Science.gov

Sample records for computer decision support

  1. Computer Based Decision Support in Dentistry.

    ERIC Educational Resources Information Center

    Wagner, Ina-Veronika; Schneider, Werner

    1991-01-01

    The paper discusses computer-based decision support in the following areas: the dental patient record system; diagnosis and treatment of diseases of the oral mucosa; treatment strategy in complex clinical situations; diagnosis and treatment of functional disturbances of the masticatory system; and patient recall. (DB)

  2. Computer Based Decision Support in Dentistry.

    ERIC Educational Resources Information Center

    Wagner, Ina-Veronika; Schneider, Werner

    1991-01-01

    The paper discusses computer-based decision support in the following areas: the dental patient record system; diagnosis and treatment of diseases of the oral mucosa; treatment strategy in complex clinical situations; diagnosis and treatment of functional disturbances of the masticatory system; and patient recall. (DB)

  3. Computational Support for Technology- Investment Decisions

    NASA Technical Reports Server (NTRS)

    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.

  4. Human-Computer Interaction with Medical Decisions Support Systems

    NASA Technical Reports Server (NTRS)

    Adolf, Jurine A.; Holden, Kritina L.

    1994-01-01

    Decision Support Systems (DSSs) have been available to medical diagnosticians for some time, yet their acceptance and use have not increased with advances in technology and availability of DSS tools. Medical DSSs will be necessary on future long duration space missions, because access to medical resources and personnel will be limited. Human-Computer Interaction (HCI) experts at NASA's Human Factors and Ergonomics Laboratory (HFEL) have been working toward understanding how humans use DSSs, with the goal of being able to identify and solve the problems associated with these systems. Work to date consists of identification of HCI research areas, development of a decision making model, and completion of two experiments dealing with 'anchoring'. Anchoring is a phenomenon in which the decision maker latches on to a starting point and does not make sufficient adjustments when new data are presented. HFEL personnel have replicated a well-known anchoring experiment and have investigated the effects of user level of knowledge. Future work includes further experimentation on level of knowledge, confidence in the source of information and sequential decision making.

  5. Human-Computer Interaction with Medical Decisions Support Systems

    NASA Technical Reports Server (NTRS)

    Adolf, Jurine A.; Holden, Kritina L.

    1994-01-01

    Decision Support Systems (DSSs) have been available to medical diagnosticians for some time, yet their acceptance and use have not increased with advances in technology and availability of DSS tools. Medical DSSs will be necessary on future long duration space missions, because access to medical resources and personnel will be limited. Human-Computer Interaction (HCI) experts at NASA's Human Factors and Ergonomics Laboratory (HFEL) have been working toward understanding how humans use DSSs, with the goal of being able to identify and solve the problems associated with these systems. Work to date consists of identification of HCI research areas, development of a decision making model, and completion of two experiments dealing with 'anchoring'. Anchoring is a phenomenon in which the decision maker latches on to a starting point and does not make sufficient adjustments when new data are presented. HFEL personnel have replicated a well-known anchoring experiment and have investigated the effects of user level of knowledge. Future work includes further experimentation on level of knowledge, confidence in the source of information and sequential decision making.

  6. Mobile computing platform with decision support modules for hemotherapy.

    PubMed

    Huang, Richard S P; Nedelcu, Elena; Bai, Yu; Wahed, Amer; Klein, Kimberly; Gregoric, Igor; Patel, Manish; Kar, Biswajit; Loyalka, Pranav; Nathan, Sriram; Loubser, Paul; Weeks, Phillip A; Radovancevic, Rajko; Nguyen, Andy N D

    2014-06-01

    We describe the development of a mobile computing platform (MCP) with a decision support module (DSM) for patients in our coagulation-based hemotherapy service. The core of our MCP consists of a Microsoft Excel spreadsheet template used to gather and compute data on cardiopulmonary bypass (CPB) patients intraoperatively. The DSM is embedded into the Excel file, where the user would enter in laboratory results, and through our 45 embedded algorithms, recommendations for transfusion products would be displayed in the Excel file. The DSM has helped decrease the time it takes to come to a transfusion recommendation, helps double-check recommendations, and is an excellent tool for teaching. Furthermore, the problems that occur with a paper system have been eliminated, and we are now able to access this information easily and reliably. The development and implementation of our MCP system has greatly increased the productivity and efficiency of our hemotherapy service. Copyright© by the American Society for Clinical Pathology.

  7. Computer Based Decision Support: The Substrate for Dental Practice in the 21st Century.

    ERIC Educational Resources Information Center

    Abbey, Louis M.

    1991-01-01

    The dental profession can contribute to effective computer-based decision support through developing data standards and a comprehensive computerized patient record system that can be integrated with evolving health care decision support networks. (DB)

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

    ERIC Educational Resources Information Center

    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…

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

    ERIC Educational Resources Information Center

    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…

  10. Computer aided decision support system for cervical cancer classification

    NASA Astrophysics Data System (ADS)

    Rahmadwati, Rahmadwati; Naghdy, Golshah; Ros, Montserrat; Todd, Catherine

    2012-10-01

    Conventional analysis of a cervical histology image, such a pap smear or a biopsy sample, is performed by an expert pathologist manually. This involves inspecting the sample for cellular level abnormalities and determining the spread of the abnormalities. Cancer is graded based on the spread of the abnormal cells. This is a tedious, subjective and time-consuming process with considerable variations in diagnosis between the experts. This paper presents a computer aided decision support system (CADSS) tool to help the pathologists in their examination of the cervical cancer biopsies. The main aim of the proposed CADSS system is to identify abnormalities and quantify cancer grading in a systematic and repeatable manner. The paper proposes three different methods which presents and compares the results using 475 images of cervical biopsies which include normal, three stages of pre cancer, and malignant cases. This paper will explore various components of an effective CADSS; image acquisition, pre-processing, segmentation, feature extraction, classification, grading and disease identification. Cervical histological images are captured using a digital microscope. The images are captured in sufficient resolution to retain enough information for effective classification. Histology images of cervical biopsies consist of three major sections; background, stroma and squamous epithelium. Most diagnostic information are contained within the epithelium region. This paper will present two levels of segmentations; global (macro) and local (micro). At the global level the squamous epithelium is separated from the background and stroma. At the local or cellular level, the nuclei and cytoplasm are segmented for further analysis. Image features that influence the pathologists' decision during the analysis and classification of a cervical biopsy are the nuclei's shape and spread; the ratio of the areas of nuclei and cytoplasm as well as the texture and spread of the abnormalities

  11. Effectiveness of an Electronic Performance Support System on Computer Ethics and Ethical Decision-Making Education

    ERIC Educational Resources Information Center

    Kert, Serhat Bahadir; Uz, Cigdem; Gecu, Zeynep

    2014-01-01

    This study examined the effectiveness of an electronic performance support system (EPSS) on computer ethics education and the ethical decision-making processes. There were five different phases to this ten month study: (1) Writing computer ethics scenarios, (2) Designing a decision-making framework (3) Developing EPSS software (4) Using EPSS in a…

  12. Effectiveness of an Electronic Performance Support System on Computer Ethics and Ethical Decision-Making Education

    ERIC Educational Resources Information Center

    Kert, Serhat Bahadir; Uz, Cigdem; Gecu, Zeynep

    2014-01-01

    This study examined the effectiveness of an electronic performance support system (EPSS) on computer ethics education and the ethical decision-making processes. There were five different phases to this ten month study: (1) Writing computer ethics scenarios, (2) Designing a decision-making framework (3) Developing EPSS software (4) Using EPSS in a…

  13. EWall - Electronic Card Wall: Computational Support for Decision-Making in Collaborative Environments

    DTIC Science & Technology

    2007-12-17

    Support for Decision-Making in Collaborative Environments Final Report Grant Number: N000140410569 December 2007 Submitted to...4.2.1. Decision-Making Constructs in Distributed Environments ............................ 15 4.2.2. Collaborative Knowledge in Asynchronous...work environments . We developed an experimental computational environment referred to as the EWall system. The EWall system is designed to be used for

  14. Computer decision support system for the stomach cancer diagnosis

    NASA Astrophysics Data System (ADS)

    Polyakov, E. V.; Sukhova, O. G.; Korenevskaya, P. Y.; Ovcharova, V. S.; Kudryavtseva, I. O.; Vlasova, S. V.; Grebennikova, O. P.; Burov, D. A.; Yemelyanova, G. S.; Selchuk, V. Y.

    2017-01-01

    The paper considers the creation of the computer knowledge base containing the data of histological, cytologic, and clinical researches. The system is focused on improvement of diagnostics quality of stomach cancer - one of the most frequent death causes among oncologic patients.

  15. Computer-assisted diagnostic decision support: history, challenges, and possible paths forward.

    PubMed

    Miller, Randolph A

    2009-09-01

    This paper presents a brief history of computer-assisted diagnosis, including challenges and future directions. Some ideas presented in this article on computer-assisted diagnostic decision support systems (CDDSS) derive from prior work by the author and his colleagues (see list in Acknowledgments) on the INTERNIST-1 and QMR projects. References indicate the original sources of many of these ideas.

  16. Computer-Assisted Diagnostic Decision Support: History, Challenges, and Possible Paths Forward

    ERIC Educational Resources Information Center

    Miller, Randolph A.

    2009-01-01

    This paper presents a brief history of computer-assisted diagnosis, including challenges and future directions. Some ideas presented in this article on computer-assisted diagnostic decision support systems (CDDSS) derive from prior work by the author and his colleagues (see list in Acknowledgments) on the INTERNIST-1 and QMR projects. References…

  17. Computer-Assisted Diagnostic Decision Support: History, Challenges, and Possible Paths Forward

    ERIC Educational Resources Information Center

    Miller, Randolph A.

    2009-01-01

    This paper presents a brief history of computer-assisted diagnosis, including challenges and future directions. Some ideas presented in this article on computer-assisted diagnostic decision support systems (CDDSS) derive from prior work by the author and his colleagues (see list in Acknowledgments) on the INTERNIST-1 and QMR projects. References…

  18. Computer-based tools for decision support at the Hanford Site

    SciTech Connect

    Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.

    1992-11-01

    To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high` level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the ``glue`` or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission.

  19. Computer-based tools for decision support at the Hanford Site

    SciTech Connect

    Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.

    1992-11-01

    To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high' level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the glue'' or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission.

  20. Computer-aided decision support systems for endoscopy in the gastrointestinal tract: a review.

    PubMed

    Liedlgruber, Michael; Uhl, Andreas

    2011-01-01

    Today, medical endoscopy is a widely used procedure to inspect the inner cavities of the human body. The advent of endoscopic imaging techniques-allowing the acquisition of images or videos-created the possibility for the development of the whole new branch of computer-aided decision support systems. Such systems aim at helping physicians to identify possibly malignant abnormalities more accurately. At the beginning of this paper, we give a brief introduction to the history of endoscopy, followed by introducing the main types of endoscopes which emerged so far (flexible endoscope, wireless capsule endoscope, and confocal laser endomicroscope). We then give a brief introduction to computer-aided decision support systems specifically targeted at endoscopy in the gastrointestinal tract. Then we present general facts and figures concerning computer-aided decision support systems and summarize work specifically targeted at computer-aided decision support in the gastrointestinal tract. This summary is followed by a discussion of some common issues concerning the approaches reviewed and suggestions of possible ways to resolve them.

  1. Computer Decision Support to Improve Autism Screening and Care in Community Pediatric Clinics

    ERIC Educational Resources Information Center

    Bauer, Nerissa S.; Sturm, Lynne A.; Carroll, Aaron E.; Downs, Stephen M.

    2013-01-01

    An autism module was added to an existing computer decision support system (CDSS) to facilitate adherence to recommended guidelines for screening for autism spectrum disorders in primary care pediatric clinics. User satisfaction was assessed by survey and informal feedback at monthly meetings between clinical staff and the software team. To assess…

  2. Computer Decision Support to Improve Autism Screening and Care in Community Pediatric Clinics

    ERIC Educational Resources Information Center

    Bauer, Nerissa S.; Sturm, Lynne A.; Carroll, Aaron E.; Downs, Stephen M.

    2013-01-01

    An autism module was added to an existing computer decision support system (CDSS) to facilitate adherence to recommended guidelines for screening for autism spectrum disorders in primary care pediatric clinics. User satisfaction was assessed by survey and informal feedback at monthly meetings between clinical staff and the software team. To assess…

  3. Biomedical Informatics for Computer-Aided Decision Support Systems: A Survey

    PubMed Central

    Belle, Ashwin; Kon, Mark A.; Najarian, Kayvan

    2013-01-01

    The volumes of current patient data as well as their complexity make clinical decision making more challenging than ever for physicians and other care givers. This situation calls for the use of biomedical informatics methods to process data and form recommendations and/or predictions to assist such decision makers. The design, implementation, and use of biomedical informatics systems in the form of computer-aided decision support have become essential and widely used over the last two decades. This paper provides a brief review of such systems, their application protocols and methodologies, and the future challenges and directions they suggest. PMID:23431259

  4. Biomedical informatics for computer-aided decision support systems: a survey.

    PubMed

    Belle, Ashwin; Kon, Mark A; Najarian, Kayvan

    2013-01-01

    The volumes of current patient data as well as their complexity make clinical decision making more challenging than ever for physicians and other care givers. This situation calls for the use of biomedical informatics methods to process data and form recommendations and/or predictions to assist such decision makers. The design, implementation, and use of biomedical informatics systems in the form of computer-aided decision support have become essential and widely used over the last two decades. This paper provides a brief review of such systems, their application protocols and methodologies, and the future challenges and directions they suggest.

  5. A computer-based decision support system aids distribution in planning and control of foodservices.

    PubMed

    Hicks, Z R; Matthews, M E; Norback, J P

    1986-09-01

    Three scenarios, developed from typical situations in the foodservice, were stimulated on the Sperry 1100/80 computer to illustrate how the decision support system assisted dietitians. The scenarios included an analysis of price changes and discounts from a potential vendor; menu planning and pricing for a holiday dinner for 800 to 900 employees; and a comparison of costs between 1 day of meals for a patient on a general and a diabetic diet. In the analysis of price discounts, 1.5 hours were required for finding an acceptable solution using the decision support system. Prices were changed on 349 ingredients; then matrix multiplication within the decision support system resulted in recosting all menu items with those ingredients and provided new prices for cost per meals. Eight new ingredients, 13 menu items, and 2 menu plans for two different holiday meals were entered into the computer; precise amounts and prices for menu items and meals were obtained in 1 hour. Twelve hours was the minimum time estimated for finding a solution by hand calculations. Time to calculate costs of 27 different menu items for one patient day was estimated to be 9 hours manually. With the decision support system, cost comparisons were available in 1 hour. Both the usefulness and the potential of the decision support system were demonstrated.

  6. Enabling Water Quality Management Decision Support and Public Outreach Using Cloud-Computing Services

    NASA Astrophysics Data System (ADS)

    Sun, A. Y.; Scanlon, B. R.; Uhlman, K.

    2013-12-01

    Watershed management is a participatory process that requires collaboration among multiple groups of people. Environmental decision support systems (EDSS) have long been used to support such co-management and co-learning processes in watershed management. However, implementing and maintaining EDSS in-house can be a significant burden to many water agencies because of budget, technical, and policy constraints. Basing on experiences from several web-GIS environmental management projects in Texas, we showcase how cloud-computing services can help shift the design and hosting of EDSS from the traditional client-server-based platforms to be simple clients of cloud-computing services.

  7. Tactical Decision Making and Decision Support Systems.

    ERIC Educational Resources Information Center

    Harmon, Joel I.

    1986-01-01

    The use of computerized decision support systems in higher education for making tactical institutional decisions is reviewed, with attention to the kind of administrative problems that lie somewhere between programmed to nonprogrammed decisions and require a combination of computer support and administrative judgment. (MSE)

  8. Integration of sensing and computing in an intelligent decision support system for homeland security defense

    SciTech Connect

    Wu, Qishi; Zhu, Mengxia; Rao, Nageswara S

    2009-04-01

    We propose an intelligent decision support system based on sensor and computer networks that incorporates various component techniques for sensor deployment, data routing, distributed computing, and information fusion. The integrated system is deployed in a distributed environment composed of both wireless sensor networks for data collection and wired computer networks for data processing in support of homeland security defense. We present the system framework and formulate the analytical problems and develop approximate or exact solutions for the subtasks: (i) sensor deployment strategy based on a two-dimensional genetic algorithm to achieve maximum coverage with cost constraints; (ii) data routing scheme to achieve maximum signal strength with minimum path loss, high energy efficiency, and effective fault tolerance; (iii) network mapping method to assign computing modules to network nodes for high-performance distributed data processing; and (iv) binary decision fusion rule that derive threshold bounds to improve system hit rate and false alarm rate. These component solutions are implemented and evaluated through either experiments or simulations in various application scenarios. The extensive results demonstrate that these component solutions imbue the integrated system with the desirable and useful quality of intelligence in decision making.

  9. The Use of Computer-Aided Decision Support Systems for Complex Source Selection Decisions

    DTIC Science & Technology

    1989-09-01

    making processes under which virtually all decisions can be categorized. Optimizing. To optimize is to make the best possible decision under the... community ; 45 AFIT students may not be a representative sample. A subjective case may be made, however, that these subjects were relatively typical...career paths of the population studied, compared with that which apparently exists in the acquisition community . Discussion of Variables Major Constructs

  10. Modern data-driven decision support systems: the role of computing with words and computational linguistics

    NASA Astrophysics Data System (ADS)

    Kacprzyk, Janusz; Zadrożny, Sławomir

    2010-05-01

    We present how the conceptually and numerically simple concept of a fuzzy linguistic database summary can be a very powerful tool for gaining much insight into the very essence of data. The use of linguistic summaries provides tools for the verbalisation of data analysis (mining) results which, in addition to the more commonly used visualisation, e.g. via a graphical user interface, can contribute to an increased human consistency and ease of use, notably for supporting decision makers via the data-driven decision support system paradigm. Two new relevant aspects of the analysis are also outlined which were first initiated by the authors. First, following Kacprzyk and Zadrożny, it is further considered how linguistic data summarisation is closely related to some types of solutions used in natural language generation (NLG). This can make it possible to use more and more effective and efficient tools and techniques developed in NLG. Second, similar remarks are given on relations to systemic functional linguistics. Moreover, following Kacprzyk and Zadrożny, comments are given on an extremely relevant aspect of scalability of linguistic summarisation of data, using a new concept of a conceptual scalability.

  11. Using old technology to implement modern computer-aided decision support for primary diabetes care.

    PubMed Central

    Hunt, D. L.; Haynes, R. B.; Morgan, D.

    2001-01-01

    BACKGROUND: Implementation rates of interventions known to be beneficial for people with diabetes mellitus are often suboptimal. Computer-aided decision support systems (CDSSs) can improve these rates. The complexity of establishing a fully integrated electronic medical record that provides decision support, however, often prevents their use. OBJECTIVE: To develop a CDSS for diabetes care that can be easily introduced into primary care settings and diabetes clinics. THE SYSTEM: The CDSS uses fax-machine-based optical character recognition software for acquiring patient information. Simple, 1-page paper forms, completed by patients or health practitioners, are faxed to a central location. The information is interpreted and recorded in a database. This initiates a routine that matches the information against a knowledge base so that patient-specific recommendations can be generated. These are formatted and faxed back within 4-5 minutes. IMPLEMENTATION: The system is being introduced into 2 diabetes clinics. We are collecting information on frequency of use of the system, as well as satisfaction with the information provided. CONCLUSION: Computer-aided decision support can be provided in any setting with a fax machine, without the need for integrated electronic medical records or computerized data-collection devices. PMID:11825194

  12. Emergency physicians' attitudes and preferences regarding computed tomography, radiation exposure, and imaging decision support.

    PubMed

    Griffey, Richard T; Jeffe, Donna B; Bailey, Thomas

    2014-07-01

    Although computerized decision support for imaging is often recommended for optimizing computed tomography (CT) use, no studies have evaluated emergency physicians' (EPs') preferences regarding computerized decision support in the emergency department (ED). In this needs assessment, the authors sought to determine if EPs view overutilization as a problem, if they want decision support, and if so, the kinds of support they prefer. A 42-item, Web-based survey of EPs was developed and used to measure EPs' attitudes, preferences, and knowledge. Key contacts at local EDs sent letters describing the study to their physicians. Exploratory principal components analysis (PCA) was used to determine the underlying factor structure of multi-item scales, Cronbach's alpha was used to measure internal consistency of items on a scale, Spearman correlations were used to describe bivariate associations, and multivariable linear regression analysis was used to identify variables independently associated with physician interest in decision support. Of 235 surveys sent, 155 (66%) EPs responded. Five factors emerged from the PCA. EPs felt that: 1) CT overutilization is a problem in the ED (α = 0.75); 2) a patient's cumulative CT study count affects decisions of whether and what type of imaging study to order only some of the time (α = 0.75); 3) knowledge that a patient has had prior CT imaging for the same indication makes EPs less likely to order a CT (α = 0.42); 4) concerns about malpractice, patient satisfaction, or insistence on CTs affect CT ordering decisions (α = 0.62); and 5) EPs want decision support before ordering CTs (α = 0.85). Performance on knowledge questions was poor, with only 18% to 39% correctly responding to each of the three multiple-choice items about effective radiation doses of chest radiograph and single-pass abdominopelvic CT, as well as estimated increased risk of cancer from a 10-mSv exposure. Although EPs wanted information on patients' cumulative

  13. Decision time for clinical decision support systems.

    PubMed

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

    2014-08-01

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

  14. Institutional Research as Decision Support.

    ERIC Educational Resources Information Center

    Rohrbaugh, John

    1986-01-01

    The advent of decision support systems, specific computer applications for organizational decision-making, redefines the primary professional role of institutional researchers, but a more comprehensive understanding of organizational behavior and development is necessary for them to work well. (MSE)

  15. From clinical requirement to personalized wellness decision support: a data-driven framework for computer-supported guideline refinement.

    PubMed

    Hsueh, Pei-Yun; Lan, Ci-Wei; Deng, Vincent; Zhu, Xinxin

    2012-01-01

    Personalized wellness decision support has gained significant attention, owing to the shift to a patient-centric paradigm in healthcare domains, and the consequent availability of a wealth of patient-related data. Despite the success of data-driven analytics in improving practice outcome, there is a gap towards their deployment in guideline-based practice. In this paper we report on findings related to computer-supported guideline refinement, which maps a patient's guideline requirements to personalized recommendations that suit the patient's current context. In particular, we present a novel data-driven personalization framework, casting the mapping task as a statistical decision problem in search of a solution to maximize expected utility. The proposed framework is well suited to produce personalized recommendations based on not only clinical factors but contextual factors that reflect individual differences in non-clinical settings. We then describe its implementation within the guideline-based clinical decision support system and discuss opportunities and challenges looking forward.

  16. Computer models used to support cleanup decision-making at hazardous and radioactive waste sites

    SciTech Connect

    Moskowitz, P.D.; Pardi, R.; DePhillips, M.P.; Meinhold, A.F.

    1992-07-01

    Massive efforts are underway to cleanup hazardous and radioactive waste sites located throughout the US To help determine cleanup priorities, computer models are being used to characterize the source, transport, fate and effects of hazardous chemicals and radioactive materials found at these sites. Although, the US Environmental Protection Agency (EPA), the US Department of Energy (DOE), and the US Nuclear Regulatory Commission (NRC) have provided preliminary guidance to promote the use of computer models for remediation purposes, no Agency has produced directed guidance on models that must be used in these efforts. To identify what models are actually being used to support decision-making at hazardous and radioactive waste sites, a project jointly funded by EPA, DOE and NRC was initiated. The purpose of this project was to: (1) Identify models being used for hazardous and radioactive waste site assessment purposes; and (2) describe and classify these models. This report presents the results of this study.

  17. Computer models used to support cleanup decision-making at hazardous and radioactive waste sites

    SciTech Connect

    Moskowitz, P.D.; Pardi, R.; DePhillips, M.P.; Meinhold, A.F.

    1992-07-01

    Massive efforts are underway to cleanup hazardous and radioactive waste sites located throughout the US To help determine cleanup priorities, computer models are being used to characterize the source, transport, fate and effects of hazardous chemicals and radioactive materials found at these sites. Although, the US Environmental Protection Agency (EPA), the US Department of Energy (DOE), and the US Nuclear Regulatory Commission (NRC) have provided preliminary guidance to promote the use of computer models for remediation purposes, no Agency has produced directed guidance on models that must be used in these efforts. To identify what models are actually being used to support decision-making at hazardous and radioactive waste sites, a project jointly funded by EPA, DOE and NRC was initiated. The purpose of this project was to: (1) Identify models being used for hazardous and radioactive waste site assessment purposes; and (2) describe and classify these models. This report presents the results of this study.

  18. Clinical decision support foundations.

    PubMed

    Pradhan, Malcolm; Liaw, Siaw Teng

    2010-01-01

    This chapter gives an educational overview of: * The elements of a clinical decision; * The elements of decision making: prior probability, evidence (likelihood), posterior probability, actions, utility (value); * A framework for decision making, and support, encompassing validity, utility, importance and certainty; and * The required elements of a clinical decision support system. * The role of knowledge management in the construction and maintenance of clinical decision support.

  19. Improving Computational Efficiency of Model Predictive Control Genetic Algorithms for Real-Time Decision Support

    NASA Astrophysics Data System (ADS)

    Minsker, B. S.; Zimmer, A. L.; Ostfeld, A.; Schmidt, A.

    2014-12-01

    Enabling real-time decision support, particularly under conditions of uncertainty, requires computationally efficient algorithms that can rapidly generate recommendations. In this paper, a suite of model predictive control (MPC) genetic algorithms are developed and tested offline to explore their value for reducing CSOs during real-time use in a deep-tunnel sewer system. MPC approaches include the micro-GA, the probability-based compact GA, and domain-specific GA methods that reduce the number of decision variable values analyzed within the sewer hydraulic model, thus reducing algorithm search space. Minimum fitness and constraint values achieved by all GA approaches, as well as computational times required to reach the minimum values, are compared to large population sizes with long convergence times. Optimization results for a subset of the Chicago combined sewer system indicate that genetic algorithm variations with coarse decision variable representation, eventually transitioning to the entire range of decision variable values, are most efficient at addressing the CSO control problem. Although diversity-enhancing micro-GAs evaluate a larger search space and exhibit shorter convergence times, these representations do not reach minimum fitness and constraint values. The domain-specific GAs prove to be the most efficient and are used to test CSO sensitivity to energy costs, CSO penalties, and pressurization constraint values. The results show that CSO volumes are highly dependent on the tunnel pressurization constraint, with reductions of 13% to 77% possible with less conservative operational strategies. Because current management practices may not account for varying costs at CSO locations and electricity rate changes in the summer and winter, the sensitivity of the results is evaluated for variable seasonal and diurnal CSO penalty costs and electricity-related system maintenance costs, as well as different sluice gate constraint levels. These findings indicate

  20. Recurrent neural networks in computer-based clinical decision support for laryngopathies: an experimental study.

    PubMed

    Szkoła, Jarosław; Pancerz, Krzysztof; Warchoł, Jan

    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 ENs, we may modify and combine them with another kind of RNNs, namely, with the Jordan networks. The modified Elman-Jordan networks (EJNs) manifest a faster and more exact achievement of the target pattern. Validation experiments were carried out on speech signals of patients from the control group and with two kinds of laryngopathies.

  1. A Computer Based Decision Support System for Tailoring Logistics Support Analysis Record (LSAR) Requirements

    DTIC Science & Technology

    1989-09-01

    physical teardown logistics demonstration ( PTLD ) both to record data as a result of the PTLD , and to review the results of the PTLD against the LSAR...manually insert and describe those support items not identified in the LSAR but found to be required during the PTLD review. ENDTEXT @22,1 WAIT CLEAR

  2. Survey on computer aided decision support for diagnosis of celiac disease

    PubMed Central

    Hegenbart, Sebastian; Uhl, Andreas; Vécsei, Andreas

    2015-01-01

    Celiac disease (CD) is a complex autoimmune disorder in genetically predisposed individuals of all age groups triggered by the ingestion of food containing gluten. A reliable diagnosis is of high interest in view of embarking on a strict gluten-free diet, which is the CD treatment modality of first choice. The gold standard for diagnosis of CD is currently based on a histological confirmation of serology, using biopsies performed during upper endoscopy. Computer aided decision support is an emerging option in medicine and endoscopy in particular. Such systems could potentially save costs and manpower while simultaneously increasing the safety of the procedure. Research focused on computer-assisted systems in the context of automated diagnosis of CD has started in 2008. Since then, over 40 publications on the topic have appeared. In this context, data from classical flexible endoscopy as well as wireless capsule endoscopy (WCE) and confocal laser endomicrosopy (CLE) has been used. In this survey paper, we try to give a comprehensive overview of the research focused on computer-assisted diagnosis of CD. PMID:25770906

  3. A Compute Perspective: Delivering Decision Support Products in 24 Hours from the Airborne Snow Observatory

    NASA Astrophysics Data System (ADS)

    Ramirez, P.; Mattmann, C. A.; Painter, T. H.; Seidel, F. C.; Trangsrud, A.; Hart, A. F.; Goodale, C. E.; Boardman, J. W.; Heneghan, C.; Verma, R.; Khudikyan, S.; Boustani, M.; Zimdars, P. A.; Horn, J.; Neely, S.

    2013-12-01

    The JPL Airborne Snow Observatory (ASO) must process 100s of GB of raw data to 100s of Terabytes of derived data in 24 hour Near Real Time (NRT) latency in a geographically distributed mobile compute and data-intensive processing setting. ASO provides meaningful information to water resource managers in the Western US letting them know how much water to maintain; or release, and what the prospectus of the current snow season is in the Sierra Nevadas. Providing decision support products processed from airborne data in a 24 hour timeframe is an emergent field and required the team to develop a novel solution as this process is typically done over months. We've constructed a system that combines Apache OODT; with Apache Tika; with the Interactive Data Analysis (IDL)/ENVI programming environment to rapidly and unobtrusively generate, distribute and archive ASO data as soon as the plane lands near Mammoth Lakes, CA. Our system is flexible, underwent several redeployments and reconfigurations, and delivered this critical information to stakeholders during the recent "Snow On" campaign March 2013 - June 2013. This talk will take you through a day in the life of the compute team from data acquisition, delivery, processing, and dissemination. Within this context, we will discuss the architecture of ASO; the open source software we used; the data we stored; and how it was delivered to its users. Moreover we will discuss the logistics, system engineering, and staffing that went into the developing, deployment, and operation of the mobile compute system.

  4. Computer decision support as a source of interpretation error: the case of electrocardiograms.

    PubMed

    Tsai, Theodore L; Fridsma, Douglas B; Gatti, Guido

    2003-01-01

    The aim of this study was to determine the effect that the computer interpretation (CI) of electrocardiograms (EKGs) has on the accuracy of resident (noncardiologist) physicians reading EKGs. A randomized, controlled trial was conducted in a laboratory setting from February through June 2001, using a two-period crossover design with matched pairs of subjects randomly assigned to sequencing groups. Subjects' interpretive accuracy of discrete, cardiologist-determined EKG findings were measured as judged by a board-certified internist. Without the CI, subjects interpreted 48.9% (95% confidence interval, 45.0% to 52.8%) of the findings correctly. With the CI, subjects interpreted 55.4% (51.9% to 58.9%) correctly (p < 0.0001). When the CIs that agreed with the gold standard (Correct CIs) were not included, 53.1% (47.7% to 58.5%) of the findings were interpreted correctly. When the correct CI was included, accuracy increased to 68.1% (63.2% to 72.7%; p < 0.0001). When computer advice that did not agree with the gold standard (Incorrect CI) was not provided to the subjects, 56.7% (48.5% to 64.5%) of findings were interpreted correctly. Accuracy dropped to 48.3% (40.4% to 56.4%) when the incorrect computer advice was provided (p = 0.131). Subjects erroneously agreed with the incorrect CI more often when it was presented with the EKG 67.7% (57.2% to 76.7%) than when it was not 34.6% (23.8% to 47.3%; p < 0.0001). Computer decision support systems can generally improve the interpretive accuracy of internal medicine residents in reading EKGs. However, subjects were influenced significantly by incorrect advice, which tempers the overall usefulness of computer-generated advice in this and perhaps other areas.

  5. Computer Decision Support as a Source of Interpretation Error: The Case of Electrocardiograms

    PubMed Central

    Tsai, Theodore L.; Fridsma, Douglas B.; Gatti, Guido

    2003-01-01

    Objective: The aim of this study was to determine the effect that the computer interpretation (CI) of electrocardiograms (EKGs) has on the accuracy of resident (noncardiologist) physicians reading EKGs. Design: A randomized, controlled trial was conducted in a laboratory setting from February through June 2001, using a two-period crossover design with matched pairs of subjects randomly assigned to sequencing groups. Measurements: Subjects' interpretive accuracy of discrete, cardiologist-determined EKG findings were measured as judged by a board-certified internist. Results: Without the CI, subjects interpreted 48.9% (95% confidence interval, 45.0% to 52.8%) of the findings correctly. With the CI, subjects interpreted 55.4% (51.9% to 58.9%) correctly (p < 0.0001). When the CIs that agreed with the gold standard (Correct CIs) were not included, 53.1% (47.7% to 58.5%) of the findings were interpreted correctly. When the correct CI was included, accuracy increased to 68.1% (63.2% to 72.7%; p < 0.0001). When computer advice that did not agree with the gold standard (Incorrect CI) was not provided to the subjects, 56.7% (48.5% to 64.5%) of findings were interpreted correctly. Accuracy dropped to 48.3% (40.4% to 56.4%) when the incorrect computer advice was provided (p = 0.131). Subjects erroneously agreed with the incorrect CI more often when it was presented with the EKG 67.7% (57.2% to 76.7%) than when it was not 34.6% (23.8% to 47.3%; p < 0.0001). Conclusions: Computer decision support systems can generally improve the interpretive accuracy of internal medicine residents in reading EKGs. However, subjects were influenced significantly by incorrect advice, which tempers the overall usefulness of computer-generated advice in this and perhaps other areas. PMID:12807810

  6. Improving outcomes in radiology: bringing computer-based decision support and education to the point of care.

    PubMed

    Kahn, Charles E

    2005-04-01

    Many computer applications have been developed in radiology and other medical disciplines to help physicians make decisions. Artificial intelligence (AI)--an approach to computer-based manipulation of symbols to simulate human reasoning--forms the basis of many of these systems. This article's goals are to: acquaint the reader with the motivations and opportunities for computer-based medical decision support systems; identify AI techniques and applications in radiology decision making; assess the impact of these technologies; and consider new directions and opportunities for AI in radiology. Among the exciting new directions is the use of AI to integrate radiology reporting, online decision support, and just-in-time learning to provide useful information and continuing education that is embedded within a radiologist's daily workflow.

  7. Intelligent Support for Human Computer Interaction and Decision-Making in Distribution Planning and Scheduling Systems

    DTIC Science & Technology

    1993-02-28

    transportation planning in the Army. The work addressed frameworks and tools for human - computer interaction in systems involving large amounts of...diverse information and development of decision making models. Research on human - computer interaction involved: (1) dynamic display generation for

  8. Analysis of Human-Computer Interaction in the Expeditionary Warfare Decision Support System (EDSS)

    DTIC Science & Technology

    2004-09-01

    Interaction in the Expeditionary Warfare Decision Support System ( EDSS ) Technical Report APL-UW TR 0402 September 2004 by David W. Jones1, Max H. Miller2...benefited from Mr. Glenn Palmer’s extensive EDSS documentation and the research of Elizabeth Kreamer of the Naval Research Laboratory, Washington, D.C...UNIVERSITY OF WASHINGTON • APPLIED PHYSICS LABORATORY_________________ TR 0402 ii Abstract The Expeditionary Warfare Decision Support System ( EDSS

  9. Gray-box reservoir routing to compute flow propagation in operational forecasting and decision support systems

    NASA Astrophysics Data System (ADS)

    Russano, Euan; Schwanenberg, Dirk; Alvarado Montero, Rodolfo

    2017-04-01

    Operational forecasting and decision support systems for flood mitigation and the daily management of water resources require computationally efficient flow routing models. If backwater effects do not play an important role, a hydrological routing approach is often a pragmatic choice. It offers a reasonable accuracy at low computational costs in comparison to a more detailed hydraulic model. This work presents a nonlinear reservoir routing scheme as well as its implementation for the flow propagation between the hydro reservoir Três Marias and a downstream inundation-affected city Pirapora in Brazil. We refer to the model as a gray-box approach due to the identification of the parameter k by a data-driven approach for each reservoir of the cascade, instead of using estimates based on physical characteristics. The model reproduces the discharge at the gauge Pirapora, using 15 reservoirs in the cascade. The obtained results are compared with the ones obtained from the full-hydrodynamic model SOBEK. Results show a relatively good performance for the validation period, with a RMSE of 139.48 for the gray-box model, while the full-hydrodynamic model shows a RMSE of 136.67. The simulation time for a period of several years for the full-hydrodynamic took approximately 64s, while the gray-box model only required about 0.50s. This provides a significant speedup of the computation by only a little trade-off in accuracy, pointing at the potential of the simple approach in the context of time-critical, operational applications. Key-words: flow routing, reservoir routing, gray-box model

  10. Patient-specific computer-based decision support in primary healthcare—a randomized trial

    PubMed Central

    2014-01-01

    Background Computer-based decision support systems are a promising method for incorporating research evidence into clinical practice. However, evidence is still scant on how such information technology solutions work in primary healthcare when support is provided across many health problems. In Finland, we designed a trial where a set of evidence-based, patient-specific reminders was introduced into the local Electronic Patient Record (EPR) system. The aim was to measure the effects of such reminders on patient care. The hypothesis was that the total number of triggered reminders would decrease in the intervention group compared with the control group, indicating an improvement in patient care. Methods From July 2009 to October 2010 all the patients of one health center were randomized to an intervention or a control group. The intervention consisted of patient-specific reminders concerning 59 different health conditions triggered when the healthcare professional (HCP) opened and used the EPR. In the intervention group, the triggered reminders were shown to the HCP; in the control group, the triggered reminders were not shown. The primary outcome measure was the change in the number of reminders triggered over 12 months. We developed a unique data gathering method, the Repeated Study Virtual Health Check (RSVHC), and used Generalized Estimation Equations (GEE) for analysing the incidence rate ratio, which is a measure of the relative difference in percentage change in the numbers of reminders triggered in the intervention group and the control group. Results In total, 13,588 participants were randomized and included. Contrary to our expectation, the total number of reminders triggered increased in both the intervention and the control groups. The primary outcome measure did not show a significant difference between the groups. However, with the inclusion of patients followed up over only six months, the total number of reminders increased significantly less in the

  11. Clinical experience with a decision support computer program using Bayes' theorem to diagnose chest pain patients.

    PubMed

    Aase, O

    1999-01-01

    A decision support computer program (DSP) was used by the emergency room physician as a diagnostic tool on patients admitted with acute chest pain to guide the referral of these patients either to the Coronary Care Unit (CCU) or general ward. The DSP used Bayes' theorem on 38 anamnestic and clinical variables to classify patients into one of nine diagnoses. During a six months trial period 32 physicians used the DSP to diagnose 493 patients admitted with acute chest pain. The physicians referred the patients to CCU or general ward based on their clinical judgements, the ECG findings and the diagnostic estimates given by the DSP. The program correctly diagnosed 150 (84%) of 178 patients with acute myocardial infarction and 63 of 112 patients with unstable angina. However, acute ischemic heart disease (acute myocardial infarction or unstable angina) was correctly classified by the DSP for 259 (89%) of 290 patients. By using the DSP, the number of patients unnecessarily referred to CCU was reduced from 35% to 19% and the number of patients in need of CCU observation misallocated to general ward was reduced from 13% to 10%. Thus, use of the DSP in the emergency room on easily available anamnestic and clinical variables may improve referrals to the CCU, optimize therapy and resource use.

  12. Computer Decision Support Changes Physician Practice But Not Knowledge Regarding Autism Spectrum Disorders

    PubMed Central

    Carroll, A.E.; Saha, C.; Downs, S.M.

    2015-01-01

    Summary Objective To examine whether adding an autism module promoting adherence to clinical guidelines to an existing computer decision support system (CDSS) changed physician knowledge and self-reported clinical practice. Methods The CHICA (Child Health Improvement through Computer Automation) system, a CDSS, was enhanced with a module to improve management of autism in 2 of the 4 community pediatric clinics using the system. We examined the knowledge and beliefs of pediatric users using cross-sectional surveys administered at 3 time points (baseline, 12 months and 24 months post-implementation) between November 2010 and January 2013. Surveys measured knowledge, beliefs and self-reported practice patterns related to autism. Results A total of 45, 39, and 42 pediatricians responded at each time point, respectively, a 95-100% response rate. Respondents’ knowledge of autism and perception of role for diagnosis did not vary between control and intervention groups either at baseline or any of the two post-intervention time points. At baseline, there was no difference between these groups in rates in the routine use of parent-rated screening instruments for autism. However, by 12 and 24 months post-implementation there was a significant difference between intervention and control clinics in terms of the intervention clinics consistently screening eligible patients with a validated autism tool. Physicians at all clinics reported ongoing challenges to community resources for further work-up and treatment related to autism. Conclusions A CDSS module to improve primary care management of ASD in pediatric practice led to significant improvements in physician-reported use of validated screening tools to screen for ASDs. However it did not lead to corresponding changes in physician knowledge or attitudes. PMID:26448791

  13. IONIO Project: Computer-mediated Decision Support System and Communication in Ocean Science

    NASA Astrophysics Data System (ADS)

    Oddo, Paolo; Acierno, Arianna; Cuna, Daniela; Federico, Ivan; Galati, Maria Barbara; Awad, Esam; Korres, Gerasimos; Lecci, Rita; Manzella, Giuseppe M. R.; Merico, Walter; Perivoliotis, Leonidas; Pinardi, Nadia; Shchekinova, Elena; Mannarini, Gianandrea; Vamvakaki, Chrysa; Pecci, Leda; Reseghetti, Franco

    2013-04-01

    A decision Support System is composed by four main steps. The first one is the definition of the problem, the issue to be covered, decisions to be taken. Different causes can provoke different problems, for each of the causes or its effects it is necessary to define a list of information and/or data that are required in order to take the better decision. The second step is the determination of sources from where information/data needed for decision-making can be obtained and who has that information. Furthermore it must be possible to evaluate the quality of the sources to see which of them can provide the best information, and identify the mode and format in which the information is presented. The third step is relying on the processing of knowledge, i.e. if the information/data are fitting for purposes. It has to be decided which parts of the information/data need to be used, what additional data or information is necessary to access, how can information be best presented to be able to understand the situation and take decisions. Finally, the decision making process is an interactive and inclusive process involving all concerned parties, whose different views must be taken into consideration. A knowledge based discussion forum is necessary to reach a consensus. A decision making process need to be examined closely and refined, and modified to meet differing needs over time. The report is presenting legal framework and knowledge base for a scientific based decision support system and a brief exploration of some of the skills that enhances the quality of decisions taken.

  14. Decision Support Systems in Libraries.

    ERIC Educational Resources Information Center

    Heindel, Allan; Napier, H. Albert

    Following a review of the contributions of computers and managerial science/operations research to the management of libraries, this paper introduces the concept of decision support systems. DSS, a blending of these techniques, can lead to more effective decisions by library managers. A case study of the utilization of a DSS in the budgeting…

  15. Decision Support for Medical Treatment: A TPN Prescription System on a Central Hospital Computer

    PubMed Central

    Moliver, Nina; Coates, Allan L.

    1987-01-01

    An interactive decision-support system for the prescription of total or partial parenteral nutrition (TPN) is described. The system is applicable to all sizes and ages of patients, from premature infants to adults. Both the physician and the pharmacist are users of the system, with the physician using rule-based safety checks and branching algorithms to make decisions in the prescription process, and the pharmacist receiving the prescription totals electronically in order to complete further calculations needed. Since its introduction, the system appears to have increased the safety of the TPN prescription, saved time, and improved the quality and appropriateness of TPN prescriptions.

  16. Use of a computer decision support system and antimicrobial therapy appropriateness.

    PubMed

    Filice, Gregory A; Drekonja, Dimitri M; Thurn, Joseph R; Rector, Thomas S; Hamann, Galen M; Masoud, Bobbie T; Leuck, Anne-Marie; Nordgaard, Curtis L; Eilertson, Meredith K; Johnson, James R

    2013-06-01

     To determine whether antimicrobial (AM) courses ordered with an antimicrobial computer decision support system (CDSS) were more likely to be appropriate than courses ordered without the CDSS.  Retrospective cohort study. Blinded expert reviewers judged whether AM courses were appropriate, considering drug selection, route, dose, and duration.  A 279-bed university-affiliated Department of Veterans Affairs (VA) hospital.  A 500-patient random sample of inpatients who received a therapeutic AM course between October 2007 and September 2008. Intervention. An optional CDSS, available at the point of order entry in the VA computerized patient record system. CDSS courses were significantly more likely to be appropriate (111/254, 44%) compared with non-CDSS courses (81/246, 33%, P = .013). Courses were more likely to be appropriate when the initial provider diagnosis of the condition being treated was correct (168/273, 62%) than when it was incorrect, uncertain, or a sign or symptom rather than a disease (24/227, 11%, P < .001. In multivariable analysis, CDSS-ordered courses were more likely to be appropriate than non-CDSS-ordered courses (odds ratio [OR], 1.83; 95% confidence interval [CI], 1.13-2.98). Courses were also more likely to be judged appropriate when the initial provider diagnosis of the condition being treated was correct than when it was incorrect, uncertain, or a sign or symptom rather than a disease (OR, 3.56; 95% CI, 1.4-9.0).  Use of the CDSS was associated with more appropriate AM use. To achieve greater improvements, strategies are needed to improve provider diagnoses of syndromes that are infectious or possibly infectious.

  17. The expenditure of computer-related worktime using clinical decision support systems in chronic pain therapy.

    PubMed

    Hecht, Timm; Bundscherer, Anika C; Lassen, Christoph L; Lindenberg, Nicole; Graf, Bernhard M; Ittner, Karl-Peter; Wiese, Christoph H R

    2015-08-01

    Estimate the expenditure of computer-related worktime resulting from the use of clinical decision support systems (CDSS) to prevent adverse drug reactions (ADR) among patients undergoing chronic pain therapy and compare the employed check systems with respect to performance and practicability. Data were collected retrospectively from 113 medical records of patients under chronic pain therapy during 2012/2013. Patient-specific medications were checked for potential drug-drug interactions (DDI) using two publicly available CDSS, Apotheken Umschau (AU) and Medscape (MS), and a commercially available CDSS AiDKlinik® (AID). The time needed to analyze patient pharmacotherapy for DDIs was taken with a stopwatch. Measurements included the time needed for running the analysis and printing the results. CDSS were compared with respect to the expenditure of time and usability. Only patient pharmacotherapies with at least two prescribed drugs and fitting the criteria of the corresponding CDSS were analyzed. Additionally, a qualitative evaluation of the used check systems was performed, employing a questionnaire asking five pain physicians to compare and rate the performance and practicability of the three CDSSs. The AU tool took a total of 3:55:45 h with an average of 0:02:32 h for 93 analyzed patient regimens and led to the discovery of 261 DDIs. Using the Medscape interaction checker required a total of 1:28:35 h for 38 patients with an average of 0:01:58 h and a yield of 178 interactions. The CDSS AID required a total of 3:12:27 h for 97 patients with an average time of analysis of 0:01:59 h and the discovery of 170 DDIs. According to the pain physicians the CDSS AID was chosen as the preferred tool. Applying a CDSS to examine a patients drug regimen for potential DDIs causes an average extra expenditure of work time of 2:09 min, which extends patient treatment time by 25 % on average. Nevertheless, the authors believe that the extra expenditure of time employing a CDSS is

  18. A Decision Support System for Cost-Effectiveness Analysis for Control and Security of Computer Systems.

    DTIC Science & Technology

    1985-09-01

    Support System for Cost- Master’s Thesis Effectiveness Analysis for Control and September 1985 Security of Computer Systems 6. PERFORMING ORG . REPORT...F )3010 >~T .0 0 Find directory U Figulre 8. i reaFlw iara fies.obe ->~Ne8 DrbelExoue Controls Inc z W &Z ,~L. UJ. LiL La CA CC 449 -*LA- D. P Erase

  19. Anatomy of a Decision Support System.

    ERIC Educational Resources Information Center

    Chachra, Vinod; Heterick, Robert C.

    1982-01-01

    The decision support system (DSS) environment, the functional requirements of a DSS, and the architectural requirements of the computer systems and communications network necessary to support a DSS are discussed. Changes in the computing environment that are necessary to implement decision support systems are suggested. (Author/MLW)

  20. Using Computational Modeling to Assess the Impact of Clinical Decision Support on Cancer Screening within Community Health Centers

    PubMed Central

    Carney, Timothy Jay; Morgan, Geoffrey P.; Jones, Josette; McDaniel, Anna M.; Weaver, Michael; Weiner, Bryan; Haggstrom, David A.

    2014-01-01

    Our conceptual model demonstrates our goal to investigate the impact of clinical decision support (CDS) utilization on cancer screening improvement strategies in the community health care (CHC) setting. We employed a dual modeling technique using both statistical and computational modeling to evaluate impact. Our statistical model used the Spearman’s Rho test to evaluate the strength of relationship between our proximal outcome measures (CDS utilization) against our distal outcome measure (provider self-reported cancer screening improvement). Our computational model relied on network evolution theory and made use of a tool called Construct-TM to model the use of CDS measured by the rate of organizational learning. We employed the use of previously collected survey data from community health centers Cancer Health Disparities Collaborative (HDCC). Our intent is to demonstrate the added valued gained by using a computational modeling tool in conjunction with a statistical analysis when evaluating the impact a health information technology, in the form of CDS, on health care quality process outcomes such as facility-level screening improvement. Significant simulated disparities in organizational learning over time were observed between community health centers beginning the simulation with high and low clinical decision support capability. PMID:24953241

  1. The GRAIDS Trial: the development and evaluation of computer decision support for cancer genetic risk assessment in primary care.

    PubMed

    Emery, J

    2005-01-01

    The development and evaluation of computer decision support for the assessment of cancer genetic risk in primary care is reported with two series of studies described: the RAGs (Risk Assessment in Genetics) studies and the GRAIDS (Genetic Risk Assessment in an Intranet and Decision Support) Trial. In the GRAIDS Trial, 45 general practices in Eastern England have been recruited and randomised. Comparison practices attend an educational session and receive clinical guidelines about familial breast and colorectal cancer. In the intervention practices a lead clinician is trained in cancer genetics and use of the GRAIDS software. The GRAIDS software is a simple pedigree-drawing program that implements clinical guidelines for familial breast and colorectal cancer and presents individualised information about breast cancer risk in a range of formats. Outcome measures of the trial include: frequency of software use, practitioners' attitudes towards the software, total number of referrals to secondary care about familial cancer and the proportion that meet regional referral criteria, and a patient-centred measure of informed decision making. The family history will become an increasingly important tool in primary care to assess genetic risk. This research evaluates an approach to support high-quality advice about cancer genetics in primary care which could be applied more broadly as our understanding of complex disease genetics increases.

  2. Evolutionary and Neural Computing Based Decision Support System for Disease Diagnosis from Clinical Data Sets in Medical Practice.

    PubMed

    Sudha, M

    2017-09-27

    As a recent trend, various computational intelligence and machine learning approaches have been used for mining inferences hidden in the large clinical databases to assist the clinician in strategic decision making. In any target data the irrelevant information may be detrimental, causing confusion for the mining algorithm and degrades the prediction outcome. To address this issue, this study attempts to identify an intelligent approach to assist disease diagnostic procedure using an optimal set of attributes instead of all attributes present in the clinical data set. In this proposed Application Specific Intelligent Computing (ASIC) decision support system, a rough set based genetic algorithm is employed in pre-processing phase and a back propagation neural network is applied in training and testing phase. ASIC has two phases, the first phase handles outliers, noisy data, and missing values to obtain a qualitative target data to generate appropriate attribute reduct sets from the input data using rough computing based genetic algorithm centred on a relative fitness function measure. The succeeding phase of this system involves both training and testing of back propagation neural network classifier on the selected reducts. The model performance is evaluated with widely adopted existing classifiers. The proposed ASIC system for clinical decision support has been tested with breast cancer, fertility diagnosis and heart disease data set from the University of California at Irvine (UCI) machine learning repository. The proposed system outperformed the existing approaches attaining the accuracy rate of 95.33%, 97.61%, and 93.04% for breast cancer, fertility issue and heart disease diagnosis.

  3. Decision Support Systems: The Need, The Challenge.

    ERIC Educational Resources Information Center

    Roberts, Michael M.

    1982-01-01

    The evolution of decision support systems (DSS) has enabled computer and information technology to assist the management process of decision making. Decision support systems are designed to look forward in time, to forecast outcomes of uncertain events. A 70-item bibliography is included. (MLW)

  4. The Effect of Interactivity on Decision Confidence and Outcome Expectations in Computer Supported Task Environment

    ERIC Educational Resources Information Center

    Lee, Kiljae

    2013-01-01

    While interactivity is regarded as a distinguishing characteristic of computer technology, the explanation on its impact remains in its infancy. The present research investigates what it means to provide a more (or less) interactive computer interface design by attempting to uncover its cognitive influences on the user's expectation of outcome and…

  5. The Effect of Interactivity on Decision Confidence and Outcome Expectations in Computer Supported Task Environment

    ERIC Educational Resources Information Center

    Lee, Kiljae

    2013-01-01

    While interactivity is regarded as a distinguishing characteristic of computer technology, the explanation on its impact remains in its infancy. The present research investigates what it means to provide a more (or less) interactive computer interface design by attempting to uncover its cognitive influences on the user's expectation of outcome and…

  6. An Integrated Approach to Computer-Based Decision Support at the Point of Care

    PubMed Central

    Cimino, James J.

    2007-01-01

    Information needs that arise when clinicians use clinical information systems often go unresolved, forcing clinicians to defer decisions or make them with incomplete knowledge. My research characterizes these needs in order to build information systems that can help clinicians get timely answers to their questions. My colleagues and I have developed “Infobuttons”, which are links between clinical information systems and on-line knowledge resources, and have developed an “Infobutton Manager” (IM) that attempts to determine the information need based on the context of what the user is doing. The IM presents users with a set of questions, each of which is a link to an online information resource that will answer the question. The Infobutton Manager has been successfully deployed in five systems at four institutions and provides users with over 1,000 accesses to on-line health information each month, with a positive impact on patient care. PMID:18528510

  7. Personal computer based decision support system for routing nuclear spent fuel

    SciTech Connect

    Chin, Shih-Miao; Joy, D.S.; Johnson, P.E. ); Bobic, S.M.; Miaou, Shaw-Pin . Transportation Center)

    1989-11-14

    An approach has been formulated to route nuclear spent fuel over the US Interstate highway network. This approach involves the generation of alternative routes so that any potential adverse impacts will not only concentrate on regions along the shortest path between the nuclear power plant and repository. Extensive literature research on the shortest path finding algorithms has been carried out. Consequently, an extremely efficient shortest path algorithm has been implemented and significantly increases the overall system performance. State-of-the-art interactive computer graphics is used. In addition to easy-to-use pop-up menus, full color mapping and display capabilities are also incorporated. All of these features have been implemented on commonly available personal computers. 6 figs., 2 tabs.

  8. A computational framework for supporting environmental-climate-energy decision-making

    EPA Science Inventory

    GLIMPSE is a effort in which the U.S. EPA Office of Research and Development is developing tools to support long-term, coordinated environmental, climate, and energy planning. The purpose of this presentation is to discuss the underlying science questions; provide an overview of ...

  9. A computational framework for supporting environmental-climate-energy decision-making

    EPA Science Inventory

    GLIMPSE is a effort in which the U.S. EPA Office of Research and Development is developing tools to support long-term, coordinated environmental, climate, and energy planning. The purpose of this presentation is to discuss the underlying science questions; provide an overview of ...

  10. Hybrid expert system for decision supporting in the medical area: complexity and cognitive computing.

    PubMed

    Brasil, L M; de Azevedo, F M; Barreto, J M

    2001-09-01

    This paper proposes a hybrid expert system (HES) to minimise some complexity problems pervasive to the artificial intelligence such as: the knowledge elicitation process, known as the bottleneck of expert systems; the model choice for knowledge representation to code human reasoning; the number of neurons in the hidden layer and the topology used in the connectionist approach; the difficulty to obtain the explanation on how the network arrived to a conclusion. Two algorithms applied to developing of HES are also suggested. One of them is used to train the fuzzy neural network and the other to obtain explanations on how the fuzzy neural network attained a conclusion. To overcome these difficulties the cognitive computing was integrated to the developed system. A case study is presented (e.g. epileptic crisis) with the problem definition and simulations. Results are also discussed.

  11. Designing a Hydro-Economic Collaborative Computer Decision Support System: Approaches, Best Practices, Lessons Learned, and Future Trends

    NASA Astrophysics Data System (ADS)

    Rosenberg, D. E.

    2008-12-01

    Designing and implementing a hydro-economic computer model to support or facilitate collaborative decision making among multiple stakeholders or users can be challenging and daunting. Collaborative modeling is distinguished and more difficult than non-collaborative efforts because of a large number of users with different backgrounds, disagreement or conflict among stakeholders regarding problem definitions, modeling roles, and analysis methods, plus evolving ideas of model scope and scale and needs for information and analysis as stakeholders interact, use the model, and learn about the underlying water system. This presentation reviews the lifecycle for collaborative model making and identifies some key design decisions that stakeholders and model developers must make to develop robust and trusted, verifiable and transparent, integrated and flexible, and ultimately useful models. It advances some best practices to implement and program these decisions. Among these best practices are 1) modular development of data- aware input, storage, manipulation, results recording and presentation components plus ways to couple and link to other models and tools, 2) explicitly structure both input data and the meta data that describes data sources, who acquired it, gaps, and modifications or translations made to put the data in a form usable by the model, 3) provide in-line documentation on model inputs, assumptions, calculations, and results plus ways for stakeholders to document their own model use and share results with others, and 4) flexibly program with graphical object-oriented properties and elements that allow users or the model maintainers to easily see and modify the spatial, temporal, or analysis scope as the collaborative process moves forward. We draw on examples of these best practices from the existing literature, the author's prior work, and some new applications just underway. The presentation concludes by identifying some future directions for collaborative

  12. Development of computer automated decision support system for surface water quality assessment

    NASA Astrophysics Data System (ADS)

    Sharma, Asheesh; Naidu, Madhuri; Sargaonkar, Aabha

    2013-02-01

    The Overall Index of Pollution (OIP) is a single number that expresses the overall water quality by integrating measurements of 14 different physicochemical, toxicological, and bacteriological water quality parameters. It provides a simple and concise method for water quality classification as, 'Excellent', 'Acceptable', 'Slightly Polluted', 'Polluted', and 'Heavily Polluted'. OIP values range from 0 to 16. A high OIP value signals poor water quality, while a low value signals good water quality based on the classification scheme developed for India. In this paper, we present a computer-automated, user-friendly, and standalone Surface Water Quality Assessment Tool (SWQAT), which calculates OIP values and displays it on Google map. The software is developed in VB.Net and SQL database. The software application is demonstrated through water quality assessment of two rivers of India, namely Cauvery and Tungabhadra. OIP values are estimated at 10 sampling stations on the river Cauvery and at eight sampling stations on the river Tungabhadra. The Cauvery river OIP scores in the range 0.85-7.91 while for Tungabhadra river, it is in range 2.08 to 8.97. The results are useful to analyze the variations in the water quality of different sites at different times. SWQAT improves understanding of general water quality issues, communicates water quality status, and draws the need for and effectiveness of protection measures.

  13. Management Decision Support Systems: From Theory to Practice.

    ERIC Educational Resources Information Center

    Wong, Simon C. H.

    1995-01-01

    A decision support system integrates individuals' intellectual resources with computer capabilities to improve decision-making quality. This paper presents the theoretical aspects of decision making and decision support and shows how the theories can be applied in developing an operational management decision-making support system for room booking…

  14. A cyber-enabled spatial decision support system to inventory Mangroves in Mozambique: coupling scientific workflows and cloud computing

    Treesearch

    Wenwu Tang; Wenpeng Feng; Meijuan Jia; Jiyang Shi; Huifang Zuo; Christina E. Stringer; Carl C. Trettin

    2017-01-01

    Mangroves are an important terrestrial carbon reservoir with numerous ecosystem services. Yet, it is difficult to inventory mangroves because of their low accessibility. A sampling approach that produces accurate assessment while maximizing logistical integrity of inventory operation is often required. Spatial decision support systems (SDSSs) provide support for...

  15. Development of a computer-interpretable clinical guideline model for decision support in the differential diagnosis of hyponatremia.

    PubMed

    González-Ferrer, Arturo; Valcárcel, M Ángel; Cuesta, Martín; Cháfer, Joan; Runkle, Isabelle

    2017-07-01

    Hyponatremia is the most common type of electrolyte imbalance, occurring when serum sodium is below threshold levels, typically 135mmol/L. Electrolyte balance has been identified as one of the most challenging subjects for medical students, but also as one of the most relevant areas to learn about according to physicians and researchers. We present a computer-interpretable guideline (CIG) model that will be used for medical training to learn how to improve the diagnosis of hyponatremia applying an expert consensus document (ECDs). We used the PROForma set of tools to develop the model, using an iterative process involving two knowledge engineers (a computer science Ph.D. and a preventive medicine specialist) and two expert endocrinologists. We also carried out an initial validation of the model and a qualitative post-analysis from the results of a retrospective study (N=65 patients), comparing the consensus diagnosis of two experts with the output of the tool. The model includes over two-hundred "for", "against" and "neutral" arguments that are selectively triggered depending on the input value of more than forty patient-state variables. We share the methodology followed for the development process and the initial validation results, that achieved a high ratio of 61/65 agreements with the consensus diagnosis, having a kappa value of K=0.86 for overall agreement and K=0.80 for first-ranked agreement. Hospital care professionals involved in the project showed high expectations of using this tool for training, but the process to follow for a successful diagnosis and application is not trivial, as reported in this manuscript. Secondary benefits of using these tools are associated to improving research knowledge and existing clinical practice guidelines (CPGs) or ECDs. Beyond point-of-care clinical decision support, knowledge-based decision support systems are very attractive as a training tool, to help selected professionals to better understand difficult diseases that

  16. Patient-Specific Computational Modeling of Upper Extremity Arteriovenous Fistula Creation: Its Feasibility to Support Clinical Decision-Making

    PubMed Central

    Bosboom, E. Marielle H.; Kroon, Wilco; van der Linden, Wim P. M.; Planken, R. Nils; van de Vosse, Frans N.; Tordoir, Jan H. M.

    2012-01-01

    Introduction Inadequate flow enhancement on the one hand, and excessive flow enhancement on the other hand, remain frequent complications of arteriovenous fistula (AVF) creation, and hamper hemodialysis therapy in patients with end-stage renal disease. In an effort to reduce these, a patient-specific computational model, capable of predicting postoperative flow, has been developed. The purpose of this study was to determine the accuracy of the patient-specific model and to investigate its feasibility to support decision-making in AVF surgery. Methods Patient-specific pulse wave propagation models were created for 25 patients awaiting AVF creation. Model input parameters were obtained from clinical measurements and literature. For every patient, a radiocephalic AVF, a brachiocephalic AVF, and a brachiobasilic AVF configuration were simulated and analyzed for their postoperative flow. The most distal configuration with a predicted flow between 400 and 1500 ml/min was considered the preferred location for AVF surgery. The suggestion of the model was compared to the choice of an experienced vascular surgeon. Furthermore, predicted flows were compared to measured postoperative flows. Results Taken into account the confidence interval (25th and 75th percentile interval), overlap between predicted and measured postoperative flows was observed in 70% of the patients. Differentiation between upper and lower arm configuration was similar in 76% of the patients, whereas discrimination between two upper arm AVF configurations was more difficult. In 3 patients the surgeon created an upper arm AVF, while model based predictions allowed for lower arm AVF creation, thereby preserving proximal vessels. In one patient early thrombosis in a radiocephalic AVF was observed which might have been indicated by the low predicted postoperative flow. Conclusions Postoperative flow can be predicted relatively accurately for multiple AVF configurations by using computational modeling. This

  17. CHESS: a computer-based system for providing information, referrals, decision support and social support to people facing medical and other health-related crises.

    PubMed

    Gustafson, D H; Bosworth, K; Hawkins, R P; Boberg, E W; Bricker, E

    1992-01-01

    CHESS (the Comprehensive Health Enhancement Support System) is an interactive, computer-based system to support people facing health-related crises or concerns. CHESS provides information, referral to service providers, support in making tough decisions and networking to experts and others facing the same concerns. CHESS will improve access to health and human services for people who would otherwise face psychological, social, economic or geographic barriers to receiving services. CHESS has developed programs in five specific topic areas: Academic Crisis, Adult Children of Alcoholics, AIDS/HIV Infection, Breast Cancer and Sexual Assault. The lessons learned, and the structures developed, will serve as a model for future implementation of CHESS programs in a broad range of other topic areas. CHESS is designed around three major desired outcomes: 1) improving the emotional health status of users; 2) increasing the cost-effective use of health and human services; and 3) reducing the incidence of risk-taking behaviors that can lead to injury or illness. Pilot-testing and initial analysis of controlled evaluation data has shown that CHESS is extensively used, is useful and easy-to-use, and produces positive emotional outcomes. Further evaluation in continuing.

  18. Computeer-based decision support tools for evaluation of actions affecting flow and water quality in the San Joaquin Basin

    SciTech Connect

    Quinn, N.W.T.

    1993-01-01

    This document is a preliminary effort to draw together some of the important simulation models that are available to Reclamation or that have been developed by Reclamation since 1987. This document has also attempted to lay out a framework by which these models might be used both for the purposes for which they were originally intended and to support the analysis of other issues that relate to the hydrology and to salt and water quality management within the San Joaquin Valley. To be successful as components of a larger Decision Support System the models should to be linked together using custom designed interfaces that permit data sharing between models and that are easy to use. Several initiatives are currently underway within Reclamation to develop GIS - based and graphics - based decision support systems to improve the general level of understanding of the models currently in use, to standardize the methodology used in making planning and operations studies and to permit improved data analysis, interpretation and display. The decision support systems should allow greater participation in the planning process, allow the analysis of innovative actions that are currently difficult to study with present models and should lead to better integrated and more comprehensive plans and policy decisions in future years.

  19. Using computer decision support systems in NHS emergency and urgent care: ethnographic study using normalisation process theory

    PubMed Central

    2013-01-01

    Background Information and communication technologies (ICTs) are often proposed as ‘technological fixes’ for problems facing healthcare. They promise to deliver services more quickly and cheaply. Yet research on the implementation of ICTs reveals a litany of delays, compromises and failures. Case studies have established that these technologies are difficult to embed in everyday healthcare. Methods We undertook an ethnographic comparative analysis of a single computer decision support system in three different settings to understand the implementation and everyday use of this technology which is designed to deal with calls to emergency and urgent care services. We examined the deployment of this technology in an established 999 ambulance call-handling service, a new single point of access for urgent care and an established general practice out-of-hours service. We used Normalization Process Theory as a framework to enable systematic cross-case analysis. Results Our data comprise nearly 500 hours of observation, interviews with 64 call-handlers, and stakeholders and documents about the technology and settings. The technology has been implemented and is used distinctively in each setting reflecting important differences between work and contexts. Using Normalisation Process Theory we show how the work (collective action) of implementing the system and maintaining its routine use was enabled by a range of actors who established coherence for the technology, secured buy-in (cognitive participation) and engaged in on-going appraisal and adjustment (reflexive monitoring). Conclusions Huge effort was expended and continues to be required to implement and keep this technology in use. This innovation must be understood both as a computer technology and as a set of practices related to that technology, kept in place by a network of actors in particular contexts. While technologies can be ‘made to work’ in different settings, successful implementation has been

  20. The Effect of Level of Patient Acuity, Critical Care Experience, and ACLS Certification on Clinical Decision Making: Implications for Computer Decision Support Systems

    PubMed Central

    Henry, Suzanne Bakken

    1990-01-01

    This study examined the effect of patient acuity, critical care experience, and ACLS certification on clinical decision making. Each subject (N=68) completed two computerized clinical simulations. Ventricular tachycardia (VT) represented the high acuity situation and atrial flutter (AF) the lower acuity situation. Clinical decision making was measured by proficiency score, patient outcome (cure/die), and amount of data collected. In the AF simulation, proficiency scores were higher (p=.000), more dysrhythmias were cured (p<.005), and more data were collected (p=.040) than in the VT simulation. Experienced and inexperienced nurses did not differ on proficiency score, however, inexperienced nurses collected more data (p=.048) and cured fewer atrial flutter simulations (p=.04). ACLS certified nurses had higher proficiency scores (p=.033) and collected less data (p=.048). Clinical decision making on two simulations was affected by patient acuity, critical care experience, and ACLS certification. These findings have implications for the design and implementation of clinical decision support systems.

  1. Information gap decision support for contaminant remediation

    NASA Astrophysics Data System (ADS)

    Vesselinov, V. V.; O'Malley, D.

    2013-12-01

    Uncertainty quantifications and decision analyses under severe lack of information are ubiquitous in every applied field of engineering, policy, and science. A severe lack of information precludes our ability to determine unbiased probabilistic distributions for model parameters and model predictions; therefore, model and decision uncertainties due to a severe lack of information cannot be characterized probabilistically. To circumvent this problem, information gap (info-gap) theory has been developed to explicitly recognize and quantify the implications of information gaps in decision making. Here we present a decision analysis based on info-gap theory developed for a source identification problem where the locations and mass fluxes of contaminants impacting groundwater resources are unknown. The problem is characterized with a lack of information related to (1) model parameters representing contaminant migration in the aquifer, and (2) observed contamination concentration in the existing monitoring wells. These two sources of uncertainty are coupled through an inverse model where the observed concentrations are applied to estimate model parameters. The decision goal is based on contaminant predictions at points of compliance. The decision analysis is demonstrated for synthetic and real-world test cases. The applied uncertainty-quantification, decision-support techniques and computational algorithms are implemented in code MADS (Model Analyses for Decision Support; http://mads.lanl.gov). MADS is C/C++ code that provides a framework for model-based decision support. MADS performs various types of model analyses including sensitivity analysis, parameter estimation, uncertainty quantification, model calibration, selection and averaging. To perform the analyses, MADS can be coupled with any external simulators. Our efforts target development of an interactive computer-based Decision Support System (DSS) that will help domain scientist, managers, regulators, and

  2. Evaluation of selected environmental decision support software

    SciTech Connect

    Sullivan, T.M.; Moskowitz, P.D.; Gitten, M.

    1997-06-01

    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.

  3. Spatial Decision Support Workshop 2011

    DTIC Science & Technology

    2011-01-01

    report are those of the author(s) and should not contrued as an official Department of the Army position, policy or decision, unless so designated by...and temporal development of phenomena and processes ;  Complex multi-dimensional and heterogeneous data describing decision situations;  Large or...information is an integral part of DoD operations and installation management. Spatial decision support processes and systems combine GIS and other

  4. Continuous Decision Support

    DTIC Science & Technology

    2015-12-24

    without the support and patience of Mr. Rich Moore and Dr. Ross Jackson in HQ AFMC/A9A. My A9A co-workers also provided valuable insights and often...acted as sounding boards throughout the process . I would particularly like to thank Mr. Roger Moulder for his insights on design of experiments, Dr...Lance Champagne for his statistical guidance, and Dr. Brad Boehmke for his all-around help on navigating the Ph.D. process . I am indebted to Dr. Ted

  5. Using and Evaluating Administrative Decision Support Systems.

    ERIC Educational Resources Information Center

    King, William R.

    1981-01-01

    Computer technology is rapidly being integrated into decision support systems that far surpass the potential of other information systems. To take advantage of this potential, the administrator must be able to evaluate these systems in terms that are relevant to the organization. (Author/MLW)

  6. A shotgun wedding: business decision support meets clinical decision support.

    PubMed

    Oliveira, Jason

    2002-01-01

    By effectively closing the loop between the data, analytics, processes, and methods supporting business and clinical decision making, a healthcare organization closes the loop between its knowledge generation activities and its actions at the bedside: knowledge guiding actions, actions generating knowledge.

  7. Decision Support Framework (DSF) (Formerly Decision Support Platform)

    EPA Science Inventory

    The Science Advisory Board (SAB) provided several comments on the draft Ecosystem Services Research Program's (ESRP's) Multi-Year Plan (MYP). This presentation provides a response to comments related to the decision support framework (DSF) part of Long-Term Goal 1. The comments...

  8. Decision Support Framework (DSF) (Formerly Decision Support Platform)

    EPA Science Inventory

    The Science Advisory Board (SAB) provided several comments on the draft Ecosystem Services Research Program's (ESRP's) Multi-Year Plan (MYP). This presentation provides a response to comments related to the decision support framework (DSF) part of Long-Term Goal 1. The comments...

  9. Automating hypertext for decision support

    NASA Technical Reports Server (NTRS)

    Bieber, Michael

    1990-01-01

    A decision support system (DSS) shell is being constructed that can support applications in a variety of fields, e.g., engineering, manufacturing, finance. The shell provides a hypertext-style interface for 'navigating' among DSS application models, data, and reports. The traditional notion of hypertext had to be enhanced. Hypertext normally requires manually, pre-defined links. A DSS shell, however, requires that hypertext connections to be built 'on the fly'. The role of hypertext is discussed in augmenting DSS applications and the decision making process. Also discussed is how hypertext nodes, links, and link markers tailored to an arbitrary DSS application were automatically generated.

  10. Psychopharmacological Treatment in the RAISE-ETP Study: Outcomes of a Manual and Computer Decision Support System Based Intervention.

    PubMed

    Robinson, Delbert G; Schooler, Nina R; Correll, Christoph U; John, Majnu; Kurian, Benji T; Marcy, Patricia; Miller, Alexander L; Pipes, Ronny; Trivedi, Madhukar H; Kane, John M

    2017-09-15

    The Recovery After an Initial Schizophrenia Episode-Early Treatment Program compared NAVIGATE, a comprehensive program for first-episode psychosis, to clinician-choice community care over 2 years. Quality of life and psychotic and depressive symptom outcomes were found to be better with NAVIGATE. Compared with previous comprehensive first-episode psychosis interventions, NAVIGATE medication treatment included unique elements of detailed first-episode-specific psychotropic medication guidelines and a computerized decision support system to facilitate shared decision making regarding prescriptions. In the present study, the authors compared NAVIGATE and community care on the psychotropic medications prescribed, side effects experienced, metabolic outcomes, and scores on the Adherence Estimator scale, which assesses beliefs related to nonadherence. Prescription data were obtained monthly. At baseline and at 3, 6, 12, 18, and 24 months, participants reported whether they were experiencing any of 21 common antipsychotic side effects, vital signs were obtained, fasting blood samples were collected, and the Adherence Estimator scale was completed. Over the 2-year study period, compared with the 181 community care participants, the 223 NAVIGATE participants had more medication visits, were more likely to receive a prescription for an antipsychotic and more likely to receive one conforming to NAVIGATE prescribing principles, and were less likely to receive a prescription for an antidepressant. NAVIGATE participants experienced fewer side effects and gained less weight; other vital signs and cardiometabolic laboratory findings did not differ between groups. Adherence Estimator scores improved in the NAVIGATE group but not in the community care group. As part of comprehensive care services, medication prescription can be optimized for first-episode psychosis, contributing to better outcomes with a lower side effect burden than standard care.

  11. Using computational modeling to assess the impact of clinical decision support on cancer screening improvement strategies within the community health centers.

    PubMed

    Carney, Timothy Jay; Morgan, Geoffrey P; Jones, Josette; McDaniel, Anna M; Weaver, Michael; Weiner, Bryan; Haggstrom, David A

    2014-10-01

    Our conceptual model demonstrates our goal to investigate the impact of clinical decision support (CDS) utilization on cancer screening improvement strategies in the community health care (CHC) setting. We employed a dual modeling technique using both statistical and computational modeling to evaluate impact. Our statistical model used the Spearman's Rho test to evaluate the strength of relationship between our proximal outcome measures (CDS utilization) against our distal outcome measure (provider self-reported cancer screening improvement). Our computational model relied on network evolution theory and made use of a tool called Construct-TM to model the use of CDS measured by the rate of organizational learning. We employed the use of previously collected survey data from community health centers Cancer Health Disparities Collaborative (HDCC). Our intent is to demonstrate the added valued gained by using a computational modeling tool in conjunction with a statistical analysis when evaluating the impact a health information technology, in the form of CDS, on health care quality process outcomes such as facility-level screening improvement. Significant simulated disparities in organizational learning over time were observed between community health centers beginning the simulation with high and low clinical decision support capability.

  12. The Case for Conceptual and Computable Cross-Fertilization Between Audit and Feedback and Clinical Decision Support.

    PubMed

    Brown, Benjamin; Peek, Niels; Buchan, Iain

    2015-01-01

    Many patients do not receive care consistent with best practice. Health informatics interventions often attempt to address this problem by comparing care provided to patients (e.g., from electronic health record data) to quality standards (e.g., described in clinical guidelines) and feeding this information back to clinicians. Traditionally these interventions are delivered at the patient-level as computerized clinical decision support (CDS) or at the population level as audit and feedback (A&F). Both CDS and A&F can improve care for patients but are variably effective; the challenge is to understand how the efficacy can be maximized. Although CDS and A&F are traditionally considered separate approaches, we argue that the systems share common mechanisms, and efficacy may be improved by cross-fertilizing relevant features and concepts. We draw on the Health Informatics and Implementation Science literature to argue that common mechanisms include functions typically associated with the other system, in addition to other features that may prove fruitful for further research.

  13. Pilot study to validate a computer-based clinical decision support system for dyslipidemia treatment (HTE-DLP).

    PubMed

    Zamora, A; Fernández de Bobadilla, F; Carrion, C; Vázquez, G; Paluzie, G; Elosua, R; Vilaseca, M; Martín-Urda, A; Rivera, A; Plana, N; Masana, L

    2013-12-01

    Pilot study to validate a Computerized Decision Support Systems (CDS) (HTE-DLP) for improving treatment of hyperlipidemia. HTE-DLP was programmed to offer automatic specific reminders for lipid treatment. Seventy-seven patients with high cardiovascular risk were randomized. 10 expert physicians in cardiovascular-risk management were recruited. We assessed number of patients at LDL <70 mg/dl after 12 weeks of treatment. A greater proportion of intervention group reached the LDL-C <70 mg/ml [55.0% vs 12.5%, p = 0.003; OR: 3.26 IC (1.16-9.15)]. "High potency statins" and combined therapy were used more frequently in the intervention group than the control group (p = 0.001). Seven adverse effects were documented in the intervention group and two in the control group. An acceptable relationship was observed with regard to costeffectiveness in the intervention group. Physicians expressed good agreement with HTE-DLP (86.1%) and comfortable ease-of-use (85%). Use of a CDSS in high-risk cardiovascular patients resulted in a significant reduction in LDL-C levels. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  14. IBM's Health Analytics and Clinical Decision Support.

    PubMed

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

    2014-08-15

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

  15. Strategic Decision Making and Group Decision Support Systems.

    ERIC Educational Resources Information Center

    McGrath, Michael Robert

    1986-01-01

    Institutional strategic decisions require the participation of every individual with a significant stake in the solution, and group decision support systems are being developed to respond to the political and consensual problems of collective decision-making. (MSE)

  16. Evaluation of agricultural land resources by implementing a computer-based spatial decision support system for national deciders in Benin, West Africa

    NASA Astrophysics Data System (ADS)

    Roehrig, Julia; Laudien, Rainer

    2009-01-01

    The marginality index for agricultural land use, which was originally defined on a global scale, was used to evaluate agricultural land resources of Benin. For the assessment of the index, several biophysical factors limiting agricultural production under low capital input are analyzed using a fuzzy logic based algorithm. For Benin, we determined the marginality index (MI) successfully in a spatial resolution of 1km x 1km using influencing factors with a higher spatial resolution and an adapted fuzzy logic based algorithm. The results of the approach proved that the chosen indicators on a global scale are also useful indicators on a national scale. The necessary modifications were slight and mostly with the aim to increase the tangibility for national decision makers. On a national scale, data derived from remote sensing like MODIS or SRTM are interesting and embolden sources to derive input data. To support national decision makers, input data and algorithms were implemented within a computer-based Spatial Decision Support System (SDSS). With the developed SDSS 'AGROLAND' the user is able to visualize and analyze agricultural land resources based on the MI. Additionally, advanced model based raster analyses as well as the possibility of user interactions during runtime are implemented.

  17. THE COMPUTER AND CAREER DECISIONS.

    ERIC Educational Resources Information Center

    ELLIS, ALLAN B.; WETHERELL, CHARLES B.

    THE NEED FOR STUDENT ACCESS TO A COMPUTER FACILITY, THE REASONING BEHIND THIS NEED, AND A GENERAL DESCRIPTION OF THE EQUIPMENT REQUIRED WAS REPORTED IN THIS TECHNICAL MEMORANDUM. THE NEED FOR THE DEVELOPMENT OF AN INFORMATION SYSTEM FOR CAREER CHOICE WAS PRESENTED. DISCUSSIONS OF RESEARCH INTENTIONS INCLUDED (1) A MODEL OF DECISION-MAKING, (2) THE…

  18. EVALUATING ENVIRONMENTAL DECISION SUPPORT TOOLS.

    SciTech Connect

    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.

  19. Joint Command Decision Support System

    DTIC Science & Technology

    2011-06-01

    Greenley et al. 2006) resulted in the identification of a set of overarching principles for the implementation of Joint Command Decision Support (Hales...and adjustment of resources, and longer term feasibility planning. As highlighted in the Joint Staff Front End Analysis report ( Greenley et al. 2006...Townsend (2006). The Federal Response to Hurricane Katrina Lessons Learned, Washington, D.C. February 2006. Greenley , A., Baker, K. & Cochran, L. (2006

  20. Data Fusion for Decision Support

    DTIC Science & Technology

    2014-03-27

    of work in fire science were put to work, applying the Fire Susceptibility Index (FSI) on a new, 30 m scale with Landsat 8 data. Eight data sources...initial results, qualitatively validated with wildfire behavior basics, appear promising, providing a view of fire danger in the landscape not seen in...the current state of practice. Keywords: Air Force, Data Fusion, Decision Support, Emergency Management, Fire Susceptibility Index, Geographic

  1. Decision Support Methods and Tools

    NASA Technical Reports Server (NTRS)

    Green, Lawrence L.; Alexandrov, Natalia M.; Brown, Sherilyn A.; Cerro, Jeffrey A.; Gumbert, Clyde r.; Sorokach, Michael R.; Burg, Cecile M.

    2006-01-01

    This paper is one of a set of papers, developed simultaneously and presented within a single conference session, that are intended to highlight systems analysis and design capabilities within the Systems Analysis and Concepts Directorate (SACD) of the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC). This paper focuses on the specific capabilities of uncertainty/risk analysis, quantification, propagation, decomposition, and management, robust/reliability design methods, and extensions of these capabilities into decision analysis methods within SACD. These disciplines are discussed together herein under the name of Decision Support Methods and Tools. Several examples are discussed which highlight the application of these methods within current or recent aerospace research at the NASA LaRC. Where applicable, commercially available, or government developed software tools are also discussed

  2. Decision support for financial forecasting

    SciTech Connect

    Jairam, B.N.; Morris, J.D.; Emrich, M.L.; Hardee, H.K.

    1988-10-01

    A primary mission of the Budget Management Division of the Air Force is fiscal analysis. This involves formulating, justifying, and tracking financial data during budget preparation and execution. An essential requirement of this process is the ready availability and easy manipulation of past and current budget data. This necessitates the decentralization of the data. A prototypical system, BAFS (Budget Analysis and Forecasting System), that provides such a capability is presented. In its current state, the system is designed to be a decision support tool. A brief report of the budget decisions and activities is presented. The system structure and its major components are discussed. An insight into the implementation strategies and the tool used is provided. The paper concludes with a discussion of future enhancements and the system's evolution into an expert system. 4 refs., 3 figs.

  3. A decision support tool for antibiotic therapy.

    PubMed Central

    Evans, R. S.; Classen, D. C.; Pestotnik, S. L.; Clemmer, T. P.; Weaver, L. K.; Burke, J. P.

    1995-01-01

    We developed a decision support tool to assist physicians anticipating the need for antibiotic therapy. The initial screen alerts physicians of pertinent patient information, provides direct access to other essential medical information, and stimulates clinical judgment by suggesting an antibiotic regimen. The decision support tool also suggests the dose and interval for any ordered antibiotics selected by the physicians. During a 7-month pilot study, all antibiotics for patients admitted to the Shock/Trauma/Respiratory Intensive Care Unit (STRICU) were ordered using the decision support tool. Clinical data from the study period and a 12-month control period (the previous year) were collected and compared. The decision support tool was used to order antibiotics 588 times during the study period and the suggested antibiotics were used 218 (37%) times. The computer suggested dosages were used over 90% of the time. The mean cost of antibiotics was $87.00 (p < 0.04) less per patient during the study period as compared to the control period. Prospective assessment revealed only 3 antibiotic adverse drug events (ADEs) (0.9%) among 336 study patients as compared to 15 ADEs (2.4%) among 626 control patients (p = 0.164). PMID:8563367

  4. Role of Remotely Sensed Observations and Computational Systems in Support of Decision-Making in Developing and Fragile States

    NASA Technical Reports Server (NTRS)

    Khan, Maudood; Rickman, Doug; Limaye, Ashutosh; Crosson, Bill; Layman, Charles; Hemmings, Sarah

    2010-01-01

    The topics covered in this slide presentation are: (1) Post-war growth of U.S scientific enterprise, (2) Success of air quality regulations, (3) Complexity and coupled systems, (4) Advances in remote sensing technology, (5) Development planning in the 21stcentury, (5a) The challenge for policy maker and scientist, (5b) Decision-making science, (5c) Role of public-private partnerships.

  5. Solar energy decision support system

    NASA Astrophysics Data System (ADS)

    Ramachandra, T. V.; Rajeev Kumar, J.; Vamsee Krishna, S.; Shruthi, B. V.

    2006-03-01

    Energy plays a prominent role in human society. As a result of technological and industrial developments, the demand for energy is rapidly increasing. Existing power sources that are mainly fossil fuel based are leaving an unacceptable legacy of waste and pollution apart from diminishing stock of fuels. Hence, the focus is now shifted to large-scale propagation of renewable energy. Renewable energy technologies are clean sources of energy that have a much lower environmental impact than conventional energy technologies. Solar energy is one such renewable energy. Most renewable energy comes either directly or indirectly from the sun. Estimation of solar energy potential of a region requires detailed solar radiation climatology, and it is necessary to collect extensive radiation data of high accuracy covering all climatic zones of the region. In this regard, a decision support system (DSS) would help to estimate solar energy potential considering the regions’ energy requirement. This article explains the design and implementation of DSS for assessment of solar energy. The DSS with executive information systems and reporting tools helps to tap vast data resources and deliver information. The main hypothesis is that this tool can be used to form a core of practical methodology that is resilient and can be used by decision-making bodies to assess various scenarios. It also offers means of entering, accessing and interpreting the information for the purpose of sound decision-making.

  6. Solar energy decision support system

    NASA Astrophysics Data System (ADS)

    Ramachandra, T. V.; Jha, Rajeev Kumar; Vamsee Krishna, S.; Shruthi, B. V.

    2005-12-01

    Energy plays a prominent role in human society. As a result of technological and industrial development, the demand for energy is rapidly increasing. Existing power sources that are mainly fossil fuel based are leaving an unacceptable legacy of waste and pollution apart from diminishing stock of fuels. Hence, the focus is now shifted to large-scale propagation of renewable energy. Renewable energy technologies are clean sources of energy that have a much lower environmental impact than conventional energy technologies. Solar energy is one such renewable energy. Most renewable energy comes either directly or indirectly from the sun. Estimation of solar energy potential of a region requires detailed solar radiation climatology, and it is necessary to collect extensive radiation data of high accuracy covering all climatic zones of the region. In this regard, a decision support system (DSS) would help in estimating solar energy potential considering the region's energy requirement. This article explains the design and implementation of DSS for assessment of solar energy. The DSS with executive information systems and reporting tools helps to tap vast data resources and deliver information. The main hypothesis is that this tool can be used to form a core of practical methodology that will result in more resilient in time and can be used by decision-making bodies to assess various scenarios. It also offers means of entering, accessing, and interpreting the information for the purpose of sound decision making.

  7. Decision Support for Ecosystem Management (Chapter 28)

    Treesearch

    Keith Reynolds; Jennifer Bjork; Rachel Riemann Hershey; Dan Schmoldt; John Payne; Susan King; Lee DeCola; Mark J. Twery; Pat Cunningham

    1999-01-01

    This chapter presents a management perspective on decision support for ecosystem management.The Introduction provides a brief historical overview of decision support technology as it has been used in natural resource management, discusses the role of decision support in ecosystem management as we see it, and summarizes the current state of the technology.

  8. The Contribution of a Decision Support System to Educational Decision-Making Processes

    ERIC Educational Resources Information Center

    Klein, Joseph; Ronen, Herman

    2003-01-01

    In the light of reports of bias, the present study investigated the hypothesis that administrative educational decisions assisted by Decision Support Systems (DSS) are characterized by different pedagogical and organizational orientation than decisions made without computer assistance. One hundred and ten high school teachers were asked to suggest…

  9. The Contribution of a Decision Support System to Educational Decision-Making Processes

    ERIC Educational Resources Information Center

    Klein, Joseph; Ronen, Herman

    2003-01-01

    In the light of reports of bias, the present study investigated the hypothesis that administrative educational decisions assisted by Decision Support Systems (DSS) are characterized by different pedagogical and organizational orientation than decisions made without computer assistance. One hundred and ten high school teachers were asked to suggest…

  10. A Framework for Classifying Decision Support Systems

    PubMed Central

    Sim, Ida; Berlin, Amy

    2003-01-01

    Background Computer-based clinical decision support systems (CDSSs) vary greatly in design and function. A taxonomy for classifying CDSS structure and function would help efforts to describe and understand the variety of CDSSs in the literature, and to explore predictors of CDSS effectiveness and generalizability. Objective To define and test a taxonomy for characterizing the contextual, technical, and workflow features of CDSSs. Methods We retrieved and analyzed 150 English language articles published between 1975 and 2002 that described computer systems designed to assist physicians and/or patients with clinical decision making. We identified aspects of CDSS structure or function and iterated our taxonomy until additional article reviews did not result in any new descriptors or taxonomic modifications. Results Our taxonomy comprises 95 descriptors along 24 descriptive axes. These axes are in 5 categories: Context, Knowledge and Data Source, Decision Support, Information Delivery, and Workflow. The axes had an average of 3.96 coded choices each. 75% of the descriptors had an inter-rater agreement kappa of greater than 0.6. Conclusions We have defined and tested a comprehensive, multi-faceted taxonomy of CDSSs that shows promising reliability for classifying CDSSs reported in the literature. PMID:14728243

  11. The design of aircraft using the decision support problem technique

    NASA Technical Reports Server (NTRS)

    Mistree, Farrokh; Marinopoulos, Stergios; Jackson, David M.; Shupe, Jon A.

    1988-01-01

    The Decision Support Problem Technique for unified design, manufacturing and maintenance is being developed at the Systems Design Laboratory at the University of Houston. This involves the development of a domain-independent method (and the associated software) that can be used to process domain-dependent information and thereby provide support for human judgment. In a computer assisted environment, this support is provided in the form of optimal solutions to Decision Support Problems.

  12. Visual Decision Support Tool for Supporting Asset ...

    EPA Pesticide Factsheets

    Abstract:Managing urban water infrastructures faces the challenge of jointly dealing with assets of diverse types, useful life, cost, ages and condition. Service quality and sustainability require sound long-term planning, well aligned with tactical and operational planning and management. In summary, the objective of an integrated approach to infrastructure asset management is to assist utilities answer the following questions:•Who are we at present?•What service do we deliver?•What do we own?•Where do we want to be in the long-term?•How do we get there?The AWARE-P approach (www.aware-p.org) offers a coherent methodological framework and a valuable portfolio of software tools. It is designed to assist water supply and wastewater utility decision-makers in their analyses and planning processes. It is based on a Plan-Do-Check-Act process and is in accordance with the key principles of the International Standards Organization (ISO) 55000 standards on asset management. It is compatible with, and complementary to WERF’s SIMPLE framework. The software assists in strategic, tactical, and operational planning, through a non-intrusive, web-based, collaborative environment where objectives and metrics drive IAM planning. It is aimed at industry professionals and managers, as well as at the consultants and technical experts that support them. It is easy to use and maximizes the value of information from multiple existing data sources, both in da

  13. Decision support system for drinking water management

    NASA Astrophysics Data System (ADS)

    Janža, M.

    2012-04-01

    The problems in drinking water management are complex and often solutions must be reached under strict time constrains. This is especially distinct in case of environmental accidents in the catchment areas of the wells that are used for drinking water supply. The beneficial tools that can help decision makers and make program of activities more efficient are decision support systems (DSS). In general they are defined as computer-based support systems that help decision makers utilize data and models to solve unstructured problems. The presented DSS was developed in the frame of INCOME project which is focused on the long-term stable and safe drinking water supply in Ljubljana. The two main water resources Ljubljana polje and Barje alluvial aquifers are characterized by a strong interconnection of surface and groundwater, high vulnerability, high velocities of groundwater flow and pollutant transport. In case of sudden pollution, reactions should be very fast to avoid serious impact to the water supply. In the area high pressures arising from urbanization, industry, traffic, agriculture and old environmental burdens. The aim of the developed DSS is to optimize the activities in cases of emergency water management and to optimize the administrative work regarding the activities that can improve groundwater quality status. The DSS is an interactive computer system that utilizes data base, hydrological modelling, and experts' and stakeholders' knowledge. It consists of three components, tackling the different abovementioned issues in water management. The first one utilizes the work on identification, cleaning up and restoration of illegal dumpsites that are a serious threat to the qualitative status of groundwater. The other two components utilize the predictive capability of the hydrological model and scenario analysis. The user interacts with the system by a graphical interface that guides the user step-by-step to the recommended remedial measures. Consequently, the

  14. Designing a Decision-Support System for Enrollment Management.

    ERIC Educational Resources Information Center

    Glover, Robert H.

    1986-01-01

    The conceptual framework, design, and implementation plan for building a decision-support system for enrollment management at a private university are outlined, including information about the computer hardware and software used in implementation. (Author/MSE)

  15. Evaluating the impact of an integrated computer-based decision support with person-centered analytics for the management of asthma in primary care: a randomized controlled trial.

    PubMed

    Tamblyn, Robyn; Ernst, Pierre; Winslade, Nancy; Huang, Allen; Grad, Roland; Platt, Robert W; Ahmed, Sara; Moraga, Teresa; Eguale, Tewodros

    2015-07-01

    Computer-based decision support has been effective in providing alerts for preventive care. Our objective was to determine whether a personalized asthma management computer-based decision support increases the quality of asthma management and reduces the rate of out-of-control episodes. A cluster-randomized trial was conducted in Quebec, Canada among 81 primary care physicians and 4447 of their asthmatic patients. Patients were followed from the first visit for 3-33 months. The physician control group used the Medical Office of the 21st century (MOXXI) system, an integrated electronic health record. A custom-developed asthma decision support system was integrated within MOXXI and was activated for physicians in the intervention group. At the first visit, 9.8% (intervention) to 12.9% (control) of patients had out-of-control asthma, which was defined as a patient having had an emergency room visit or hospitalization for respiratory-related problems and/or more than 250 doses of fast-acting β-agonist (FABA) dispensed in the past 3 months. By the end of the trial, there was a significant increase in the ratio of doses of inhaled corticosteroid use to fast-acting β-agonist (0.93 vs. 0.69: difference: 0.27; 95% CI: 0.02-0.51; P = 0.03) in the intervention group. The overall out-of-control asthma rate was 54.7 (control) and 46.2 (intervention) per 100 patients per year (100 PY), a non-significant rate difference of -8.7 (95% CI: -24.7, 7.3; P = 0.29). The intervention's effect was greater for patients with out-of-control asthma at the beginning of the study, a group who accounted for 44.7% of the 5597 out-of-control asthma events during follow-up, as there was a reduction in the event rate of -28.4 per 100 PY (95% CI: -55.6, -1.2; P = 0.04) compared to patients with in-control asthma at the beginning of the study (-0.08 [95% CI: -10.3, 8.6; P = 0.86]). This study evaluated the effectiveness of a novel computer-assisted ADS system that facilitates systematic monitoring

  16. Evaluating the impact of an integrated computer-based decision support with person-centered analytics for the management of asthma in primary care: a randomized controlled trial

    PubMed Central

    Ernst, Pierre; Winslade, Nancy; Huang, Allen; Grad, Roland; Platt, Robert W; Ahmed, Sara; Moraga, Teresa; Eguale, Tewodros

    2015-01-01

    Background Computer-based decision support has been effective in providing alerts for preventive care. Our objective was to determine whether a personalized asthma management computer-based decision support increases the quality of asthma management and reduces the rate of out-of-control episodes. Methods A cluster-randomized trial was conducted in Quebec, Canada among 81 primary care physicians and 4447 of their asthmatic patients. Patients were followed from the first visit for 3–33 months. The physician control group used the Medical Office of the 21st century (MOXXI) system, an integrated electronic health record. A custom-developed asthma decision support system was integrated within MOXXI and was activated for physicians in the intervention group. Results At the first visit, 9.8% (intervention) to 12.9% (control) of patients had out-of-control asthma, which was defined as a patient having had an emergency room visit or hospitalization for respiratory-related problems and/or more than 250 doses of fast-acting β-agonist (FABA) dispensed in the past 3 months. By the end of the trial, there was a significant increase in the ratio of doses of inhaled corticosteroid use to fast-acting β-agonist (0.93 vs. 0.69: difference: 0.27; 95% CI: 0.02–0.51; P = 0.03) in the intervention group. The overall out-of-control asthma rate was 54.7 (control) and 46.2 (intervention) per 100 patients per year (100 PY), a non-significant rate difference of −8.7 (95% CI: −24.7, 7.3; P = 0.29). The intervention’s effect was greater for patients with out-of-control asthma at the beginning of the study, a group who accounted for 44.7% of the 5597 out-of-control asthma events during follow-up, as there was a reduction in the event rate of −28.4 per 100 PY (95% CI: −55.6, −1.2; P = 0.04) compared to patients with in-control asthma at the beginning of the study (−0.08 [95% CI: −10.3, 8.6; P = 0.86]). Discussion This study evaluated the effectiveness of a novel computer

  17. Clinical Decision Support and Palivizumab

    PubMed Central

    Hogan, A.; Michel, J.; Localio, A.R.; Karavite, D.; Song, L.; Ramos, M.J.; Fiks, A.G.; Lorch, S.; Grundmeier, R.W.

    2015-01-01

    Background and Objectives Palivizumab can reduce hospitalizations due to respiratory syncytial virus (RSV), but many eligible infants fail to receive the full 5-dose series. The efficacy of clinical decision support (CDS) in fostering palivizumab receipt has not been studied. We sought a comprehensive solution for identifying eligible patients and addressing barriers to palivizumab administration. Methods We developed workflow and CDS tools targeting patient identification and palivizumab administration. We randomized 10 practices to receive palivizumab-focused CDS and 10 to receive comprehensive CDS for premature infants in a 3-year longitudinal cluster-randomized trial with 2 baseline and 1 intervention RSV seasons. Results There were 356 children eligible to receive palivizumab, with 194 in the palivizumab-focused group and 162 in the comprehensive CDS group. The proportion of doses administered to children in the palivizumab-focused intervention group increased from 68.4% and 65.5% in the two baseline seasons to 84.7% in the intervention season. In the comprehensive intervention group, proportions of doses administered declined during the baseline seasons (from 71.9% to 62.4%) with partial recovery to 67.9% during the intervention season. The palivizumab-focused group improved by 19.2 percentage points in the intervention season compared to the prior baseline season (p < 0.001), while the comprehensive intervention group only improved 5.5 percentage points (p = 0.288). The difference in change between study groups was significant (p = 0.05). Conclusions Workflow and CDS tools integrated in an EHR may increase the administration of palivizumab. The support focused on palivizumab, rather than comprehensive intervention, was more effective at improving palivizumab administration. PMID:26767069

  18. Proceedings of the Workshop on The Human-Computer Partnership in Decision-Support Held in San Luis Obispo, California on May 2-4, 2000

    DTIC Science & Technology

    2000-09-01

    Fire Department’s course for training Fire Chiefs. This course consisted of a series of situational decision games designed to evaluate the firefighters...course for training Fire Chiefs. This course consisted of a series of situational decision games designed to evaluate the firefighters ability to deal... Leads to anchor desks & home echelons, creating smarter warriors, improved PERSTEMPO, higher morale & better support. Leads to anchor desks ho e

  19. Technical challenges, past and future, in implementing THERESA: a one million patient, one billion item computer-based patient record and decision support system

    NASA Astrophysics Data System (ADS)

    Camp, Henry N.

    1996-02-01

    Challenges in implementing a computer-based patient record (CPR)--such as absolute data integrity, high availability, permanent on-line storage of very large complex records, rapid search times, ease of use, commercial viability, and portability to other hospitals and doctor's offices--are given along with their significance, the solutions, and their successes. The THERESA CPR has been used sine 1983 in direct patient care by a public hospital that is the primary care provider to 350,000 people. It has 1000 beds with 45,000 admissions and 750,000 outpatient visits annually. The system supports direct provider entry, including by physicians, of complete medical `documents'. Its demonstration site currently contains 1.1 billion data items on 1 million patients. It is also a clinical decision-aiding tool used for quality assurance and cost containment, for teaching as faculty and students can easily find and `thumb through' all cases similar to a particular study, and for research with over a billion medical items that can be searched and analyzed on-line within context and with continuity. The same software can also run in a desktop microcomputer managing a private practice physician's office.

  20. A decision class analysis of critical care life-support decision-making.

    PubMed

    Seiver, A

    1993-02-01

    Decision analysis is a powerful methodology that can help clinicians make good decisions. Because it is not practical to place a decision analyst at the bedside in critical care units, the application of this methodology will require leveraging the analyst through computer-based systems. A decision class analysis is a collective analysis of a group of decisions that provides the high-level specification for such a computer system. This paper presents a decision class analysis of critical care life-support decisions. Key elements of this analysis are: the simplification of an otherwise extremely complex multistage sequential decision problem by using a sequence of two-stage models, and the use of six generic knowledge maps that capture the extremely complex relevant medical knowledge.

  1. Decision Support Systems for Academic Administration.

    ERIC Educational Resources Information Center

    Moore, Laurence J.; Greenwood, Allen G.

    1984-01-01

    The history and features of Decision Support Systems (DSS) and use of the approach by academic administrators are discussed. The objective of DSS is to involve the manager/decision maker in the decision-analysis process while simultaneously relieving that person of the burden of developing and performing detailed analysis. DSS represents a…

  2. Intelligent decision support in process environments

    SciTech Connect

    Hollnagel, E.; Mancini, G.; Woods, D.D.

    1986-01-01

    This book deals with the basis for design of intelligent systems to support human decision-making in supervisory control, and provides a view of how human and artificial cognitive systems can interact. It covers the design and development of intelligent decision aiding systems, as well as the testing and evaluation. Topics discussed include: decision theory; cognitive engineering; systems engineering; and artificial intelligence.

  3. Decision Support Systems for Academic Administration.

    ERIC Educational Resources Information Center

    Moore, Laurence J.; Greenwood, Allen G.

    1984-01-01

    The history and features of Decision Support Systems (DSS) and use of the approach by academic administrators are discussed. The objective of DSS is to involve the manager/decision maker in the decision-analysis process while simultaneously relieving that person of the burden of developing and performing detailed analysis. DSS represents a…

  4. Computer Graphics and Administrative Decision-Making.

    ERIC Educational Resources Information Center

    Yost, Michael

    1984-01-01

    Reduction in prices now makes it possible for almost any institution to use computer graphics for administrative decision making and research. Current and potential uses of computer graphics in these two areas are discussed. (JN)

  5. Computational Toxicology as Implemented by the U.S. EPA: Providing High Throughput Decision Support Tools for Screening and Assessing Chemical Exposure, Hazard and Risk

    EPA Science Inventory

    Computational toxicology is the application of mathematical and computer models to help assess chemical hazards and risks to human health and the environment. Supported by advances in informatics, high-throughput screening (HTS) technologies, and systems biology, the U.S. Environ...

  6. Computational Toxicology as Implemented by the U.S. EPA: Providing High Throughput Decision Support Tools for Screening and Assessing Chemical Exposure, Hazard and Risk

    EPA Science Inventory

    Computational toxicology is the application of mathematical and computer models to help assess chemical hazards and risks to human health and the environment. Supported by advances in informatics, high-throughput screening (HTS) technologies, and systems biology, the U.S. Environ...

  7. Investigating the Heart Pump Implant Decision Process: Opportunities for Decision Support Tools to Help.

    PubMed

    Yang, Qian; Zimmerman, John; Steinfeld, Aaron; Carey, Lisa; Antaki, James F

    2016-05-01

    Clinical decision support tools (DSTs) are computational systems that aid healthcare decision-making. While effective in labs, almost all these systems failed when they moved into clinical practice. Healthcare researchers speculated it is most likely due to a lack of user-centered HCI considerations in the design of these systems. This paper describes a field study investigating how clinicians make a heart pump implant decision with a focus on how to best integrate an intelligent DST into their work process. Our findings reveal a lack of perceived need for and trust of machine intelligence, as well as many barriers to computer use at the point of clinical decision-making. These findings suggest an alternative perspective to the traditional use models, in which clinicians engage with DSTs at the point of making a decision. We identify situations across patients' healthcare trajectories when decision supports would help, and we discuss new forms it might take in these situations.

  8. Investigating the Heart Pump Implant Decision Process: Opportunities for Decision Support Tools to Help

    PubMed Central

    Yang, Qian; Zimmerman, John; Steinfeld, Aaron; Carey, Lisa; Antaki, James F.

    2016-01-01

    Clinical decision support tools (DSTs) are computational systems that aid healthcare decision-making. While effective in labs, almost all these systems failed when they moved into clinical practice. Healthcare researchers speculated it is most likely due to a lack of user-centered HCI considerations in the design of these systems. This paper describes a field study investigating how clinicians make a heart pump implant decision with a focus on how to best integrate an intelligent DST into their work process. Our findings reveal a lack of perceived need for and trust of machine intelligence, as well as many barriers to computer use at the point of clinical decision-making. These findings suggest an alternative perspective to the traditional use models, in which clinicians engage with DSTs at the point of making a decision. We identify situations across patients’ healthcare trajectories when decision supports would help, and we discuss new forms it might take in these situations. PMID:27833397

  9. Computers and the Development of Design Decision Making Skills.

    ERIC Educational Resources Information Center

    Blandford, Ann; And Others

    1994-01-01

    Discussion of how to teach decision-making skills to undergraduate engineering design students highlights a computer-based decision support tool, WOMBAT (Weighted Objectives Method by Arguing with the Tutor). Changes in WOMBAT from an earlier version are described, and an example of dialog between a user and the system is included. (Contains 24…

  10. Personalizing Drug Selection Using Advanced Clinical Decision Support.

    PubMed

    Pestian, John; Spencer, Malik; Matykiewicz, Pawel; Zhang, Kejian; Vinks, Alexander A; Glauser, Tracy

    2009-06-23

    This article describes the process of developing an advanced pharmacogenetics clinical decision support at one of the United States' leading pediatric academic medical centers. This system, called CHRISTINE, combines clinical and genetic data to identify the optimal drug therapy when treating patients with epilepsy or Attention Deficit Hyperactivity Disorder. In the discussion a description of clinical decision support systems is provided, along with an overview of neurocognitive computing and how it is applied in this setting.

  11. Personalizing Drug Selection Using Advanced Clinical Decision Support

    PubMed Central

    Pestian, John; Spencer, Malik; Matykiewicz, Pawel; Zhang, Kejian; Vinks, Alexander A.; Glauser, Tracy

    2009-01-01

    This article describes the process of developing an advanced pharmacogenetics clinical decision support at one of the United States’ leading pediatric academic medical centers. This system, called CHRISTINE, combines clinical and genetic data to identify the optimal drug therapy when treating patients with epilepsy or Attention Deficit Hyperactivity Disorder. In the discussion a description of clinical decision support systems is provided, along with an overview of neurocognitive computing and how it is applied in this setting. PMID:19898682

  12. Costs Associated with Implementation of Computer-Assisted Clinical Decision Support System for Antenatal and Delivery Care: Case Study of Kassena-Nankana District of Northern Ghana

    PubMed Central

    Dalaba, Maxwell Ayindenaba; Akweongo, Patricia; Williams, John; Saronga, Happiness Pius; Tonchev, Pencho; Sauerborn, Rainer; Mensah, Nathan; Blank, Antje; Kaltschmidt, Jens; Loukanova, Svetla

    2014-01-01

    Objective This study analyzed cost of implementing computer-assisted Clinical Decision Support System (CDSS) in selected health care centres in Ghana. Methods A descriptive cross sectional study was conducted in the Kassena-Nankana district (KND). CDSS was deployed in selected health centres in KND as an intervention to manage patients attending antenatal clinics and the labour ward. The CDSS users were mainly nurses who were trained. Activities and associated costs involved in the implementation of CDSS (pre-intervention and intervention) were collected for the period between 2009–2013 from the provider perspective. The ingredients approach was used for the cost analysis. Costs were grouped into personnel, trainings, overheads (recurrent costs) and equipment costs (capital cost). We calculated cost without annualizing capital cost to represent financial cost and cost with annualizing capital costs to represent economic cost. Results Twenty-two trained CDSS users (at least 2 users per health centre) participated in the study. Between April 2012 and March 2013, users managed 5,595 antenatal clients and 872 labour clients using the CDSS. We observed a decrease in the proportion of complications during delivery (pre-intervention 10.74% versus post-intervention 9.64%) and a reduction in the number of maternal deaths (pre-intervention 4 deaths versus post-intervention 1 death). The overall financial cost of CDSS implementation was US$23,316, approximately US$1,060 per CDSS user trained. Of the total cost of implementation, 48% (US$11,272) was pre-intervention cost and intervention cost was 52% (US$12,044). Equipment costs accounted for the largest proportion of financial cost: 34% (US$7,917). When economic cost was considered, total cost of implementation was US$17,128–lower than the financial cost by 26.5%. Conclusions The study provides useful information in the implementation of CDSS at health facilities to enhance health workers' adherence to practice guidelines

  13. Visualising Uncertainty for Decision Support

    DTIC Science & Technology

    2016-12-01

    Transactions on Visualization and Computer Graphics 18, 2496 -- 2505. MAYER, R. E. & MORENO, R. 2002. Aids to computer-based multimedia learning ...SORDEN, S. D. 2005. A Cognitive Approach to Instructional Design for Multimedia Learning . Informing Science Journal, 8, 263-279. SUMMERS, V. A...Operating Picture (HiCOP) incorporating aspects of a User Defined Operating Picture (UDOP) and multimedia narrative

  14. Using Visualization in Cockpit Decision Support Systems

    SciTech Connect

    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.

  15. Decision support systems in health economics.

    PubMed

    Quaglini, S; Dazzi, L; Stefanelli, M; Barosi, G; Marchetti, M

    1999-08-01

    This article describes a system addressed to different health care professionals for building, using, and sharing decision support systems for resource allocation. The system deals with selected areas, namely the choice of diagnostic tests, the therapy planning, and the instrumentation purchase. Decision support is based on decision-analytic models, incorporating an explicit knowledge representation of both the medical domain knowledge and the economic evaluation theory. Application models are built on top of meta-models, that are used as guidelines for making explicit both the cost and effectiveness components. This approach improves the transparency and soundness of the collaborative decision-making process and facilitates the result interpretation.

  16. New approaches for real time decision support systems

    NASA Technical Reports Server (NTRS)

    Hair, D. Charles; Pickslay, Kent

    1994-01-01

    NCCOSC RDT&E Division (NRaD) is conducting research into ways of improving decision support systems (DSS) that are used in tactical Navy decision making situations. The research has focused on the incorporation of findings about naturalistic decision-making processes into the design of the DSS. As part of that research, two computer tools were developed that model the two primary naturalistic decision-making strategies used by Navy experts in tactical settings. Current work is exploring how best to incorporate the information produced by those tools into an existing simulation of current Navy decision support systems. This work has implications for any applications involving the need to make decisions under time constraints, based on incomplete or ambiguous data.

  17. A decision-supported outpatient practice system.

    PubMed Central

    Barrows, R. C.; Allen, B. A.; Smith, K. C.; Arni, V. V.; Sherman, E.

    1996-01-01

    We describe a Decision-supported Outpatient Practice (DOP) system developed and now in use at the Columbia-Presbyterian Medical Center. DOP is an automated ambulatory medical record system that integrates in-patient and ambulatory care data, and incorporates active and passive decision support mechanisms with a view towards improving the quality of primary care. Active decision support occurs in the form of event-driven reminders created within a remote clinical information system with its central data repository and decision support system (DSS). Novel features of DOP include patient specific health maintenance task lists calculated by the remote DSS. uses of a semantically structured controlled medical vocabulary to support clinical results review and provider data entry, and exploitation of an underlying ambulatory data model that provides for an explicit record of evolution of insight regarding patient management. Benefits, challenges, and plans are discussed. PMID:8947774

  18. Multi-Objective Markov Decision Processes for Data-Driven Decision Support

    PubMed Central

    Lizotte, Daniel J.; Laber, Eric B.

    2016-01-01

    We present new methodology based on Multi-Objective Markov Decision Processes for developing sequential decision support systems from data. Our approach uses sequential decision-making data to provide support that is useful to many different decision-makers, each with different, potentially time-varying preference. To accomplish this, we develop an extension of fitted-Q iteration for multiple objectives that computes policies for all scalarization functions, i.e. preference functions, simultaneously from continuous-state, finite-horizon data. We identify and address several conceptual and computational challenges along the way, and we introduce a new solution concept that is appropriate when different actions have similar expected outcomes. Finally, we demonstrate an application of our method using data from the Clinical Antipsychotic Trials of Intervention Effectiveness and show that our approach offers decision-makers increased choice by a larger class of optimal policies. PMID:28018133

  19. Prolog: A Practical Language for Decision Support Systems in Nursing?

    PubMed Central

    Ozbolt, Judy G.

    1987-01-01

    Developing decision support systems for nursing has been limited by difficulties in defining and representing nursing's knowledge base and by a lack of knowledge of how nurses make decisions. Recent theoretical and empirical work offers solutions to those problems. The challenge now is to represent nursing knowledge in a way that is comprehensible to both nurse and computer and to design decision support modalities that are accurate, efficient, and appropriate for nurses with different levels of expertise. This paper reviews the issues and critically evaluates Prolog as a tool for meeting the challenge.

  20. Naval Aviation Maintenance Decision Support System

    DTIC Science & Technology

    1989-03-01

    Processing FCF Functional Check Flight 99 FMC Fully Mission Capable JCN Job Control Number MCC Maintenance Contorl Chief MESM Mission Essential Support...DESIGN, EVALUATION AND EVOLUTION........................6 A. DECISION MAKING THEORY...............6 1. The Decision Making Process ...........7 2...87 2. Prototyping and Adaptive Design ...... 88 V. CONCLUSIONS AND RECOMMENDATIONS ... .......... 91 A. CONCLUSIONS

  1. A Hyperknowledge Framework of Decision Support Systems.

    ERIC Educational Resources Information Center

    Chang, Ai-Mei; And Others

    1994-01-01

    Presents a hyperknowledge framework of decision support systems (DSS). This framework formalizes specifics about system functionality, representation of knowledge, navigation of the knowledge system, and user-interface traits as elements of a DSS environment that conforms closely to human cognitive processes in decision making. (Contains 52…

  2. Decision Support Systems and Public Policy Analysis.

    ERIC Educational Resources Information Center

    Hall, Owen P., Jr.

    1986-01-01

    This article outlines an approach for developing and applying computerized decision support systems to the formulation and evaluation of public policy. To meet the challenge of financial resource limitations, new management systems must be developed to improve both governmental efficiency and decision-making effectiveness. (Author/BS)

  3. Geospatial decision support systems for societal decision making

    USGS Publications Warehouse

    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

  4. Computer models for economic and silvicultural decisions

    Treesearch

    Rosalie J. Ingram

    1989-01-01

    Computer systems can help simplify decisionmaking to manage forest ecosystems. We now have computer models to help make forest management decisions by predicting changes associated with a particular management action. Models also help you evaluate alternatives. To be effective, the computer models must be reliable and appropriate for your situation.

  5. A Decision Support System for Academic Scheduling.

    ERIC Educational Resources Information Center

    Burleson, Donald K.; Leivano, Rodrigo J.

    1986-01-01

    Describes the use of a decision support system to operate on a database for academic scheduling. Discusses the scheduling environment, database subsystem, dialog subsystem, modeling subsystem, and output formats. (JM)

  6. Decision Support for Attack Submarine Commanders.

    DTIC Science & Technology

    1980-10-01

    AD-AO95 892 DECISION SCIENCE CONSORTIUM INC FALLS CHURCH VA F./e 12/2 DECISION SUPPORT FOR ATTACK SUBMARINE COMMANDERS. (U) OCT 80 M S COHEN, R V...BROWN N00014-80-C-0046 UNCLASSIFIED TR-8S-11 ML DECISIN IEN$CE CUIVSURTiUM, MrC. DECISION SUPPORT FOR A TTA CK SUBMARINE COMMANDERS Marvin S . Cohen and...on reverse) DDI ,o..ŕ 1473 EDITION OF I NOV 65 IS OISOLCTZ Unclassified S /N 0102-014-6601 1 SECURITY CLASIFICATION OF TNIS PAGE (10bon DW& tateo* 01

  7. Computational Cognition and Robust Decision Making

    DTIC Science & Technology

    2013-03-06

    processes underlying human performance in complex problem solving tasks; 2. Achieving robust and seamless symbiosis between humans and systems in...prediction, planning, scheduling, and decision making. Challenges and Strategy: • Seek computational principles for optimal symbiosis of mixed human

  8. Group decision support using Toulmin argument structures

    SciTech Connect

    Janssen, T. |; Sage, A.P.

    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.

  9. Decision support systems for ecosystem management: An evaluation of existing systems

    Treesearch

    H. Todd Mowrer; Klaus Barber; Joe Campbell; Nick Crookston; Cathy Dahms; John Day; Jim Laacke; Jim Merzenich; Steve Mighton; Mike Rauscher; Rick Sojda; Joyce Thompson; Peter Trenchi; Mark Twery

    1997-01-01

    This report evaluated 24 computer-aided decision support systems (DSS) that can support management decision-making in forest ecosystems. It compares the scope of each system, spatial capabilities, computational methods, development status, input and output requirements, user support availability, and system performance. Questionnaire responses from the DSS developers (...

  10. The Computer as Adaptive Instructional Decision Maker.

    ERIC Educational Resources Information Center

    Kopstein, Felix F.; Seidel, Robert J.

    The computer's potential for education, and most particularly for instruction, is contingent on the development of a class of instructional decision models (formal instructional strategies) that interact with the student through appropriate peripheral equipment (man-machine interfaces). Computer hardware and software by themselves should not be…

  11. Using Visualization in Cockpit Decision Support Systems

    NASA Technical Reports Server (NTRS)

    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 airflow hazard visualization cockpit decision support system are summarized. The studies demonstrate that such a system significantly improves the performance of helicopter pilots landing under turbulent conditions. Based on these results, design principles and implications for cockpit decision support systems using visualization are presented.

  12. A decision support system for rainfed agricultural areas of Mexico

    USDA-ARS?s Scientific Manuscript database

    Rural inhabitants of arid lands lack sufficient water to fulfill their agricultural and household needs. They do not have readily available technical information to support decisions regarding the course of action they should follow to handle the agro-climatic risk. In this paper, a computer model (...

  13. Computational toxicology as implemented by the U.S. EPA: providing high throughput decision support tools for screening and assessing chemical exposure, hazard and risk.

    PubMed

    Kavlock, Robert; Dix, David

    2010-02-01

    Computational toxicology is the application of mathematical and computer models to help assess chemical hazards and risks to human health and the environment. Supported by advances in informatics, high-throughput screening (HTS) technologies, and systems biology, the U.S. Environmental Protection Agency EPA is developing robust and flexible computational tools that can be applied to the thousands of chemicals in commerce, and contaminant mixtures found in air, water, and hazardous-waste sites. The Office of Research and Development (ORD) Computational Toxicology Research Program (CTRP) is composed of three main elements. The largest component is the National Center for Computational Toxicology (NCCT), which was established in 2005 to coordinate research on chemical screening and prioritization, informatics, and systems modeling. The second element consists of related activities in the National Health and Environmental Effects Research Laboratory (NHEERL) and the National Exposure Research Laboratory (NERL). The third and final component consists of academic centers working on various aspects of computational toxicology and funded by the U.S. EPA Science to Achieve Results (STAR) program. Together these elements form the key components in the implementation of both the initial strategy, A Framework for a Computational Toxicology Research Program (U.S. EPA, 2003), and the newly released The U.S. Environmental Protection Agency's Strategic Plan for Evaluating the Toxicity of Chemicals (U.S. EPA, 2009a). Key intramural projects of the CTRP include digitizing legacy toxicity testing information toxicity reference database (ToxRefDB), predicting toxicity (ToxCast) and exposure (ExpoCast), and creating virtual liver (v-Liver) and virtual embryo (v-Embryo) systems models. U.S. EPA-funded STAR centers are also providing bioinformatics, computational toxicology data and models, and developmental toxicity data and models. The models and underlying data are being made publicly

  14. Computer-aided decision making.

    Treesearch

    Keith M. Reynolds; Daniel L. Schmoldt

    2006-01-01

    Several major classes of software technologies have been used in decisionmaking for forest management applications over the past few decades. These computer-based technologies include mathematical programming, expert systems, network models, multi-criteria decisionmaking, and integrated systems. Each technology possesses unique advantages and disadvantages, and has...

  15. Bayesian Decision Support for Adaptive Lung Treatments

    NASA Astrophysics Data System (ADS)

    McShan, Daniel; Luo, Yi; Schipper, Matt; TenHaken, Randall

    2014-03-01

    Purpose: A Bayesian Decision Network will be demonstrated to provide clinical decision support for adaptive lung response-driven treatment management based on evidence that physiologic metrics may correlate better with individual patient response than traditional (population-based) dose and volume-based metrics. Further, there is evidence that information obtained during the course of radiation therapy may further improve response predictions. Methods: Clinical factors were gathered for 58 patients including planned mean lung dose, and the bio-markers IL-8 and TGF-β1 obtained prior to treatment and two weeks into treatment along with complication outcomes for these patients. A Bayesian Decision Network was constructed using Netica 5.0.2 from Norsys linking these clinical factors to obtain a prediction of radiation induced lung disese (RILD) complication. A decision node was added to the network to provide a plan adaption recommendation based on the trade-off between the RILD prediction and complexity of replanning. A utility node provides the weighting cost between the competing factors. Results: The decision node predictions were optimized against the data for the 58 cases. With this decision network solution, one can consider the decision result for a new patient with specific findings to obtain a recommendation to adaptively modify the originally planned treatment course. Conclusions: A Bayesian approach allows handling and propagating probabilistic data in a logical and principled manner. Decision networks provide the further ability to provide utility-based trade-offs, reflecting non-medical but practical cost/benefit analysis. The network demonstrated illustrates the basic concept, but many other factors may affect these decisions and work on building better models are being designed and tested. Acknowledgement: Supported by NIH-P01-CA59827

  16. Management Needs for Computer Support.

    ERIC Educational Resources Information Center

    Irby, Alice J.

    University management has many and varied needs for effective computer services in support of their processing and information functions. The challenge for the computer center managers is to better understand these needs and assist in the development of effective and timely solutions. Management needs can range from accounting and payroll to…

  17. Quantitative Decision Support Requires Quantitative User Guidance

    NASA Astrophysics Data System (ADS)

    Smith, L. A.

    2009-12-01

    Is it conceivable that models run on 2007 computer hardware could provide robust and credible probabilistic information for decision support and user guidance at the ZIP code level for sub-daily meteorological events in 2060? In 2090? Retrospectively, how informative would output from today’s models have proven in 2003? or the 1930’s? Consultancies in the United Kingdom, including the Met Office, are offering services to “future-proof” their customers from climate change. How is a US or European based user or policy maker to determine the extent to which exciting new Bayesian methods are relevant here? or when a commercial supplier is vastly overselling the insights of today’s climate science? How are policy makers and academic economists to make the closely related decisions facing them? How can we communicate deep uncertainty in the future at small length-scales without undermining the firm foundation established by climate science regarding global trends? Three distinct aspects of the communication of the uses of climate model output targeting users and policy makers, as well as other specialist adaptation scientists, are discussed. First, a brief scientific evaluation of the length and time scales at which climate model output is likely to become uninformative is provided, including a note on the applicability the latest Bayesian methodology to current state-of-the-art general circulation models output. Second, a critical evaluation of the language often employed in communication of climate model output, a language which accurately states that models are “better”, have “improved” and now “include” and “simulate” relevant meteorological processed, without clearly identifying where the current information is thought to be uninformative and misleads, both for the current climate and as a function of the state of the (each) climate simulation. And thirdly, a general approach for evaluating the relevance of quantitative climate model output

  18. Computerized Clinical Decision Support: Contributions from 2014.

    PubMed

    Bouaud, J; Koutkias, V

    2015-08-13

    To summarize recent research and propose a selection of best papers published in 2014 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry systems in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was finally organized to conclude on the selection of best papers. Among the 1,254 returned papers published in 2014, the full review process selected four best papers. The first one is an experimental contribution to a better understanding of unintended uses of CDSSs. The second paper describes the effective use of previously collected data to tailor and adapt a CDSS. The third paper presents an innovative application that uses pharmacogenomic information to support personalized medicine. The fourth paper reports on the long-term effect of the routine use of a CDSS for antibiotic therapy. As health information technologies spread more and more meaningfully, CDSSs are improving to answer users' needs more accurately. The exploitation of previously collected data and the use of genomic data for decision support has started to materialize. However, more work is still needed to address issues related to the correct usage of such technologies, and to assess their effective impact in the long term.

  19. Computerized Clinical Decision Support: Contributions from 2014

    PubMed Central

    Koutkias, V.

    2015-01-01

    Summary Objective To summarize recent research and propose a selection of best papers published in 2014 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. Method A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry systems in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was finally organized to conclude on the selection of best papers. Results Among the 1,254 returned papers published in 2014, the full review process selected four best papers. The first one is an experimental contribution to a better understanding of unintended uses of CDSSs. The second paper describes the effective use of previously collected data to tailor and adapt a CDSS. The third paper presents an innovative application that uses pharmacogenomic information to support personalized medicine. The fourth paper reports on the long-term effect of the routine use of a CDSS for antibiotic therapy. Conclusions As health information technologies spread more and more meaningfully, CDSSs are improving to answer users’ needs more accurately. The exploitation of previously collected data and the use of genomic data for decision support has started to materialize. However, more work is still needed to address issues related to the correct usage of such technologies, and to assess their effective impact in the long term. PMID:26293858

  20. Computer modeling of human decision making

    NASA Technical Reports Server (NTRS)

    Gevarter, William B.

    1991-01-01

    Models of human decision making are reviewed. Models which treat just the cognitive aspects of human behavior are included as well as models which include motivation. Both models which have associated computer programs, and those that do not, are considered. Since flow diagrams, that assist in constructing computer simulation of such models, were not generally available, such diagrams were constructed and are presented. The result provides a rich source of information, which can aid in construction of more realistic future simulations of human decision making.

  1. Decision support system for nursing management control

    SciTech Connect

    Ernst, C.J.

    1983-01-01

    A knowledge representation approach for expert systems supporting decision processes in business is proposed. A description of a knowledge representation schema using a logic programming metalanguage is described, then the role of such a schema in a management expert system is demonstrated through the problem of nursing management control in hospitals. 18 references.

  2. Query Reformulation for Clinical Decision Support Search

    DTIC Science & Technology

    2014-11-01

    Query Reformulation for Clinical Decision Support Search Luca Soldaini, Arman Cohan, Andrew Yates, Nazli Goharian, Ophir Frieder Information...work, we present a query reformulation approach that addresses the unique formulation of case reports, making them suitable to be used on a general... reformulation approach does not directly take into account the generic question type (diagnosis, test, treatment) provided with each approach. To ameliorate

  3. Microcomputer Use in Administrative Decision Support Systems.

    ERIC Educational Resources Information Center

    Brown, Kenneth G.; Droegemueller, Lee

    1983-01-01

    Some of the major problems facing higher education over the next decade and how microcomputer-based decision support systems can be used to address these as well as everyday administrative problems are discussed. Examples using electronic spreadsheets and database management systems are provided. (Author/MLW)

  4. Developing Academic Library Decision Support Systems.

    ERIC Educational Resources Information Center

    Chorba, Ronald W.; Bommer, Michael R. W.

    1983-01-01

    The approach to designing decision support systems for academic library management which is described explores online retrieval of profiles of user productivity, resource utilization, and resource availability. Database models, implementation considerations, database management systems, a sample application, and supplementing manager's judgement…

  5. Scalable software architectures for decision support.

    PubMed

    Musen, M A

    1999-12-01

    Interest in decision-support programs for clinical medicine soared in the 1970s. Since that time, workers in medical informatics have been particularly attracted to rule-based systems as a means of providing clinical decision support. Although developers have built many successful applications using production rules, they also have discovered that creation and maintenance of large rule bases is quite problematic. In the 1980s, several groups of investigators began to explore alternative programming abstractions that can be used to build decision-support systems. As a result, the notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) problem-solving methods--domain-independent algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper highlights how developers can construct large, maintainable decision-support systems using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community.

  6. Watershed forest management using decision support technology

    Treesearch

    Mark Twery; Robert Northrop

    2004-01-01

    Using innovative partnerships and a variety of decision support tools, we identified the needs and goals of Baltimore, Maryland, for their reservoir properties containing over 17000 forested acres; developed a management plan; determined the information necessary to evaluate conditions, processes, and context; chose tools to use; collected, organized, and analyzed data...

  7. Modeling uncertainty in requirements engineering decision support

    NASA Technical Reports Server (NTRS)

    Feather, Martin S.; Maynard-Zhang, Pedrito; Kiper, James D.

    2005-01-01

    One inherent characteristic of requrements engineering is a lack of certainty during this early phase of a project. Nevertheless, decisions about requirements must be made in spite of this uncertainty. Here we describe the context in which we are exploring this, and some initial work to support elicitation of uncertain requirements, and to deal with the combination of such information from multiple stakeholders.

  8. A Multiple Objective Decision Support Tool (MODS)

    SciTech Connect

    2003-12-14

    The Multiple Objective Decision Support (MODS) tool is an automated tool used to assist decision makers and policy analysts with multiple-objective decision problems. The classes of problems that this decision support tool addresses have both multiple objectives and multiple stakeholders. Decision problems, which have multiple objectives that in general cannot be maximized simultaneously, and multiple stakeholders, who have different perspectives about the relative importance of the objectives, require analytic approaches and tools that can provide flexible support to decision makers. This tool provides capabilities for the management, analysis, and graphical display for these types of decision problems drawn from diverse problem domains. The MODS tool is a unique integration of analysis algorithms, an information database, and a graphical user interface. This collection of algorithms, the combination of an information database with the analysis into a single tool, and the graphical user interface provides a technically advanced tool to decision makers and policy analysts. There are two main issues when addressing problems of this type: what set of attributes should be used to characterize the tokens in the domain of interest, and how should the values of these attributes and their weights be determined and combined to provide a relative ordering to the tokens. This tool addresses both of these issues. This decision support tool provides a flexible way to derive and use a chosen set of attributes. For example, the tool could be used to first perform a paired comparison of a large set of attributes and from this evaluation select those attributes that have the highest weights. The flexibility of the tool allows experimentation with various attribute sets and this capability, along with domain expertise, addresses the first issue. To address the second issue, several algorithms have been implemented. For example, two algorithms that have been implemented are the

  9. Decision making and problem solving with computer assistance

    NASA Technical Reports Server (NTRS)

    Kraiss, F.

    1980-01-01

    In modern guidance and control systems, the human as manager, supervisor, decision maker, problem solver and trouble shooter, often has to cope with a marginal mental workload. To improve this situation, computers should be used to reduce the operator from mental stress. This should not solely be done by increased automation, but by a reasonable sharing of tasks in a human-computer team, where the computer supports the human intelligence. Recent developments in this area are summarized. It is shown that interactive support of operator by intelligent computer is feasible during information evaluation, decision making and problem solving. The applied artificial intelligence algorithms comprehend pattern recognition and classification, adaptation and machine learning as well as dynamic and heuristic programming. Elementary examples are presented to explain basic principles.

  10. The conceptual foundation of environmental decision support.

    PubMed

    Reichert, Peter; Langhans, Simone D; Lienert, Judit; Schuwirth, Nele

    2015-05-01

    Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how societal preferences can be described and elicited, and (iii) how these concepts can best be used to support communication with authorities, politicians, and the public in environmental management. The goal of this paper is to discuss key requirements for a conceptual framework to address these issues and to suggest how these can best be met. We argue that a combination of probability theory and scenario planning with multi-attribute utility theory fulfills these requirements, and discuss adaptations and extensions of these theories to improve their application for supporting environmental decision making. With respect to (i) we suggest the use of intersubjective probabilities, if required extended to imprecise probabilities, to describe the current state of scientific knowledge. To address (ii), we emphasize the importance of value functions, in addition to utilities, to support decisions under risk. We discuss the need for testing "non-standard" value aggregation techniques, the usefulness of flexibility of value functions regarding attribute data availability, the elicitation of value functions for sub-objectives from experts, and the consideration of uncertainty in value and utility elicitation. With respect to (iii), we outline a well-structured procedure for transparent environmental decision support that is based on a clear separation of scientific prediction and societal valuation. We illustrate aspects of the suggested methodology by its application to river management in general and with a small, didactical case study on spatial river rehabilitation prioritization.

  11. IBM’s Health Analytics and Clinical Decision Support

    PubMed Central

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

    2014-01-01

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

  12. Decision support for patient care: implementing cybernetics.

    PubMed

    Ozbolt, Judy; Ozdas, Asli; Waitman, Lemuel R; Smith, Janis B; Brennan, Grace V; Miller, Randolph A

    2004-01-01

    The application of principles and methods of cybernetics permits clinicians and managers to use feedback about care effectiveness and resource expenditure to improve quality and to control costs. Keys to the process are the specification of therapeutic goals and the creation of an organizational culture that supports the use of feedback to improve care. Daily feedback on the achievement of each patient's therapeutic goals provides tactical decision support, enabling clinicians to adjust care as needed. Monthly or quarterly feedback on aggregated goal achievement for all patients on a clinical pathway provides strategic decision support, enabling clinicians and managers to identify problems with supposed "best practices" and to test hypotheses about solutions. Work is underway at Vanderbilt University Medical Center to implement feedback loops in care and management processes and to evaluate the effects.

  13. COMBAT study - Computer based assessment and treatment - A clinical trial evaluating impact of a computerized clinical decision support tool on pain in cancer patients.

    PubMed

    Raj, Sunil X; Brunelli, Cinzia; Klepstad, Pål; Kaasa, Stein

    2017-08-08

    The prevalence of pain in cancer patients are relatively high and indicate inadequate pain management strategies. Therefore, it is necessary to develop new methods and to improve implementation of guidelines to assess and treat pain. The vast improvement in information technology facilitated development of a computerized symptom assessment and decision support system (CCDS) - the Combat system - which was implemented in an outpatient cancer clinic to evaluate improvement in pain management. We conducted a controlled before-and-after study between patient cohorts in two consecutive study periods: before (n=80) and after (n=134) implementation of the Combat system. Patients in the first cohort completed questionnaires with the paper-and-pencil method and this data was not shown to physicians. Patients in the latter cohort completed an electronic questionnaire by using an iPad and the data were automatically transferred and presented to physicians at point of care. Additionally, the system provided computerized decision support at point of care for the physician based on the electronic questionnaires completed by the patients, an electronic CRF completed by physicians and clinical guidelines. The Combat system did not improve pain intensity and there were no significant alterations in the prescribed dose of opiates compared to the cohort of patients managed without the Combat system. The Combat system did not improve pain management. This may be explained by several factors, however, we consider lack of proper implementation of the CCDS in the clinic to be the most important factor. As a result, we did not manage to change the behaviour of the physicians in the clinic. There is a need to conduct larger prospective studies to evaluate the efficacy of modern information technology to improve pain management in cancer patients. Before introducing new information technology in the clinics, it is important to have a well thought out implementation strategy. The trial is

  14. Decision Support for Operations and Maintenance IV

    SciTech Connect

    2011-12-22

    DSOM (Decision Support for Operations and Maintenance) is an expert operations and maintenance system that integrates plant operations, fuel management, and maintenance processes. The DSOM package provides operators with the information they need for cost-effective operating decisions creating savings in fuel, personnel, maintenance, and plant life extension. DSOM provides operators real-time system performance information to allow them to determine if the plant is malfunctioning or running below expectations. By catching potential problems, DSOM enables plants to operate safely at peak efficiency, while providing a higher level of reliability and safety.

  15. Computerized Clinical Decision Support: Contributions from 2015.

    PubMed

    Koutkias, V; Bouaud, J

    2016-11-10

    To summarize recent research and select the best papers published in 2015 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry (CPOE) systems. The aim was to identify a list of candidate best papers from the retrieved papers that were then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the IMIA editorial team was finally conducted to conclude in the best paper selection. Among the 974 retrieved papers, the entire review process resulted in the selection of four best papers. One paper reports on a CDSS routinely applied in pediatrics for more than 10 years, relying on adaptations of the Arden Syntax. Another paper assessed the acceptability and feasibility of an important CPOE evaluation tool in hospitals outside the US where it was developed. The third paper is a systematic, qualitative review, concerning usability flaws of medication-related alerting functions, providing an important evidence-based, methodological contribution in the domain of CDSS design and development in general. Lastly, the fourth paper describes a study quantifying the effect of a complex, continuous-care, guideline-based CDSS on the correctness and completeness of clinicians' decisions. While there are notable examples of routinely used decision support systems, this 2015 review on CDSSs and CPOE systems still shows that, despite methodological contributions, theoretical frameworks, and prototype developments, these technologies are not yet widely spread (at least with their full functionalities) in routine clinical practice. Further research, testing, evaluation, and training are still needed for these tools to be adopted in clinical practice and, ultimately, illustrate the benefits that they promise.

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

    PubMed

    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.

  17. Supporting collaborative computing and interaction

    SciTech Connect

    Agarwal, Deborah; McParland, Charles; Perry, Marcia

    2002-05-22

    To enable collaboration on the daily tasks involved in scientific research, collaborative frameworks should provide lightweight and ubiquitous components that support a wide variety of interaction modes. We envision a collaborative environment as one that provides a persistent space within which participants can locate each other, exchange synchronous and asynchronous messages, share documents and applications, share workflow, and hold videoconferences. We are developing the Pervasive Collaborative Computing Environment (PCCE) as such an environment. The PCCE will provide integrated tools to support shared computing and task control and monitoring. This paper describes the PCCE and the rationale for its design.

  18. Data Mining and Data Fusion for Enhanced Decision Support

    SciTech Connect

    Khan, Shiraj; Ganguly, Auroop R; Gupta, Amar

    2008-01-01

    The process of Data Mining converts information to knowledge by utilizing tools from the disciplines of computational statistics, database technologies, machine learning, signal processing, nonlinear dynamics, process modeling, simulation, and allied disciplines. Data Mining allows business problems to be analyzed from diverse perspectives, including dimensionality reduction, correlation and co-occurrence, clustering and classification, regression and forecasting, anomaly detection, and change analysis. The predictive insights generated from Data Mining can be further utilized through real-time analysis and decision sciences, as well as through human-driven analysis based on management by exceptions or by objectives, to generate actionable knowledge. The tools that enable the transformation of raw data to actionable predictive insights are collectively referred as Decision Support tools. This chapter presents a new formalization of the decision process, leading to a new Decision Superiority model, partially motivated by the Joint Directors of Laboratories (JDL) Data Fusion Model. In addition, it examines the growing importance of Data Fusion concepts.

  19. Supporting registration decisions during 3D medical volume reconstructions

    NASA Astrophysics Data System (ADS)

    Bajcsy, Peter; Lee, Sang-Chul; Clutter, David

    2006-03-01

    We propose a methodology for making optimal registration decisions during 3D volume reconstruction in terms of (a) anticipated accuracy of aligned images, (b) uncertainty of obtained results during the registration process, (c) algorithmic repeatability of alignment procedure, and (d) computational requirements. We researched and developed a web-enabled, web services based, data-driven, registration decision support system. The registration decisions include (1) image spatial size (image sub-area or entire image), (2) transformation model (e.g., rigid, affine or elastic), (3) invariant registration feature (intensity, morphology or a sequential combination of the two), (4) automation level (manual, semi-automated, or fully-automated), (5) evaluations of registration results (multiple metrics and methods for establishing ground truth), and (6) assessment of resources (computational resources and human expertise, geographically local or distributed). Our goal is to provide mechanisms for evaluating the tradeoffs of each registration decision in terms of the aforementioned impacts. First, we present a medical registration methodology for making registration decisions that lead to registration results with well-understood accuracy, uncertainty, consistency and computational complexity characteristics. Second, we have built software tools that enable geographically distributed researchers to optimize their data-driven registration decisions by using web services and supercomputing resources. The support developed for registration decisions about 3D volume reconstruction is available to the general community with the access to the NCSA supercomputing resources. We illustrate performance by considering 3D volume reconstruction of blood vessels in histological sections of uveal melanoma from serial fluorescent labeled paraffin sections labeled with antibodies to CD34 and laminin. The specimens are studied by fluorescence confocal laser scanning microscopy (CLSM) images.

  20. Proactive and Adaptive Decision Support Study (PDS)

    DTIC Science & Technology

    2014-08-31

    Arlington, VA 22203-1995 703-696-2875 jeffrey.g.morrison@navy.mil Report Prepared By: Thomas G. Allen Boston Fusion Corp. 1 Van de Graaff Drive...7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Boston Fusion Corp.,1 Van de Graaff Drive, Suite 107,Burlington,MA,01803 8. PERFORMING...During August, the principal activities for Boston Fusion were related to the preparation for, and attendance at, the ONR Proactive Decision Support

  1. Information integration in a decision support system.

    PubMed

    Hudson, D L; Cohen, M E; Deedwania, P C

    1994-01-01

    Electronic medical records pose a challenge because of the complex types of data which are included. Decision support systems must be able to deal effectively with these data types. In the expert system demonstrated here, a diversity of data types are included. These data are processed by three different methods. However, the different methods of processing are transparent to the user. An overall rule-based interface integrates the different methods into one comprehensive system.

  2. Gila San Francisco Decision Support Tool - 2010

    SciTech Connect

    Sun, Amy Cha-Tien; Tidwell, Vincent C.; Klisa, Geoff; Poplionski, Will

    2014-12-01

    The Gila-San Francisco Decision Support Tool analyzes the water demand and supply for the Gila San Francisco region spanning four counties in southwestern New Mexico (Catron, Hidalgo, Luna and Grant). Catalyzed by the 2004 Arizona Water Settlement Act and prompted by a keen awareness for the unique ecology in the region, the model was developed by Sandia with a collaborative modeling team from federal, state, local, and public stakeholders

  3. Executive Support Systems: An Innovation Decision Perspective

    DTIC Science & Technology

    1990-01-01

    account . The exception and annotation ability of MIDS alerted the executives to what was happening and prevented a ripple effect of overreactions...information directly to these executives, an executive support system (ESS) allows more effective analysis, control, planning, and decision making...Automated improve- ments to the management process have the potential to highly leverage the executive’s effectiveness . An ESS is a concept, a clustered IT

  4. Best Practices in Clinical Decision Support

    PubMed Central

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

    2010-01-01

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

  5. SANDS - Sediment Analysis Network for Decision Support

    NASA Astrophysics Data System (ADS)

    Hardin, D. M.; Hawkins, L.; He, M.; Ebersole, S.

    2010-12-01

    Since the year 2000, Eastern Louisiana, coastal Mississippi, Alabama, and the western Florida panhandle have been affected by 28 tropical storms, seven of which were hurricanes. These tropical cyclones have significantly altered normal coastal processes and characteristics in the Gulf region through sediment disturbance. Although tides, seasonality, and agricultural development influence suspended sediment and sediment deposition over periods of time, tropical storm activity has the capability of moving the largest sediment loads in the shortest periods of time for coastal areas. The SANDS project is also investigating the effects of sediment immersed oil from the Deepwater Horizon disaster in April 2010 which has the potential to resurface as a result of tropical storm activity. The importance of sediments upon water quality, coastal erosion, habitats and nutrients has made their study and monitoring vital to decision makers in the region. Currently agencies such as United States Army Corps of Engineers (USACE), NASA, and Geological Survey of Alabama (GSA) are employing a variety of in-situ and airborne based measurements to assess and monitor sediment loading and deposition. These methods provide highly accurate information but are limited in geographic range, are not continuous over a region and, in the case of airborne LIDAR are expensive and do not recur on a regular basis. Multi-temporal and multi-spectral satellite imagery that shows tropical-storm-induced suspended sediment and storm-surge sediment deposits can provide decision makers with immediate and long-term information about the impacts of tropical storms and hurricanes. It can also be valuable for those conducting research and for projects related to coastal issues such as recovery, planning, management, and mitigation. The Sediment Analysis Network for Decision Support has generated a number of decision support products derived from MODIS, Landsat and SeaWiFS instruments that potentially support

  6. Sustaining the Army Training Mission by Re-Thinking Decision Support Systems: Shifting from Decision-Making Individuals to Sense-Making Agents

    DTIC Science & Technology

    2004-12-01

    traditional concept of decision making as a basically rational process ( Simon 1960). In an effort to reconceptualize decision making, this paper...originates in organization science ( Simon 1960). Decision Support Systems are computer technologies used to support complex decision making in...technical tools supporting the traditional concept of decision making as a basically rational process ( Simon 1960). The techno-centric character of DSS

  7. Web Support System for Group Collaborative Decisions

    NASA Astrophysics Data System (ADS)

    Rigopoulos, George; Psarras, John; Askounis, Dimitrios Th.

    In this research, we present a Group Decision Support System (GDSS) based on web technology, which can be used in asynchronous mode from group members. It supports small collaborative groups in classification decisions, implementing a supervised multicriteria methodology. A facilitator, who defines necessary parameters and initiates the procedure, coordinates the entire operation. Next, members evaluate the proposed parameter set and express their preferences in numeric format. Aggregation of individuals` preferences is executed at the parameter level by utilization of OWA operator and a group parameter set is produced which is used as input for the classification algorithm. A multicriteria classification algorithm is used for the classification of actions (people, projects etc.). Finally, group members evaluate results and consensus as well as satisfaction indexes are calculated. In case of low acceptance level, parameters are redefined and aggregation phase is repeated. The system has been utilized effectively to solve group classification problems in business environment. The overall architecture as well the methodology is presented, along with a sample application. Empirical findings from GDSS application and the methodology provide evidence that it is a valid approach for similar decision problems in numerous business environments, including production, human resources and operations.

  8. Issues of trust and ethics in computerized clinical decision support systems.

    PubMed

    Alexander, Gregory L

    2006-01-01

    Clinical decision support systems are computer technologies that model and provide support for human decision-making processes. Decision support mechanisms facilitate and enhance a clinician's ability to make decisions at the point of care. Decisions are facilitated through technology by using automated mechanisms that provide alerts or messages to clinicians about a potential patient problem. A clinician's level of trust in these technologies to support decision making is affected by how knowledge is represented in these tools, their ability to make reasonable decisions, and how they are designed. Furthermore, ethical tensions occur if these systems do not promote standards, if clinicians do not understand how to use these systems, and when professional relationships are affected. Issues of trust and ethical concerns will be examined in this article, using a research study of midwestern nursing homes that implemented a clinical decision support system.

  9. Business models for health care decision support.

    PubMed

    Gaughan, Phil

    2003-01-01

    CareScience, Inc. is a public company (NASDAQ: CARE) that originated ten years ago to commercialize risk adjustment and complication predictions developed by the Wharton School of Business and the University of Pennsylvania School of Medicine. Over the past decade, the company has grown to approximately 200 clients and 150 employees. Among the "firsts" recorded by the company, CareScience was the first to offer a clinical decision support system as an Application Service Provider (ASP), the first to offer peer-to-peer clinical data sharing among health care provider organizations and practitioners (Santa Barbara Care Data Exchange), and the first to provide a care management outsourcing arrangement.

  10. Automating Guidelines for Clinical Decision Support: Knowledge Engineering and Implementation

    PubMed Central

    Tso, Geoffrey J.; Tu, Samson W.; Oshiro, Connie; Martins, Susana; Ashcraft, Michael; Yuen, Kaeli W.; Wang, Dan; Robinson, Amy; Heidenreich, Paul A.; Goldstein, Mary K.

    2016-01-01

    As utilization of clinical decision support (CDS) increases, it is important to continue the development and refinement of methods to accurately translate the intention of clinical practice guidelines (CPG) into a computable form. In this study, we validate and extend the 13 steps that Shiffman et al.5 identified for translating CPG knowledge for use in CDS. During an implementation project of ATHENA-CDS, we encoded complex CPG recommendations for five common chronic conditions for integration into an existing clinical dashboard. Major decisions made during the implementation process were recorded and categorized according to the 13 steps. During the implementation period, we categorized 119 decisions and identified 8 new categories required to complete the project. We provide details on an updated model that outlines all of the steps used to translate CPG knowledge into a CDS integrated with existing health information technology. PMID:28269916

  11. A Decision Support System for Optimum Use of Fertilizers

    SciTech Connect

    R. L. Hoskinson; J. R. Hess; R. K. Fink

    1999-07-01

    The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems' infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

  12. A Decision Support System for Optimum Use of Fertilizers

    SciTech Connect

    Hoskinson, Reed Louis; Hess, John Richard; Fink, Raymond Keith

    1999-07-01

    The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems’ infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

  13. Linquistic geometry: new technology for decision support

    NASA Astrophysics Data System (ADS)

    Stilman, Boris; Yakhnis, Vladimir

    2003-09-01

    Linguistic Geometry (LG) is a revolutionary gaming approach which is ideally suited for military decision aids for Air, Ground, Naval, and Space-based operations, as well guiding robotic vehicles and traditional entertainment games. When thinking about modern or future military operations, the game metaphor comes to mind right away. Indeed, the air space together with the ground and seas may be viewed as a gigantic three-dimensional game board. Refining this picture, the LG approach is capable of providing an LG hypergame, that is, a system of multiple concurrent interconnected multi-player abstract board games (ABG) of various resolutions and time frames reflecting various kinds of hardware and effects involved in the battlespace and the solution space. By providing a hypergame representation of the battlespace, LG already provides a significant advance in situational awareness. However, the greatest advantage of the LG approach is an ability to provide commanders of campaigns and missions with decision options resulting in attainment of the commander's intent. At each game turn, an LG decision support tool assigns the best actions to each of the multitude of battlespace actors (UAVs, bombers, cruise missiles, etc.). This is done through utilization of algorithms finding winning strategies and tactics, which are the core of the LG approach.

  14. Creating clinical decision support systems for respiratory medicine.

    PubMed

    Tams, Carl G; Euliano, Neil R

    2015-01-01

    Clinical decision support systems are vital for advances in improving patient therapeutic care. We share lessons learned from creating two respiratory clinical decisions support systems for ventilating patients in a critical care setting.

  15. Sediment Analysis Network for Decision Support (SANDS)

    NASA Astrophysics Data System (ADS)

    Hardin, D. M.; Keiser, K.; Graves, S. J.; Conover, H.; Ebersole, S.

    2009-12-01

    Since the year 2000, Eastern Louisiana, coastal Mississippi, Alabama, and the western Florida panhandle have been affected by 28 tropical storms, seven of which were hurricanes. These tropical cyclones have significantly altered normal coastal processes and characteristics in the Gulf region through sediment disturbance. Although tides, seasonality, and agricultural development influence suspended sediment and sediment deposition over periods of time, tropical storm activity has the capability of moving the largest sediment loads in the shortest periods of time for coastal areas. The importance of sediments upon water quality, coastal erosion, habitats and nutrients has made their study and monitoring vital to decision makers in the region. Currently agencies such as United States Army Corps of Engineers (USACE), NASA, and Geological Survey of Alabama (GSA) are employing a variety of in-situ and airborne based measurements to assess and monitor sediment loading and deposition. These methods provide highly accurate information but are limited in geographic range, are not continuous over a region and, in the case of airborne LIDAR are expensive and do not recur on a regular basis. Multi-temporal and multi-spectral satellite imagery that shows tropical-storm-induced suspended sediment and storm-surge sediment deposits can provide decision makers with immediate and long-term information about the impacts of tropical storms and hurricanes. It can also be valuable for those conducting research and for projects related to coastal issues such as recovery, planning, management, and mitigation. The recently awarded Sediment Analysis Network for Decision Support will generate decision support products using NASA satellite observations from MODIS, Landsat and SeaWiFS instruments to support resource management, planning, and decision making activities in the Gulf of Mexico. Specifically, SANDS will generate decision support products that address the impacts of tropical storms

  16. Flood Impact Modelling to support decision making

    NASA Astrophysics Data System (ADS)

    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.

  17. Decision support software technology demonstration plan

    SciTech Connect

    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.

  18. Introduction to Decision Support Systems for Risk Based Management of Contaminated Sites

    EPA Science Inventory

    A book on Decision Support Systems for Risk-based Management of contaminated sites is appealing for two reasons. First, it addresses the problem of contaminated sites, which has worldwide importance. Second, it presents Decision Support Systems (DSSs), which are powerful comput...

  19. Introduction to Decision Support Systems for Risk Based Management of Contaminated Sites

    EPA Science Inventory

    A book on Decision Support Systems for Risk-based Management of contaminated sites is appealing for two reasons. First, it addresses the problem of contaminated sites, which has worldwide importance. Second, it presents Decision Support Systems (DSSs), which are powerful comput...

  20. Developing the U.S. Wildland Fire Decision Support System

    Treesearch

    Erin Noonan-Wright; Tonja S. Opperman; Mark A. Finney; Tom Zimmerman; Robert C. Seli; Lisa M. Elenz; David E. Calkin; John R. Fiedler

    2011-01-01

    A new decision support tool, the Wildland Fire Decision Support System (WFDSS) has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply...

  1. Intelligent Decisions? Intelligent Support? Agenda and Participants for the Internal Workshop on Intelligent Decision Support Systems : Retrospects and Prospects, August 29 - September 2, 2005, Certosa di Pontignano (Siena), Italy

    DTIC Science & Technology

    2005-09-01

    desired outcome obtains. This tradition is usually associated with Blaise Pascal and the invention of probability calculus, but can be found even earlier...41 12. KRAEMER, SARA & CARAYON, PASCALE : INFORMATION DECISION SUPPORT SYSTEMS IN COMPUTER AND INFORMATION SECURITY...KRAEMER, SARA & CARAYON, PASCALE : INFORMATION DECISION SUPPORT SYSTEMS IN COMPUTER AND INFORMATION SECURITY Over the past several decades, computer and

  2. A Proposed Computer-Assisted Decision Making System for the Hellenic Navy Decision Makers

    DTIC Science & Technology

    1987-03-01

    creates and sustains a corporate moral code. It appears that nations with a long history, especially of fighting defensive wars, are’ more likely to...experiences and needs of the potential adopters. An idea that is not comnatible with the prevalent values and norms of a cultural and social Estem will...Decision Support Systems, ed: \\V. C. House, Petrocelli Books, New YorK/Princeton, 1983. " Corporate war rooms pluginto the computer," Business Week, August

  3. How Decision Support Systems Can Benefit from a Theory of Change Approach.

    PubMed

    Allen, Will; Cruz, Jennyffer; Warburton, Bruce

    2017-06-01

    Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders' expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can "contribute" to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.

  4. How Decision Support Systems Can Benefit from a Theory of Change Approach

    NASA Astrophysics Data System (ADS)

    Allen, Will; Cruz, Jennyffer; Warburton, Bruce

    2017-06-01

    Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders' expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can "contribute" to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.

  5. Decision investigation and support environment (DISE)

    NASA Astrophysics Data System (ADS)

    VonPlinsky, Michael J.; Johnson, Pete; Crowder, Ed

    2001-09-01

    The "Decision Integration and Support Environment" (DISE) is a Bayesian network (BN) based modeling and simulation of the target nomination and aircraft tasking decision process. FTI has developed two BNs to model these processes, incorporating aircraft, target, and overall mission priorities from the Air Operations Center (OAC) and the mission planners/command staff. DISE operates in event driven interactions with FTI's AOC model, being triggered from within the Time Critical Target (TCT) Operations cell. As new target detections are received by the AOC from off-board ISR Sources and processed by the Automatic Target Recognition (ATR) module in the AOC, DISE is called to determine if the target should be prosectued, and if so, which of the available aircraft should be tasked to attack it. A range of decision criteria, with priorities established off-line and input into the tool, are associated with this process, including factors such as: * Fuel Level - amount of fuel in aircraft * Type of Weapon - available weapons on board aircraft * Probability of Survival - depends on the type of TST, time criticality and other factors * Potential Collateral Damage - amount of damage incurred on TST surroundings * Time Criticality of TST - how "critical" it is to attack the target depending on its launch status * Time to Target - aircraft's distance (in minutes) from the TST * Current Mission Priority - priority of the mission to which the aircraft is currently assigned * TST Mission Priority - determined when the target is originally nominated * Possible Reassignment - represents whether it is even possible to reassign the aircraft * Aircraft Re-tasking Availability - represents any factor not taken into account by the model, including commander override.

  6. Decision Support for Emergency Operations Centers

    NASA Technical Reports Server (NTRS)

    Harvey, Craig; Lawhead, Joel; Watts, Zack

    2005-01-01

    The Flood Disaster Mitigation Decision Support System (DSS) is a computerized information system that allows regional emergency-operations government officials to make decisions regarding the dispatch of resources in response to flooding. The DSS implements a real-time model of inundation utilizing recently acquired lidar elevation data as well as real-time data from flood gauges, and other instruments within and upstream of an area that is or could become flooded. The DSS information is updated as new data become available. The model generates realtime maps of flooded areas and predicts flood crests at specified locations. The inundation maps are overlaid with information on population densities, property values, hazardous materials, evacuation routes, official contact information, and other information needed for emergency response. The program maintains a database and a Web portal through which real-time data from instrumentation are gathered into the database. Also included in the database is a geographic information system, from which the program obtains the overlay data for areas of interest as needed. The portal makes some portions of the database accessible to the public. Access to other portions of the database is restricted to government officials according to various levels of authorization. The Flood Disaster Mitigation DSS has been integrated into a larger DSS named REACT (Real-time Emergency Action Coordination Tool), which also provides emergency operations managers with data for any type of impact area such as floods, fires, bomb

  7. Decision support system for the diagnosis of schizophrenia disorders.

    PubMed

    Razzouk, D; Mari, J J; Shirakawa, I; Wainer, J; Sigulem, D

    2006-01-01

    Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ). The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34%) and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.

  8. Semantic technologies in a decision support system

    NASA Astrophysics Data System (ADS)

    Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

    2015-10-01

    The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).

  9. Incident Waste Decision Support Tool - Waste Materials ...

    EPA Pesticide Factsheets

    Report This is the technical documentation to the waste materials estimator module of I-WASTE. This document outlines the methodology and data used to develop the Waste Materials Estimator (WME) contained in the Incident Waste Decision Support Tool (I-WASTE DST). Specifically, this document reflects version 6.4 of the I-WASTE DST. The WME is one of four primary features of the I-WASTE DST. The WME is both a standalone calculator that generates waste estimates in terms of broad waste categories, and is also integrated into the Incident Planning and Response section of the tool where default inventories of specific waste items are provided in addition to the estimates for the broader waste categories. The WME can generate waste estimates for both common materials found in open spaces (soil, vegetation, concrete, and asphalt) and for a vast array of items and materials found in common structures.

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

    NASA Astrophysics Data System (ADS)

    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.

  11. Decision Support for Patient Preference-based Care Planning

    PubMed Central

    Ruland, Cornelia M.

    1999-01-01

    Objective: While preference elicitation techniques have been effective in helping patients make decisions consistent with their preferences, little is known about whether information about patient preferences affects clinicians in clinical decision making and improves patient outcomes. The purpose of this study was to evaluate a decision support system for eliciting elderly patients' preferences for self-care capability and providing this information to nurses in clinical practice—specifically, its effect on nurses' care priorities and the patient outcomes of preference achievement and patient satisfaction. Design: Three-group quasi-experimental design with one experimental and two control groups (N = 151). In the experimental group computer-processed information about individual patient's preferences was placed in patients' charts to be used for care planning. Results: Information about patient preferences changed nurses' care priorities to be more consistent with patient preferences and improved patients' preference achievement and physical functioning. Further, higher consistency between patient preferences and nurses' care priorities was associated with higher preference achievement, and higher preference achievement with greater patient satisfaction. Conclusion: This study demonstrated that decision support for eliciting patient preferences and including them in nursing care planning is an effective and feasible strategy for improving nursing care and patient outcomes. PMID:10428003

  12. Reducing Risk with Clinical Decision Support

    PubMed Central

    Maloney, F.L.; Feblowitz, J.; Samal, L.; Sato, L.; Wright, A.

    2014-01-01

    Summary Objective Identify clinical opportunities to intervene to prevent a malpractice event and determine the proportion of malpractice claims potentially preventable by clinical decision support (CDS). Materials and Methods Cross-sectional review of closed malpractice claims over seven years from one malpractice insurance company and seven hospitals in the Boston area. For each event, clinical opportunities to intervene to avert the malpractice event and the presence or absence of CDS that might have a role in preventing the event, were assigned by a panel of expert raters. Compensation paid out to resolve a claim (indemnity), was associated with each CDS type. Results Of the 477 closed malpractice cases, 359 (75.3%) were categorized as substantiated and 195 (54%) had at least one opportunity to intervene. Common opportunities to intervene related to performance of procedure, diagnosis, and fall prevention. We identified at least one CDS type for 63% of substantiated claims. The 41 CDS types identified included clinically significant test result alerting, diagnostic decision support and electronic tracking of instruments. Cases with at least one associated intervention accounted for $40.3 million (58.9%) of indemnity. Discussion CDS systems and other forms of health information technology (HIT) are expected to improve quality of care, but their potential to mitigate risk had not previously been quantified. Our results suggest that, in addition to their known benefits for quality and safety, CDS systems within HIT have a potential role in decreasing malpractice payments. Conclusion More than half of malpractice events and over $40 million of indemnity were potentially preventable with CDS. PMID:25298814

  13. Considerations for a successful clinical decision support system.

    PubMed

    Castillo, Ranielle S; Kelemen, Arpad

    2013-07-01

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

  14. 12 CFR 944.4 - Decision on community support statements.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Decision on community support statements. 944.4 Section 944.4 Banks and Banking FEDERAL HOUSING FINANCE BOARD FEDERAL HOME LOAN BANK MISSION COMMUNITY SUPPORT REQUIREMENTS § 944.4 Decision on community support statements. (a) Action on community support...

  15. Medical Question Answering for Clinical Decision Support.

    PubMed

    Goodwin, Travis R; Harabagiu, Sanda M

    2016-10-01

    The goal of modern Clinical Decision Support (CDS) systems is to provide physicians with information relevant to their management of patient care. When faced with a medical case, a physician asks questions about the diagnosis, the tests, or treatments that should be administered. Recently, the TREC-CDS track has addressed this challenge by evaluating results of retrieving relevant scientific articles where the answers of medical questions in support of CDS can be found. Although retrieving relevant medical articles instead of identifying the answers was believed to be an easier task, state-of-the-art results are not yet sufficiently promising. In this paper, we present a novel framework for answering medical questions in the spirit of TREC-CDS by first discovering the answer and then selecting and ranking scientific articles that contain the answer. Answer discovery is the result of probabilistic inference which operates on a probabilistic knowledge graph, automatically generated by processing the medical language of large collections of electronic medical records (EMRs). The probabilistic inference of answers combines knowledge from medical practice (EMRs) with knowledge from medical research (scientific articles). It also takes into account the medical knowledge automatically discerned from the medical case description. We show that this novel form of medical question answering (Q/A) produces very promising results in (a) identifying accurately the answers and (b) it improves medical article ranking by 40%.

  16. Medical Question Answering for Clinical Decision Support

    PubMed Central

    Goodwin, Travis R.; Harabagiu, Sanda M.

    2017-01-01

    The goal of modern Clinical Decision Support (CDS) systems is to provide physicians with information relevant to their management of patient care. When faced with a medical case, a physician asks questions about the diagnosis, the tests, or treatments that should be administered. Recently, the TREC-CDS track has addressed this challenge by evaluating results of retrieving relevant scientific articles where the answers of medical questions in support of CDS can be found. Although retrieving relevant medical articles instead of identifying the answers was believed to be an easier task, state-of-the-art results are not yet sufficiently promising. In this paper, we present a novel framework for answering medical questions in the spirit of TREC-CDS by first discovering the answer and then selecting and ranking scientific articles that contain the answer. Answer discovery is the result of probabilistic inference which operates on a probabilistic knowledge graph, automatically generated by processing the medical language of large collections of electronic medical records (EMRs). The probabilistic inference of answers combines knowledge from medical practice (EMRs) with knowledge from medical research (scientific articles). It also takes into account the medical knowledge automatically discerned from the medical case description. We show that this novel form of medical question answering (Q/A) produces very promising results in (a) identifying accurately the answers and (b) it improves medical article ranking by 40%. PMID:28758046

  17. The ECG as decision support in STEMI.

    PubMed

    Ripa, Maria Sejersten

    2012-03-01

    The electrocardiogram (ECG) can be used for determining the presence, location and extent of jeopardized myocardium during acute coronary occlusion. Accordingly, the ECG has become essential in the treatment of patients with acute coronary syndrome (ACS). This thesis aims at optimizing the decision support, provided by the ECG, for choosing the best treatment strategy in the individual patient with ST-segment elevation acute myocardial infarction (STEMI). ECG recorded in the prehospital setting has become the standard of care in many communities, but to achieve the full advantage of this early approach it is important that the ECG is recorded from accurately placed electrodes to produce an ECG that resembles the standard 12-lead ECG. Accurate electrode placement is difficult especially in the acute setting, and we investigated an alternative lead system with fewer electrodes in easily identified positions. We showed that the system produced waveforms similar to the standard 12-lead ECG. However, occasional diagnostic errors were seen, compromising general acceptance of the system. Once the ECG has been recorded a decision regarding triage must be made on the basis of a correct ECG diagnosis. We found that trained paramedics can diagnose STEMI correctly in patients without ECG confounding factors, while the presence of ECG confounding factors decreased their ability substantially. Consequently, since many patients do present with ECG confounding factors, transmission to an on-call cardiologist for an early correct diagnosis is needed. We showed that time to pPCI was reduced by more than 1 hour by transmitting prehospital ECG to a cardiologist's handheld device for diagnosis, triage, and activation of the catheterization laboratory when needed. The optimal treatment strategy is dependent on the duration of ischemia however patient information is often inaccurate. Accordingly, it would be advantageous if the first available ECG can help identify patients who will

  18. A cluster randomized trial of decision support strategies for reducing antibiotic use in acute bronchitis.

    PubMed

    Gonzales, Ralph; Anderer, Tammy; McCulloch, Charles E; Maselli, Judith H; Bloom, Frederick J; Graf, Thomas R; Stahl, Melissa; Yefko, Michelle; Molecavage, Julie; Metlay, Joshua P

    2013-02-25

    National quality indicators show little change in the overuse of antibiotics for uncomplicated acute bronchitis. We compared the effect of 2 decision support strategies on antibiotic treatment of uncomplicated acute bronchitis. We conducted a 3-arm cluster randomized trial among 33 primary care practices belonging to an integrated health care system in central Pennsylvania. The printed decision support intervention sites (11 practices) received decision support for acute cough illness through a print-based strategy, the computer-assisted decision support intervention sites (11 practices) received decision support through an electronic medical record-based strategy, and the control sites (11 practices) served as a control arm. Both intervention sites also received clinician education and feedback on prescribing practices, as well as patient education brochures at check-in. Antibiotic prescription rates for uncomplicated acute bronchitis in the winter period (October 1, 2009, through March 31, 2010) following introduction of the intervention were compared with the previous 3 winter periods in an intent-to-treat analysis. Compared with the baseline period, the percentage of adolescents and adults prescribed antibiotics during the intervention period decreased at the printed decision support intervention sites (from 80.0% to 68.3%) and at the computer-assisted decision support intervention sites (from 74.0% to 60.7%) but increased slightly at the control sites (from 72.5% to 74.3%). After controlling for patient and clinician characteristics, as well as clustering of observations by clinician and practice site, the differences for the intervention sites were statistically significant from the control sites (P = .003 for control sites vs printed decision support intervention sites and P = .01 for control sites vs computer-assisted decision support intervention sites) but not between themselves (P = .67 for printed decision support intervention sites vs computer

  19. A Four-Phase Model of the Evolution of Clinical Decision Support Architectures

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    Background A large body of evidence over many years suggests that clinical decision support systems can be helpful in improving both clinical outcomes and adherence to evidence-based guidelines. However, to this day, clinical decision support systems are not widely used outside of a small number of sites. One reason why decision support systems are not widely used is the relative difficulty of integrating such systems into clinical workflows and computer systems. Purpose To review and synthesize the history of clinical decision support systems, and to propose a model of various architectures for integrating clinical decision support systems with clinical systems. Methods The authors conducted an extensive review of the clinical decision support literature since 1959, sequenced the systems and developed a model. Results The model developed consists of four phases: standalone decision support systems, decision support integrated into clinical systems, standards for sharing clinical decision support content and service models for decision support. These four phases have not heretofore been identified, but they track remarkably well with the chronological history of clinical decision support, and show evolving and increasingly sophisticated attempts to ease integrating decision support systems into clinical workflows and other clinical systems. Conclusions Each of the four evolutionary approaches to decision support architecture has unique advantages and disadvantages. A key lesson was that there were common limitations that almost all the approaches faced, and no single approach has been able to entirely surmount: 1) fixed knowledge representation systems inherently circumscribe the type of knowledge that can be represented in them, 2) there are serious terminological issues, 3) patient data may be spread across several sources with no single source having a complete view of the patient, and 4) major difficulties exist in transferring successful interventions from one

  20. User Centered Clinical Decision Support Tools

    PubMed Central

    Sofianou, A.; Kannry, J.; Mann, D.M.; McGinn, T.G.

    2014-01-01

    Summary Background Dissemination and adoption of clinical decision support (CDS) tools is a major initiative of the Affordable Care Act’s Meaningful Use program. Adoption of CDS tools is multipronged with personal, organizational, and clinical settings factoring into the successful utilization rates. Specifically, the diffusion of innovation theory implies that ‘early adopters’ are more inclined to use CDS tools and younger physicians tend to be ranked in this category. Objective This study examined the differences in adoption of CDS tools across providers’ training level. Participants From November 2010 to 2011, 168 residents and attendings from an academic medical institution were enrolled into a randomized controlled trial. Intervention The intervention arm had access to the CDS tool through the electronic health record (EHR) system during strep and pneumonia patient visits. Main Measures The EHR system recorded details on how intervention arm interacted with the CDS tool including acceptance of the initial CDS alert, completion of risk-score calculators and the signing of medication order sets. Using the EHR data, the study performed bivariate tests and general estimating equation (GEE) modeling to examine the differences in adoption of the CDS tool across residents and attendings. Key Results The completion rates of the CDS calculator and medication order sets were higher amongst first year residents compared to all other training levels. Attendings were the less likely to accept the initial step of the CDS tool (29.3%) or complete the medication order sets (22.4%) that guided their prescription decisions, resulting in attendings ordering more antibiotics (37.1%) during an CDS encounter compared to residents. Conclusion There is variation in adoption of CDS tools across training levels. Attendings tended to accept the tool less but ordered more medications. CDS tools should be tailored to clinicians’ training levels. PMID:25589914

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

    PubMed

    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. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. A rule-based clinical decision model to support interpretation of multiple data in health examinations.

    PubMed

    Kuo, Kuan-Liang; Fuh, Chiou-Shann

    2011-12-01

    Health examinations can obtain relatively complete health information and thus are important for the personal and public health management. For clinicians, one of the most important works in the health examinations is to interpret the health examination results. Continuously interpreting numerous health examination results of healthcare receivers is tedious and error-prone. This paper proposes a clinical decision support system to assist solving above problems. In order to customize the clinical decision support system intuitively and flexibly, this paper also proposes the rule syntax to implement computer-interpretable logic for health examinations. It is our purpose in this paper to describe the methodology of the proposed clinical decision support system. The evaluation was performed by the implementation and execution of decision rules on health examination results and a survey on clinical decision support system users. It reveals the efficiency and user satisfaction of proposed clinical decision support system. Positive impact of clinical data interpretation is also noted.

  3. Updated Decision Support Tool for the Management of Waste ...

    EPA Pesticide Factsheets

    Symposium Paper EPA's Office of Research and Development has developed a suite of web-based decision support tools that will assist in the decision making process for the disposal of debris resulting from incidents of national significance.

  4. Human Decision Processes: Implications for SSA Support Tools

    NASA Astrophysics Data System (ADS)

    Picciano, P.

    2013-09-01

    Despite significant advances in computing power and artificial intelligence (AI), few critical decisions are made without a human decision maker in the loop. Space Situational Awareness (SSA) missions are both critical and complex, typically adhering to the human-in-the-loop (HITL) model. The collection of human operators injects a needed diversity of expert knowledge, experience, and authority required to successfully fulfill SSA tasking. A wealth of literature on human decision making exists citing myriad empirical studies and offering a varied set of prescriptive and descriptive models of judgment and decision making (Hastie & Dawes, 2001; Baron, 2000). Many findings have been proven sufficiently robust to allow information architects or system/interface designers to take action to improve decision processes. For the purpose of discussion, these concepts are bifurcated in two groups: 1) vulnerabilities to mitigate, and 2) capabilities to augment. These vulnerabilities and capabilities refer specifically to the decision process and should not be confused with a shortcoming or skill of a specific human operator. Thus the framing of questions and orders, the automated tools with which to collaborate, priming and contextual data, and the delivery of information all play a critical role in human judgment and choice. Evaluating the merits of any decision can be elusive; in order to constrain this discussion, ‘rational choice' will tend toward the economic model characteristics such as maximizing utility and selection consistency (e.g., if A preferred to B, and B preferred to C, than A should be preferred to C). Simple decision models often encourage one to list the pros and cons of a decision, perhaps use a weighting schema, but one way or another weigh the future benefit (or harm) of making a selection. The result (sought by the rationalist models) should drive toward higher utility. Despite notable differences in researchers' theses (to be discussed in the full

  5. Comparative impact of guidelines, clinical data, and decision support on prescribing decisions: an interactive web experiment with simulated cases.

    PubMed

    Sintchenko, Vitali; Coiera, Enrico; Iredell, Jonathan R; Gilbert, Gwendolyn L

    2004-01-01

    The aim of this study was to compare the clinical impact of computerized decision support with and without electronic access to clinical guidelines and laboratory data on antibiotic prescribing decisions. A crossover trial was conducted of four levels of computerized decision support-no support, antibiotic guidelines, laboratory reports, and laboratory reports plus a decision support system (DSS), randomly allocated to eight simulated clinical cases accessed by the Web. Rate of intervention adoption was measured by frequency of accessing information support, cost of use was measured by time taken to complete each case, and effectiveness of decision was measured by correctness of and self-reported confidence in individual prescribing decisions. Clinical impact score was measured by adoption rate and decision effectiveness. Thirty-one intensive care and infectious disease specialist physicians (ICPs and IDPs) participated in the study. Ventilator-associated pneumonia treatment guidelines were used in 24 (39%) of the 62 case scenarios for which they were available, microbiology reports in 36 (58%), and the DSS in 37 (60%). The use of all forms of information support did not affect clinicians' confidence in their decisions. Their use of the DSS plus microbiology report improved the agreement of decisions with those of an expert panel from 65% to 97% (p=0.0002), or to 67% (p=0.002) when antibiotic guidelines only were accessed. Significantly fewer IDPs than ICPs accessed information support in making treatment decisions. On average, it took 245 seconds to make a decision using the DSS compared with 113 seconds for unaided prescribing (p<0.001). The DSS plus microbiology reports had the highest clinical impact score (0.58), greater than that of electronic guidelines (0.26) and electronic laboratory reports (0.45). When used, computer-based decision support significantly improved decision quality. In measuring the impact of decision support systems, both their

  6. Emulation Modeling with Bayesian Networks for Efficient Decision Support

    NASA Astrophysics Data System (ADS)

    Fienen, M. N.; Masterson, J.; Plant, N. G.; Gutierrez, B. T.; Thieler, E. R.

    2012-12-01

    Bayesian decision networks (BDN) have long been used to provide decision support in systems that require explicit consideration of uncertainty; applications range from ecology to medical diagnostics and terrorism threat assessments. Until recently, however, few studies have applied BDNs to the study of groundwater systems. BDNs are particularly useful for representing real-world system variability by synthesizing a range of hydrogeologic situations within a single simulation. Because BDN output is cast in terms of probability—an output desired by decision makers—they explicitly incorporate the uncertainty of a system. BDNs can thus serve as a more efficient alternative to other uncertainty characterization methods such as computationally demanding Monte Carlo analyses and others methods restricted to linear model analyses. We present a unique application of a BDN to a groundwater modeling analysis of the hydrologic response of Assateague Island, Maryland to sea-level rise. Using both input and output variables of the modeled groundwater response to different sea-level (SLR) rise scenarios, the BDN predicts the probability of changes in the depth to fresh water, which exerts an important influence on physical and biological island evolution. Input variables included barrier-island width, maximum island elevation, and aquifer recharge. The variability of these inputs and their corresponding outputs are sampled along cross sections in a single model run to form an ensemble of input/output pairs. The BDN outputs, which are the posterior distributions of water table conditions for the sea-level rise scenarios, are evaluated through error analysis and cross-validation to assess both fit to training data and predictive power. The key benefit for using BDNs in groundwater modeling analyses is that they provide a method for distilling complex model results into predictions with associated uncertainty, which is useful to decision makers. Future efforts incorporate

  7. Does clinical decision support reduce unwarranted variation in yield of CT pulmonary angiogram?

    PubMed

    Prevedello, Luciano M; Raja, Ali S; Ip, Ivan K; Sodickson, Aaron; Khorasani, Ramin

    2013-11-01

    The study objective was to determine whether previously documented effects of clinical decision support on computed tomography for pulmonary embolism in the emergency department (ie, decreased use and increased yield) are due to a decrease in unwarranted variation. We evaluated clinical decision support effect on intra- and inter-physician variability in the yield of pulmonary embolism computed tomography (PE-CT) in this setting. The study was performed in an academic adult medical center emergency department with 60,000 annual visits. We enrolled all patients who had PE-CT performed 18 months pre- and post-clinical decision support implementation. Intra- and inter-physician variability in yield (% PE-CT positive for acute pulmonary embolism) were assessed. Yield variability was measured using logistic regression accounting for patient characteristics. A total of 1542 PE-CT scans were performed before clinical decision support, and 1349 PE-CT scans were performed after clinical decision support. Use of PE-CT decreased from 26.5 to 24.3 computed tomography scans/1000 patient visits after clinical decision support (P < .02); yield increased from 9.2% to 12.6% (P < .01). Crude inter-physician variability in yield ranged from 2.6% to 20.5% before clinical decision support and from 0% to 38.1% after clinical decision support. After controlling for patient characteristics, the post-clinical decision support period showed significant inter-physician variability (P < .04). Intra-physician variability was significant in 3 of the 25 physicians (P < .04), all with increased yield post-clinical decision support. Overall PE-CT yield increased after clinical decision support implementation despite significant heterogeneity among physicians. Increased inter-physician variability in yield after clinical decision support was not explained by patient characteristics alone and may be due to variable physician acceptance of clinical decision support. Clinical decision support alone is

  8. Bi-Level Decision Making for Supporting Energy and Water Nexus

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Vesselinov, V. V.

    2016-12-01

    The inseparable relationship between energy production and water resources has led to the emerging energy-water nexus concept, which provides a means for integrated management and decision making of these two critical resources. However, the energy-water nexus frequently involves decision makers with different and competing management objectives. Furthermore, there is a challenge that decision makers and stakeholders might be making decisions sequentially from a higher level to a lower level, instead of at the same decision level, whereby the objective of a decision maker at a higher level should be satisfied first. In this study, a bi-level decision model is advanced to handle such decision-making situations for managing the energy-water nexus. The work represents a unique contribution to developing an integrated decision-support framework/tool to quantify and analyze the tradeoffs between the two-level energy-water nexus decision makers. Here, plans for electricity generation, fuel supply, water supply, capacity expansion of the power plants and environmental impacts are optimized to provide effective decision support. The developed decision-support framework is implemented in Julia (a high-level, high-performance dynamic programming language for technical computing) and is a part of the MADS (Model Analyses & Decision Support) framework (http://mads.lanl.gov). To demonstrate the capabilities of the developed methodology, a series of analyses are performed for synthetic problems consistent with actual real-world energy-water nexus management problems.

  9. Decision Support for Environmental Management of Industrial ...

    EPA Pesticide Factsheets

    Non-hazardous solid materials from industrial processes, once regarded as waste and disposed in landfills, offer numerous environmental and economic advantages when put to beneficial uses (BUs). Proper management of these industrial non-hazardous secondary materials (INSM) requires estimates of their probable environmental impacts among disposal as well as BU options. The U.S. Environmental Protection Agency (EPA) has recently approved new analytical methods (EPA Methods 1313–1316) to assess leachability of constituents of potential concern in these materials. These new methods are more realistic for many disposal and BU options than historical methods, such as the toxicity characteristic leaching protocol. Experimental data from these new methods are used to parameterize a chemical fate and transport (F&T) model to simulate long-term environmental releases from flue gas desulfurization gypsum (FGDG) when disposed of in an industrial landfill or beneficially used as an agricultural soil amendment. The F&T model is also coupled with optimization algorithms, the Beneficial Use Decision Support System (BUDSS), under development by EPA to enhance INSM management. The objective of this paper is to demonstrate the methodologies and encourage similar applications to improve environmental management and BUs of INSM through F&T simulation coupled with optimization, using realistic model parameterization.

  10. Global Turbulence Decision Support for Aviation

    NASA Astrophysics Data System (ADS)

    Williams, J.; Sharman, R.; Kessinger, C.; Feltz, W.; Wimmers, A.

    2009-09-01

    Turbulence is widely recognized as the leading cause of injuries to flight attendants and passengers on commercial air carriers, yet legacy decision support products such as SIGMETs and SIGWX charts provide relatively low spatial- and temporal-resolution assessments and forecasts of turbulence, with limited usefulness for strategic planning and tactical turbulence avoidance. A new effort is underway to develop an automated, rapid-update, gridded global turbulence diagnosis and forecast system that addresses upper-level clear-air turbulence, mountain-wave turbulence, and convectively-induced turbulence. This NASA-funded effort, modeled on the U.S. Federal Aviation Administration's Graphical Turbulence Guidance (GTG) and GTG Nowcast systems, employs NCEP Global Forecast System (GFS) model output and data from NASA and operational satellites to produce quantitative turbulence nowcasts and forecasts. A convective nowcast element based on GFS forecasts and satellite data provides a basis for diagnosing convective turbulence. An operational prototype "Global GTG” system has been running in real-time at the U.S. National Center for Atmospheric Research since the spring of 2009. Initial verification based on data from TRMM, Cloudsat and MODIS (for the convection nowcasting) and AIREPs and AMDAR data (for turbulence) are presented. This product aims to provide the "single authoritative source” for global turbulence information for the U.S. Next Generation Air Transportation System.

  11. Intelligent decision support systems for mechanical ventilation.

    PubMed

    Tehrani, Fleur T; Roum, James H

    2008-11-01

    An overview of different methodologies used in various intelligent decision support systems (IDSSs) for mechanical ventilation is provided. The applications of the techniques are compared in view of today's intensive care unit (ICU) requirements. Information available in the literature is utilized to provide a methodological review of different systems. Comparisons are made of different systems developed for specific ventilation modes as well as those intended for use in wider applications. The inputs and the optimized parameters of different systems are discussed and rule-based systems are compared to model-based techniques. The knowledge-based systems used for closed-loop control of weaning from mechanical ventilation are also described. Finally, in view of increasing trend towards automation of mechanical ventilation, the potential utility of intelligent advisory systems for this purpose is discussed. IDSSs for mechanical ventilation can be quite helpful to clinicians in today's ICU settings. To be useful, such systems should be designed to be effective, safe, and easy to use at patient's bedside. In particular, these systems must be capable of noise removal, artifact detection and effective validation of data. Systems that can also be adapted for closed-loop control/weaning of patients at the discretion of the clinician, may have a higher potential for use in the future.

  12. An Intelligent Polar Cyberinfrastrucuture to Support Spatiotemporal Decision Making

    NASA Astrophysics Data System (ADS)

    Song, M.; Li, W.; Zhou, X.

    2014-12-01

    In the era of big data, polar sciences have already faced an urgent demand of utilizing intelligent approaches to support precise and effective spatiotemporal decision-making. Service-oriented cyberinfrastructure has advantages of seamlessly integrating distributed computing resources, and aggregating a variety of geospatial data derived from Earth observation network. This paper focuses on building a smart service-oriented cyberinfrastructure to support intelligent question answering related to polar datasets. The innovation of this polar cyberinfrastructure includes: (1) a problem-solving environment that parses geospatial question in natural language, builds geoprocessing rules, composites atomic processing services and executes the entire workflow; (2) a self-adaptive spatiotemporal filter that is capable of refining query constraints through semantic analysis; (3) a dynamic visualization strategy to support results animation and statistics in multiple spatial reference systems; and (4) a user-friendly online portal to support collaborative decision-making. By means of this polar cyberinfrastructure, we intend to facilitate integration of distributed and heterogeneous Arctic datasets and comprehensive analysis of multiple environmental elements (e.g. snow, ice, permafrost) to provide a better understanding of the environmental variation in circumpolar regions.

  13. Cost-Effectiveness of Decision Support Strategies in Acute Bronchitis.

    PubMed

    Michaelidis, Constantinos I; Kern, Melissa S; Smith, Kenneth J

    2015-10-01

    A recent clinical trial suggests that printed (PDS) and computer decision support (CDS) interventions are safe and effective in reducing antibiotic use in acute bronchitis relative to usual care (UC). Our aim was to evaluate the cost-effectiveness of decision support interventions in reducing antibiotic use in acute bronchitis. We conducted a clinical trial-based cost-effectiveness analysis comparing UC, PDS and CDS for management of acute bronchitis. We assumed a societal perspective, 5-year program duration and 30-day time horizon. The U.S. population aged 13-64 years presenting with acute bronchitis in the ambulatory setting. Printed and computer decision support interventions relative to usual care. Cost per antibiotic prescription safely avoided. In the base case, PDS dominated UC and CDS, with lesser total costs (PDS: $2,574, UC: $2,768, CDS: $2,805) and fewer antibiotic prescriptions (PDS: 3.79, UC: 4.60, CDS: 3.95) per patient over 5 years. In one-way sensitivity analyses, PDS dominated UC across all parameter values, except when antibiotics reduced work loss by ≥ 1.9 days or the probability of hospitalization within 30 days was ≥ 0.9 % in PDS (base case: 0.2 %) or ≤ 0.4 % in UC (base case: 1.0 %). The dominance of PDS over CDS was sensitive both to probability of hospitalization and plausible variation in the adjusted odds of antibiotic use in both strategies. A PDS strategy to reduce antibiotic use in acute bronchitis is less costly and more effective than both UC and CDS strategies, although results were sensitive to variation in probability of hospitalization and the adjusted odds of antibiotic use. This simple, low-cost, safe, and effective intervention would be an economically reasonable component of a multi-component approach to address antibiotic overuse in acute bronchitis.

  14. Clinical Decision Support Systems for the Practice of Evidence-based Medicine

    PubMed Central

    Sim, Ida; Gorman, Paul; Greenes, Robert A.; Haynes, R. Brian; Kaplan, Bonnie; Lehmann, Harold; Tang, Paul C.

    2001-01-01

    Background: The use of clinical decision support systems to facilitate the practice of evidence-based medicine promises to substantially improve health care quality. Objective: To describe, on the basis of the proceedings of the Evidence and Decision Support track at the 2000 AMIA Spring Symposium, the research and policy challenges for capturing research and practice-based evidence in machine-interpretable repositories, and to present recommendations for accelerating the development and adoption of clinical decision support systems for evidence-based medicine. Results: The recommendations fall into five broad areas—capture literature-based and practice-based evidence in machine-interpretable knowledge bases; develop maintainable technical and methodological foundations for computer-based decision support; evaluate the clinical effects and costs of clinical decision support systems and the ways clinical decision support systems affect and are affected by professional and organizational practices; identify and disseminate best practices for work flow–sensitive implementations of clinical decision support systems; and establish public policies that provide incentives for implementing clinical decision support systems to improve health care quality. Conclusions: Although the promise of clinical decision support system–facilitated evidence-based medicine is strong, substantial work remains to be done to realize the potential benefits. PMID:11687560

  15. Case-based reasoning in Intelligent Health Decision Support Systems.

    PubMed

    González, Carolina; López, Diego M; Blobel, Bernd

    2013-01-01

    Decision-making is a crucial task for decision makers in healthcare, especially because decisions have to be made quickly, accurately and under uncertainty. Taking into account the importance of providing quality decisions, offering assistance in this complex process has been one of the main challenges of Artificial Intelligence throughout history. Decision Support Systems (DSS) have gained popularity in the medical field for their efficacy to assist decision-making. In this sense, many DSS have been developed, but only few of them consider processing and analysis of information contained in electronic health records, in order to identify individual or population health risk factors. This paper deals with Intelligent Decision Support Systems that are integrated into Electronic Health Records Systems (EHRS) or Public Health Information Systems (PHIS). It provides comprehensive support for a wide range of decisions with the purpose of improving quality of care delivered to patients or public health planning, respectively.

  16. Launching a virtual decision lab: development and field-testing of a web-based patient decision support research platform.

    PubMed

    Hoffman, Aubri S; Llewellyn-Thomas, Hilary A; Tosteson, Anna N A; O'Connor, Annette M; Volk, Robert J; Tomek, Ivan M; Andrews, Steven B; Bartels, Stephen J

    2014-12-12

    Over 100 trials show that patient decision aids effectively improve patients' information comprehension and values-based decision making. However, gaps remain in our understanding of several fundamental and applied questions, particularly related to the design of interactive, personalized decision aids. This paper describes an interdisciplinary development process for, and early field testing of, a web-based patient decision support research platform, or virtual decision lab, to address these questions. An interdisciplinary stakeholder panel designed the web-based research platform with three components: a) an introduction to shared decision making, b) a web-based patient decision aid, and c) interactive data collection items. Iterative focus groups provided feedback on paper drafts and online prototypes. A field test assessed a) feasibility for using the research platform, in terms of recruitment, usage, and acceptability; and b) feasibility of using the web-based decision aid component, compared to performance of a videobooklet decision aid in clinical care. This interdisciplinary, theory-based, patient-centered design approach produced a prototype for field-testing in six months. Participants (n = 126) reported that: the decision aid component was easy to use (98%), information was clear (90%), the length was appropriate (100%), it was appropriately detailed (90%), and it held their interest (97%). They spent a mean of 36 minutes using the decision aid and 100% preferred using their home/library computer. Participants scored a mean of 75% correct on the Decision Quality, Knowledge Subscale, and 74 out of 100 on the Preparation for Decision Making Scale. Completing the web-based decision aid reduced mean Decisional Conflict scores from 31.1 to 19.5 (p < 0.01). Combining decision science and health informatics approaches facilitated rapid development of a web-based patient decision support research platform that was feasible for use in research studies in

  17. Reliability analysis framework for computer-assisted medical decision systems

    SciTech Connect

    Habas, Piotr A.; Zurada, Jacek M.; Elmaghraby, Adel S.; Tourassi, Georgia D.

    2007-02-15

    We present a technique that enhances computer-assisted decision (CAD) systems with the ability to assess the reliability of each individual decision they make. Reliability assessment is achieved by measuring the accuracy of a CAD system with known cases similar to the one in question. The proposed technique analyzes the feature space neighborhood of the query case to dynamically select an input-dependent set of known cases relevant to the query. This set is used to assess the local (query-specific) accuracy of the CAD system. The estimated local accuracy is utilized as a reliability measure of the CAD response to the query case. The underlying hypothesis of the study is that CAD decisions with higher reliability are more accurate. The above hypothesis was tested using a mammographic database of 1337 regions of interest (ROIs) with biopsy-proven ground truth (681 with masses, 656 with normal parenchyma). Three types of decision models, (i) a back-propagation neural network (BPNN), (ii) a generalized regression neural network (GRNN), and (iii) a support vector machine (SVM), were developed to detect masses based on eight morphological features automatically extracted from each ROI. The performance of all decision models was evaluated using the Receiver Operating Characteristic (ROC) analysis. The study showed that the proposed reliability measure is a strong predictor of the CAD system's case-specific accuracy. Specifically, the ROC area index for CAD predictions with high reliability was significantly better than for those with low reliability values. This result was consistent across all decision models investigated in the study. The proposed case-specific reliability analysis technique could be used to alert the CAD user when an opinion that is unlikely to be reliable is offered. The technique can be easily deployed in the clinical environment because it is applicable with a wide range of classifiers regardless of their structure and it requires neither additional

  18. Reliability analysis framework for computer-assisted medical decision systems.

    PubMed

    Habas, Piotr A; Zurada, Jacek M; Elmaghraby, Adel S; Tourassi, Georgia D

    2007-02-01

    We present a technique that enhances computer-assisted decision (CAD) systems with the ability to assess the reliability of each individual decision they make. Reliability assessment is achieved by measuring the accuracy of a CAD system with known cases similar to the one in question. The proposed technique analyzes the feature space neighborhood of the query case to dynamically select an input-dependent set of known cases relevant to the query. This set is used to assess the local (query-specific) accuracy of the CAD system. The estimated local accuracy is utilized as a reliability measure of the CAD response to the query case. The underlying hypothesis of the study is that CAD decisions with higher reliability are more accurate. The above hypothesis was tested using a mammographic database of 1337 regions of interest (ROIs) with biopsy-proven ground truth (681 with masses, 656 with normal parenchyma). Three types of decision models, (i) a back-propagation neural network (BPNN), (ii) a generalized regression neural network (GRNN), and (iii) a support vector machine (SVM), were developed to detect masses based on eight morphological features automatically extracted from each ROI. The performance of all decision models was evaluated using the Receiver Operating Characteristic (ROC) analysis. The study showed that the proposed reliability measure is a strong predictor of the CAD system's case-specific accuracy. Specifically, the ROC area index for CAD predictions with high reliability was significantly better than for those with low reliability values. This result was consistent across all decision models investigated in the study. The proposed case-specific reliability analysis technique could be used to alert the CAD user when an opinion that is unlikely to be reliable is offered. The technique can be easily deployed in the clinical environment because it is applicable with a wide range of classifiers regardless of their structure and it requires neither additional

  19. Decision Support System in the Management of Resource-Sharing Networks.

    ERIC Educational Resources Information Center

    Dubey, Yogendra P.

    1984-01-01

    Reports on emergence of decision support system (DSS) as a practical approach for applying computers and information to problems facing management. Information processing and decision making in organizations, simulation-model-based DSS in management of library resource sharing networks, and a resource-sharing simulation system are highlighted.…

  20. [Computerized decision support systems: EBM at the bedside].

    PubMed

    Capobussi, Matteo; Banzi, Rita; Moja, Lorenzo; Bonovas, Stefanos; González-Lorenzo, Marien; Liberati, Elisa Giulia; Polo Friz, Hernan; Nanni, Oriana; Mangia, Massimo; Ruggiero, Francesca

    2016-11-01

    One of the aims of Evidence-Based Medicine is to improve quality and appropriateness of care by the expedition of the knowledge transfer process. Computerized Decision Support Systems (CDSSs) are computer programs that provide alerts to the prescribing doctor directly at the moment of medical examination. In fact, alerts are integrated within the single patient electronic health record. CDSS based on the best available and updated evidence and guidelines may be an efficient tool to facilitate the transfer of the latest results from clinical research directly at the bedside, thus supporting decision-making. The CODES (COmputerized DEcision Support) trial is a research program funded by the Italian Ministry of Health and the Lombardy Region. It aims to evaluate the feasibility of the implementation of a CDSS at the hospital level and to assess its efficacy in daily clinical practice. The CODES project includes two pragmatic RCTs testing a CDSS (i.e. the EBMeDS - MediDSS) in two large Italian hospitals: the first is a general hospital in Vimercate (Lombardy), the second is an oncologic research center in Meldola (Emilia Romagna). The CDSS supports a full spectrum of decisions: therapy, drug interactions, diagnosis, and management of health care services are covered by a hundreds of reminders. However only few reminders are activated per patient, highlighting crucial problems in the delivery of high-quality care. The two trials have similar design and primary outcome, the rate at which alerts detected by the software are resolved by a decision of the clinicians. The project also includes the assessment of barriers and facilitators in the adoption of these new technologies by hospital staff members and the retrospective evaluation of the repeated risks in prescription habits. The trials are ongoing and currently more than 10,000 patients have been randomized. The qualitative analysis revealed a progressive shift in the perception of the tool. Doctors are now seeing it

  1. Decision-support systems for forest management

    Treesearch

    H. Michael Rauscher

    2005-01-01

    The basic concept of sustainable development, formulated in the Brundtland report and applied to forest management by the Montreal Process, has focused attention on the need for formal decision processes (Brundtland. 1987). The application of decision theory is essential because meeting the needs of the present without compromising the ability of future generations to...

  2. A Framework and Model for Evaluating Clinical Decision Support Architectures

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    In this paper, we develop a four-phase model for evaluating architectures for clinical decision support that focuses on: defining a set of desirable features for a decision support architecture; building a proof-of-concept prototype; demonstrating that the architecture is useful by showing that it can be integrated with existing decision support systems and comparing its coverage to that of other architectures. We apply this framework to several well-known decision support architectures, including Arden Syntax, GLIF, SEBASTIAN and SAGE PMID:18462999

  3. HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS

    EPA Science Inventory

    Decision makers using environmental decision support tools are often confronted with information that predicts a multitude of different human health effects due to environmental stressors. If these health effects need to be contrasted with costs or compared with alternative scena...

  4. HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS

    EPA Science Inventory

    Decision makers using environmental decision support tools are often confronted with information that predicts a multitude of different human health effects due to environmental stressors. If these health effects need to be contrasted with costs or compared with alternative scena...

  5. Clinical Decision Support Systems and Prevention

    PubMed Central

    Njie, Gibril J.; Proia, Krista K.; Thota, Anilkrishna B.; Finnie, Ramona K.C.; Hopkins, David P.; Banks, Starr M.; Callahan, David B.; Pronk, Nicolaas P.; Rask, Kimberly J.; Lackland, Daniel T.; Kottke, Thomas E.

    2016-01-01

    Context Clinical decision support systems (CDSSs) can help clinicians assess cardiovascular disease (CVD) risk and manage CVD risk factors by providing tailored assessments and treatment recommendations based on individual patient data. The goal of this systematic review was to examine the effectiveness of CDSSs in improving screening for CVD risk factors, practices for CVD-related preventive care services such as clinical tests and prescribed treatments, and management of CVD risk factors. Evidence acquisition An existing systematic review (search period, January 1975–January 2011) of CDSSs for any condition was initially identified. Studies of CDSSs that focused on CVD prevention in that review were combined with studies identified through an updated search (January 2011–October 2012). Data analysis was conducted in 2013. Evidence synthesis A total of 45 studies qualified for inclusion in the review. Improvements were seen for recommended screening and other preventive care services completed by clinicians, recommended clinical tests completed by clinicians, and recommended treatments prescribed by clinicians (median increases of 3.8, 4.0, and 2.0 percentage points, respectively). Results were inconsistent for changes in CVD risk factors such as systolic and diastolic blood pressure, total and low-density lipoprotein cholesterol, and hemoglobin A1C levels. Conclusions CDSSs are effective in improving clinician practices related to screening and other preventive care services, clinical tests, and treatments. However, more evidence is needed from implementation of CDSSs within the broad context of comprehensive service delivery aimed at reducing CVD risk and CVD-related morbidity and mortality. PMID:26477805

  6. Real-time decision support and information gathering system for financial domain

    NASA Astrophysics Data System (ADS)

    Tseng, Chiu-Che; Gmytrasiewicz, Piotr J.

    2006-05-01

    The challenge of the investment domain is that a large amount of diverse information can be potentially relevant to an investment decision, and that, frequently, the decisions have to be made in a timely manner. This presents the potential for better decision support, but poses the challenge of building a decision support agent that gathers information from different sources and incorporates it for timely decision support. These problems motivate us to investigate ways in which the investors can be equipped with a flexible real-time decision support system to be practical in time-critical situations. The flexible real-time decision support system considers a tradeoff between decision quality and computation cost. For this purpose, we propose a system that uses the object oriented Bayesian knowledge base (OOBKB) design to create a decision model at the most suitable level of detail to guide the information gathering activities, and to produce an investment recommendation within a reasonable length of time. The decision models our system uses are implemented as influence diagrams. We validate our system with experiments in a simplified investment domain. The experiments show that our system produces a quality recommendation under different urgency situations. The contribution of our system is that it provides the flexible decision recommendation for an investor under time constraints in a complex environment.

  7. Coordinating complex decision support activities across distributed applications

    NASA Technical Reports Server (NTRS)

    Adler, Richard M.

    1994-01-01

    Knowledge-based technologies have been applied successfully to automate planning and scheduling in many problem domains. Automation of decision support can be increased further by integrating task-specific applications with supporting database systems, and by coordinating interactions between such tools to facilitate collaborative activities. Unfortunately, the technical obstacles that must be overcome to achieve this vision of transparent, cooperative problem-solving are daunting. Intelligent decision support tools are typically developed for standalone use, rely on incompatible, task-specific representational models and application programming interfaces (API's), and run on heterogeneous computing platforms. Getting such applications to interact freely calls for platform independent capabilities for distributed communication, as well as tools for mapping information across disparate representations. Symbiotics is developing a layered set of software tools (called NetWorks! for integrating and coordinating heterogeneous distributed applications. he top layer of tools consists of an extensible set of generic, programmable coordination services. Developers access these services via high-level API's to implement the desired interactions between distributed applications.

  8. Computerized decision support system improves fluid resuscitation following severe burns: an original study.

    PubMed

    Salinas, José; Chung, Kevin K; Mann, Elizabeth A; Cancio, Leopoldo C; Kramer, George C; Serio-Melvin, Maria L; Renz, Evan M; Wade, Charles E; Wolf, Steven E

    2011-09-01

    Several formulas have been developed to guide resuscitation in severely burned patients during the initial 48 hrs after injury. These approaches require manual titration of fluid that may result in human error during this process and lead to suboptimal outcomes. The goal of this study was to analyze the efficacy of a computerized open-loop decision support system for burn resuscitation compared to historical controls. Fluid infusion rates and urinary output from 39 severely burned patients with >20% total body surface area burns were recorded upon admission (Model group). A fluid-response model based on these data was developed and incorporated into a computerized open-loop algorithm and computer decision support system. The computer decision support system was used to resuscitate 32 subsequent patients with severe burns (computer decision support system group) and compared with the Model group. Burn intensive care unit of a metropolitan Level 1 Trauma center. Acute burn patients with >20% total body surface area requiring active fluid resuscitation during the initial 24 to 48 hours after burn. We found no significant difference between the Model and computer decision support system groups in age, total body surface area, or injury mechanism. Total crystalloid volume during the first 48 hrs post burn, total crystalloid intensive care unit volume, and initial 24-hr crystalloid intensive care unit volume were all lower in the computer decision support system group. Infused volume per kilogram body weight (mL/kg) and per percentage burn (mL/kg/total body surface area) were also lower for the computer decision support system group. The number of patients who met hourly urinary output goals was higher in the computer decision support system group. Implementation of a computer decision support system for burn resuscitation in the intensive care unit resulted in improved fluid management of severely burned patients. All measures of crystalloid fluid volume were reduced

  9. A Multi-criterial Decision Support System for Forest Management

    Treesearch

    Donald Nute; Geneho Kim; Walter D. Potter; Mark J. Twery; H. Michael Rauscher; Scott Thomasma; Deborah Bennett; Peter Kollasch

    1999-01-01

    We describe a research project that has as its goal development of a full-featured decision support system for managing forested land to satisfy multiple criteria represented as timber, wildlife, water, ecological, and wildlife objectives. The decision process proposed for what was originally conceived of as a Northeast Decision Model (NED) includes data acquisition,...

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

    PubMed

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

    2017-05-19

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

  11. Perfusion computed tomography to assist decision making for stroke thrombolysis

    PubMed Central

    Levi, Christopher; Krishnamurthy, Venkatesh; McElduff, Patrick; Miteff, Ferdi; Spratt, Neil J.; Bateman, Grant; Donnan, Geoffrey; Davis, Stephen; Parsons, Mark

    2015-01-01

    The use of perfusion imaging to guide selection of patients for stroke thrombolysis remains controversial because of lack of supportive phase three clinical trial evidence. We aimed to measure the outcomes for patients treated with intravenous recombinant tissue plasminogen activator (rtPA) at a comprehensive stroke care facility where perfusion computed tomography was routinely used for thrombolysis eligibility decision assistance. Our overall hypothesis was that patients with ‘target’ mismatch on perfusion computed tomography would have improved outcomes with rtPA. This was a prospective cohort study of consecutive ischaemic stroke patients who fulfilled standard clinical/non-contrast computed tomography eligibility criteria for treatment with intravenous rtPA, but for whom perfusion computed tomography was used to guide the final treatment decision. The ‘real-time’ perfusion computed tomography assessments were qualitative; a large perfusion computed tomography ischaemic core, or lack of significant perfusion lesion-core mismatch were considered relative exclusion criteria for thrombolysis. Specific volumetric perfusion computed tomography criteria were not used for the treatment decision. The primary analysis compared 3-month modified Rankin Scale in treated versus untreated patients after ‘off-line’ (post-treatment) quantitative volumetric perfusion computed tomography eligibility assessment based on presence or absence of ‘target’ perfusion lesion-core mismatch (mismatch ratio >1.8 and volume >15 ml, core <70 ml). In a second analysis, we compared outcomes of the perfusion computed tomography-selected rtPA-treated patients to an Australian historical cohort of non-contrast computed tomography-selected rtPA-treated patients. Of 635 patients with acute ischaemic stroke eligible for rtPA by standard criteria, thrombolysis was given to 366 patients, with 269 excluded based on visual real-time perfusion computed tomography assessment. After off

  12. Reef Ecosystem Services and Decision Support Database

    EPA Science Inventory

    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...

  13. Reef Ecosystem Services and Decision Support Database

    EPA Science Inventory

    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...

  14. Decision support system and medical liability.

    PubMed Central

    Allaërt, F. A.; Dusserre, L.

    1992-01-01

    Expert systems, which are going to be an essential tool in Medicine, are evolving in terms of sophistication of both knowledge representation and types of reasoning models used. The more efficient they are, the more often they will be used and professional liability will be involved. So after giving a short survey of configuration and working of expert systems, the authors will study the liabilities of people building and the using expert systems regarding some various dysfunctions. Of course the expert systems have to be considered only for human support and they should not possess any authority themselves, therefore the doctors must keep in mind that it is their own responsibility and as such keep their judgment and criticism. However other professionals could be involved, if they have participated in the building of expert systems. The different liabilities and the burden of proof are discussed according to some possible dysfunctions. In any case the final proof is inside the expert system by itself through re-computation of data. PMID:1482972

  15. Management Needs for Computer Support.

    ERIC Educational Resources Information Center

    Irby, Alice J.

    1978-01-01

    The many and varied demands on university computer services are discussed and the importance of an effective data processing system for university management is emphasized. Case studies of computer use in admissions, registration, and billing are presented as well as the role of top level management in implementing data processing. (BH)

  16. Future of electronic health records: implications for decision support.

    PubMed

    Rothman, Brian; Leonard, Joan C; Vigoda, Michael M

    2012-01-01

    The potential benefits of the electronic health record over traditional paper are many, including cost containment, reductions in errors, and improved compliance by utilizing real-time data. The highest functional level of the electronic health record (EHR) is clinical decision support (CDS) and process automation, which are expected to enhance patient health and healthcare. The authors provide an overview of the progress in using patient data more efficiently and effectively through clinical decision support to improve health care delivery, how decision support impacts anesthesia practice, and how some are leading the way using these systems to solve need-specific issues. Clinical decision support uses passive or active decision support to modify clinician behavior through recommendations of specific actions. Recommendations may reduce medication errors, which would result in considerable savings by avoiding adverse drug events. In selected studies, clinical decision support has been shown to decrease the time to follow-up actions, and prediction has proved useful in forecasting patient outcomes, avoiding costs, and correctly prompting treatment plan modifications by clinicians before engaging in decision-making. Clinical documentation accuracy and completeness is improved by an electronic health record and greater relevance of care data is delivered. Clinical decision support may increase clinician adherence to clinical guidelines, but educational workshops may be equally effective. Unintentional consequences of clinical decision support, such as alert desensitization, can decrease the effectiveness of a system. Current anesthesia clinical decision support use includes antibiotic administration timing, improved documentation, more timely billing, and postoperative nausea and vomiting prophylaxis. Electronic health record implementation offers data-mining opportunities to improve operational, financial, and clinical processes. Using electronic health record data

  17. Online decision support system for surface irrigation management

    NASA Astrophysics Data System (ADS)

    Wang, Wenchao; Cui, Yuanlai

    2017-04-01

    Irrigation has played an important role in agricultural production. Irrigation decision support system is developed for irrigation water management, which can raise irrigation efficiency with few added engineering services. An online irrigation decision support system (OIDSS), in consist of in-field sensors and central computer system, is designed for surface irrigation management in large irrigation district. Many functions have acquired in OIDSS, such as data acquisition and detection, real-time irrigation forecast, water allocation decision and irrigation information management. The OIDSS contains four parts: Data acquisition terminals, Web server, Client browser and Communication system. Data acquisition terminals are designed to measure paddy water level, soil water content in dry land, ponds water level, underground water level, and canals water level. A web server is responsible for collecting meteorological data, weather forecast data, the real-time field data, and manager's feedback data. Water allocation decisions are made in the web server. Client browser is responsible for friendly displaying, interacting with managers, and collecting managers' irrigation intention. Communication system includes internet and the GPRS network used by monitoring stations. The OIDSS's model is based on water balance approach for both lowland paddy and upland crops. Considering basic database of different crops water demands in the whole growth stages and irrigation system engineering information, the OIDSS can make efficient decision of water allocation with the help of real-time field water detection and weather forecast. This system uses technical methods to reduce requirements of user's specialized knowledge and can also take user's managerial experience into account. As the system is developed by the Browser/Server model, it is possible to make full use of the internet resources, to facilitate users at any place where internet exists. The OIDSS has been applied in

  18. Military Medical Decision Support for Homeland Defense During Emergency

    DTIC Science & Technology

    2004-12-01

    Integrated Decision Support ( MERMAIDS ) developed for training of emergency response teams using heterogeneous resources under a unified command and control...The MERMAIDS has been designed to contain a decision-centric interface, which is not only useful for emergency information management, but has...decision models to support response planning during emergency conditions. An expert heuristic evaluation of the MERMAIDS is encouraging. The expert

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

    PubMed Central

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

    2017-01-01

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

  20. Development of Asset Management Decision Support Tools for Power Equipment

    NASA Astrophysics Data System (ADS)

    Okamoto, Tatsuki; Takahashi, Tsuguhiro

    Development of asset management decision support tools become very intensive in order to reduce maintenance cost of power equipment due to the liberalization of power business. This article reviews some aspects of present status of asset management decision support tools development for power equipment based on the papers published in international conferences, domestic conventions, and several journals.

  1. Becoming a Mother: Supported Decision-Making in Context

    ERIC Educational Resources Information Center

    Jamieson, Rhiann; Theodore, Kate; Raczka, Roman

    2016-01-01

    Little is known about how women with intellectual disabilities make decisions in relation to pregnancy. Social support is important for mothers with intellectual disabilities in many areas. This study explored how the support network influenced the decision-making of women with intellectual disabilities in relation to pregnancy. The study extended…

  2. Becoming a Mother: Supported Decision-Making in Context

    ERIC Educational Resources Information Center

    Jamieson, Rhiann; Theodore, Kate; Raczka, Roman

    2016-01-01

    Little is known about how women with intellectual disabilities make decisions in relation to pregnancy. Social support is important for mothers with intellectual disabilities in many areas. This study explored how the support network influenced the decision-making of women with intellectual disabilities in relation to pregnancy. The study extended…

  3. Automation and Accountability in Decision Support System Interface Design

    ERIC Educational Resources Information Center

    Cummings, Mary L.

    2006-01-01

    When the human element is introduced into decision support system design, entirely new layers of social and ethical issues emerge but are not always recognized as such. This paper discusses those ethical and social impact issues specific to decision support systems and highlights areas that interface designers should consider during design with an…

  4. A computational framework for supporting environmental ...

    EPA Pesticide Factsheets

    GLIMPSE is a effort in which the U.S. EPA Office of Research and Development is developing tools to support long-term, coordinated environmental, climate, and energy planning. The purpose of this presentation is to discuss the underlying science questions; provide an overview of current and future GLIMPSE capabilities; introduce GCAM, the computational engine behind GLIMPSE; and, highlight relevant activities in China, including the ABaCAS framework and GCAM-China. A group of Chinese visitors will be on the EPA RTP campus July 28, 9-noon. The visitors are from the PowerChina Huadong Engineering Corporation (weblink is here: http://www.ecidi.com/en/introduction.aspx) and are in US for a training program at Duke. The group is interested in broad management topics such as international business development and managing environmental projects as well as interacting with practitioners to understand “real world” case studies and issues. Their background is primarily related to hydro power but their corporate mission is “Providing engineering services and promoting harmonious development between Man and Nature,” implying a broad interest in the environment. Several researchers with projects with connections to China have been asked to provide an overview of their research to the visitors. I will be talking about the GLIMPSE air-climate-energy decision support project.

  5. A computational framework for supporting environmental ...

    EPA Pesticide Factsheets

    GLIMPSE is a effort in which the U.S. EPA Office of Research and Development is developing tools to support long-term, coordinated environmental, climate, and energy planning. The purpose of this presentation is to discuss the underlying science questions; provide an overview of current and future GLIMPSE capabilities; introduce GCAM, the computational engine behind GLIMPSE; and, highlight relevant activities in China, including the ABaCAS framework and GCAM-China. A group of Chinese visitors will be on the EPA RTP campus July 28, 9-noon. The visitors are from the PowerChina Huadong Engineering Corporation (weblink is here: http://www.ecidi.com/en/introduction.aspx) and are in US for a training program at Duke. The group is interested in broad management topics such as international business development and managing environmental projects as well as interacting with practitioners to understand “real world” case studies and issues. Their background is primarily related to hydro power but their corporate mission is “Providing engineering services and promoting harmonious development between Man and Nature,” implying a broad interest in the environment. Several researchers with projects with connections to China have been asked to provide an overview of their research to the visitors. I will be talking about the GLIMPSE air-climate-energy decision support project.

  6. Decision Support Systems and Line Performance: Case of Gold Coast University Hospital.

    PubMed

    Connor, Martin; Ghapanchi, Amir Hossein; Blumenstein, Michael; Amrollahi, Alireza; Najaftorkaman, Mohammadreza

    2015-01-01

    Computer-based decision support information systems have been promoted for their potential to improve physician performance and patient outcomes and support clinical decision making. The current case study reported design and implementation of a high-level decision support system (DSS) which facilitated the flow of data from operational level to top managers and leadership level of hospitals. The results shows that development of a DSS improve data connectivity, timing, and responsiveness issues via centralised sourcing and storing of principal health-related information in the hospital. The implementation of the system has resulted in significant enhancements in outpatient waiting times management.

  7. Decision-support systems for natural-hazards and land-management issues

    USGS Publications Warehouse

    Dinitz, Laura; Forney, William; Byrd, Kristin

    2012-01-01

    Scientists at the USGS Western Geographic Science Center are developing decision-support systems (DSSs) for natural-hazards and land-management issues. DSSs are interactive computer-based tools that use data and models to help identify and solve problems. These systems can provide crucial support to policymakers, planners, and communities for making better decisions about long-term natural hazards mitigation and land-use planning.

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

    ERIC Educational Resources Information Center

    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…

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

    ERIC Educational Resources Information Center

    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…

  10. Environmental Decision Support with Consistent Metrics

    EPA Science Inventory

    One of the most effective ways to pursue environmental progress is through the use of consistent metrics within a decision making framework. The US Environmental Protection Agency’s Sustainable Technology Division has developed TRACI, the Tool for the Reduction and Assessment of...

  11. Proactive and Adaptive Decision Support Study (PDS)

    DTIC Science & Technology

    2014-12-09

    Approved for public release; distribution unlimited. • DMOC-, N3- and N6-specific CCIRs • GCCS-M • C2RPC / MTC2 SOA • ENMS and other network health...Process RFI Request for Information SMDP Semi-Markov decision process SOA Service-Oriented Architecture SOP Standard Operating Procedure TTP Tactics, Techniques, and Procedures

  12. Environmental Decision Support with Consistent Metrics

    EPA Science Inventory

    One of the most effective ways to pursue environmental progress is through the use of consistent metrics within a decision making framework. The US Environmental Protection Agency’s Sustainable Technology Division has developed TRACI, the Tool for the Reduction and Assessment of...

  13. Medication-related Clinical Decision Support in Computerized Provider Order Entry Systems: A Review

    PubMed Central

    Kuperman, Gilad J.; Bobb, Anne; Payne, Thomas H.; Avery, Anthony J.; Gandhi, Tejal K.; Burns, Gerard; Classen, David C.; Bates, David W.

    2007-01-01

    While medications can improve patients’ health, the process of prescribing them is complex and error prone, and medication errors cause many preventable injuries. Computer provider order entry (CPOE) with clinical decision support (CDS), can improve patient safety and lower medication-related costs. To realize the medication-related benefits of CDS within CPOE, one must overcome significant challenges. Healthcare organizations implementing CPOE must understand what classes of CDS their CPOE systems can support, assure that clinical knowledge underlying their CDS systems is reasonable, and appropriately represent electronic patient data. These issues often influence to what extent an institution will succeed with its CPOE implementation and achieve its desired goals. Medication-related decision support is probably best introduced into healthcare organizations in two stages, basic and advanced. Basic decision support includes drug-allergy checking, basic dosing guidance, formulary decision support, duplicate therapy checking, and drug–drug interaction checking. Advanced decision support includes dosing support for renal insufficiency and geriatric patients, guidance for medication-related laboratory testing, drug-pregnancy checking, and drug–disease contraindication checking. In this paper, the authors outline some of the challenges associated with both basic and advanced decision support and discuss how those challenges might be addressed. The authors conclude with summary recommendations for delivering effective medication-related clinical decision support addressed to healthcare organizations, application and knowledge base vendors, policy makers, and researchers. PMID:17068355

  14. Computing support for High Energy Physics

    SciTech Connect

    Avery, P.; Yelton, J.

    1996-12-01

    This computing proposal (Task S) is submitted separately but in support of the High Energy Experiment (CLEO, Fermilab, CMS) and Theory tasks. The authors have built a very strong computing base at Florida over the past 8 years. In fact, computing has been one of the main contributions to their experimental collaborations, involving not just computing capacity for running Monte Carlos and data reduction, but participation in many computing initiatives, industrial partnerships, computing committees and collaborations. These facts justify the submission of a separate computing proposal.

  15. Are mobile health applications useful for supporting shared decision making in diagnostic and treatment decisions?

    PubMed

    Abbasgholizadeh Rahimi, Samira; Menear, Matthew; Robitaille, Hubert; Légaré, France

    2017-06-01

    Mobile health (mHealth) applications intended to support shared decision making in diagnostic and treatment decisions are increasingly available. In this paper, we discuss some recent studies on mHealth applications with relevance to shared decision making. We discuss the potential advantages and disadvantages of using mHealth in shared decision making in various contexts, and suggest some directions for future research in this quickly expanding field.

  16. Space-time statistics for decision support to smart farming.

    PubMed

    Stein, A; Hoosbeek, M R; Sterk, G

    1997-01-01

    This paper summarizes statistical procedures which are useful for precision farming at different scales. Three topics are addressed: spatial comparison of scenarios for land use, analysis of data in the space-time domain, and sampling in space and time. The first study compares six scenarios for nitrate leaching to ground water. Disjunctive cokriging reduces the computing time by 80% without loss of accuracy. The second study analyses wind erosion during four storms in a field in Niger measured with 21 devices. We investigated the use of temporal replicates to overcome the lack of spatial data. The third study analyses the effects of sampling in space and time for soil nutrient data in a Southwest African field. We concluded that statistical procedures are indispensable for decision support to smart farming.

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

    PubMed

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

    2012-02-01

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

  18. Public Databases Supporting Computational Toxicology

    EPA Science Inventory

    A major goal of the emerging field of computational toxicology is the development of screening-level models that predict potential toxicity of chemicals from a combination of mechanistic in vitro assay data and chemical structure descriptors. In order to build these models, resea...

  19. Public Databases Supporting Computational Toxicology

    EPA Science Inventory

    A major goal of the emerging field of computational toxicology is the development of screening-level models that predict potential toxicity of chemicals from a combination of mechanistic in vitro assay data and chemical structure descriptors. In order to build these models, resea...

  20. Personal Computer Ownership--A Major Decision.

    ERIC Educational Resources Information Center

    Collins, Eleanor M.

    1982-01-01

    Considerations to be taken into account before buying a home computer include one's attitude toward computers, need, cost, and available space. A personal computer can be beneficial as a tutor, entertainer, record-keeper, and aid to the handicapped. Home economists must attempt to understand the implications of home computers for family life. (JOW)

  1. Exploration Clinical Decision Support System: Medical Data Architecture

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

  2. A knowledge-based decision support system for payload scheduling

    NASA Technical Reports Server (NTRS)

    Floyd, Stephen; Ford, Donnie

    1988-01-01

    The role that artificial intelligence/expert systems technologies play in the development and implementation of effective decision support systems is illustrated. A recently developed prototype system for supporting the scheduling of subsystems and payloads/experiments for NASA's Space Station program is presented and serves to highlight various concepts. The potential integration of knowledge based systems and decision support systems which has been proposed in several recent articles and presentations is illustrated.

  3. Mobile decision support for transplantation patient data.

    PubMed

    Krause, Andreas; Hartl, Dominik; Theis, Fabian; Stangl, Manfred; Gerauer, Klaus E; Mehlhorn, Alexander T

    2004-06-15

    In high-critical medical fields instant information delivery is essential. Task-flow analyses within the transplantation unit of the Technische Universität München revealed that valuable time could be saved in pre-transplantation management being able to retrieve data of organ receivers ubiquitously. Inspired by this clinical scenario, a mobile application was designed and implemented providing surgeons with decision-relevant information on potential organ receivers. It assists them in considering the prospects of forthcoming organ transplantations and facilitates decision making and documentation with regard to high security demands. The described system services three organ receiver lists and is used by the surgeons in every transplantation procedure. After a 6-month period of clinical usage, the system has been evaluated in terms of handling, clinical benefit and total time savings. Intuitive, ubiquitous access to decision-relevant patient data and authenticated documentation were the major improvements with average total time savings of 50 min in comparison to the old system.

  4. Decision support for redesigning wastewater treatment technologies.

    PubMed

    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.

  5. Neural and computational mechanisms of postponed decisions

    PubMed Central

    Martínez-García, Marina; Rolls, Edmund T.; Deco, Gustavo; Romo, Ranulfo

    2011-01-01

    We consider the mechanisms that enable decisions to be postponed for a period after the evidence has been provided. Using an information theoretic approach, we show that information about the forthcoming action becomes available from the activity of neurons in the medial premotor cortex in a sequential decision-making task after the second stimulus is applied, providing the information for a decision about whether the first or second stimulus is higher in vibrotactile frequency. The information then decays in a 3-s delay period in which the neuronal activity declines before the behavioral response can be made. The information then increases again when the behavioral response is required. We model this neuronal activity using an attractor decision-making network in which information reflecting the decision is maintained at a low level during the delay period, and is then selectively restored by a nonspecific input when the response is required. One mechanism for the short-term memory is synaptic facilitation, which can implement a mechanism for postponed decisions that can be correct even when there is little neuronal firing during the delay period before the postponed decision. Another mechanism is graded firing rates by different neurons in the delay period, with restoration by the nonspecific input of the low-rate activity from the higher-rate neurons still firing in the delay period. These mechanisms can account for the decision making and for the memory of the decision before a response can be made, which are evident in the activity of neurons in the medial premotor cortex. PMID:21709222

  6. Group Decision Support System applied to the medical pluri-disciplinary decision group: usability and efficacy.

    PubMed

    Degardin-Capon, Nathalie; Bricon-Souf, Nathalie; Beuscart-Zephir, Marie-Catherine; Beuscart, Régis

    2008-01-01

    This paper aims to study whether the application of a Group Decision Support System to medical collective decision committees is possible and to determine which GDSS specifications are convenient. We introduce the common knowledge about GDSS and define the process of the collective medical decision. An experimental GDSS has been tested in an actual medical collective decision committee. A usability analysis has been performed to precise usability and acceptability of the system and to highlight pro and cons of the various functionalities of the GDSS. Information sharing was conveniently supported by the GDSS. All the documents were available for the support of the discussion. But, the introduction of a GDSS in the decision committee added new constraints such as the necessity of an excellent preparation phase. Limits of the system have been revealed: lack of feedback on decision actors, lack of support to obtain the consensus and lack of memorisation. According to these results, we have proposed new GDSS features to improve the decision. Using a GDSS supporting the medical collective decision is realistic and may support the process of the consensual decision.

  7. Computers in pharmacokinetics. Choosing software for clinical decision making.

    PubMed

    Buffington, D E; Lampasona, V; Chandler, M H

    1993-09-01

    Over the past 20 years, pharmacokinetic programs have been developed for clinical decision making. These clinical pharmacokinetic software programs are designed to assist the clinician in the analysis, interpretation and reporting of serum drug concentration data for a variety of medications. The programs vary in the extent of features and range of medications supported and thus warrant careful review before selecting or purchasing such a program for routine use. A series of programs which are commercially available in the United States was reviewed for this article. The focus of the review is not to recommend a single program or to provide a ranked list of commercially available programs. Information is presented to clinicians to better their understanding of the features of these computer-based clinical resources. As an introduction to this topic, the information presented concentrates on the system and support features. Those programs that were reviewed demonstrate the ability to assist in the analysis of serum or plasma drug concentration data for most of the medications that warrant therapeutic drug monitoring. They provide both Bayesian and non-Bayesian methods for predicting serum drug concentrations. Standard personal computers were sufficient to run each of the programs reviewed. In addition, most programs offered technical and clinical support. However, the quality of the user manuals and training material varies among software programs. In-depth analytical comparisons are currently being conducted for future publication.

  8. Decision support systems for robotic surgery and acute care

    NASA Astrophysics Data System (ADS)

    Kazanzides, Peter

    2012-06-01

    Doctors must frequently make decisions during medical treatment, whether in an acute care facility, such as an Intensive Care Unit (ICU), or in an operating room. These decisions rely on a various information sources, such as the patient's medical history, preoperative images, and general medical knowledge. Decision support systems can assist by facilitating access to this information when and where it is needed. This paper presents some research eorts that address the integration of information with clinical practice. The example systems include a clinical decision support system (CDSS) for pediatric traumatic brain injury, an augmented reality head- mounted display for neurosurgery, and an augmented reality telerobotic system for minimally-invasive surgery. While these are dierent systems and applications, they share the common theme of providing information to support clinical decisions and actions, whether the actions are performed with the surgeon's own hands or with robotic assistance.

  9. Mining multi-dimensional data for decision support

    SciTech Connect

    Donato, J.M.; Schryver, J.C.; Hinkel, G.C.; Schmoyer, R.L. Jr.; Grady, N.W.; Leuze, M.R. |

    1998-06-01

    While it is widely recognized that data can be a valuable resource for any organization, extracting information contained within the data is often a difficult problem. Attempts to obtain information from data may be limited by legacy data storage formats, lack of expert knowledge about the data, difficulty in viewing the data, or the volume of data needing to be processed. The rapidly developing field of Data Mining or Knowledge Data Discovery is a blending of Artificial Intelligence, Statistics, and Human-Computer Interaction. Sophisticated data navigation tools to obtain the information needed for decision support do not yet exist. Each data mining task requires a custom solution that depends upon the character and quantity of the data. This paper presents a two-stage approach for handling the prediction of personal bankruptcy using credit card account data, combining decision tree and artificial neural network technologies. Topics to be discussed include the pre-processing of data, including data cleansing, the filtering of data for pertinent records, and the reduction of data for attributes contributing to the prediction of bankruptcy, and the two steps in the mining process itself.

  10. Distributed Hydrologic Modeling Apps for Decision Support in the Cloud

    NASA Astrophysics Data System (ADS)

    Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.

    2013-12-01

    Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it

  11. A decision-support system for off-site nuclear emergencies.

    PubMed

    Yihua, X; Lin, G; Su, P; Tiefu, L; Honghui, X; Yongxing, Z; Xinzeng, S

    1998-03-01

    In the case of a nuclear emergency, quick, well-founded decisions must be made about the type of protective action, its region of application, and initiation time. These typically are tasks for computer-based systems. Even with emergency-preparedness, exercises, and training, the decision-support system is one of great importance. This paper describes a decision-support system recently developed by the China Institute of Atomic Energy; it can optimally rank actions during the early phase of an accident using multiattribute utility analysis, and for the intermediate and later phases by cost-benefit analysis. This system runs both on MICRO VAX II and PC systems.

  12. NASA E-DECIDER Rapid Disaster Decision Support Products

    NASA Image and Video Library

    2014-09-03

    A NASA-funded disaster decision support system, provided a number of rapid response map data products to decision makers at the California Earthquake Clearinghouse following its activation for the Aug. 24, 2014 magnitude 6.0 earthquake in Napa, California

  13. Decision Support Framework (DSF) Team Research Implementation Plan

    EPA Science Inventory

    The mission of ORD's Ecosystem Services Research Program (ESRP) is to provide the information and methods needed by decision-makers to assess the benefits of ecosystem goods and services to human well-being for inclusion in management alternatives. The Decision Support Framework...

  14. Decision Support Framework (DSF) Team Research Implementation Plan

    EPA Science Inventory

    The mission of ORD's Ecosystem Services Research Program (ESRP) is to provide the information and methods needed by decision-makers to assess the benefits of ecosystem goods and services to human well-being for inclusion in management alternatives. The Decision Support Framework...

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

    NASA Astrophysics Data System (ADS)

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

    PubMed

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

    2012-03-01

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

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

    PubMed

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

    2014-10-01

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

  18. The Organizational Impact of a Decision Support System.

    ERIC Educational Resources Information Center

    Pope, James A.; Cross, Edward M.

    1984-01-01

    The results of a follow-up evaluation of a decision support system installed 5 years ago at Guilford College are reported. Changes in the system, resulting procedures, and the organization are described. (Author/MLW)

  19. DECISION SUPPORT FRAMEWORK FOR STORMWATER MANAGEMENT IN URBAN WATERSHEDS

    EPA Science Inventory

    To assist stormwater management professionals in planning for best management practices (BMPs) implementation, the U.S. Environmental Protection Agency (USEPA) is developing a decision support system for placement of BMPs at strategic locations in urban watersheds. This tool wil...

  20. DECISION SUPPORT FRAMEWORK FOR STORMWATER MANAGEMENT IN URBAN WATERSHEDS

    EPA Science Inventory

    To assist stormwater management professionals in planning for best management practices (BMPs) implementation, the U.S. Environmental Protection Agency (USEPA) is developing a decision support system for placement of BMPs at strategic locations in urban watersheds. This tool wil...

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

    PubMed

    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.

  2. Decision Support Systems: A Preliminary Study,

    DTIC Science & Technology

    1977-09-01

    goal for data management research is an integrated data system -12- _ _...__ _ _ ... ’ . ENGLISH LOGIC FORMAL DATA LISP OR SUBSET (KOWALSKI LANG FOR...studies are indicated to determine if cannonical forms can be used to make vector operations out of operations like COND (from LISP ). Studies of the...W.W., Boyer, Robert S., and Henneman , William H., (1972), "Computer Proofs of Limits Theorems", A.I. Jour., 3, pp. 27-60. 12. Bledsoe, W.W. and

  3. A Fuzzy Logic Decision Support Tool

    DTIC Science & Technology

    1989-10-01

    also be improved . The Navy and Air Force have developed expert systems , the Air Strike Plan- ning Advisor (ASPA) and the Knowledge- based Replanning...use of fuzzy logic not only in industrial process con- trol but, more generally, in knowledge- based systems in which the deduction of an answer to a...having to move closer. If not already known, these percentages can be computed based on a number of known parameters and distribution functions. Fuzzy

  4. Medical decision support systems and therapeutics: The role of autopilots.

    PubMed

    Woosley, R L; Whyte, J; Mohamadi, A; Romero, K

    2016-02-01

    For decades, medical practice has increasingly relied on prescription medicines to treat, cure, or prevent illness but their net benefit is reduced by prescribing errors that result in adverse drug reactions (ADRs) and tens of thousands of deaths each year. Optimal prescribing requires effective management of massive amounts of data. Clinical decision support systems (CDSS) can help manage information and support optimal therapeutic decisions before errors are made by operating as the prescribers' "autopilot."

  5. Decision-support and intelligent tutoring systems in medical education.

    PubMed

    Frize, M; Frasson, C

    2000-08-01

    One of the challenges in medical education is to teach the decision-making process. This learning process varies according to the experience of the student and can be supported by various tools. In this paper we present several approaches that can strengthen this mechanism, from decision-support tools, such as scoring systems, Bayesian models, neural networks, to cognitive models that can reproduce how the students progressively build their knowledge into memory and foster pedagogic methods.

  6. An analysis of symbolic linguistic computing models in decision making

    NASA Astrophysics Data System (ADS)

    Rodríguez, Rosa M.; Martínez, Luis

    2013-01-01

    It is common that experts involved in complex real-world decision problems use natural language for expressing their knowledge in uncertain frameworks. The language is inherent vague, hence probabilistic decision models are not very suitable in such cases. Therefore, other tools such as fuzzy logic and fuzzy linguistic approaches have been successfully used to model and manage such vagueness. The use of linguistic information implies to operate with such a type of information, i.e. processes of computing with words (CWW). Different schemes have been proposed to deal with those processes, and diverse symbolic linguistic computing models have been introduced to accomplish the linguistic computations. In this paper, we overview the relationship between decision making and CWW, and focus on symbolic linguistic computing models that have been widely used in linguistic decision making to analyse if all of them can be considered inside of the CWW paradigm.

  7. Interactive Decision Support for Academic Advising

    ERIC Educational Resources Information Center

    Mohamed, Abdallah

    2016-01-01

    Purpose: This paper aims to support academic advising, which plays a crucial role in student success and retention. The paper focuses on one of the most challenging tasks involved in academic advising: individual course scheduling. This task includes not only careful planning for different courses over several semesters according to students'…

  8. Interactive Decision Support for Academic Advising

    ERIC Educational Resources Information Center

    Mohamed, Abdallah

    2016-01-01

    Purpose: This paper aims to support academic advising, which plays a crucial role in student success and retention. The paper focuses on one of the most challenging tasks involved in academic advising: individual course scheduling. This task includes not only careful planning for different courses over several semesters according to students'…

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

    NASA Astrophysics Data System (ADS)

    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.

  10. Nurses' ethical decision-making role in artificial nutritional support.

    PubMed

    Tsaloglidou, A; Rammos, K; Kiriklidis, K; Zourladani, A; Matziari, C

    This study provides an insight into the process of ethical decision-making regarding the initiation or withdrawal of artificial nutritional support of seriously ill patients and explores the nursing involvement in it. Fifteen health carers were recruited from a clinical nutrition unit in the UK and qualitative research methods were used to gather data. The findings of the study indicate that nursing contribution to decision-making appeared to be in the 'back room' as the nurses feel that the decisions about difficult ethical dilemmas are 'out of their hands' because of lack of knowledge, experience and confidence. The medical staff and the clinical nurse specialist appear to be primarily responsible for making important decisions. It is clear from the study that to become more effective in the process, nurses need to enhance their knowledge in nutritional support and to develop their practical skills in ethical decision-making through experience and research.

  11. Group decision support system for customer-driven product design

    NASA Astrophysics Data System (ADS)

    Lin, Zhihang; Chen, Hang; Chen, Kuen; Che, Ada

    2000-10-01

    This paper describes the work on the development of a group decision support system for customer driven product design. The customer driven is to develop products, which meet all customer requirements in whole life cycle of products. A process model of decision during product primary design is proposed to formulate the structured, semi-structured and unstructured decision problems. The framework for the decision support system is presented that integrated both advances in the group decision making and distributed artificial intelligent. The system consists of the product primary design tool kit and the collaborative platform with multi-agent structure. The collaborative platform of the system and the product primary design tool kit, including the VOC (Voice of Customer) tool, QFD (Quality Function Deployment) tool, the Conceptual design tool, Reliability analysis tool and the cost and profit forecasting tool, are indicated.

  12. Towards ethical decision support and knowledge management in neonatal intensive care.

    PubMed

    Yang, L; Frize, M; Eng, P; Walker, R; Catley, C

    2004-01-01

    Recent studies in neonatal medicine, clinical nursing, and cognitive psychology have indicated the need to augment current decision-making practice in neonatal intensive care units with computerized, intelligent decision support systems. Rapid progress in artificial intelligence and knowledge management facilitates the design of collaborative ethical decision-support tools that allow clinicians to provide better support for parents facing inherently difficult choices, such as when to withdraw aggressive treatment. The appropriateness of using computers to support ethical decision-making is critically analyzed through research and literature review. In ethical dilemmas, multiple diverse participants need to communicate and function as a team to select the best treatment plan. In order to do this, physicians require reliable estimations of prognosis, while parents need a highly useable tool to help them assimilate complex medical issues and address their own value system. Our goal is to improve and structuralize the ethical decision-making that has become an inevitable part of modern neonatal care units. The paper contributes to clinical decision support by outlining the needs and basis for ethical decision support and justifying the proposed development efforts.

  13. Fuzzy Cognitive Map scenario-based medical decision support systems for education.

    PubMed

    Georgopoulos, Voula C; Chouliara, Spyridoula; Stylios, Chrysostomos D

    2014-01-01

    Soft Computing (SC) techniques are based on exploiting human knowledge and experience and they are extremely useful to model any complex decision making procedure. Thus, they have a key role in the development of Medical Decision Support Systems (MDSS). The soft computing methodology of Fuzzy Cognitive Maps has successfully been used to represent human reasoning and to infer conclusions and decisions in a human-like way and thus, FCM-MDSSs have been developed. Such systems are able to assist in critical decision-making, support diagnosis procedures and consult medical professionals. Here a new methodology is introduced to expand the utilization of FCM-MDSS for learning and educational purposes using a scenario-based learning (SBL) approach. This is particularly important in medical education since it allows future medical professionals to safely explore extensive "what-if" scenarios in case studies and prepare for dealing with critical adverse events.

  14. Moving toward climate-informed agricultural decision support - can we use PRISM data for more than just monthly averages?

    USDA-ARS?s Scientific Manuscript database

    Decision support systems/models for agriculture are varied in target application and complexity, ranging from simple worksheets to near real-time forecast systems requiring significant computational and manpower resources. Until recently, most such decision support systems have been constructed with...

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

    SciTech Connect

    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.

  16. System Engineering and Evolution Decision Support

    DTIC Science & Technology

    2007-11-02

    invoked the applet. 5. LANGUAGE SUPPORT FOR INTELLIGENT SOFTWARE DECOYS We believe that Eiffel is a natural choice of programming languages for...implementing intelligent software decoys, at least for the purposes of initial experimentation with such decoys. In contrast to Ada, for example, Eiffel ...operations ensure postconditions invariant invariants end Moreover, Eiffel provides for inheritance of the assertions from ancestor classes by a descendant

  17. Computer Maintenance Operations Center (CMOC), additional computer support equipment ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Computer Maintenance Operations Center (CMOC), additional computer support equipment - Beale Air Force Base, Perimeter Acquisition Vehicle Entry Phased-Array Warning System, Techinical Equipment Building, End of Spencer Paul Road, north of Warren Shingle Road (14th Street), Marysville, Yuba County, CA

  18. Computer Maintenance Operations Center (CMOC), additional computer support equipment ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Computer Maintenance Operations Center (CMOC), additional computer support equipment - Beale Air Force Base, Perimeter Acquisition Vehicle Entry Phased-Array Warning System, Techinical Equipment Building, End of Spencer Paul Road, north of Warren Shingle Road (14th Street), Marysville, Yuba County, CA

  19. Development and description of a decision analysis based decision support tool for stroke prevention in atrial fibrillation

    PubMed Central

    Thomson, R.; Robinson, A.; Greenaway, J.; Lowe, P.

    2002-01-01

    Background: There is an increasing move towards clinical decision making that engages the patient, which has led to the development and use of decision aids to support better decisions. The treatment of patients in atrial fibrillation (AF) with warfarin to prevent stroke is a decision that is sensitive to patient preferences as shown by a previous decision analysis. Aim: To develop a computerised decision support tool, building upon a previous decision analysis, which would engage individual patient preferences in reaching a shared decision on whether to take warfarin to prevent stroke. Methods: The development process had two main phases: (1) the development phase which employed focus groups and repeated interviews with GPs/practice nurses and patients alongside an iterative development of a computerised tool; (2) the training and testing phase in which GPs and practice nurses underwent training in the use of the tool, including the use of simulated patients. The tool was then used in a feasibility study in a small number of patients with AF to inform the design of a subsequent randomised controlled trial. Results: The prototype tool had three components: (1) derivation of an individual patient's values for relevant health states using a standard gamble; (2) presentation/discussion of a patient's risks of stroke using the Framingham equation and the benefits/risks of warfarin from a systematic literature review; and (3) decision making component incorporating the outcome of a Markov decision analysis model. Older patients could be taken through the decision analysis based computerised tool, and patients and clinicians welcomed information on risks and benefits of treatments. The tool required time and training to use. Patients' decisions in the feasibility phase did not necessarily coincide with the output of the decision analysis model, but decision conflict appeared to be reduced and both patients and GPs were satisfied with the process. Conclusions: It is

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

    PubMed

    Lee, Seonah

    2013-10-01

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

  1. Fuzzy Naive Bayesian model for medical diagnostic decision support.

    PubMed

    Wagholikar, Kavishwar B; Vijayraghavan, Sundararajan; Deshpande, Ashok W

    2009-01-01

    This work relates to the development of computational algorithms to provide decision support to physicians. The authors propose a Fuzzy Naive Bayesian (FNB) model for medical diagnosis, which extends the Fuzzy Bayesian approach proposed by Okuda. A physician's interview based method is described to define a orthogonal fuzzy symptom information system, required to apply the model. For the purpose of elaboration and elicitation of characteristics, the algorithm is applied to a simple simulated dataset, and compared with conventional Naive Bayes (NB) approach. As a preliminary evaluation of FNB in real world scenario, the comparison is repeated on a real fuzzy dataset of 81 patients diagnosed with infectious diseases. The case study on simulated dataset elucidates that FNB can be optimal over NB for diagnosing patients with imprecise-fuzzy information, on account of the following characteristics - 1) it can model the information that, values of some attributes are semantically closer than values of other attributes, and 2) it offers a mechanism to temper exaggerations in patient information. Although the algorithm requires precise training data, its utility for fuzzy training data is argued for. This is supported by the case study on infectious disease dataset, which indicates optimality of FNB over NB for the infectious disease domain. Further case studies on large datasets are required to establish utility of FNB.

  2. System-Agnostic Clinical Decision Support Services: Benefits and Challenges for Scalable Decision Support

    PubMed Central

    Kawamoto, Kensaku; Del Fiol, Guilherme; Orton, Charles; Lobach, David F

    2010-01-01

    System-agnostic clinical decision support (CDS) services provide patient evaluation capabilities that are independent of specific CDS systems and system implementation contexts. While such system-agnostic CDS services hold great potential for facilitating the widespread implementation of CDS systems, little has been described regarding the benefits and challenges of their use. In this manuscript, the authors address this need by describing potential benefits and challenges of using a system-agnostic CDS service. This analysis is based on the authors’ formal assessments of, and practical experiences with, various approaches to developing, implementing, and maintaining CDS capabilities. In particular, the analysis draws on the authors’ experience developing and leveraging a system-agnostic CDS Web service known as SEBASTIAN. A primary potential benefit of using a system-agnostic CDS service is the relative ease and flexibility with which the service can be leveraged to implement CDS capabilities across applications and care settings. Other important potential benefits include facilitation of centralized knowledge management and knowledge sharing; the potential to support multiple underlying knowledge representations and knowledge resources through a common service interface; improved simplicity and componentization; easier testing and validation; and the enabling of distributed CDS system development. Conversely, important potential challenges include the increased effort required to develop knowledge resources capable of being used in many contexts and the critical need to standardize the service interface. Despite these challenges, our experiences to date indicate that the benefits of using a system-agnostic CDS service generally outweigh the challenges of using this approach to implementing and maintaining CDS systems. PMID:21603281

  3. System-agnostic clinical decision support services: benefits and challenges for scalable decision support.

    PubMed

    Kawamoto, Kensaku; Del Fiol, Guilherme; Orton, Charles; Lobach, David F

    2010-01-01

    System-agnostic clinical decision support (CDS) services provide patient evaluation capabilities that are independent of specific CDS systems and system implementation contexts. While such system-agnostic CDS services hold great potential for facilitating the widespread implementation of CDS systems, little has been described regarding the benefits and challenges of their use. In this manuscript, the authors address this need by describing potential benefits and challenges of using a system-agnostic CDS service. This analysis is based on the authors' formal assessments of, and practical experiences with, various approaches to developing, implementing, and maintaining CDS capabilities. In particular, the analysis draws on the authors' experience developing and leveraging a system-agnostic CDS Web service known as SEBASTIAN. A primary potential benefit of using a system-agnostic CDS service is the relative ease and flexibility with which the service can be leveraged to implement CDS capabilities across applications and care settings. Other important potential benefits include facilitation of centralized knowledge management and knowledge sharing; the potential to support multiple underlying knowledge representations and knowledge resources through a common service interface; improved simplicity and componentization; easier testing and validation; and the enabling of distributed CDS system development. Conversely, important potential challenges include the increased effort required to develop knowledge resources capable of being used in many contexts and the critical need to standardize the service interface. Despite these challenges, our experiences to date indicate that the benefits of using a system-agnostic CDS service generally outweigh the challenges of using this approach to implementing and maintaining CDS systems.

  4. Evaluating Detection and Diagnostic Decision Support Systems for Bioterrorism Response

    PubMed Central

    Sundaram, Vandana; McDonald, Kathryn M.; Smith, Wendy M.; Szeto, Herbert; Schleinitz, Mark D.; Owens, Douglas K.

    2004-01-01

    We evaluated the usefulness of detection systems and diagnostic decision support systems for bioterrorism response. We performed a systematic review by searching relevant databases (e.g., MEDLINE) and Web sites for reports of detection systems and diagnostic decision support systems that could be used during bioterrorism responses. We reviewed over 24,000 citations and identified 55 detection systems and 23 diagnostic decision support systems. Only 35 systems have been evaluated: 4 reported both sensitivity and specificity, 13 were compared to a reference standard, and 31 were evaluated for their timeliness. Most evaluations of detection systems and some evaluations of diagnostic systems for bioterrorism responses are critically deficient. Because false-positive and false-negative rates are unknown for most systems, decision making on the basis of these systems is seriously compromised. We describe a framework for the design of future evaluations of such systems. PMID:15078604

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

    PubMed Central

    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

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

    PubMed

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

    2016-03-01

    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.

  7. Using Google Earth in Marine Research and Operational Decision Support

    NASA Astrophysics Data System (ADS)

    Blower, J. D.; Bretherton, D.; Haines, K.; Liu, C.; Rawlings, C.; Santokhee, A.; Smith, I.

    2006-12-01

    A key advantage of Virtual Globes ("geobrowsers") such as Google Earth is that they can display many different geospatial data types at a huge range of spatial scales. In this demonstration and poster display we shall show how marine data from disparate sources can be brought together in a geobrowser in order to support both scientific research and operational search and rescue activities. We have developed the Godiva2 interactive website for browsing and exploring marine data, mainly output from supercomputer analyses and predictions of ocean circulation. The user chooses a number of parameters (e.g. sea temperature at 100m depth on 1st July 2006) and can load an image of the resulting data in Google Earth. Through the use of an automatically-refreshing NetworkLink the user can explore the whole globe at a very large range of spatial scales: the displayed data will automatically be refreshed to show data at increasingly fine resolution as the user zooms in. This is a valuable research tool for exploring these terabyte- scale datasets. Many coastguard organizations around the world use SARIS, a software application produced by BMT Cordah Ltd., to predict the drift pattern of objects in the sea in order to support search and rescue operations. Different drifting objects have different trajectories depending on factors such as their buoyancy and windage and so a computer model, supported by meteorological and oceanographic data, is needed to help rescuers locate their targets. We shall demonstrate how Google Earth is used to display output from the SARIS model (including the search target location and associated error polygon) alongside meteorological data (wind vectors) and oceanographic data (sea temperature, surface currents) from Godiva2 in order to support decision-making. We shall also discuss the limitations of using Google Earth in this context: these include the difficulties of working with time- dependent data and the need to access data securely. essc

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

    PubMed

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

    2015-11-01

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

  9. Barriers to and facilitators of implementing shared decision making and decision support in a paediatric hospital: A descriptive study

    PubMed Central

    Boland, Laura; McIsaac, Daniel I; Lawson, Margaret L

    2016-01-01

    OBJECTIVE: To explore multiple stakeholders’ perceived barriers to and facilitators of implementing shared decision making and decision support in a tertiary paediatric hospital. METHODS: An interpretive descriptive qualitative study was conducted using focus groups and interviews to examine senior hospital administrators’, clinicians’, parents’ and youths’ perceived barriers to and facilitators of shared decision making and decision support implementation. Data were analyzed using inductive thematic analysis. RESULTS: Fifty-seven stakeholders participated. Six barrier and facilitator themes emerged. The main barrier was gaps in stakeholders’ knowledge of shared decision making and decision support. Facilitators included compatibility between shared decision making and the hospital’s culture and ideal practices, perceptions of positive patient and family outcomes associated with shared decision making, and positive attitudes regarding shared decision making and decision support. However, youth attitudes regarding the necessity and usefulness of a decision support program were a barrier. Two themes were both a barrier and a facilitator. First, stakeholder groups were uncertain which clinical situations are suitable for shared decision making (eg, new diagnoses, chronic illnesses, complex decisions or urgent decisions). Second, the clinical process may be hindered if shared decision making and decision support decrease efficiency and workflow; however, shared decision making may reduce repeat visits and save time over the long term. CONCLUSIONS: Specific knowledge translation strategies that improve shared decision making knowledge and match specific barriers identified by each stakeholder group may be required to promote successful shared decision making and decision support implementation in the authors’ paediatric hospital. PMID:27398058

  10. Human-Computer Interactions and Decision Behavior

    DTIC Science & Technology

    1984-01-01

    Narang A. Cohill J. Pittman J. Elkerton M. Revesman R. Fainter C. Rieger L. Folley J. Schurick M. Hakkinen A. Siochi D. Johnson T. Spine C. Ku M. Sti...W., Yunten, T., , Johnson , D. H. DMS: A comprehensive system for managing human- computer dialogue. In Proceedings of Human Factors in Computer...interactive system. Wel! known software metrics are used in this analysis. 3. The Dialogue Author a. Reports Johnson , D. H., Hartson, H. R. The role

  11. Decision support system for theater missile defense

    NASA Astrophysics Data System (ADS)

    Gonsalves, Paul; Burge, Janet; Popp, Ben

    2003-08-01

    Military services require C4I systems that support a full spectrum of operations. This is specifically relevant to the theatre missile defense (TMD) mission planning and analysis community where there have been several recent concept changes; advancements in information technology, sensors, and weapons; and expansion in the diversity and capabilities of potential adversaries. To fully support campaign development and analysis in this new environment, there is a need for systems and tools that enhance understanding of adversarial behavior, assess potential threat capabilities and vulnerabilities, perform C4I system trades, and provide methods to identify macro-level novel or emergent combat tactics and behavior derived from simpler micro-level rules. Such systems must also be interactive, collaborative, and semi-autonomous, providing the INTEL analyst with the means for exploration and potential exploitation of novel enemy behavior patterns. To address these issues we have developed an Intelligent Threat Assessment Processor (ITAP) to provide prediction and interpretation of enemy courses of actions (eCOAs) for the TMD domain. This system uses a combination of genetic algorithm-based optimization in tandem with the spatial analysis and visualization capabilities of a commercial-off-the-shelf (COTS) geographic information system to generate and evaluate potential eCOAs.

  12. Structured decision making as a method for linking quantitative decision support to community fundamental objectives

    EPA Science Inventory

    Decision support intended to improve ecosystem sustainability requires that we link stakeholder priorities directly to quantitative tools and measures of desired outcomes. Actions taken at the community level can have large impacts on production and delivery of ecosystem service...

  13. Structured decision making as a method for linking quantitative decision support to community fundamental objectives

    EPA Science Inventory

    Decision support intended to improve ecosystem sustainability requires that we link stakeholder priorities directly to quantitative tools and measures of desired outcomes. Actions taken at the community level can have large impacts on production and delivery of ecosystem service...

  14. Computational study of developing high-quality decision trees

    NASA Astrophysics Data System (ADS)

    Fu, Zhiwei

    2002-03-01

    Recently, decision tree algorithms have been widely used in dealing with data mining problems to find out valuable rules and patterns. However, scalability, accuracy and efficiency are significant concerns regarding how to effectively deal with large and complex data sets in the implementation. In this paper, we propose an innovative machine learning approach (we call our approach GAIT), combining genetic algorithm, statistical sampling, and decision tree, to develop intelligent decision trees that can alleviate some of these problems. We design our computational experiments and run GAIT on three different data sets (namely Socio- Olympic data, Westinghouse data, and FAA data) to test its performance against standard decision tree algorithm, neural network classifier, and statistical discriminant technique, respectively. The computational results show that our approach outperforms standard decision tree algorithm profoundly at lower sampling levels, and achieves significantly better results with less effort than both neural network and discriminant classifiers.

  15. Reviewing model application to support animal health decision making.

    PubMed

    Singer, Alexander; Salman, Mo; Thulke, Hans-Hermann

    2011-04-01

    Animal health is of societal importance as it affects human welfare, and anthropogenic interests shape decision making to assure animal health. Scientific advice to support decision making is manifold. Modelling, as one piece of the scientific toolbox, is appreciated for its ability to describe and structure data, to give insight in complex processes and to predict future outcome. In this paper we study the application of scientific modelling to support practical animal health decisions. We reviewed the 35 animal health related scientific opinions adopted by the Animal Health and Animal Welfare Panel of the European Food Safety Authority (EFSA). Thirteen of these documents were based on the application of models. The review took two viewpoints, the decision maker's need and the modeller's approach. In the reviewed material three types of modelling questions were addressed by four specific model types. The correspondence between tasks and models underpinned the importance of the modelling question in triggering the modelling approach. End point quantifications were the dominating request from decision makers, implying that prediction of risk is a major need. However, due to knowledge gaps corresponding modelling studies often shed away from providing exact numbers. Instead, comparative scenario analyses were performed, furthering the understanding of the decision problem and effects of alternative management options. In conclusion, the most adequate scientific support for decision making - including available modelling capacity - might be expected if the required advice is clearly stated.

  16. Creating Shareable Clinical Decision Support Rules for a Pharmacogenomics Clinical Guideline Using Structured Knowledge Representation

    PubMed Central

    Linan, Margaret K.; Sottara, Davide; Freimuth, Robert R.

    2015-01-01

    Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema. The modeling and extraction processes developed here demonstrate how structured knowledge representations can be used to support the creation of shareable CDS rules from PGx guidelines. PMID:26958298

  17. Creating Shareable Clinical Decision Support Rules for a Pharmacogenomics Clinical Guideline Using Structured Knowledge Representation.

    PubMed

    Linan, Margaret K; Sottara, Davide; Freimuth, Robert R

    2015-01-01

    Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema. The modeling and extraction processes developed here demonstrate how structured knowledge representations can be used to support the creation of shareable CDS rules from PGx guidelines.

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

    ERIC Educational Resources Information Center

    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…

  19. Designing Computerized Decision Support That Works for Clinicians and Families

    PubMed Central

    Fiks, Alexander G.

    2011-01-01

    Evidence-based decision-making is central to the practice of pediatrics. Clinical trials and other biomedical research provide a foundation for this process, and practice guidelines, drawing from their results, inform the optimal management of an increasing number of childhood health problems. However, many clinicians fail to adhere to guidelines. Clinical decision support delivered using health information technology, often in the form of electronic health records, provides a tool to deliver evidence-based information to the point of care and has the potential to overcome barriers to evidence-based practice. An increasing literature now informs how these systems should be designed and implemented to most effectively improve outcomes in pediatrics. Through the examples of computerized physician order entry, as well as the impact of alerts at the point of care on immunization rates, the delivery of evidence-based asthma care, and the follow-up of children with attention deficit hyperactivity disorder, the following review addresses strategies for success in using these tools. The following review argues that, as decision support evolves, the clinician should no longer be the sole target of information and alerts. Through the Internet and other technologies, families are increasingly seeking health information and gathering input to guide health decisions. By enlisting clinical decision support systems to deliver evidence-based information to both clinicians and families, help families express their preferences and goals, and connect families to the medical home, clinical decision support may ultimately be most effective in improving outcomes. PMID:21315295

  20. Map-based decision aids for fire support

    NASA Astrophysics Data System (ADS)

    Yarosh, Victor

    1996-06-01

    The Fire Control Division at ARDEC is developing prototype decision aid tools to enable fire support echelons to rapidly respond to requests for fire support. Decision aids on fire support platforms can assist in route planning, site selection, and develop mobility overlays to enable the shooter to rapidly move into position and prepare for the fire mission. The Decision Aid system utilizes an integrated design approach which has each module interacting with the others by sharing data bases and common algorithms to provide recommended courses of action for route planning and generation, position selection, self defense, logistics estimates, situational awareness and fire mission planning aids such as tactical assessment, tactical planning, sustainment, etc. The Decision Aid system will use expert system artificial intelligence which will be developed from knowledge bases utilizing object oriented design. The modules currently reason on Defense Mapping Agency Interim Terrain Data and Digital Terrain Elevation Data and collect mission, intelligence, and sensor data from the digitized battlefield information distribution system to provide the crew or mission planners with intelligent recommendations. The system can provide a trade off analysis of time vs. safety, enable commanders to rapidly respond to fire support request, automatically generate OpOrders, and create overlays which depict mobility corridors, NBC areas, friendly units, overhead concealment, communications, and threat areas. The Decision Aids system can provide a vastly improved mobility, situational awareness, and decision cycle capabilities which can be utilized to increase the tempo of battle.

  1. A fuzzy expert system for diabetes decision support application.

    PubMed

    Lee, Chang-Shing; Wang, Mei-Hui

    2011-02-01

    An increasing number of decision support systems based on domain knowledge are adopted to diagnose medical conditions such as diabetes and heart disease. It is widely pointed that the classical ontologies cannot sufficiently handle imprecise and vague knowledge for some real world applications, but fuzzy ontology can effectively resolve data and knowledge problems with uncertainty. This paper presents a novel fuzzy expert system for diabetes decision support application. A five-layer fuzzy ontology, including a fuzzy knowledge layer, fuzzy group relation layer, fuzzy group domain layer, fuzzy personal relation layer, and fuzzy personal domain layer, is developed in the fuzzy expert system to describe knowledge with uncertainty. By applying the novel fuzzy ontology to the diabetes domain, the structure of the fuzzy diabetes ontology (FDO) is defined to model the diabetes knowledge. Additionally, a semantic decision support agent (SDSA), including a knowledge construction mechanism, fuzzy ontology generating mechanism, and semantic fuzzy decision making mechanism, is also developed. The knowledge construction mechanism constructs the fuzzy concepts and relations based on the structure of the FDO. The instances of the FDO are generated by the fuzzy ontology generating mechanism. Finally, based on the FDO and the fuzzy ontology, the semantic fuzzy decision making mechanism simulates the semantic description of medical staff for diabetes-related application. Importantly, the proposed fuzzy expert system can work effectively for diabetes decision support application.

  2. Promoting Shared Decision Making in Disorders of Sex Development (DSD): Decision Aids and Support Tools.

    PubMed

    Siminoff, L A; Sandberg, D E

    2015-05-01

    Specific complaints and grievances from adult patients with disorders of sex development (DSD), and their advocates center around the lack of information or misinformation they were given about their condition and feeling stigmatized and shamed by the secrecy surrounding their condition and its management. Many also attribute poor sexual function to damaging genital surgery and/or repeated, insensitive genital examinations. These reports suggest the need to reconsider the decision-making process for the treatment of children born with DSD. This paper proposes that shared decision making, an important concept in adult health care, be operationalized for the major decisions commonly encountered in DSD care and facilitated through the utilization of decision aids and support tools. This approach may help patients and their families make informed decisions that are better aligned with their personal values and goals. It may also lead to greater confidence in decision making with greater satisfaction and less regret. A brief review of the past and current approach to DSD decision making is provided, along with a review of shared decision making and decision aids and support tools. A case study explores the need and potential utility of this suggested new approach.

  3. User's Guide for SeedCalc: A Decision-Support System for Integrated Pest Management in Slash Pine Seed Orchards

    Treesearch

    Carl W. Fatzinger; Wayne N. Dixon

    1996-01-01

    SeedCalc, a decision-support system designed for use on personal computers, evaluates the consequences of different pest management strategies in slash pine (Pinus ellliottii Engelm. var. elliottii) seed orchards.

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

    PubMed

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

    2017-09-01

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

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

    NASA Astrophysics Data System (ADS)

    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. Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses

    PubMed Central

    Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

    2016-01-01

    Background Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. Objective The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Methods Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Results Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however

  7. Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses.

    PubMed

    Syrowatka, Ania; Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

    2016-01-26

    Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than

  8. Periodicals collection management using a decision support system

    SciTech Connect

    Compton, M.L.; Moser, E.C.

    1993-12-31

    Sandia National Laboratories is a multiprogram national laboratory established in 1949. The Library currently uses DOBIS for its automated system, including the Periodicals Control function for periodical check-in. DOBIS performs processing and control functions adequately, but could not meet our reporting needs. Therefore the Library`s Periodicals Decision Team decided that they needed another ``system`` for collection management. A Periodicals Decision Support System was created using information downloaded from DOBIS and uploaded into dBASE IV. The Periodical Decision Support System functions as an information-processing system that has aided us in making collection management decisions for periodicals. It certainly allows us to do interactive ad-hoc analysis; although there are no modeling tools currently incorporated in the system. We hope that these modeling tools will come later. We have been gathering information and developing needed reports to achieve this goal.

  9. On conceptualization of a decision support system in health informatics.

    PubMed

    Nykänen, P

    2001-01-01

    A decision support system can be approached from two major disciplinary perspectives, those of information systems science (IS) and artificial intelligence (AI). We present in this study an extended ontology for a decision support system in health informatics, which is founded on experience from related research fields as well as being informed by our case studies. The ontology emphasises the need to cover environmental and contextual variables as an integral part of a decision support systems development methodology. With the addition of these variables, the focus in decision support systems development shifts from a task ontology towards a domain ontology. The results of this study help the system developers to take the system's context into account through the set of defined variables that are linked to the application domain. These variables explicate relevant constructs and present a vocabulary for a decision support system. However, applying the ontology requires a more thorough analysis of the domain and therefore more qualified resources for systems development. This indicates the need to focus more on education and training in health informatics.

  10. OASIS: A GEOGRAPHICAL DECISION SUPPORT SYSTEM FOR GROUND-WATER CONTAMINANT MODELING

    EPA Science Inventory

    Three new software technologies were applied to develop an efficient and easy to use decision support system for ground-water contaminant modeling. Graphical interfaces create a more intuitive and effective form of communication with the computer compared to text-based interfaces...

  11. APPLICATION OF THE US DECISION SUPPORT TOOL FOR MATERIALS AND WASTE MANAGEMENT

    EPA Science Inventory

    EPA¿s National Risk Management Research Laboratory has led the development of a municipal solid waste decision support tool (MSW-DST). The computer software can be used to calculate life-cycle environmental tradeoffs and full costs of different waste management plans or recycling...

  12. APPLICATION OF THE US DECISION SUPPORT TOOL FOR MATERIALS AND WASTE MANAGEMENT

    EPA Science Inventory

    EPA¿s National Risk Management Research Laboratory has led the development of a municipal solid waste decision support tool (MSW-DST). The computer software can be used to calculate life-cycle environmental tradeoffs and full costs of different waste management plans or recycling...

  13. OASIS: A GEOGRAPHICAL DECISION SUPPORT SYSTEM FOR GROUND-WATER CONTAMINANT MODELING

    EPA Science Inventory

    Three new software technologies were applied to develop an efficient and easy to use decision support system for ground-water contaminant modeling. Graphical interfaces create a more intuitive and effective form of communication with the computer compared to text-based interfaces...

  14. ClinicalAccess: a clinical decision support tool.

    PubMed

    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.

  15. Relational Algebra in Spatial Decision Support Systems Ontologies.

    PubMed

    Diomidous, Marianna; Chardalias, Kostis; Koutonias, Panagiotis; Magnita, Adrianna; Andrianopoulos, Charalampos; Zimeras, Stelios; Mechili, Enkeleint Aggelos

    2017-01-01

    Decision Support Systems (DSS) is a powerful tool, for facilitates researchers to choose the correct decision based on their final results. Especially in medical cases where doctors could use these systems, to overcome the problem with the clinical misunderstanding. Based on these systems, queries must be constructed based on the particular questions that doctors must answer. In this work, combination between questions and queries would be presented via relational algebra.

  16. Application of GIS in foreign direct investment decision support system

    NASA Astrophysics Data System (ADS)

    Zhou, Jianlan; Sun, Koumei

    2007-06-01

    It is important to make decisions on how to attract foreign direct investment (FDI) to China and know how the inequality of FDI introduction by locational different provinces. Following background descriptions on China's FDI economic environments and FDI-related policies, this paper demonstrates the uses of geographical information system (GIS) and multi-criterion decision-making (MCDM) framework in solving a spatial multi-objective problem of evaluating and ranking China's provinces for FDI introduction. It implements a foreign direct investment decision support system, which reveals the main determinants of FDI in China and gives some results of regional geographical analysis over spatial data.

  17. Modular analytics management architecture for interoperability and decision support

    NASA Astrophysics Data System (ADS)

    Marotta, Stephen; Metzger, Max; Gorman, Joe; Sliva, Amy

    2016-05-01

    The Dual Node Decision Wheels (DNDW) architecture is a new approach to information fusion and decision support systems. By combining cognitive systems engineering organizational analysis tools, such as decision trees, with the Dual Node Network (DNN) technical architecture for information fusion, the DNDW can align relevant data and information products with an organization's decision-making processes. In this paper, we present the Compositional Inference and Machine Learning Environment (CIMLE), a prototype framework based on the principles of the DNDW architecture. CIMLE provides a flexible environment so heterogeneous data sources, messaging frameworks, and analytic processes can interoperate to provide the specific information required for situation understanding and decision making. It was designed to support the creation of modular, distributed solutions over large monolithic systems. With CIMLE, users can repurpose individual analytics to address evolving decision-making requirements or to adapt to new mission contexts; CIMLE's modular design simplifies integration with new host operating environments. CIMLE's configurable system design enables model developers to build analytical systems that closely align with organizational structures and processes and support the organization's information needs.

  18. Using High Performance Computing to Support Water Resource Planning

    SciTech Connect

    Groves, David G.; Lembert, Robert J.; May, Deborah W.; Leek, James R.; Syme, James

    2015-10-22

    In recent years, decision support modeling has embraced deliberation-withanalysis— an iterative process in which decisionmakers come together with experts to evaluate a complex problem and alternative solutions in a scientifically rigorous and transparent manner. Simulation modeling supports decisionmaking throughout this process; visualizations enable decisionmakers to assess how proposed strategies stand up over time in uncertain conditions. But running these simulation models over standard computers can be slow. This, in turn, can slow the entire decisionmaking process, interrupting valuable interaction between decisionmakers and analytics.

  19. Decision Support Method with AHP Based on Evaluation Grid Method

    NASA Astrophysics Data System (ADS)

    Yumoto, Masaki

    In the Decision Support Method with AHP, there is a tendency for accuracy to fall remarkably when only qualitative criteria estimate alternatives. To solve this problem, it is necessary to define the setting method of criteria clearly. Evaluation Grid Method can construct the recognition structure, which is the element of the target causality model. Through the verification of the hypothesis, the criteria of AHP can be extracted. This paper proposes how to model human's recognition structure with Evaluation Grid Method, and how to support the decision with AHP using the criteria which constructs the model. In practical experiments, the proposal method contributed to creation of objective criteria, and examinees were able to receive the good decision support.

  20. Decision support system for the provision of emergency sanitation.

    PubMed

    Zakaria, F; Garcia, H A; Hooijmans, C M; Brdjanovic, D

    2015-04-15

    Proper provision of sanitation in emergencies is considered a life-saving intervention. Without access to sanitation, refugees at emergency camps are at a high risk of contracting diseases. Even the most knowledgeable relief agencies have experienced difficulties providing sanitation alternatives in such challenging scenarios. This study developed a computer-based decision support system (DSS) to plan a sanitation response in emergencies. The sanitation alternatives suggested by the DSS are based on a sanitation chain concept that considers different steps in the faecal sludge management, from the toilet or latrine to the safe disposal of faecal matters. The DSS first screens individual sanitation technologies using the user's given input. Remaining sanitation options are then built into a feasible sanitation chain. Subsequently, each technology in the chain is evaluated on a scoring system. Different sanitation chains can later be ranked based on the total evaluation scores. The DSS addresses several deficiencies encountered in the provision of sanitation in emergencies including: the application of standard practices and intuition, the omission of site specific conditions, the limited knowledge exhibited by emergency planners, and the provision of sanitation focused exclusively on the collection step (i.e., just the provision of toilets).

  1. Machine Learning Techniques for Decision Support in Intelligent Data Management

    NASA Astrophysics Data System (ADS)

    Lynnes, C.; Miller, J.; Ramapriyan, H.; Isaac, D.; Harberts, R.

    2002-12-01

    NASA's growth in remote sensing data volumes has kept pace with Moore's Law, i.e., doubling every 18 months, with future growth likely from new instruments. Also, advances in instrumental design (e.g., hyperspectral scanners) and science algorithms are enabling more near-real-time applications of the data. The confluence of low-latency requirements with high data volumes and numbers of files poses major challenges for archive data management. In order to make the right data available at the right time, an archive will need to apply knowledge of the data content in its data management decisions. This decision support domain includes aspects such as automatic quality assessment, feature detection to support caching decisions, and content-based metadata to support efficient data selection. In this study, we evaluate a variety of machine learning algorithms for use in several decision support roles in intelligent data management. Machine learning algorithms such as neural networks and clustering have been used for decision support in business and policy domains. These techniques have found some use in remote sensing, e.g., for cloud and land cover classification. Yet most research on remote sensing data rests on science-based algorithms, such as those based on radiative transfer equations. Machine learning for scientific applications faces challenges such as discretization constraints, non-physical basis, and the difficulty of assembling training sets. However, these difficulties may be less significant in the decision support role. For instance, it is often enough to know whether a data attribute exceeds a certain threshold when selecting it for an application, without knowing the exact value. The training data problem can be surmounted by using products output by the science-based algorithms. On the other hand, an advantage of machine learning algorithms for decision support is their speed once they have been trained. Data management decisions must be made while the

  2. Aeromedical evacuation planning using geospatial decision-support.

    PubMed

    Bastian, Nathaniel D; Fulton, Lawrence V

    2014-02-01

    In this study, we proffer an algorithmic, geospatial-based decision-support methodology that assists military decision-makers in determining which aeromedical evacuation (MEDEVAC) assets to launch after receiving an injury location, given knowledge only of terrain, aircraft location, and aircraft capabilities. The objective is for military medical planners to use this decision-support tool (1) to improve real-time situational awareness by visualization of MEDEVAC coverage, showing which areas can be reached within established timelines; (2) to support medical planning by visualizing the impact of changes in the medical footprint to the MEDEVAC coverage; and (3) to support decision-making by providing a time-sorted list of MEDEVAC asset packages to select from, given the location of the patients. This same geospatial-based decision tool can be used for proper emplacement of evacuation assets such that the theater is covered within a truly representative 1-hour response time. We conclude with a discussion of applicability of this tool in medical force structure planning. Reprint & Copyright © 2014 Association of Military Surgeons of the U.S.

  3. Shared decision making in Chile: supportive policies and research initiatives.

    PubMed

    Bravo, Paulina; Cabieses, Báltica; Bustamante, Claudia; Campos, Solange; Stacey, Dawn

    2011-01-01

    WHAT ABOUT POLICY REGARDING SDM? Since 1999, there has been a small but growing interest by academics, the government, and society as a whole in strengthening patients' and professionals' involvement in shared decision making (SDM). Two governmental policy documents that indicate support for SDM are (1) Health Reform in 2003 and (2) Sanitary Objectives 2011-2020, which includes a brief section on client participation and SDM. WHAT ABOUT TOOLS - DECISION SUPPORT FOR PATIENTS? Research by Chilean academics has highlighted the patients' desire to participate in health decisions and effective approaches for enhancing health professionals' skills in interprofessional SDM; however, little has been done to support this need and the work is centralised in only one academic institution. Decision support tools and coaching interventions are limited to patients considering decisions about managing type 2 diabetes. WHAT ABOUT PROFESSIONAL INTEREST AND IMPLEMENTATION? Although there is increasing attention to studying patients' participation and involvement on their healthcare, little has been studied in relation to professionals' interest in SDM. As well, there are significant challenges for implementation of a country-wide SDM policy. WHAT DOES THE FUTURE LOOK LIKE? The future looks promising given the new health policies, local Chilean research projects, and international initiatives. Collaboration between health professionals, academics, and government policy makers, with public involvement needs to be strengthened in order to promote concrete strategies to implement SDM in Chile.

  4. Systems Analysis and Design for Decision Support Systems on Economic Feasibility of Projects

    NASA Astrophysics Data System (ADS)

    Balaji, S. Arun

    2010-11-01

    This paper discuss about need for development of the Decision Support System (DSS) software for economic feasibility of projects in Rwanda, Africa. The various economic theories needed and the corresponding formulae to compute payback period, internal rate of return and benefit cost ratio of projects are clearly given in this paper. This paper is also deals with the systems flow chart to fabricate the system in any higher level computing language. The various input requirements from the projects and the output needed for the decision makers are also included in this paper. The data dictionary used for input and output data structure is also explained.

  5. Computing and Systems Applied in Support of Coordinated ...

    EPA Pesticide Factsheets

    This talk focuses on how Dr. Loughlin is applying Computing and Systems models, tools and methods to more fully understand the linkages among energy systems, environmental quality, and climate change. Dr. Loughlin will highlight recent and ongoing research activities, including: applying sensitivity analysis to assess the impacts of clean energy technologies, conducting scenario analysis to explore the efficacy of environmental regulations under deep uncertainty, and developing decision support systems that allow analysts and decision-makers to examine state-level climate actions. Dr. Loughlin will conclude with a brief discussion of the lessons learned over the first half of his career. Dr. Loughlin has been invited to give the keynote talk at the 1st Annual Computing and Systems Graduate Research Symposium, sponsored by the Department of Civil, Construction and Environmental Engineering at North Carolina State University.

  6. Security Aspects of Computer Supported Collaborative Work

    DTIC Science & Technology

    1993-09-01

    its enabling software. CSCW has been described by some as computer- based tools which can be used to facilitate the exchange and sharing of...information by work groups. Others have described it as a computer- based shared environment that supports two or more users. [Bock92] CSCW is a rapidly...Groupware applications according to the type of work they are designed 6 to accomplish. Based on this first criteria, they recognize four general classes

  7. Robust averaging protects decisions from noise in neural computations.

    PubMed

    Li, Vickie; Herce Castañón, Santiago; Solomon, Joshua A; Vandormael, Hildward; Summerfield, Christopher

    2017-08-01

    An ideal observer will give equivalent weight to sources of information that are equally reliable. However, when averaging visual information, human observers tend to downweight or discount features that are relatively outlying or deviant ('robust averaging'). Why humans adopt an integration policy that discards important decision information remains unknown. Here, observers were asked to judge the average tilt in a circular array of high-contrast gratings, relative to an orientation boundary defined by a central reference grating. Observers showed robust averaging of orientation, but the extent to which they did so was a positive predictor of their overall performance. Using computational simulations, we show that although robust averaging is suboptimal for a perfect integrator, it paradoxically enhances performance in the presence of "late" noise, i.e. which corrupts decisions during integration. In other words, robust decision strategies increase the brain's resilience to noise arising in neural computations during decision-making.

  8. Enabling computer decisions based on EEG input

    NASA Technical Reports Server (NTRS)

    Culpepper, Benjamin J.; Keller, Robert M.

    2003-01-01

    Multilayer neural networks were successfully trained to classify segments of 12-channel electroencephalogram (EEG) data into one of five classes corresponding to five cognitive tasks performed by a subject. Independent component analysis (ICA) was used to segregate obvious artifact EEG components from other sources, and a frequency-band representation was used to represent the sources computed by ICA. Examples of results include an 85% accuracy rate on differentiation between two tasks, using a segment of EEG only 0.05 s long and a 95% accuracy rate using a 0.5-s-long segment.

  9. Enabling computer decisions based on EEG input

    NASA Technical Reports Server (NTRS)

    Culpepper, Benjamin J.; Keller, Robert M.

    2003-01-01

    Multilayer neural networks were successfully trained to classify segments of 12-channel electroencephalogram (EEG) data into one of five classes corresponding to five cognitive tasks performed by a subject. Independent component analysis (ICA) was used to segregate obvious artifact EEG components from other sources, and a frequency-band representation was used to represent the sources computed by ICA. Examples of results include an 85% accuracy rate on differentiation between two tasks, using a segment of EEG only 0.05 s long and a 95% accuracy rate using a 0.5-s-long segment.

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

    NASA Technical Reports Server (NTRS)

    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.

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

    PubMed

    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.

  12. Novel Applications of Intuitionistic Fuzzy Digraphs in Decision Support Systems

    PubMed Central

    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

  13. COMPUTER SUPPORT SYSTEMS FOR ESTIMATING CHEMICAL TOXICITY: PRESENT CAPABILITIES AND FUTURE TRENDS

    EPA Science Inventory

    Computer Support Systems for Estimating Chemical Toxicity: Present Capabilities and Future Trends

    A wide variety of computer-based artificial intelligence (AI) and decision support systems exist currently to aid in the assessment of toxicity for environmental chemicals. T...

  14. COMPUTER SUPPORT SYSTEMS FOR ESTIMATING CHEMICAL TOXICITY: PRESENT CAPABILITIES AND FUTURE TRENDS

    EPA Science Inventory

    Computer Support Systems for Estimating Chemical Toxicity: Present Capabilities and Future Trends

    A wide variety of computer-based artificial intelligence (AI) and decision support systems exist currently to aid in the assessment of toxicity for environmental chemicals. T...

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

    NASA Astrophysics Data System (ADS)

    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

  16. Interprofessional education about patient decision support in specialty care.

    PubMed

    Politi, Mary C; Pieterse, Arwen H; Truant, Tracy; Borkhoff, Cornelia; Jha, Vikram; Kuhl, Laura; Nicolai, Jennifer; Goss, Claudia

    2011-11-01

    Specialty care involves services provided by health professionals who focus on treating diseases affecting one body system. In contrast to primary care - aimed at providing continuous, comprehensive care - specialty care often involves intermittent episodes of care focused around specific medical conditions. In addition, it typically includes multiple providers who have unique areas of expertise that are important in supporting patients' care. Interprofessional care involves multiple professionals from different disciplines collaborating to provide an integrated approach to patient care. For patients to experience continuity of care across interprofessional providers, providers need to communicate and maintain a shared sense of responsibility to their patients. In this article, we describe challenges inherent in providing interprofessional patient decision support in specialty care. We propose ways for providers to engage in interprofessional decision support and discuss promising approaches to teaching an interprofessional decision support to specialty care providers. Additional evaluation and empirical research are required before further recommendations can be made about education for interprofessional decision support in specialty care.

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

    PubMed Central

    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

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

    PubMed

    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.

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

    SciTech Connect

    Johnson, R.

    1995-06-01

    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.

  20. Technology Infusion Challenges from a Decision Support Perspective

    NASA Technical Reports Server (NTRS)

    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.

  1. Collaborative Brain-Computer Interface for Aiding Decision-Making

    PubMed Central

    Poli, Riccardo; Valeriani, Davide; Cinel, Caterina

    2014-01-01

    We look at the possibility of integrating the percepts from multiple non-communicating observers as a means of achieving better joint perception and better group decisions. Our approach involves the combination of a brain-computer interface with human behavioural responses. To test ideas in controlled conditions, we asked observers to perform a simple matching task involving the rapid sequential presentation of pairs of visual patterns and the subsequent decision as whether the two patterns in a pair were the same or different. We recorded the response times of observers as well as a neural feature which predicts incorrect decisions and, thus, indirectly indicates the confidence of the decisions made by the observers. We then built a composite neuro-behavioural feature which optimally combines the two measures. For group decisions, we uses a majority rule and three rules which weigh the decisions of each observer based on response times and our neural and neuro-behavioural features. Results indicate that the integration of behavioural responses and neural features can significantly improve accuracy when compared with the majority rule. An analysis of event-related potentials indicates that substantial differences are present in the proximity of the response for correct and incorrect trials, further corroborating the idea of using hybrids of brain-computer interfaces and traditional strategies for improving decision making. PMID:25072739

  2. Studying Collective Human Decision Making and Creativity with Evolutionary Computation.

    PubMed

    Sayama, Hiroki; Dionne, Shelley D

    2015-01-01

    We report a summary of our interdisciplinary research project "Evolutionary Perspective on Collective Decision Making" that was conducted through close collaboration between computational, organizational, and social scientists at Binghamton University. We redefined collective human decision making and creativity as evolution of ecologies of ideas, where populations of ideas evolve via continual applications of evolutionary operators such as reproduction, recombination, mutation, selection, and migration of ideas, each conducted by participating humans. Based on this evolutionary perspective, we generated hypotheses about collective human decision making, using agent-based computer simulations. The hypotheses were then tested through several experiments with real human subjects. Throughout this project, we utilized evolutionary computation (EC) in non-traditional ways-(1) as a theoretical framework for reinterpreting the dynamics of idea generation and selection, (2) as a computational simulation model of collective human decision-making processes, and (3) as a research tool for collecting high-resolution experimental data on actual collaborative design and decision making from human subjects. We believe our work demonstrates untapped potential of EC for interdisciplinary research involving human and social dynamics.

  3. Computational Biology Support: RECOMB Conference Series (Conference Support)

    SciTech Connect

    Michael Waterman

    2006-06-15

    This funding was support for student and postdoctoral attendance at the Annual Recomb Conference from 2001 to 2005. The RECOMB Conference series was founded in 1997 to provide a scientific forum for theoretical advances in computational biology and their applications in molecular biology and medicine. The conference series aims at attracting research contributions in all areas of computational molecular biology. Typical, but not exclusive, the topics of interest are: Genomics, Molecular sequence analysis, Recognition of genes and regulatory elements, Molecular evolution, Protein structure, Structural genomics, Gene Expression, Gene Networks, Drug Design, Combinatorial libraries, Computational proteomics, and Structural and functional genomics. The origins of the conference came from the mathematical and computational side of the field, and there remains to be a certain focus on computational advances. However, the effective use of computational techniques to biological innovation is also an important aspect of the conference. The conference had a growing number of attendees, topping 300 in recent years and often exceeding 500. The conference program includes between 30 and 40 contributed papers, that are selected by a international program committee with around 30 experts during a rigorous review process rivaling the editorial procedure for top-rate scientific journals. In previous years papers selection has been made from up to 130--200 submissions from well over a dozen countries. 10-page extended abstracts of the contributed papers are collected in a volume published by ACM Press and Springer, and are available at the conference. Full versions of a selection of the papers are published annually in a special issue of the Journal of Computational Biology devoted to the RECOMB Conference. A further point in the program is a lively poster session. From 120-300 posters have been presented each year at RECOMB 2000. One of the highlights of each RECOMB conference is a

  4. Distributed decision support for the 21st century mission space

    NASA Astrophysics Data System (ADS)

    McQuay, William K.

    2002-07-01

    The past decade has produced significant changes in the conduct of military operations: increased humanitarian missions, asymmetric warfare, the reliance on coalitions and allies, stringent rules of engagement, concern about casualties, and the need for sustained air operations. Future mission commanders will need to assimilate a tremendous amount of information, make quick-response decisions, and quantify the effects of those decisions in the face of uncertainty. Integral to this process is creating situational assessment-understanding the mission space, simulation to analyze alternative futures, current capabilities, planning assessments, course-of-action assessments, and a common operational picture-keeping everyone on the same sheet of paper. Decision support tools in a distributed collaborative environment offer the capability of decomposing these complex multitask processes and distributing them over a dynamic set of execution assets. Decision support technologies can semi-automate activities, such as planning an operation, that have a reasonably well-defined process and provide machine-level interfaces to refine the myriad of information that is not currently fused. The marriage of information and simulation technologies provides the mission commander with a collaborative virtual environment for planning and decision support.

  5. ENABLING SMART MANUFACTURING TECHNOLOGIES FOR DECISION-MAKING SUPPORT.

    PubMed

    Helu, Moneer; Libes, Don; Lubell, Joshua; Lyons, Kevin; Morris, K C

    2016-01-01

    Smart manufacturing combines advanced manufacturing capabilities and digital technologies throughout the product lifecycle. These technologies can provide decision-making support to manufacturers through improved monitoring, analysis, modeling, and simulation that generate more and better intelligence about manufacturing systems. However, challenges and barriers have impeded the adoption of smart manufacturing technologies. To begin to address this need, this paper defines requirements for data-driven decision making in manufacturing based on a generalized description of decision making. Using these requirements, we then focus on identifying key barriers that prevent the development and use of data-driven decision making in industry as well as examples of technologies and standards that have the potential to overcome these barriers. The goal of this research is to promote a common understanding among the manufacturing community that can enable standardization efforts and innovation needed to continue adoption and use of smart manufacturing technologies.

  6. ENABLING SMART MANUFACTURING TECHNOLOGIES FOR DECISION-MAKING SUPPORT

    PubMed Central

    Helu, Moneer; Libes, Don; Lubell, Joshua; Lyons, Kevin; Morris, KC

    2017-01-01

    Smart manufacturing combines advanced manufacturing capabilities and digital technologies throughout the product lifecycle. These technologies can provide decision-making support to manufacturers through improved monitoring, analysis, modeling, and simulation that generate more and better intelligence about manufacturing systems. However, challenges and barriers have impeded the adoption of smart manufacturing technologies. To begin to address this need, this paper defines requirements for data-driven decision making in manufacturing based on a generalized description of decision making. Using these requirements, we then focus on identifying key barriers that prevent the development and use of data-driven decision making in industry as well as examples of technologies and standards that have the potential to overcome these barriers. The goal of this research is to promote a common understanding among the manufacturing community that can enable standardization efforts and innovation needed to continue adoption and use of smart manufacturing technologies. PMID:28649678

  7. Making the Right Decisions: Leadership in 1-to-1 Computing in Education

    ERIC Educational Resources Information Center

    Towndrow, Phillip A.; Vallance, Michael

    2013-01-01

    Purpose: The purpose of this paper is to detail the necessity for more informed decision making and leadership in the implementation of 1-to-1 computing in education. Design/methodology/approach: The contexts of high-tech countries of Singapore and Japan are used as case studies to contextualize and support four evidence-based recommendations for…

  8. Making the Right Decisions: Leadership in 1-to-1 Computing in Education

    ERIC Educational Resources Information Center

    Towndrow, Phillip A.; Vallance, Michael

    2013-01-01

    Purpose: The purpose of this paper is to detail the necessity for more informed decision making and leadership in the implementation of 1-to-1 computing in education. Design/methodology/approach: The contexts of high-tech countries of Singapore and Japan are used as case studies to contextualize and support four evidence-based recommendations for…

  9. Advances in Computer-Supported Learning

    ERIC Educational Resources Information Center

    Neto, Francisco; Brasileiro, Francisco

    2007-01-01

    The Internet and growth of computer networks have eliminated geographic barriers, creating an environment where education can be brought to a student no matter where that student may be. The success of distance learning programs and the availability of many Web-supported applications and multimedia resources have increased the effectiveness of…

  10. Gender Issues in Computer-Supported Learning.

    ERIC Educational Resources Information Center

    Gunn, Cathy; French, Sheila; McLeod, Hamish; McSporran, Mae; Conole, Grainne

    2002-01-01

    Discusses gender-related differences in performance and interaction styles in computer-supported learning (CSL) environments. Presents a summary of gender-related issues identified by international research and academic practice together with opinions expressed in an online discussion forum, and offers suggestions to increase the flexibility of…

  11. Summary Street: Interactive Computer Support for Writing

    ERIC Educational Resources Information Center

    Wade-Stein, David; Kintsch, Eileen

    2004-01-01

    Summary Street is educational software based on latent semantic analysis (LSA), a computer method for representing the content of texts. The classroom trial described here demonstrates the power of LSA to support an educational goal by providing automatic feedback on the content of students' summaries. Summary Street provides this feedback in an…

  12. Advances in Computer-Supported Learning

    ERIC Educational Resources Information Center

    Neto, Francisco; Brasileiro, Francisco

    2007-01-01

    The Internet and growth of computer networks have eliminated geographic barriers, creating an environment where education can be brought to a student no matter where that student may be. The success of distance learning programs and the availability of many Web-supported applications and multimedia resources have increased the effectiveness of…

  13. Assessment of (Computer-Supported) Collaborative Learning

    ERIC Educational Resources Information Center

    Strijbos, J. -W.

    2011-01-01

    Within the (Computer-Supported) Collaborative Learning (CS)CL research community, there has been an extensive dialogue on theories and perspectives on learning from collaboration, approaches to scaffold (script) the collaborative process, and most recently research methodology. In contrast, the issue of assessment of collaborative learning has…

  14. Computer-Supported Co-operative Learning.

    ERIC Educational Resources Information Center

    Florea, Adina Magda

    1998-01-01

    Discusses the impact of computer-supported cooperative work tools in the creation of educational environments and the facilities such tools bring to teaching methods, and examines the relationship between new techniques and the learner-centered, active learning approach in higher education. The importance of collaborative learning in this context…

  15. Computer-Supported Co-operative Learning.

    ERIC Educational Resources Information Center

    Florea, Adina Magda

    1998-01-01

    Discusses the impact of computer-supported cooperative work tools in the creation of educational environments and the facilities such tools bring to teaching methods, and examines the relationship between new techniques and the learner-centered, active learning approach in higher education. The importance of collaborative learning in this context…

  16. Specifying Computer-Supported Collaboration Scripts

    ERIC Educational Resources Information Center

    Kobbe, Lars; Weinberger, Armin; Dillenbourg, Pierre; Harrer, Andreas; Hamalainen, Raija; Hakkinen, Paivi; Fischer, Frank

    2007-01-01

    Collaboration scripts facilitate social and cognitive processes of collaborative learning by shaping the way learners interact with each other. Computer-supported collaboration scripts generally suffer from the problem of being restrained to a specific learning platform. A standardization of collaboration scripts first requires a specification of…

  17. Computer-Supported Intentional Learning Environments.

    ERIC Educational Resources Information Center

    Scardamalia, Marlene; And Others

    1989-01-01

    Describes the design of the Computer-Supported Intentional Learning Environment (CSILE), a database that allows the storage and retrieval of information in several media, e.g., text and drawings. Research on cognitive abilities and learning strategies is reviewed, learner control is discussed, and the implementation of CSILE in grades five and six…

  18. Workflow-driven clinical decision support for personalized oncology.

    PubMed

    Bucur, Anca; van Leeuwen, Jasper; Christodoulou, Nikolaos; Sigdel, Kamana; Argyri, Katerina; Koumakis, Lefteris; Graf, Norbert; Stamatakos, Georgios

    2016-07-21

    The adoption in oncology of Clinical Decision Support (CDS) may help clinical users to efficiently deal with the high complexity of the domain, lead to improved patient outcomes, and reduce the current knowledge gap between clinical research and practice. While significant effort has been invested in the implementation of CDS, the uptake in the clinic has been limited. The barriers to adoption have been extensively discussed in the literature. In oncology, current CDS solutions are not able to support the complex decisions required for stratification and personalized treatment of patients and to keep up with the high rate of change in therapeutic options and knowledge. To address these challenges, we propose a framework enabling efficient implementation of meaningful CDS that incorporates a large variety of clinical knowledge models to bring to the clinic comprehensive solutions leveraging the latest domain knowledge. We use both literature-based models and models built within the p-medicine project using the rich datasets from clinical trials and care provided by the clinical partners. The framework is open to the biomedical community, enabling reuse of deployed models by third-party CDS implementations and supporting collaboration among modelers, CDS implementers, biomedical researchers and clinicians. To increase adoption and cope with the complexity of patient management in oncology, we also support and leverage the clinical processes adhered to by healthcare organizations. We design an architecture that extends the CDS framework with workflow functionality. The clinical models are embedded in the workflow models and executed at the right time, when and where the recommendations are needed in the clinical process. In this paper we present our CDS framework developed in p-medicine and the CDS implementation leveraging the framework. To support complex decisions, the framework relies on clinical models that encapsulate relevant clinical knowledge. Next to

  19. Web-LCCA: decision support system for military display acquisition

    NASA Astrophysics Data System (ADS)

    Binder, Michael L.; Calvo, Alberto B.; Gibson, Gregory J.

    2000-08-01

    This paper describes a Decision Support System for military display acquisition being developed under U.S. Display Consortium (USDC) sponsorship. The core of the system is a standard Life-Cycle Cost model. The system will use World Wide Web technology to make it widely accessible to Industry and Government Program Offices for use in the Display Acquisition Decision Process. Web-LCCA (Life-Cycle Cost Analyzer), a derivative of TASC's LCCATM, has been designed to aid in the evaluation of different Display System acquisition options. The target users of Web-LCCA are display vendors (Industry) and buyers (Government Program Offices). Web-LCCA will be USDC's standard tool for supporting cost tradeoffs and acquisition decisions among current operational displays and new flat panel display products.

  20. Self-Evaluation of Decision-Making: A General Bayesian Framework for Metacognitive Computation

    PubMed Central

    2017-01-01

    People are often aware of their mistakes, and report levels of confidence in their choices that correlate with objective performance. These metacognitive assessments of decision quality are important for the guidance of behavior, particularly when external feedback is absent or sporadic. However, a computational framework that accounts for both confidence and error detection is lacking. In addition, accounts of dissociations between performance and metacognition have often relied on ad hoc assumptions, precluding a unified account of intact and impaired self-evaluation. Here we present a general Bayesian framework in which self-evaluation is cast as a “second-order” inference on a coupled but distinct decision system, computationally equivalent to inferring the performance of another actor. Second-order computation may ensue whenever there is a separation between internal states supporting decisions and confidence estimates over space and/or time. We contrast second-order computation against simpler first-order models in which the same internal state supports both decisions and confidence estimates. Through simulations we show that second-order computation provides a unified account of different types of self-evaluation often considered in separate literatures, such as confidence and error detection, and generates novel predictions about the contribution of one’s own actions to metacognitive judgments. In addition, the model provides insight into why subjects’ metacognition may sometimes be better or worse than task performance. We suggest that second-order computation may underpin self-evaluative judgments across a range of domains. PMID:28004960

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

    SciTech Connect

    Hirsch, Gary B.; Homer, Jack; 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.

  2. Clinical decision support: the power behind the electronic health record.

    PubMed

    Glaser, John

    2008-07-01

    There are six strategic objectives for promoting adoption of clinical decision support: Use a standardized format for representing clinical data and CDS interventions. Ensure appropriate access to clinical data and CDS interventions. Provide support and incentives for providers to use CDS. Disseminate information about best practices for system design, CDS delivery, and CDS implementation. Continue national demonstrations and evaluation of CDS use. Leverage data interchange between EHRs.

  3. A roadmap for national action on clinical decision support.

    PubMed

    Osheroff, Jerome A; Teich, Jonathan M; Middleton, Blackford; Steen, Elaine B; Wright, Adam; Detmer, Don E

    2007-01-01

    This document comprises an AMIA Board of Directors approved White Paper that presents a roadmap for national action on clinical decision support. It is published in JAMIA for archival and dissemination purposes. The full text of this material has been previously published on the AMIA Web site (www.amia.org/inside/initiatives/cds). AMIA is the copyright holder.

  4. Integrated decision support tools for Puget Sound salmon recovery planning

    EPA Science Inventory

    We developed a set of tools to provide decision support for community-based salmon recovery planning in Salish Sea watersheds. Here we describe how these tools are being integrated and applied in collaboration with Puget Sound tribes and community stakeholders to address restora...

  5. Knowledge Flow Mesh and Its Dynamics: A Decision Support Environment

    DTIC Science & Technology

    2008-06-01

    paper was the ability of the United States military to achieve dominance through information superiority. The use of intelligent sensors and... Intelligence Agency, National Security Agency, Defense Intelligence Agency, and individual Service intelligence agencies). In fact, these edge entities would... intelligence , design, choice, and implementation. 6. Support variety of decision processes and styles. 7. DSS should be adaptable and flexible. 8. DSS

  6. A knowledge-based decision support system for payload scheduling

    NASA Technical Reports Server (NTRS)

    Tyagi, Rajesh; Tseng, Fan T.

    1988-01-01

    This paper presents the development of a prototype Knowledge-based Decision Support System, currently under development, for scheduling payloads/experiments on space station missions. The DSS is being built on Symbolics, a Lisp machine, using KEE, a commercial knowledge engineering tool.

  7. Implementation problems of decision support system for nosocomial infection.

    PubMed

    Rems, M; Bohanec, M; Urh, B; Kramar, Z

    1997-01-01

    Decision support system for nosocomial infection therapy Ptah can reduce antibiotic misuse with data about bacteria resistance and antibiotic ineffectiveness. Resistance vectors in time series show epidemiological problems with resistant bacterias, named house-bacteria. Most important implementation factors are integrated hospital information system and doctors, nurses and managers interested in problems of nosocomial infection.

  8. DECISION SUPPORT FRAMEWORK FOR PLACEMENT OF BMPS IN URBAN WATERSHEDS

    EPA Science Inventory

    To assist stormwater management professionals in planning for best management practices (BMPs) implementation, the U.S. Environmental Protection Agency (USEPA) initiated a research in 2003 to develop a decision support system for placement of BMPs at strategic locations in urban ...

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

    ERIC Educational Resources Information Center

    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. A Roadmap for National Action on Clinical Decision Support

    PubMed Central

    Osheroff, Jerome A.; Teich, Jonathan M.; Middleton, Blackford; Steen, Elaine B.; Wright, Adam; Detmer, Don E.

    2007-01-01

    This document comprises an AMIA Board of Directors approved White Paper that presents a roadmap for national action on clinical decision support. It is published in JAMIA for archival and dissemination purposes. The full text of this material has been previously published on the AMIA Web site (www.amia.org/inside/initiatives/cds). AMIA is the copyright holder. PMID:17213487

  11. A Decision Support System for Predicting Students' Performance

    ERIC Educational Resources Information Center

    Livieris, Ioannis E.; Mikropoulos, Tassos A.; Pintelas, Panagiotis

    2016-01-01

    Educational data mining is an emerging research field concerned with developing methods for exploring the unique types of data that come from educational context. These data allow the educational stakeholders to discover new, interesting and valuable knowledge about students. In this paper, we present a new user-friendly decision support tool for…

  12. Decision Support System for Disability Assessment and Intervention.

    ERIC Educational Resources Information Center

    Dowler, Denetta L.; And Others

    1991-01-01

    Constructed decision support system to aid referral of good candidates for rehabilitation from Social Security Administration to rehabilitation counselors. Three layers of system were gross screening based on policy guidelines, training materials, and interviews with experts; physical and mental functional capacity items derived from policy…

  13. Integrated decision support tools for Puget Sound salmon recovery planning

    EPA Science Inventory

    We developed a set of tools to provide decision support for community-based salmon recovery planning in Salish Sea watersheds. Here we describe how these tools are being integrated and applied in collaboration with Puget Sound tribes and community stakeholders to address restora...

  14. A Web-Based Decision Support Tool for Academic Advising

    ERIC Educational Resources Information Center

    Feghali, Tony; Zbib, Imad; Hallal, Sophia

    2011-01-01

    Student advising is an important and time-consuming effort in academic life. This paper attempts to solve a technology-based "last mile" problem by developing and evaluating a web-based decision support tool (the Online Advisor) that helps advisors and students make better use of an already present university student information system. Two…

  15. DECISION SUPPORT FRAMEWORK FOR PLACEMENT OF BMPS IN URBAN WATERSHEDS

    EPA Science Inventory

    To assist stormwater management professionals in planning for best management practices (BMPs) implementation, the U.S. Environmental Protection Agency (USEPA) initiated a research in 2003 to develop a decision support system for placement of BMPs at strategic locations in urban ...

  16. A Decision Support System for Solving Multiple Criteria Optimization Problems

    ERIC Educational Resources Information Center

    Filatovas, Ernestas; Kurasova, Olga

    2011-01-01

    In this paper, multiple criteria optimization has been investigated. A new decision support system (DSS) has been developed for interactive solving of multiple criteria optimization problems (MOPs). The weighted-sum (WS) approach is implemented to solve the MOPs. The MOPs are solved by selecting different weight coefficient values for the criteria…

  17. Decision support for sustainable forestry: enhancing the basic rational model.

    Treesearch

    H.R. Ekbia; K.M. Reynolds

    2007-01-01

    Decision-support systems (DSS) have been extensively used in the management of natural resources for nearly two decades. However, practical difficulties with the application of DSS in real-world situations have become increasingly apparent. Complexities of decisionmaking, encountered in the context of ecosystem management, are equally present in sustainable forestry....

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

    ERIC Educational Resources Information Center

    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…

  19. A Decision Support Tool for Determining Army Enlistment Initiatives

    DTIC Science & Technology

    2001-09-01

    the Personnel Command (PERSCOM) meet to form the Enlisted Incentive Review Board ( EIRB ). The task of the EIRB is to determine the enlistment...it evaluate the effects of new incentives. The EIRB requires a quantitative decision support tool that will assist the members in doing the following

  20. Using Clinical Decision Support Software in Health Insurance Company

    NASA Astrophysics Data System (ADS)

    Konovalov, R.; Kumlander, Deniss

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

  1. The Contribution of a Decision Support System to Complex Educational Decisions

    ERIC Educational Resources Information Center

    Klein, Joseph

    2005-01-01

    This study examined the effect of complexity of problems on the degree of disparity between intuitive (PDM) and computer-assisted (DSS) decision-making. 840 teachers chose intuitive solutions for educational dilemmas, and recorded the relative importance of the guiding criteria. Utilizing this information, DSS calculated preferred solutions. Of…

  2. Tools to support evidence-informed public health decision making

    PubMed Central

    2014-01-01

    Background Public health professionals are increasingly expected to engage in evidence-informed decision making to inform practice and policy decisions. Evidence-informed decision making involves the use of research evidence along with expertise, existing public health resources, knowledge about community health issues, the local context and community, and the political climate. The National Collaborating Centre for Methods and Tools has identified a seven step process for evidence-informed decision making. Tools have been developed to support public health professionals as they work through each of these steps. This paper provides an overview of tools used in three Canadian public health departments involved in a study to develop capacity for evidence-informed decision making. Methods As part of a knowledge translation and exchange intervention, a Knowledge Broker worked with public health professionals to identify and apply tools for use with each of the steps of evidence-informed decision making. The Knowledge Broker maintained a reflective journal and interviews were conducted with a purposive sample of decision makers and public health professionals. This paper presents qualitative analysis of the perceived usefulness and usability of the tools. Results Tools were used in the health departments to assist in: question identification and clarification; searching for the best available research evidence; assessing the research evidence for quality through critical appraisal; deciphering the ‘actionable message(s)’ from the research evidence; tailoring messages to the local context to ensure their relevance and suitability; deciding whether and planning how to implement research evidence in the local context; and evaluating the effectiveness of implementation efforts. Decision makers provided descriptions of how the tools were used within the health departments and made suggestions for improvement. Overall, the tools were perceived as valuable for advancing

  3. Tools to support evidence-informed public health decision making.

    PubMed

    Yost, Jennifer; Dobbins, Maureen; Traynor, Robyn; DeCorby, Kara; Workentine, Stephanie; Greco, Lori

    2014-07-18

    Public health professionals are increasingly expected to engage in evidence-informed decision making to inform practice and policy decisions. Evidence-informed decision making involves the use of research evidence along with expertise, existing public health resources, knowledge about community health issues, the local context and community, and the political climate. The National Collaborating Centre for Methods and Tools has identified a seven step process for evidence-informed decision making. Tools have been developed to support public health professionals as they work through each of these steps. This paper provides an overview of tools used in three Canadian public health departments involved in a study to develop capacity for evidence-informed decision making. As part of a knowledge translation and exchange intervention, a Knowledge Broker worked with public health professionals to identify and apply tools for use with each of the steps of evidence-informed decision making. The Knowledge Broker maintained a reflective journal and interviews were conducted with a purposive sample of decision makers and public health professionals. This paper presents qualitative analysis of the perceived usefulness and usability of the tools. Tools were used in the health departments to assist in: question identification and clarification; searching for the best available research evidence; assessing the research evidence for quality through critical appraisal; deciphering the 'actionable message(s)' from the research evidence; tailoring messages to the local context to ensure their relevance and suitability; deciding whether and planning how to implement research evidence in the local context; and evaluating the effectiveness of implementation efforts. Decision makers provided descriptions of how the tools were used within the health departments and made suggestions for improvement. Overall, the tools were perceived as valuable for advancing and sustaining evidence

  4. Workflow Technology to Enrich a Computerized Clinical Chart with Decision Support Facilities

    PubMed Central

    Panzarasa, Silvia; Quaglini, Silvana; Cavallini, Anna; Micieli, Giuseppe; Pernice, Corrado; Pessina, Mauro; Stefanelli, Mario

    2006-01-01

    Literature results and personal experience show that intrusive modalities of presenting suggestions of computerized clinical practice guidelines are detrimental to the routine use of an information system. This paper describes a solution for smoothly integrating a guideline-based decision support system into an existing computerized clinical chart for patients admitted to a Stroke Unit. Since many years, the healthcare personnel were using a commercial product for the ordinary patients’ data management, and they were satisfied with it. Thus, the decision support system has been integrated keeping attention to minimize changes and preserve existing human-computer interaction. Our decision support system is based on workflow technology. The paper illustrates the middleware layer developed to allow communication between the workflow management system and the clinical chart. At the same time, the consequent modification of the graphical users' interface is illustrated. PMID:17238415

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

    PubMed

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

    2013-09-01

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

  6. A Decision Support System for Concrete Bridge Maintenance

    NASA Astrophysics Data System (ADS)

    Rashidi, Maria; Lemass, Brett; Gibson, Peter

    2010-05-01

    The maintenance of bridges as a key element in transportation infrastructure has become a major concern for asset managers and society due to increasing traffic volumes, deterioration of existing bridges and well-publicised bridge failures. A pivotal responsibility for asset managers in charge of bridge remediation is to identify the risks and assess the consequences of remediation programs to ensure that the decisions are transparent and lead to the lowest predicted losses in recognized constraint areas. The ranking of bridge remediation treatments can be quantitatively assessed using a weighted constraint approach to structure the otherwise ill-structured phases of problem definition, conceptualization and embodiment [1]. This Decision Support System helps asset managers in making the best decision with regards to financial limitations and other dominant constraints imposed upon the problem at hand. The risk management framework in this paper deals with the development of a quantitative intelligent decision support system for bridge maintenance which has the ability to provide a source for consistent decisions through selecting appropriate remediation treatments based upon cost, service life, product durability/sustainability, client preferences, legal and environmental constraints. Model verification and validation through industry case studies is ongoing.

  7. A decision support system to determine optimal ventilator settings.

    PubMed

    Akbulut, Fatma Patlar; Akkur, Erkan; Akan, Aydin; Yarman, B Siddik

    2014-01-10

    Choosing the correct ventilator settings for the treatment of patients with respiratory tract disease is quite an important issue. Since the task of specifying the parameters of ventilation equipment is entirely carried out by a physician, physician's knowledge and experience in the selection of these settings has a direct effect on the accuracy of his/her decisions. Nowadays, decision support systems have been used for these kinds of operations to eliminate errors. Our goal is to minimize errors in ventilation therapy and prevent deaths caused by incorrect configuration of ventilation devices. The proposed system is designed to assist less experienced physicians working in the facilities without having lung mechanics like cottage hospitals. This article describes a decision support system proposing the ventilator settings required to be applied in the treatment according to the patients' physiological information. The proposed model has been designed to minimize the possibility of making a mistake and to encourage more efficient use of time in support of the decision making process while the physicians make critical decisions about the patient. Artificial Neural Network (ANN) is implemented in order to calculate frequency, tidal volume, FiO2 outputs, and this classification model has been used for estimation of pressure support / volume support outputs. For the obtainment of the highest performance in both models, different configurations have been tried. Various tests have been realized for training methods, and a number of hidden layers mostly affect factors regarding the performance of ANNs. The physiological information of 158 respiratory patients over the age of 60 and were treated in three different hospitals between the years 2010 and 2012 has been used in the training and testing of the system. The diagnosed disease, core body temperature, pulse, arterial systolic pressure, diastolic blood pressure, PEEP, PSO2, pH, pCO2, bicarbonate data as well as the

  8. Forecasting for Computer Aided Career Decisions: Prospects and Procedures.

    ERIC Educational Resources Information Center

    Durstine, Richard M.

    This paper is the second step in the preparation of forecasts of occupational and industrial information which will meet the needs of the Information System for Vocational Decisions (ISVD). The author discusses the computation routines which need to be developed, tested and operationalized toward the goal of combining occupational and industrial…

  9. Computer-Assisted Community Planning and Decision Making.

    ERIC Educational Resources Information Center

    College of the Atlantic, Bar Harbor, ME.

    The College of the Atlantic (COA) developed a broad-based, interdisciplinary curriculum in ecological policy and community planning and decision-making that incorporates two primary computer-based tools: ARC/INFO Geographic Information System (GIS) and STELLA, a systems-dynamics modeling tool. Students learn how to use and apply these tools…

  10. Computer Simulation of Small Group Decisions: Model Three.

    ERIC Educational Resources Information Center

    Hare, A.P.; Scheiblechner, Hartmann

    In a test of three computer models to simulate group decisions, data were used from 31 American and Austrian groups on a total of 307 trials. The task for each group was to predict a series of answers of an unknown subject on a value-orientation questionnaire, after being given a sample of his typical responses. The first model, used the mean of…

  11. Pharmacists' awareness of clinical decision support in pharmacy information systems: an exploratory evaluation.

    PubMed

    Hines, Lisa E; Saverno, Kim R; Warholak, Terri L; Taylor, Ann; Grizzle, Amy J; Murphy, John E; Malone, Daniel C

    2011-12-01

    Clinical decision support (CDS), such as drug-drug interaction (DDI) and drug-allergy checking, has been used in pharmacy information systems for several decades; however, there has been limited research on CDS use by practicing pharmacists. The purpose of this study was to document pharmacists' awareness of DDI and other medication-related CDS features available within pharmacy information systems. Researchers conducted on-site interviews with pharmacists throughout the state of Arizona from December 2008 to November 2009 regarding their pharmacy information systems features. Pharmacists were asked to provide information about DDI and other medication-related decision support features of the pharmacy software at their practice site. Descriptive statistics were used to summarize interview responses. Sixty-one pharmacists from a variety of practice settings completed the interview. All respondents indicated that their pharmacy system provided drug-allergy and DDI alerts. Approximately 60% of the pharmacists reported that their DDI decision support systems included recommendations for managing drug interactions. Two-thirds of respondents reported that their pharmacy's computer system permitted the addition of medications from other pharmacies and/or over-the-counter products to a patient's profile. Approximately 40% of the pharmacists reported that some drugs entered into the pharmacy computer system were not included in (or linked to) the electronic DDI checking. Most pharmacists indicated the presence of other medication-related decision support features, such as drug-disease (78%), drug-age precautions (67%), and inappropriate dosage alerts (79%). However, fewer pharmacists reported more advanced functionality, such as laboratory recommendations (34%) and pediatric dosing (39%). Overall, pharmacists' awareness regarding the many decision support functionalities of their systems was limited. Based on the study findings, it appears that there are a number of

  12. Decision support system for health care resources allocation

    PubMed Central

    Sebaa, Abderrazak; Nouicer, Amina; Tari, AbdelKamel; Tarik, Ramtani; Abdellah, Ouhab

    2017-01-01

    Background A study about healthcare resources can improve decisions regarding the allotment and mobilization of medical resources and to better guide future investment in the health sector. Aim The aim of this work was to design and implement a decision support system to improve medical resources allocation of Bejaia region. Methods To achieve the retrospective cohort study, we integrated existing clinical databases from different Bejaia department health sector institutions (an Algerian department) to collect information about patients from January 2015 through December 2015. Data integration was performed in a data warehouse using the multi-dimensional model and OLAP cube. During implementation, we used Microsoft SQL server 2012 and Microsoft Excel 2010. Results A medical decision support platform was introduced, and was implemented during the planning stages allowing the management of different medical orientations, it provides better apportionment and allotment of medical resources, and ensures that the allocation of health care resources has optimal effects on improving health. Conclusion In this study, we designed and implemented a decision support system which would improve health care in Bejaia department to especially assist in the selection of the optimum location of health center and hospital, the specialty of the health center, the medical equipment and the medical staff. PMID:28848645

  13. Decision support system for health care resources allocation.

    PubMed

    Sebaa, Abderrazak; Nouicer, Amina; Tari, AbdelKamel; Tarik, Ramtani; Abdellah, Ouhab

    2017-06-01

    A study about healthcare resources can improve decisions regarding the allotment and mobilization of medical resources and to better guide future investment in the health sector. The aim of this work was to design and implement a decision support system to improve medical resources allocation of Bejaia region. To achieve the retrospective cohort study, we integrated existing clinical databases from different Bejaia department health sector institutions (an Algerian department) to collect information about patients from January 2015 through December 2015. Data integration was performed in a data warehouse using the multi-dimensional model and OLAP cube. During implementation, we used Microsoft SQL server 2012 and Microsoft Excel 2010. A medical decision support platform was introduced, and was implemented during the planning stages allowing the management of different medical orientations, it provides better apportionment and allotment of medical resources, and ensures that the allocation of health care resources has optimal effects on improving health. In this study, we designed and implemented a decision support system which would improve health care in Bejaia department to especially assist in the selection of the optimum location of health center and hospital, the specialty of the health center, the medical equipment and the medical staff.

  14. Computer-supported access to engineering information

    SciTech Connect

    Schwarz, H.; Glock, H.J.; Mueller, F.

    1985-01-01

    A computer-based documentation system is described that provides access to the information stored in written documents and drawings. This system contains the syntax of a documentation language, several computer programs, and special methods. The latter enable users to formulate the semantics of their own documentation language, to employ that language when describing the information content of documents and formulating queries, and to organize the storage and retrieval procedure. The system is explained by its application to nuclear power plant documentation. Finally, a layer model of an integrated software system is presented that is suited to support engineers work continuously. 7 references.

  15. Semantic Interoperability in Clinical Decision Support Systems: A Systematic Review.

    PubMed

    Marco-Ruiz, Luis; Bellika, Johan Gustav

    2015-01-01

    The interoperability of Clinical Decision Support (CDS) systems with other health information systems has become one of the main limitations to their broad adoption. Semantic interoperability must be granted in order to share CDS modules across different health information systems. Currently, numerous standards for different purposes are available to enable the interoperability of CDS systems. We performed a literature review to identify and provide an overview of the available standards that enable CDS interoperability in the areas of clinical information, decision logic, terminology, and web service interfaces.

  16. Virtual medical record implementation for enhancing clinical decision support.

    PubMed

    Gomoi, Valentin-Sergiu; Dragu, Daniel; Stoicu-Tivadar, Vasile

    2012-01-01

    Development of clinical decision support systems (CDS) is a process which highly depends on the local databases, this resulting in low interoperability. To increase the interoperability of CDS a standard representation of clinical information is needed. The paper suggests a CDS architecture which integrates several HL7 standards and the new vMR (virtual Medical Record). The clinical information for the CDS systems (the vMR) is represented with Topic Maps technology. Beside the implementation of the vMR, the architecture integrates: a Data Manager, an interface, a decision making system (based on Egadss), a retrieving data module. Conclusions are issued.

  17. Toward image analysis and decision support for ultrasound technology.

    PubMed

    Crofts, Gillian; Padman, Rema; Maharaja, Nisha

    2013-01-01

    Ultrasound is a low cost and efficient method of detecting diseases and abnormalities in the body. Yet there is a lack of precision and reliability associated with the technology, partly due to the operator dependent nature of ultrasound scanning. When scanning is performed to an agreed protocol, ultrasound has been shown to be highly reliable. This research aims to minimize these limitations that arise during ultrasound training, scanning and reporting by developing and evaluating an image analysis and decision support system that can aid the decision making process. We hypothesize that this intervention will likely increase the role of ultrasound in diagnosis when compared with other imaging technologies, particularly in low resource settings.

  18. CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

    SciTech Connect

    Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.; Strasburg, Jana D.

    2011-11-15

    We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

  19. A decision support system for managing forest fire casualties.

    PubMed

    Bonazountas, Marc; Kallidromitou, Despina; Kassomenos, Pavlos; Passas, Nikos

    2007-09-01

    Southern Europe is exposed to anthropogenic and natural forest fires. These result in loss of lives, goods and infrastructure, but also deteriorate the natural environment and degrade ecosystems. The early detection and combating of such catastrophes requires the use of a decision support system (DSS) for emergency management. The current literature reports on a series of efforts aimed to deliver DSSs for the management of the forest fires by utilising technologies like remote sensing and geographical information systems (GIS), yet no integrated system exists. This manuscript presents the results of scientific research aiming to the development of a DSS for managing forest fires. The system provides a series of software tools for the assessment of the propagation and combating of forest fires based on Arc/Info, ArcView, Arc Spatial Analyst, Arc Avenue, and Visual C++ technologies. The system integrates GIS technologies under the same data environment and utilises a common user interface to produce an integrated computer system based on semi-automatic satellite image processing (fuel maps), socio-economic risk modelling and probabilistic models that would serve as a useful tool for forest fire prevention, planning and management. Its performance has been demonstrated via real time up-to-date accurate information on the position and evolution of the fire. The system can assist emergency assessment, management and combating of the incident. A site demonstration and validation has been accomplished for the island of Evoia, Greece, an area particularly vulnerable to forest fires due to its ecological characteristics and prevailing wind patterns.

  20. Applying the Wildland Fire Decision Support System (WFDSS) to support risk-informed decision making: The Gold Pan Fire, Bitterroot National Forest, Montana, USA

    Treesearch

    Erin K. Noonan-Wright; Tonja S. Opperman

    2015-01-01

    In response to federal wildfire policy changes, risk-informed decision-making by way of improved decision support, is increasingly becoming a component of managing wildfires. As fire incidents escalate in size and complexity, the Wildland Fire Decision Support System (WFDSS) provides support with different analytical tools as fire conditions change. We demonstrate the...

  1. Supporting end of life decision making: Case studies of relational closeness in supported decision making for people with severe or profound intellectual disability.

    PubMed

    Watson, Joanne; Wilson, Erin; Hagiliassis, Nick

    2017-08-16

    The United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) promotes the use of supported decision making in lieu of substitute decision making. To date, there has been a lack of focus on supported decision making for people with severe or profound intellectual disability, including for end of life decisions. Five people with severe or profound intellectual disability's experiences of supported decision making were examined. This article is particularly focused on one participant's experiences at the end of his life. All five case studies identified that supporters were most effective in providing decision-making support for participants when they were relationally close to the person and had knowledge of the person's life story, particularly in relation to events that demonstrated preference. Findings from this study provide new understandings of supported decision making for people with severe or profound intellectual disability and have particular relevance for supporting decision making at the end of life. © 2017 John Wiley & Sons Ltd.

  2. Insurance Contract Analysis for Company Decision Support in Acquisition Management

    NASA Astrophysics Data System (ADS)

    Chernovita, H. P.; Manongga, D.; Iriani, A.

    2017-01-01

    One of company activities to retain their business is marketing the products which include in acquisition management to get new customers. Insurance contract analysis using ID3 to produce decision tree and rules to be decision support for the insurance company. The decision tree shows 13 rules that lead to contract termination claim. This could be a guide for the insurance company in acquisition management to prevent contract binding with these contract condition because it has a big chance for the customer to terminate their insurance contract before its expired date. As the result, there are several strong points that could be the determinant of contract termination such as: 1) customer age whether too young or too old, 2) long insurance period (above 10 years), 3) big insurance amount, 4) big amount of premium charges, and 5) payment method.

  3. Middle Mississippi River decision support system: user's manual

    USGS Publications Warehouse

    Rohweder, Jason J.; Zigler, Steven J.; Fox, Timothy J.; Hulse, Steven N.

    2005-01-01

    This user's manual describes the Middle Mississippi River Decision Support System (MMRDSS) and gives detailed examples on its use. The MMRDSS provides a framework to assist decision makers regarding natural resource issues in the Middle Mississippi River floodplain. The MMRDSS is designed to provide users with a spatially explicit tool for tasks, such as inventorying existing knowledge, developing models to investigate the potential effects of management decisions, generating hypotheses to advance scientific understanding, and developing scientifically defensible studies and monitoring. The MMRDSS also includes advanced tools to assist users in evaluating differences in complexity, connectivity, and structure of aquatic habitats among river reaches. The Environmental Systems Research Institute ArcView 3.x platform was used to create and package the data and tools of the MMRDSS.

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

    ERIC Educational Resources Information Center

    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…

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

    ERIC Educational Resources Information Center

    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…

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

    NASA Technical Reports Server (NTRS)

    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.

  7. Using nursing clinical decision support systems to achieve meaningful use.

    PubMed

    Harrison, Roberta L; Lyerla, Frank

    2012-07-01

    The Health Information Technology and Clinical Health Act (one component of the American Recovery and Reinvestment Act) is responsible for providing incentive payments to hospitals and eligible providers in an effort to support the adoption of electronic health records. Future penalties are planned for electronic health record noncompliance. In order to receive incentives and avoid penalties, hospitals and eligible providers must demonstrate "meaningful use" of their electronic health records. One of the meaningful-use objectives established by the Centers for Medicare & Medicaid Services involves the use of a clinical decision support rule that addresses a hospital-defined, high-priority condition. This article describes the Plan-Do-Study-Act process for creating and implementing a nursing clinical decision support system designed to improve guideline adherence for hypoglycemia management. This project identifies hypoglycemia management as the high-priority area. However, other facilities with different high-priority conditions may find the process presented in this article useful for implementing additional clinical decision support rules geared toward improving outcomes and meeting federal mandates.

  8. Encounter Decision Aid vs. Clinical Decision Support or Usual Care to Support Patient-Centered Treatment Decisions in Osteoporosis: The Osteoporosis Choice Randomized Trial II.

    PubMed

    LeBlanc, Annie; Wang, Amy T; Wyatt, Kirk; Branda, Megan E; Shah, Nilay D; Van Houten, Holly; Pencille, Laurie; Wermers, Robert; Montori, Victor M

    2015-01-01

    Osteoporosis Choice, an encounter decision aid, can engage patients and clinicians in shared decision making about osteoporosis treatment. Its effectiveness compared to the routine provision to clinicians of the patient's estimated risk of fracture using the FRAX calculator is unknown. Patient-level, randomized, three-arm trial enrolling women over 50 with osteopenia or osteoporosis eligible for treatment with bisphosphonates, where the use of Osteoporosis Choice was compared to FRAX only and to usual care to determine impact on patient knowledge, decisional conflict, involvement in the decision-making process, decision to start and adherence to bisphosphonates. We enrolled 79 women in the three arms. Because FRAX estimation alone and usual care produced similar results, we grouped them for analysis. Compared to these, use of Osteoporosis Choice increased patient knowledge (median score 6 vs. 4, p = .01), improved understanding of fracture risk and risk reduction with bisphosphonates (p = .01 and p<.0001, respectively), had no effect on decision conflict, and increased patient engagement in the decision making process (OPTION scores 57% vs. 43%, p = .001). Encounters with the decision aid were 0.8 minutes longer (range: 33 minutes shorter to 3.0 minutes longer). There were twice as many patients receiving and filling prescriptions in the decision aid arm (83% vs. 40%, p = .07); medication adherence at 6 months was no different across arms. Supporting both patients and clinicians during the clinical encounter with the Osteoporosis Choice decision aid efficiently improves treatment decision making when compared to usual care with or without clinical decision support with FRAX results. clinical trials.gov NCT00949611.

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

    PubMed

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

    2016-12-01

    Cancer patients often do not make informed decisions regarding clinical trial participation. This study evaluated whether a web-based decision aid (DA) could support trial decisions compared with our cancer center's website. Adults diagnosed with cancer in the past 6 months who had not previously participated in a cancer clinical trial were eligible. Participants were randomized to view the DA or our cancer center's website (enhanced usual care [UC]). Controlling for whether participants had heard of cancer clinical trials and educational attainment, multivariable linear regression examined group on knowledge, self-efficacy for finding trial information, decisional conflict (values clarity and uncertainty), intent to participate, decision readiness, and trial perceptions. Two hundred patients (86%) consented between May 2014 and April 2015. One hundred were randomized to each group. Surveys were completed by 87 in the DA group and 90 in the UC group. DA group participants reported clearer values regarding trial participation than UC group participants reported (least squares [LS] mean = 15.8 vs. 32, p < .0001) and less uncertainty (LS mean = 24.3 vs. 36.4, p = .025). The DA group had higher objective knowledge than the UC group's (LS mean = 69.8 vs. 55.8, p < .0001). There were no differences between groups in intent to participate. Improvements on key decision outcomes including knowledge, self-efficacy, certainty about choice, and values clarity among participants who viewed the DA suggest web-based DAs can support informed decisions about trial participation among cancer patients facing this preference-sensitive choice. Although better informing patients before trial participation could improve retention, more work is needed to examine DA impact on enrollment and retention. This paper describes evidence regarding a decision tool to support patients' decisions about trial participation. By improving knowledge, helping patients clarify preferences for

  10. Development and Evaluation of Computer-Based Versions of the Decision Board for Early Breast Cancer

    DTIC Science & Technology

    2004-11-01

    of the node-negative Decision Board + Revised the computer version of the node-negative Decision Board + Field testing of the computer version of the...node-negative Decision Board was completed + Completed field testing of the computer version of the node-negative Decision Board Year 2 • Completed...field testing of the computerized version of the surgery Decision Board + Developed prototype of the computerized version of the node-negative Decision

  11. Designing Real-time Decision Support for Trauma Resuscitations

    PubMed Central

    Yadav, Kabir; Chamberlain, James M.; Lewis, Vicki R.; Abts, Natalie; Chawla, Shawn; Hernandez, Angie; Johnson, Justin; Tuveson, Genevieve; Burd, Randall S.

    2016-01-01

    Background Use of electronic clinical decision support (eCDS) has been recommended to improve implementation of clinical decision rules. Many eCDS tools, however, are designed and implemented without taking into account the context in which clinical work is performed. Implementation of the pediatric traumatic brain injury (TBI) clinical decision rule at one Level I pediatric emergency department includes an electronic questionnaire triggered when ordering a head computed tomography using computerized physician order entry (CPOE). Providers use this CPOE tool in less than 20% of trauma resuscitation cases. A human factors engineering approach could identify the implementation barriers that are limiting the use of this tool. Objectives The objective was to design a pediatric TBI eCDS tool for trauma resuscitation using a human factors approach. The hypothesis was that clinical experts will rate a usability-enhanced eCDS tool better than the existing CPOE tool for user interface design and suitability for clinical use. Methods This mixed-methods study followed usability evaluation principles. Pediatric emergency physicians were surveyed to identify barriers to using the existing eCDS tool. Using standard trauma resuscitation protocols, a hierarchical task analysis of pediatric TBI evaluation was developed. Five clinical experts, all board-certified pediatric emergency medicine faculty members, then iteratively modified the hierarchical task analysis until reaching consensus. The software team developed a prototype eCDS display using the hierarchical task analysis. Three human factors engineers provided feedback on the prototype through a heuristic evaluation, and the software team refined the eCDS tool using a rapid prototyping process. The eCDS tool then underwent iterative usability evaluations by the five clinical experts using video review of 50 trauma resuscitation cases. A final eCDS tool was created based on their feedback, with content analysis of the

  12. Supported decision making: a review of the international literature.

    PubMed

    Davidson, Gavin; Kelly, Berni; Macdonald, Geraldine; Rizzo, Maria; Lombard, Louise; Abogunrin, Oluwaseye; Clift-Matthews, Victoria; Martin, Alison

    2015-01-01

    Supported decision making (SDM) refers to the process of supporting people, whose decision making ability may be impaired, to make decisions and so promote autonomy and prevent the need for substitute decision making. There have been developments in SDM but mainly in the areas of intellectual disabilities and end-of-life care rather than in mental health. The main aim of this review was to provide an overview of the available evidence relevant to SDM and so facilitate discussion of how this aspect of law, policy and practice may be further developed in mental health services. The method used for this review was a Rapid Evidence Assessment which involved: developing appropriate search strategies; searching relevant databases and grey literature; then assessing, including and reviewing relevant studies. Included studies were grouped into four main themes: studies reporting stakeholders' views on SDM; studies identifying barriers to the implementation of SDM; studies highlighting ways to improve implementation; and studies on the impact of SDM. The available evidence on implementation and impact, identified by this review, is limited but there are important rights-based, effectiveness and pragmatic arguments for further developing and researching SDM for people with mental health problems.

  13. Decision support system based semantic web for personalized patient care.

    PubMed

    Douali, Nassim; De Roo, Jos; Jaulent, Marie-Christine

    2012-01-01

    Personalized medicine may be considered an extension of traditional approaches to understanding and treating diseases, but with greater precision. A profile of a patient's genetic variation can guide the selection of drugs or treatment protocols that minimize harmful side effects or ensure a more successful outcome. In this paper we describe a decision support system designed to assist physicians for personalized care, and methodology for integration in the clinical workflow. A reasoning method for interacting heterogeneous knowledge and data is a necessity in the context of personalized medicine. Development of clinical decision support based semantic web for personalized patient care is to achieve its potential and improve the quality, safety and efficiency of healthcare.

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

    PubMed

    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.

  15. What can Natural Language Processing do for Clinical Decision Support?

    PubMed Central

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

    2009-01-01

    Computerized Clinical Decision Support (CDS) aims to aid decision making of health care providers and the public by providing easily accessible health-related information at the point and time it is needed. Natural Language Processing (NLP) is instrumental in using free-text information to drive CDS, representing clinical knowledge and CDS interventions in standardized formats, and leveraging clinical narrative. The early innovative NLP research of clinical narrative was followed by a period of stable research conducted at the major clinical centers and a shift of mainstream interest to biomedical NLP. This review primarily focuses on the recently renewed interest in development of fundamental NLP methods and advances in the NLP systems for CDS. The current solutions to challenges posed by distinct sublanguages, intended user groups, and support goals are discussed. PMID:19683066

  16. Interactive financial decision support for clinical research trials.

    PubMed

    Holler, Benjamin; Forgione, Dana A; Baisden, Clinton E; Abramson, David A; Calhoon, John H

    2011-01-01

    The purpose of this article is to describe a decision support approach useful for evaluating proposals to conduct clinical research trials. Physicians often do not have the time or background to account for all the expenses of a clinical trial. Their evaluation process may be limited and driven by factors that do not indicate the potential for financial losses that a trial may impose. We analyzed clinical trial budget templates used by hospitals, health science centers, research universities, departments of medicine, and medical schools. We compiled a databank of costs and reviewed recent research trials conducted by the Department of Cardiothoracic Surgery in a major academic health science center. We then developed an interactive spreadsheet-based budgetary decision support approach that accounts for clinical trial income and costs. It can be tailored to provide quick and understandable data entry, accurate cost rates per subject, and clear go/no-go signals for the physician.

  17. Decision support system for material handling and packaging design

    NASA Astrophysics Data System (ADS)

    Johnsson, Mats I.; Mazouz, Abdel K.; Han, Chingping

    1992-02-01

    The reliability of the materials handling process involving automated stacking of packages on a pallet or automated sorting of packages in a distribution system depends mainly on the design of the package and the material used for the package. Many problems can be eliminated that result in a higher utilization of the system if the package is designed not only for the product and its requirements but also for an automated handling system with different types of grasping devices. A decision support system is being developed to help the package designer select the most appropriate material and design to satisfy the requirements of the automated materials handling process. The decision support system is programmed in C++ which gives the flexibility and portability needed for this type of system. The user interface is using graphics to ease the understanding of different design options during the selection process.

  18. A Flight Deck Decision Support Tool for Autonomous Airborne Operations

    NASA Technical Reports Server (NTRS)

    Ballin, Mark G.; Sharma, Vivek; Vivona, Robert A.; Johnson, Edward J.; Ramiscal, Ermin

    2002-01-01

    NASA is developing a flight deck decision support tool to support research into autonomous operations in a future distributed air/ground traffic management environment. This interactive real-time decision aid, referred to as the Autonomous Operations Planner (AOP), will enable the flight crew to plan autonomously in the presence of dense traffic and complex flight management constraints. In assisting the flight crew, the AOP accounts for traffic flow management and airspace constraints, schedule requirements, weather hazards, aircraft operational limits, and crew or airline flight-planning goals. This paper describes the AOP and presents an overview of functional and implementation design considerations required for its development. Required AOP functionality is described, its application in autonomous operations research is discussed, and a prototype software architecture for the AOP is presented.

  19. Invited review: Helping dairy farmers to improve economic performance utilizing data-driving decision support tools.

    PubMed

    Cabrera, V E

    2017-07-18

    The objective of this review paper is to describe the development and application of a suite of more than 40 computerized dairy farm decision support tools contained at the University of Wisconsin-Madison (UW) Dairy Management website http://DairyMGT.info. These data-driven decision support tools are aimed to help dairy farmers improve their decision-making, environmental stewardship and economic performance. Dairy farm systems are highly dynamic in which changing market conditions and prices, evolving policies and environmental restrictions together with every time more variable climate conditions determine performance. Dairy farm systems are also highly integrated with heavily interrelated components such as the dairy herd, soils, crops, weather and management. Under these premises, it is critical to evaluate a dairy farm following a dynamic integrated system approach. For this approach, it is crucial to use meaningful data records, which are every time more available. These data records should be used within decision support tools for optimal decision-making and economic performance. Decision support tools in the UW-Dairy Management website (http://DairyMGT.info) had been developed using combination and adaptation of multiple methods together with empirical techniques always with the primary goal for these tools to be: (1) highly user-friendly, (2) using the latest software and computer technologies, (3) farm and user specific, (4) grounded on the best scientific information available, (5) remaining relevant throughout time and (6) providing fast, concrete and simple answers to complex farmers' questions. DairyMGT.info is a translational innovative research website in various areas of dairy farm management that include nutrition, reproduction, calf and heifer management, replacement, price risk and environment. This paper discusses the development and application of 20 selected (http://DairyMGT.info) decision support tools.

  20. Computerized Adaptive Test vs. decision trees: Development of a support decision system to identify suicidal behavior.

    PubMed

    Delgado-Gomez, D; Baca-Garcia, E; Aguado, D; Courtet, P; Lopez-Castroman, J

    2016-12-01

    Several Computerized Adaptive Tests (CATs) have been proposed to facilitate assessments in mental health. These tests are built in a standard way, disregarding useful and usually available information not included in the assessment scales that could increase the precision and utility of CATs, such as the history of suicide attempts. Using the items of a previously developed scale for suicidal risk, we compared the performance of a standard CAT and a decision tree in a support decision system to identify suicidal behavior. We included the history of past suicide attempts as a class for the separation of patients in the decision tree. The decision tree needed an average of four items to achieve a similar accuracy than a standard CAT with nine items. The accuracy of the decision tree, obtained after 25 cross-validations, was 81.4%. A shortened test adapted for the separation of suicidal and non-suicidal patients was developed. CATs can be very useful tools for the assessment of suicidal risk. However, standard CATs do not use all the information that is available. A decision tree can improve the precision of the assessment since they are constructed using a priori information. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. Checklist and Decision Support in Nutritional Care for Burned Patients

    DTIC Science & Technology

    2016-10-01

    AD______________ AWARD NUMBER: W81XWH-12-2-0074 TITLE: Checklist and Decision Support in Nutritional Care for Burned Patients PRINCIPAL...in Nutritional Care for Burned Patients 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-12-2-0074 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Steven E... nutritional goals are not met in severely burned adults, 2) To find strategies to address identified gaps in feeding to incorporate into a checklist with easy

  2. Clinical Decision Support for Vascular Disease in Community Family Practice

    PubMed Central

    Keshavjee, K; Holbrook, AM; Lau, E; Esporlas-Jewer, I; Troyan, S

    2006-01-01

    The COMPETE III Vascular Disease Tracker (C3VT) is a personalized, Web-based, clinical decision support tool that provides patients and physicians access to a patient’s 16 individual vascular risk markers, specific advice for each marker and links to best practices in vascular disease management. It utilizes the chronic care model1 so that physicians can better manage patients with chronic diseases. Over 1100 patients have been enrolled into the COMPETE III study to date.

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

    PubMed

    Reisman, Y

    1996-01-01

    During the last three decades a great deal of research has been devoted to the development of integrated clinical decision support systems. This report aims to give a basic understanding of what is required for such a system. By means of a large literature study a survey is given of the major components of computer-based clinical aid systems. The main approaches and several aspects of evaluation of such programs are described. The computer has several inherent capabilities which are suitable for medical problem solving and can help in the formalization of medical knowledge. The components of such systems include the computer database, the reasoning engine and the user interface. The different approaches on which the reasoning engine is built are based on manipulation of information and advocate the use of knowledge to construct a solution to a problem. The information in the mode vary from data-intensive to knowledge-intensive. Assessment of decision support systems is a very important phase in the development of such systems. Evaluation should be made on the accuracy of the program, the nature of the system, the use of the data and the acceptance by the target users. Whatever the model is, its effectiveness will depend on the data with which the program has to work. Acceptance by physicians depends among other things on ease of use of the user interface. Profound changes in the delivery of health care will be induced through the rapid growth of on-line computer communication together with the development of integrated clinical decision support systems and electronic medical records. Notwithstanding the rapid growth of computer technology, computer-aided decision making is in its infancy and real support in daily practice is not yet achieved.

  4. NASA Wrangler: Automated Cloud-Based Data Assembly in the RECOVER Wildfire Decision Support System

    NASA Technical Reports Server (NTRS)

    Schnase, John; Carroll, Mark; Gill, Roger; Wooten, Margaret; Weber, Keith; Blair, Kindra; May, Jeffrey; Toombs, William

    2017-01-01

    NASA Wrangler is a loosely-coupled, event driven, highly parallel data aggregation service designed to take advantageof the elastic resource capabilities of cloud computing. Wrangler automatically collects Earth observational data, climate model outputs, derived remote sensing data products, and historic biophysical data for pre-, active-, and post-wildfire decision making. It is a core service of the RECOVER decision support system, which is providing rapid-response GIS analytic capabilities to state and local government agencies. Wrangler reduces to minutes the time needed to assemble and deliver crucial wildfire-related data.

  5. An Oceanographic Decision Support System for Scientific Field Experiments

    NASA Astrophysics Data System (ADS)

    Maughan, T.; Das, J.; McCann, M. P.; Rajan, K.

    2011-12-01

    . The ODSS was used for automated shore-based control of mobile assets and was also used to compute safety bounds for operation of MBARI AUVs and provide projections of drifters advected [1,4] due to surface conditions. Scientist and operations teams use the ODSS during the daily planning meetings for situation awareness and real time access to data to support decisions on sampling strategies and platform logistics. References 1. J.Das, F. Py, T. Maughan, J Ryan , K. Rajan & G. Sukhatme, Simultaneous Tracking and Sampling of Dynamic Oceanographic Features with Autonomous Underwater Vehicles and Lagrangian Drifters, Accepted, Intnl. Symp. on Experimental Robotics (ISER), N. Delhi, India, Dec 2010. 2. S. Jiminez, F. Py & K. Rajan, Learning Identification Models for In-situ Sampling of Ocean features, Working notes of the RSS'10 Workshop on Active Learning for Robotics. Robotics Systems Sciences, Spain. 2010 3. Py, F. , Jiminez, S. , and Rajan, K. "Modeling dynamic coastal ocean features for in-situ identication and adaptive sampling", Journal of Atmospheric and Ocean Technology-Ocean(2010). Submitted, in Review. 4. J. Das, K. Rajan, S. Frolov, J. Ryan, F. Py, D. Caron & G. Sukhatme, Towards Marine Bloom Trajectory Prediction for AUV Mission Planning, ICRA, May 2010, Anchorage

  6. NASA's past, current and potential future support in bringing climate projection information to the decision support level

    NASA Astrophysics Data System (ADS)

    Lee, T. J.

    2015-12-01

    It is common that we use global climate models or Earth system models to perform climate projection into the future. Because of the long integration time and the tremendous computing resources required for such a projection, the model resolution is typically not at a spatial scale fine enough for climate assessment or decision support purposes. A number of "downscaling technologies" have been developed over the years to bring the climate projection information to the local level for management and policy decision support purposes. In the past couple of years, NASA supported a number of regional to local climate projection activities: NASA Climate Adaption Science Investigators focused on climate resilience at NASA center level, National Climate Assessment (NCA) Capacity Building focused on data sets and tools to support NCA, NCA Indicators focused on creating simple indicators specifically designed for decision support, Assessing the Fidelity of Dynamical Downscaling with the NASA Unifies-WRF Model focused on understanding the credibility of dynamical downscaling technique using a regional climate model. All of these projects have a component in creating or using downscaled climate information. With the consequence of climate change beginning to emerge, there is a continuous need to better quantify the quality of downscaled climate projections. In this talk I will give an overview on NASA's efforts to understand the various techniques, the limitations including the risks of using these techniques, and finally, I will provide a view on possible future researches in this area.

  7. Modeling access, cost, and perceived quality: computer simulation benefits orthodontic clinic staffing decisions.

    PubMed

    Montgomery, J B; LaFrancois, G G; Perry, M J

    2000-02-01

    Given limited financial resources, simulation permits a financial analysis of the optimum staffing levels for orthodontists and dental assistants in an orthodontic clinic. A computer simulation provides the information for managerial review. This study, by building a computer simulation of an orthodontic service, set out to determine the most efficient mix between providers and support staff to maximize access, maximize perceived quality, and minimize expenditures. Six combinations of providers and support staff were compared during an animated, computer-generated what-if analysis. Based on the clinic workload and size, on the cost per patient, and on the cost per quality point, the research team recommended a staffing mix of one orthodontist and three assistants. This study shows that computer simulation is an enormous asset as a decision support tool for management.

  8. Decision making technical support study for the US Army's Chemical Stockpile Disposal Program

    SciTech Connect

    Feldman, D.L.; Dobson, J.E.

    1990-08-01

    This report examines the adequacy of current command and control systems designed to make timely decisions that would enable sufficient warning and protective response to an accident at the Edgewood area of Aberdeen Proving Ground (APG), Maryland, and at Pine Bluff Arsenal (PBA), Arkansas. Institutional procedures designed to facilitate rapid accident assessment, characterization, warning, notification, and response after the onset of an emergency and computer-assisted decision-making aids designed to provide salient information to on- and-off-post emergency responders are examined. The character of emergency decision making at APG and PBA, as well as potential needs for improvements to decision-making practices, procedures, and automated decision-support systems (ADSSs), are described and recommendations are offered to guide equipment acquisition and improve on- and off-post command and control relationships. We recommend that (1) a continued effort be made to integrate on- and off-post command control, and decision-making procedures to permit rapid decision making; (2) the pathways for alert and notification among on- and off-post officials be improved and that responsibilities and chain of command among off-post agencies be clarified; (3) greater attention be given to organizational and social context factors that affect the adequacy of response and the likelihood that decision-making systems will work as intended; and (4) faster improvements be made to on-post ADSSs being developed at APG and PBA, which hold considerable promise for depicting vast amounts of information. Phased development and procurement of computer-assisted decision-making tools should be undertaken to balance immediate needs against available resources and to ensure flexibility, equity among sites, and compatibility among on- and off-post systems. 112 refs., 6 tabs.

  9. Model-driven decision support for monitoring network design: methods and applications

    NASA Astrophysics Data System (ADS)

    Vesselinov, V. V.; Harp, D. R.; Mishra, P. K.; Katzman, D.

    2012-12-01

    A crucial aspect of any decision-making process for environmental management of contaminated sites and protection of groundwater resources is the identification of scientifically defensible remediation scenarios. The selected scenarios are ranked based on both their protective and cost effectiveness. The decision-making process is facilitated by implementation of site-specific data- and model-driven analyses for decision support (DS) taking into account existing uncertainties to evaluate alternative characterization and remedial activities. However, due to lack of data and/or complex interdependent uncertainties (conceptual elements, model parameters, measurement/computational errors, etc.), the DS optimization problem is ill posed (non unique) and the model-prediction uncertainties are difficult to quantify. Recently, we have developed and implemented several novel theoretical approaches and computational algorithms for model-driven decision support. New and existing DS tools have been employed for model analyses of the fate and extent of a chromium plume in the regional aquifer at Sandia Canyon Site, LANL. Since 2007, we have performed three iterations of DS analyses implementing different models, decision-making tools, and data sets providing guidance on design of a subsurface monitoring network for (1) characterization of the flow and transports processes, and (2) protection of the water users. The monitoring network is augmented by new wells at locations where acquired new data can effectively reduce uncertainty in model predicted contaminant concentrations. A key component of the DS analyses is contaminant source identification. Due to data and conceptual uncertainties, subsurface processes controlling the contaminant arrival at the top of the regional aquifer are not well defined. Nevertheless, the model-based analyses of the existing data and conceptual knowledge, including respective uncertainties, provide constrained probabilistic estimates of the

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

    NASA Astrophysics Data System (ADS)

    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.

  11. Supportability Challenges, Metrics, and Key Decisions for Future Human Spaceflight

    NASA Technical Reports Server (NTRS)

    Owens, Andrew C.; de Weck, Olivier L.; Stromgren, Chel; Cirillo, William; Goodliff, Kandyce

    2017-01-01

    Future crewed missions beyond Low Earth Orbit (LEO) represent a logistical challenge that is unprecedented in human space flight. Astronauts will travel farther and stay in space for longer than any previous mission, far from timely abort or resupply from Earth. Under these conditions, supportability { defined as the set of system characteristics that influence the logistics and support required to enable safe and effective operations of systems { will be a much more significant driver of space system lifecycle properties than it has been in the past. This paper presents an overview of supportability for future human space flight. The particular challenges of future missions are discussed, with the differences between past, present, and future missions highlighted. The relationship between supportability metrics and mission cost, performance, schedule, and risk is also discussed. A set of pro- posed strategies for managing supportability is presented (including reliability growth, uncertainty reduction, level of repair, commonality, redundancy, In-Space Manufacturing (ISM) (including the use of material recycling and In-Situ Resource Utilization (ISRU) for spares and maintenance items), reduced complexity, and spares inventory decisions such as the use of predeployed or cached spares - along with a discussion of the potential impacts of each of those strategies. References are provided to various sources that describe these supportability metrics and strategies, as well as associated modeling and optimization techniques, in greater detail. Overall, supportability is an emergent system characteristic and a holistic challenge for future system development. System designers and mission planners must carefully consider and balance the supportability metrics and decisions described in this paper in order to enable safe and effective beyond-LEO human space flight.

  12. Dynamic remapping decisions in multi-phase parallel computations

    NASA Technical Reports Server (NTRS)

    Nicol, D. M.; Reynolds, P. F., Jr.

    1986-01-01

    The effectiveness of any given mapping of workload to processors in a parallel system is dependent on the stochastic behavior of the workload. Program behavior is often characterized by a sequence of phases, with phase changes occurring unpredictably. During a phase, the behavior is fairly stable, but may become quite different during the next phase. Thus a workload assignment generated for one phase may hinder performance during the next phase. We consider the problem of deciding whether to remap a paralled computation in the face of uncertainty in remapping's utility. Fundamentally, it is necessary to balance the expected remapping performance gain against the delay cost of remapping. This paper treats this problem formally by constructing a probabilistic model of a computation with at most two phases. We use stochastic dynamic programming to show that the remapping decision policy which minimizes the expected running time of the computation has an extremely simple structure: the optimal decision at any step is followed by comparing the probability of remapping gain against a threshold. This theoretical result stresses the importance of detecting a phase change, and assessing the possibility of gain from remapping. We also empirically study the sensitivity of optimal performance to imprecise decision threshold. Under a wide range of model parameter values, we find nearly optimal performance if remapping is chosen simply when the gain probability is high. These results strongly suggest that except in extreme cases, the remapping decision problem is essentially that of dynamically determining whether gain can be achieved by remapping after a phase change; precise quantification of the decision model parameters is not necessary.

  13. Sequential decision making in computational sustainability via adaptive submodularity

    USGS Publications Warehouse

    Andreas Krause,; Daniel Golovin,; Converse, Sarah J.

    2015-01-01

    Many problems in computational sustainability require making a sequence of decisions in complex, uncertain environments. Such problems are generally notoriously difficult. In this article, we review the recently discovered notion of adaptive submodularity, an intuitive diminishing returns condition that generalizes the classical notion of submodular set functions to sequential decision problems. Problems exhibiting the adaptive submodularity property can be efficiently and provably near-optimally solved using simple myopic policies. We illustrate this concept in several case studies of interest in computational sustainability: First, we demonstrate how it can be used to efficiently plan for resolving uncertainty in adaptive management scenarios. Secondly, we show how it applies to dynamic conservation planning for protecting endangered species, a case study carried out in collaboration with the US Geological Survey and the US Fish and Wildlife Service.

  14. Embedded systems for supporting computer accessibility.

    PubMed

    Mulfari, Davide; Celesti, Antonio; Fazio, Maria; Villari, Massimo; Puliafito, Antonio

    2015-01-01

    Nowadays, customized AT software solutions allow their users to interact with various kinds of computer systems. Such tools are generally available on personal devices (e.g., smartphones, laptops and so on) commonly used by a person with a disability. In this paper, we investigate a way of using the aforementioned AT equipments in order to access many different devices without assistive preferences. The solution takes advantage of open source hardware and its core component consists of an affordable Linux embedded system: it grabs data coming from the assistive software, which runs on the user's personal device, then, after processing, it generates native keyboard and mouse HID commands for the target computing device controlled by the end user. This process supports any operating system available on the target machine and it requires no specialized software installation; therefore the user with a disability can rely on a single assistive tool to control a wide range of computing platforms, including conventional computers and many kinds of mobile devices, which receive input commands through the USB HID protocol.

  15. Personalization and Patient Involvement in Decision Support Systems: Current Trends

    PubMed Central

    Sacchi, L.; Lanzola, G.; Viani, N.

    2015-01-01

    Summary Objectives This survey aims at highlighting the latest trends (2012-2014) on the development, use, and evaluation of Information and Communication Technologies (ICT) based decision support systems (DSSs) in medicine, with a particular focus on patient-centered and personalized care. Methods We considered papers published on scientific journals, by querying PubMed and Web of Science™. Included studies focused on the implementation or evaluation of ICT-based tools used in clinical practice. A separate search was performed on computerized physician order entry systems (CPOEs), since they are increasingly embedding patient-tailored decision support. Results We found 73 papers on DSSs (53 on specific ICT tools) and 72 papers on CPOEs. Although decision support through the delivery of recommendations is frequent (28/53 papers), our review highlighted also DSSs only based on efficient information presentation (25/53). Patient participation in making decisions is still limited (9/53), and mostly focused on risk communication. The most represented medical area is cancer (12%). Policy makers are beginning to be included among stakeholders (6/73), but integration with hospital information systems is still low. Concerning knowledge representation/management issues, we identified a trend towards building inference engines on top of standard data models. Most of the tools (57%) underwent a formal assessment study, even if half of them aimed at evaluating usability and not effectiveness. Conclusions Overall, we have noticed interesting evolutions of medical DSSs to improve communication with the patient, consider the economic and organizational impact, and use standard models for knowledge representation. However, systems focusing on patient-centered care still do not seem to be available at large. PMID:26293857

  16. Decision support system for economic value of irrigation water

    NASA Astrophysics Data System (ADS)

    El-Gafy, Inas; El-Ganzori, Akram

    2012-06-01

    The mismatch between the supply and demand, inequitable distribution and the over irrigation of water consuming crops are the main constraints that are faced in the implementation of the integrated water resources management in Egypt. With water scarcity, the problem under consideration is that the current cropping pattern is not economically efficient in the utilization of the available water resource. Moreover, in consequence of the importance of the agricultural sector to the national economies, it is necessary to be aware of the economic performance of water use in the crops production. The scope of this study is to develop economic value of irrigation water maps of Egypt. The objective of the study is carried out by acquiring a Decision Support System for economic value of irrigation water of Egypt. This Decision Support System is applied for developing economic value maps for the irrigation water that is used for cultivating 45 crops under cereal, fiber, legumes, and vegetables, herbalist, and forages categories at each governorate of Egypt in year 2008 and 2009. The crops that achieve the highest and lowest economic value of irrigation water at each governorate of Egypt were identified. The reasons of the variations in the economic value of irrigation water at the governorates of Egypt were determined. The developed Decision Support System could be used yearly as a tool for demonstrating a picture about the economic value of irrigation water for the decision makers in the areas of water resources and agriculture. The developed economic value of irrigation water maps can be used in proposing a cropping pattern that maximizes the economic value of irrigation water in each governorate of Egypt.

  17. Personalization and Patient Involvement in Decision Support Systems: Current Trends.

    PubMed

    Quaglini, S; Sacchi, L; Lanzola, G; Viani, N

    2015-08-13

    This survey aims at highlighting the latest trends (2012-2014) on the development, use, and evaluation of Information and Communication Technologies (ICT) based decision support systems (DSSs) in medicine, with a particular focus on patient-centered and personalized care. We considered papers published on scientific journals, by querying PubMed and Web of ScienceTM. Included studies focused on the implementation or evaluation of ICT-based tools used in clinical practice. A separate search was performed on computerized physician order entry systems (CPOEs), since they are increasingly embedding patient-tailored decision support. We found 73 papers on DSSs (53 on specific ICT tools) and 72 papers on CPOEs. Although decision support through the delivery of recommendations is frequent (28/53 papers), our review highlighted also DSSs only based on efficient information presentation (25/53). Patient participation in making decisions is still limited (9/53), and mostly focused on risk communication. The most represented medical area is cancer (12%). Policy makers are beginning to be included among stakeholders (6/73), but integration with hospital information systems is still low. Concerning knowledge representation/management issues, we identified a trend towards building inference engines on top of standard data models. Most of the tools (57%) underwent a formal assessment study, even if half of them aimed at evaluating usability and not effectiveness. Overall, we have noticed interesting evolutions of medical DSSs to improve communication with the patient, consider the economic and organizational impact, and use standard models for knowledge representation. However, systems focusing on patient-centered care still do not seem to be available at large.

  18. An Advanced Decision Support Tool for Electricity Infrastructure Operations

    SciTech Connect

    Chen, Yousu; Huang, Zhenyu; Wong, Pak C.; Mackey, Patrick S.; Allwardt, Craig H.; Ma, Jian; Greitzer, Frank L.

    2010-01-31

    Electricity infrastructure, as one of the most critical infrastructures in the U.S., plays an important role in modern societies. Its failure would lead to significant disruption of people’s lives, industry and commercial activities, and result in massive economic losses. Reliable operation of electricity infrastructure is an extremely challenging task because human operators need to consider thousands of possible configurations in near real-time to choose the best option and operate the network effectively. In today’s practice, electricity infrastructure operation is largely based on operators’ experience with very limited real-time decision support, resulting in inadequate management of complex predictions and the inability to anticipate, recognize, and respond to situations caused by human errors, natural disasters, or cyber attacks. Therefore, a systematic approach is needed to manage the complex operational paradigms and choose the best option in a near-real-time manner. This paper proposes an advanced decision support tool for electricity infrastructure operations. The tool has the functions of turning large amount of data into actionable information to help operators monitor power grid status in real time; performing trend analysis to indentify system trend at the regional level or system level to help the operator to foresee and discern emergencies, studying clustering analysis to assist operators to identify the relationships between system configurations and affected assets, and interactively evaluating the alternative remedial actions to aid operators to make effective and timely decisions. This tool can provide significant decision support on electricity infrastructure operations and lead to better reliability in power grids. This paper presents examples with actual electricity infrastructure data to demonstrate the capability of this tool.

  19. Proactive Decision Support Via Narrative-Integrated Multi-Level Support System (NIMSS)

    DTIC Science & Technology

    2014-11-30

    unlimited Overall objective is to create and test (using specific applications) a theory and model-based technology for enabling and advancing a...decision-makers build, maintain, and represent situational context. Integrate multiple existing theories and conceptual models of context that address...Develop NIMSS Theory & Formalism In this task, we will develop the NIM context model and develop a Decision Support model based on the underlying context

  20. Gaussian quantum computation with oracle-decision problems

    NASA Astrophysics Data System (ADS)

    Adcock, Mark R. A.; Høyer, Peter; Sanders, Barry C.

    2013-04-01

    We study a simple-harmonic-oscillator quantum computer solving oracle decision problems. We show that such computers can perform better by using nonorthogonal Gaussian wave functions rather than orthogonal top-hat wave functions as input to the information encoding process. Using the Deutsch-Jozsa problem as an example, we demonstrate that Gaussian modulation with optimized width parameter results in a lower error rate than for the top-hat encoding. We conclude that Gaussian modulation can allow for an improved trade-off between encoding, processing and measurement of the information.

  1. A Semantic Approach with Decision Support for Safety Service in Smart Home Management.

    PubMed

    Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

    2016-08-03

    Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.

  2. A Semantic Approach with Decision Support for Safety Service in Smart Home Management

    PubMed Central

    Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

    2016-01-01

    Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate. PMID:27527170

  3. Bridging groundwater models and decision support with a Bayesian network

    USGS Publications Warehouse

    Fienen, Michael N.; Masterson, John P.; Plant, Nathaniel G.; Gutierrez, Benjamin T.; Thieler, E. Robert

    2013-01-01

    Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.

  4. A new decision support model for preanesthetic evaluation.

    PubMed

    Sobrie, Olivier; Lazouni, Mohammed El Amine; Mahmoudi, Saïd; Mousseau, Vincent; Pirlot, Marc

    2016-09-01

    The principal challenges in the field of anesthesia and intensive care consist of reducing both anesthetic risks and mortality rate. The ASA score plays an important role in patients' preanesthetic evaluation. In this paper, we propose a methodology to derive simple rules which classify patients in a category of the ASA scale on the basis of their medical characteristics. This diagnosis system is based on MR-Sort, a multiple criteria decision analysis model. The proposed method intends to support two steps in this process. The first is the assignment of an ASA score to the patient; the second concerns the decision to accept-or not-the patient for surgery. In order to learn the model parameters and assess its effectiveness, we use a database containing the parameters of 898 patients who underwent preanesthesia evaluation. The accuracy of the learned models for predicting the ASA score and the decision of accepting the patient for surgery is assessed and proves to be better than that of other machine learning methods. Furthermore, simple decision rules can be explicitly derived from the learned model. These are easily interpretable by doctors, and their consistency with medical knowledge can be checked. The proposed model for assessing the ASA score produces accurate predictions on the basis of the (limited) set of patient attributes in the database available for the tests. Moreover, the learned MR-Sort model allows for easy interpretation by providing human-readable classification rules. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  5. Demonstration of Decision Support Tools for Sustainable Development

    SciTech Connect

    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.

  6. Bridging groundwater models and decision support with a Bayesian network

    NASA Astrophysics Data System (ADS)

    Fienen, Michael N.; Masterson, John P.; Plant, Nathaniel G.; Gutierrez, Benjamin T.; Thieler, E. Robert

    2013-10-01

    Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.

  7. The economic valuation of improved process plant decision support technology.

    PubMed

    White, Douglas C

    2007-06-01

    How can investments that would potentially improve a manufacturing plant's decision process be economically justified? What is the value of "better information," "more flexibility," or "improved integration" and the technologies that provide these effects? Technology investments such as improved process modelling, new real time historians and other databases, "smart" instrumentation, better data analysis and visualization software, and/or improved user interfaces often include these benefits as part of their valuation. How are these "soft" benefits to be converted to a quantitative economic return? Quantification is important if rational management decisions are to be made about the correct amount of money to invest in the technologies, and which technologies to choose among the many available ones. Modelling the plant operational decision cycle-detect, analyse, forecast, choose and implement--provides a basis for this economic quantification. In this paper a new economic model is proposed for estimation of the value of decision support investments based on their effect upon the uncertainty in forecasting plant financial performance. This model leads to quantitative benefit estimates that have a realistic financial basis. An example is presented demonstrating the application of the method.

  8. Decision Integration and Support Engine (DISE) for dynamic aircraft and ISR asset tasking/retasking decision support for the AOC

    NASA Astrophysics Data System (ADS)

    VonPlinsky, Michael J.; Crowder, Ed

    2002-07-01

    The Decision Integration and Support Environment (DISE) is a Bayesian network (BN) based modeling and simulation of the target nomination and aircraft tasking decision processes. DISE operates in event driven interactions with FTI's AOC model, being triggered from within the Time Critical Target (TCT) Operations cell. As new target detections are received by the AOC from off-board ISR sources and processed by the Automatic Target Recognition (ATR) module in the AOC, DISE is called to determine if the target should be prosecuted, and if so, which of the available aircraft should be tasked to attack it. A range of decision criteria, with priorities established off-line and input into the tool, are associated with this process. DISE, when running in its constructive mode, automatically selects the best-suited aircraft and assigns the new target. In virtual mode, with a human operator, DISE presents the user with a suitability ranked list of the available aircraft for assignment. Recent DISE enhancements are applying this concept to the prioritization and scheduling of ISR support requests from Users to support both latent and dynamic tasking and scheduling of both space-based and airborne ISR assets.

  9. Coordinated machine learning and decision support for situation awareness.

    SciTech Connect

    Draelos, Timothy John; Zhang, Peng-Chu.; Wunsch, Donald C.; Seiffertt, John; Conrad, Gregory N.; Brannon, Nathan Gregory

    2007-09-01

    For applications such as force protection, an effective decision maker needs to maintain an unambiguous grasp of the environment. Opportunities exist to leverage computational mechanisms for the adaptive fusion of diverse information sources. The current research employs neural networks and Markov chains to process information from sources including sensors, weather data, and law enforcement. Furthermore, the system operator's input is used as a point of reference for the machine learning algorithms. More detailed features of the approach are provided, along with an example force protection scenario.

  10. Decision support framework for oil-spill response

    SciTech Connect

    Octavio, K.H.

    1986-01-01

    A review of the state of oil spill response planning and an interpretation of the administrative, procedural and political climate surrounding response in general and in the Venezuelan case in particular reveals critical areas where things go wrong, affecting speed and appropriateness of response. Generic issues faced by any region preparing contingency plans are identified and techniques for resolving them and the appropriate institutional setting are suggested. The first reported design of an integrated interactive graphic microcomputer based decision Support System for operational oil spill response is presented. The integrated DSS with its status display and log entries provides a formal mechanism for recording activities, and their justifications at the time of occurrence so that activities and their consequences can be reviewed to improve procedures and priorities. There is an identifiable dearth of realistic training exercises meant to hone decision making skills under the pressures of an ongoing major spill event. The design of an operational oil spill response training system based directly on the framework of an interactive, graphics oriented Decision Support System for operational response to oil spills is presented. This training framework not only develops skills needed by new spill response coordinators in devising and carrying out action plans, it also identified flaws or gaps in managerial or institutional arrangements before the response system is tested by an actual spill. The underlying concepts of both the DSS and the training exercise are general and can be readily applied to any region concerned with organizing oil spill response.

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

    SciTech Connect

    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.

  12. Technosocial Predictive Analytics in Support of Naturalistic Decision Making

    SciTech Connect

    Sanfilippo, Antonio P.; Cowell, Andrew J.; Malone, Elizabeth L.; Riensche, Roderick M.; Thomas, James J.; Unwin, Stephen D.; Whitney, Paul D.; Wong, Pak C.

    2009-06-23

    A main challenge we face in fostering sustainable growth is to anticipate outcomes through predictive and proactive across domains as diverse as energy, security, the environment, health and finance in order to maximize opportunities, influence outcomes and counter adversities. The goal of this paper is to present new methods for anticipatory analytical thinking which address this challenge through the development of a multi-perspective approach to predictive modeling as a core to a creative decision making process. This approach is uniquely multidisciplinary in that it strives to create decision advantage through the integration of human and physical models, and leverages knowledge management and visual analytics to support creative thinking by facilitating the achievement of interoperable knowledge inputs and enhancing the user’s cognitive access. We describe a prototype system which implements this approach and exemplify its functionality with reference to a use case in which predictive modeling is paired with analytic gaming to support collaborative decision-making in the domain of agricultural land management.

  13. Healthcare decision support system for administration of chronic diseases.

    PubMed

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

    2014-07-01

    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. 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; the rules are extensively compiled by physicians through a developmental user interface that enables knowledge base construction, modification, and integration. Further, screening results are visualized for the self-intuitive understanding of personal health status by patients. A recommendation message is output through the Web service by receiving patient information from the hospital information recording system and object attribute values as input factors. The proposed system can verify patient behavior by acting as an intellectualized backbone of chronic diseases management; further, it supports self-management and scheduling of screening. Chronic patients can continuously receive active recommendations related to their healthcare through the rule management system, and they can model the system by acting as decision makers in diseases management; secondary diseases can be prevented and health management can be performed by reference to patient-specific lifestyle guidelines.

  14. Decision support for integrated water-energy planning.

    SciTech Connect

    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.

  15. Decision support using the Multistatic Tactical Planning Aid (MSTPA)

    NASA Astrophysics Data System (ADS)

    Strode, Christopher; Mourre, Baptiste; Rixen, Michel

    2012-01-01

    The Multistatic Tactical Planning Aid (MSTPA) is a tool currently in development at NATO Undersea Research Centre which may be used to model the performance of a given multistatic sensor network in terms of the probability of detection of a submarine, the ability to hold a track and whether such a track could be correctly classified as such. The tool therefore considers the entire chain of events from an initial calculation of signal excess, the generation of a contact considering localisation errors, followed by the subsequent tracking and classification process. In its current form, the tool may be used to plan a particular multistatic scenario through operational analysis of many Monte Carlo simulations. The future development of MSTPA will transition towards a real-time decision support tool to assist operators and planners at sea. This study introduces a number of generic decision support techniques which may be wrapped around the MSTPA tool. The acoustic performance metric that will drive decisions will of course be subject to uncertainty relating to environmental measurements and extrapolations. The effect of this uncertainty on acoustic performance is examined here. Future studies will consider the sensitivity of the eventual decision—in terms of optimum sensor positions—to the acoustic uncertainty.

  16. A highly scalable, interoperable clinical decision support service

    PubMed Central

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

    2014-01-01

    Objective To create a clinical decision support (CDS) system that is shareable across healthcare delivery systems and settings over large geographic regions. Materials and methods The enterprise clinical rules service (ECRS) realizes nine design principles through a series of enterprise java beans and leverages off-the-shelf rules management systems in order to provide consistent, maintainable, and scalable decision support in a variety of settings. Results The ECRS is deployed at Partners HealthCare System (PHS) and is in use for a series of trials by members of the CDS consortium, including internally developed systems at PHS, the Regenstrief Institute, and vendor-based systems deployed at locations in Oregon and New Jersey. Performance measures indicate that the ECRS provides sub-second response time when measured apart from services required to retrieve data and assemble the continuity of care document used as input. Discussion We consider related work, design decisions, comparisons with emerging national standards, and discuss uses and limitations of the ECRS. Conclusions ECRS design, implementation, and use in CDS consortium trials indicate that it provides the flexibility and modularity needed for broad use and performs adequately. Future work will investigate additional CDS patterns, alternative methods of data passing, and further optimizations in ECRS performance. PMID:23828174

  17. Clinical Decision Support Systems for Comorbidity: Architecture, Algorithms, and Applications

    PubMed Central

    Fan, Aihua; Tang, Yu

    2017-01-01

    In this paper, we present the design of a clinical decision support system (CDSS) for monitoring comorbid conditions. Specifically, we address the architecture of a CDSS by characterizing it from three layers and discuss the algorithms in each layer. Also we address the applications of CDSSs in a few real scenarios and analyze the accuracy of a CDSS in consideration of the potential conflicts when using multiple clinical practice guidelines concurrently. Finally, we compare the system performance in our design with that in the other design schemes. Our study shows that our proposed design can achieve a clinical decision in a shorter time than the other designs, while ensuring a high level of system accuracy. PMID:28373881

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

    NASA Astrophysics Data System (ADS)

    Steinberg, N.

    2016-12-01

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

  19. Combining decision support and image processing: a PROforma model.

    PubMed

    Sordo, M; Fox, J; Blum, C; Taylor, P; Lee, R; Alberdi, E

    2001-01-01

    This paper addresses two important problems in medical image interpretation:(1) integration of numeric and symbolic information, (2) access to external sources of medical knowledge. We have developed a prototype in which image processing algorithms are combined with symbolic representations for reasoning, decision making and task management in an integrated, platform-independent system for the differential diagnosis of abnormalities in mammograms. The prototype is based on PROforma, a generic technology for building decision support systems based on clinical guidelines. The PROforma language defines a set of tasks, one of which, the enquiry, is used as means of interaction with the outside world. However, the current enquiry model has proved to be too limited for our purposes. In this paper we outline a more general model, which can be used as an interface between symbolic functions and image or other signal data.

  20. Decision support for workload assessment - Introducing WC FIELDE

    NASA Technical Reports Server (NTRS)

    Casper, Patricia A.; Shively, Robert J.; Hart, Sandra G.

    1987-01-01

    Currently there is a great demand for mental workload evaluation in the course of system design and modification. In light of this demand, a microprocessor-based decision support system has been created called WC FIELDE: Workload Consultant for FIELD Evaluation. The system helps the user select workload measures appropriate to his or her application from the large pool of currently available techniques. Both novices and those with some workload experience may benefit from using WC FIELDE, since the system's operation is entirely transparent and all rules involved in the decision process are available for the user to examine. WC FIELDE recommends several assessment methodologies in decreasing order of appropriateness, and provides additional information on each measure at the end of the program in the form of text files.