WorldWideScience

Sample records for clinical decision support

  1. Decision time for clinical decision support systems

    OpenAIRE

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

    2014-01-01

    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

    Data.gov (United States)

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

  3. Grand challenges in clinical decision support.

    Science.gov (United States)

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

    2008-04-01

    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

    CERN Document Server

    Bennett, Casey C

    2012-01-01

    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

    Czech Academy of Sciences Publication Activity Database

    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 http://library.utia.cas.cz/separaty/2010/SI/vajda-information theory models for clinical decision support.doc

  6. Clinical decision support system in dental implantology

    OpenAIRE

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

    2013-01-01

    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.

    Science.gov (United States)

    Crowell, Karen; Vardell, Emily

    2015-01-01

    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

    Directory of Open Access Journals (Sweden)

    Kolostoumpis G.

    2012-01-01

    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

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan; Zvárová, Jana

    2016-01-01

    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.

    Science.gov (United States)

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

    2016-06-01

    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.

    Science.gov (United States)

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

    2015-07-01

    Healthcare information technology systems are considered the ideal tool to inculcate evidence-based nursing practices. The wound clinical decision support system was built locally to support nurses to manage pressure ulcer wounds in their daily practice. However, its adoption rate is not optimal. The study's objective was to discover the concepts that informed the RNs' decisions to adopt the wound clinical decision support system as an evidence-based technology in their nursing practice. This was an exploratory, descriptive, and qualitative design using face-to-face interviews, individual interviews, and active participatory observation. A purposive, theoretical sample of 14 RNs was recruited from one of the largest public tertiary hospitals in Singapore after obtaining ethics approval. After consenting, the nurses were interviewed and observed separately. Recruitment stopped when data saturation was reached. All transcribed interview data underwent a concurrent thematic analysis, whereas observational data were content analyzed independently and subsequently triangulated with the interview data. Eight emerging themes were identified, namely, use of the wound clinical decision support system, beliefs in the wound clinical decision support system, influences of the workplace culture, extent of the benefits, professional control over nursing practices, use of knowledge, gut feelings, and emotions (fear, doubt, and frustration). These themes represented the nurses' mental outlook as they made decisions on adopting the wound clinical decision support system in light of the complexities of their roles and workloads. This research has provided insight on the nurses' thoughts regarding their decision to interact with the computer environment in a Singapore context. It captured the nurses' complex thoughts when deciding whether to adopt or reject information technology as they practice in a clinical setting. PMID:26066306

  12. Grand Challenges in Clinical Decision Support v10

    OpenAIRE

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

    2007-01-01

    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

    Science.gov (United States)

    Greenes, Robert A.

    2009-01-01

    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.

    Science.gov (United States)

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

    2016-04-01

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

    Science.gov (United States)

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

    1999-02-01

    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

    OpenAIRE

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

    2000-01-01

    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.

    Science.gov (United States)

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

    2014-01-01

    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

    Science.gov (United States)

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

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

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

    Science.gov (United States)

    Khalifa, Mohamed; Alswailem, Osama

    2015-01-01

    Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital. PMID:26152955

  20. Clinical decision support for perioperative information management systems.

    Science.gov (United States)

    Wanderer, Jonathan P; Ehrenfeld, Jesse M

    2013-12-01

    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

    Directory of Open Access Journals (Sweden)

    Tiago OLIVEIRA

    2012-09-01

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

  2. Details of a Successful Clinical Decision Support System

    Science.gov (United States)

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

    2007-01-01

    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

    OpenAIRE

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

    2014-01-01

    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.

    Science.gov (United States)

    Kuo, Kuan-Liang; Fuh, Chiou-Shann

    2010-10-01

    Health examinations play a key role in preventive medicine. We propose a health examination system named Health Examination Automatic Logic System (HEALS) to assist clinical workers in improving the total quality of health examinations. Quality of automated inference is confirmed by the zero inference error where during 6 months and 14,773 cases. Automated inference time is less than one second per case in contrast to 2 to 5 min for physicians. The most significant result of efficiency evaluation is that 3,494 of 4,356 (80.2%) cases take less than 3 min per case for producing a report summary. In the evaluation of effectiveness, novice physicians got 18% improvement in making decisions with the assistance of our system. We conclude that a health examination system with a clinical decision system can greatly reduce the mundane burden on clinical workers and markedly improve the quality and efficiency of health examination tasks. PMID:20703626

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

    DEFF Research Database (Denmark)

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

    2012-01-01

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

    Science.gov (United States)

    Wright, Adam; Sittig, Dean F

    2008-12-01

    In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are: PMID:18434256

  7. Quantitative ultrasound texture analysis for clinical decision making support

    Science.gov (United States)

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

    2015-03-01

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

    NARCIS (Netherlands)

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

    2000-01-01

    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.

    Science.gov (United States)

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

    2014-04-01

    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

    Science.gov (United States)

    Wolfenden, Andrew

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Brinner Kristin M

    2009-10-01

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

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

    Directory of Open Access Journals (Sweden)

    Hoath James I

    2010-10-01

    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.

    Science.gov (United States)

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

    2011-01-01

    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

    NARCIS (Netherlands)

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

    2011-01-01

    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.

    OpenAIRE

    Geissbuhler, A.; Miller, R A

    1998-01-01

    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.

    OpenAIRE

    Kashyap, Vipul; Morales, Alfredo; Hongsermeier, Tonya

    2006-01-01

    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

    OpenAIRE

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

    2003-01-01

    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

    Science.gov (United States)

    Kunisch, Joseph Martin

    2012-01-01

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

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

    OpenAIRE

    Kilsdonk, E.

    2016-01-01

    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.

    OpenAIRE

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

    1999-01-01

    The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A te...

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

    OpenAIRE

    Giannessi, Massimo

    2010-01-01

    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

    OpenAIRE

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

    2011-01-01

    A substantial reduction in hospitalization rates has been associated with the implementation of the Interventions to Reduce Acute Care Transfers (INTERACT) quality improvement intervention using the accompanying paper-based clinical practice tools (INTERACT II). There is significant potential to further increase the impact of INTERACT by integrating INTERACT II tools into nursing home (NH) health information technology (HIT) via standalone or integrated clinical decision support (CDS) systems...

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

    OpenAIRE

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

    2011-01-01

    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

    DEFF Research Database (Denmark)

    Gøtze, John; Hijikata, Masao

    1997-01-01

    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.

    Science.gov (United States)

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

    2014-01-01

    Whole genome sequence (WGS) information could soon be routinely available to clinicians to support the personalized care of their patients. At such time, clinical decision support (CDS) integrated into the clinical workflow will likely be necessary to support genome-guided clinical care. Nevertheless, developing CDS capabilities for WGS information presents many unique challenges that need to be overcome for such approaches to be effective. In this manuscript, we describe the development of a prototype CDS system that is capable of providing genome-guided CDS at the point of care and within the clinical workflow. To demonstrate the functionality of this prototype, we implemented a clinical scenario of a hypothetical patient at high risk for Lynch Syndrome based on his genomic information. We demonstrate that this system can effectively use service-oriented architecture principles and standards-based components to deliver point of care CDS for WGS information in real-time. PMID:25954430

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

    Evidence-based medical practice requires that clinical guidelines need to be documented in such a way that they represent a clinical workflow in its most accessible form. In order to optimize clinical processes to improve clinical outcomes, we propose a Service Oriented Architecture (SOA) based approach for implementing clinical guidelines that can be accessed from an Electronic Health Record (EHR) application with a Web Services enabled communication mechanism with the Enterprise Service Bus. We have used Business Process Modelling Notation (BPMN) for modelling and presenting the clinical pathway in the form of a workflow. The aim of this study is to produce spontaneous alerts in the healthcare workflow in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD). The use of BPMN as a tool to automate clinical guidelines has not been previously employed for providing Clinical Decision Support (CDS). PMID:25160142

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

    Science.gov (United States)

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

    2015-01-01

    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

    Science.gov (United States)

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

    2016-01-01

    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

    Science.gov (United States)

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

    2016-03-01

    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

    OpenAIRE

    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

    2010-01-01

    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

    OpenAIRE

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

    2013-01-01

    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

    OpenAIRE

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

    2008-01-01

    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

    OpenAIRE

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

    2015-01-01

    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

    Directory of Open Access Journals (Sweden)

    Weise-Kelly Lorraine

    2011-08-01

    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

    Directory of Open Access Journals (Sweden)

    Wu Helen W

    2012-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Casey Lynnette Overby

    2014-02-01

    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

    CERN Document Server

    Bennett, Casey; Selove, Rebecca

    2012-01-01

    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

    Directory of Open Access Journals (Sweden)

    Zhou Li

    2012-11-01

    Full Text Available Abstract Background Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs, Software Engineers (SEs, and Subject Matter Experts (SMEs to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. Methods The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. Results While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. Conclusions A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR systems, testing, and reporting.

  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.

    Science.gov (United States)

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

    2013-01-01

    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

    International Nuclear Information System (INIS)

    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

    Directory of Open Access Journals (Sweden)

    Clark Michael E

    2010-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Navarro Tamara

    2011-08-01

    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

    DEFF Research Database (Denmark)

    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

    2016-01-01

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

    Science.gov (United States)

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

    1998-06-01

    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.

    Science.gov (United States)

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

    2008-01-01

    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

    OpenAIRE

    Jan Warchoł; Jarosław Szkoła; Krzysztof Pancerz

    2011-01-01

    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

    Directory of Open Access Journals (Sweden)

    Yishai Ofran

    2014-10-01

    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.

    Science.gov (United States)

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

    2015-12-01

    The clinical decision support system is utilized to translate knowledge into evidence-based practice in clinical settings. Many studies have been conducted to understand users' adoption of the clinical decision support system. A critical review was conducted to understand the theoretical or conceptual frameworks used to inform the studies on the adoption of the clinical decision support system. The review identified 15 theoretical and conceptual frameworks using multiple hybrids of theories and concepts. The Technology Acceptance Model was the most frequently used baseline framework combined with frameworks such as the diffusion of innovation, social theory, longitudinal theory, and so on. The results from these articles yielded multiple concepts influencing the adoption of the clinical decision support system. These concepts can be recategorized into nine major concepts, namely, the information system, person (user or patient), social, organization, perceived benefits, emotions, trustability, relevance (fitness), and professionalism. None of the studies found all the nine concepts. That said, most of them have identified the information system, organization, and person concepts as three of its concepts affecting the use of the clinical decision support system. Within each of the concepts, its subconcepts were noted to be very varied. Yet each of these subconcepts has significantly contributed toward the different facets of the concepts. A pluralistic framework was built using the concepts and subconcepts to provide an overall framework construct for future study on the adoption of the clinical decision support system. PMID:26535769

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

    Science.gov (United States)

    Wu, Dehua

    2016-01-01

    The spatial position and distribution of human body meridian are expressed limitedly in the decision support system (DSS) of acupuncture and moxibustion at present, which leads to the failure to give the effective quantitative analysis on the spatial range and the difficulty for the decision-maker to provide a realistic spatial decision environment. Focusing on the limit spatial expression in DSS of acupuncture and moxibustion, it was proposed that on the basis of the geographic information system, in association of DSS technology, the design idea was developed on the human body meridian spatial DSS. With the 4-layer service-oriented architecture adopted, the data center integrated development platform was taken as the system development environment. The hierarchical organization was done for the spatial data of human body meridian via the directory tree. The structured query language (SQL) server was used to achieve the unified management of spatial data and attribute data. The technologies of architecture, configuration and plug-in development model were integrated to achieve the data inquiry, buffer analysis and program evaluation of the human body meridian spatial DSS. The research results show that the human body meridian spatial DSS could reflect realistically the spatial characteristics of the spatial position and distribution of human body meridian and met the constantly changeable demand of users. It has the powerful spatial analysis function and assists with the scientific decision in clinical treatment and teaching of acupuncture and moxibustion. It is the new attempt to the informatization research of human body meridian. PMID:26946752

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

    Science.gov (United States)

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

    2015-01-01

    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

    Directory of Open Access Journals (Sweden)

    Ash Joan S

    2012-02-01

    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.

    Science.gov (United States)

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

    2013-08-01

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

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

    Science.gov (United States)

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

    2014-12-01

    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.

    Science.gov (United States)

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

    2016-06-01

    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

    Science.gov (United States)

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

    2013-01-01

    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.

    LENUS (Irish Health Repository)

    Collins, I M

    2012-03-02

    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

    Directory of Open Access Journals (Sweden)

    Jason M Baron

    2014-01-01

    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

    Directory of Open Access Journals (Sweden)

    Megan Doerr

    2014-03-01

    Full Text Available Family health history is a leading predictor of disease risk. Nonetheless, it is underutilized to guide care and, therefore, is ripe for health information technology intervention. To fill the family health history practice gap, Cleveland Clinic has developed a family health history collection and clinical decision support tool, MyFamily. This report describes the impact and process of implementing MyFamily into primary care, cancer survivorship and cancer genetics clinics. Ten providers participated in semi-structured interviews that were analyzed to identify opportunities for process improvement. Participants universally noted positive effects on patient care, including increases in quality, personalization of care and patient engagement. The impact on clinical workflow varied by practice setting, with differences observed in the ease of integration and the use of specific report elements. Tension between the length of the report and desired detail was appreciated. Barriers and facilitators to the process of implementation were noted, dominated by the theme of increased integration with the electronic medical record. These results fed real-time improvement cycles to reinforce clinician use. This model will be applied in future institutional efforts to integrate clinical genomic applications into practice and may be useful for other institutions considering the implementation of tools for personalizing medical management.

  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.

    Science.gov (United States)

    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

    2012-01-01

    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.

    Science.gov (United States)

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

    2016-01-01

    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

    Directory of Open Access Journals (Sweden)

    Lyons-Weiler James

    2007-08-01

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

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

    Science.gov (United States)

    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

    2016-09-01

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

    International Nuclear Information System (INIS)

    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.

    Science.gov (United States)

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

    2016-03-01

    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

    Directory of Open Access Journals (Sweden)

    Weise-Kelly Lorraine

    2011-08-01

    Full Text Available Abstract Background Some drugs have a narrow therapeutic range and require monitoring and dose adjustments to optimize their efficacy and safety. Computerized clinical decision support systems (CCDSSs may improve the net benefit of these drugs. The objective of this review was to determine if CCDSSs improve processes of care or patient outcomes for therapeutic drug monitoring and dosing. Methods We conducted a decision-maker-researcher partnership systematic review. Studies from our previous review were included, and new studies were sought until January 2010 in MEDLINE, EMBASE, Evidence-Based Medicine Reviews, and Inspec databases. Randomized controlled trials assessing the effect of a CCDSS on process of care or patient outcomes were selected by pairs of independent reviewers. A study was considered to have a positive effect (i.e., CCDSS showed improvement if at least 50% of the relevant study outcomes were statistically significantly positive. Results Thirty-three randomized controlled trials were identified, assessing the effect of a CCDSS on management of vitamin K antagonists (14, insulin (6, theophylline/aminophylline (4, aminoglycosides (3, digoxin (2, lidocaine (1, or as part of a multifaceted approach (3. Cluster randomization was rarely used (18% and CCDSSs were usually stand-alone systems (76% primarily used by physicians (85%. Overall, 18 of 30 studies (60% showed an improvement in the process of care and 4 of 19 (21% an improvement in patient outcomes. All evaluable studies assessing insulin dosing for glycaemic control showed an improvement. In meta-analysis, CCDSSs for vitamin K antagonist dosing significantly improved time in therapeutic range. Conclusions CCDSSs have potential for improving process of care for therapeutic drug monitoring and dosing, specifically insulin and vitamin K antagonist dosing. However, studies were small and generally of modest quality, and effects on patient outcomes were uncertain, with no convincing

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

    International Nuclear Information System (INIS)

    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

    CERN Document Server

    Power, Daniel J

    2009-01-01

    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.

    OpenAIRE

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

    1994-01-01

    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

    DEFF Research Database (Denmark)

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

    2011-01-01

    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

    Directory of Open Access Journals (Sweden)

    Ali Mohammad Hadianfard

    2015-04-01

    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

    OpenAIRE

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

    2013-01-01

    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

    OpenAIRE

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

    2014-01-01

    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.

    OpenAIRE

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

    2001-01-01

    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

    Directory of Open Access Journals (Sweden)

    Wilczynski Nancy L

    2010-02-01

    Full Text Available Abstract Background Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this research was to form a partnership of healthcare providers, managers, and researchers to review randomized controlled trials assessing the effects of computerized decision support for six clinical application areas: primary preventive care, therapeutic drug monitoring and dosing, drug prescribing, chronic disease management, diagnostic test ordering and interpretation, and acute care management; and to identify study characteristics that predict benefit. Methods The review was undertaken by the Health Information Research Unit, McMaster University, in partnership with Hamilton Health Sciences, the Hamilton, Niagara, Haldimand, and Brant Local Health Integration Network, and pertinent healthcare service teams. Following agreement on information needs and interests with decision-makers, our earlier systematic review was updated by searching Medline, EMBASE, EBM Review databases, and Inspec, and reviewing reference lists through 6 January 2010. Data extraction items were expanded according to input from decision-makers. Authors of primary studies were contacted to confirm data and to provide additional information. Eligible trials were organized according to clinical area of application. We included randomized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a computerized clinical decision support system compared with patient care without such a system. Results Data will be summarized

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

    Science.gov (United States)

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

    2016-06-01

    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.

    Science.gov (United States)

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

    2012-01-01

    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

    OpenAIRE

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

    2014-01-01

    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

    OpenAIRE

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

    2003-01-01

    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

    OpenAIRE

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

    2009-01-01

    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.

    Directory of Open Access Journals (Sweden)

    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

    Directory of Open Access Journals (Sweden)

    Yang Zhang

    2012-01-01

    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.

    Science.gov (United States)

    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

    2016-08-01

    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.

    Science.gov (United States)

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

    2016-05-01

    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

    Directory of Open Access Journals (Sweden)

    M. Fatehi

    2005-08-01

    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.

    Science.gov (United States)

    Friedman, R H; Frank, A D

    1983-08-01

    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.

    Directory of Open Access Journals (Sweden)

    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.

    Science.gov (United States)

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

    2014-01-01

    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

    Directory of Open Access Journals (Sweden)

    Hiroyuki Yoshida

    2010-01-01

    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.

    Science.gov (United States)

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

    2016-09-01

    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.

    Science.gov (United States)

    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

    2016-08-01

    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.

    Science.gov (United States)

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

    2013-03-01

    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

    Directory of Open Access Journals (Sweden)

    Sahota Navdeep

    2011-08-01

    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

    Directory of Open Access Journals (Sweden)

    Sindhu Ravindran

    2015-01-01

    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

    OpenAIRE

    Sambasivan Murali; Esmaeilzadeh Pouyan; Kumar Naresh; Nezakati Hossein

    2012-01-01

    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.

    Science.gov (United States)

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

    2016-01-01

    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

    OpenAIRE

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

    2014-01-01

    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

    Directory of Open Access Journals (Sweden)

    Williamson Margaret

    2009-08-01

    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.

    Science.gov (United States)

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

    2015-01-01

    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

    Science.gov (United States)

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

    2016-04-01

    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.

    Science.gov (United States)

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

    2016-03-01

    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

    Science.gov (United States)

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

    2015-01-01

    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

    Directory of Open Access Journals (Sweden)

    Krasowski Matthew D

    2012-02-01

    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

    CERN Document Server

    Bouzguenda, Lotfi

    2012-01-01

    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

    OpenAIRE

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

    2016-01-01

    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

    Directory of Open Access Journals (Sweden)

    Wilczynski Nancy L

    2011-08-01

    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

    OpenAIRE

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

    2016-01-01

    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

    International Nuclear Information System (INIS)

    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

    Science.gov (United States)

    Carney, Timothy Jay

    2012-01-01

    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

    OpenAIRE

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

    2009-01-01

    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

    International Nuclear Information System (INIS)

    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

    DEFF Research Database (Denmark)

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

    2007-01-01

    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

    International Nuclear Information System (INIS)

    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

    Directory of Open Access Journals (Sweden)

    Liang Wen-Miin

    2011-03-01

    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.

    Science.gov (United States)

    Seto, Ryoma; Wakabayashi, Susumu

    2015-01-01

    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

    Science.gov (United States)

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

    2014-03-01

    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.

    Science.gov (United States)

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

    2016-02-01

    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.

    Science.gov (United States)

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

    2016-01-01

    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.

    Science.gov (United States)

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

    2011-08-01

    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.

    Science.gov (United States)

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

    2016-07-01

    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.

    OpenAIRE

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

    1992-01-01

    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

    OpenAIRE

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

    2011-01-01

    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

    International Nuclear Information System (INIS)

    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

    Energy Technology Data Exchange (ETDEWEB)

    Hardeman, F

    2000-07-01

    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:

    Science.gov (United States)

    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

    Directory of Open Access Journals (Sweden)

    Pruszydlo Markus G

    2012-11-01

    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

    International Nuclear Information System (INIS)

    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

    OpenAIRE

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

    2012-01-01

    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

    OpenAIRE

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

    1998-01-01

    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 ...

  10. EVALUATING ENVIRONMENTAL DECISION SUPPORT TOOLS.

    Energy Technology Data Exchange (ETDEWEB)

    SULLIVAN, T.

    2004-10-01

    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

    Czech Academy of Sciences Publication Activity Database

    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.

    Science.gov (United States)

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

    2010-08-23

    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

    Directory of Open Access Journals (Sweden)

    Singer Jesse

    2011-09-01

    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

    Directory of Open Access Journals (Sweden)

    Sunderajan Prabha

    2009-01-01

    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

    Science.gov (United States)

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

    2011-01-01

    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

    Directory of Open Access Journals (Sweden)

    O'Brien Timothy

    2010-01-01

    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

    OpenAIRE

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

    1996-01-01

    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.

    Science.gov (United States)

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

    2016-06-01

    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

    Directory of Open Access Journals (Sweden)

    Mark R Tonelli

    2011-01-01

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

  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.

    Science.gov (United States)

    Robson, Barry; Boray, Srinidhi

    2016-06-01

    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

    DEFF Research Database (Denmark)

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

    2012-01-01

    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

    Directory of Open Access Journals (Sweden)

    Pouyan Esmaeilzadeh

    2014-04-01

    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

    OpenAIRE

    Singer Jesse; Anane Sheila; Taverna John; Amirfar Sam

    2011-01-01

    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

    NARCIS (Netherlands)

    B. Nannings; A. Abu-Hanna

    2006-01-01

    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

    Directory of Open Access Journals (Sweden)

    Sambasivan Murali

    2012-12-01

    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.

    Science.gov (United States)

    Zhao, Kun; Qiu, Fasheng; Chen, Guantao

    2013-12-20

    Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (GC) are the agents of two common, sexually transmitted diseases afflicting women in the United States (http://www.cdc.gov). 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

    OpenAIRE

    E.A. Trachtenherz

    2001-01-01

    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

    DEFF Research Database (Denmark)

    Hansen, Poul H. Kyvsgård; Mikkola, Juliana Hsuan

    2007-01-01

    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

    OpenAIRE

    Wang, Jingyi

    2011-01-01

    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

    Directory of Open Access Journals (Sweden)

    Simon Fong

    2013-01-01

    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

    OpenAIRE

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

    2005-01-01

    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

    CERN Document Server

    Cabrera, Mariana Maceiras

    2010-01-01

    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

    International Nuclear Information System (INIS)

    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

    International Nuclear Information System (INIS)

    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

    Directory of Open Access Journals (Sweden)

    Alagiakrishnan K

    2016-01-01

    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

    OpenAIRE

    P.Kalpana,; Dr . T . Bhuvaneswari

    2011-01-01

    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

    OpenAIRE

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

    2010-01-01

    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

    Directory of Open Access Journals (Sweden)

    Wanyenze Rhoda K

    2013-02-01

    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

    International Nuclear Information System (INIS)

    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

  20. DECISIONS, METHODS AND TECHNIQUES RELATED TO DECISION SUPPORT SYSTEMS (DSS

    Directory of Open Access Journals (Sweden)

    Boghean Florin

    2015-07-01

    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

    Directory of Open Access Journals (Sweden)

    Schmaltz Heidi N

    2010-10-01

    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.

    Science.gov (United States)

    Crane, V S

    1988-03-01

    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.

    Science.gov (United States)

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

    2009-01-01

    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

    International Nuclear Information System (INIS)

    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

    Energy Technology Data Exchange (ETDEWEB)

    Aragon, Cecilia R.

    2005-07-01

    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

    CERN Document Server

    Power, Daniel J

    2013-01-01

    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

    OpenAIRE

    Warnars, Spits

    2010-01-01

    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

    International Nuclear Information System (INIS)

    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

    Directory of Open Access Journals (Sweden)

    Fay Crawford

    2010-12-01

    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.

  10. DECISION SUPPORT SYSTEM TO SUPPORT DECISION PROCESSES WITH DATA MINING

    OpenAIRE

    Rok Rupnik; Matjaž Kukar

    2007-01-01

    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.

    Science.gov (United States)

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

    2016-01-01

    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

    International Nuclear Information System (INIS)

    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

    Science.gov (United States)

    Bernknopf, R.L.

    2005-01-01

    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

    CERN Document Server

    Warnars, Spits

    2010-01-01

    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

    Data.gov (United States)

    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

    OpenAIRE

    Andrei STANCIU; Mihai FLORIN; Cristina RÃDULESCU; Ofelia ALECA

    2009-01-01

    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

    OpenAIRE

    Leonard M. Lodish

    1982-01-01

    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

    OpenAIRE

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

    1991-01-01

    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

    Directory of Open Access Journals (Sweden)

    Andrei STANCIU

    2009-06-01

    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

    Directory of Open Access Journals (Sweden)

    Ahmad M. Kabil

    2012-01-01

    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.

    Science.gov (United States)

    Ursu, Samuel C.

    1992-01-01

    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

    Energy Technology Data Exchange (ETDEWEB)

    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

    1996-12-31

    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

    Science.gov (United States)

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

    2016-01-01

    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.

    OpenAIRE

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

    2002-01-01

    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 ...

  5. DECISION SUPPORT SYSTEM FOR PRECISION FARMING

    OpenAIRE

    Harmandeep Singh; Nitika Sharma

    2013-01-01

    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

    CERN Document Server

    Kaklauskas, Arturas

    2015-01-01

    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

    Directory of Open Access Journals (Sweden)

    John Fox

    2006-03-01

    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

    Science.gov (United States)

    Seright, Teresa J.

    2010-01-01

    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.

    Science.gov (United States)

    Sauter, Vicki L.; Mandell, Marvin B.

    1990-01-01

    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

    DEFF Research Database (Denmark)

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

    2010-01-01

    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

    Directory of Open Access Journals (Sweden)

    Workman T

    2012-05-01

    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

    International Nuclear Information System (INIS)

    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

    International Nuclear Information System (INIS)

    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

    Directory of Open Access Journals (Sweden)

    Manuel Martínez-Álvarez

    2014-08-01

    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

    Directory of Open Access Journals (Sweden)

    Patrick Buckley

    2012-06-01

    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

    Science.gov (United States)

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

    2010-09-01

    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

    Directory of Open Access Journals (Sweden)

    T. Steinmetz

    2010-09-01

    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

    Energy Technology Data Exchange (ETDEWEB)

    Hardeman, F

    2002-04-01

    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

    International Nuclear Information System (INIS)

    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

    International Nuclear Information System (INIS)

    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)

    Data.gov (United States)

    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.

    Science.gov (United States)

    Croskerry, P; Nimmo, G R

    2011-06-01

    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

    International Nuclear Information System (INIS)

    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.)

  4. DECISION SUPPORT SYSTEMS FOR LOGISTICS MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Pere Tumbas

    2007-12-01

    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

    OpenAIRE

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

    1986-01-01

    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

    OpenAIRE

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

    2007-01-01

    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

    International Nuclear Information System (INIS)

    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

    OpenAIRE

    Everitt, Sally

    2011-01-01

    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

    Directory of Open Access Journals (Sweden)

    Kathrin Cresswell

    2013-03-01

    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?

    Science.gov (United States)

    Ogallo, William; Kanter, Andrew S

    2015-01-01

    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

    DEFF Research Database (Denmark)

    Vilstrup Pedersen, Klaus

    2004-01-01

    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

    International Nuclear Information System (INIS)

    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

    Directory of Open Access Journals (Sweden)

    V. Vostrovský

    2011-06-01

    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

    DEFF Research Database (Denmark)

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

    2015-01-01

    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

    DEFF Research Database (Denmark)

    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

    Science.gov (United States)

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

    2016-01-01

    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.

    Science.gov (United States)

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

    2016-01-01

    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

    CERN Document Server

    Zaleski, John R

    2010-01-01

    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

    OpenAIRE

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

    2009-01-01

    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

    Science.gov (United States)

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

    2007-01-01

    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.

    Science.gov (United States)

    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

    2016-02-01

    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

    OpenAIRE

    Chai, Junyi; Liu, James N. K.

    2011-01-01

    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...

  3. DECISION SUPPORT SYSTEM FOR PRECISION FARMING

    Directory of Open Access Journals (Sweden)

    Harmandeep Singh

    2013-01-01

    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

    OpenAIRE

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

    2013-01-01

    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

    OpenAIRE

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

    1997-01-01

    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

    Science.gov (United States)

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

    2015-04-01

    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

    Energy Technology Data Exchange (ETDEWEB)

    SULLIVAN,T.; ARMSTRONG,A.

    1998-09-01

    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

    OpenAIRE

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

    2007-01-01

    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

    OpenAIRE

    Daly, Mary Frances

    2014-01-01

    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

    NARCIS (Netherlands)

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

    2009-01-01

    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

  11. Reactive Software Agent Anesthesia Decision Support System

    Directory of Open Access Journals (Sweden)

    Grant H. Kruger

    2011-12-01

    Full Text Available Information overload of the anesthesiologist through technological advances have threatened the safety of patients under anesthesia in the operating room (OR. Traditional monitoring and alarm systems provide independent, spatially distributed indices of patient physiological state. This creates the potential to distract caregivers from direct patient care tasks. To address this situation, a novel reactive agent decision support system with graphical human machine interface was developed. The system integrates the disparate data sources available in the operating room, passes the data though a decision matrix comprising a deterministic physiologic rule base established through medical research. Patient care is improved by effecting change to the care environment by displaying risk factors and alerts as an intuitive color coded animation. The system presents a unified, contextually appropriate snapshot of the patient state including current and potential risk factors, and alerts of critical patient events to the operating room team without requiring any user intervention. To validate the efficacy of the system, a retrospective analysis focusing on the hypotension rules were performed. Results show that even with vigilant and highly trained clinicians, deviations from ideal patient care exist and it is here that the proposed system may allow more standardized and improved patient care and potentially outcomes.

  12. A systematic requirements engineering approach for decision support systems

    OpenAIRE

    Garcia Martinez, Stephany

    2014-01-01

    Decision Support Systems have emerged as a dominant technology capable to integrate heterogeneous sources into an analytical fashion to facilitate and provide a better decision-making process. Successful projects of Decision Support Systems implementation have confirmed a highlevel of user satisfaction and return on investment. Despite the potential of these systems, several surveys have indicated that the failure rate of Decision Support System projects in case studies and literature is cons...

  13. Decision support systems: Users, organization and design

    International Nuclear Information System (INIS)

    This paper reviews the features of decision support systems (DSSs), distinguishing them from other kinds of computer-based information systems. The design of an effective DSS requires consideration of not only the user's needs, characteristics and capabilities, but also a knowledge of the situation in which the user functions. It is misleading to consider the user as an individual, isolated from group influences, organisational culture and the larger social environment. The user must actively participate in the design of the DSS which must be tailored for each specific application. The design of the Ispra Risk Management Support System (IRIMS) is summarised as an example of this design philosophy. It was designed in consultation with a group of potential users and is currently being customized for a particular application in collaboration with the Netherlands Ministry for Housing, Physical Planning and the Environment. The lessons learnt from the IRIMS design process are summarised and their implications for the design of systems intended to aid process plant operators are discussed. (author). 15 refs

  14. A mobile decision support system for dynamic group decision making problems

    OpenAIRE

    P??rez, I. J.; Cabrerizo, F.J.; Herrera-Viedma, E.

    2010-01-01

    The aim of this paper is to present a decision support system model with two important characteristic: (i) mobile technologies are applied in the decision process, and (ii) the set of alternatives is not fixed over time to address dynamic decision situations in which the set of solution alternatives could change throughout the decision making process.We implement a prototype of such mobile decision support system in which experts use mobile phones to provide their preferences anywhere and any...

  15. Improving Decision Making by Means of a Marketing Decision Support System

    OpenAIRE

    Gerrit H. van Bruggen; Ale Smidts; Berend Wierenga

    1998-01-01

    Marketing decision makers are confronted with an increasing amount of information. This leads to a complex decision environment that may cause decision makers to lapse into using mental-effort-reducing heuristics such as anchoring and adjustment. In an experimental study, we find that the use of a marketing decision support system (MDSS) increases the effectiveness of marketing decision makers. An MDSS is effective because it assists its users in identifying the important decision variables a...

  16. Decision support systems in oncology: Are we there yet?

    OpenAIRE

    D'Aquin, Mathieu; Lieber, Jean; Napoli, Amedeo

    2008-01-01

    This paper presents the experience of the Kasimir project in the domain on decision knowledge management in oncology and, more broadly, a discussion about decision support systems dedicated to oncology.

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

    OpenAIRE

    Bruggen, Gerrit; Wierenga, Berend

    2009-01-01

    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., the company itself, its customers, its competitors). Moreover, a large number of interdependencies exist between the relevant variables and the outcomes of marketing actions are subject to major unc...

  18. Data Mining Session-Based Patient Reported Outcomes (PROs) in a Mental Health Setting: Toward Data-Driven Clinical Decision Support and Personalized Treatment

    CERN Document Server

    Bennett, Casey; Bragg, April; Luellen, Jason; Van Regenmorter, Christina; Lockman, Jennifer; Reiserer, Randall; 10.1109/HISB.2011.20

    2011-01-01

    The CDOI outcome measure - a patient-reported outcome (PRO) instrument utilizing direct client feedback - was implemented in a large, real-world behavioral healthcare setting in order to evaluate previous findings from smaller controlled studies. PROs provide an alternative window into treatment effectiveness based on client perception and facilitate detection of problems/symptoms for which there is no discernible measure (e.g. pain). The principal focus of the study was to evaluate the utility of the CDOI for predictive modeling of outcomes in a live clinical setting. Implementation factors were also addressed within the framework of the Theory of Planned Behavior by linking adoption rates to implementation practices and clinician perceptions. The results showed that the CDOI does contain significant capacity to predict outcome delta over time based on baseline and early change scores in a large, real-world clinical setting, as suggested in previous research. The implementation analysis revealed a number of ...

  19. A decision support tool for landfill methane generation

    OpenAIRE

    Emkes, Harriet

    2013-01-01

    This paper focuses on providing a decision support tool (DST) to enhance methane generation at individual landfill sites. To date there is no decision support tool (DST) available to provide landfill decision makers with clear and simplified information for decision makers to understand what is happening within a landfill site, to assess its performance and to be aware of potential remedies to any issues. The current lack in understanding stems from the complexity of the lan...

  20. Analytical decision support for sustainable electricity supply

    International Nuclear Information System (INIS)

    This paper addresses sustainability criteria and the associated indicators allowing operationalization of the sustainability concept in the context of electricity supply. The criteria and indicators cover economic, environmental and social aspects. Some selected results from environmental analysis, risk assessment and economic studies are shown. These studies are supported by the extensive databases developed in this work. The applications of multi-criteria analysis demonstrate the use of a framework that allows decision-makers to simultaneously address the often conflicting socio-economic and ecological criteria. 'EnergyGame', the communication-oriented software recently developed by the Paul Scherrer Institute (PSI), provides the opportunity to integrate the central knowledge-based results with subjective value judgments. In this way a sensitivity map of technology choices can be constructed in an interactive manner. Accommodation of a range of perspectives expressed in the energy debate, including the concept of sustainable development, may lead to different internal rankings of the options but some patterns appear to be relatively robust. (orig.)

  1. Post Disaster Assessment with Decision Support System

    Directory of Open Access Journals (Sweden)

    May Florence J. Franco

    2016-05-01

    Full Text Available The study aimed to develop an online system that would expedite the response of agencies after disaster strikes; generate a list of the kinds and volume of relief aids needed per family affected for a fair, precise and timely distribution; implement community-based ICT by remotely gathering all the necessary data needed for disaster assessment; and adhere to ISO 9126 standards. The system was designed to calculate the effects of disaster in human lives and economy. Integrated into the system were Goggle Maps, Mines and GeoSciences Bureau Hazard Maps, SMS sending features, best passable routes calculations, and decision support on the needs that has to be addressed. The system was made live at pdrrmcguimaras.herokuapp.com to allow remote data entry. The functionality and usability of the system were evaluated by 19 potential users by computing for the arithmetic Mean and Standard Deviation of the survey. The result showed that most of them strongly agreed that the system is acceptable based on these criteria. A group of IT experts also evaluated the system’s conformance to ISO 9126 standards using the same method. The result showed that majority of them strongly agreed that the system conforms to this international standard. The system is seen as a valuable tool for the Provincial Disaster Risk Reduction Management Council (PDRRMC and the National Disaster Risk Reduction Management Council (NDRRMC for it could help expedite the assessment of the effects of disasters and the formulation of response plans and strategies.

  2. Decision support tools for advanced energy management

    Energy Technology Data Exchange (ETDEWEB)

    Marik, Karel; Schindler, Zdenek; Stluka, Petr [Honeywell Prague Laboratory, Pod vodarenskou vezi 4, 182 08 Prague 8 (Czech Republic)

    2008-06-15

    Rising fuel costs boost energy prices, which is a driving force for improving efficiency of operation of any energy generation facility. This paper focuses on enhancing the operation of distributed integrated energy systems (IES), system that bring together all forms of cooling, heating and power (CCHP) technologies. Described methodology can be applied in power generation and district heating companies, as well as in small-scale systems that supply multiple types of utilities to consumers in industrial, commercial, residential and governmental spheres. Dispatching of such system in an optimal way needs to assess large number of production and purchasing schemes in conditions of continually changing market and variable utility demands influenced by many external factors, very often by weather conditions. The paper describes a combination of forecasting and optimization methods that supports effective decisions in IES system management. The forecaster generates the future most probable utility demand several hours or days ahead, derived from the past energy consumer behaviour. The optimizer generates economically most efficient operating schedule for the IES system that matches these forecasted energy demands and respects expected purchased energy prices. (author)

  3. Decision support tools for advanced energy management

    International Nuclear Information System (INIS)

    Rising fuel costs boost energy prices, which is a driving force for improving efficiency of operation of any energy generation facility. This paper focuses on enhancing the operation of distributed integrated energy systems (IES), system that bring together all forms of cooling, heating and power (CCHP) technologies. Described methodology can be applied in power generation and district heating companies, as well as in small-scale systems that supply multiple types of utilities to consumers in industrial, commercial, residential and governmental spheres. Dispatching of such system in an optimal way needs to assess large number of production and purchasing schemes in conditions of continually changing market and variable utility demands influenced by many external factors, very often by weather conditions. The paper describes a combination of forecasting and optimization methods that supports effective decisions in IES system management. The forecaster generates the future most probable utility demand several hours or days ahead, derived from the past energy consumer behaviour. The optimizer generates economically most efficient operating schedule for the IES system that matches these forecasted energy demands and respects expected purchased energy prices. (author)

  4. [Clinical decisions in a philosophical perspective].

    Science.gov (United States)

    Wulff, H R

    1993-09-20

    Medicine is both a scientific and a humanistic discipline. The foundation for clinical decisions has four components (two scientific and two humanistic). 1) The biological component (reasoning based on biological theory). Biological thinking is currently being revolutionised, partly through the development of systems theory. 2) The empirical component (reasoning based on experience from earlier patients), which comprises both uncontrolled and controlled experience. 3) The empathic-hermeneutic component (reasoning based on an understanding of the patient as a fellow human being). Empathy requires hermeneutic knowledge which can be acquired through personal experience and by qualitative research. 4) The ethical component which comprises both utilitarian and deontological considerations. PMID:8211903

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

    CERN Document Server

    Chai, Junyi

    2011-01-01

    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, alternative evaluation, and opinion interaction to decision aggregation. The embedded ontology structure in ONTOGDSS provides the important formal description features to facilitate decision analysis and verification. It examines the software architecture, the selection methods, the decision path, etc. Finally, the ontology application of this system is illustrated with specific real case to demonstrate its potentials towards decision-making development.

  6. ACCOUNTING KNOWLEDGE: DECISION SUPPORT IN FORESTRY

    OpenAIRE

    Ph.D Student Postolache (Males) Daniela

    2010-01-01

    The accountancy provides knowledge which can help managers make decisions about economic efficiency. This paper introduces few accounting instruments whose practical applications provide necessary knowledge for decision-making process, with the usage of concrete examples from forestry. The essay proposes ways of transforming accounting information into necessary knowledge for managers to make informed decisions, using calculation of profitability indicators, cost indicators, financial and eco...

  7. Automation bias and prescribing decision support – rates, mediators and mitigators

    OpenAIRE

    Goddard, Kate

    2012-01-01

    Purpose: Computerised clinical decision support systems (CDSS) are implemented within healthcare settings as a method to improve clinical decision quality, safety and effectiveness, and ultimately patient outcomes. Though CDSSs tend to improve practitioner performance and clinical outcomes, relatively little is known about specific impact of inaccurate CDSS output on clinicians. Although there is high heterogeneity between CDSS types and studies, reviews of the ability of CDSS to prevent medi...

  8. Decision Support for Countering Terrorist Threats against Transportation Networks

    Directory of Open Access Journals (Sweden)

    Dr. Richard Adler

    2009-01-01

    Full Text Available This article presents a dynamic decision support methodology forcounter-terrorism decision support. The initial sections introduce basic objectives and challenges of terrorism risk analysis and risk management. The remainder of the paper describes TRANSEC, a decision support framework for defining, validating, and monitoring strategies focused on managing terrorism risks to international transportation networks. The methodology and software tools underlying TRANSEC are applicable to other homeland security problems, such as critical infrastructure and border protection.

  9. Research on Development of Corn Production Decision Support System

    OpenAIRE

    Nan Lin; Dongming Li; Chunguang Bi

    2013-01-01

    This research was about the application of decision support system in agriculture. The subject of study was the corn cultivated in Jilin province, northeast of China. The research synthesized expertise and experience on corn cultivation, plant protection, soil and fertilizer, and synthesized agriculture ecology from experts, integrating computer technology, principle of decision support system with corn production knowledge. The research also concerned decision support system for corn fertili...

  10. ACCOUNTING KNOWLEDGE IN FORESTRY'S DECISION SUPPORT SYSTEMS. LITERATURE REVIEW

    OpenAIRE

    Daniela I. POSTOLACHE (MALES)

    2010-01-01

    Accounting information, processed through modern type of decision support systems, in appropriate economic analysis framework, using previous experience, gives extra knowledge to forestry managers. In our paper, we conducted a literature review, in the field of decision support systems used in international forestry, but also about the Romanian prospects and achievements in this area. Our results are useful to researchers and developers of decision support intelligent solutions, to forestry a...

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

    OpenAIRE

    White Martha; Pollack Lance; Murray Elizabeth; Lo Bernard

    2007-01-01

    Abstract Background Shared decision-making has been advocated; however there are relatively few studies on physician preferences for, and experiences of, different styles of clinical decision-making as most research has focused on patient preferences and experiences. The objectives of this study were to determine 1) physician preferences for different styles of clinical decision-making; 2) styles of clinical decision-making physicians perceive themselves as practicing; and 3) the congruence b...

  12. Decision support in an integrated environment

    Science.gov (United States)

    Collie, Brad E.; Wallace, Daniel F.; Humphrey, Andy W.

    2000-11-01

    As the United States Navy enters into an era of reduced manning, the role of the decision maker and that of automation must change in order to maintain an acceptable level of performance. In the past, the responsibility of information synthesis has typically fallen on the operator. This becomes problematic when there is a lack of systems integration (most often technologies are co-located but not integrated), thus causing the operator to process an undue amount of information when analyzing information across multiple systems. Reducing the number of operators without changing the way decisions are made would result in information overload, delayed/degraded decision-making, and increased errors/accidents. If we are to successfully take sailors off ships, we must consider decision making in a new manner. One way to address the situation is to provide the decision maker/operator with a Knowledge Management System (KMS), which reduces cognitive processing requirements on behalf of the operator. For example, decisions based on doctrine can be automated with little impact on the quality of the decision as long as the operator is informed of what actions have been taken (keeping the operator in the loop). This paper will address the definition of Knowledge, the need for a KMS, functional allocation of Knowledge processing, and how systems can be designed for Knowledge Management concepts.

  13. Business Intelligence : The impact on decision support and decision making processes

    OpenAIRE

    Andersson, Daniel; Fries, Hannes; Johansson, Per

    2008-01-01

    Historically, decision support systems have been used in organizations to facilitate better decisions. Business Intelligence has become important in recent years because the business environment is more complex and changes faster than ever before. Organizations have started to realize the value of existing information in operational, managerial, and strategic decision making. By using analytical methods and data warehousing, decision support can now be used in a flexible way and assist decisi...

  14. Reef Ecosystem Services and Decision Support Database

    Science.gov (United States)

    This scientific and management information database utilizes systems thinking to describe the linkages between decisions, human activities, and provisioning of reef ecosystem goods and services. This database provides: (1) Hierarchy of related topics - Click on topics to navigat...

  15. Modeling Based Decision Support Environment Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Phoenix Integration's vision is the creation of an intuitive human-in-the-loop engineering environment called Decision Navigator that leverages recent advances in...

  16. Decision support methodologies in public policy formulation

    OpenAIRE

    Borges, Monique; Castro, Eduardo; Marques, João

    2014-01-01

    A decision problem is relatively complex and broadly involves two distinct moments, i) information gathering and ii) use of available information and decision-making. In the first case one can discuss the potential of rigorous methods (statistical analysis and modelling) commonly used to enable and improve the collection, analysis and interpretation of the most relevant data. On the second case it is important to note that the existing information may not be enough, it is not always possible ...

  17. Decision Support Systems used in Disaster Management

    OpenAIRE

    Marius CIOCA; Lucian-Ionel CIOCA

    2010-01-01

    In a constantly changing economic and social environment, organisations, managers, specialists in finance and accounting, people in charge with warning the population in case of disasters, etc. must make important decisions caused by the mobility of internal and external factors. Decisions made in this context must balance advantages and disadvantages, forecast shortterm, medium-term and long-term consequences on the activity of an organisation or community which may be affected by disasters,...

  18. Intelligent Information System to support decision making.

    OpenAIRE

    Kathrin Rodríguez Llanes

    2010-01-01

    Making decisions is complicated in a generalized way, the materials and humans resources of the entity we belong to depends on it, such as the fulfillment of its goals. But when the situations are complex, making decisions turns into a very difficult work, due to the great amount of aspects to consider when making the right choice. To make this efficiently the administration must to consult an important volume of information, which generally, is scattered and in any different formats. That’...

  19. Using Visualization in Cockpit Decision Support Systems

    OpenAIRE

    Aragon, Cecilia R.

    2005-01-01

    In order to safely operate their aircraft, pilots must make rapid decisions based on integrating and processing large amounts of heterogeneous information. Visual displays are often the most efficient method of presenting safety-critical data to pilots in real time. However, care must be taken to ensure the pilot is provided with the appropriate amount of information to make effective decisions and not become cognitively overloaded. The results of two usability studies of a prototype air...

  20. Method for designing organization decision support system framework

    Institute of Scientific and Technical Information of China (English)

    Fan Jiancong; Liang Yongquan; Zeng Qingtian

    2006-01-01

    The concept of organization decision support system (ODSS) is defined according to practical applications and novel understanding. And a framework for ODSS is designed. The framework has three components: infrastructure, decision-making process and decision execution process. Infrastructure is responsible to transfer data and information. Decision-making process is the ODSS's soul to support decision-making. Decision execution process is to evaluate and execute decision results derived from decision-making process. The framework presents a kind of logic architecture. An example is given to verify and analyze the framework. The analysis shows that the framework has practical values, and has also reference values for understanding ODSS and for theoretical studies.

  1. Decision Support Systems (DSS) in Construction Tendering Processes

    CERN Document Server

    Mohemad, Rosmayati; Othman, Zulaiha Ali; Noor, Noor Maizura Mohamad

    2010-01-01

    The successful execution of a construction project is heavily impacted by making the right decision during tendering processes. Managing tender procedures is very complex and uncertain involving coordination of many tasks and individuals with different priorities and objectives. Bias and inconsistent decision are inevitable if the decision-making process is totally depends on intuition, subjective judgement or emotion. In making transparent decision and healthy competition tendering, there exists a need for flexible guidance tool for decision support. Aim of this paper is to give a review on current practices of Decision Support Systems (DSS) technology in construction tendering processes. Current practices of general tendering processes as applied to the most countries in different regions such as United States, Europe, Middle East and Asia are comprehensively discussed. Applications of Web-based tendering processes is also summarised in terms of its properties. Besides that, a summary of Decision Support Sy...

  2. Cyborg practices: call-handlers and computerised decision support systems in urgent and emergency care.

    Science.gov (United States)

    Pope, Catherine; Halford, Susan; Turnbull, Joanne; Prichard, Jane

    2014-06-01

    This article draws on data collected during a 2-year project examining the deployment of a computerised decision support system. This computerised decision support system was designed to be used by non-clinical staff for dealing with calls to emergency (999) and urgent care (out-of-hours) services. One of the promises of computerised decisions support technologies is that they can 'hold' vast amounts of sophisticated clinical knowledge and combine it with decision algorithms to enable standardised decision-making by non-clinical (clerical) staff. This article draws on our ethnographic study of this computerised decision support system in use, and we use our analysis to question the 'automated' vision of decision-making in healthcare call-handling. We show that embodied and experiential (human) expertise remains central and highly salient in this work, and we propose that the deployment of the computerised decision support system creates something new, that this conjunction of computer and human creates a cyborg practice. PMID:24810726

  3. MOIDSS?- Mobile Online Intelligent Decision Support System Project

    Data.gov (United States)

    National Aeronautics and Space Administration — GRID has had a successfully completed Phase I 'Mobile Online Intelligent Decision Support System' (MOIDSS). The system developed into a total solution that supports...

  4. Education for Medical Decision Support at EuroMISE Centre

    Czech Academy of Sciences Publication Activity Database

    Martinková, Patrícia; Zvára Jr., Karel; Dostálová, T.; Zvárová, Jana

    Prague, 2013, nestr. [EFMI 2013 Special Topic Conference. Prague (CZ), 17.04.2013-19.04.2013] Institutional support: RVO:67985807 Keywords : education * decision support * knowledge evaluation * e- learning Subject RIV: IN - Informatics, Computer Science

  5. Clinical Decision Making of Nurses Working in Hospital Settings

    Directory of Open Access Journals (Sweden)

    Ida Torunn Bjørk

    2011-01-01

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

  6. Sttudy on intelligent spatial decision support system of agriculture

    Institute of Scientific and Technical Information of China (English)

    ZHANG Rong-mei; SUN Jie-li

    2006-01-01

    This paper studies how to apply GIS, ES, and Data mining and WEB technologies in agriculture Decision Support System, with the researching background of Hebei expert system for farming soil variable rate fertilization. A model of agriculture intelligent spatial decision support system is built and the key technologies to implement this system are described in details.

  7. Fault-Tolerant Onboard Monitoring and Decision Support Systems

    DEFF Research Database (Denmark)

    Lajic, Zoran

    The purpose of this research project is to improve current onboard decision support systems. Special focus is on the onboard prediction of the instantaneous sea state. In this project a new approach to increasing the overall reliability of a monitoring and decision support system has been...

  8. A review of decision support technologies for amniocentesis.

    NARCIS (Netherlands)

    Durand, M.A.; Boivin, J.; Elwyn, G.

    2008-01-01

    BACKGROUND: There is an increasing interest in designing decision tools [decision support technologies (DSTs)] that support patients when they have to decide about health matters. The purpose of this review was to describe and evaluate existing DSTs for amniocentesis testing. METHODS: Ten medical an

  9. Fault Detection for Shipboard Monitoring and Decision Support Systems

    DEFF Research Database (Denmark)

    Lajic, Zoran; Nielsen, Ulrik Dam

    2009-01-01

    In this paper a basic idea of a fault-tolerant monitoring and decision support system will be explained. Fault detection is an important part of the fault-tolerant design for in-service monitoring and decision support systems for ships. In the paper, a virtual example of fault detection will be p...

  10. Priority oral health research identification for clinical decision-making.

    Science.gov (United States)

    Worthington, Helen; Clarkson, Jan; Weldon, Jo

    2015-09-01

    The Cochrane Library is a core resource for clinical decision-making globally, by clinicians, guideline developers, healthcare providers and patients.The publication of Cochrane Library systematic reviews concerning oral health conditions has grown exponentially to over 215 individual titles (as of 20 June 2015) during the past 20 years.Consequently, maintaining updates of the most clinically important reviews to provide up-to-date and accurate sources of evidence for decision-making has become a pressing concern for the editorial group behind their production, Cochrane Oral Health Group.To identify priority research required by oral health decision-makers, the Cochrane OHG embarked on a consultation process across eight defined areas of dentistry (periodontology, operative (including endodontics) and prosthodontics, paediatric dentistry, dental public health, oral and maxillofacial surgery, oral medicine, orthodontics, cleft lip and/or palate) with existing authors (by email), with members of the public (by online survey), and established internationally clinically expert panels for each area of defined area of dentistry to discuss and ratify (by teleconference) a core portfolio of priority evidence to be produced and maintained on the Cochrane Library.The resulting portfolio of priority research encompasses 81 existing titles to be maintained, and an additional 15 new systematic reviews to be developed by the Cochrane OHG in due course.The Cochrane OHG has actively responded to the outcomes of this prioritisation process by allocating resources to primarily supporting the maintenance of identified priority evidence for the Cochrane Library. PMID:26492797

  11. Decision support modeling for milk valorization

    NARCIS (Netherlands)

    Banaszewska, A.

    2014-01-01

    The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating Frie

  12. Supporting Medical Decision Making with Argumentation Tools

    Science.gov (United States)

    Lu, Jingyan; Lajoie, Susanne P.

    2008-01-01

    This study investigated the collaborative decision-making and communicative discourse of groups of learners engaged in a simulated medical emergency in two conditions. In one condition subgroups used a traditional whiteboard (TW group) to document medical arguments on how to solve a medical emergency. In the other condition subgroups used…

  13. Decision Performance Using Spatial Decision Support Systems: A Geospatial Reasoning Ability Perspective

    Science.gov (United States)

    Erskine, Michael A.

    2013-01-01

    As many consumer and business decision makers are utilizing Spatial Decision Support Systems (SDSS), a thorough understanding of how such decisions are made is crucial for the information systems domain. This dissertation presents six chapters encompassing a comprehensive analysis of the impact of geospatial reasoning ability on…

  14. Empirical Study of KMS Impact on Decision Support

    Directory of Open Access Journals (Sweden)

    Kursad OZLEN

    2014-05-01

    Full Text Available This empirical study was carried out to investigate the impact of ICT-based knowledge management systems (KMS of varying sophistication on decision support in varying decision contexts. The results indicate that the positive impact of KMS sophistication was limited to simple decision contexts only. In simple contexts, the availability of more sophisticated KMS led to more intensive balanced use of the available functions and features which resulted in improved decision quality, confidence and satisfaction. In contrast, greater KMS sophistication made no difference to system usage behaviour and decision performance in complex contexts. Such findings provide much needed empirical support for the proper fit between technology-orientated decision aids and simple decision contexts. Future research is needed to determine suitable solutions for complex contexts.

  15. Amsterdam wrist rules: A clinical decision aid

    Directory of Open Access Journals (Sweden)

    Bentohami Abdelali

    2011-10-01

    Full Text Available Abstract Background Acute trauma of the wrist is one of the most frequent reasons for visiting the Emergency Department. These patients are routinely referred for radiological examination. Most X-rays however, do not reveal any fractures. A clinical decision rule determining the need for X-rays in patients with acute wrist trauma may help to percolate and select patients with fractures. Methods/Design This study will be a multi-center observational diagnostic study in which the data will be collected cross-sectionally. The study population will consist of all consecutive adult patients (≥18 years presenting with acute wrist trauma at the Emergency Department in the participating hospitals. This research comprises two components: one study will be conducted to determine which clinical parameters are predictive for the presence of a distal radius fracture in adult patients presenting to the Emergency Department following acute wrist trauma. These clinical parameters are defined by trauma-mechanism, physical examination, and functional testing. This data will be collected in two of the three participating hospitals and will be assessed by using logistic regression modelling to estimate the regression coefficients after which a reduced model will be created by means of a log likelihood ratio test. The accuracy of the model will be estimated by a goodness of fit test and an ROC curve. The final model will be validated internally through bootstrapping and by shrinking it, an adjusted model will be generated. In the second component of this study, the developed prediction model will be validated in a new dataset consisting of a population of patients from the third hospital. If necessary, the model will be calibrated using the data from the validation study. Discussion Wrist trauma is frequently encountered at the Emergency Department. However, to this date, no decision rule regarding this type of trauma has been created. Ideally, radiographs are

  16. MACVIA Clinical Decision Algorithm in Allergic Rhinitis in adolescents and adults

    OpenAIRE

    Bousquet, Jean; Schünemann, Holger J.; Hellings, Peter W.; Arnavielhe, Sylvie; Bachert, Claus; Bedbrook, Anna; Bergmann, Karl-Christian; Bosnic-Anticevich, Sinthia; Brozek, Jan; Calderon, Moises; Canonica, G. Walter; Casale, Thomas B.; Chavannes, Niels H; Cox, Linda; Chrystyn, Henry

    2016-01-01

    International audience The selection of pharmacotherapy for patients with allergic rhinitis depends on several factors, including age, prominent symptoms, symptom severity, control of allergic rhinitis, patient preferences and cost. Allergen exposure and resulting symptoms vary and treatment adjustment is required. Clinical decision support systems (CDSS) may be beneficial for the assessment of disease control. Clinical decision support systems should be based on the best evidence and algo...

  17. ADDRESSING COMPLEX SPATIAL DECISION PROBLEMS IN MOUNTAINOUS AREAS: THE INTELLIGENT SPATIAL DECISION SUPPORT SYSTEMS (SDSS) APPROACH

    OpenAIRE

    Kostas Tolidis; Efi Dimopoulou

    2012-01-01

    This paper discusses the issue of land use planning and land policy making for mountain regions, considered as regions with specific characteristics (natural, cultural, etc.), but also development constraints. Spatial decision making in such regions is characterized by complexity (semi-structured spatial decision problems) and multiplicity of problems. These indicate the need for qualitative information in support of the decision-making process, in order to improve effectiveness in decision m...

  18. Information visualization in a distributed virtual decision support environment

    Science.gov (United States)

    Blocher, Timothy W.

    2002-07-01

    The visualization of and interaction with decision quality information is critical for effective decision makers in today's data rich environments. The generation and presentation of intuitively meaningful decision support information is the challenge. In order to investigate various visualization approaches to improve the timeliness and quality of Commander decisions, a robust, distributed virtual simulation environment, based on AFRL's Global Awareness Virtual Testbed (GAVTB), is being developed to represent an Air Operations Center (AOC) environment. The powerful Jview visualization technology is employed to efficiently and effectively utilize the simulation products to experiment with various decision quality representations and interactions required by military commanders.

  19. Information visualization to support management decisions

    OpenAIRE

    Jasser Al-Kassab; Zied M. Ouertani; Giovanni Schiuma; Andy Neely

    2014-01-01

    Information visualization can accelerate perception, provide insight and control, and harness this flood of valuable data to gain a competitive advantage in making business decisions. Although such a statement seems to be obvious, there is a lack in the literature of practical evidence of the benefit of information visualization. The main contribution of this paper is to illustrate how, for a major European apparel retailer, the visualization of performance information plays a critical role i...

  20. Decision support modeling for milk valorization

    OpenAIRE

    Banaszewska, A.

    2014-01-01

    The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating FrieslandCampina (FC), which was the fourth largest dairy company in the world at that time. In 2009, a new Milk Valorization & Allocation (MVA) department was created at the corporate level to opt...

  1. TraumaTalk: content-to-speech generation for decision support at point of care.

    OpenAIRE

    Bierner, G.

    1998-01-01

    Communicating information in clinical environments is a crucial concern for medical decision support systems. Some systems can provide this support through text output that can be read by the clinician either from a screen or hard copy. However, speech is often a more appropriate way of conveying information in cases where the decision maker's eyes are already committed to another task or in cases where the telephone is the mode of communication. Some systems synthesize speech directly from t...

  2. Experimental Approach to Effect Estimation of Decision Support Systems

    International Nuclear Information System (INIS)

    Recently human error has been introduced as one of the serious causes of accidents in safety critical systems such as nuclear power plants (NPPs). In order to prevent human errors, many efforts have been made to improve main control room (MCR) interface designs and to develop decision support systems that allow convenient MCR operation and maintenance. For the advanced MCRs, various types of decision support systems have been developed, such as intelligent advisors, alarm systems, computer-based procedures, fault diagnostic systems and computerized decision support systems. It is very important to design highly reliable decision support systems in order to adapt them in actual NPPs. In addition, to evaluate those support systems and validate their efficiency and reliability is as important as to design highly reliable decision support systems, because inappropriate decision support systems or automation systems can cause adverse effects. Research to experimentally estimate a decision support system's impact on the operator's performance has been previously reported in the literature. In most experimental studies, operator performance with decision support systems such as information aid systems is estimated by the quality and accuracy of a diagnostic performance as well as by other various subjective or objective measurements. Subjective methods such as the NASA-Task Load Index (NASATLX) and modified Cooper-Harper (MCH) have been employed to measure the subject's mental workload. In this work, target decision support systems are selected and evaluated by experiments. The target systems are an alarm system, a fault diagnosis system, a computerized procedure system, and an operation validation system. For the experimental evaluation, a prototype was implemented based on a micro-simulator

  3. Decision support for redesigning wastewater treatment technologies.

    Science.gov (United States)

    McConville, Jennifer R; Künzle, Rahel; Messmer, Ulrike; Udert, Kai M; Larsen, Tove A

    2014-10-21

    This paper offers a methodology for structuring the design space for innovative process engineering technology development. The methodology is exemplified in the evaluation of a wide variety of treatment technologies for source-separated domestic wastewater within the scope of the Reinvent the Toilet Challenge. It offers a methodology for narrowing down the decision-making field based on a strict interpretation of treatment objectives for undiluted urine and dry feces and macroenvironmental factors (STEEPLED analysis) which influence decision criteria. Such an evaluation identifies promising paths for technology development such as focusing on space-saving processes or the need for more innovation in low-cost, energy-efficient urine treatment methods. Critical macroenvironmental factors, such as housing density, transportation infrastructure, and climate conditions were found to affect technology decisions regarding reactor volume, weight of outputs, energy consumption, atmospheric emissions, investment cost, and net revenue. The analysis also identified a number of qualitative factors that should be carefully weighed when pursuing technology development; such as availability of O&M resources, health and safety goals, and other ethical issues. Use of this methodology allows for coevolution of innovative technology within context constraints; however, for full-scale technology choices in the field, only very mature technologies can be evaluated. PMID:25225855

  4. Intelligent Information System to support decision making.

    Directory of Open Access Journals (Sweden)

    Kathrin Rodríguez Llanes

    2010-06-01

    Full Text Available Making decisions is complicated in a generalized way, the materials and humans resources of the entity we belong to depends on it, such as the fulfillment of its goals. But when the situations are complex, making decisions turns into a very difficult work, due to the great amount of aspects to consider when making the right choice. To make this efficiently the administration must to consult an important volume of information, which generally, is scattered and in any different formats. That’s why appears the need of developing software that crowd together all that information and be capable of, by using powerful search engines and process algorithms improve the good decisions making process. Considering previous explanation, a complete freeware developed product is proposed, this constitutes a generic and multi-platform solution, that using artificial intelligence techniques, specifically the cases based reasoning, gives the possibility to leaders of any institution or organism of making the right choice in any situation.With client-server architecture, this system is consumed from web as a service and it can be perfectly integrated with a management system or the geographic information system to facilitate the business process.

  5. Decision support system for diabetic retinopathy using discrete wavelet transform.

    Science.gov (United States)

    Noronha, K; Acharya, U R; Nayak, K P; Kamath, S; Bhandary, S V

    2013-03-01

    Prolonged duration of the diabetes may affect the tiny blood vessels of the retina causing diabetic retinopathy. Routine eye screening of patients with diabetes helps to detect diabetic retinopathy at the early stage. It is very laborious and time-consuming for the doctors to go through many fundus images continuously. Therefore, decision support system for diabetic retinopathy detection can reduce the burden of the ophthalmologists. In this work, we have used discrete wavelet transform and support vector machine classifier for automated detection of normal and diabetic retinopathy classes. The wavelet-based decomposition was performed up to the second level, and eight energy features were extracted. Two energy features from the approximation coefficients of two levels and six energy values from the details in three orientations (horizontal, vertical and diagonal) were evaluated. These features were fed to the support vector machine classifier with various kernel functions (linear, radial basis function, polynomial of orders 2 and 3) to evaluate the highest classification accuracy. We obtained the highest average classification accuracy, sensitivity and specificity of more than 99% with support vector machine classifier (polynomial kernel of order 3) using three discrete wavelet transform features. We have also proposed an integrated index called Diabetic Retinopathy Risk Index using clinically significant wavelet energy features to identify normal and diabetic retinopathy classes using just one number. We believe that this (Diabetic Retinopathy Risk Index) can be used as an adjunct tool by the doctors during the eye screening to cross-check their diagnosis. PMID:23662341

  6. Framework for a spatial Decision Support Tool for policy and decision making

    NARCIS (Netherlands)

    Carsjens, G.J.; Chen, W.

    2008-01-01

    The main challenge of developing of a spatial DST (Decision Support Tool) to support the decision making on future livestock production will not be a technical one, but instead a challenge of meeting the con-text requirements of the tool, such as the characteristics of the country-specific spatial p

  7. Development of a decision support tool to facilitate primary care management of patients with abnormal liver function tests without clinically apparent liver disease [HTA03/38/02]. Abnormal Liver Function Investigations Evaluation (ALFIE

    Directory of Open Access Journals (Sweden)

    Sullivan Frank M

    2007-04-01

    Full Text Available Abstract Background Liver function tests (LFTs are routinely performed in primary care, and are often the gateway to further invasive and/or expensive investigations. Little is known of the consequences in people with an initial abnormal liver function (ALF test in primary care and with no obvious liver disease. Further investigations may be dangerous for the patient and expensive for Health Services. The aims of this study are to determine the natural history of abnormalities in LFTs before overt liver disease presents in the population and identify those who require minimal further investigations with the potential for reduction in NHS costs. Methods/Design A population-based retrospective cohort study will follow up all those who have had an incident liver function test (LFT in primary care to subsequent liver disease or mortality over a period of 15 years (approx. 2.3 million tests in 99,000 people. The study is set in Primary Care in the region of Tayside, Scotland (pop approx. 429,000 between 1989 and 2003. The target population consists of patients with no recorded clinical signs or symptoms of liver disease and registered with a GP. The health technologies being assessed are LFTs, viral and auto-antibody tests, ultrasound, CT, MRI and liver biopsy. The study will utilise the Epidemiology of Liver Disease In Tayside (ELDIT database to determine the outcomes of liver disease. These are based on hospital admission data (Scottish Morbidity Record 1, dispensed medication records, death certificates, and examination of medical records from Tayside hospitals. A sample of patients (n = 150 with recent initial ALF tests or invitation to biopsy will complete questionnaires to obtain quality of life data and anxiety measures. Cost-effectiveness and cost utility Markov model analyses will be performed from health service and patient perspectives using standard NHS costs. The findings will also be used to develop a computerised clinical decision

  8. Provider perspectives on electronic decision supports for obesity prevention.

    Science.gov (United States)

    Dryden, Eileen M; Hardin, Jessica; McDonald, Julia; Taveras, Elsie M; Hacker, Karen

    2012-05-01

    Despite the availability of national evidenced-based guidelines related to pediatric obesity screening and prevention, multiple studies have shown that primary care physicians find it difficult to adhere to them or are unfamiliar with them altogether. This article presents physicians' perspectives on the use of electronic decision support tools, an alert and Smart Set, to accelerate the adoption of obesity-related recommendations into their practice. The authors interviewed providers using a test encounter walk-through technique that revealed a number of barriers to using electronic decision supports for obesity care in primary care settings. Providers' suggestions for improving their use of obesity-related decision supports are presented. Careful consideration must be given to both the development of electronic decision support tools and a multilayered educational outreach strategy if providers are going to be persuaded to use such supports to help them implement pediatric obesity prevention and management best practices. PMID:22330047

  9. Research on Development of Corn Production Decision Support System

    Directory of Open Access Journals (Sweden)

    Nan Lin

    2013-07-01

    Full Text Available This research was about the application of decision support system in agriculture. The subject of study was the corn cultivated in Jilin province, northeast of China. The research synthesized expertise and experience on corn cultivation, plant protection, soil and fertilizer, and synthesized agriculture ecology from experts, integrating computer technology, principle of decision support system with corn production knowledge. The research also concerned decision support system for corn fertilization and diagnosis of insect disease and weed harming, which included system concept design, database design, knowledge base design , model base design and preliminary inference engine design according to the characteristics of corn diseases and pests of weeds.  

  10. Prototyping a Rangeland Decision Support System Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This proposal is submitted under the Innovative Tools and Techniques Supporting the Practical Uses of Earth Science Observations topic. We seek to create a...

  11. Decision Support System for Tele-Medical Transportation Management

    OpenAIRE

    M. Gupta; Yadav, S.; Mittal, V; Singh, P.; Saxena, P.

    2011-01-01

    In this paper, a Decision Support System for Management of Tele-Medical Transportation Services has been designed and developed. The system is developed with symbiotic approach to achieve the aim of providing the necessary Quality based Information Resources for real life interaction among Decision Members of Tele-Medical Transportation System to enable speedy decision management by scanning the future. The salient features of the System are: quick and interactive communication, instant conte...

  12. The Intelligent Ventilator Project: Application of Physiological Models in Decision Support

    DEFF Research Database (Denmark)

    Rees, Stephen Edward; Karbing, Dan Stieper; Allerød, Charlotte;

    2011-01-01

    Management of mechanical ventilation in intensive care patients is complicated by conflicting clinical goals. Decision support systems (DSS) may support clinicians in finding the correct balance. The objective of this study was to evaluate a computerized model-based DSS for its advice on inspired...

  13. Assessment of Transport Projects: Risk Analysis and Decision Support

    DEFF Research Database (Denmark)

    Salling, Kim Bang

    2008-01-01

    The subject of this thesis is risk analysis and decision support in the context of transport infrastructure assessment. During my research I have observed a tendency in studies of assessing transport projects of overlooking the substantial amount of uncertainties within the decision making process...... Monte Carlo simulation, being the technique behind the quantitative risk analysis of CBA-DK. The informed decision support is dealt with by a set of resulting accumulated descending graphs (ADG) which makes it possible for decision-makers to come to terms with their risk aversion given a specific...... transport projects, namely by moving from point estimates to interval results. The main focus of this Ph.D. study has been to develop a valid, flexible and functional decision support tool in which risk oriented aspects of project evaluation is implemented. Throughout the study six papers have been produced...

  14. Implications of caries diagnostic strategies for clinical management decisions

    DEFF Research Database (Denmark)

    Baelum, Vibeke; Hintze, Hanne; Wenzel, Ann;

    2012-01-01

    OBJECTIVES: In clinical practice, a visual-tactile caries examination is frequently supplemented by bitewing radiography. This study evaluated strategies for combining visual-tactile and radiographic caries detection methods and determined their implications for clinical management decisions in a...

  15. Cancer diagnostics: decision criteria for marker utilization in the clinic.

    Science.gov (United States)

    Taube, Sheila E; Jacobson, James W; Lively, Tracy G

    2005-01-01

    A new diagnostic tool must pass three major tests before it is adopted for routine clinical use. First, the tool must be robust and reproducible; second, the clinical value of the tool must be proven, i.e. the tool should reliably trigger a clinical decision that results in patient benefit; and, third, the clinical community has to be convinced of the need for this tool and the benefits it affords. Another factor that can influence the adoption of new tools relates to the cost and the vagaries of insurance reimbursement. The Cancer Diagnosis Program (CDP) of the US National Cancer Institute (NCI) launched the Program for the Assessment of Clinical Cancer Tests (PACCT) in 2000 to develop a process for moving the results of new technologies and new understanding of cancer biology more efficiently and effectively into clinical practice. PACCT has developed an algorithm that incorporates the iterative nature of assay development into an evaluation process that includes developers and end users. The effective introduction of new tests into clinical practice has been hampered by a series of common problems that are best described using examples of successes and failures. The successful application of the PACCT algorithm is described in the discussion of the recent development of the OncotypeDX assay and plan for a prospective trial of this assay by the NCI-supported Clinical Trials Cooperative Groups. The assay uses reverse transcription (RT)-PCR evaluation of a set of 16 genes that were shown to strongly associate with the risk of recurrence of breast cancer in women who presented with early stage disease (hormone responsive, and no involvement of the auxiliary lymph nodes). The test is highly reproducible. It provides information to aid the physician and patient in making important clinical decisions, including the aggressiveness of the therapy that should be recommended. A trial is planned to test whether OncotypeDX can be used as a standalone trigger for specific

  16. Intelligent decision technology support in practice

    CERN Document Server

    Neves-Silva, Rui; Jain, Lakhmi; Phillips-Wren, Gloria; Watada, Junzo; Howlett, Robert

    2016-01-01

    This book contains a collection of innovative chapters emanating from topics raised during the 5th KES International Conference on Intelligent Decision Technologies (IDT), held during 2013 at Sesimbra, Portugal. The authors were invited to expand their original papers into a plethora of innovative chapters espousing IDT methodologies and applications. This book documents leading-edge contributions, representing advances in Knowledge-Based and Intelligent Information and Engineering System. It acknowledges that researchers recognize that society is familiar with modern Advanced Information Processing and increasingly expect richer IDT systems. Each chapter concentrates on the theory, design, development, implementation, testing or evaluation of IDT techniques or applications.  Anyone that wants to work with IDT or simply process knowledge should consider reading one or more chapters and focus on their technique of choice. Most readers will benefit from reading additional chapters to access alternative techniq...

  17. Decision support in medical practice: a physician's perspective

    Science.gov (United States)

    Shieh, Yao-Yang; Roberson, Glenn H.

    1998-03-01

    A physician's decision support system consists of three components: (1) a comprehensive patient record and medical knowledge database, (2) information infrastructure for data storage, transfer, and (3) an analytical inference engine, accompanied by business operation database. Medical knowledge database provides the guideline for the selection of powerful clinical features or tests to be observed so that an accurate diagnosis as well as effective treatment can be quickly reached. With a tremendous amount of information stored in multiple data centers, it takes an effective information infrastructure to provide streamlined flow of information to the physician in a timely fashion. A real-time analytical inference engine mimics the physician's reasoning process. However due to incomplete, imperfect data and medical knowledge, a realistic output from this engine will be a list of options with associated confidence level, expected risk, so that the physician can make a well-informed final decision. Physicians are challenged to pursue the objective of ensuring an acceptable quality of care in an economically restrained environment. Therefore, business operation data have to be factored into the calculation of overall loss. Follow-up of diagnosis and treatment provides retrospective assessment of the accuracy and effectiveness of the existing inference engine.

  18. Mobile Contextualized learning games for decision support training

    NARCIS (Netherlands)

    Klemke, Roland

    2014-01-01

    This interactive workshop session introduces mobile serious games as situated, contextualized learning games. Example cases for mobile serious games for decision support training are introduced and discussed. Participants will get to know contextualization techniques used in modern mobile devices a

  19. Mobile Contextualized learning games for decision support training

    NARCIS (Netherlands)

    Klemke, Roland; Börner, Dirk; Suarez, Angel; Schneider, Jan; Antonaci, Alessandra

    2015-01-01

    This interactive workshop session introduces mobile serious games as situated, contextualized learning games. Example cases for mobile serious games for decision support training are introduced and discussed. Participants will get to know contextualization techniques used in modern mobile devices

  20. MODIS-Based Products for Operational Decision Support Systems Project

    Data.gov (United States)

    National Aeronautics and Space Administration — SMH Consulting proposes to develop a web-based decision support system to assist in Rapid Assessment, Monitoring, and Management (RAMM-DSS) on a regional scale. SMH...

  1. Marketing decision support systems: Adoption, use and satisfaction.

    NARCIS (Netherlands)

    Wierenga, B.; Oude Ophuis, P.A.M.

    1997-01-01

    This paper deals with marketing decision support systems (MDSS) in companies. In a conceptual framework five categories of factors are distinguished that potentially affect adoption, use, and satisfaction: external environment factors, organizational factors, task environment factors, user factors a

  2. Marketing Decision Support Systems: Adoption, Use and Satisfaction

    NARCIS (Netherlands)

    B. Wierenga (Berend); P.A.M. Oude Ophuis

    1997-01-01

    textabstractThis paper deals with marketing decision support systems (MDSS) in companies. In a conceptual framework five categories of factors are distinguished that potentially affect adoption, use, and satisfaction: external environment factors, organizational factors, task environment factors, us

  3. Data Mining and Decision Support: An Integrative Approach

    OpenAIRE

    Rupnik, Rok; Kukar, Matjaž

    2010-01-01

    DMDSS is a data mining application system which enables a decision support, based on the knowledge acquired from data mining models and their rules. The mission of DMDSS is to offer an easy-to-use tool which will enable business users to exploit data mining with only a basic level of understanding of the data mining concepts. DMDSS enables the integration of data mining into daily business processes and decision processes through supporting several areas of analyses. The experience of the use...

  4. Clinical Decision Making of Nurses Working in Hospital Settings

    OpenAIRE

    Ida Torunn Bjørk; Hamilton, Glenys A.

    2011-01-01

    This study analyzed nurses' perceptions of clinical decision making (CDM) in their clinical practice and compared differences in decision making related to nurse demographic and contextual variables. A cross-sectional survey was carried out with 2095 nurses in four hospitals in Norway. A 24-item Nursing Decision Making Instrument based on cognitive continuum theory was used to explore how nurses perceived their CDM when meeting an elective patient for the first time. Data were analyzed with d...

  5. Optimizing perioperative decision making: improved information for clinical workflow planning.

    Science.gov (United States)

    Doebbeling, Bradley N; Burton, Matthew M; Wiebke, Eric A; Miller, Spencer; Baxter, Laurence; Miller, Donald; Alvarez, Jorge; Pekny, Joseph

    2012-01-01

    Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40-70% of hospital revenues and 30-40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction. PMID:23304284

  6. Decision support systems for recovery of endangered species

    International Nuclear Information System (INIS)

    The listing of a species as endangered under the Endangered Species Act invokes a suite of responses to help improve conditions for the recovery of that species, to include identification of stressors contributing to population loss, decision analysis of the impacts of proposed recovery options, and implementation of optimal recovery measures. The ability of a decision support system to quantify inherent stressor uncertainties and to identify the key stressors that can be controlled or eliminated becomes key to ensuring the recovery of an endangered species. The listing of the Snake River sockeye, spring/summer chinook, and fall chinook salmon species in the Snake River as endangered provides a vivid example of the importance of sophisticated decision support systems. Operational and physical changes under consideration at eight of the hydroelectric dams along the Columbia and Lower Snake River pose significant financial impacts to a variety of stakeholders involved in the salmon population recovery process and carry significant uncertainties of outcome. A decision support system is presented to assist in the identification of optimal recovery actions for this example that includes the following: creation of datamarts of information on environmental, engineering, and ecological values that influence species survival; incorporation of decision analysis tools to determine optimal decision policies; and the use of geographic information systems (GIS) to provide a context for decision analysis and to communicate the impacts of decision policies

  7. Neural network decision support system for effective decision making in the decision to bid process

    OpenAIRE

    Parvar, Jamshid; Lowe, David; Emsley, Margaret

    2002-01-01

    Important factors in the decision to bid process are identified. A rational and optimal model of decision making for the decision to bid process, which depicts the relationships between these factors and the decision to bid options, is developed. Regression models and neural networks approach are employed to automate the rational and optimal model. Prototyping system development methodology is used as the neural networks system development. The neural networks approach in addition to the abil...

  8. Research of Agile Supply Chain Management Decision Support System

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Agile Supply Chain Management (ASCM) is an important topic and has received much attention recently.ASCM is a new management technology.Agile Supply Chain Management Decision Support System (ASCM-DSS) is presented.Firstly, agile supply chain management technology is introduced.Secondly a decision support system for agile supply chain management is proposed.Then, the implementation of ASCM-DSS in enterprise is discussed.Finally, a fuzzy intelligence decision-making process in Shanghai Turbine Generator Company (STGC) is described in detail.

  9. The analytic hierarchy process as a support for decision making

    Directory of Open Access Journals (Sweden)

    Filipović Milanka

    2007-01-01

    Full Text Available The first part of this text deals with a convention site selection as one of the most lucrative areas in the tourism industry. The second part gives a further description of a method for decision making - the analytic hierarchy process. The basic characteristics: hierarchy constructions and pair wise comparison on the given level of the hierarchy are allured. The third part offers an example of application. This example is solved using the Super - Decision software, which is developed as a computer support for the analytic hierarchy process. This indicates that the AHP approach is a useful tool to help support a decision of convention site selection. .

  10. Supporting contractors' bidding decision: RBF neural networks application

    Science.gov (United States)

    Leśniak, Agnieszka

    2016-06-01

    A bidding decision, despite its being important for the contractor, often needs to be made quickly and within a limited timeframe. To facilitate the contractor's reasoning by limiting randomness that may lead to mistakes decision support models are frequently applied. This paper presents possible applications of an Artificial Neural Network (ANN) to support bidding decisions. The proposed model involving networks with radial basis functions (RBF) was to perform a classification task. On the basis of a set of input data, the network was to suggest either participation in the bid or resignation from it. The results, 93% of correctly classified cases, confirmed the usability of RBF network in solving the problem.

  11. Decision Support for Flood Event Prediction and Monitoring

    DEFF Research Database (Denmark)

    Mioc, Darka; Anton, François; Liang, Gengsheng;

    2007-01-01

    integration, floodplain delineation, and online map interfaces. Our Web-based GIS model can dynamically display observed and predicted flood extents for decision makers and the general public. The users can access Web-based GIS that models current flood events and displays satellite imagery and digital......In this paper the development of Web GIS based decision support system for flood events is presented. To improve flood prediction we developed the decision support system for flood prediction and monitoring that integrates hydrological modelling and CARIS GIS. We present the methodology for data...

  12. Electronic market models for decision support systems on the Web

    Institute of Scientific and Technical Information of China (English)

    谢勇; 王红卫; 费奇

    2004-01-01

    With the prevalence of the Web, most decision-makers are likely to use the Web to support their decision-making. Web-based technologies are leading a major stream of researching decision support systems (DSS). We propose a formal definition and a conceptual framework for Web-based open DSS (WODSS). The formal definition gives an overall view of WODSS, and the conceptual framework based on browser/broker/server computing mode employs the electronic market to mediate decision-makers and providers, and facilitate sharing and reusing of decision resources. We also develop an admitting model, a trading model and a competing model of electronic market in WODSS based on market theory in economics. These models reveal the key mechanisms that drive WODSS operate efficiently.

  13. OPENING COMMENTS TO THE SPECIAL SESSION ON DECISION SUPPORT TOOLS.

    Energy Technology Data Exchange (ETDEWEB)

    SULLIVAN,T.; BARDOS,P.

    2000-06-01

    The emphasis of the session was on the use of decision support tools for actual remediation decisions. It considered two perspectives: site-specific decision making for example choosing a particular remediation system; and remediation in terms of a risk management/risk reduction process as part of a wider process of site management. These were addressed both as general topics and as case studies. Case studies were included to provide information on decision support techniques for specific contamination problems such as remedy selection. In the case studies, the authors present the general process to provide decision support and then discuss the application to a specific problem. The intent of this approach is to provide the interested reader with enough knowledge to determine if the process could be used on their specific set of problems. The general topics included broader issues that are not directly tied to a specific problem. The general topics included papers on the role of stakeholders in the decision process and decision support approaches for sustainable development.

  14. A crisis management decision support system to reduce ingestion dose

    International Nuclear Information System (INIS)

    Environmental accidents such as extensive radioactive or chemical contamination can have more serious consequences for a population than any other kind of accidents known before. Owing to the serious consequences and the high number of people who may be affected, the selection of the best countermeasures to ameliorate the imminent impact is very difficult and the political responsibility is enormous. To help overcome such problems the National Emergency Operations Center in Zurich (Switzerland) has developed a decision support system to evaluate acceptable countermeasures for reducing ingestion dose after an accidental release of radioactive material. The system involves all the necessary modules and techniques for efficient decision making, based on the most recent developments in decision theory as well as the necessary structuring of the decision-making process. The decision-making concept comprehends decision making on two different levels, a technical and a political one. (author)

  15. Decision Support Systems - Technical Prerequisites and Military Requirements

    CERN Document Server

    Tolk, Andreas

    2010-01-01

    Decision Support Systems in the sense of online alternative course of action (ACAO) development and analysis as well as tools for online Development of Doctrine and Tactics Techniques, and Procedures (DTTP) for support to operations make it possible to evaluate and forecast the command and control processes and the performance capabilities of the friendly and enemy forces and other decision relevant factors, support the military commander (brigade and higher) and his staff in their headquarter by increasing their ability to identify own opportunities, support all phases of the command and control process, use computer based, automatic and closed models, that can be adapted to the current situation. Objective of the paper is to present the results of studies conducted in Germany on behalf of the German Ministry of Defense with the objective to work out the conceptual basis for decision support systems and to evaluate, how this technique will influence the command and control system of the army of the federal a...

  16. Decision-making on olympic urban development - multi-actor decision support tool

    NARCIS (Netherlands)

    Heurkens, E.W.T.M.

    Subject of study is the possible organisation of the Olympic Games of 2028 in the Netherlands, as seen from an urban development viewpoint. The project focuses on the decision-making process in the initiative phase. Aim of the project is the development of a decision support tool for the complex, in

  17. Composite decision support by combining cost-benefit and multi-criteria decision

    DEFF Research Database (Denmark)

    Barfod, Michael Bruhn; Salling, Kim Bang; Leleur, Steen

    2011-01-01

    This paper concerns composite decision support based on combining cost-benefit analysis (CBA) with multi-criteria decision analysis (MCDA) for the assessment of economic as well as strategic impacts within transport projects. Specifically a composite model for assessment (COSIMA) is presented as a...

  18. Decision support in psychiatry – a comparison between the diagnostic outcomes using a computerized decision support system versus manual diagnosis

    Directory of Open Access Journals (Sweden)

    Fors Uno GH

    2008-02-01

    Full Text Available Abstract Background Correct diagnosis in psychiatry may be improved by novel diagnostic procedures. Computerized Decision Support Systems (CDSS are suggested to be able to improve diagnostic procedures, but some studies indicate possible problems. Therefore, it could be important to investigate CDSS systems with regard to their feasibility to improve diagnostic procedures as well as to save time. Methods This study was undertaken to compare the traditional 'paper and pencil' diagnostic method SCID1 with the computer-aided diagnostic system CB-SCID1 to ascertain processing time and accuracy of diagnoses suggested. 63 clinicians volunteered to participate in the study and to solve two paper-based cases using either a CDSS or manually. Results No major difference between paper and pencil and computer-supported diagnosis was found. Where a difference was found it was in favour of paper and pencil. For example, a significantly shorter time was found for paper and pencil for the difficult case, as compared to computer support. A significantly higher number of correct diagnoses were found in the diffilt case for the diagnosis 'Depression' using the paper and pencil method. Although a majority of the clinicians found the computer method supportive and easy to use, it took a longer time and yielded fewer correct diagnoses than with paper and pencil. Conclusion This study could not detect any major difference in diagnostic outcome between traditional paper and pencil methods and computer support for psychiatric diagnosis. Where there were significant differences, traditional paper and pencil methods were better than the tested CDSS and thus we conclude that CDSS for diagnostic procedures may interfere with diagnosis accuracy. A limitation was that most clinicians had not previously used the CDSS system under study. The results of this study, however, confirm that CDSS development for diagnostic purposes in psychiatry has much to deal with before it can be

  19. A Cooperative Intelligent Decision Support System for Contingency Management

    Directory of Open Access Journals (Sweden)

    Abdelkader ADLA

    2006-01-01

    Full Text Available Traditional Decision Support Systems (DSS give not enough possibilities of intervention to the user. These systems are reduced to an insular and very technical state in which the objective is not support decision but to dump data on the screen in the hope that the user will know what to do with. In complex situations, decision is not structured and it becomes primordial to design intelligent and cooperative systems allowing a joint resolution of problem based on dynamic sharing of the tasks between the user and the system and according to problems to be solved. In this perspective, we propose a cooperative architecture for intelligent decision support system. The framework embeds expert knowledge within the DSS to provide intelligent DSS using collaboration technologies by putting the decision maker effectively in the loop of the decision process. To this end, we used a structure based on domain and task conceptual modelling. Applicability and relevance of this model are illustrated through a case study where the system and the operator cooperate in decision problem which consists of identifying boiler defects, diagnosing and suggesting actions of cure.

  20. Decision Support Systems (DSS in Construction Tendering Processes

    Directory of Open Access Journals (Sweden)

    Rosmayati Mohemad

    2010-03-01

    Full Text Available The successful execution of a construction project is heavily impacted by making the right decision during tendering processes. Managing tender procedures is very complex and uncertain involving coordination of many tasks and individuals with different priorities and objectives. Bias and inconsistent decision are inevitable if the decision-making process is totally depends on intuition, subjective judgement or emotion. In making transparent decision and healthy competition tendering, there exists a need for flexible guidance tool for decision support. Aim of this paper is to give a review on current practices of Decision Support Systems (DSS technology in construction tendering processes. Current practices of general tendering processes as applied to the most countries in different regions such as United States, Europe, Middle East and Asia are comprehensively discussed. Applications of Web-based tendering processes is also summarised in terms of its properties. Besides that, a summary of Decision Support System (DSS components is included in the next section. Furthermore, prior researches on implementation of DSS approaches in tendering processes are discussed in details. Current issues arise from both of paper-based and Web-based tendering processes are outlined. Finally, conclusion is included at the end of this paper.

  1. Confronting Uncertainty in Life Cycle Assessment Used for Decision Support

    DEFF Research Database (Denmark)

    Herrmann, Ivan Tengbjerg; Hauschild, Michael Zwicky; Sohn, Michael D.;

    2014-01-01

    The aim of this article is to help confront uncertainty in life cycle assessments (LCAs) used for decision support. LCAs offer a quantitative approach to assess environmental effects of products, technologies, and services and are conducted by an LCA practitioner or analyst (AN) to support the...

  2. Education for Medical Decision Support at EuroMISE Centre

    Czech Academy of Sciences Publication Activity Database

    Martinková, Patrícia; Zvára Jr., Karel; Dostálová, T.; Zvárová, Jana

    2013-01-01

    Roč. 1, č. 1 (2013), s. 40-40. ISSN 1805-8698. [EFMI 2013 Special Topic Conference. 17.04.2013-19.04.2013, Prague] Institutional support: RVO:67985807 Keywords : education * decision support * knowledge evaluation * e-learning Subject RIV: IN - Informatics, Computer Science

  3. Developing a Decision Support System: The Software and Hardware Tools.

    Science.gov (United States)

    Clark, Phillip M.

    1989-01-01

    Describes some of the available software and hardware tools that can be used to develop a decision support system implemented on microcomputers. Activities that should be supported by software are discussed, including data entry, data coding, finding and combining data, and data compatibility. Hardware considerations include speed, storage…

  4. A decision-support tool for strategic decision-making in biopharmaceutical manufacture.

    OpenAIRE

    Lim, A.C.

    2005-01-01

    The need for software tools to support decision-making relating to biomanufacture is becoming increasingly critical in order to accelerate the time-to-market and reduce costs. The main objective of this thesis is the design and implementation of a decision-support tool that integrates both the business and process perspectives of biopharmaceutical manufacture to aid the evaluation of manufacturing alternatives. The tool, designated BioPharmKit, was built on the platform of the simulation pack...

  5. Risk Analysis Based Business Rule Enforcement for Intelligent Decision Support

    Science.gov (United States)

    Vasilecas, Olegas; Smaizys, Aidas; Brazinskas, Ramunas

    Intelligent information systems are acting by structured rules and do not deal with possible impact on the business environment or future consequences. That is the main reason why automated decisions based on such rules cannot take responsibility and requires involvement or approval of dedicated business people. This limits decision automation possibilities in information systems. However, business rules describe business policy and represent business logics. This can be used in intelligent information systems, together with risk assessment model to simulate real business environment and evaluate possible impact of automated decisions, to support intelligent decision automation. The chapter proposes risk and business rule model integration to provide full intelligent decision automation model used for business rule enforcement and implementation into intelligent software systems of information systems.

  6. Decision Support Systems: Usage And Applications In Logistics Services

    Directory of Open Access Journals (Sweden)

    Eyüp AKÇETİN

    2014-06-01

    Full Text Available Competitive advantage in logistics operations is possible by analyzing data to create information and turning that information into decision. Supply chain optimization depends on effective management of chain knowledge. Analyzing data from supply chain and making a decision creates complex operations. Therefore, these operations require benefitting from information technology. In today’s global world, businesses use outsourcing for logistics services to focus on their own field, so are seeking to achieve competitive advantage against competitors. Outsourcing requires sharing of various information and data with companies that provide logistical support. Effective strategies are based on well-analyzed the data and information. Best options for right decisions can be created only from good analysis. That’s why companies that supply logistics services achieve competitive advantage using decision support systems (DSS in industrial competition. In short, DSS has become driving force for every business in today’s knowledge-based economy.

  7. Decision Support in Heart Disease Prediction System using Naive Bayes

    Directory of Open Access Journals (Sweden)

    G.Subbalakshmi,

    2011-04-01

    Full Text Available Data Mining refers to using a variety of techniques to identify suggest of information or decision making knowledge in thedatabase and extracting these in a way that they can put to use in areas such as decision support, predictions, forecasting and estimation. The healthcare industry collects huge amounts of healthcare data which, unfortunately, are not “mined” to discover hidden information for effective decision making. Discovering relations that connect variables in a database is the subject of data mining. This research has developed a Decision Support in Heart Disease Prediction System (DSHDPS using data mining modeling technique, namely, Naïve Bayes. Using medical profiles such as age, sex, blood pressure and blood sugar it can predict the likelihood of patients getting a heart disease. It is implemented as web based questionnaire application. It can serve a training tool to train nurses and medical students to diagnose patients with heart disease.

  8. Personalised Multi-Criterial Online Decision Support for Siblings Considering Stem Cell Donation: An Interactive Aid.

    Science.gov (United States)

    Kaltoft, Mette Kjer; Salkeld, Glenn; Dowie, Jack

    2016-01-01

    Person-centred decision support combines the best available information on the considerations that matter to the individual, with the importance the person attaches to those considerations. Nurses and other health professionals can benefit from being able to draw on this support within a clinical conversation. A case study and storyline on four siblings facing a transplant coordinator's call to donate stem cells to their brother [1] is 'translated' and used to demonstrate how an interactive multi-criteria aid can be developed for each within a conversational mode. The personalized dialogue and decision aid are accessible online for interaction. Each sibling's decision exemplifies the communication including physical and psychosocial complexities within any decision cascade from call-to-test and to donate, if compatible. A shared template can embrace the informational and ethical aspects of a decision. By interactive decision support within a clinical conversation, each stakeholder can gain a personalised opinion, as well as increased generic health decision literacy [2]. PMID:27332459

  9. Decision Making Based On Management Information System and Decision Support System

    Directory of Open Access Journals (Sweden)

    Şükrü Ada

    2015-04-01

    Full Text Available Information hasbecome an essentialresource for managing modern organizations. This is so because today’sbusiness environment is volatile, dynamic, turbulent and necessitates the burgeoning demand for accurate, relevant, complete,timely and economical information needed to drive the decision-making process in order to accentuate organizational abilities to manage opportunities and threat. MIS work on online mode with an average processing speed. Generally, it is used by low level management. Decision support system are powerful tool that assist corporate executives, administrators and other senior officials in making decision regarding the problem. Management Information Systems is a useful tool that provided organized and summarized information in a proper time to decision makers and enable making accurate decision for managers in organizations. This paper will discuss the concept, characteristics, types of MIS, the MIS model, and in particular it will highlight the impact and role of MIS on decision making.

  10. Healthcare Decision Support System for Administration of Chronic Diseases

    OpenAIRE

    Woo, Ji-In; Yang, Jung-Gi; Lee, Young-Ho; Kang, Un-Gu

    2014-01-01

    Objectives A healthcare decision-making support model and rule management system is proposed based on a personalized rule-based intelligent concept, to effectively manage chronic diseases. Methods A Web service was built using a standard message transfer protocol for interoperability of personal health records among healthcare institutions. An intelligent decision service is provided that analyzes data using a service-oriented healthcare rule inference function and machine-learning platform; ...

  11. Application of Decision Support System in E-commerce

    OpenAIRE

    M.Senthil Velmurugan; Kogilah Narayanasamy

    2008-01-01

    Electronic commerce (EC) has the potential to improve efficiency and productivity in business activities. E-commerce today is no longer technological issue, but is also a business issue. A decision support system (DSS) is “an interactive information system that provides information, models and data manipulation tools to help make decisions in semi-structured and unstructured situations. E-commerce involves a number of forms, varying level of cost and complexity, depending on business need. T...

  12. Decision support database system for Hellenic Naval Personnel Management

    OpenAIRE

    Makris, Antonios K.

    1988-01-01

    The Naval Officers Personnel Management System is a very complex system especially inside the Fleet Command. Managing the system manually is neither effective nor efficient in supporting the decision makers. This thesis proposes a method to use a computer based information processing system to help decision makers in scheduling the assignment of officers to warships during the annual assignment process, as well as in other functions concerning personnel management. The thesis presents a decis...

  13. Decision support system for the operating room rescheduling problem

    OpenAIRE

    Essen, van, A.M.; Hurink, J.L.; Hartholt, Woutske; Akker, van den, J.M.

    2012-01-01

    Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three...

  14. New threats and new challenges for radiological decision support

    DEFF Research Database (Denmark)

    Andersson, Kasper Grann; Astrup, Poul; Mikkelsen, Torben;

    2011-01-01

    It is described how ongoing work will extend European standard decision support systems currently integrated in the nuclear power plant preparedness in many countries, to enable estimation of the radiological consequences of atmospheric dispersion of contaminants following a terror attack in a city....... Factors relating to the contaminant release processes, dispersion, deposition and post deposition migration are discussed, and non-radiological issues are highlighted in relation to decision making....

  15. Decision Support Systems in the Process of Improving Patient Safety

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan; Zvárová, Jana

    Hershey : IGI Global, 2013 - (Moumtzoglou, A.; Kastania, A.), s. 71-83 ISBN 978-1-4666-2657-7 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : health care * decision making * patient safety * design and implementation * classification analysis * high-dimensional data Subject RIV: BB - Applied Statistics, Operational Research http://www.igi-global.com/chapter/decision-support-systems-process-improving/73105

  16. Exploring the impact of a decision support intervention on vascular access decisions in chronic hemodialysis patients: study protocol

    Directory of Open Access Journals (Sweden)

    Donnelly Sandra

    2011-02-01

    Full Text Available Abstract Background In patients with Stage 5 Chronic Kidney Disease who require renal replacement therapy a major decision concerns modality choice. However, many patients defer the decision about modality choice or they have an urgent or emergent need of RRT, which results in them starting hemodialysis with a Central Venous Catheter. Thereafter, efforts to help patients make more timely decisions about access choices utilizing education and resource allocation strategies met with limited success resulting in a high prevalent CVC use in Canada. Providing decision support tailored to meet patients' decision making needs may improve this situation. The Registered Nurses Association of Ontario has developed a clinical practice guideline to guide decision support for adults living with Chronic Kidney Disease (Decision Support for Adults with Chronic Kidney Disease. The purpose of this study is to determine the impact of implementing selected recommendations this guideline on priority provincial targets for hemodialysis access in patients with Stage 5 CKD who currently use Central Venous Catheters for vascular access. Methods/Design A non-experimental intervention study with repeated measures will be conducted at St. Michaels Hospital in Toronto, Canada. Decisional conflict about dialysis access choice will be measured using the validated SURE tool, an instrument used to identify decisional conflict. Thereafter a tailored decision support intervention will be implemented. Decisional conflict will be re-measured and compared with baseline scores. Patients and staff will be interviewed to gain an understanding of how useful this intervention was for them and whether it would be feasible to implement more widely. Quantitative data will be analyzed using descriptive and inferential statistics. Statistical significance of difference between means over time for aggregated SURE scores (pre/post will be assessed using a paired t-test. Qualitative analysis

  17. Data Mining for Education Decision Support: A Review

    Directory of Open Access Journals (Sweden)

    Suhirman Suhirman

    2014-12-01

    Full Text Available Management of higher education must continue to evaluate on an ongoing basis in order to improve the quality of institutions. This will be able to do the necessary evaluation of various data, information, and knowledge of both internal and external institutions. They plan to use more efficiently the collected data, develop tools so that to collect and direct management information, in order to support managerial decision making. The collected data could be utilized to evaluate quality, perform analyses and diagnoses, evaluate dependability to the standards and practices of curricula and syllabi, and suggest alternatives in decision processes. Data minings to support decision making are well suited methods to provide decision support in the education environments, by generating and presenting relevant information and knowledge towards quality improvement of education processes. In educational domain, this information is very useful since it can be used as a base for investigating and enhancing the current educational standards and managements. In this paper, a review on data mining for academic decision support in education field is presented. The details of this paper will review on recent data mining in educational field and outlines future researches in educational data mining.

  18. Clinical Decision Making among Dental Students and General Practitioners.

    Science.gov (United States)

    Grembowski, David; And Others

    1989-01-01

    Senior dental students and family dental practitioners were surveyed concerning their choice of pairs of alternative treatments and the technical and patient factors influencing their decisions. Greater agreement in clinical decision-making was found among dentists than among students for all four pairs of alternative services. (MSE)

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

    Directory of Open Access Journals (Sweden)

    White Martha

    2007-03-01

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

  20. Decision Support Systems for Research and Management in Advanced Life Support

    Science.gov (United States)

    Rodriquez, Luis F.

    2004-01-01

    Decision support systems have been implemented in many applications including strategic planning for battlefield scenarios, corporate decision making for business planning, production planning and control systems, and recommendation generators like those on Amazon.com(Registered TradeMark). Such tools are reviewed for developing a similar tool for NASA's ALS Program. DSS are considered concurrently with the development of the OPIS system, a database designed for chronicling of research and development in ALS. By utilizing the OPIS database, it is anticipated that decision support can be provided to increase the quality of decisions by ALS managers and researchers.

  1. Integration of emergency data management and decision support systems

    International Nuclear Information System (INIS)

    Integrated Emergency Data Management and Decision Support System for Nuclear Emergencies (EDMDSS) is being developed by the Institute of Atomic Energy (IAE) under supervision of the National Atomic Energy Agency (NAEA), as a part of an overall National Safety System for Poland. Organisational features and technical capacities for radiological data acquisition are presented, and their evaluation for assessment of current radiological situation in Poland is discussed. Transboundary data exchange and a concept of an integrated national system for emergency data acquisition and management is proposed. A radiological situation prediction and decision support system is described. (author)

  2. Novel applications of intuitionistic fuzzy digraphs in decision support systems.

    Science.gov (United States)

    Akram, Muhammad; Ashraf, Ather; Sarwar, Mansoor

    2014-01-01

    Many problems of practical interest can be modeled and solved by using graph algorithms. In general, graph theory has a wide range of applications in diverse fields. In this paper, the intuitionistic fuzzy organizational and neural network models, intuitionistic fuzzy neurons in medical diagnosis, intuitionistic fuzzy digraphs in vulnerability assessment of gas pipeline networks, and intuitionistic fuzzy digraphs in travel time are presented as examples of intuitionistic fuzzy digraphs in decision support system. We have also designed and implemented the algorithms for these decision support systems. PMID:25045752

  3. The Intelligent Decision Support System Model of SARS

    Institute of Scientific and Technical Information of China (English)

    ZhouXingyu; ZhangJiang; LiuYang; XieYanqing; ZhangRan; ZhaoYang; HeZhongxiong

    2004-01-01

    Based on the intelligent decision support system, a new method was presented to defense the catastrophic infectious disease such as SARS, Bird Flu, etc.. By using All Set theory, the decision support system (DSS) model can be built to analyze the noise information and forecast the trend of the catastrophe then to give the method or policy to defend the disease. The model system is composed of four subsystems: the noise analysis subsystem, forecast and simulation subsystem, diagnosis subsystem and second recovery subsystem. They are discussed briefly in this paper. This model can be used not only for SARS but also for other paroxysmal accidences.

  4. Decision support system for structure synthesis of monitoring systems

    Directory of Open Access Journals (Sweden)

    Skatkov A. V.

    2008-04-01

    Full Text Available The paper is concerned with a structure synthesis of monitoring systems. In the article a decision support system for such synthesis was proposed and described. In the first phase of the process, the proposed classification of monitoring systems is used. Then adaptive algorithms, simulation and analytic modeling are used. The results of studies carried out by means of the proposed program are represented. The topicality of proposed approach was demonstrated. It should be mentioned, that algorithms were thoroughly described, the computing experiments were carried out. The authors believe that the proposed decision support system has many advantages and, consequently, is very useful in structure synthesis of monitoring systems.

  5. Verification and validation of decision support Expert Systems

    International Nuclear Information System (INIS)

    Expert Systems are being designed or considered for both on-line process control and off-line decision support in the handling of hazardous materials. There are possibilities for both positive and negative impacts on chemical industry fire/explosion loss potentials. The authors review some guidelines and tools available for the verification and validation (V and V) of expert systems. Finally, they illustrate some of the points discussed by describing the development of a prototype expert system for hazardous materials classification and loss prevention engineering decision support

  6. Decision Support System for Diabetes Mellitus through Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Tarik A. Rashid

    2016-07-01

    Full Text Available recently, the diseases of diabetes mellitus have grown into extremely feared problems that can have damaging effects on the health condition of their sufferers globally. In this regard, several machine learning models have been used to predict and classify diabetes types. Nevertheless, most of these models attempted to solve two problems; categorizing patients in terms of diabetic types and forecasting blood surge rate of patients. This paper presents an automatic decision support system for diabetes mellitus through machine learning techniques by taking into account the above problems, plus, reflecting the skills of medical specialists who believe that there is a great relationship between patient’s symptoms with some chronic diseases and the blood sugar rate. Data sets are collected from Layla Qasim Clinical Center in Kurdistan Region, then, the data is cleaned and proposed using feature selection techniques such as Sequential Forward Selection and the Correlation Coefficient, finally, the refined data is fed into machine learning models for prediction, classification, and description purposes. This system enables physicians and doctors to provide diabetes mellitus (DM patients good health treatments and recommendations.

  7. Data warehouse based decision support system in nuclear power plants

    International Nuclear Information System (INIS)

    Safety is an important element in business decision making processes in nuclear power plants. Information about component reliability, structures and systems, data recorded during the nuclear power plant's operation and outage periods, as well as experiences from other power plants are located in different database systems throughout the power plant. It would be possible to create a decision support system which would collect data, transform it into a standardized form and store it in a single location in a format more suitable for analyses and knowledge discovery. This single location where the data would be stored would be a data warehouse. Such data warehouse based decision support system could help make decision making processes more efficient by providing more information about business processes and predicting possible consequences of different decisions. Two main functionalities in this decision support system would be an OLAP (On Line Analytical Processing) and a data mining system. An OLAP system would enable the users to perform fast, simple and efficient multidimensional analysis of existing data and identify trends. Data mining techniques and algorithms would help discover new, previously unknown information from the data as well as hidden dependencies between various parameters. Data mining would also enable analysts to create relevant prediction models that could predict behaviour of different systems during operation and inspection results during outages. The basic characteristics and theoretical foundations of such decision support system are described and the reasons for choosing a data warehouse as the underlying structure are explained. The article analyzes obvious business benefits of such system as well as potential uses of OLAP and data mining technologies. Possible implementation methodologies and problems that may arise, especially in the field of data integration, are discussed and analyzed.(author)

  8. E-DECIDER Decision Support Gateway For Earthquake Disaster Response

    Science.gov (United States)

    Glasscoe, M. T.; Stough, T. M.; Parker, J. W.; Burl, M. C.; Donnellan, A.; Blom, R. G.; Pierce, M. E.; Wang, J.; Ma, Y.; Rundle, J. B.; Yoder, M. R.

    2013-12-01

    Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) is a NASA-funded project developing capabilities for decision-making utilizing remote sensing data and modeling software in order to provide decision support for earthquake disaster management and response. E-DECIDER incorporates earthquake forecasting methodology and geophysical modeling tools developed through NASA's QuakeSim project in order to produce standards-compliant map data products to aid in decision-making following an earthquake. Remote sensing and geodetic data, in conjunction with modeling and forecasting tools, help provide both long-term planning information for disaster management decision makers as well as short-term information following earthquake events (i.e. identifying areas where the greatest deformation and damage has occurred and emergency services may need to be focused). E-DECIDER utilizes a service-based GIS model for its cyber-infrastructure in order to produce standards-compliant products for different user types with multiple service protocols (such as KML, WMS, WFS, and WCS). The goal is to make complex GIS processing and domain-specific analysis tools more accessible to general users through software services as well as provide system sustainability through infrastructure services. The system comprises several components, which include: a GeoServer for thematic mapping and data distribution, a geospatial database for storage and spatial analysis, web service APIs, including simple-to-use REST APIs for complex GIS functionalities, and geoprocessing tools including python scripts to produce standards-compliant data products. These are then served to the E-DECIDER decision support gateway (http://e-decider.org), the E-DECIDER mobile interface, and to the Department of Homeland Security decision support middleware UICDS (Unified Incident Command and Decision Support). The E-DECIDER decision support gateway features a web interface that

  9. Requirements for and limitations on designing decision support systems

    International Nuclear Information System (INIS)

    Decision Support Systems (DSS), which combine the capabilities of modern computers and human skills in solving complex ill-structured problems of organizational management, has been created as an evolution and development of Decision Theory, Management Information Systems and Data Base Management Systems. The DSS help users to formulate and analyze decision alternatives in a number of ways by making use of objective and subjective data, models, knowledge. The main components of a conceptual DSS model are 'user-system' interface, block of problem analysis and structuring, decision-making block, data base, model base, and knowledge base. The 'user-system' interface contains facilities for generating and controlling the dialogue. The blocks of problem analysis and decision-making incorporate procedures and methods which help formulate the problem, analyze approaches to its solution, and generate the result by making use of the data, model and knowledge bases. The preliminary analysis and structuring of the problem are carried out either by the decision maker alone or jointly with a skilled consultant-analyst. The ability to conceive the structure of a problem correctly is an art reinforced by experience and intuition. The complexity of even a preliminary analysis, and the presence of numerous ill-defined factors, set a number of requirements to DSS. An effective decision-making depends on both the harmony of decision-maker and consultant efforts and the DSS capacities. Problems arising in designing each of DSS blocks and examples of its successful implementation are considered in paper. At the early stages of its development DSS was treated as a computer-based facility for assisting in processing huge amounts of data with rigidly assigned models and in presenting decision results. It was explicitly assumed that the problem solved was sufficiently clear and understandable. We believe, the major purpose of the next generation of DSS must be: assistance in providing for

  10. Technology Infusion Challenges from a Decision Support Perspective

    Science.gov (United States)

    Adumitroaie, V.; Weisbin, C. R.

    2009-01-01

    In a restricted science budget environment and increasingly numerous required technology developments, the technology investment decisions within NASA are objectively more and more difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Under these conditions it is rationally desirable to build an investment portfolio, which has the highest possible technology infusion rate. Arguably the path to infusion is subject to many influencing factors, but here only the challenges associated with the very initial stages are addressed: defining the needs and the subsequent investment decision-support process. It is conceivable that decision consistency and possibly its quality suffer when the decision-making process has limited or no traceability. This paper presents a structured decision-support framework aiming to provide traceable, auditable, infusion- driven recommendations towards a selection process in which these recommendations are used as reference points in further discussions among stakeholders. In this framework addressing well-defined requirements, different measures of success can be defined based on traceability to specific selection criteria. As a direct result, even by using simplified decision models the likelihood of infusion can be probed and consequently improved.

  11. Decision support model for introduction of gamification solution using AHP.

    Science.gov (United States)

    Kim, Sangkyun

    2014-01-01

    Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform. PMID:24892075

  12. Decision Support Model for Introduction of Gamification Solution Using AHP

    Directory of Open Access Journals (Sweden)

    Sangkyun Kim

    2014-01-01

    Full Text Available Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.

  13. An object-oriented approach to site characterization decision support

    International Nuclear Information System (INIS)

    Effective decision support for site characterization is key to determining the nature and extent of contamination and the associated human and environmental risks. Site characterization data, however, present particular problems to technical analysts and decision-makers. Such data are four dimensional, incorporating temporal and spatial components. Their sheer volume can be daunting -- sites with hundreds of monitoring wells and thousands of samples sent for laboratory analyses are not uncommon. Data are derived from a variety of sources including laboratory analyses, non-intrusive geophysical surveys, historical information, bore logs, in-field estimates of key physical parameters such as aquifer transmissivity, soil moisture content, depth-to-water table, etc. Ultimately, decisions have to be made based on data that are always incomplete, often confusing, inaccurate, or inappropriate, and occasionally wrong. In response to this challenge, two approaches to environmental decision support have arisen, Data Quality Objectives (DQOS) and the Observational Approach (OA). DQOs establish criteria for data collection by clearly defining the decisions that need to be made, the uncertainty that can be tolerated, and the type and amount of data that needs to be collected to satisfy the uncertainty requirements. In practice, DQOs are typically based on statistical measures. The OA accepts the fact that the process of characterizing and remediating contaminated sites is always uncertain. Decision-making with the OA is based on what is known about a site, with contingencies developed for potential future deviations from the original assumptions about contamination nature, extent, and risks posed

  14. Simulation-based decision support for evaluating operational plans

    Directory of Open Access Journals (Sweden)

    Johan Schubert

    2015-12-01

    Full Text Available In this article, we describe simulation-based decision support techniques for evaluation of operational plans within effects-based planning. Using a decision support tool, developers of operational plans are able to evaluate thousands of alternative plans against possible courses of events and decide which of these plans are capable of achieving a desired end state. The objective of this study is to examine the potential of a decision support system that helps operational analysts understand the consequences of numerous alternative plans through simulation and evaluation. Operational plans are described in the effects-based approach to operations concept as a set of actions and effects. For each action, we examine several different alternative ways to perform the action. We use a representation where a plan consists of several actions that should be performed. Each action may be performed in one of several different alternative ways. Together these action alternatives make up all possible plan instances, which are represented as a tree of action alternatives that may be searched for the most effective sequence of alternative actions. As a test case, we use an expeditionary operation with a plan of 43 actions and several alternatives for these actions, as well as a scenario of 40 group actors. Decision support for planners is provided by several methods that analyze the impact of a plan on the 40 actors, e.g., by visualizing time series of plan performance. Detailed decision support for finding the most influential actions of a plan is presented by using sensitivity analysis and regression tree analysis. Finally, a decision maker may use the tool to determine the boundaries of an operation that it must not move beyond without risk of drastic failure. The significant contribution of this study is the presentation of an integrated approach for evaluation of operational plans.

  15. Neuro computing in knowledge-based decision support systems

    International Nuclear Information System (INIS)

    Knowledge-based decision support systems of today are due to development of many decades. More and more methodologies and application areas have been involved during this time. In this paper neural methods are combined with knowledge-based methodologies. Self-Organizing Map (SOM) is used together with rule-based reasoning, and realized in a prototype of a decision support system. This system, which can be used e.g. in fault diagnosis, is based on an earlier study including compatibility analysis. A Matlab-based tool is capable of doing tasks in fault detection and identification. We show with an example how SOM analysis can help decision making in a computerized decision support system. Quantisation error between normal data and error data is one important methodological tool in this analysis. This kind of decision making is needed for instance in control room in state monitoring of a safety critical process in industry. A scenario about a leak in the primary circuit of a BWR nuclear power plant is also shortly demonstrated. (Author)

  16. Knowledge Management Technology for Decision Support: an empirical examination

    Directory of Open Access Journals (Sweden)

    Meliha Handzic

    2001-11-01

    Full Text Available This paper reports the results of an empirical examination of the effectiveness of one type of knowledge management technology, namely 'contextual knowledge repository', for supporting individual decision makers in a predictive judgement task context. 31 volunteer subjects participated in the study. The results indicate that a given technology was fairly useful, but insufficient to maximally enhance individual decision making. On one hand, subjects were found to extract more knowledge and make significantly smaller decision errors than their notional naive counterparts. On the other hand, subjects tended to extract less knowledge and make significantly larger decision errors compared to notional optimal counterparts. These findings suggest that individuals could potentially benefit from those knowledge management technologies that would provide additional explicit analytical and procedural knowledge, or those that would facilitate sharing of tacit knowledge through interaction with others. Future research is necessary to address these issues.

  17. Breast cancer therapy planning - a novel support concept for a sequential decision making problem.

    Science.gov (United States)

    Scherrer, Alexander; Schwidde, Ilka; Dinges, Andreas; Rüdiger, Patrick; Kümmel, Sherko; Küfer, Karl-Heinz

    2015-09-01

    Breast cancer is the most common carcinosis with the largest number of mortalities in women. Its therapy comprises a wide spectrum of different treatment modalities a breast oncologist decides about for the individual patient case. These decisions happen according to medical guide lines, current scientific publications and experiences acquired in former cases. Clinical decision making therefore involves the time-consuming search for possible therapy options and their thorough testing for applicability to the current patient case.This research work addresses breast cancer therapy planning as a multi-criteria sequential decision making problem. The approach is based on a data model for patient cases with therapy descriptions and a mathematical notion for therapeutic relevance of medical information. This formulation allows for a novel decision support concept, which targets at eliminating observed weaknesses in clinical routine of breast cancer therapy planning. PMID:25315184

  18. Driving and dementia: a clinical decision pathway

    OpenAIRE

    Carter, Kirsty; Monaghan, Sophie; O'Brien, John; Teodorczuk, Andrew; Mosimann, Urs; Taylor, John-Paul

    2014-01-01

    Objective This study aimed to develop a pathway to bring together current UK legislation, good clinical practice and appropriate management strategies that could be applied across a range of healthcare settings. Methods The pathway was constructed by a multidisciplinary clinical team based in a busy Memory Assessment Service. A process of successive iteration was used to develop the pathway, with input and refinement provided via survey and small group meetings with individuals from a wide ra...

  19. Driving and dementia: a clinical decision pathway

    OpenAIRE

    Carter, Kirsty; Monaghan, Sophie; O'Brien, John; Teodorczuk, Andrew; Mosimann, Urs Peter; Taylor, John-Paul

    2014-01-01

    OBJECTIVE This study aimed to develop a pathway to bring together current UK legislation, good clinical practice and appropriate management strategies that could be applied across a range of healthcare settings. METHODS The pathway was constructed by a multidisciplinary clinical team based in a busy Memory Assessment Service. A process of successive iteration was used to develop the pathway, with input and refinement provided via survey and small group meetings with individuals fr...

  20. Clinical Decision Making in Renal Pain Management

    OpenAIRE

    Aganovic, Damir; Prcic, Alen; Kulovac, Benjamin; Hadziosmanovic, Osman

    2012-01-01

    Objectives: To determine the optimal medication for the treatment of renal colic using evidence based medicine (EBM) parameters (RR, ARR, NNT, NNH, ARI, RRI). Sample and Methodology: During 2010, an ITT study was conducted on 400 outpatients of the Sarajevo University Clinical Center Urology Clinic in order to investigate renal colic pain relief drugs. Each group consisting of 100 patients was administered either Metamizol amp. i.v., or Diclofenac amp. i.m., or Butylscopolamine amp. i.v., whi...

  1. Leveraging Expert Knowledge to Improve Machine-Learned Decision Support Systems

    OpenAIRE

    Kuusisto, Finn; Dutra, Inês; Elezaby, Mai; Mendonça, Eneida A.; Shavlik, Jude; Burnside, Elizabeth S.

    2015-01-01

    While the use of machine learning methods in clinical decision support has great potential for improving patient care, acquiring standardized, complete, and sufficient training data presents a major challenge for methods relying exclusively on machine learning techniques. Domain experts possess knowledge that can address these challenges and guide model development. We present Advice-Based-Learning (ABLe), a framework for incorporating expert clinical knowledge into machine learning models, a...

  2. Impact of a decision-support tool on decision making at the district level in Kenya

    OpenAIRE

    Nutley, Tara; McNabb, Sarah; Salentine, Shannon

    2013-01-01

    Background In many countries, the responsibility for planning and delivery of health services is devolved to the subnational level. Health programs, however, often fall short of efficient use of data to inform decisions. As a result, programs are not as effective as they can be at meeting the health needs of the populations they serve. In Kenya, a decision-support tool, the District Health Profile (DHP) tool was developed to integrate data from health programs, primarily HIV, at the district ...

  3. Improving Clinical Decisions on T2DM Patients Integrating Clinical, Administrative and Environmental Data.

    Science.gov (United States)

    Segagni, Daniele; Sacchi, Lucia; Dagliati, Arianna; Tibollo, Valentina; Leporati, Paola; De Cata, Pasqale; Chiovato, Luca; Bellazzi, Riccardo

    2015-01-01

    This work describes an integrated informatics system developed to collect and display clinically relevant data that can inform physicians and researchers about Type 2 Diabetes Mellitus (T2DM) patient clinical pathways and therapy adherence. The software we developed takes data coming from the electronic medical record (EMR) of the IRCCS Fondazione Maugeri (FSM) hospital of Pavia, Italy, and combines the data with administrative, pharmacy drugs (purchased from the local healthcare agency (ASL) of the Pavia area), and open environmental data of the same region. By using different use cases, we explain the importance of gathering and displaying the data types through a single informatics tool: the use of the tool as a calculator of risk factors and indicators to improve current detection of T2DM, a generator of clinical pathways and patients' behaviors from the point of view of the hospital care management, and a decision support tool for follow-up visits. The results of the performed data analysis report how the use of the dashboard displays meaningful clinical decisions in treating complex chronic diseases and might improve health outcomes. PMID:26262138

  4. Risk perception and clinical decision making in primary care

    DEFF Research Database (Denmark)

    Barfoed, Benedicte Marie Lind

    2015-01-01

    Objectives We aim to present new knowledge about different perspectives of health care professionals’ risk perceptions and clinical decision making. Furthermore, we intend to discuss differences between professional and personal risk perceptions and the impact on decisions in terms of both short...... considerations and the specific context. Most research has been focused on understanding of the concepts of risk. However healthcare professionals’ risk perception and personal attitudes also affect their clinical decision-making and risk communication. The differences between health care professionals’ personal...... and professional risk perception and attitudes and the subsequent impact on patients’ decision making have not previously been discussed. Content 1. Peder Halvorsen, MD, Professor, General Practice, Department of Community Medicine, The Arctic University of Norway: Making good decisions: Intuition or...

  5. Pricing Decision Support System for Generation Companies in Electricity Market

    Institute of Scientific and Technical Information of China (English)

    FangDebin; WangXianjia

    2005-01-01

    In order to meet the requirement of separating power plants from power network and that of the competition based power transaction in power market, the pricing decision support system for generation companies (GCPDSS) is built in electricity market. This paper introduces the conception of intelligent decision support system (IDSS) and puts emphasis on the systematical structural framework,work process, design principal, and fundamental function of GCPDSS. The system has the module to analyze the cost, to forecast the demand of power, to construct the pricing strategies, to manage the pricing risk, and to dispatch giving the pricing strategies.The case study illustrates that the friendly window-based user interface of the system enables the user to take full advantage of the capabilities of the system in order to make effective real-time decisions.

  6. Model-based decision support in diabetes care.

    Science.gov (United States)

    Salzsieder, E; Vogt, L; Kohnert, K-D; Heinke, P; Augstein, P

    2011-05-01

    The model-based Karlsburg Diabetes Management System (KADIS®) has been developed as a patient-focused decision-support tool to provide evidence-based advice for physicians in their daily efforts to optimize metabolic control in diabetes care of their patients on an individualized basis. For this purpose, KADIS® was established in terms of a personalized, interactive in silico simulation procedure, implemented into a problem-related diabetes health care network and evaluated under different conditions by conducting open-label mono- and polycentric trials, and a case-control study, and last but not least, by application in routine diabetes outpatient care. The trial outcomes clearly show that the recommendations provided to the physicians by KADIS® lead to significant improvement of metabolic control. This model-based decision-support system provides an excellent tool to effectively guide physicians in personalized decision-making to achieve optimal metabolic control for their patients. PMID:20621384

  7. Behavior-aware decision support systems : LDRD final report.

    Energy Technology Data Exchange (ETDEWEB)

    Hirsch, Gary B.; Homer, Jack (Homer Consulting); Chenoweth, Brooke N.; Backus, George A.; Strip, David R.

    2007-11-01

    As Sandia National Laboratories serves its mission to provide support for the security-related interests of the United States, it is faced with considering the behavioral responses that drive problems, mitigate interventions, or lead to unintended consequences. The effort described here expands earlier works in using healthcare simulation to develop behavior-aware decision support systems. This report focuses on using qualitative choice techniques and enhancing two analysis models developed in a sister project.

  8. Data assimilation in the decision support system RODOS

    DEFF Research Database (Denmark)

    Rojas-Palma, C.; Madsen, H.; Gering, F.; Puch, R.; Turcanu, C.; Astrup, P.; Müller, H.; Richter, K.; Zheleznyak, M.; Treebushny, D.; Kolomeev, M.; Kamaev, D.; Wynn, H.

    2003-01-01

    . The process of combining model predictions and observations, usually referred to as data assimilation, is described in this article within the framework of the real time on-line decision support system (RODOS) for off-site nuclear emergency management in Europe. Data assimilation capabilities, based...

  9. Team Machine: A Decision Support System for Team Formation

    Science.gov (United States)

    Bergey, Paul; King, Mark

    2014-01-01

    This paper reports on the cross-disciplinary research that resulted in a decision-support tool, Team Machine (TM), which was designed to create maximally diverse student teams. TM was used at a large United States university between 2004 and 2012, and resulted in significant improvement in the performance of student teams, superior overall balance…

  10. Making Risk Models Operational for Situational Awareness and Decision Support

    International Nuclear Information System (INIS)

    We present CARIM, a decision support tool to aid in the evaluation of plans for converting control systems to digital instruments. The model provides the capability to optimize planning and resource allocation to reduce risk from multiple safety and economic perspectives. (author)

  11. Explanation of Probabilistic Inference for Decision Support Systems

    OpenAIRE

    Elsaesser, Christopher

    2013-01-01

    An automated explanation facility for Bayesian conditioning aimed at improving user acceptance of probability-based decision support systems has been developed. The domain-independent facility is based on an information processing perspective on reasoning about conditional evidence that accounts both for biased and normative inferences. Experimental results indicate that the facility is both acceptable to naive users and effective in improving understanding.

  12. Decision support for optimising energy consumption in European greenhouses

    NARCIS (Netherlands)

    Korner, O.; Warner, D.; Tzilivakis, J.; Eveleens-Clark, B.A.; Heuvelink, E.

    2008-01-01

    Improving existing greenhouse structures in terms of insulation and other features can save energy with significantly lower investment costs than building new greenhouses. Within the EU Framework VI project GREENERGY a decision support system has been developed that offers the potential to be used b

  13. PROBLEM DESCRIPTIONS FOR THE DECISION SUPPORT SOFTWARE DEMONSTRATION

    Energy Technology Data Exchange (ETDEWEB)

    SULLIVAN,T.; ARMSTRONG,A.; OSLEEB,J.

    1998-09-14

    This demonstration is focused on evaluating the utility of decision support software in addressing environmental problems. Three endpoints have been selected for evaluation: (1) Visualization, (2) Sample Optimization, and (3) Cost/Benefit Analysis. The definitions for these three areas in this program are listed.

  14. The structure of decision support systems administrator next information network

    OpenAIRE

    І.Ю. Субач; П.В. Хусаінов; Міщенко, В.О.; Д.Е. Прусов

    2009-01-01

     Tasks of execute orderly administrator of special purpose information network are analyzed, and the structure and functions of the system are proved that support taking decisions in real time. Key words: information networks, information services, methods of increasing the efficiency, information evaluation, intellectual data analysis.

  15. Revisiting the dose calculation methodologies in European decision support systems

    DEFF Research Database (Denmark)

    Andersson, Kasper Grann; Roos, Per; Hou, Xiaolin;

    2012-01-01

    connection with management of the consequences of other types of contaminating incidents, including ‘dirty bomb’ explosions. This would require a number of new modelling features and parametric changes. Also for nuclear power plant preparedness a number of revisions of the decision support systems are called...

  16. Decision support system for containment and release management

    International Nuclear Information System (INIS)

    The Containment and Release Management project was carried out within the Reinforced Concerted Action Programme for Accident Management Support and partly financed by the European Union. In this report a prototype of an accident management support system is presented. The support system integrates several concepts from accident management research, like safety objective trees, severe accident phenomena, calculation models and an emergency response data system. These concepts are provided by the prototype in such a way that the decision making process of accident management is supported. The prototype application is demonstrated by process data taken from a severe accident scenario for a pressurized water reactor (PWR) that was simulated with the thermohydraulic computer program MAAP. The prototype was derived from a decision support framework based on a decision theory. For established and innovative concepts from accident management research it is pointed out in which way these concepts can support accident management and how these concepts can be integrated. This approach is generic in two ways; it applies to both pressurized and boiling water reactors and it applies to both in vessel management and containment and release management. The prototype application was developed in Multimedia Toolbox 3.0 and requires at least a 386 PC with 4 MB memory, 6 MB free disk space and MS Windows 3.1. (orig.)

  17. Measuring agreement between decision support reminders: the cloud vs. the local expert

    OpenAIRE

    Dixon, Brian Edward; Simonaitis, Linas; Perkins, Susan M; Wright, Adam; Middleton, Blackford

    2014-01-01

    Background A cloud-based clinical decision support system (CDSS) was implemented to remotely provide evidence-based guideline reminders in support of preventative health. Following implementation, we measured the agreement between preventive care reminders generated by an existing, local CDSS and the new, cloud-based CDSS operating on the same patient visit data. Methods Electronic health record data for the same set of patients seen in primary care were sent to both the cloud-based web servi...

  18. Measuring agreement between decision support reminders: the cloud vs. the local expert

    OpenAIRE

    Dixon, Brian Edward; Simonaitis, Linas; Perkins, Susan M; Wright, Adam; Middleton, Blackford

    2014-01-01

    Background: A cloud-based clinical decision support system (CDSS) was implemented to remotely provide evidence-based guideline reminders in support of preventative health. Following implementation, we measured the agreement between preventive care reminders generated by an existing, local CDSS and the new, cloud-based CDSS operating on the same patient visit data. Methods: Electronic health record data for the same set of patients seen in primary care were sent to both the cloud-based web ser...

  19. Interactive Decision-Support Tool for Risk-Based Radiation Therapy Plan Comparison for Hodgkin Lymphoma

    Energy Technology Data Exchange (ETDEWEB)

    Brodin, N. Patrik [Department of Radiation Oncology, Albert Einstein College of Medicine of Yeshiva University, New York, New York (United States); Maraldo, Maja V., E-mail: dra.maraldo@gmail.com [Department of Radiation Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Aznar, Marianne C. [Department of Radiation Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Niels Bohr Institute, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Vogelius, Ivan R. [Department of Radiation Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Petersen, Peter M. [Department of Radiation Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Department of Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Department of Hematology, Rigshospitalet, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Bentzen, Søren M. [Department of Radiation Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Department of Human Oncology, University of Wisconsin Medical School, Madison, Wisconsin (United States); Specht, Lena [Department of Radiation Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Department of Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Department of Hematology, Rigshospitalet, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark)

    2014-02-01

    Purpose: To present a novel tool that allows quantitative estimation and visualization of the risk of various relevant normal tissue endpoints to aid in treatment plan comparison and clinical decision making in radiation therapy (RT) planning for Hodgkin lymphoma (HL). Methods and Materials: A decision-support tool for risk-based, individualized treatment plan comparison is presented. The tool displays dose–response relationships, derived from published clinical data, for a number of relevant side effects and thereby provides direct visualization of the trade-off between these endpoints. The Quantitative Analyses of Normal Tissue Effects in the Clinic reports were applied, complemented with newer data where available. A “relevance score” was assigned to each data source, reflecting how relevant the input data are to current RT for HL. Results: The tool is applied to visualize the local steepness of dose–response curves to drive the reoptimization of a volumetric modulated arc therapy treatment plan for an HL patient with head-and-neck involvement. We also use this decision-support tool to visualize and quantitatively evaluate the trade-off between a 3-dimensional conformal RT plan and a volumetric modulated arc therapy plan for a patient with mediastinal HL. Conclusion: This multiple-endpoint decision-support tool provides quantitative risk estimates to supplement the clinical judgment of the radiation oncologist when comparing different RT options.

  20. Interactive Decision-Support Tool for Risk-Based Radiation Therapy Plan Comparison for Hodgkin Lymphoma

    International Nuclear Information System (INIS)

    Purpose: To present a novel tool that allows quantitative estimation and visualization of the risk of various relevant normal tissue endpoints to aid in treatment plan comparison and clinical decision making in radiation therapy (RT) planning for Hodgkin lymphoma (HL). Methods and Materials: A decision-support tool for risk-based, individualized treatment plan comparison is presented. The tool displays dose–response relationships, derived from published clinical data, for a number of relevant side effects and thereby provides direct visualization of the trade-off between these endpoints. The Quantitative Analyses of Normal Tissue Effects in the Clinic reports were applied, complemented with newer data where available. A “relevance score” was assigned to each data source, reflecting how relevant the input data are to current RT for HL. Results: The tool is applied to visualize the local steepness of dose–response curves to drive the reoptimization of a volumetric modulated arc therapy treatment plan for an HL patient with head-and-neck involvement. We also use this decision-support tool to visualize and quantitatively evaluate the trade-off between a 3-dimensional conformal RT plan and a volumetric modulated arc therapy plan for a patient with mediastinal HL. Conclusion: This multiple-endpoint decision-support tool provides quantitative risk estimates to supplement the clinical judgment of the radiation oncologist when comparing different RT options

  1. Designing a Clinical Framework to Guide Gross Motor Intervention Decisions for Infants and Young Children with Hypotonia

    Science.gov (United States)

    Darrah, Johanna; O'Donnell, Maureen; Lam, Joyce; Story, Maureen; Wickenheiser, Diane; Xu, Kaishou; Jin, Xiaokun

    2013-01-01

    Clinical practice frameworks are a valuable component of clinical education, promoting informed clinical decision making based on the best available evidence and/or clinical experience. They encourage standardized intervention approaches and evaluation of practice. Based on an international project to support the development of an enhanced service…

  2. Syncope: risk stratification and clinical decision making.

    Science.gov (United States)

    Peeters, Suzanne Y G; Hoek, Amber E; Mollink, Susan M; Huff, J Stephen

    2014-04-01

    Syncope is a common occurrence in the emergency department, accounting for approximately 1% to 3% of presentations. Syncope is best defined as a brief loss of consciousness and postural tone followed by spontaneous and complete recovery. The spectrum of etiologies ranges from benign to life threatening, and a structured approach to evaluating these patients is key to providing care that is thorough, yet cost-effective. This issue reviews the most relevant evidence for managing and risk stratifying the syncope patient, beginning with a focused history, physical examination, electrocardiogram, and tailored diagnostic testing. Several risk stratification decision rules are compared for performance in various scenarios, including how age and associated comorbidities may predict short-term and long-term adverse events. An algorithm for structured, evidence-based care of the syncope patient is included to ensure that patients requiring hospitalization are managed appropriately and those with benign causes are discharged safely. PMID:25105200

  3. Assessing the quality of decision support technologies using the International Patient Decision Aid Standards instrument (IPDASi.

    Directory of Open Access Journals (Sweden)

    Glyn Elwyn

    Full Text Available OBJECTIVES: To describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids. DESIGN: Scale development study, involving construct, item and scale development, validation and reliability testing. SETTING: There has been increasing use of decision support technologies--adjuncts to the discussions clinicians have with patients about difficult decisions. A global interest in developing these interventions exists among both for-profit and not-for-profit organisations. It is therefore essential to have internationally accepted standards to assess the quality of their development, process, content, potential bias and method of field testing and evaluation. METHODS: Scale development study, involving construct, item and scale development, validation and reliability testing. PARTICIPANTS: Twenty-five researcher-members of the International Patient Decision Aid Standards Collaboration worked together to develop the instrument (IPDASi. In the fourth Stage (reliability study, eight raters assessed thirty randomly selected decision support technologies. RESULTS: IPDASi measures quality in 10 dimensions, using 47 items, and provides an overall quality score (scaled from 0 to 100 for each intervention. Overall IPDASi scores ranged from 33 to 82 across the decision support technologies sampled (n = 30, enabling discrimination. The inter-rater intraclass correlation for the overall quality score was 0.80. Correlations of dimension scores with the overall score were all positive (0.31 to 0.68. Cronbach's alpha values for the 8 raters ranged from 0.72 to 0.93. Cronbach's alphas based on the dimension means ranged from 0.50 to 0.81, indicating that the dimensions, although well correlated, measure different aspects of decision support technology quality. A short version (19 items was also developed that had very similar mean scores to IPDASi and high correlation

  4. Design document for landfill capping Prototype Decision Support System

    International Nuclear Information System (INIS)

    The overall objective of the Prototype Decision Support System for shallow land burial project is to ''Develop a Decision Support System tool which incorporates simulation modeling and multi-objective decision theory for the purpose of designing and evaluating alternative trench cap designs for mixed waste landfill covers. The goal is to improve the quality of technical information used by the risk manager to select landfill cover designs while taking into account technological, economical, and regulatory factors.'' The complexity of the technical and non-technical information, and how the information varies in importance across sites, points to the need for decision analysis tools that provide a common basis for integrating, synthesizing, and valuing the decision input. Because the cost of remediating thousands of contaminated DOE sites is projected to be in the 10's--100's of billions of dollars, methods will be needed to establish cleanup priorities and to help in the selection and evaluation of cost effective remediation alternatives. Even at this early stage in DOE's cleanup program, it is certain that capping technologies will be heavily relied upon to remediate the 3000+ landfills on DOE property. Capping is favored in remediating most DOE landfills because, based on preliminary baseline risk assessments, human and ecological risks are considered to be low at most of these sites and the regulatory requirements for final closure of old landfills can be met using a well designed cap to isolate the buried waste. This report describes a program plan to design, develop, and test a decision support system (DSS) for assisting the DOE risk manager in evaluating capping alternatives for radioactive and hazardous waste landfills. The DOE DSS will incorporate methods for calculating, integrating and valuing technical, regulatory, and economic criteria

  5. Wireless Sensor Networking for Rain-fed Farming Decision Support

    CERN Document Server

    Panchard, J; Sheshshayee, M S; Papadimitratos, P; Kumar, S; Hubaux, J-P

    2009-01-01

    Wireless sensor networks (WSNs) can be a valuable decision-support tool for farmers. This motivated our deployment of a WSN system to support rain-fed agriculture in India. We defined promising use cases and resolved technical challenges throughout a two-year deployment of our COMMON-Sense Net system, which provided farmers with environment data. However, the direct use of this technology in the field did not foster the expected participation of the population. This made it difficult to develop the intended decision-support system. Based on this experience, we take the following position in this paper: currently, the deployment of WSN technology in developing regions is more likely to be effective if it targets scientists and technical personnel as users, rather than the farmers themselves. We base this claim on the lessons learned from the COMMON-Sense system deployment and the results of an extensive user experiment with agriculture scientists, which we describe in this paper.

  6. Food chain data customization for decision support systems in Austria

    International Nuclear Information System (INIS)

    In the case of a nuclear accident in Europe the integral decision support system R.O.D.O.S. ( real-time on-line decision support system for off-site emergency management) supplies comprehensive information on the present and future radiological situation, and the consequences of measures to protect the population. These data comprise mainly map information such as population distribution, rivers, roads, vegetation areas and production data of various food products. This work concentrates on the customization of the data for the food chain and dose module for terrestrial pathways. During the last fifteen years two different codes have been used in Austria for support during accidents with radioactive releases: O.E.C.O.S.Y.S. and R.O.D.O.S.. Adaptations and improvements have been performed to give better tools, they are detailed in this paper. (N.C.)

  7. Tablet-based patient monitoring and decision support systems in hospital care.

    Science.gov (United States)

    Baig, Mirza Mansoor; GholamHosseini, Hamid; Linden, Maria

    2015-08-01

    Remote patient monitoring with evidence-based decision support is revolutionizing healthcare. This novel approach could enable both patients and healthcare providers to improve quality of care and reduce costs. Clinicians can also view patients' data within the hospital network on tablet computers as well as other ubiquitous devices. Today, a wide range of applications are available on tablet computers which are increasingly integrating into the healthcare mainstream as clinical decision support systems. Despite the benefits of tablet-based healthcare applications, there are concerns around the accuracy, security and stability of such applications. In this study, we developed five tablet-based application screens for remote patient monitoring at hospital care settings and identified related issues and challenges. The ultimate aim of this research is to integrate decision support algorithms into the monitoring system in order to improve inpatient care and the effectiveness of such applications. PMID:26736485

  8. Decision making and strategic planning for disaster preparedness with a multi-criteria-analysis decision support system

    OpenAIRE

    Schlobinski, Sascha; Zuccaro, Giulio; Scholl, Martin; Meiers, Daniel; Denzer, Ralf; Guarino, Sergio; Engelbach, Wolf; Taveter, Kuldar; Frysinger, Steven

    2015-01-01

    In the context of the CRISMA FP7 project we have developed a seamless decision support concept to connect simulated crisis scenarios and aggregated performance indicators of impact scenarios with state of the art Multi-Criteria Decision Analysis (MCDA) methods. To prove the practicality of the approach we have developed a decision support tool realising the important aspects of the method. The tool is a highly interactive and user-friendly decision support system (DSS) that effectively helps ...

  9. Computerised Genetic Risk Assessment and Decision Support in Primary Care

    OpenAIRE

    Andrew Coulson; David Glasspool; John Fox; Jon Emery

    2000-01-01

    Public awareness of the availability of genetic testing threatens to put severe strain upon genetics clinics in the near future. General practitioners (GPs) could help avert this problem by making an initial genetic risk assessment and acting as gatekeepers to specialist services. However, studies in the United Kingdom suggest that few GPs feel they have the requisite skills for taking family history details and making an appropriate referral decision. They are also poorly served by compute...

  10. Prediction Models and Decision Support: Chances and Challenges

    OpenAIRE

    Kappen, T.H.

    2015-01-01

    A clinical prediction model can assist doctors in arriving at the most likely diagnosis or estimating the prognosis. By utilizing various patient- and disease-related properties, such models can yield objective estimations of the risk of a disease or the probability of a certain disease course for individual patients. Doctors can then use this individual probability in their decision making process, thereby (hopefully) improving patient outcome. However, even when its probability estimates ar...

  11. Integrated assessment for supporting decision making with multiple criteria

    Directory of Open Access Journals (Sweden)

    Friedrich R.

    2015-01-01

    Full Text Available Decisions about the development of the energy system should take all relevant criteria into account, including costs and health, environmental and climate impacts. As usually no decision alternative fulfils all criteria better than all other alternatives, a weighting between the indicators that show the degree of fulfilment of the criteria, is necessary. In the following the “impact pathway approach” is described that supports decisions by using weighting factors that are derived from measuring or observing the preferences of the population. The methodology is applied to rank technologies for generating electricity according to their social costs, which is a summary indicator comprising simultaneously costs, impacts of air pollution on health and biodiversity and climate impacts.

  12. Decision Support for GPs: Towards a more certain future?

    Directory of Open Access Journals (Sweden)

    Peter Pritchard

    1995-09-01

    Full Text Available General practitioners are expected to make decisions on the problems of every patient whom they see, under conditions of great uncertainty. Pressure for cost containment is growing, and quality of care and accountability are major issues. Medical knowledge of varying relevance is accumulating at an increasing rate, so that GPs find themselves in a quicksand of volatile and unvalidated knowledge. Weighing up all the options, and seeking more information in order to select the favoured option is not easy in the time available. Then there is the burning question whether a decision has benefited an individual patient. The new generation of knowledge-based decision support (KBDS computer systems may be able to offer some help.

  13. Prioritization of engineering support requests and advanced technology projects using decision support and industrial engineering models

    Science.gov (United States)

    Tavana, Madjid

    1995-01-01

    The evaluation and prioritization of Engineering Support Requests (ESR's) is a particularly difficult task at the Kennedy Space Center (KSC) -- Shuttle Project Engineering Office. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant pieces of information concerning Safety, Supportability, O&M Cost Savings, Process Enhancement, Reliability, and Implementation. Various analytical and normative models developed over the past have helped decision makers at KSC utilize large volumes of information in the evaluation of ESR's. The purpose of this project is to build on the existing methodologies and develop a multiple criteria decision support system that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The model utilizes the Analytic Hierarchy Process (AHP), subjective probabilities, the entropy concept, and Maximize Agreement Heuristic (MAH) to enhance the decision maker's intuition in evaluating a set of ESR's.

  14. A Decision Support Model and Tool to Assist Financial Decision-Making in Universities

    Science.gov (United States)

    Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive

    2015-01-01

    In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…

  15. Education for healthcare clinical support workers.

    Science.gov (United States)

    Lewis, Robin; Kelly, Shona

    2015-12-01

    This article reviews the current situation regarding the provision of education and training for healthcare clinical support workers (HCSWs). In the UK, there has been an increasing reliance on unqualified clinical support staff to provide a significant proportion of the direct patient care in all healthcare settings. HCSWs routinely undertake several nursing activities that were traditionally the responsibility of nursing students or junior staff nurses. There is a need for an urgent review of the training of healthcare support staff. A 'tick box' approach to training, with an emphasis on classroom-based or on-the-job learning, makes it difficult for HCSWs to integrate theory into practice, and supports a transactional approach to caring rather than a relational approach to caregiving. Lessons from the educational experiences of other healthcare groups should be applied to the training of HCSWs. An immersive, participatory teaching and learning strategy is one approach that could be used. PMID:26647705

  16. Impella ventricular support in clinical practice

    DEFF Research Database (Denmark)

    Burzotta, Francesco; Trani, Carlo; Doshi, Sagar N;

    2015-01-01

    Mechanical circulatory support represents an evolving field of clinical research and practice. Currently, several cardiac assist devices have been developed but, among different institutions and countries, a large variation in indications for use and device selection exists. The Impella platform is...... the operative protocols, this working group attempted to establish the best clinical practice with the technology. The present paper reviews the main theoretical principles of Impella and provides an up-to-date summary of the best practical aspects of device use which may help others gain the maximal...... advantage with Impella technology in a variety of clinical settings....

  17. Overcoming barriers to development of cooperative medical decision support models.

    Science.gov (United States)

    Hudson, Donna L; Cohen, Maurice E

    2012-01-01

    Attempts to automate the medical decision making process have been underway for the at least fifty years, beginning with data-based approaches that relied chiefly on statistically-based methods. Approaches expanded to include knowledge-based systems, both linear and non-linear neural networks, agent-based systems, and hybrid methods. While some of these models produced excellent results none have been used extensively in medical practice. In order to move these methods forward into practical use, a number of obstacles must be overcome, including validation of existing systems on large data sets, development of methods for including new knowledge as it becomes available, construction of a broad range of decision models, and development of non-intrusive methods that allow the physician to use these decision aids in conjunction with, not instead of, his or her own medical knowledge. None of these four requirements will come easily. A cooperative effort among researchers, including practicing MDs, is vital, particularly as more information on diseases and their contributing factors continues to expand resulting in more parameters than the human decision maker can process effectively. In this article some of the basic structures that are necessary to facilitate the use of an automated decision support system are discussed, along with potential methods for overcoming existing barriers. PMID:23366358

  18. A Customized Drought Decision Support Tool for Hsinchu Science Park

    Science.gov (United States)

    Huang, Jung; Tien, Yu-Chuan; Lin, Hsuan-Te; Liu, Tzu-Ming; Tung, Ching-Pin

    2016-04-01

    Climate change creates more challenges for water resources management. Due to the lack of sufficient precipitation in Taiwan in fall of 2014, many cities and counties suffered from water shortage during early 2015. Many companies in Hsinchu Science Park were significantly influenced and realized that they need a decision support tool to help them managing water resources. Therefore, a customized computer program was developed, which is capable of predicting the future status of public water supply system and water storage of factories when the water rationing is announced by the government. This program presented in this study for drought decision support (DDSS) is a customized model for a semiconductor company in the Hsinchu Science Park. The DDSS is programmed in Java which is a platform-independent language. System requirements are any PC with the operating system above Windows XP and an installed Java SE Runtime Environment 7. The DDSS serves two main functions. First function is to predict the future storage of Baoshan Reservoir and Second Baoshan Reservoir, so to determine the time point of water use restriction in Hsinchu Science Park. Second function is to use the results to help the company to make decisions to trigger their response plans. The DDSS can conduct real-time scenario simulations calculating the possible storage of water tank for each factory with pre-implementation and post-implementation of those response plans. In addition, DDSS can create reports in Excel to help decision makers to compare results between different scenarios.

  19. The thinking doctor: clinical decision making in contemporary medicine.

    Science.gov (United States)

    Trimble, Michael; Hamilton, Paul

    2016-08-01

    Diagnostic errors are responsible for a significant number of adverse events. Logical reasoning and good decision-making skills are key factors in reducing such errors, but little emphasis has traditionally been placed on how these thought processes occur, and how errors could be minimised. In this article, we explore key cognitive ideas that underpin clinical decision making and suggest that by employing some simple strategies, physicians might be better able to understand how they make decisions and how the process might be optimised. PMID:27481378

  20. Advanced intelligent computational technologies and decision support systems

    CERN Document Server

    Kountchev, Roumen

    2014-01-01

    This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like: intelligent predictive diagnosis; intelligent analyzing of medical images; new format for coding of single and sequences of medical images; Medical Decision Support Systems; diagnosis of Down’s syndrome; computational perspectives for electronic fetal monitoring; efficient compression of CT Images; adaptive interpolation and halftoning for medical images; applications of artificial neural networks for real-life problems solving; present and perspectives for Electronic Healthcare Record Systems; adaptive approaches for noise reduction in sequences of CT images etc.

  1. Computational intelligence for decision support in cyber-physical systems

    CERN Document Server

    Ali, A; Riaz, Zahid

    2014-01-01

    This book is dedicated to applied computational intelligence and soft computing techniques with special reference to decision support in Cyber Physical Systems (CPS), where the physical as well as the communication segment of the networked entities interact with each other. The joint dynamics of such systems result in a complex combination of computers, software, networks and physical processes all combined to establish a process flow at system level. This volume provides the audience with an in-depth vision about how to ensure dependability, safety, security and efficiency in real time by making use of computational intelligence in various CPS applications ranging from the nano-world to large scale wide area systems of systems. Key application areas include healthcare, transportation, energy, process control and robotics where intelligent decision support has key significance in establishing dynamic, ever-changing and high confidence future technologies. A recommended text for graduate students and researche...

  2. On the heuristic nature of medical decision-support systems.

    Science.gov (United States)

    Aliferis, C F; Miller, R A

    1995-03-01

    In the realm of medical decision-support systems, the term "heuristic systems" is often considered to be synonymous with "medical artificial intelligence systems" or with "systems employing informal model(s) of problem solving". Such a view may be inaccurate and possibly impede the conceptual development of future systems. This article examines the nature of heuristics and the levels at which heuristic solutions are introduced during system design and implementation. The authors discuss why heuristics are ubiquitous in all medical decision-support systems operating at non-trivial domains, and propose a unifying definition of heuristics that encompasses formal and ad hoc systems. System developers should be aware of the heuristic nature of all problem solving done in complex real world domains, and characterize their own use of heuristics in describing system development and implementation. PMID:9082138

  3. Effect of guideline based computerised decision support on decision making of multidisciplinary teams: cluster randomised trial in cardiac rehabilitation

    OpenAIRE

    Goud, R.; de Keizer, N F; ter Riet, G; Wyatt, J C; Hasman, A.; Hellemans, I.M.; Peek, N.

    2009-01-01

    OBJECTIVE: To determine the extent to which computerised decision support can improve concordance of multidisciplinary teams with therapeutic decisions recommended by guidelines. DESIGN: Multicentre cluster randomised trial. PARTICIPANTS: Multidisciplinary cardiac rehabilitation teams in Dutch centres and their cardiac rehabilitation patients. INTERVENTIONS: Teams received an electronic patient record system with or without additional guideline based decision support. MAIN OUTCOME MEASURES: C...

  4. Study on Decision Support System of Employee Turnover Risk Management

    OpenAIRE

    Xiang Liu

    2009-01-01

    Employee turnover risk is becoming an important aspect that influences the stability and development of enterprises in the times of knowledge economy. After analyzing the factors of employee turnover risk which would threaten enterprise production and operation activities, a decision support system in this field will be proposed, and it is realized by message processing mechanism, software combination technology and system integration. Also, the corresponding management strategies were set up...

  5. SUWAMAS, a decision support model for sustainable waste management systems

    OpenAIRE

    Marquez Oropeza, Eduardo

    2006-01-01

    SUWAMAS is a decision support model designed to deliver sustainable waste management strategies. Recommended strategies promote economic growth and social cohesion without impairing environmental quality. These strategies consider the integrated product policy approach and European waste management strategic drivers. SUWAMAS is designed to minimise unsustainable production and consumption patterns through the life cycle of the product system. The product system consists of recovery and dispos...

  6. Spreadsheet decision support model for training exercise material requirements planning

    OpenAIRE

    Tringali, Arthur M

    1997-01-01

    Approved for public release; distribution is unlimited This thesis focuses on developing a spreadsheet decision support model that can be used by combat engineer platoon and company commanders in determining the material requirements and estimated costs associated with military training exercises. The model combines the business practice of Material Requirements Planning and the commercial spreadsheet software capabilities of Lotus 1-2-3 to calculate the requirements for food, consumable s...

  7. Distributed decision support and organizational connectivity: A case study

    OpenAIRE

    Jeusfeld, Manfred A.; Bui, Tung X.

    1997-01-01

    While the Internet has been grabbing most of the attention of the information systems researchers and practitioners, online transaction processing systems still take the lion’s share of business information systems. Although many Decision Support Systems (DSS) have been developed, they failed to become mainstream products due to their limited availability, applicability, and interoperability. In this paper, we propose a script language to make use of the vast resource of the Internet...

  8. Analytical and Decision Support Tools for Genomics-Assisted Breeding

    OpenAIRE

    Varshney, Rajeev K; Singh, Vikas K; Hickey, John M; Xun, Xu; Marshall, David F.; Wang, Jun; Edwards, David; Ribaut, Jean-Marcel

    2016-01-01

    To successfully implement genomics-assisted breeding (GAB) in crop improvement programs, efficient and effective analytical and decision support tools (ADSTs) are 'must haves' to evaluate and select plants for developing next-generation crops. Here we review the applications and deployment of appropriate ADSTs for GAB, in the context of next-generation sequencing (NGS), an emerging source of massive genomic information. We discuss suitable software tools and pipelines for marker-based approac...

  9. Decision support for optimising energy consumption in European greenhouses

    OpenAIRE

    Korner, O.; D. Warner(Colorado State University); Tzilivakis, J.; Eveleens-Clark, B.A.; Heuvelink, E.

    2008-01-01

    Improving existing greenhouse structures in terms of insulation and other features can save energy with significantly lower investment costs than building new greenhouses. Within the EU Framework VI project GREENERGY a decision support system has been developed that offers the potential to be used by the advisory services for growers all over Europe. It evaluates the impacts of either using different greenhouse materials (e.g. for the cover or screens) or building a complete new structure on ...

  10. Simulation as a decision support tool in maintenance float systems

    OpenAIRE

    Peito, Francisco; Pereira, Guilherme; Leitão, Armando; Dias, Luís M. S.

    2011-01-01

    This paper is concerned with the use of simulation as a decision support tool in maintenance systems, specifically in MFS (Maintenance Float Systems). For this purpose and due to its high complexity, in this paper the authors explore and present a possible way to construct a MFS model using Arena® simulation language, where some of the most common performance measures are identified, calculated and analysed.

  11. Agent-Based Process-Critiquing Decision Support Systems

    Czech Academy of Sciences Publication Activity Database

    Bošanský, Branislav; Lhotská, L.

    Bratislava: Slovak Technical University, 2009, s. 1-6. [ISABEL 2009. International Symposium on Applied Sciences in Biomedical and Communication Technologies /2./. Bratislava (SK), 24.12.2009-27.12.2009] R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : critiquing decision support system * multi-agent system * process * medical guidelines Subject RIV: IN - Informatics, Computer Science

  12. A decision support system for regional hazardous waste management alternatives

    OpenAIRE

    Amouzegar, Mahyar A.; Jacobsen, Stephen E.

    1998-01-01

    With the passage of the Resource Conservation and Recovery Act (RCRA), and the subsequent amendments to RCRA, efforts to provide tighter controls on the transportation and disposal of hazardous waste have been steadily gaining ground. This paper, intended as a decision support tool for regional planning, incorporates information on the hazardous waste generation, treatment capacity and the costs of waste treatment alternatives into an optimization problem of finding the relationship between g...

  13. Agent-Based Process-Critiquing Decision Support System

    Czech Academy of Sciences Publication Activity Database

    Bošanský, Branislav; Lhotská, L.

    Los Alamitos : IEEE Computer Society, 2009, s. 1-6. ISBN 978-1-4244-4640-7. [ISABEL 2009. International Symposium on Applied Sciences in Biomedical and Communication Technologies /2./. Bratislava (SK), 24.12.2009-27.12.2009] R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : decision support system s * health care * multi - agent system s Subject RIV: EC - Immunology

  14. Intelligent Decision Support System for Bank Loans Risk Classification

    Institute of Scientific and Technical Information of China (English)

    杨保安; 马云飞; 俞莲

    2001-01-01

    Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BLRC, the key financial and non-financial factors are analyzed. Meanwhile, ES and Model Base (MB) which contain ANN are designed . The general framework,interaction and integration of the system are given. In addition, how the system realizes BLRC is elucidated in detail.

  15. The Heureka forestry decision support system : an overview

    OpenAIRE

    Wikström, Peder; Edenius, Lars; Elfving, Björn; Eriksson, Ljusk Ola; Lämås, Tomas; Sonesson, Johan; Öhman, Karin; Wallerman, Jörgen; Waller, Carina; Klintebäck, Fredrik

    2011-01-01

    Mathematical programming and computers have been used for several decades to solve complex and long term forest management planning problems. The ever increasing demand on the forest ecosystem to produce wood and other goods and services poses a corresponding demand on a forest decision support system. As a response to meet new requirements the development of the Heureka system was initiated at SLU in 2002 and a first version of the system was released in 2009. Based on a common kernel, a num...

  16. Fuzzy integrals as a tool for multicriteria decision support

    Czech Academy of Sciences Publication Activity Database

    Mesiar, Radko

    Berlin : Springer, 2011 - (Melo- Pinto , P.; Couto, P.; Serodio, C.; Fodor, J.), s. 9-15 ISBN 978-3-642-24000-3. - (Advances in Intelligent and Soft Computing. 107). [EUROFUSE 2011. Regua (PT), 21.09.2011-23.09.2011] R&D Projects: GA ČR GAP402/11/0378 Institutional research plan: CEZ:AV0Z10750506 Keywords : fuzzy integral * copula * multicriteria decision support Subject RIV: BA - General Mathematics

  17. INTEGRATION OF FORESTRY DECISION SUPPORT SYSTEMS IN GIS

    OpenAIRE

    STEFANIA PIZZIRANI; STEPHEN BATHGATE

    2012-01-01

    Landscape characteristics underpin the ability of the forestry industry to deliver in an increasingly complex operational environment. However, the range of site types within the British public forest estate includes many with soil or exposure constraints. Until recently it was not possible to effectively assess the scale of constraints and spatially allocate land appropriately to the objectives suggested by policy makers. Stand level forestry decision support systems have been developed to a...

  18. Knowledge Management and Decision Support for Sustainable Land Management

    OpenAIRE

    Liniger, Hanspeter; Schwilch, Gudrun

    2010-01-01

    Much research has focused on desertification and land degradation assessments without putting sufficient emphasis on prevention and mitigation, although the concept of sustainable land management (SLM) is increasingly being acknowledged. A variety of SLM measures have already been applied at the local level, but they are rarely adequately recognised, evaluated, shared or used for decision support. WOCAT (World Overview of Technologies and Approaches) has developed an internationally recognise...

  19. A multi-criteria decision analysis tool to support electricity

    OpenAIRE

    Ribeiro, Fernando; Ferreira, Paula Varandas; Araújo, Maria Madalena Teixeira de

    2012-01-01

    A Multi-Criteria Decision Analysis (MCDA) tool was designed to support the evaluation of different electricity production scenarios. The MCDA tool is implemented in Excel worksheet and uses information obtained from a mixed integer optimization model. Given the input, the MCDA allowed ranking different scenarios relying on their performance on 13 criteria covering economic, job market, quality of life of local populations, technical and environmental issues. The criteria were weighte...

  20. Entrepreneurial decision support engine in forecasting business opportunities

    OpenAIRE

    Burghelea, Madalina

    2014-01-01

    The master thesis aims at creating a decision support system for new entrepreneurs, which studies the online data on web domains and could recommend to the new entrepreneur if it is a good idea to join that particular business niche. DatoSphera is a data startup for entrepreneurs, inside the Big Data Incubator Incubio. The project followed different stages of development from being part of the Incubio Research department to being incubated after only one month and transformed into a real comp...

  1. Decision support system for structure synthesis of monitoring systems

    OpenAIRE

    Skatkov A. V.; Voronin D. Y.; Danilchuk D. N.

    2008-01-01

    The paper is concerned with a structure synthesis of monitoring systems. In the article a decision support system for such synthesis was proposed and described. In the first phase of the process, the proposed classification of monitoring systems is used. Then adaptive algorithms, simulation and analytic modeling are used. The results of studies carried out by means of the proposed program are represented. The topicality of proposed approach was demonstrated. It should be mentioned, that algor...

  2. DESERT: Decision Support System for Evaluating River Basin Strategies

    OpenAIRE

    Ivanov, P.; Masliev, I.; Kularathna, M.; A. Kuzmin; Somlyody, L.

    1995-01-01

    An integrated PC-based software package for decision support in water quality management on a river basin scale has been developed. The software incorporates a number of useful tools, including an easy-to-use data handling module with a dBase style database engine, simulation and calibration of hydraulics and water quality, display of computed data with the help of external spreadsheet software, and optimization based on dynamic programming algorithm. The main utility of the package is to pro...

  3. Support Vector Machines for decision support in electricity markets׳ strategic bidding

    DEFF Research Database (Denmark)

    Pinto, Tiago; Sousa, Tiago M.; Praça, Isabel;

    2015-01-01

    . The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and...

  4. A Knowledge Management and Decision Support Model for Enterprises

    Directory of Open Access Journals (Sweden)

    Patrizia Ribino

    2011-01-01

    Full Text Available We propose a novel knowledge management system (KMS for enterprises. Our system exploits two different approaches for knowledge representation and reasoning: a document-based approach based on data-driven creation of a semantic space and an ontology-based model. Furthermore, we provide an expert system capable of supporting the enterprise decisional processes and a semantic engine which performs intelligent search on the enterprise knowledge bases. The decision support process exploits the Bayesian networks model to improve business planning process when performed under uncertainty.

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

    Science.gov (United States)

    Marcum, James A

    2013-10-01

    What role, if any, should emotions play in clinical reasoning and decision making? Traditionally, emotions have been excluded from clinical reasoning and decision making, but with recent advances in cognitive neuropsychology they are now considered an important component of them. Today, cognition is thought to be a set of complex processes relying on multiple types of intelligences. The role of mathematical logic (hypothetico-deductive thinking) or verbal linguistic intelligence in cognition, for example, is well documented and accepted; however, the role of emotional intelligence has received less attention-especially because its nature and function are not well understood. In this paper, I argue for the inclusion of emotions in clinical reasoning and decision making. To that end, developments in contemporary cognitive neuropsychology are initially examined and analyzed, followed by a review of the medical literature discussing the role of emotions in clinical practice. Next, a published clinical case is reconstructed and used to illustrate the recognition and regulation of emotions played during a series of clinical consultations, which resulted in a positive medical outcome. The paper's main thesis is that emotions, particularly in terms of emotional intelligence as a practical form of intelligence, afford clinical practitioners a robust cognitive resource for providing quality medical care. PMID:23975905

  6. Disaster Management with a Next Generation Disaster Decision Support System

    Science.gov (United States)

    Chen, Y.

    2015-12-01

    As populations become increasingly concentrated in large cities, the world is experiencing an inevitably growing trend towards the urbanisation of disasters. Scientists have contributed significant advances in understanding the geophysical causes of natural hazards and have developed sophisticated tools to predict their effects; while, much less attention has been devoted to tools that increase situational awareness, facilitate leadership, provide effective communication channels and data flow and enhance the cognitive abilities of decision makers and first responders. In this paper, we envisioned the capabilities of a next generation disaster decision support system and hence proposed a state-of-the-art system architecture design to facilitate the decision making process in natural catastrophes such as flood and bushfire by utilising a combination of technologies for multi-channel data aggregation, disaster modelling, visualisation and optimisation. Moreover, we put our thoughts into action by implementing an Intelligent Disaster Decision Support System (IDDSS). The developed system can easily plug in to external disaster models and aggregate large amount of heterogeneous data from government agencies, sensor networks, and crowd sourcing platforms in real-time to enhance the situational awareness of decision makers and offer them a comprehensive understanding of disaster impacts from diverse perspectives such as environment, infrastructure and economy, etc. Sponsored by the Australian Government and the Victorian Department of Justice (Australia), the system was built upon a series of open-source frameworks (see attached figure) with four key components: data management layer, model application layer, processing service layer and presentation layer. It has the potential to be adopted by a range of agencies across Australian jurisdictions to assist stakeholders in accessing, sharing and utilising available information in their management of disaster events.

  7. Retooling institutional support infrastructure for clinical research.

    Science.gov (United States)

    Snyder, Denise C; Brouwer, Rebecca N; Ennis, Cory L; Spangler, Lindsey L; Ainsworth, Terry L; Budinger, Susan; Mullen, Catherine; Hawley, Jeffrey; Uhlenbrauck, Gina; Stacy, Mark

    2016-05-01

    Clinical research activities at academic medical centers are challenging to oversee. Without effective research administration, a continually evolving set of regulatory and institutional requirements can divert investigator and study team attention away from a focus on scientific gain, study conduct, and patient safety. However, even when the need for research administration is recognized, there can be struggles over what form it should take. Central research administration may be viewed negatively, with individual groups preferring to maintain autonomy over processes. Conversely, a proliferation of individualized approaches across an institution can create inefficiencies or invite risk. This article describes experiences establishing a unified research support office at the Duke University School of Medicine based on a framework of customer support. The Duke Office of Clinical Research was formed in 2012 with a vision that research administration at academic medical centers should help clinical investigators navigate the complex research environment and operationalize research ideas. The office provides an array of services that have received high satisfaction ratings. The authors describe the ongoing culture change necessary for success of the unified research support office. Lessons learned from implementation of the Duke Office of Clinical Research may serve as a model for other institutions undergoing a similar transition. PMID:27125563

  8. Demonstration of Decision Support Tools for Sustainable Development

    Energy Technology Data Exchange (ETDEWEB)

    Shropshire, David Earl; Jacobson, Jacob Jordan; Berrett, Sharon; Cobb, D. A.; Worhach, P.

    2000-11-01

    The Demonstration of Decision Support Tools for Sustainable Development project integrated the Bechtel/Nexant Industrial Materials Exchange Planner and the Idaho National Engineering and Environmental Laboratory System Dynamic models, demonstrating their capabilities on alternative fuel applications in the Greater Yellowstone-Teton Park system. The combined model, called the Dynamic Industrial Material Exchange, was used on selected test cases in the Greater Yellow Teton Parks region to evaluate economic, environmental, and social implications of alternative fuel applications, and identifying primary and secondary industries. The test cases included looking at compressed natural gas applications in Teton National Park and Jackson, Wyoming, and studying ethanol use in Yellowstone National Park and gateway cities in Montana. With further development, the system could be used to assist decision-makers (local government, planners, vehicle purchasers, and fuel suppliers) in selecting alternative fuels, vehicles, and developing AF infrastructures. The system could become a regional AF market assessment tool that could help decision-makers understand the behavior of the AF market and conditions in which the market would grow. Based on this high level market assessment, investors and decision-makers would become more knowledgeable of the AF market opportunity before developing detailed plans and preparing financial analysis.

  9. Decision support for integrated water-energy planning.

    Energy Technology Data Exchange (ETDEWEB)

    Tidwell, Vincent Carroll; Malczynski, Leonard A.; Kobos, Peter Holmes; Castillo, Cesar; Hart, William Eugene; Klise, Geoffrey T.

    2009-10-01

    Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 39% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. Coupled to this water use is the required pumping, conveyance, treatment, storage and distribution of the water which requires on average 3% of all electric power generated. While water and energy use are tightly coupled, planning and management of these fundamental resources are rarely treated in an integrated fashion. Toward this need, a decision support framework has been developed that targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. The framework integrates analysis and optimization capabilities to identify trade-offs, and 'best' alternatives among a broad list of energy/water options and objectives. The decision support framework is formulated in a modular architecture, facilitating tailored analyses over different geographical regions and scales (e.g., national, state, county, watershed, NERC region). An interactive interface allows direct control of the model and access to real-time results displayed as charts, graphs and maps. Ultimately, this open and interactive modeling framework provides a tool for evaluating competing policy and technical options relevant to the energy-water nexus.

  10. North Slope Decision Support for Water Resource Planning and Management

    Energy Technology Data Exchange (ETDEWEB)

    Schnabel, William; Brumbelow, Kelly

    2013-03-31

    The objective of this project was to enhance the water resource decision-making process with respect to oil and gas exploration/production activities on Alaska’s North Slope. To this end, a web-based software tool was developed to allow stakeholders to assemble, evaluate, and communicate relevant information between and amongst themselves. The software, termed North Slope Decision Support System (NSDSS), is a visually-referenced database that provides a platform for running complex natural system, planning, and optimization models. The NSDSS design was based upon community input garnered during a series of stakeholder workshops, and the end product software is freely available to all stakeholders via the project website. The tool now resides on servers hosted by the UAF Water and Environmental Research Center, and will remain accessible and free-of-charge for all interested stakeholders. The development of the tool fostered new advances in the area of data evaluation and decision support technologies, and the finished product is envisioned to enhance water resource planning activities on Alaska’s North Slope.

  11. Step towards multiplatform framework for supporting pediatric and neonatology care unit decision process

    OpenAIRE

    Guimarães, Tiago; Coimbra, Cecília; Portela, Filipe; Santos, Manuel; Machado, José Manuel; Abelha, António

    2015-01-01

    Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total...

  12. An Automated Approach for Ranking Journals to Help in Clinician Decision Support

    OpenAIRE

    Jonnalagadda, Siddhartha R.; Moosavinasab, Soheil; Nath, Chinmoy; Li, Dingcheng; Chute, Christopher G.; Liu, Hongfang

    2014-01-01

    Point of care access to knowledge from full text journal articles supports decision-making and decreases medical errors. However, it is an overwhelming task to search through full text journal articles and find quality information needed by clinicians. We developed a method to rate journals for a given clinical topic, Congestive Heart Failure (CHF). Our method enables filtering of journals and ranking of journal articles based on source journal in relation to CHF. We also obtained a journal p...

  13. The Adoption of Electronic Medical Records and Decision Support Systems in Korea

    OpenAIRE

    Chae, Young Moon; Yoo, Ki Bong; Kim, Eun Sook; Chae, Hogene

    2011-01-01

    Objectives To examine the current status of hospital information systems (HIS), analyze the effects of Electronic Medical Records (EMR) and Clinical Decision Support Systems (CDSS) have upon hospital performance, and examine how management issues change over time according to various growth stages. Methods Data taken from the 2010 survey on the HIS status and management issues for 44 tertiary hospitals and 2009 survey on hospital performance appraisal were used. A chi-square test was used to ...

  14. Building a financial decision support system with Oracle

    CERN Document Server

    Angberg, M

    2001-01-01

    CERN (European Organization for Nuclear Research) is the world's leading particle physics research laboratory. It is a truly global organization, collaborating with more than 500 research institutes around the world. The laboratory is currently working on the construction of its largest and most complex scientific instrument ever, the Large Hadron Collider (LHC), due for completion in 2007. Under the current economic climate, however, the laboratory, along with many other businesses and organizations, is having to face shrinking resources and reduced staff levels. Since CERN is expected to continue to grow, it will be forced to achieve higher productivity with fewer resources. In the area of administrative information systems, the situation described above led us to the decision to use Oracle's Data Warehousing concepts and J2EE for the implementation of a scalable and flexible financial decision support system with a low maintenance cost. This paper outlines the experiences drawn from this implementation, fr...

  15. Data assimilation in the decision support system RODOS

    DEFF Research Database (Denmark)

    Rojas-Palma, C.; Madsen, H.; Gering, F.;

    2003-01-01

    . The process of combining model predictions and observations, usually referred to as data assimilation, is described in this article within the framework of the real time on-line decision support system (RODOS) for off-site nuclear emergency management in Europe. Data assimilation capabilities, based...... the system. This would in turn provide decision makers with uncertainty estimates taking into account both model and observation errors. This paper describes the methodology employed as well as results of some preliminary studies based on simulated data....... on Kalman filters, are under development for several modules of the RODOS system, including the atmospheric dispersion, deposition, food chain and hydrological models. The use of such a generic data assimilation methodology enables the propagation of uncertainties throughout the various modules of...

  16. System for decision analysis support on complex waste management issues

    International Nuclear Information System (INIS)

    A software system called the Waste Flow Analysis has been developed and applied to complex environmental management processes for the United States Department of Energy (US DOE). The system can evaluate proposed methods of waste retrieval, treatment, storage, transportation, and disposal. Analysts can evaluate various scenarios to see the impacts to waste slows and schedules, costs, and health and safety risks. Decision analysis capabilities have been integrated into the system to help identify preferred alternatives based on a specific objectives may be to maximize the waste moved to final disposition during a given time period, minimize health risks, minimize costs, or combinations of objectives. The decision analysis capabilities can support evaluation of large and complex problems rapidly, and under conditions of variable uncertainty. The system is being used to evaluate environmental management strategies to safely disposition wastes in the next ten years and reduce the environmental legacy resulting from nuclear material production over the past forty years

  17. Water flow algorithm decision support tool for travelling salesman problem

    Science.gov (United States)

    Kamarudin, Anis Aklima; Othman, Zulaiha Ali; Sarim, Hafiz Mohd

    2016-08-01

    This paper discuss about the role of Decision Support Tool in Travelling Salesman Problem (TSP) for helping the researchers who doing research in same area will get the better result from the proposed algorithm. A study has been conducted and Rapid Application Development (RAD) model has been use as a methodology which includes requirement planning, user design, construction and cutover. Water Flow Algorithm (WFA) with initialization technique improvement is used as the proposed algorithm in this study for evaluating effectiveness against TSP cases. For DST evaluation will go through usability testing conducted on system use, quality of information, quality of interface and overall satisfaction. Evaluation is needed for determine whether this tool can assists user in making a decision to solve TSP problems with the proposed algorithm or not. Some statistical result shown the ability of this tool in term of helping researchers to conduct the experiments on the WFA with improvements TSP initialization.

  18. Towards an integrated approach in supporting microbiological food safety decisions

    DEFF Research Database (Denmark)

    Havelaar, A.H.; Braunig, J.; Christiansen, K.;

    2007-01-01

    Decisions on food safety involve consideration of a wide range of concerns including the public health impact of foodborne illness, the economic importance of the agricultural sector and the food industry, and the effectiveness and efficiency of interventions. To support such decisions, we propose...... an integrated scientific approach combining veterinary and medical epidemiology, risk assessment for the farm-to-fork food chain as well as agricultural and health economy. Scientific advice is relevant in all stages of the policy cycle: to assess the magnitude of the food safety problem, to define...... the priorities for action, to establish the causes for the problem, to choose between different control options, to define targets along the food chain and to measure success....

  19. A model-referenced procedure to support adversarial decision processes

    International Nuclear Information System (INIS)

    In public enquiries concerning major facilities, such as the construction of a new electric power plant, it is observed that a useable decision model should be made commonly available alongside the open provision of data and assumptions. The protagonist, eg the electric utility, generally makes use of a complex, proprietary model for detailed evaluation of options. A simple emulator of this, based upon a regression analysis of numerous scenarios, and validated by further simulations is shown to be feasible and potentially attractive. It would be in the interests of the utility to make such a model-referenced decision support method generally available. The approach is considered in relation to the recent Hinkley Point C public enquiry for a new nuclear power plant in the UK. (Author)

  20. Perspectives on Spatial Decision Support Concerning Location of Biogas Production

    DEFF Research Database (Denmark)

    Bojesen, Mikkel

    Biogas production is a contemporary important topic in many agri-intensive countries, among these Denmark, where biogas has received increasingly political and scholarly awareness during recent years. The Danish government has set an ambition that 50% of the livestock slurry should by 2020 by used...... in biogas production. This ambition requires that more than 20 new large scale centralised biogas plants are built. The location of these plants is associated with a number of externalities and uncertainties and the existing biogas sector struggles to establish itself as a viable energy producing...... sector. Meanwhile planners and decision makers struggle to find sustainable locations that comprehensively balance the multiple concerns the location of biogas facilities includes. This PhD project examines how spatial decision support models can be used to ensure sustainable locations of future biogas...

  1. A hybrid decision support system for iron ore supply

    Directory of Open Access Journals (Sweden)

    A. Samolejová

    2012-01-01

    Full Text Available Many European metallurgical companies are forced to import iron ore from remote destinations. For these companies it is necessary to determine the amount of iron ore that will have to be ordered and to create such a delivery schedule so that the continuous operation of blast-furnace plant is not disrupted and there is no exceedingly large stock of this raw material. The objective of this article is to design the decision support system for iron ore supply which would effi ciently reduce uncertainty and risk of that decision-making. The article proposes a hybrid intelligent system which represents a combination of diff erent artifi cial intelligence methods with dynamic simulation technique for that purpose.

  2. Decision Support System for Maintenance Management Using Bayesian Networks

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The maintenance process has undergone several major developments that have led to proactive considerations and the transformation from the traditional "fail and fix" practice into the "predict and prevent" proactive maintenance methodology. The anticipation action, which characterizes this proactive maintenance strategy is mainly based on monitoring, diagnosis, prognosis and decision-making modules. Oil monitoring is a key component of a successful condition monitoring program. It can be used as a proactive tool to identify the wear modes of rubbing parts and diagnoses the faults in machinery. But diagnosis relying on oil analysis technology must deal with uncertain knowledge and fuzzy input data. Besides other methods, Bayesian Networks have been extensively applied to fault diagnosis with the advantages of uncertainty inference; however, in the area of oil monitoring, it is a new field. This paper presents an integrated Bayesian network based decision support for maintenance of diesel engines.

  3. Towards an integrated approach in supporting microbiological food safety decisions

    DEFF Research Database (Denmark)

    Havelaar, A.H.; Braunig, J.; Christiansen, K.; Cornu, M.; Hald, Tine; Mangen, M.J.J.; Mølbak, Lars; Pielaat, A.; Snary, E.; Van Pelt, W.; Velthuis, A.; Wahlstrom, H.

    Decisions on food safety involve consideration of a wide range of concerns including the public health impact of foodborne illness, the economic importance of the agricultural sector and the food industry, and the effectiveness and efficiency of interventions. To support such decisions, we propose...... an integrated scientific approach combining veterinary and medical epidemiology, risk assessment for the farm-to-fork food chain as well as agricultural and health economy. Scientific advice is relevant in all stages of the policy cycle: to assess the magnitude of the food safety problem, to define...... the priorities for action, to establish the causes for the problem, to choose between different control options, to define targets along the food chain and to measure success....

  4. A Decision Support Framework for Automated Screening of Diabetic Retinopathy

    Directory of Open Access Journals (Sweden)

    H. Thompson

    2006-02-01

    Full Text Available The early signs of diabetic retinopathy (DR are depicted by microaneurysms among other signs. A prompt diagnosis when the disease is at the early stage can help prevent irreversible damages to the diabetic eye. In this paper, we propose a decision support system (DSS for automated screening of early signs of diabetic retinopathy. Classification schemes for deducing the presence or absence of DR are developed and tested. The detection rule is based on binary-hypothesis testing problem which simplifies the problem to yes/no decisions. An analysis of the performance of the Bayes optimality criteria applied to DR is also presented. The proposed DSS is evaluated on the real-world data. The results suggest that by biasing the classifier towards DR detection, it is possible to make the classifier achieve good sensitivity.

  5. Malaria elimination: moving forward with spatial decision support systems.

    Science.gov (United States)

    Kelly, Gerard C; Tanner, Marcel; Vallely, Andrew; Clements, Archie

    2012-07-01

    Operational challenges facing contemporary malaria elimination have distinct geospatial elements including the need for high-resolution location-based surveillance, targeted prevention and response interventions, and effective delivery of essential services at optimum levels of coverage. Although mapping and geographical reconnaissance (GR) has traditionally played an important role in supporting malaria control and eradication, its full potential as an applied health systems tool has not yet been fully realised. As accessibility to global positioning system (GPS), geographic information system (GIS) and mobile computing technology increases, the role of an integrated spatial decision support system (SDSS) framework for supporting the increased operational demands of malaria elimination requires further exploration, validation and application; particularly in the context of resource-poor settings. PMID:22607693

  6. New Decision Support for Landslide and Other Disaster Events

    Science.gov (United States)

    Nair, U. S.; Keiser, K.; Wu, Y.; Kaulfus, A.; Srinivasan, K.; Anderson, E. R.; McEniry, M.

    2013-12-01

    An Event-Driven Data delivery (ED3) framework has been created that provides reusable services and configurations to support better data preparedness for decision support of disasters and other events by rapidly providing pre-planned access to data, special processing, modeling and other capabilities, all executed in response to criteria-based events. ED3 facilitates decision makers to plan in advance of disasters and other types of events for the data necessary for decisions and response activities. A layer of services provided in the ED3 framework allows systems to support user definition of subscriptions for data plans that will be triggered when events matching specified criteria occur. Pre-planning for data in response to events lessens the burden on decision makers in the aftermath of an event and allows planners to think through the desired processing for specialized data products. Additionally the ED3 framework provides support for listening for event alerts and support for multiple workflow managers that provide data and processing functionality in response to events. Landslides are often costly and, at times, deadly disaster events. Whereas intense and/or sustained rainfall is often the primary trigger for landslides, soil type and slope are also important factors in determining the location and timing of slope failure. Accounting for the substantial spatial variability of these factors is one of the major difficulties when predicting the timing and location of slope failures. A wireless sensor network (WSN), developed by NASA SERVIR and USRA, with peer-to-peer communication capability and low power consumption, is ideal for high spatial in situ monitoring in remote locations. In collaboration with the University of Huntsville at Alabama, WSN equipped with accelerometer, rainfall and soil moisture sensors is being integrated into an end-to-end landslide warning system. The WSN is being tested to ascertain communication capabilities and the density of

  7. Radiological emergency assessment of local decision support system

    International Nuclear Information System (INIS)

    Local decision support system has been developed based on the needs of Krsko Nuclear Power Plant for quick dose projection and it is one of important features required for proposal of intervention before actual release may occur. Radiological emergency assessment in the case of nuclear accident is based on plant status analysis, radiation monitoring data and on prediction of release of radioactive sources to the environment. There are possibilities to use automatic features to predict release source term and manual options for selection of release parameters. Advanced environmental modelling is used for assessment of atmospheric dispersion of radioactive contamination in the environment. (author)

  8. Artificial intelligence based decision support for trumpeter swan management

    Science.gov (United States)

    Sojda, Richard S.

    2002-01-01

    The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988

  9. Supply chain decision making supported by an Open books policy

    OpenAIRE

    Agndal, Henrik; Nilsson, Ulf

    2008-01-01

    Based on a study of a buyer–seller relationship in the automotive industry, this article identifies 17 different decision-making processes where openly sharing cost data—a so-called open books policy—plays an important supporting role. These processes relate to supplier selection, various activities that occur prior to production, and the full-speed production stage of the exchange process. Overall, open books plays the greatest role in the pre-production stage, although it is found to suppor...

  10. A hybrid decision support system for iron ore supply

    OpenAIRE

    A. Samolejová; J. Feliks; R. Lenort; P. Besta

    2012-01-01

    Many European metallurgical companies are forced to import iron ore from remote destinations. For these companies it is necessary to determine the amount of iron ore that will have to be ordered and to create such a delivery schedule so that the continuous operation of blast-furnace plant is not disrupted and there is no exceedingly large stock of this raw material. The objective of this article is to design the decision support system for iron ore supply which would effi ciently reduce uncer...

  11. Collaborative Decision Support Systems for Primary Health care Managers

    Directory of Open Access Journals (Sweden)

    Gunjan Pahuja

    2012-03-01

    Full Text Available In this paper, a collaborative DSS Model for health care systems and results obtained are described. The proposed framework [1] embeds expert knowledge within DSS to provide intelligent decision support, and implements the intelligent DSS using collaboration technologies. The problem space contains several Hub and Spoke networks. Information about such networks is dynamically captured and represented in a Meta-data table. This master table enables collaboration between any two networks in the problem space, through load transfer, between them. In order to show the collaboration the sample database of 15 health care centers is taken assuming that there are 5 health care centers in one network.

  12. Development of a decision support system for cost analysis.

    Science.gov (United States)

    Chae, Y M

    1989-01-01

    Korean hospitals are experiencing an increasing amount of financial difficulty due to government control of hospital rates since national health insurance has been implemented. The decision support system (DSS) was developed to provide cost and revenue information for the services rendered by each department in an effort to reduce costs. This information may be used to identify the causes of financial loss if cost exceeds revenue and to develop budgets for the next year. The DSS was developed using a micromainframe interface approach where the mainframe computer collects and summarises daily cost data and the micro computer allocates the data to each department. PMID:10304295

  13. Decision Support System for S&OP and Production Sequencing

    OpenAIRE

    Svendsen, Ole-Johan Øby

    2011-01-01

    The main objective of this thesis is to create a decision support system for Pipelife’s Sales and Operations Planning as well as a production sequencing system. This has been done by application of theory in a real case scenario.This thesis is written in cooperation with Pipelife Surnadal. Pipelife Surnadal is a producer of plastic pipes and related parts. Pipelife is a major player in the market with 150 employees and a turnover of around 700 million NOK.A literature study and a literature r...

  14. HARP - A Software Tool for Decision Support during Nuclear Emergenccies

    Czech Academy of Sciences Publication Activity Database

    Pecha, Petr; Hofman, Radek

    Bologna : University og Bologna, 2009, s. 81-82. [Handling Complexity and Uncertainty in Environmental Studies. Bologna (IT), 05.07.2009-09.07.2009] R&D Projects: GA ČR(CZ) GA102/07/1596 Institutional research plan: CEZ:AV0Z10750506 Keywords : pollution propagation * uncertainty analysis * population protection Subject RIV: AQ - Safety, Health Protection, Human - Machine http://library.utia.cas.cz/separaty/2009/AS/pecha-harp-a software tool for decision support during nuclear emergenccies.pdf

  15. The approaches for the decision support in case natural hazards

    Science.gov (United States)

    Vyazilov, Evgeny; Chunyaev, Nikita

    2013-04-01

    In spite of using highly automated systems of measurement, collecting, storing, handling, prediction and delivery of information on the marine environment, including natural hazards, the amount of damage from natural phenomena increases. Because information on the marine environment delivered to the industrial facilities not effectively used. To such information pays little attention by individual decision-makers and not always perform preventive measures necessary for reduce and prevent damage. Automation of information support will improve the efficiency management of the marine activities. In Russia develops "The Unified system of the information about World ocean" (ESIMO, http://esimo.ru/), that integrates observation, analysis, prognostic and climate data. Necessary to create tools to automatic selection natural disasters through all integrated data; notification decision-makers about arising natural hazards - software agent; provision of information in a compact form for the decision-makers; assessment of possible damage and costs to the preventive measures; providing information on the impacts of environment on economic facilities and recommendations for decision-making; the use of maps, diagrams, tables for reporting. Tools for automatic selection designed for identification of natural phenomena based on the resources ESIMO and corresponding critical values of the indicators environment. The result of this module will be constantly updated database of critical situations of environment for each object or technological process. To operational notify and provide current information about natural hazards proposes using a software agent that is installed on the computer decision-makers, which is activated in case critical situations and provides a minimum of information. In the event of natural disaster software agent should be able to inform decision-makers about this, providing information on the current situation, and the possibility for more and detailed

  16. Supporting Coral Reef Ecosystem Management Decisions Appropriate to Climate Change

    Science.gov (United States)

    Hendee, J. C.; Fletcher, P.; Shein, K. A.

    2013-05-01

    There has been a perception that the myriad of environmental information products derived from satellite and other instrumental sources means ipso facto that there is a direct use for them by environmental managers. Trouble is, as information providers, for the most part we don't really know what decisions managers face daily, nor is it a trivial matter to ascertain the effect of management decisions on the environment, at least in a time frame that facilitates timely maintenance and enhancement of decision support software. To bridge this gap in understanding, we conducted a Needs Assessment (using methodology from the NOAA/Coastal Services Center's Product Design and Evaluation training program) from December, 2011 through May, 2012, in which we queried 15 resource managers in southeast Florida to identify the types of climate data and information products they needed to understand the effects of climate change in their region of purview, and how best these products should be delivered and subsequently enhanced or corrected. Our intent has been to develop a suite of software and information products customized specifically for environmental managers. This report summarizes our success to date, including a report on the development of software for gathering and presenting specific types of climate data, and a narrative about how some U.S. government sponsored efforts, such as Giovanni and TerraVis, as well as non-governmental sponsored efforts such as Marxan, Zonation, SimCLIM, and other off-the-shelf software might be customized for use in specific regions.

  17. Decision support system for the analysis of hospital operation indicators.

    Science.gov (United States)

    Wu, Fan; Lin, Jiunn Rong; Tsai, Wen-Chen

    2002-12-01

    The inauguration of national health insurance (NHI) in many countries and their worsening financial condition has increased the sensitivity to operational cost and efficiency in hospitals. For several years, hospitals have been monitoring their operations by analyzing the financial and operational reports that are provided. Because of the rapidly changing character of the medical industry, statistical data shown on paper are no longer sufficient for decision makers. This paper describes a decision support system (DSS) for hospital administrators to assist in analyzing their operations efficiently and precisely. In hospitals, operational data of outpatients and inpatients are now stored on computers, resulting in much easier and faster data acquisition for administrators. The proposed system makes suggestions to hospital administrators and is able to self-learn to improve its future usefulness. With the dual capabilities of integrating evaluations and data collecting, the system can assist administrators in discovering and resolving problems quickly. The system provides multidimensional and multilevel analyses, by using data warehousing techniques, and generates appropriate advice to users by employing decision-making methodology. The self-learning function of the system makes it work like an expert, continually modifying its content (knowledge) and generating advice that is promptly updated to accord with changes in the medical industry. PMID:12594099

  18. Decision-Making Amplification under Uncertainty: An Exploratory Study of Behavioral Similarity and Intelligent Decision Support Systems

    Science.gov (United States)

    Campbell, Merle Wayne

    2013-01-01

    Intelligent decision systems have the potential to support and greatly amplify human decision-making across a number of industries and domains. However, despite the rapid improvement in the underlying capabilities of these "intelligent" systems, increasing their acceptance as decision aids in industry has remained a formidable challenge.…

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

    Directory of Open Access Journals (Sweden)

    Xinqian Li

    2014-12-01

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

  20. Ecological user interface for emergency management decision support systems

    DEFF Research Database (Denmark)

    Andersen, V.

    2003-01-01

    The user interface for decision support systems is normally structured for presenting relevant data for the skilled user in order to allow fast assessment and action of the hazardous situation, or for more complex situations to present the relevant rules and procedures to be followed in order to...... abstraction supporting the situation assessment and remedial actions based on the domain knowledge of the user. The concept of ecological user interface has been tested and appreciated in a variety of other domains using prototypes designed to be representative of industrial processes. The purpose of this...... paper is to discuss the possibility of using the same principles for emergency management with the aim of improved performance in complex and unanticipated situations....

  1. A decision support system for the reading of ancient documents

    DEFF Research Database (Denmark)

    Roued-Cunliffe, Henriette

    2011-01-01

    The research presented in this thesis is based in the Humanities discipline of Ancient History and begins by attempting to understand the interpretation process involved in reading ancient documents and how this process can be aided by computer systems such as Decision Support Systems (DSS). The...... thesis balances between the use of IT tools to aid Humanities research and the understanding that Humanities research must involve human beings. It does not attempt to develop a system that can automate the reading of ancient documents. Instead it seeks to demonstrate and develop tools that can support......, by remembering complex reasoning, can aid the process of interpretation that is reading ancient documents. It is based on the idea that the interpretation process goes through a network of interpretation. The network of interpretation illustrates a recursive process where scholars move between...

  2. Decision Support for Integrated Energy-Water Planning

    Science.gov (United States)

    Tidwell, V. C.; William, H.; Klise, G.; Kobos, P. H.; Malczynski, L. A.

    2008-12-01

    Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 40% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. To meet their demand for water, proposed power plants must often target waterways and aquifers prone to overdraft or which may be home to environmentally sensitive species. Acquisition of water rights, permits and public support may therefore be a formidable hurdle when licensing new power plants. Given these current difficulties, what does the future hold when projected growth in population and the economy may require a 30% increase in power generation capacity by 2025? Technology solutions can only take us so far, as noted by the National Energy-Water Roadmap Exercise. This roadmap identified the need for long-term and integrated resource planning supported with scientifically credible models as a leading issue. To address this need a decision support framework is being developed that targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. The framework integrates analysis and optimization capabilities to help identify potential trade-offs, and "best" alternatives among an overwhelming number of energy/water options and objectives. The decision support tool is comprised of three basic elements: a system dynamics model coupling the physical and economic systems important to integrated energy-water planning and management; an optimization toolbox; and a software wrapper that integrates the aforementioned elements along with additional external energy/water models, databases, and visualization products. An interactive interface allows direct interaction with the model and access to real-time results organized according to a variety of reference systems, e.g., from a political, watershed, or electric power grid perspective. With this unique synthesis of various

  3. Integrated Decision Support for Global Environmental Change Adaptation

    Science.gov (United States)

    Kumar, S.; Cantrell, S.; Higgins, G. J.; Marshall, J.; VanWijngaarden, F.

    2011-12-01

    Environmental changes are happening now that has caused concern in many parts of the world; particularly vulnerable are the countries and communities with limited resources and with natural environments that are more susceptible to climate change impacts. Global leaders are concerned about the observed phenomena and events such as Amazon deforestation, shifting monsoon patterns affecting agriculture in the mountain slopes of Peru, floods in Pakistan, water shortages in Middle East, droughts impacting water supplies and wildlife migration in Africa, and sea level rise impacts on low lying coastal communities in Bangladesh. These environmental changes are likely to get exacerbated as the temperatures rise, the weather and climate patterns change, and sea level rise continues. Large populations and billions of dollars of infrastructure could be affected. At Northrop Grumman, we have developed an integrated decision support framework for providing necessary information to stakeholders and planners to adapt to the impacts of climate variability and change at the regional and local levels. This integrated approach takes into account assimilation and exploitation of large and disparate weather and climate data sets, regional downscaling (dynamic and statistical), uncertainty quantification and reduction, and a synthesis of scientific data with demographic and economic data to generate actionable information for the stakeholders and decision makers. Utilizing a flexible service oriented architecture and state-of-the-art visualization techniques, this information can be delivered via tailored GIS portals to meet diverse set of user needs and expectations. This integrated approach can be applied to regional and local risk assessments, predictions and decadal projections, and proactive adaptation planning for vulnerable communities. In this paper we will describe this comprehensive decision support approach with selected applications and case studies to illustrate how this

  4. Implementing a decision support system (DSS in e-business

    Directory of Open Access Journals (Sweden)

    Alexandra Ruiz G.

    2010-05-01

    Full Text Available Decision support systems (DSS and e-business (EB have emerged as separate areas. However, currently, and for some years now, DSS and EB have become merged to provide customers with greater benefits and added value. There are different types of DSS and different categories and business models for EB; one area’s applicability to the other thus expands the possible combi- nations which can arise from such different categories. Some representative examples would include auction sites which, through applying intelligent agents, can learn about which products to offer or when and where to sell them; DSS allow a company’s in- formation avilable in web portals for customers and employees to be accessed in a controlled way and decisions thus made; vir- tual stores may be positively affected by data mining and data warehousing being applied; complex algorithms could be used in customer relationship management for predicting and analysing “what would happen if” to identify revenue opportunities in com- petitive markets; and a wide range of other applications where imagination is the limit. Research into DSS / BE must be ongoing due to the constant emergence of new business models and DSS subsystems. Applications can be varied and provide bi-directio- nal support for each one. New interaction mechanisms and efforts to satisfy customers are also the focus of inspiration for new applications for DSS systems in EB.

  5. How Turing and Wolf influenced my Decision Support Systems.

    Science.gov (United States)

    Richards, Bernard

    2013-01-01

    Decision Support Systems (DSS) have a vital role to play in today's scenario for Patient Care. They can embody a vast knowledge not normally found in one individual where diagnosis and treatment are involved. This paper highlights the training in minute details and precise mathematics needed in a successful DSS and indicates how such attention-to-detail was instilled into the writer as a result of working with Alan Turing and Emil Wolf who have both since achieved world-wide recognition in their own fields as a result of international publicity by the current writer. The article discusses four Decision Support Systems written by the present writer all of which have been shown to improve patient treatment and care, and which are of such complexity that, without their use, patient care would fall short of optimum. The Systems considered are those for Intensive Care Units, Cardiovascular Surgery, a Programmed Investigation Unit, and Diagnosis of Congenital Abnormalities. All these Systems have performed better than the human alternatives and have shown their value in the improvement of patient care. PMID:23542962

  6. Electronic oral health record for decision support in dentistry

    Czech Academy of Sciences Publication Activity Database

    Zvárová, Jana; Chleborád, K.; Zvára, K.; Dostálová, T.

    Warsaw: Miedzynarodowe Centrum Biocybernetyki, 2014 - (Bobrowski, L.; Mansmann, U.; Enachescu, C.), s. 10-12. (Lecture notes of the ICB seminars). [International seminar statistics and clinical practice /9./. Warsaw (PL), 01.06.2014-04.06.2014] Grant ostatní: Prvouk(CZ) P2/LF1/6; Prvouk(CZ) P29/LF2 Institutional support: RVO:67985807 Keywords : electronic health record * electronic oral health record * forensic dentistry Subject RIV: IN - Informatics, Computer Science

  7. Automatic system testing of a decision support system for insulin dosing using Google Android.

    Science.gov (United States)

    Spat, Stephan; Höll, Bernhard; Petritsch, Georg; Schaupp, Lukas; Beck, Peter; Pieber, Thomas R

    2013-01-01

    Hyperglycaemia in hospitalized patients is a common and costly health care problem. The GlucoTab system is a mobile workflow and decision support system, aiming to facilitate efficient and safe glycemic control of non-critically ill patients. Being a medical device, the GlucoTab requires extensive and reproducible testing. A framework for high-volume, reproducible and automated system testing of the GlucoTab system was set up applying several Open Source tools for test automation and system time handling. The REACTION insulin titration protocol was investigated in a paper-based clinical trial (PBCT). In order to validate the GlucoTab system, data from this trial was used for simulation and system tests. In total, 1190 decision support action points were identified and simulated. Four data points (0.3%) resulted in a GlucoTab system error caused by a defective implementation. In 144 data points (12.1%), calculation errors of physicians and nurses in the PBCT were detected. The test framework was able to verify manual calculation of insulin doses and detect relatively many user errors and workflow anomalies in the PBCT data. This shows the high potential of the electronic decision support application to improve safety of implementation of an insulin titration protocol and workflow management system in clinical wards. PMID:23542995

  8. Design of a decision support system for preventive maintenance planning in health structures.

    Science.gov (United States)

    Miniati, Roberto; Dori, Fabrizio; Gentili, Guido Biffi

    2012-01-01

    The appropriate maintenance of medical devices, including performance inspections and preventive maintenance, is fundamental in mitigating clinical risk caused by adverse events in health care. Although several models for managing and planning preventive maintenance have been developed, the problem is lacking in standard methodology and still presents an open challenge for today's health experts. This paper aims to provide and develop methodology together with support systems able to assist decision makers in constructing preventive maintenance and performance inspection plans, taking into account both the technical and economic needs of hospital clinical engineering departments. Interventions by decision makers are of crucial importance within complex situations where large numbers, types of devices and different contractual situations are involved. SISMA system has achieved optimal results with minimum expense and maximum security for patients and technicians at the University Hospital of Florence where it has been applied in actual case studies. PMID:22735735

  9. Developing genomic knowledge bases and databases to support clinical management: current perspectives

    Directory of Open Access Journals (Sweden)

    Huser V

    2014-09-01

    Full Text Available Vojtech Huser,1 Murat Sincan,2,3 James J Cimino1,4 1Laboratory for Informatics Development, National Institutes of Health Clinical Center, Bethesda, MD, USA; 2Undiagnosed Diseases Program, 3Office of the Clinical Director, National Human Genome Research Institute, National Institutes of Health, MD, USA; 4National Library of Medicine, National Institutes of Health, MD, USA Abstract: Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward. Keywords: personalized medicine, knowledge bases, databases, clinical decision support, clinical informatics

  10. Risk and uncertainty in the structure of management decision support

    International Nuclear Information System (INIS)

    The monograph is structured into five chapters addressing the following subject matters: 1 - The risk descriptor implied by the power systems with nuclear injection; 1.1 - Concepts and operators for describing the nuclear power risk; 1.2 - Risk approach in a holistic conception; 2 - Modelling the risk in the frame of re-engineering concept; 2.1 - Defining and interpreting the power re-engineering; 2.2 - Managerial re-engineering of power production systems; 3 - Informatics system of managing the power objectives with nuclear injection; 3.1 - Informatics systems for risk at the level of CANDU - 600 nuclear plant; 3.2. - Expert function structure applicable to the management of power objectives with nuclear injection; 4 - Assisting support in the operation of nuclear facilities; 4.1 - Assisting support system for nuclear plant operation; 4.2 - Program products for dedicated drivers; 5 - The management decision activities at the level of power systems with nuclear injection; 5.1 - Preliminaries in making power decision; 5.2 - Applications of decision models of sustainable power systems with nuclear injection; 5.3 - Re-engineering of power decision in the frame of maximal utility theory. The successful application of re-engineering concept is based on knowledge and managing capacity of design leadership and its ability of dealing the error generating sources. The main stages of implementing successfully the re-engineering are: - Replacing the pollution processes instead of adjusting measures; - Raising the designer responsibility by radical innovation of processes' architecture; - Re-designing the processes by basic changes at the level of the management functions and structures; - Raising the personnel professionalism by motivation as optimal way of improving the workers mentalities; - Accurate definition of objectives in the frame of re-engineering program; - Application of re-engineering in industrial units starting from the management level; - Selecting as general

  11. A review of clinical decision-making: Models and current research

    OpenAIRE

    Banning, M

    2007-01-01

    Aims and objectives: The aim of this paper was to review the current literature with respect to clinical decision-making models and the educational application of models to clinical practice. This was achieved by exploring the function and related research of the three available models of clinical decision making: information processing model, the intuitive-humanist model and the clinical decision making model. Background: Clinical decision-making is a unique process that involves the inte...

  12. Decision Support Systems and Management of The River Elbe

    Science.gov (United States)

    Wind, H. G.

    The European Community demands the development of a river basin management plan for all European rivers. The European Commission has also defined a number of objectives that must be met, for instance water quality etc. For a specific river additional objectives can be formulated for other functions which are satisfied by the river like shipping, nature, water quantity etc. The objectives can be regarded as a solution space. The objectives should be satisfied under criteria such as a safe transport of water, ice and sediment. The collection of measures can be seen as a measures space. In the plan of action of the river basin management plan is outlined by which set of measures (or by which part of the measures space) the present state should be transferred into the desired state. The selection of that set of measures which is acceptable for all relevant actors, is complicated by the various demands of the actors, knowledge about impacts of measures, availability of data and the impact of processes which are outside the borders of the system. In order to support this selection process, use can be made of a decision support system. For various rivers such as the Elbe and the Danube such a system is presently under construction. During the presentation some research questions related to the development of decision support systems will be outlined, such as: Integration of social systems, ecological systems and physical systems. Internal consistency of models, data and information demand. Time horizon related to the stiffness of the model system and the external developments. Information supply and information demand: a fallacy?

  13. Decision support system based on knowledge base in Guangdong nuclear power plant

    International Nuclear Information System (INIS)

    The decision support system is one of the assistant decision tools to the decision-makers, and it is a complex systematic project to found the decision support system. This paper introduces the establishing process of the decision support system in Guangdong Nuclear Power Plant based on knowledge base. The main method includes three steps. First is organizing, mining and getting the knowledge. Second is constructing the knowledge base based on RDBMS. Third is setting up the decision support system. Practice shows that this method has certain practical value. (authors)

  14. A Methodology to Support Decision Making in Flood Plan Mitigation

    Science.gov (United States)

    Biscarini, C.; di Francesco, S.; Manciola, P.

    2009-04-01

    The focus of the present document is on specific decision-making aspects of flood risk analysis. A flood is the result of runoff from rainfall in quantities too great to be confined in the low-water channels of streams. Little can be done to prevent a major flood, but we may be able to minimize damage within the flood plain of the river. This broad definition encompasses many possible mitigation measures. Floodplain management considers the integrated view of all engineering, nonstructural, and administrative measures for managing (minimizing) losses due to flooding on a comprehensive scale. The structural measures are the flood-control facilities designed according to flood characteristics and they include reservoirs, diversions, levees or dikes, and channel modifications. Flood-control measures that modify the damage susceptibility of floodplains are usually referred to as nonstructural measures and may require minor engineering works. On the other hand, those measures designed to modify the damage potential of permanent facilities are called non-structural and allow reducing potential damage during a flood event. Technical information is required to support the tasks of problem definition, plan formulation, and plan evaluation. The specific information needed and the related level of detail are dependent on the nature of the problem, the potential solutions, and the sensitivity of the findings to the basic information. Actions performed to set up and lay out the study are preliminary to the detailed analysis. They include: defining the study scope and detail, the field data collection, a review of previous studies and reports, and the assembly of needed maps and surveys. Risk analysis can be viewed as having many components: risk assessment, risk communication and risk management. Risk assessment comprises an analysis of the technical aspects of the problem, risk communication deals with conveying the information and risk management involves the decision process

  15. A Collaborative Decision Environment to Support UAV Wildfire Monitoring Missions

    Science.gov (United States)

    Frost, C. R.; Enomoto, F. Y.; D'Ortenzio, M. V.; Nguyen, Q. B.

    2006-12-01

    NASA developed the Collaborative Decision Environment (CDE), the ground-based component of its Intelligent Mission Management (IMM) technology for science missions employing long endurance unmanned aerial vehicles (UAVs). The CDE was used to support science mission planning and decision-making for a NASA- and U.S. Forest Service-sponsored mission to monitor wildfires in the western United States using a multi- spectral imager flown onboard the General Atomics Altair UAV in summer of 2006. The CDE is a ground-based system that provides the mission/science team with situational awareness, collaboration, and decision tools. The CDE is used for pre-flight planning, mission monitoring, and visualization of acquired data. It integrates external data products used for planning and executing a mission, such as weather, large wildfire locations, satellite-derived fire detection data, temporarily restricted airspace, and satellite imagery. While a prototype CDE was developed as a Java-based client/server application in 2004-2005, the team investigated the use of Google Earth to take advantage of its 3-D visualization capabilities, friendly user interface, and enhanced graphics performance. External data is acquired via the Internet by leveraging established and emerging Open Geospatial Consortium (OGC) standards and is re-formatted into the Keyhole Markup Language (KML) specification used by Google Earth. Aircraft flight position and sensor data products are relayed from the instrument ground station to CDE servers where they are made available to users. An instant messaging chat server is used to facilitate real-time communication between remote users. This paper will present an overview of the CDE system architecture, and discuss how science user input was crucial to shaping and developing the system. Examples from the UAV mission will be used to illustrate the presentation. Plans for future development work to improve mission operations, such as integration with

  16. Merging Air Quality and Public Health Decision Support Systems

    Science.gov (United States)

    Hudspeth, W. B.; Bales, C. L.

    2003-12-01

    The New Mexico Air Quality Mapper (NMAQM) is a Web-based, open source GIS prototype application that Earth Data Analysis Center is developing under a NASA Cooperative Agreement. NMAQM enhances and extends existing data and imagery delivery systems with an existing Public Health system called the Rapid Syndrome Validation Project (RSVP). RSVP is a decision support system operating in several medical and public health arenas. It is evolving to ingest remote sensing data as input to provide early warning of human health threats, especially those related to anthropogenic atmospheric pollutants and airborne pathogens. The NMAQM project applies measurements of these atmospheric pollutants, derived from both remotely sensed data as well as from in-situ air quality networks, to both forecasting and retrospective analyses that influence human respiratory health. NMAQM provides a user-friendly interface for visualizing and interpreting environmentally-linked epidemiological phenomena. The results, and the systems made to provide the information, will be applicable not only to decision-makers in the public health realm, but also to air quality organizations, demographers, community planners, and other professionals in information technology, and social and engineering sciences. As an accessible and interactive mapping and analysis application, it allows environment and health personnel to study historic data for hypothesis generation and trend analysis, and then, potentially, to predict air quality conditions from daily data acquisitions. Additional spin off benefits to such users include the identification of gaps in the distribution of in-situ monitoring stations, the dissemination of air quality data to the public, and the discrimination of local vs. more regional sources of air pollutants that may bear on decisions relating to public health and public policy.

  17. Collaborative Decision Making: Complementary Developments of a Model and an Architecture as a Tool Support

    OpenAIRE

    Jankovic, Marija; ZARATÉ, Pascale; Bocquet, Jean-Claude; Stal-Le Cardinal, Julie

    2009-01-01

    Cardinal (2009). "Collaborative Decision Making: Complementary Developments of a Model and an Architecture as a Tool Support." International Journal of Decision Support System Technology (IJDSST) 1(1): 35-45. ABSTRACT. Recent years we can hear a lot about cooperative decision-making, group or collaborative decision-making. These types of decisions are the consequences of developed working conditions: geographical dispersion, team working, and concurrent working. In the paper we present two re...

  18. Intelligent Decision Support Systems For Admission Management In Higher Education Institutes

    OpenAIRE

    Rajan Vohra; Nripendra Narayan Das

    2011-01-01

    On the basis of their use, the DSS has received positive feedback from the University's decision makers. Making use of Intelligent Decision Support Systems (IDSS) technologies suited to provide decision support in the higher education environments, by generating and presenting relevant information and knowledge which are helpful in taking the decision regarding admission management in higher education colleges or universities. The university decision makers' needs and the DSS components are i...

  19. Data assimilation in the decision support system RODOS

    International Nuclear Information System (INIS)

    Model predictions for a rapid assessment and prognosis of possible radiological consequences after an accidental release of radionuclides play an important role in nuclear emergency management. Radiological observations, e.g. dose rate measurements, can be used to improve such model predictions. The process of combining model predictions and observations, usually referred to as data assimilation, is described in this article within the framework of the real time on-line decision support system (RODOS) for off-site nuclear emergency management in Europe. Data assimilation capabilities, based on Kalman filters,are under development for several modules of the RODOS system, including the atmospheric dispersion, deposition, food chain and hydrological models. The use of such a generic data assimilation methodology enables the propagation of uncertainties throughout the various modules of the system. This would in turn provide decision makers with uncertainty estimates taking into account both model and observation errors. This paper describes the methodology employed as well as results of some preliminary studies based on simulated data. (author)

  20. Integrated environmental decision support tool based on GIS technology

    International Nuclear Information System (INIS)

    Environmental restoration and management decisions facing the US Department of Energy require balancing trade-offs between diverse land uses and impacts over multiple spatial and temporal scales. Many types of environmental data have been collected for the Hanford Site and the Columbia River in Washington State over the past fifty years. Pacific Northwest National Laboratory (PNNL) is integrating these data into a Geographic Information System (GIS) based computer decision support tool. This tool provides a comprehensive and concise description of the current environmental landscape that can be used to evaluate the ecological and monetary trade-offs between future land use, restoration and remediation options before action is taken. Ecological impacts evaluated include effects to individual species of concern and habitat loss and fragmentation. Monetary impacts include those associated with habitat mitigation. The tool is organized as both a browsing tool for educational purposes, and as a framework that leads a project manager through the steps needed to be in compliance with environmental requirements