracy of the 3.0T model were all statistically superior to those of the 1.5T model (90.4% vs. 73.1%; 88.7% vs. 74.6%) (p<0.05). The image-based CDSS for the detection of SVI was successfully constructed using SVM. According to our CDSSs, the specificity and accuracy of 3.0T were superior to those of 1.5T

  13. Decision support tools for policy and planning

    A decision support system (DSS) is being developed at the Radioactive Liquid Waste Treatment Facility, Los Alamos National Laboratory (LANL). The DSS will be used to evaluate alternatives for improving LANL's existing central radioactive waste water treatment plant and to evaluate new site-wide liquid waste treatment schemes that are required in order to handle the diverse waste streams produced at LANL. The decision support system consists of interacting modules that perform the following tasks: rigorous process simulation, configuration management, performance analysis, cost analysis, risk analysis, environmental impact assessment, transportation modeling, and local, state, and federal regulation compliance checking. Uncertainty handling techniques are used with these modules and also with a decision synthesis module which combines results from the modules listed above. We believe the DSS being developed can be applied to almost any other industrial water treatment facility with little modification because in most situations the waste streams are less complex, fewer regulations apply, and the political environment is simpler. The techniques being developed are also generally applicable to policy and planning decision support systems in the chemical process industry

  14. Comparison of Alternative Processes for Support Decisions

    Manuel Martínez-Álvarez


    Full Text Available There are many tasks that revolve around combinatorial analysis problems, same tasks found in Decision Support Systems (DSS as most of these are responsible for assessing a number of possibilities to deliver the best options. Within the analysis of possible solutions is performed by the DSS there are alternative procedures inside the engine for making decisions that involve them. As part of these alternative procedures today has highlighted the use of metaheuristics, thus in this paper we propose a comparison of some of them trying to broaden the spectrum we have for the applications nowadays.

  15. Using Information Aggregation Markets for Decision Support

    Patrick Buckley


    Full Text Available Information Aggregation Markets, often referred to as prediction markets, are markets that are designed to aggregate information from a disparate pool of human individuals to make predictions about the likely outcome of future uncertain events. This paper looks at how Information Aggregation Markets can be incorporated into the standard body of decision making theory. It examines how Information Aggregation Markets can be used as decision support systems, and provides empirical evidence from a wide variety of sources as to the effectiveness and practicality of Information Aggregation Markets. Finally, this paper details some future research questions to be addressed in the area of Information Aggregation Markets.

  16. Tsunami early warning and decision support

    Steinmetz, T.; Raape, U.; Teßmann, S.; Strobl, C.; Friedemann, M.; Kukofka, T.; Riedlinger, T.; Mikusch, E.; Dech, S.


    An innovative newly developed modular and standards based Decision Support System (DSS) is presented which forms part of the German Indonesian Tsunami Early Warning System (GITEWS). The GITEWS project stems from the effort to implement an effective and efficient Tsunami Early Warning and Mitigation System for the coast of Indonesia facing the Sunda Arc along the islands of Sumatra, Java and Bali. The geological setting along an active continental margin which is very close to densely populated areas is a particularly difficult one to cope with, because potential tsunamis' travel times are thus inherently short. National policies require an initial warning to be issued within the first five minutes after an earthquake has occurred. There is an urgent requirement for an end-to-end solution where the decision support takes the entire warning chain into account. The system of choice is based on pre-computed scenario simulations and rule-based decision support which is delivered to the decision maker through a sophisticated graphical user interface (GUI) using information fusion and fast information aggregation to create situational awareness in the shortest time possible. The system also contains risk and vulnerability information which was designed with the far end of the warning chain in mind - it enables the decision maker to base his acceptance (or refusal) of the supported decision also on regionally differentiated risk and vulnerability information (see Strunz et al., 2010). While the system strives to provide a warning as quickly as possible, it is not in its proper responsibility to send and disseminate the warning to the recipients. The DSS only broadcasts its messages to a dissemination system (and possibly any other dissemination system) which is operated under the responsibility of BMKG - the meteorological, climatological and geophysical service of Indonesia - which also hosts the tsunami early warning center. The system is to be seen as one step towards

  17. Tsunami early warning and decision support

    T. Steinmetz


    Full Text Available An innovative newly developed modular and standards based Decision Support System (DSS is presented which forms part of the German Indonesian Tsunami Early Warning System (GITEWS. The GITEWS project stems from the effort to implement an effective and efficient Tsunami Early Warning and Mitigation System for the coast of Indonesia facing the Sunda Arc along the islands of Sumatra, Java and Bali. The geological setting along an active continental margin which is very close to densely populated areas is a particularly difficult one to cope with, because potential tsunamis' travel times are thus inherently short. National policies require an initial warning to be issued within the first five minutes after an earthquake has occurred. There is an urgent requirement for an end-to-end solution where the decision support takes the entire warning chain into account. The system of choice is based on pre-computed scenario simulations and rule-based decision support which is delivered to the decision maker through a sophisticated graphical user interface (GUI using information fusion and fast information aggregation to create situational awareness in the shortest time possible. The system also contains risk and vulnerability information which was designed with the far end of the warning chain in mind – it enables the decision maker to base his acceptance (or refusal of the supported decision also on regionally differentiated risk and vulnerability information (see Strunz et al., 2010. While the system strives to provide a warning as quickly as possible, it is not in its proper responsibility to send and disseminate the warning to the recipients. The DSS only broadcasts its messages to a dissemination system (and possibly any other dissemination system which is operated under the responsibility of BMKG – the meteorological, climatological and geophysical service of Indonesia – which also hosts the tsunami early warning center. The system is to be seen

  18. Decision Strategy Research and Policy Support

    Hardeman, F


    The objective of SCK-CEN's R and D programme on decision strategies and policy support is: (1) to investigate the decision making process, with all its relevant dimensions, in the context of radiation protection or other nuclear issues (with particular emphasis on emergency preparedness); (2) to disseminate knowledge on decision making and nuclear emergencies, including the organisation of training courses, the contribution to manuals or guidelines, the participation in working groups or discussion forums; (3) to assist the authorities and the industry on any topic related to radiation protection and to make expertise and infrastructure available; (4) to participate in and contribute to initiatives related to social sciences and their implementation into SCK-CEN; (5) to co-ordinate efforts of SCK-CEN related to medical applications of ionising radiation. Principal achievements in 2001 are described.

  19. RODOS: decision support for nuclear emergencies

    RODOS (Real-time On-line DecisiOn Support) is an integrated and comprehensive real-time on-line decision support system for off-site emergency management of nuclear accidents. It is being developed by a consortium of some 40 institutes across Europe with support from, inter alia, the European Commission. Designed as a generic software tool, the RODOS system will be applicable from the very early stages until many years after an accident, and from the vicinity of a release to far distant areas. Decision support will be provided at various levels, ranging from the largely descriptive presenting information on the present and future radiological situation to an evaluation and ranking of the benefits and disadvantages of different countermeasures' options. This report contains a number of papers written during 1996/1997, which describe the RODOS project, the main software components of the system, the status of its development and its potential role for improving emergency response in Europe. (orig.)

  20. Spill operation system decision support system

    The MSRC Spill Operation System (SOS) is a tool for the support of decision-making at the time of a catastrophic oil spill. SOS provides MSRC decision-makers with access to information about the source of the spill, the spill environment, and the availability of spill response resources. This system is designed to meet the information needs of a Response Supervisor, an Environmental Advisor, Logistics/Maintenance Supervisor, Operations Supervisor, and the MSRC Regional General Manager. The SOS project Objectives are: (1) integrate currently available data, systems, and technologies; (2) develop an application that effectively supports mobilized operations and can be adapted to support normal operations; (3) ensure that the development of computer applications is driven by user needs and not by technology; and (4) coordinate with government and other industry organizations to avoid duplication of effort. Design Objectives for SOS are: (1) centralize management information storage while decentralizing decision making capabilities; (2) boost User confidence by providing a system that is easy to learn, easy to use, and is open-quotes Sailor Proofclose quotes; and (3) use visualization technology in providing spill related information. This approach includes the use of Geographic Information System (GIS) technology for maps and geographically associated resource; and support MSRC's concept of operation which includes - a swift notification of response personnel; fast mobilization of response resources; and accurate tracking of resources during a spill. MSRC is organized into five responsibility regions

  1. Clinical Information Support System (CISS)

    Department of Veterans Affairs — Clinical Information Support System (CISS) is a web-based portal application that provides a framework of services for the VA enterprise and supplies an integration...

  2. Better clinical decision making and reducing diagnostic error.

    Croskerry, P; Nimmo, G R


    A major amount of our time working in clinical practice involves thinking and decision making. Perhaps it is because decision making is such a commonplace activity that it is assumed we can all make effective decisions. However, this is not the case and the example of diagnostic error supports this assertion. Until quite recently there has been a general nihilism about the ability to change the way that we think, but it is now becoming accepted that if we can think about, and understand, our thinking processes we can improve our decision making, including diagnosis. In this paper we review the dual process model of decision making and highlight ways in which decision making can be improved through the application of this model to our day-to-day practice and by the adoption of de-biasing strategies and critical thinking. PMID:21677922

  3. Knowledge representation for decision support systems

    This book is organized into three sections in accordance with the structure of the conference program. First section contains four major papers which were commissioned by the Programme Committee to set the tone for the conference and to provide a structured source of relevant material from contributing disciplines. The second section contains specific papers submitted to the conference, and concerned with the following topics of specific interest: epistemological issues for decision support systems (DSS), capturing organizational knowledge for DSS, complementarity between human and formal DSS, and representations for adaption. The third section contains the short papers on any topic of relevance to the theme of the conference. It is hoped that the two working conferences organized by WG 8.3 will contribute to the development of a coherent knowledge and understanding of the class of computerized information systems called Decision Support Systems. (Auth.)


    Pere Tumbas


    Full Text Available The environment where managers make decisions has been significantly changed ttiese years. Today, organizations design their products in one country, purchase of materials and raw materials in the other one, production is done in the third country, and finished products are brought out in many countries in the world. Logistics, as a transaction intensive function mutually connect these substantially different business processes and enables more effective and efficient management of the long logistics chains. In realizing such a task, the intensive use of infomiation technologies that provide timely transaction processing and give support in decisionmaking processes is especially important for logistics. The work reviews information systems development in the field of logistics, and a special attention is paid to the conceptual level of the global structure in decision support systems (DSS. Possible contents of identified subsystems are cited and potential development trends of its application are discussed.

  5. Decision Support System Mine -The Management Model

    Kaden, S.; Michels, I.; Tiemer, K.


    The Decision Support System MINE has been developed for the analysis of regional water policies in open-pit lignite mining areas. It is based on a two-level model approach. The first-level planning model is used for the estimation of rational strategies of long-term development applying dynamic multi-criteria analysis. Therefor simplified submodels are used for a rough time discretization (yearly time steps and larger). The second-level management model considers managerial/operational aspect...

  6. A decision support system for forensic entomology

    Morvan, Gildas; Jolly, Daniel; Dupont, Daniel; Kubiak, Philippe


    International audience This paper presents a multiagent-based model of insect development on a dead body and a three layers Decision Support System architecture able to perform retrodictive (abductive) reasoning from multiagent-based models or more generally, complex systems models. This architecture is used in order to compute post-mortem intervals from entomological data sampled on cadavers. Knowing the exact time of a death is fundamental in criminal investigations. Thus, it is necessar...

  7. Decision support system to select cover systems

    The objective of this technology is to provide risk managers with a defensible, objective way to select capping alternatives for remediating radioactive and mixed waste landfills. The process of selecting containment cover technologies for mixed waste landfills requires consideration of many complex and interrelated technical, regulatory, and economic issues. A Decision Support System (DSS) is needed to integrate the knowledge of experts from scientific, engineering, and management disciplines to help in selecting the best capping practice for the site

  8. Clinical decision making in veterinary practice

    Everitt, Sally


    Aim The aim of this study is to develop an understanding of the factors which influence veterinary surgeons’ clinical decision making during routine consultations. Methods The research takes a qualitative approach using video-cued interviews, in which one of the veterinary surgeon’s own consultations is used as the basis of a semi-structured interview exploring decision making in real cases. The research focuses primarily on small animal consultations in first opinion practice, how...

  9. Computerised decision support systems for healthcare professionals: an interpretative review

    Kathrin Cresswell


    Full Text Available Purpose Computerised decision support systems are designed to support clinicians in making decisions and thereby enhance the quality and safety of care. We aimed to undertake an interpretative review of the empirical evidence on computerised decision support systems, their contexts of use, and summarise evidence on the effectiveness of these tools and insights into how these can be successfully implemented and adopted.Methods We systematically searched the empirical literature to identify systematic literature reviews on computerised decision support applications and their impact on the quality and safety of healthcare delivery over a 13-year period (1997–2010. The databases searched included: MEDLINE, EMBASE, The Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, The Cochrane Central Register of Controlled Trials, The Cochrane Methodology Register, The Health Technology Assessment Database, and The National Health Service (NHS Economic Evaluation Database. To be eligible for inclusion, systematic reviews needed to address computerised decision support systems, and at least one of the following: impact on safety; quality; or organisational, implementation or adoption considerations.Results Our searches yielded 121 systematic reviews relating to eHealth, of which we identified 41 as investigating computerised decision support systems. These indicated that, whilst there was a lack of investigating potential risks, such tools can result in improvements in practitioner performance in the promotion of preventive care and guideline adherence, particularly if specific information is available in real time and systems are effectively integrated into clinical workflows. However, the evidence regarding impact on patient outcomes was less clear-cut with reviews finding either no, inconsistent or modest benefits.Conclusions Whilst the potential of clinical decision support systems in improving, in particular

  10. Towards a Clinical Decision Support System for Drug Allergy Management: Are Existing Drug Reference Terminologies Sufficient for Identifying Substitutes and Cross-Reactants?

    Ogallo, William; Kanter, Andrew S


    Drug allergy cross-reactivity checking is an important component of electronic health record systems. Currently, a single, open-source medication dictionary that can provide this function does not exist. In this study, we assessed the feasibility of using RxNorm and NDF-RT (National Drug File--Reference Terminology) for allergy management decision support. We evaluated the performance of using the Pharmacological Class, Mechanism of Action and Chemical Structure NDF-RT classifications in discriminating between safe and cross-reactive alternatives to a sample of common drug allergens. The positive predictive values for the three approaches were 96.3%, 99.3% and 96.2% respectively. The negative predictive values were 94.7%, 56.8% and 92.6%. Our findings suggest that in the absence of an established medication allergy classification system, using the Pharmacologic Class and Chemical Structure classifications in NDF-RT may still be effective for discriminating between safe and cross-reactive alternatives to potential allergens. PMID:26262387

  11. Context based support for Clinical Reasoning

    Vilstrup Pedersen, Klaus


    Intelligence, Knowledge Management Systems and Business Intelligence to make context sensitive, patient case specific analysis and knowledge management. The knowledge base consists of patient health records, reasoning process information and clinical guidelines. Patient specific information and knowledge is...... paper a framework for a Clinical Reasoning Knowledge Warehouse (CRKW) is presented, intended to support the reasoning process, by providing the decision participants with an analysis platform that captures and enhances information and knowledge. The CRKW mixes theories and models from Artificial...... continually enhanced by adding results of analysis. Context sensitive analysis is done by retrieving similar patient cases and guidelines from the knowledge base in a case based fashion....

  12. Decision support models for natural gas dispatch

    A decision support model is presented which will give utilities the support tools to manage the purchasing of natural gas supplies in the most cost effective manner without reducing winter safety stocks to below minimum levels. In Business As Usual (BAU) purchasing quantities vary with the daily forecasts. With Material Requirements Planning (MRP) and Linear Programming (LP), two types of factors are used: seasonal weather and decision rule. Under current practices, BAU simulation uses the least expensive gas source first, then adding successively more expensive sources. Material Requirements Planning is a production planning technique which uses a parent item master production schedule to determine time phased requirements for component points. Where the MPS is the aggregate gas demand forecasts for the contract year. This satisfies daily demand with least expensive gas and uses more expensive when necessary with automatic computation of available-to-promise (ATP) gas a dispacher knows daily when extra gas supplies may be ATP. Linear Programming is a mathematical algorithm used to determine optimal allocations of scarce resources to achieve a desired result. The LP model determines optimal daily gas purchase decisions with respect to supply cost minimization. Using these models, it appears possible to raise gross income margins 6 to 10% with minimal additions of customers and no new gas supply

  13. GIS as spatial decision support system

    V. Vostrovský


    Full Text Available This paper describes the possibility of the Geographic Information Systems (GIS as a means to support decision making in solving spatial problems. Spatial problems accompany every human activity, of which agriculture is no exception. The solutions to these problems requires the application of available knowledge in the relevant decision-making processes. GISs integrate hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information. Coupled with GISs, geography helps to better understand and apply geographic knowledge to a host of global problems (unemployment, environmental pollution, the loss of arable land, epidemics etc.. The result may be a geographical approach represents a new way of thinking and solutions to existing spatial problems. This approach allows to apply existing knowledge to model and analyze these problems and thus help to solve them.

  14. Handling risk attitudes for preference learning and intelligent decision support

    Franco de los Ríos, Camilo; Hougaard, Jens Leth; Nielsen, Kurt


    Intelligent decision support should allow integrating human knowledge with efficient algorithms for making interpretable and useful recommendations on real world decision problems. Attitudes and preferences articulate and come together under a decision process that should be explicitly modeled...

  15. Handling Risk Attitudes for Preference Learning and Intelligent Decision Support

    Franco de los Ríos, Camilo; Hougaard, Jens Leth; Nielsen, Kurt

    Intelligent decision support should allow integrating human knowledge with efficient algorithms for making interpretable and useful recommendations on real world decision problems. Attitudes and preferences articulate and come together under a decision process that should be explicitly modeled for...

  16. Supporting Parental Decisions About Genomic Sequencing for Newborn Screening: The NC NEXUS Decision Aid

    Lewis, Megan A.; Paquin, Ryan S.; Roche, Myra I.; Furberg, Robert D.; Rini, Christine; Berg, Jonathan S.; Powell, Cynthia M.; Bailey, Donald B.


    Advances in genomic sequencing technology have raised fundamental challenges to the traditional ways genomic information is communicated. These challenges will become increasingly complex and will affect a much larger population in the future if genomics is incorporated into standard newborn screening practice. Clinicians, public health officials, and other stakeholders will need to agree on the types of information that they should seek and communicate to parents. Currently, few evidence-based and validated tools are available to support parental informed decision-making. These tools will be necessary as genomics is integrated into clinical practice and public health systems. In this article we describe how the North Carolina Newborn Exome Sequencing for Universal Screening study is addressing the need to support parents in making informed decisions about the use of genomic testing in newborn screening. We outline the context for newborn screening and justify the need for parental decision support. We also describe the process of decision aid development and the data sources, processes, and best practices being used in development. By the end of the study, we will have an evidenced-based process and validated tools to support parental informed decision-making about the use of genomic sequencing in newborn screening. Data from the study will help answer important questions about which genomic information ought to be sought and communicated when testing newborns. PMID:26729698

  17. Supporting Parental Decisions About Genomic Sequencing for Newborn Screening: The NC NEXUS Decision Aid.

    Lewis, Megan A; Paquin, Ryan S; Roche, Myra I; Furberg, Robert D; Rini, Christine; Berg, Jonathan S; Powell, Cynthia M; Bailey, Donald B


    Advances in genomic sequencing technology have raised fundamental challenges to the traditional ways genomic information is communicated. These challenges will become increasingly complex and will affect a much larger population in the future if genomics is incorporated into standard newborn screening practice. Clinicians, public health officials, and other stakeholders will need to agree on the types of information that they should seek and communicate to parents. Currently, few evidence-based and validated tools are available to support parental informed decision-making. These tools will be necessary as genomics is integrated into clinical practice and public health systems. In this article we describe how the North Carolina Newborn Exome Sequencing for Universal Screening study is addressing the need to support parents in making informed decisions about the use of genomic testing in newborn screening. We outline the context for newborn screening and justify the need for parental decision support. We also describe the process of decision aid development and the data sources, processes, and best practices being used in development. By the end of the study, we will have an evidenced-based process and validated tools to support parental informed decision-making about the use of genomic sequencing in newborn screening. Data from the study will help answer important questions about which genomic information ought to be sought and communicated when testing newborns. PMID:26729698

  18. Medical Device Data and Modeling for Clinical Decision Making

    Zaleski, John R


    This cutting-edge volume is the first book that provides you with practical guidance on the use of medical device data for bioinformatics modeling purposes. You learn how to develop original methods for communicating with medical devices within healthcare enterprises and assisting with bedside clinical decision making. The book guides in the implementation and use of clinical decision support methods within the context of electronic health records in the hospital environment.This highly valuable reference also teaches budding biomedical engineers and bioinformaticists the practical benefits of

  19. Towards the Realization of an Integrated Decision Support Environment for Organizational Decision Making

    Shaofeng Liu; Alex H.B. Duffy; Robert Ian Whitfield; Iain M. Boyle; Iain McKenna


    Traditional decision support systems are based on the paradigm of a single decision maker working at a standalone computer or terminal who has a specific decision to make with a specific goal in mind. Organizational decision support systems aim to support decision makers at all levels of an organization (from executive, middle management managers to operators), who have a variety of decisions to make, with different priorities, often in a distributed and dynamic environment. Such systems need...

  20. Computational Support for Technology- Investment Decisions

    Adumitroaie, Virgil; Hua, Hook; Lincoln, William; Block, Gary; Mrozinski, Joseph; Shelton, Kacie; Weisbin, Charles; Elfes, Alberto; Smith, Jeffrey


    Strategic Assessment of Risk and Technology (START) is a user-friendly computer program that assists human managers in making decisions regarding research-and-development investment portfolios in the presence of uncertainties and of non-technological constraints that include budgetary and time limits, restrictions related to infrastructure, and programmatic and institutional priorities. START facilitates quantitative analysis of technologies, capabilities, missions, scenarios and programs, and thereby enables the selection and scheduling of value-optimal development efforts. START incorporates features that, variously, perform or support a unique combination of functions, most of which are not systematically performed or supported by prior decision- support software. These functions include the following: Optimal portfolio selection using an expected-utility-based assessment of capabilities and technologies; Temporal investment recommendations; Distinctions between enhancing and enabling capabilities; Analysis of partial funding for enhancing capabilities; and Sensitivity and uncertainty analysis. START can run on almost any computing hardware, within Linux and related operating systems that include Mac OS X versions 10.3 and later, and can run in Windows under the Cygwin environment. START can be distributed in binary code form. START calls, as external libraries, several open-source software packages. Output is in Excel (.xls) file format.

  1. Entrustment Decision Making in Clinical Training.

    Ten Cate, Olle; Hart, Danielle; Ankel, Felix; Busari, Jamiu; Englander, Robert; Glasgow, Nicholas; Holmboe, Eric; Iobst, William; Lovell, Elise; Snell, Linda S; Touchie, Claire; Van Melle, Elaine; Wycliffe-Jones, Keith


    The decision to trust a medical trainee with the critical responsibility to care for a patient is fundamental to clinical training. When carefully and deliberately made, such decisions can serve as significant stimuli for learning and also shape the assessment of trainees. Holding back entrustment decisions too much may hamper the trainee's development toward unsupervised practice. When carelessly made, however, they jeopardize patient safety. Entrustment decision-making processes, therefore, deserve careful analysis.Members (including the authors) of the International Competency-Based Medical Education Collaborative conducted a content analysis of the entrustment decision-making process in health care training during a two-day summit in September 2013 and subsequently reviewed the pertinent literature to arrive at a description of the critical features of this process, which informs this article.The authors discuss theoretical backgrounds and terminology of trust and entrustment in the clinical workplace. The competency-based movement and the introduction of entrustable professional activities force educators to rethink the grounds for assessment in the workplace. Anticipating a decision to grant autonomy at a designated level of supervision appears to align better with health care practice than do most current assessment practices. The authors distinguish different modes of trust and entrustment decisions and elaborate five categories, each with related factors, that determine when decisions to trust trainees are made: the trainee, supervisor, situation, task, and the relationship between trainee and supervisor. The authors' aim in this article is to lay a theoretical foundation for a new approach to workplace training and assessment. PMID:26630606

  2. An Ontology-driven Framework for Supporting Complex Decision Process

    Chai, Junyi; Liu, James N. K.


    The study proposes a framework of ONTOlogy-based Group Decision Support System (ONTOGDSS) for decision process which exhibits the complex structure of decision-problem and decision-group. It is capable of reducing the complexity of problem structure and group relations. The system allows decision makers to participate in group decision-making through the web environment, via the ontology relation. It facilitates the management of decision process as a whole, from criteria generation, alternat...


    Harmandeep Singh


    Full Text Available A decision support system for precision farming is designed to assist farmers, agricultural experts, research workers or any intellectuals with guidance in making various farming related decisions and help them to access, display and analyze data that have geographic content and meaning. The concept of precision farming is not only related with the use of technologies but it is also about the five R’s that is use of right input (nutrients, water, fertilizer, money, machinery etc., at the right time, at the right place, in the right amount and in the right manner. There is need to have accurate information and suitable decisions regarding the right inputs required for the farming practices and to initiate the step towards the precision farming. DSS calculates irrigation requirement of crops. In this paper, Maps that are shown generated with the help of ArcGIS software (ArcMap tool. The system has been developed using Hypertext Pre Processor (PHP at front end and MySQL at back end.

  4. Using a group decision support system to make investment prioritisation decisions

    Read, Martin; Gear, Tony; Minkes, Leonard; Irving, Ann


    This paper is concerned with how decision making groups involved in making investment prioritisation decisions involving funding of technology and science projects may be supported by a group decision support system (GDSS). While interested in decision outcomes, the primary focus of this paper is the role of a group support system as an aid to developing shared understanding within a group. The paper develops the conceptual framework of decision-making, communication and group support, and de...

  5. Decision support on demand: Emerging electronic markets for decision technologies

    Hemant K. Bhargava; Krishnan, Ramayya; Muller, Rudolf


    For the individual or organization wishing to employ a scientific approach in solving decision problems, there is a plethora of relevant concepts, methods, models, and software. Yet, relative to their potential or to peer software such as database technologies, decision technologies are little used in real-world decision making. We argue that at least some of the problems that restrict the use of decision technologies are rooted in the use of conventional market mechanisms to distrib...

  6. Flood Impact Modelling to support decision making

    Owen, Gareth; Quinn, Paul; O'Donnell, Greg


    Much of what is known about the impacts of landuse change and Natural Flood Management (NFM) is at the local/plot scale. Evidence of the downstream impacts at the larger catchment scale is limited. However, the strategic and financial decisions of land managers, stakeholders and policy makers are made at the larger scale. There are a number of techniques that have the potential to scale local impacts to the catchment scale. This poster will show findings for the 30km2 Leven catchment, North Yorkshire, England. A NFM approach has been adopted by the Environment Agency to reduce flood risk within the catchment. A dense network of stream level gauges were installed in the catchment at the commencement of this project to gain a detailed understanding of the catchment behaviour during storm events. A novel Flood Impact Modelling (FIM) approach has been adopted which uses the network of gauges to disaggregate the outlet hydrograph in terms of source locations. Using a combination of expert opinion and local evidence, the model can be used to assess the impacts of distributed changes in land use management and NFM on flood events. A number of potential future landuse and NFM scenarios have been modelled to investigate their impact on flood peaks. These modelled outcomes are mapped to a simple Decision Support Matrix (DSM). The DSM encourages end users (e.g. land managers and policy makers) to develop an NFM scheme by studying the degree to which local runoff can be attenuated and how that flow will propagate through the network to the point of impact. The DSM relates the impact on flood peaks in terms of alterations to soil management practices and landscape flow connectivity (e.g. soil underdrainage), which can be easily understood by farmers and land managers. The DSM and the FIM together provide a simple to use and transparent modelling tool, making best use of expert knowledge, to support decision making.

  7. Decision support software technology demonstration plan



    The performance evaluation of innovative and alternative environmental technologies is an integral part of the US Environmental Protection Agency's (EPA) mission. Early efforts focused on evaluating technologies that supported the implementation of the Clean Air and Clean Water Acts. In 1986 the Agency began to demonstrate and evaluate the cost and performance of remediation and monitoring technologies under the Superfund Innovative Technology Evaluation (SITE) program (in response to the mandate in the Superfund Amendments and Reauthorization Act of 1986 (SARA)). In 1990, the US Technology Policy was announced. This policy placed a renewed emphasis on making the best use of technology in achieving the national goals of improved quality of life for all Americans, continued economic growth, and national security. In the spirit of the technology policy, the Agency began to direct a portion of its resources toward the promotion, recognition, acceptance, and use of US-developed innovative environmental technologies both domestically and abroad. Decision Support Software (DSS) packages integrate environmental data and simulation models into a framework for making site characterization, monitoring, and cleanup decisions. To limit the scope which will be addressed in this demonstration, three endpoints have been selected for evaluation: Visualization; Sample Optimization; and Cost/Benefit Analysis. Five topics are covered in this report: the objectives of the demonstration; the elements of the demonstration plan; an overview of the Site Characterization and Monitoring Technology Pilot; an overview of the technology verification process; and the purpose of this demonstration plan.

  8. Informal Online Decision Making: Current Practices and Support System Design

    André, Paul; Drucker, Steven; schraefel, m.c.


    Existing group decision support systems are too complex to support lightweight, informal decision making made popular by the amount of information available on the Web. From an examination of related work, an online survey and a formative study to examine how people currently use the Web for decision support, we present a set of design recommendations towards the development of an informal Web decision support tool.

  9. Towards a model for exploring the relationship between managerial decision problems and decision support opportunities

    Daly, Mary Frances


    The organisational decision making environment is complex, and decision makers must deal with uncertainty and ambiguity on a continuous basis. Managing and handling decision problems and implementing a solution, requires an understanding of the complexity of the decision domain to the point where the problem and its complexity, as well as the requirements for supporting decision makers, can be described. Research in the Decision Support Systems domain has been extensive over the last thirty y...

  10. Marketing Decision Making and Decision Support: Challenges and Perspectives for Successful Marketing Management Support Systems

    G.H. van Bruggen (Gerrit); B. Wierenga (Berend)


    textabstractMarketing management support systems (MMSS) are computer-enabled devices that help marketers to make better decisions. Marketing processes can be quite complex, involving large numbers of variables and mostly outcomes are the results of the actions of many different stakeholders (e.g., t