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Sample records for clinical decision support

  1. Clinical Decision Support (CDS) Inventory

    Data.gov (United States)

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

  2. Decision support for clinical laboratory capacity planning.

    Science.gov (United States)

    van Merode, G G; Hasman, A; Derks, J; Goldschmidt, H M; Schoenmaker, B; Oosten, M

    1995-01-01

    The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for supporting decisions at the overall laboratory level (concerning the division of the laboratory into job shops) and for supporting decisions at the job shop level (assignment of staff to workstations and sample scheduling). Experiments with these modules are described showing both the functionality and the validity.

  3. Clinical Productivity System - A Decision Support Model

    CERN Document Server

    Bennett, Casey C

    2012-01-01

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

  4. ClinicalAccess: a clinical decision support tool.

    Science.gov (United States)

    Crowell, Karen; Vardell, Emily

    2015-01-01

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

  5. Clinical decision support system in dental implantology

    Directory of Open Access Journals (Sweden)

    Alexandra Polášková

    2013-06-01

    Full Text Available Implantology is rapidly developing interdisciplinary field providing enormous amounts of data to be classified, evaluated and interpreted. The analysis of clinical data remains a big challenge, because each new system has specific requirements. The aim of study was prepare specific tool for treatment planning. Decision support system is built on Expert system. It is interactive software which provides clinical recommendations and treatment planning. Expert systems are knowledge-based computer programs designed to provide assistance in diagnosis and treatment planning. These systems are used for health care (dentistry, medicine, pharmacy etc.. The application contained the medical history analysis to obtaining information useful in formulating a diagnosis and providing implant insertion and prosthetic reconstruction to the patient; the diagnostic examination of dental implant procedure; implant positioning diagnosis – 3-D measurement; diagnostic information for treatment planning; treatment plan in the form of objective measurement of implant placement that helps surgeon and prosthodontics. The decision algorithm implemented by programming language is used. Core of program is an expert knowledge programming like a decision tree. The analysis of the decision-making process for implant treatment in general practice is prepared and analyzed.

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

    Directory of Open Access Journals (Sweden)

    Kolostoumpis G.

    2012-01-01

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

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

    Science.gov (United States)

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

    2016-06-01

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

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

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

    2015-07-01

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

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

    Science.gov (United States)

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

    2016-04-01

    Dashboard systems for clinical decision support integrate data from multiple sources. These systems, the newest in a long line of dose calculators and other decision support tools, utilize Bayesian approaches to fully individualize dosing using information gathered through therapeutic drug monitoring. In the treatment of inflammatory bowel disease patients with infliximab, dashboards may reduce therapeutic failures and treatment costs. The history and future development of modern Bayesian dashboard systems is described. PMID:26785109

  10. Improving clinical decision support using data mining techniques

    Science.gov (United States)

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

    1999-02-01

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

  11. Bayesian networks for clinical decision support : a rational approach to dynamic decision-making under uncertainty

    NARCIS (Netherlands)

    Gerven, M.A.J. van

    2007-01-01

    This dissertation deals with decision support in the context of clinical oncology. (Dynamic) Bayesian networks are used as a framework for (dynamic) decision-making under uncertainty and applied to a variety of diagnostic, prognostic, and treatment problems in medicine. It is shown that the proposed

  12. A Clinical Decision Support System for Breast Cancer Patients

    Science.gov (United States)

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

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

  13. Clinical decision support for perioperative information management systems.

    Science.gov (United States)

    Wanderer, Jonathan P; Ehrenfeld, Jesse M

    2013-12-01

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

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

    Science.gov (United States)

    Khalifa, Mohamed; Alswailem, Osama

    2015-01-01

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

  15. Guideline Formalization and Knowledge Representation for Clinical Decision Support

    Directory of Open Access Journals (Sweden)

    Tiago OLIVEIRA

    2012-09-01

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

  16. Exploration Clinical Decision Support System: Medical Data Architecture

    Science.gov (United States)

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

    2016-01-01

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

  17. Details of a Successful Clinical Decision Support System

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

    2007-01-01

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

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

    Science.gov (United States)

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

    2009-04-01

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

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

    Science.gov (United States)

    Wright, Adam; Sittig, Dean F

    2008-12-01

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

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

    Science.gov (United States)

    Inada, Masanori; Sato, Mayumi; Yoneyama, Akiko

    2011-05-01

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

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

    Science.gov (United States)

    Inada, Masanori; Sato, Mayumi; Yoneyama, Akiko

    2011-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Oberg Ryan

    2011-04-01

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

  3. Pregnancy outcomes in Ghana : Relavance of clinical decision making support tools for frontline providers of care

    NARCIS (Netherlands)

    Amoakoh-Coleman, M.

    2016-01-01

    Ghana’s slow progress towards attaining millennium development goal 5 has been associated with gaps in quality of care, particularly quality of clinical decision making for clients. This thesis reviews the relevance and effect of clinical decision making support tools on pregnancy outcomes. Relevanc

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

    OpenAIRE

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

    2008-01-01

    Computerized decision support for use at the point of care has to be comprehensive. It means that clinical information stored in electronic health records needs to be integrated with various forms of clinical knowledge (elicited from experts, discovered from data or summarized in systematic reviews of clinical trials). In order to provide such comprehensive support we created the MET-A3Support framework for constructing clinical applications aimed at various medical conditions. We employed th...

  5. Fuzzy Logic in Clinical Practice Decision Support Systems

    NARCIS (Netherlands)

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

    2000-01-01

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

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

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

    2014-04-01

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

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

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    Wolfenden, Andrew

    2012-01-01

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

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    's intention to use eCDS. The decisive reason for using or not using the eCDS is its perceived usefulness. Functional characteristics such as speed and ease of use are important but alone these are not enough. Specific information technology, professional, patient and environment features can help or hinder...... the use. CONCLUSIONS: Primary care professionals have to perceive eCDS guidance useful for their work before they use it....

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

    Directory of Open Access Journals (Sweden)

    Brinner Kristin M

    2009-10-01

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

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

    Directory of Open Access Journals (Sweden)

    Hoath James I

    2010-10-01

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

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

    Science.gov (United States)

    Sandell, Protik

    2007-01-01

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

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

    Science.gov (United States)

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

    2012-02-01

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

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

    Science.gov (United States)

    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…

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

    NARCIS (Netherlands)

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

    2011-01-01

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

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

    OpenAIRE

    Kashyap, Vipul; Morales, Alfredo; Hongsermeier, Tonya

    2006-01-01

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

  16. Evaluation of a novel electronic genetic screening and clinical decision support tool in prenatal clinical settings.

    Science.gov (United States)

    Edelman, Emily A; Lin, Bruce K; Doksum, Teresa; Drohan, Brian; Edelson, Vaughn; Dolan, Siobhan M; Hughes, Kevin; O'Leary, James; Vasquez, Lisa; Copeland, Sara; Galvin, Shelley L; DeGroat, Nicole; Pardanani, Setul; Gregory Feero, W; Adams, Claire; Jones, Renee; Scott, Joan

    2014-07-01

    "The Pregnancy and Health Profile" (PHP) is a free prenatal genetic screening and clinical decision support (CDS) software tool for prenatal providers. PHP collects family health history (FHH) during intake and provides point-of-care risk assessment for providers and education for patients. This pilot study evaluated patient and provider responses to PHP and effects of using PHP in practice. PHP was implemented in four clinics. Surveys assessed provider confidence and knowledge and patient and provider satisfaction with PHP. Data on the implementation process were obtained through semi-structured interviews with administrators. Quantitative survey data were analyzed using Chi square test, Fisher's exact test, paired t tests, and multivariate logistic regression. Open-ended survey questions and interviews were analyzed using qualitative thematic analysis. Of the 83% (513/618) of patients that provided feedback, 97% felt PHP was easy to use and 98% easy to understand. Thirty percent (21/71) of participating physicians completed both pre- and post-implementation feedback surveys [13 obstetricians (OBs) and 8 family medicine physicians (FPs)]. Confidence in managing genetic risks significantly improved for OBs on 2/6 measures (p values ≤0.001) but not for FPs. Physician knowledge did not significantly change. Providers reported value in added patient engagement and reported mixed feedback about the CDS report. We identified key steps, resources, and staff support required to implement PHP in a clinical setting. To our knowledge, this study is the first to report on the integration of patient-completed, electronically captured and CDS-enabled FHH software into primary prenatal practice. PHP is acceptable to patients and providers. Key to successful implementation in the future will be customization options and interoperability with electronic health records.

  17. Clinical-decision support based on medical literature: A complex network approach

    Science.gov (United States)

    Jiang, Jingchi; Zheng, Jichuan; Zhao, Chao; Su, Jia; Guan, Yi; Yu, Qiubin

    2016-10-01

    In making clinical decisions, clinicians often review medical literature to ensure the reliability of diagnosis, test, and treatment because the medical literature can answer clinical questions and assist clinicians making clinical decisions. Therefore, finding the appropriate literature is a critical problem for clinical-decision support (CDS). First, the present study employs search engines to retrieve relevant literature about patient records. However, the result of the traditional method is usually unsatisfactory. To improve the relevance of the retrieval result, a medical literature network (MLN) based on these retrieved papers is constructed. Then, we show that this MLN has small-world and scale-free properties of a complex network. According to the structural characteristics of the MLN, we adopt two methods to further identify the potential relevant literature in addition to the retrieved literature. By integrating these potential papers into the MLN, a more comprehensive MLN is built to answer the question of actual patient records. Furthermore, we propose a re-ranking model to sort all papers by relevance. We experimentally find that the re-ranking model can improve the normalized discounted cumulative gain of the results. As participants of the Text Retrieval Conference 2015, our clinical-decision method based on the MLN also yields higher scores than the medians in most topics and achieves the best scores for topics: #11 and #12. These research results indicate that our study can be used to effectively assist clinicians in making clinical decisions, and the MLN can facilitate the investigation of CDS.

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

    OpenAIRE

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

    1999-01-01

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

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

    OpenAIRE

    Kilsdonk, E.

    2016-01-01

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

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

    OpenAIRE

    Giannessi, Massimo

    2010-01-01

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

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

    OpenAIRE

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

    2011-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  4. Clinical Decision Support for Whole Genome Sequence Information Leveraging a Service-Oriented Architecture: a Prototype

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2009-01-01

    There are two essential reasons for the slow progress in the acceptance of clinical case retrieval and similarity search-based decision support systems; the especial complexity of clinical data making it difficult to define a meaningful and effective distance function on them and the lack of transparency and explanation ability in many existing clinical case retrieval decision support systems. In this paper, we try to address these two problems by introducing a novel technique for visualizing inter-patient similarity based on a node-link representation with neighborhood graphs and by considering two techniques for learning discriminative distance function that help to combine the power of strong "black box" learners with the transparency of case retrieval and nearest neighbor classification. PMID:19964399

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-03-01

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

  11. Support and Assessment for Fall Emergency Referrals (SAFER 1): Cluster Randomised Trial of Computerised Clinical Decision Support for Paramedics

    OpenAIRE

    Helen Anne Snooks; Ben Carter; Jeremy Dale; Theresa Foster; Ioan Humphreys; Philippa Anne Logan; Ronan Anthony Lyons; Suzanne Margaret Mason; Ceri James Phillips; Antonio Sanchez; Mushtaq Wani; Alan Watkins; Bridget Elizabeth Wells; Richard Whitfield; Ian Trevor Russell

    2014-01-01

    Objective To evaluate effectiveness, safety and cost-effectiveness of Computerised Clinical Decision Support (CCDS) for paramedics attending older people who fall. Design Cluster trial randomised by paramedic; modelling. Setting 13 ambulance stations in two UK emergency ambulance services. Participants 42 of 409 eligible paramedics, who attended 779 older patients for a reported fall. Interventions Intervention paramedics received CCDS on Tablet computers to guide patient care. Control parame...

  12. Discriminative distance functions and the patient neighborhood graph for clinical decision support.

    Science.gov (United States)

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

    2010-01-01

    There are two essential reasons for the slow progress in the acceptance of clinical similarity search-based decision support systems (DSSs); the especial complexity of biomedical data making it difficult to define a meaningful and effective distance function and the lack of transparency and explanation ability in many existing DSSs. In this chapter, we address these two problems by introducing a novel technique for visualizing patient similarity with neighborhood graphs and by considering two techniques for learning discriminative distance functions. We present an experimental study and discuss our implementation of similarity visualization within a clinical DSS. PMID:20865536

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

    Directory of Open Access Journals (Sweden)

    Wu Helen W

    2012-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Casey Lynnette Overby

    2014-02-01

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

  15. Constructing Clinical Decision Support Systems for Adverse Drug Event Prevention: A Knowledge-based Approach.

    Science.gov (United States)

    Koutkias, Vassilis; Kilintzis, Vassilis; Stalidis, George; Lazou, Katerina; Collyda, Chrysa; Chazard, Emmanuel; McNair, Peter; Beuscart, Regis; Maglaveras, Nicos

    2010-11-13

    A knowledge-based approach is proposed that is employed for the construction of a framework suitable for the management and effective use of knowledge on Adverse Drug Event (ADE) prevention. The framework has as its core part a Knowledge Base (KB) comprised of rule-based knowledge sources, that is accompanied by the necessary inference and query mechanisms to provide healthcare professionals and patients with decision support services in clinical practice, in terms of alerts and recommendations on preventable ADEs. The relevant Knowledge Based System (KBS) is developed in the context of the EU-funded research project PSIP (Patient Safety through Intelligent Procedures in Medication). In the current paper, we present the foundations of the framework, its knowledge model and KB structure, as well as recent progress as regards the population of the KB, the implementation of the KBS, and results on the KBS verification in decision support operation.

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

    CERN Document Server

    Bennett, Casey; Selove, Rebecca

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Zhou Li

    2012-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Vivek Patkar

    2011-01-01

    Full Text Available Multidisciplinary team (MDT model in cancer care was introduced and endorsed to ensure that care delivery is consistent with the best available evidence. Over the last few years, regular MDT meetings have become a standard practice in oncology and gained the status of the key decision-making forum for patient management. Despite the fact that cancer MDT meetings are well accepted by clinicians, concerns are raised over the paucity of good-quality evidence on their overall impact. There are also concerns over lack of the appropriate support for this important but overburdened decision-making platform. The growing acceptance by clinical community of the health information technology in recent years has created new opportunities and possibilities of using advanced clinical decision support (CDS systems to realise full potential of cancer MDT meetings. In this paper, we present targeted summary of the available evidence on the impact of cancer MDT meetings, discuss the reported challenges, and explore the role that a CDS technology could play in addressing some of these challenges.

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

    International Nuclear Information System (INIS)

    Multidisciplinary team (MDT) model in cancer care was introduced and endorsed to ensure that care delivery is consistent with the best available evidence. Over the last few years, regular MDT meetings have become a standard practice in oncology and gained the status of the key decision-making forum for patient management. Despite the fact that cancer MDT meetings are well accepted by clinicians, concerns are raised over the paucity of good-quality evidence on their overall impact. There are also concerns over lack of the appropriate support for this important but overburdened decision-making platform. The growing acceptance by clinical community of the health information technology in recent years has created new opportunities and possibilities of using advanced clinical decision support (CDS) systems to realise full potential of cancer MDT meetings. In this paper, we present targeted summary of the available evidence on the impact of cancer MDT meetings, discuss the reported challenges, and explore the role that a CDS technology could play in addressing some of these challenges

  20. Mobile Clinical Decision Support Systems in Our Hands - Great Potential but also a Concern.

    Science.gov (United States)

    Masic, Izet; Begic, Edin

    2016-01-01

    Due to the powerful computer resources as well as the availability of today's mobile devices, a special field of mobile systems for clinical decision support in medicine has been developed. The benefits of these applications (systems) are: availability of necessary hardware (mobile phones, tablets and phablets are widespread, and can be purchased at a relatively affordable price), availability of mobile applications (free or for a "small" amount of money) and also mobile applications are tailored for easy use and save time of clinicians in their daily work. In these systems lies a huge potential, and certainly a great economic benefit, so this issue must be approached multidisciplinary. PMID:27350467

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

    Science.gov (United States)

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

    1998-06-01

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

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

    Science.gov (United States)

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

    2008-01-01

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

  3. Mobile Clinical Decision Support Systems in Our Hands - Great Potential but also a Concern.

    Science.gov (United States)

    Masic, Izet; Begic, Edin

    2016-01-01

    Due to the powerful computer resources as well as the availability of today's mobile devices, a special field of mobile systems for clinical decision support in medicine has been developed. The benefits of these applications (systems) are: availability of necessary hardware (mobile phones, tablets and phablets are widespread, and can be purchased at a relatively affordable price), availability of mobile applications (free or for a "small" amount of money) and also mobile applications are tailored for easy use and save time of clinicians in their daily work. In these systems lies a huge potential, and certainly a great economic benefit, so this issue must be approached multidisciplinary.

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

    Directory of Open Access Journals (Sweden)

    Clark Michael E

    2010-04-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

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

    Science.gov (United States)

    Wu, Dehua

    2016-01-01

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

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

    Science.gov (United States)

    Wu, Dehua

    2016-01-01

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

  8. A conceptual framework and protocol for defining clinical decision support objectives applicable to medical specialties

    Directory of Open Access Journals (Sweden)

    Timbie Justin W

    2012-09-01

    Full Text Available Abstract Background The U.S. Centers for Medicare and Medicaid Services established the Electronic Health Record (EHR Incentive Program in 2009 to stimulate the adoption of EHRs. One component of the program requires eligible providers to implement clinical decision support (CDS interventions that can improve performance on one or more quality measures pre-selected for each specialty. Because the unique decision-making challenges and existing HIT capabilities vary widely across specialties, the development of meaningful objectives for CDS within such programs must be supported by deliberative analysis. Design We developed a conceptual framework and protocol that combines evidence review with expert opinion to elicit clinically meaningful objectives for CDS directly from specialists. The framework links objectives for CDS to specialty-specific performance gaps while ensuring that a workable set of CDS opportunities are available to providers to address each performance gap. Performance gaps may include those with well-established quality measures but also priorities identified by specialists based on their clinical experience. Moreover, objectives are not constrained to performance gaps with existing CDS technologies, but rather may include those for which CDS tools might reasonably be expected to be developed in the near term, for example, by the beginning of Stage 3 of the EHR Incentive program. The protocol uses a modified Delphi expert panel process to elicit and prioritize CDS meaningful use objectives. Experts first rate the importance of performance gaps, beginning with a candidate list generated through an environmental scan and supplemented through nominations by panelists. For the highest priority performance gaps, panelists then rate the extent to which existing or future CDS interventions, characterized jointly as “CDS opportunities,” might impact each performance gap and the extent to which each CDS opportunity is compatible with

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Ash Joan S

    2012-02-01

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

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

    Science.gov (United States)

    Dolan, James G

    2010-01-01

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

  12. Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine.

    Science.gov (United States)

    Castaneda, Christian; Nalley, Kip; Mannion, Ciaran; Bhattacharyya, Pritish; Blake, Patrick; Pecora, Andrew; Goy, Andre; Suh, K Stephen

    2015-01-01

    , and logistical concerns. Ensuring data security and protection of patient rights while simultaneously facilitating standardization is paramount to maintaining public support. The capabilities of supercomputing need to be applied strategically. A standardized, methodological implementation must be applied to developed artificial intelligence systems with the ability to integrate data and information into clinically relevant knowledge. Ultimately, the integration of bioinformatics and clinical data in a clinical decision support system promises precision medicine and cost effective and personalized patient care.

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

    Science.gov (United States)

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

    2014-12-01

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

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

    DEFF Research Database (Denmark)

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

    2011-01-01

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

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

    LENUS (Irish Health Repository)

    Collins, I M

    2012-03-02

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

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

    Science.gov (United States)

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

    2016-06-01

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

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

    Science.gov (United States)

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

    2012-01-01

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

  18. Clinical Information System Services and Capabilities Desired for Scalable, Standards-Based, Service-oriented Decision Support: Consensus Assessment of the Health Level 7 Clinical Decision Support Work Group

    Science.gov (United States)

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

    2012-01-01

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

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

    Science.gov (United States)

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

    2012-01-01

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

  20. Decision support basics

    CERN Document Server

    Power, Daniel J

    2009-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  2. Evaluating acceptance and user experience of a guideline-based clinical decision support system execution platform.

    Science.gov (United States)

    Buenestado, David; Elorz, Javier; Pérez-Yarza, Eduardo G; Iruetaguena, Ander; Segundo, Unai; Barrena, Raúl; Pikatza, Juan M

    2013-04-01

    This study aims to determine what the initial disposition of physicians towards the use of Clinical Decision Support Systems (CDSS) based on Computerised Clinical Guidelines and Protocols (CCGP) is; and whether their prolonged utilisation has a positive effect on their intention to adopt them in the future. For a period of 3 months, 8 volunteer paediatricians monitored each up to 10 asthmatic patients using two CCGPs deployed in the-GuidesMed CDSS. A Technology Acceptance Model (TAM) questionnaire was supplied to them before and after using the system. Results from both questionnaires are analysed searching for significant improvements in opinion between them. An additional survey was performed to analyse the usability of the system. It was found that initial disposition of physicians towards e-GuidesMed is good. Improvement between the pre and post iterations of the TAM questionnaire has been found to be statistically significant. Nonetheless, slightly lower values in the Compatibility and Habit variables show that participants perceive possible difficulties to integrate e-GuidesMed into their daily routine. The variable Facilitators shows the highest correlation with the Intention to Use. Usability of the system has also been rated very high and, in this regard, no fundamental flaw has been detected. Initial views towards e-GuidesMed are positive, and become reinforced after continued utilisation of the system. In order to achieve an effective implementation, it becomes essential to facilitate conditions to integrate the system into the physician's daily routine.

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

    Science.gov (United States)

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

    2016-09-01

    Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders. Methods We used Arksey and O'Malley's scoping review framework which progresses through five stages: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses multiple disciplines, we searched health care, computing science and business databases. Results Our search resulted in 4605 manuscripts. Titles and abstracts were screened for relevance. The reliability of the screening process was high with an average percentage of agreement of 92.3 %. Of the located articles, 123 were considered relevant. Within this literature, there were 43 CDS tools located. These were classified into 3 main areas: computer-based tools/questionnaires (n = 8, 19 %), treatment algorithms/models (n = 14, 33 %), and clinical prediction rules/classification systems (n = 21, 49 %). Each of these areas and the associated evidence are described. The state of evidentiary support for CDS tools is still preliminary and lacks external validation, head-to-head comparisons, or evidence of generalizability across different populations and settings. Conclusions CDS tools, especially those employing rapidly advancing computer technologies, are under development and of potential interest to health care providers, case management organizations and funders of care. Based on the results of this scoping review, we conclude that these tools, models and systems should be subjected to further validation before they can be recommended for large-scale implementation for managing patients with MSK disorders. PMID:26667939

  4. Formative assessment and design of a complex clinical decision support tool for pulmonary embolism.

    Science.gov (United States)

    Khan, Sundas; McCullagh, Lauren; Press, Anne; Kharche, Manish; Schachter, Andy; Pardo, Salvatore; McGinn, Thomas

    2016-02-01

    Electronic health record (EHR)-based clinical decision support (CDS) tools are rolled out with the urgency to meet federal requirements without time for usability testing and refinement of the user interface. As part of a larger project to design, develop and integrate a pulmonary embolism CDS tool for emergency physicians, we conducted a formative assessment to determine providers' level of interest and input on designs and content. This was a study to conduct a formative assessment of emergency medicine (EM) physicians that included focus groups and key informant interviews. The focus of this study was twofold, to determine the general attitude towards CDS tool integration and the ideal integration point into the clinical workflow. To accomplish this, we first approached EM physicians in a focus group, then, during key informant interviews, we presented workflow designs and gave a scenario to help the providers visualise how the CDS tool works. Participants were asked questions regarding the trigger location, trigger words, integration into their workflow, perceived utility and heuristic of the tool. Results from the participants' survey responses to trigger location, perceived utility and efficiency, indicated that the providers felt the tool would be more of a hindrance than an aid. However, some providers commented that they had not had exposure to CDS tools but had used online calculators, and thought the tools would be helpful at the point-of-care if integrated into the EHR. Furthermore, there was a preference for an order entry wireframe. This study highlights several factors to consider when designing CDS tools: (1) formative assessment of EHR functionality and clinical environment workflow, (2) focus groups and key informative interviews to incorporate providers' perceptions of CDS and workflow integration and/or (3) the demonstration of proposed workflows through wireframes to help providers visualise design concepts.

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

    Directory of Open Access Journals (Sweden)

    Weise-Kelly Lorraine

    2011-08-01

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

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

    Science.gov (United States)

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

    2016-03-01

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

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

    International Nuclear Information System (INIS)

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

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

    Directory of Open Access Journals (Sweden)

    Ali Mohammad Hadianfard

    2015-04-01

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

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

    OpenAIRE

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

    2014-01-01

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

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

    OpenAIRE

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

    2013-01-01

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

  11. Usability evaluation of a clinical decision support tool for osteoporosis disease management

    Directory of Open Access Journals (Sweden)

    Newton David

    2010-12-01

    Full Text Available Abstract Background Osteoporosis affects over 200 million people worldwide at a high cost to healthcare systems. Although guidelines are available, patients are not receiving appropriate diagnostic testing or treatment. Findings from a systematic review of osteoporosis interventions and a series of focus groups were used to develop a functional multifaceted tool that can support clinical decision-making in osteoporosis disease management at the point of care. The objective of our study was to assess how well the prototype met functional goals and usability needs. Methods We conducted a usability study for each component of the tool--the Best Practice Recommendation Prompt (BestPROMPT, the Risk Assessment Questionnaire (RAQ, and the Customised Osteoporosis Education (COPE sheet--using the framework described by Kushniruk and Patel. All studies consisted of one-on-one sessions with a moderator using a standardised worksheet. Sessions were audio- and video-taped and transcribed verbatim. Data analysis consisted of a combination of qualitative and quantitative analyses. Results In study 1, physicians liked that the BestPROMPT can provide customised recommendations based on risk factors identified from the RAQ. Barriers included lack of time to use the tool, the need to alter clinic workflow to enable point-of-care use, and that the tool may disrupt the real reason for the visit. In study 2, patients completed the RAQ in a mean of 6 minutes, 35 seconds. Of the 42 critical incidents, 60% were navigational and most occurred when the first nine participants were using the stylus pen; no critical incidents were observed with the last six participants that used the touch screen. Patients thought that the RAQ questions were easy to read and understand, but they found it difficult to initiate the questionnaire. Suggestions for improvement included improving aspects of the interface and navigation. The results of study 3 showed that most patients were able

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

    OpenAIRE

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

    2001-01-01

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

  13. Usability of clinical decision support system as a facilitator for learning the assistive technology adaptation process.

    Science.gov (United States)

    Danial-Saad, Alexandra; Kuflik, Tsvi; Weiss, Patrice L Tamar; Schreuer, Naomi

    2016-01-01

    The aim of this study was to evaluate the usability of Ontology Supported Computerized Assistive Technology Recommender (OSCAR), a Clinical Decision Support System (CDSS) for the assistive technology adaptation process, its impact on learning the matching process, and to determine the relationship between its usability and learnability. Two groups of expert and novice clinicians (total, n = 26) took part in this study. Each group filled out system usability scale (SUS) to evaluate OSCAR's usability. The novice group completed a learning questionnaire to assess OSCAR's effect on their ability to learn the matching process. Both groups rated OSCAR's usability as "very good", (M [SUS] = 80.7, SD = 11.6, median = 83.7) by the novices, and (M [SUS] = 81.2, SD = 6.8, median = 81.2) by the experts. The Mann-Whitney results indicated that no significant differences were found between the expert and novice groups in terms of OSCAR's usability. A significant positive correlation existed between the usability of OSCAR and the ability to learn the adaptation process (rs = 0.46, p = 0.04). Usability is an important factor in the acceptance of a system. The successful application of user-centered design principles during the development of OSCAR may serve as a case study that models the significant elements to be considered, theoretically and practically in developing other systems. Implications for Rehabilitation Creating a CDSS with a focus on its usability is an important factor for its acceptance by its users. Successful usability outcomes can impact the learning process of the subject matter in general, and the AT prescription process in particular. The successful application of User-Centered Design principles during the development of OSCAR may serve as a case study that models the significant elements to be considered, theoretically and practically. The study emphasizes the importance of close collaboration between the developers and

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

    Directory of Open Access Journals (Sweden)

    Wilczynski Nancy L

    2010-02-01

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

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Helen Anne Snooks

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

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

    Directory of Open Access Journals (Sweden)

    Yang Zhang

    2012-01-01

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

  18. Decision Support for Radiologists

    Directory of Open Access Journals (Sweden)

    M. Fatehi

    2005-08-01

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

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

    Science.gov (United States)

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

    2016-08-01

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

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

    Science.gov (United States)

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

    2016-05-01

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

  1. A Belief Rule-Based (BRB) Decision Support System for Assessing Clinical Asthma Suspicion

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Hossain, Emran; Khalid, Md. Saifuddin;

    2014-01-01

    Asthma is a common chronic disease that affects millions of people around the world. The most common signs and symptoms of asthma are cough; breathlessness; wheeze; chest tightness and respiratory rate. They cannot be measured accurately since they consist of various types of uncertainty such as ......Asthma is a common chronic disease that affects millions of people around the world. The most common signs and symptoms of asthma are cough; breathlessness; wheeze; chest tightness and respiratory rate. They cannot be measured accurately since they consist of various types of uncertainty...... such as vagueness; imprecision; randomness; ignorance and incompleteness. Consequently; traditional disease diagnosis; which is performed by a physician; cannot deliver accurate results. Therefore; this paper presents the design; development and application of a decision support system for assessing asthma under...... conditions of uncertainty. The Belief Rule-Based Inference Methodology Using the Evidential Reasoning (RIMER) approach was adopted to develop this expert system; which is named the Belief Rule-Based Expert System (BRBES). The system can handle various types of uncertainty in knowledge representation...

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

    Directory of Open Access Journals (Sweden)

    Caricia Catalani

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  5. Decision support systems

    DEFF Research Database (Denmark)

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

    2007-01-01

    system Crop Protection Online is widely used by advisors and as a learning tool for students. Although the system has been validated in many field trials over the years and has shown reliable results, the number of end-users among farmers has been relatively low during the last 10 years (approximately...... 1000 farmers). A sociological investigation of farmers' decision-making styles in the area of crop protection has shown that arable farmers can be divided into three major groups: (a) system-orientated farmers, (b) experience-based farmers and (c) advisory-orientated farmers. The information required......The highly complex knowledge of scientific disciplines makes nuanced analysis and modelling possible. However, the information produced often does not reach farmers because it is presented in a way that does not correspond to the way their work is carried out in practice. The decision support...

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

    Science.gov (United States)

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

    2016-09-01

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

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

    Science.gov (United States)

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

    2016-08-01

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

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

    Science.gov (United States)

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

    2016-08-01

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

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

    Science.gov (United States)

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

    2013-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Sahota Navdeep

    2011-08-01

    Full Text Available Abstract Background Acute medical care often demands timely, accurate decisions in complex situations. Computerized clinical decision support systems (CCDSSs have many features that could help. However, as for any medical intervention, claims that CCDSSs improve care processes and patient outcomes need to be rigorously assessed. The objective of this review was to systematically review the effects of CCDSSs on process of care and patient outcomes for acute medical care. Methods We conducted a decision-maker-researcher partnership systematic review. MEDLINE, EMBASE, Evidence-Based Medicine Reviews databases (Cochrane Database of Systematic Reviews, DARE, ACP Journal Club, and others, and the Inspec bibliographic database were searched to January 2010, in all languages, for randomized controlled trials (RCTs of CCDSSs in all clinical areas. We included RCTs that evaluated the effect on process of care or patient outcomes of a CCDSS used for acute medical care compared with care provided without a CCDSS. A study was considered to have a positive effect (i.e., CCDSS showed improvement if at least 50% of the relevant study outcomes were statistically significantly positive. Results Thirty-six studies met our inclusion criteria for acute medical care. The CCDSS improved process of care in 63% (22/35 of studies, including 64% (9/14 of medication dosing assistants, 82% (9/11 of management assistants using alerts/reminders, 38% (3/8 of management assistants using guidelines/algorithms, and 67% (2/3 of diagnostic assistants. Twenty studies evaluated patient outcomes, of which three (15% reported improvements, all of which were medication dosing assistants. Conclusion The majority of CCDSSs demonstrated improvements in process of care, but patient outcomes were less likely to be evaluated and far less likely to show positive results.

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

    Directory of Open Access Journals (Sweden)

    Sindhu Ravindran

    2015-01-01

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

  12. An RDF/OWL knowledge base for query answering and decision support in clinical pharmacogenetics.

    Science.gov (United States)

    Samwald, Matthias; Freimuth, Robert; Luciano, Joanne S; Lin, Simon; Powers, Robert L; Marshall, M Scott; Adlassnig, Klaus-Peter; Dumontier, Michel; Boyce, Richard D

    2013-01-01

    Genetic testing for personalizing pharmacotherapy is bound to become an important part of clinical routine. To address associated issues with data management and quality, we are creating a semantic knowledge base for clinical pharmacogenetics. The knowledge base is made up of three components: an expressive ontology formalized in the Web Ontology Language (OWL 2 DL), a Resource Description Framework (RDF) model for capturing detailed results of manual annotation of pharmacogenomic information in drug product labels, and an RDF conversion of relevant biomedical datasets. Our work goes beyond the state of the art in that it makes both automated reasoning as well as query answering as simple as possible, and the reasoning capabilities go beyond the capabilities of previously described ontologies.

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

    OpenAIRE

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2016-03-01

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

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

    Science.gov (United States)

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

    2016-03-01

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

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses...... multiple disciplines, we searched health care, computing science and business databases. Results Our search resulted in 4605 manuscripts. Titles and abstracts were screened for relevance. The reliability of the screening process was high with an average percentage of agreement of 92.3 %. Of the located...... articles, 123 were considered relevant. Within this literature, there were 43 CDS tools located. These were classified into 3 main areas: computer-based tools/questionnaires (n = 8, 19 %), treatment algorithms/models (n = 14, 33 %), and clinical prediction rules/classification systems (n = 21, 49 %). Each...

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

    Science.gov (United States)

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

    2016-04-01

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

  18. Perceived barriers of heart failure nurses and cardiologists in using clinical decision support systems in the treatment of heart failure patients

    NARCIS (Netherlands)

    de Vries, Arjen E.; van der Wal, Martje H. L.; Nieuwenhuis, Maurice M. W.; de Jong, Richard M.; van Dijk, Rene B.; Jaarsma, Tiny; Hillege, Hans L.; Jorna, Rene J.

    2013-01-01

    Background: Clinical Decision Support Systems (CDSSs) can support guideline adherence in heart failure (HF) patients. However, the use of CDSSs is limited and barriers in working with CDSSs have been described as a major obstacle. It is unknown if barriers to CDSSs are present and differ between HF

  19. Decision support for participatory wetland decision-making

    NARCIS (Netherlands)

    Goosen, H.; Janssen, R.H.H.; Vermaat, J.E.

    2007-01-01

    Decision support systems can be helpful tools in wetland planning and management. Decision support systems can contribute to efficient exchange of information between experts, stakeholders, decision makers and laypeople. However, the achievements of decision support systems are repeatedly being repo

  20. Clinical Decision Support and Closed-Loop Control for Cardiopulmonary Management and Intensive Care Unit Sedation Using Expert Systems.

    Science.gov (United States)

    Gholami, Behnood; Bailey, James M; Haddad, Wassim M; Tannenbaum, Allen R

    2012-03-01

    Patients in the intensive care unit (ICU) who require mechanical ventilation due to acute respiratory failure also frequently require the administration of sedative agents. The need for sedation arises both from patient anxiety due to the loss of personal control and the unfamiliar and intrusive environment of the ICU, and also due to pain or other variants of noxious stimuli. While physicians select the agent(s) used for sedation and cardiovascular function, the actual administration of these agents is the responsibility of the nursing staff. If clinical decision support systems and closed-loop control systems could be developed for critical care monitoring and lifesaving interventions as well as the administration of sedation and cardiopulmonary management, the ICU nurse could be released from the intense monitoring of sedation, allowing her/him to focus on other critical tasks. One particularly attractive strategy is to utilize the knowledge and experience of skilled clinicians, capturing explicitly the rules expert clinicians use to decide on how to titrate drug doses depending on the level of sedation. In this paper, we extend the deterministic rule-based expert system for cardiopulmonary management and ICU sedation framework presented in [1] to a stochastic setting by using probability theory to quantify uncertainty and hence deal with more realistic clinical situations.

  1. Shared clinical decision making

    Science.gov (United States)

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

    2015-01-01

    Objectives: To determine preferences of patients regarding their involvement in the clinical decision making process and the related factors in Saudi Arabia. Methods: This cross-sectional study was conducted in a major family practice center in King Abdulaziz Medical City, Riyadh, Saudi Arabia, between March and May 2012. Multivariate multinomial regression models were fitted to identify factors associated with patients preferences. Results: The study included 236 participants. The most preferred decision-making style was shared decision-making (57%), followed by paternalistic (28%), and informed consumerism (14%). The preference for shared clinical decision making was significantly higher among male patients and those with higher level of education, whereas paternalism was significantly higher among older patients and those with chronic health conditions, and consumerism was significantly higher in younger age groups. In multivariate multinomial regression analysis, compared with the shared group, the consumerism group were more likely to be female [adjusted odds ratio (AOR) =2.87, 95% confidence interval [CI] 1.31-6.27, p=0.008] and non-dyslipidemic (AOR=2.90, 95% CI: 1.03-8.09, p=0.04), and the paternalism group were more likely to be older (AOR=1.03, 95% CI: 1.01-1.05, p=0.04), and female (AOR=2.47, 95% CI: 1.32-4.06, p=0.008). Conclusion: Preferences of patients for involvement in the clinical decision-making varied considerably. In our setting, underlying factors that influence these preferences identified in this study should be considered and tailored individually to achieve optimal treatment outcomes. PMID:26620990

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

    CERN Document Server

    Bouzguenda, Lotfi

    2012-01-01

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

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

    OpenAIRE

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

    2016-01-01

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

  4. An Intelligent Clinical Decision Support System for Patient-Specific Predictions to Improve Cervical Intraepithelial Neoplasia Detection

    Directory of Open Access Journals (Sweden)

    Panagiotis Bountris

    2014-01-01

    Full Text Available Nowadays, there are molecular biology techniques providing information related to cervical cancer and its cause: the human Papillomavirus (HPV, including DNA microarrays identifying HPV subtypes, mRNA techniques such as nucleic acid based amplification or flow cytometry identifying E6/E7 oncogenes, and immunocytochemistry techniques such as overexpression of p16. Each one of these techniques has its own performance, limitations and advantages, thus a combinatorial approach via computational intelligence methods could exploit the benefits of each method and produce more accurate results. In this article we propose a clinical decision support system (CDSS, composed by artificial neural networks, intelligently combining the results of classic and ancillary techniques for diagnostic accuracy improvement. We evaluated this method on 740 cases with complete series of cytological assessment, molecular tests, and colposcopy examination. The CDSS demonstrated high sensitivity (89.4%, high specificity (97.1%, high positive predictive value (89.4%, and high negative predictive value (97.1%, for detecting cervical intraepithelial neoplasia grade 2 or worse (CIN2+. In comparison to the tests involved in this study and their combinations, the CDSS produced the most balanced results in terms of sensitivity, specificity, PPV, and NPV. The proposed system may reduce the referral rate for colposcopy and guide personalised management and therapeutic interventions.

  5. Decision support for emergency management

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

    Carney, Timothy Jay

    2012-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sang Youn; Moon, Sung Kyoung; Hwang, Sung Il; Sung, Chang Kyu; Cho, Jeong Yeon; Kim, Seung Hyup; Lee, Hak Jong [Seoul National University College of Medicine, Seoul (Korea, Republic of); Jung, Dae Chul [National Cancer Center, Ilsan (Korea, Republic of); Lee, Ji Won [Kangwon National University College of Medicine, Chuncheon (Korea, Republic of)

    2011-10-15

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

  8. Perceived barriers of heart failure nurses and cardiologists in using clinical decision support systems in the treatment of heart failure patients

    OpenAIRE

    Vries, Arjen E. de; van der Wal, Martje H. L.; Nieuwenhuis, Maurice M. W.; Richard M. de Jong; Rene B. van Dijk; Jaarsma, Tiny; Hillege, Hans L; Jorna, Rene J.

    2013-01-01

    Background Clinical Decision Support Systems (CDSSs) can support guideline adherence in heart failure (HF) patients. However, the use of CDSSs is limited and barriers in working with CDSSs have been described as a major obstacle. It is unknown if barriers to CDSSs are present and differ between HF nurses and cardiologists. Therefore the aims of this study are; 1. Explore the type and number of perceived barriers of HF nurses and cardiologists to use a CDSS in the treatment of HF patients. 2. ...

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

    Directory of Open Access Journals (Sweden)

    Liang Wen-Miin

    2011-03-01

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

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

    Science.gov (United States)

    Seto, Ryoma; Wakabayashi, Susumu

    2015-01-01

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

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

    Science.gov (United States)

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

    2014-03-01

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

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

    Science.gov (United States)

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

    2016-02-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2011-08-01

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

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

    Science.gov (United States)

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

    2016-07-01

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

  16. Patient and primary care provider experience using a family health history collection, risk stratification, and clinical decision support tool: a type 2 hybrid controlled implementation-effectiveness trial

    OpenAIRE

    Wu, R. Ryanne; Orlando, Lori A.; Himmel, Tiffany L; Buchanan, Adam H; Powell, Karen P; Hauser, Elizabeth R.; Agbaje, Astrid B; Henrich, Vincent C.; Ginsburg, Geoffrey S.

    2013-01-01

    Background Family health history (FHH) is the single strongest predictor of disease risk and yet is significantly underutilized in primary care. We developed a patient facing FHH collection tool, MeTree©, that uses risk stratification to generate clinical decision support for breast cancer, colorectal cancer, ovarian cancer, hereditary cancer syndromes, and thrombosis. Here we present data on the experience of patients and providers after integration of MeTree© into 2 primary care practices. ...

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

    Directory of Open Access Journals (Sweden)

    Pruszydlo Markus G

    2012-11-01

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

  18. Platform decisions supported by gaming

    DEFF Research Database (Denmark)

    Hansen, Poul H. Kyvsgård; Mikkola, Juliana Hsuan

    2007-01-01

    be described as being a configuration problem with a high number of variables. These variables are different in nature; they have contradictory influence on the total performance, and, their importance change over time. Consequently, the specific platform decisions become highly complex and the consequences...... support to the platform decision making.......Platform is an ambiguous multidisciplinary concept. The philosophy behind it is easy to communicate and makes intuitively sense. However, the ease in communication does overshadow the high complexity when the concept is implemented. The practical industrial platform implementation challenge can...

  19. EVALUATING ENVIRONMENTAL DECISION SUPPORT TOOLS.

    Energy Technology Data Exchange (ETDEWEB)

    SULLIVAN, T.

    2004-10-01

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

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

    OpenAIRE

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

    1998-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Sunderajan Prabha

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Singer Jesse

    2011-09-01

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

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

    Directory of Open Access Journals (Sweden)

    O'Brien Timothy

    2010-01-01

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

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

    Science.gov (United States)

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

    2016-06-01

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

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

    NARCIS (Netherlands)

    B. Nannings; A. Abu-Hanna

    2006-01-01

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

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

    Science.gov (United States)

    Robson, Barry; Boray, Srinidhi

    2016-06-01

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

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

    Science.gov (United States)

    Robson, Barry; Boray, Srinidhi

    2016-06-01

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

  8. Integrating clinical research into clinical decision making

    Directory of Open Access Journals (Sweden)

    Mark R Tonelli

    2011-01-01

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

  9. Decision Support for effective production control

    DEFF Research Database (Denmark)

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

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Sambasivan Murali

    2012-12-01

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

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

    Science.gov (United States)

    Zhao, Kun; Qiu, Fasheng; Chen, Guantao

    2013-12-20

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

  12. Estimating the Horizon of articles to decide when to stop searching in systematic reviews: an example using a systematic review of RCTs evaluating osteoporosis clinical decision support tools.

    Science.gov (United States)

    Kastner, Monika; Straus, Sharon; Goldsmith, Charlie H

    2007-10-11

    Researchers conducting systematic reviews need to search multiple bibliographic databases such as MEDLINE and EMBASE. However, researchers have no rational search stopping rule when looking for potentially-relevant articles. We empirically tested a stopping rule based on the concept of capture-mark-recapture (CMR), which was first pioneered in ecology. The principles of CMR can be adapted to systematic reviews and meta-analyses to estimate the Horizon of articles in the literature with its confidence interval. We retrospectively tested this Horizon Estimation using a systematic review of randomized controlled trials (RCTs) that evaluated clinical decision support tools for osteoporosis disease management. The Horizon Estimation was calculated based on 4 bibliographic databases that were included as the main data sources for the review in the following order: MEDLINE, EMBASE, CINAHL, and EBM Reviews. The systematic review captured 68% of known articles from the 4 data sources, which represented 592 articles that were estimated as missing from the Horizon.

  13. Integrating Decision Support and Social Networks

    Directory of Open Access Journals (Sweden)

    Francisco Antunes

    2012-01-01

    Full Text Available We elaborate on the shifting of decision support systems towards social networking, which is based on the concepts of Web 2.0 and Semantic Web technology. As the characteristics of the relevant components are different from traditional decision support systems, we present necessary adaptations when adopting social networks for decision support within an organization. We also present organizational obstacles when adopting/using such systems and clues to overcome them.

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

    OpenAIRE

    Wang, Jingyi

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Simon Fong

    2013-01-01

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

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

    CERN Document Server

    Cabrera, Mariana Maceiras

    2010-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Boghean Florin

    2015-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Alagiakrishnan K

    2016-01-01

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

  19. Marketing Decision Support Systemen in kort bestek

    NARCIS (Netherlands)

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

    1991-01-01

    textabstractVoor u liggen de uitkomsten van een onderzoek over marketing decision support systemen bij Nederlandse bedrijven. Bij marketing decision support systemen worden de mogelijkbeden die de moderne informaticatechnologie biedt, aangewend ten behoeve van het marketing management. Door de toena

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

    Directory of Open Access Journals (Sweden)

    Wanyenze Rhoda K

    2013-02-01

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

  1. Clinical practice guidelines and patient decision aids. An inevitable relationship.

    NARCIS (Netherlands)

    Weijden, T. van der; Boivin, A.; Burgers, J.S.; Schunemann, H.J.; Elwyn, G.

    2012-01-01

    As health professionals and patients are moving toward shared models of decision making, there is a growing need for integrated decision support tools that facilitate uptake of best evidence in routine clinical practice in a patient-centered manner. This article charts the landscape of clinical prac

  2. Indonesian Earthquake Decision Support System

    OpenAIRE

    Warnars, Spits

    2010-01-01

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

  3. Using Visualization in Cockpit Decision Support Systems

    Energy Technology Data Exchange (ETDEWEB)

    Aragon, Cecilia R.

    2005-07-01

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

  4. Decision support, analytics, and business intelligence

    CERN Document Server

    Power, Daniel J

    2013-01-01

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

  5. Effects of a computerized provider order entry and a clinical decision support system to improve cefazolin use in surgical prophylaxis: a cost saving analysis

    Directory of Open Access Journals (Sweden)

    Okumura LM

    2016-10-01

    Full Text Available Background: Computerized Provider Order Entry (CPOE and Clinical Decision Support System (CDSS help practitioners to choose evidence-based decisions, regarding patients’ needs. Despite its use in developed countries, in Brazil, the impact of a CPOE/CDSS to improve cefazolin use in surgical prophylaxis was not assessed yet. Objective: We aimed to evaluate the impact of a CDSS to improve the use of prophylactic cefazolin and to assess the cost savings associated to inappropriate prescribing. Methods: This is a cross-sectional study that compared two different scenarios: one prior CPOE/CDSS versus after software implementation. We conducted twelve years of data analysis (3 years prior and 9 years after CDSS implementation, where main outcomes from this study included: cefazolin Defined Daily Doses/100 bed-days (DDD, crude costs and product of costs-DDD (cost-DDD/100 bed-days. We applied a Spearman rho non-parametric test to assess the reduction of cefazolin consumption through the years. Results: In twelve years, 84,383 vials of cefazolin were dispensed and represented 38.89 DDD/100 bed-days or USD 44,722.99. Surgical wards were the largest drug prescribers and comprised >95% of our studied sample. While in 2002, there were 6.31 DDD/100 bed-days, 9 years later there was a reduction to 2.15 (p<0.05. In a scenario without CDSS, the hospital would have consumed 75.72 DDD/100 bed-days, which is equivalent to USD 116 998.07. It is estimated that CDSS provided USD 50,433.39 of cost savings. Conclusion: The implementation of a CPOE/CDSS helped to improve prophylactic cefazolin use by reducing its consumption and estimated direct costs.

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

    OpenAIRE

    Rok Rupnik; Matjaž Kukar

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Schmaltz Heidi N

    2010-10-01

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

  8. Evaluation of selected environmental decision support software

    International Nuclear Information System (INIS)

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

  9. Evaluation of selected environmental decision support software

    Energy Technology Data Exchange (ETDEWEB)

    Sullivan, T.M.; Moskowitz, P.D. [Brookhaven National Lab., Upton, NY (United States); Gitten, M. [Environmental Project Control, Maynard, MA (United States)

    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.

  10. Perceived barriers of heart failure nurses and cardiologists in using clinical decision support systems in the treatment of heart failure patients

    Science.gov (United States)

    2013-01-01

    Background Clinical Decision Support Systems (CDSSs) can support guideline adherence in heart failure (HF) patients. However, the use of CDSSs is limited and barriers in working with CDSSs have been described as a major obstacle. It is unknown if barriers to CDSSs are present and differ between HF nurses and cardiologists. Therefore the aims of this study are; 1. Explore the type and number of perceived barriers of HF nurses and cardiologists to use a CDSS in the treatment of HF patients. 2. Explore possible differences in perceived barriers between two groups. 3. Assess the relevance and influence of knowledge management (KM) on Responsibility/Trust (R&T) and Barriers/Threats (B&T). Methods A questionnaire was developed including; B&T, R&T, and KM. For analyses, descriptive techniques, 2-tailed Pearson correlation tests, and multiple regression analyses were performed. Results The response- rate of 220 questionnaires was 74%. Barriers were found for cardiologists and HF nurses in all the constructs. Sixty-five percent did not want to be dependent on a CDSS. Nevertheless thirty-six percent of HF nurses and 50% of cardiologists stated that a CDSS can optimize HF medication. No relationship between constructs and age; gender; years of work experience; general computer experience and email/internet were observed. In the group of HF nurses a positive correlation (r .33, PKM was associated with the constructs B&T (B=.55, P=barriers in working with a CDSS in all of the examined constructs. KM has a strong positive correlation with perceived barriers, indicating that increasing knowledge about CDSSs can decrease their barriers. PMID:23622342

  11. Indonesian Earthquake Decision Support System

    CERN Document Server

    Warnars, Spits

    2010-01-01

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

  12. Geospatial decision support systems for societal decision making

    Science.gov (United States)

    Bernknopf, R.L.

    2005-01-01

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

  13. A Geospatial Decision Support System Toolkit Project

    Data.gov (United States)

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

  14. A Marketing Decision Support System for Retailers

    OpenAIRE

    Leonard M. Lodish

    1982-01-01

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

  15. Marketing Decision Support Systemen in kort bestek

    OpenAIRE

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

    1991-01-01

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

  16. A Decision Support System for Supervised Assignment in Banking Decisions

    Science.gov (United States)

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

    This study presents a Decision Support System (DSS) which supports assignment of actions (e.g., numbers, projects, people etc.) into predefined categories according to their score on evaluation criteria. It implements a novel classification algorithm based on multicriteria analysis and fuzzy preference relations. More detailed, assignment to classes is based on the concept of category threshold, which defines at what degree an alternative can be included in a specific category. For each category a threshold is defined by the corresponding decision maker, which indicates its lower limit with respect to the evaluation criteria. Actions are then evaluated according to the criteria and fuzzy inclusion degrees are calculated for each category. Finally, an action is assigned to the category for which the inclusion degree is the maximum. The DSS implements the above classification algorithm, providing a user-friendly interface, which supports decision makers to formulate and solve similar problems. In addition to the DSS, we present a real world application at a classification problem within the environment of a Greek bank. Results derived from evaluation experiments in the business environment provide evidence that the proposed methodology and the DSS can effectively support decision makers in classification decisions. The methodology as well as the proposed DSS can be used to classification problems not only in financial domain but to a variety of domains such as production, environmental, or human resources.

  17. Solutions for decision support in university management

    Directory of Open Access Journals (Sweden)

    Andrei STANCIU

    2009-06-01

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

  18. Evaluating Ethical Responsibility in Inverse Decision Support

    Directory of Open Access Journals (Sweden)

    Ahmad M. Kabil

    2012-01-01

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

  19. Group decision support using Toulmin argument structures

    Energy Technology Data Exchange (ETDEWEB)

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

    1996-12-31

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

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

    Science.gov (United States)

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

    2016-01-01

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

  1. Biometric and intelligent decision making support

    CERN Document Server

    Kaklauskas, Arturas

    2015-01-01

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

  2. Legal Considerations in Clinical Decision Making.

    Science.gov (United States)

    Ursu, Samuel C.

    1992-01-01

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

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

    Directory of Open Access Journals (Sweden)

    John Fox

    2006-03-01

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

  4. Decision support system for vehicle scheduling

    Directory of Open Access Journals (Sweden)

    C. Gaindric

    1999-08-01

    Full Text Available A decision support system (DSS is described to form schedules of traffic from a central warehouse to a set of consumers by cyclic routes. The system may be used by dispatchers at transportation enterprises. The system structure, short description of modules, and algorithms solving the originating problems are presented.

  5. Nitrogenius: a nitrogen decision support system

    NARCIS (Netherlands)

    Erisman, J.W.; Hensen, A.; Vries, de W.; Kros, H.; Wal, van der T.; Winter, de W.; Wien, J.E.; Elswijk, van M.; Maat, M.; Sanders, K.

    2002-01-01

    A nitrogen decision support system in the form of a game (NitroGenius) was developed for the Second International Nitrogen Conference. The aims were to: i) improve understanding among scientists and policy makers about the complexity of nitrogen pollution problems in an area of intensive agricultura

  6. Decision support system for nursing management control

    Energy Technology Data Exchange (ETDEWEB)

    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.

  7. Decision Support and Knowledge-Based Systems.

    Science.gov (United States)

    Konsynski, Benn R.; And Others

    1988-01-01

    A series of articles addresses issues concerning decision support and knowledge based systems. Topics covered include knowledge-based systems for information centers; object oriented systems; strategic information systems case studies; user perception; manipulation of certainty factors by individuals and expert systems; spreadsheet program use;…

  8. Fault Isolation for Shipboard Decision Support

    DEFF Research Database (Denmark)

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

    2010-01-01

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

  9. The conceptual foundation of environmental decision support.

    Science.gov (United States)

    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.

  10. Using Information Aggregation Markets for Decision Support

    Directory of Open Access Journals (Sweden)

    Patrick Buckley

    2012-06-01

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

  11. Comparison of Alternative Processes for Support Decisions

    Directory of Open Access Journals (Sweden)

    Manuel Martínez-Álvarez

    2014-08-01

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

  12. Tsunami early warning and decision support

    Directory of Open Access Journals (Sweden)

    T. Steinmetz

    2010-09-01

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

  13. Personalized Clinical Decision Making in Gastrointestinal Malignancies

    DEFF Research Database (Denmark)

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

    2016-01-01

    and initial stages. This article outlines the potential use of fluorodeoxyglucose-PET/CT in clinical decision making with special regard to preoperative evaluation and response assessment in gastric cancer (including the gastroesophageal junction), pancreatic cancer (excluding neuroendocrine tumors...

  14. DECISION SUPPORT SYSTEMS FOR LOGISTICS MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Pere Tumbas

    2007-12-01

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

  15. A decision support system for forensic entomology

    OpenAIRE

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

    2007-01-01

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

  16. Weibull Decision Support Systems in Maintenance

    Directory of Open Access Journals (Sweden)

    Aboura Khalid

    2014-05-01

    Full Text Available Background: The Weibull distribution is one of the most important lifetime distributions in applied statistics. Weibull analysis is the leading method in the world for fitting and analyzing lifetime data. We discuss one of the earliest decision support system for the assessment of a distribution for the parameters of the Weibull reliability model using expert information. We then present a different approach to assess the parameters distribution.

  17. From hydrological modelling to decision support

    Science.gov (United States)

    Haberlandt, U.

    2010-08-01

    Decision support for planning and management of water resources needs to consider many target criteria simultaneously like water availability, water quality, flood protection, agriculture, ecology, etc. Hydrologic models provide information about the water balance components and are fundamental for the simulation of ecological processes. Objective of this contribution is to discuss the suitability of classical hydrologic models on one hand and of complex eco-hydrologic models on the other hand to be used as part of decision support systems. The discussion is based on results from two model comparison studies. It becomes clear that none of the hydrologic models tested fulfils all requirements in an optimal sense. Regarding the simulation of water quality parameters like nitrogen leaching a high uncertainty needs to be considered. Recommended for decision support is a hybrid metamodel approach, which comprises a hydrologic model, empirical relationships for the less dynamic processes and makes use of simulation results from complex eco-hydrologic models through second-order modelling at a generalized level.

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

    Directory of Open Access Journals (Sweden)

    Kathrin Cresswell

    2013-03-01

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

  19. Web Support System for Group Collaborative Decisions

    Science.gov (United States)

    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.

  20. GIS as spatial decision support system

    Directory of Open Access Journals (Sweden)

    V. Vostrovský

    2011-06-01

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

  1. Towards better modelling and decision support

    DEFF Research Database (Denmark)

    Meli, Mattia; Grimm, V; Augusiak, J.;

    2014-01-01

    The potential of ecological models for supporting environmental decision making is increasingly acknowledged. However, it often remains unclear whether a model is realistic and reliable enough. Good practice for developing and testing ecological models has not yet been established. Therefore, TRACE......, thereby also linking modellers and model users, for example stakeholders, decision makers, and developers of policies. We report on first experiences in producing TRACE documents. We found that the original idea underlying TRACE was valid, but to make its use more coherent and efficient, an update of its......, a general framework for documenting a model's rationale, design, and testing was recently suggested. Originally TRACE was aimed at documenting good modelling practice. However, the word 'documentation' does not convey TRACE's urgency. Therefore, we re-define TRACE as a tool for planning, performing...

  2. Better clinical decision making and reducing diagnostic error.

    Science.gov (United States)

    Croskerry, P; Nimmo, G R

    2011-06-01

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

  3. Clinical Information Support System (CISS)

    Data.gov (United States)

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

  4. Computational Support for Technology- Investment Decisions

    Science.gov (United States)

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

    2007-01-01

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

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

    Science.gov (United States)

    Ogallo, William; Kanter, Andrew S

    2015-01-01

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

  6. Clinical decision making in veterinary practice

    OpenAIRE

    Everitt, Sally

    2011-01-01

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

  7. Sediment Analysis Network for Decision Support (SANDS)

    Science.gov (United States)

    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

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

    OpenAIRE

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

    1997-01-01

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

  9. Decision support software technology demonstration plan

    Energy Technology Data Exchange (ETDEWEB)

    SULLIVAN,T.; ARMSTRONG,A.

    1998-09-01

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

  10. Context based support for Clinical Reasoning

    DEFF Research Database (Denmark)

    Vilstrup Pedersen, Klaus

    2004-01-01

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

  11. Clinical decision making of nurses working in hospital settings.

    Science.gov (United States)

    Bjørk, Ida Torunn; Hamilton, Glenys A

    2011-01-01

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

  12. Medical Device Data and Modeling for Clinical Decision Making

    CERN Document Server

    Zaleski, John R

    2010-01-01

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

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

    NARCIS (Netherlands)

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

    2009-01-01

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

  14. Clinical decision making in Barrett's oesophagus can be supported by computerized immunoquantitation and morphometry of features associated with proliferation and differentiation.

    Science.gov (United States)

    Polkowski, W; Baak, J P; van Lanschot, J J; Meijer, G A; Schuurmans, L T; Ten Kate, F J; Obertop, H; Offerhaus, G J

    1998-02-01

    (especially Ki67 and SI) can be a valuable adjunct tool for clinical decision making in Barrett's oesophagus.

  15. Reactive Software Agent Anesthesia Decision Support System

    Directory of Open Access Journals (Sweden)

    Grant H. Kruger

    2011-12-01

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

  16. Patterns of use of decision support tools by clinicians.

    Science.gov (United States)

    Hayward, Robert S; El-Hajj, Mohamad; Voth, Tanya K; Deis, Kelly

    2006-01-01

    This paper analyses information behavior data automatically gathered by an integrated clinical information environment used by internal medicine physicians and trainees at the University of Alberta. The study reviews how clinical information systems, decision-support tools and evidence resources were used over a 13 month period. Aggregate and application-specific frequency and duration of use was compared for location, time of day, physician status, and application-type (clinical information system or 5 categories of knowledge resources). Significant differences are observed for when and where resources were used, diurnal patterns of use, minutes spent per encounter, and patterns of use for physicians and trainees. We find that evidence use is not restricted to either the place or time of clinical work, resources are used for very short periods at the point-of-care, and that use of filtered evidence-based resources is concentrated among trainees.

  17. Development of a Web-Based Clinical Decision Support System for Drug Prescription: Non-Interventional Naturalistic Description of the Antipsychotic Prescription Patterns in 4345 Outpatients and Future Applications

    Science.gov (United States)

    Berrouiguet, Sofian; Barrigón, Maria Luisa; Brandt, Sara A.; Ovejero-García, Santiago; Álvarez-García, Raquel; Carballo, Juan Jose; Lenca, Philippe; Courtet, Philippe; Baca-García, Enrique

    2016-01-01

    Purpose The emergence of electronic prescribing devices with clinical decision support systems (CDSS) is able to significantly improve management pharmacological treatments. We developed a web application available on smartphones in order to help clinicians monitor prescription and further propose CDSS. Method A web application (www.MEmind.net) was developed to assess patients and collect data regarding gender, age, diagnosis and treatment. We analyzed antipsychotic prescriptions in 4345 patients attended in five Psychiatric Community Mental Health Centers from June 2014 to October 2014. The web-application reported average daily dose prescribed for antipsychotics, prescribed daily dose (PDD), and the PDD to defined daily dose (DDD) ratio. Results The MEmind web-application reported that antipsychotics were used in 1116 patients out of the total sample, mostly in 486 (44%) patients with schizophrenia related disorders but also in other diagnoses. Second generation antipsychotics (quetiapine, aripiprazole and long-acting paliperidone) were preferably employed. Low doses were more frequently used than high doses. Long acting paliperidone and ziprasidone however, were the only two antipsychotics used at excessive dosing. Antipsychotic polypharmacy was used in 287 (26%) patients with classic depot drugs, clotiapine, amisulpride and clozapine. Conclusions In this study we describe the first step of the development of a web application that is able to make polypharmacy, high dose usage and off label usage of antipsychotics visible to clinicians. Current development of the MEmind web application may help to improve prescription security via momentary feedback of prescription and clinical decision support system. PMID:27764107

  18. Healthcare performance turned into decision support

    DEFF Research Database (Denmark)

    Sørup, Christian Michel; Jacobsen, Peter

    2013-01-01

    has not yet been attempted. Hospital management is provided with valuable information when given insight into the factors that control employee absence behaviour. Having this insight will enable the managers to promote a healthy working environment, thus lowering employee absence rates to a minimum.......Purpose – The purpose of this study is to first create an overview of relevant factors directly influencing employee absence in the healthcare sector. The overview is used to further investigate the factors identified using employee satisfaction survey scores exclusively. The result of the overall...... from the healthcare sector, the results obtained could be restricted to this sector. Inclusion of data from Arbejdsmarkedets Tillægspension (ATP) showed no deviation from the results in the healthcare sector. Practical implications – The product of the study is a decision support tool for leaders...

  19. Semantic technologies in a decision support system

    Science.gov (United States)

    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).

  20. Quantitative Decision Support Requires Quantitative User Guidance

    Science.gov (United States)

    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

  1. 基于数据仓库的临床决策支持系统在我院的应用%Application of Clinical Decision-making Support System Based on Data Warehouse in the Hospital

    Institute of Scientific and Technical Information of China (English)

    赵妍; 王颖; 闫国涛; 邵伟

    2016-01-01

    目的:建设临床决策支持系统,辅助医生从日常大量的临床数据中迅速挖掘出有价值的信息,为患者快速制定个性化的诊疗方案、降低医疗风险、提升医疗质量。方法收集国内外相关材料,利用数据仓库、数据挖掘技术,结合相关医疗保障政策建立一个符合临床实际操作的临床决策系统。结果该系统可智能提供安全诊疗方案、药物过敏警示、重复检验检查提示等相关功能。结论基于数据仓库的临床决策支持系统的应用,减轻了医生负担,是基层医院信息化发展的趋势。%Objective To establish a clinical decision-making support system to assist physicians in quickly mining valuable information from a large number of daily clinical data, developing personalized diagnosis and treatment program for patients, and improving medical quality. Methods The related domestic and foreign information was collected, on the basis of which the data warehouse and data mining technology were deployed in combination of relevant medical security policies to establish a clinical decision-making system suited for practical clinical operation. Results The system was equipped with versatile features, including smart provision of secure treatment programs, drug allergy alerts and reminders for repeated testing and inspection. Conclusion The clinical decision-making support system developed based on data warehouse reduced doctors burden and was the future trend for the development of hospital informatization.

  2. Apply creative thinking of decision support in electrical nursing record.

    Science.gov (United States)

    Hao, Angelica Te-Hui; Hsu, Chien-Yeh; Li-Fang, Huang; Jian, Wen-Shan; Wu, Li-Bin; Kao, Ching-Chiu; Lu, Mei-Show; Chang, Her-Kung

    2006-01-01

    The nursing process consists of five interrelated steps: assessment, diagnosis, planning, intervention, and evaluation. In the nursing process, the nurse collects a great deal of data and information. The amount of data and information may exceed the amount the nurse can process efficiently and correctly. Thus, the nurse needs assistance to become proficient in the planning of nursing care, due to the difficulty of simultaneously processing a large set of information. Computer systems are viewed as tools to expand the capabilities of the nurse's mind. Using computer technology to support clinicians' decision making may provide high-quality, patient-centered, and efficient healthcare. Although some existing nursing information systems aid in the nursing process, they only provide the most fundamental decision support--i.e., standard care plans associated with common nursing diagnoses. Such a computerized decision support system helps the nurse develop a care plan step-by-step. But it does not assist the nurse in the decision-making process. The decision process about how to generate nursing diagnoses from data and how to individualize the care plans still reminds of the nurse. The purpose of this study is to develop a pilot structure in electronic nursing record system integrated with international nursing standard for improving the proficiency and accuracy of plan of care in clinical pathway process. The proposed pilot systems not only assist both student nurses and nurses who are novice in nursing practice, but also experts who need to work in a practice area which they are not familiar with.

  3. Investing in deliberation: a definition and classification of decision support interventions for people facing difficult health decisions.

    Science.gov (United States)

    Elwyn, Glyn; Frosch, Dominick; Volandes, Angelo E; Edwards, Adrian; Montori, Victor M

    2010-01-01

    This article provides an analysis of 'decision aids', interventions to support patients facing tough decisions. Interest has increased since the concept of shared decision making has become widely considered to be a means of achieving desirable clinical outcomes. We consider the aims of these interventions and examine assumptions about their use. We propose three categories, interventions that are used in face-to-face encounters, those designed for use outside clinical encounters and those which are mediated, using telephone or other communication media. We propose the following definition: decision support interventions help people think about choices they face; they describe where and why choice exists; they provide information about options, including, where reasonable, the option of taking no action. These interventions help people to deliberate, independently or in collaboration with others, about options, by considering relevantattributes; they support people to forecast how they might feel about short, intermediate and long-term outcomes which have relevant consequences, in ways which help the process of constructing preferences and eventual decision making, appropriate to their individual situation. Although quality standards have been published for these interventions, we are also cautious about premature closure and consider that the need for short versions for use inside clinical encounters and long versions for external use requires further research. More work is also needed on the use of narrative formats and the translation of theory into practical designs. The interest in decision support interventions for patients heralds a transformation in clinical practice although many important areas remain unresolved.

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

    OpenAIRE

    Bruggen, Gerrit; Wierenga, Berend

    2009-01-01

    textabstractMarketing management support systems (MMSS) are computer-enabled devices that help marketers to make better decisions. Marketing processes can be quite complex, involving large numbers of variables and mostly outcomes are the results of the actions of many different stakeholders (e.g., the company itself, its customers, its competitors). Moreover, a large number of interdependencies exist between the relevant variables and the outcomes of marketing actions are subject to major unc...

  5. Probability, clinical decision making and hypothesis testing

    Directory of Open Access Journals (Sweden)

    A Banerjee

    2009-01-01

    Full Text Available Few clinicians grasp the true concept of probability expressed in the ′P value.′ For most, a statistically significant P value is the end of the search for truth. In fact, the opposite is the case. The present paper attempts to put the P value in proper perspective by explaining different types of probabilities, their role in clinical decision making, medical research and hypothesis testing.

  6. A problem solving framework for group decision support system

    Institute of Scientific and Technical Information of China (English)

    陈晓红; 周艳菊; 胡东滨

    2002-01-01

    A new problem solving framework for group decision support system using layer model approach is proposed. This kind of framework includes four basic layers, namely, application layer, task layer, logical layer and physical layer. Based on indicating the respective meanings of those layers a task skeleton of group decision support system and a logical structure of group decision support system generator are put forward and discussed in detail. The framework provides theoretical guidance for developing group decision support system to lower systematic development complexity and support reuse of software.

  7. Analytical decision support for sustainable electricity supply

    International Nuclear Information System (INIS)

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

  8. Post Disaster Assessment with Decision Support System

    Directory of Open Access Journals (Sweden)

    May Florence J. Franco

    2016-05-01

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

  9. Decision support tools for advanced energy management

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-06-15

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

  10. ACCOUNTING KNOWLEDGE: DECISION SUPPORT IN FORESTRY

    OpenAIRE

    Ph.D Student Postolache (Males) Daniela

    2010-01-01

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

  11. Decision Support for Countering Terrorist Threats against Transportation Networks

    Directory of Open Access Journals (Sweden)

    Dr. Richard Adler

    2009-01-01

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

  12. Research on Development of Corn Production Decision Support System

    OpenAIRE

    Nan Lin; Dongming Li; Chunguang Bi

    2013-01-01

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

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

    OpenAIRE

    Daniela I. POSTOLACHE (MALES)

    2010-01-01

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

  14. Decision support in an integrated environment

    Science.gov (United States)

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

    2000-11-01

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

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

    CERN Document Server

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

    2011-01-01

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

  16. Developing a Support Tool for Global Product Development Decisions

    DEFF Research Database (Denmark)

    Søndergaard, Erik Stefan; Ahmed-Kristensen, Saeema

    2016-01-01

    presents results from 51 decisions made in the three companies, and based on the results of the studies a framework for a decision-support tool is outlined and discussed. The paper rounds off with an identification of future research opportunities in the area of global product development and decision-making....

  17. Psychotherapy treatment decisions supported by SelectCare

    NARCIS (Netherlands)

    Witteman, C.L.M.

    2008-01-01

    SelectCare is a computerized decision support system for psychotherapists who decide how to treat their depressed patients. This paper descibes the decision making model that is implemented in SelectCare and the decision elements it uses to give advice to its users. The system itself is then present

  18. Modeling Based Decision Support Environment Project

    Data.gov (United States)

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

  19. Decision Support Systems used in Disaster Management

    OpenAIRE

    Marius CIOCA; Lucian-Ionel CIOCA

    2010-01-01

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

  20. Clinical Decision Support System on Basis of Case-Based Reasoning for Traditional Chinese Medicine%基于案例推理的中医临床诊疗决策支持系统

    Institute of Scientific and Technical Information of China (English)

    杨丽; 周雪忠; 毕斓馨; 张润顺; 王映辉; 刘保延; 谢琪

    2014-01-01

    Real world clinical diagnosis and treatment activity is a complicated decision-making task. The effective clinical cases of traditional Chinese medicine (TCM) of highly experienced physicians play an important role in the routine diagnosis and treatment and the formulation of medical knowledge . Based on TCM electronic medical record data, this paper proposed a decision support prototype system on TCM clinical diagnosis and treatment based on TCM effective clinical cases and case-based reasoning (CBR) algorithm, which is used to assist inexperienced clinicians to make more reliable clinical decisions, and thereafter to improve the clinical curative effectiveness. The system integrates TCM clinical cases data set from a TCM clinical data warehouse, and retrieves the similar cases based on CBR method. In particular, according to the underlying personalized diagnosis and treatment for patients in TCM, this system implemented a flexible diagnosis and treatment modification mechanism based on correlation analysis among symptoms, diagnoses (syndrome or pattern in TCM) and medicine. Finally, through a demonstration of clinical application, we made an initial evaluation of the usefulness and practical effects of the system.%真实世界临床诊疗活动是一个复杂的决策过程。中医学中名老中医效验案例对日常诊疗行为的指导和诊疗知识的普及具有重要作用。本文基于临床实际中医病历数据,提出基于名老中医临床诊疗效验案例,基于案例推理的中医临床诊疗决策支持系统,用来辅助经验不足的临床医师做出临床决策,以提高临床疗效。该系统从中医临床数据仓库中筛选加工形成中医学临床效验案例库,基于案例推理和相似性计算实现类似案例的检索和展示。特别是针对不同案例的个体性特点,实现了基于症-诊断-药相关分析的灵活的案例修正方案,以满足临床诊疗过程中个体化诊疗决策的需求

  1. Method for designing organization decision support system framework

    Institute of Scientific and Technical Information of China (English)

    Fan Jiancong; Liang Yongquan; Zeng Qingtian

    2006-01-01

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

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

    CERN Document Server

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

    2010-01-01

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

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

    Data.gov (United States)

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

  4. [Clinical decisions in a philosophical perspective].

    Science.gov (United States)

    Wulff, H R

    1993-09-20

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

  5. Fault Detection for Shipboard Monitoring and Decision Support Systems

    DEFF Research Database (Denmark)

    Lajic, Zoran; Nielsen, Ulrik Dam

    2009-01-01

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

  6. Sttudy on intelligent spatial decision support system of agriculture

    Institute of Scientific and Technical Information of China (English)

    ZHANG Rong-mei; SUN Jie-li

    2006-01-01

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

  7. A review of decision support technologies for amniocentesis.

    NARCIS (Netherlands)

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

    2008-01-01

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

  8. Fault-Tolerant Onboard Monitoring and Decision Support Systems

    DEFF Research Database (Denmark)

    Lajic, Zoran

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

  9. Adjuncts or adversaries to shared decision-making? Applying the Integrative Model of behavior to the role and design of decision support interventions in healthcare interactions.

    NARCIS (Netherlands)

    Frosch, D.; Legare, F.; Fishbein, M.; Elwyn, G.

    2009-01-01

    ABSTRACT: BACKGROUND: A growing body of literature documents the efficacy of decision support interventions (DESI) in helping patients make informed clinical decisions. DESIs are frequently described as an adjunct to shared decision-making between a patient and healthcare provider, however little is

  10. Decision support modeling for milk valorization

    NARCIS (Netherlands)

    Banaszewska, A.

    2014-01-01

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

  11. Empirical Study of KMS Impact on Decision Support

    Directory of Open Access Journals (Sweden)

    Kursad OZLEN

    2014-05-01

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

  12. Generic Opinion Mining System for Decision Support

    Directory of Open Access Journals (Sweden)

    Dr.P.G.Naik

    2016-04-01

    Full Text Available Social networking sites prove to be indispensible tools for decision making owing to the large repository of user views accumulated over a period of time. Such a real data can be exploited for various purposes such as making buying decisions, analysing the user views about new product launched by a company, product promotion campaign , impact of policy decisions made by a political party on society etc. In the current work the authors have proposed a generic model for feature based polarity determination by sentiment analysis of tweets. This model has been implemented by the seamless integration of R tool, XML, JAVA, Link Parser A practical multistep system, in place, efficiently extracts data from tweet text, pre-process the raw data to remove noise, and tags their polarity. Data used in the current study is derived from online product feature based reviews collected from tweeter tweets. Link parser version 4.1 b is employed for parsing a natural sentence which is broken into multiple tokens corresponding to noun and adjective before being stored in a persistent storage medium. The objectivity score is determined using SentiWordNet 3.0 lexical resource which is parsed using a tool implemented in Java. The linguistic hedges are taken care of using Zadeh’s proposition which modifies the final objectivity score. The objectivity score so computed, provides the necessary guidelines in influencing decisions. The authors have tested the model for product purchase decisions of two different sets of products, smart phone and laptop based on predefined set of features. The model is generic and can be applied to any set of products evaluated on a predefined set of features.

  13. Developing the US Wildland Fire Decision Support System

    Directory of Open Access Journals (Sweden)

    Erin K. Noonan-Wright

    2011-01-01

    Full Text Available 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 information to the decision making process. Risk-informed decision-making is becoming increasingly important as a means of improving fire management and offers substantial opportunities to benefit natural and community resource protection, management response effectiveness, firefighter resource use and exposure, and, possibly, suppression costs. This paper reviews the development, structure, and function of WFDSS, and how it contributes to increased flexibility and agility in decision making, leading to improved fire management program effectiveness.

  14. Group Decision Support Systems and Group Communication: A Comparison of Decision Making in Computer-Supported and Nonsupported Groups.

    Science.gov (United States)

    Poole, Marshall Scott; And Others

    1993-01-01

    Explores the effects of Group Decision Support Systems (GDSS) on small group communication and decision-making processes. Finds that comparing GDSS, manual, and baseline conditions enables separation of effects resulting from procedural structures from those resulting from computerization. Results support some aspects of the research model and…

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

    OpenAIRE

    Kostas Tolidis; Efi Dimopoulou

    2012-01-01

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

  16. Decision support modeling for milk valorization

    OpenAIRE

    Banaszewska, A.

    2014-01-01

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

  17. Information visualization in a distributed virtual decision support environment

    Science.gov (United States)

    Blocher, Timothy W.

    2002-07-01

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

  18. Intelligent Information System to support decision making.

    Directory of Open Access Journals (Sweden)

    Kathrin Rodríguez Llanes

    2010-06-01

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

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

    NARCIS (Netherlands)

    Carsjens, G.J.; Chen, W.

    2008-01-01

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

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

    OpenAIRE

    Bierner, G.

    1998-01-01

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

  1. Clinical Decision Making of Nurses Working in Hospital Settings

    Directory of Open Access Journals (Sweden)

    Ida Torunn Bjørk

    2011-01-01

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

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

    Science.gov (United States)

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

    2012-05-01

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

  3. Research on Development of Corn Production Decision Support System

    Directory of Open Access Journals (Sweden)

    Nan Lin

    2013-07-01

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

  4. Prototyping a Rangeland Decision Support System Project

    Data.gov (United States)

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

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

    OpenAIRE

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

    2016-01-01

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

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

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  7. A Gaussian Model of Expert Opinions for Supporting Design Decisions

    NARCIS (Netherlands)

    Rajabalinejad, M.

    2012-01-01

    Decision making in design is of great importance, resulting in success or failure of a system. This paper describes a robust decision support tool for engineering design process, which can be used throughout the design process. The tool is graphical and designed to communicate efficiently with diffe

  8. Decision support for information systems management : applying analytic hierarchy process

    NARCIS (Netherlands)

    Huizingh, Eelko K.R.E.; Vrolijk, Hans C.J.

    1995-01-01

    Decision-making in the field of information systems has become more complex due to a larger number of alternatives, multiple and sometimes conflicting goals, and an increasingly turbulent environment. In this paper we explore the appropriateness of Analytic Hierarchy Process to support I/S decision

  9. A Gaussian decision-support tool for engineering design process

    NARCIS (Netherlands)

    Rajabalinejad, Mohammad; Spitas, Christos

    2013-01-01

    Decision-making in design is of great importance, resulting in success or failure of a system (Liu et al., 2010; Roozenburg and Eekels, 1995; Spitas, 2011a). This paper describes a robust decision-support tool for engineering design process, which can be used throughout the design process in either

  10. Intelligent decision technology support in practice

    CERN Document Server

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

    2016-01-01

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

  11. DECISION SUPPORT FRAMEWORK FOR STORMWATER MANAGEMENT IN URBAN WATERSHEDS

    Science.gov (United States)

    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...

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

    NARCIS (Netherlands)

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

    1997-01-01

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

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

    NARCIS (Netherlands)

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

    1997-01-01

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

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

    Data.gov (United States)

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

  15. Mobile Contextualized learning games for decision support training

    NARCIS (Netherlands)

    Klemke, Roland

    2014-01-01

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

  16. Mobile Contextualized learning games for decision support training

    NARCIS (Netherlands)

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

    2015-01-01

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

  17. Data Mining and Decision Support: An Integrative Approach

    OpenAIRE

    Rupnik, Rok; Kukar, Matjaž

    2010-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Sullivan Frank M

    2007-04-01

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

  19. The Development of Clinical Decision Support System in U.S. and Its Enlightenment%美国临床决策支持系统发展与启示

    Institute of Scientific and Technical Information of China (English)

    盛赟; 张越

    2016-01-01

    美国典型的临床决策支持系统包括QMR,DXplain,MYCIN,Isabel,VisualDx等。美国临床决策支持系统在发展过程中存在许多问题:CDSS的应用对患者结果以及医生表现的效果评估良莠不齐,CDSS接受过程障碍重重,现有CDSS与临床需求不匹配等。美国临床决策支持系统发展过程中的问题及经验值得我们借鉴,例如:致力于推广临床决策支持系统的图书管理员应该与临床医生和医疗教育工作者紧密合作,以权衡临床决策支持系统和电子病历及其他系统整合的能力,以及实用性、准确性、可靠性和知识度的深度,同时加快流程,改善病人治疗结果,降低成本也很重要[1]。%Typical Clinical Decision Support System in U.S. include QMR, DXplain, MYCIN, Isabel, VisualDX etc.. A branch of problems exists with the development of CDSS: the results of studies that evaluate the effect of CDSS on patient outcome and physician performance are not consistent; there are many barriers to adoption of CDSS; current CDSS program may not meet the need of clinicians, etc. The successful experiences accumulated in the development of the US health decision support system are worth referring to. For instance, librarians seeking to add robust CDSS should partner with clinicians and medical educators to weigh usability, ability to integrate with electronic medical records and other systems, accuracy, reliability, depth of knowledge base, and improvements to process and patient outcomes, along with costs reduction, which can be substantial[1].

  20. A Stochastic Decision Support System for Economic Order Quantity Problem

    Directory of Open Access Journals (Sweden)

    Amir Yousefli

    2012-01-01

    Full Text Available Improving decisions efficiency is one of the major concerns of the decision support systems. Specially in the uncertain environment, decision support systems could be implemented efficiently to simplify decision making process. In this paper stochastic economic order quantity (EOQ problem is investigated in which decision variables and objective function are uncertain in nature and optimum probability distribution functions of them are calculated through a geometric programming model. Obtained probability distribution functions of the decision variables and the objective function are used as optimum knowledge to design a new probabilistic rule base (PRB as a decision support system for EOQ model. The developed PRB is a new type of the stochastic rule bases that can be used to infer optimum or near optimum values of the decision variables and the objective function of the EOQ model without solving the geometric programming problem directly. Comparison between the results of the developed PRB and the optimum solutions which is provided in the numerical example illustrates the efficiency of the developed PRB.

  1. DYNAMICALLY EVOLVING CLINICAL PRACTICES AND IMPLICATIONS FOR PREDICTING MEDICAL DECISIONS

    Science.gov (United States)

    CHEN, JONATHAN H; GOLDSTEIN, MARY K; ASCH, STEVEN M; ALTMAN, RUSS B

    2015-01-01

    Automatically data-mining clinical practice patterns from electronic health records (EHR) can enable prediction of future practices as a form of clinical decision support (CDS). Our objective is to determine the stability of learned clinical practice patterns over time and what implication this has when using varying longitudinal historical data sources towards predicting future decisions. We trained an association rule engine for clinical orders (e.g., labs, imaging, medications) using structured inpatient data from a tertiary academic hospital. Comparing top order associations per admission diagnosis from training data in 2009 vs. 2012, we find practice variability from unstable diagnoses with rank biased overlap (RBO)0.6. Predicting admission orders for future (2013) patients with associations trained on recent (2012) vs. older (2009) data improved accuracy evaluated by area under the receiver operating characteristic curve (ROC-AUC) 0.89 to 0.92, precision at ten (positive predictive value of the top ten predictions against actual orders) 30% to 37%, and weighted recall (sensitivity) at ten 2.4% to 13%, (P<10−10). Training with more longitudinal data (2009-2012) was no better than only using recent (2012) data. Secular trends in practice patterns likely explain why smaller but more recent training data is more accurate at predicting future practices. PMID:26776186

  2. Research of Agile Supply Chain Management Decision Support System

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Filipović Milanka

    2007-01-01

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

  4. MULTI SUPPORT VECTOR MACHINES DECISION MODEL AND ITS APPLICATION

    Institute of Scientific and Technical Information of China (English)

    阎威武; 陈治纲; 邵惠鹤

    2002-01-01

    Support Vector Machines (SVM) is a powerful machine learning method developed from statistical learning theory and is currently an active field in artificial intelligent technology. SVM is sensitive to noise vectors near hyperplane since it is determined only by few support vectors. In this paper, Multi SVM decision model(MSDM)was proposed. MSDM consists of multiple SVMs and makes decision by synthetic information based on multi SVMs. MSDM is applied to heart disease diagnoses based on UCI benchmark data set. MSDM somewhat inproves the robust of decision system.

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

    Science.gov (United States)

    Leśniak, Agnieszka

    2016-06-01

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

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

    Institute of Scientific and Technical Information of China (English)

    谢勇; 王红卫; 费奇

    2004-01-01

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

  7. Decision Support Systems - Technical Prerequisites and Military Requirements

    CERN Document Server

    Tolk, Andreas

    2010-01-01

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

  8. Web-Based Group Decision Support System: an Economic Application

    Directory of Open Access Journals (Sweden)

    Ion ISTUDOR

    2010-01-01

    Full Text Available Decision Support Systems (DSS form a specific class of computerized information systems that support business and managerial decision-making activities. Making the right decision in business primarily depends on the quality of data. It also depends on the ability to analyze the data with a view to identifying trends that can suggest solutions and strategies. A “cooperative” decision support system means the data are collected, analyzed and then provided to a human agent who can help the system to revise or refine the data. It means that both a human component and computer component work together to come up with the best solution. This paper describes the usage of a software product (Vanguard System to a specific economic application (evaluating the financial risk assuming that the rate of the economic profitability can be under the value of the interest rate.

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

    DEFF Research Database (Denmark)

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

    2011-01-01

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

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

    NARCIS (Netherlands)

    Heurkens, E.W.T.M.

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

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

    Directory of Open Access Journals (Sweden)

    Fors Uno GH

    2008-02-01

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

  12. Decision Support Systems (DSS in Construction Tendering Processes

    Directory of Open Access Journals (Sweden)

    Rosmayati Mohemad

    2010-03-01

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

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

    Science.gov (United States)

    Clark, Phillip M.

    1989-01-01

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

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

    OpenAIRE

    Lim, A.C.

    2005-01-01

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

  15. Clinical Decision Making of Nurses Working in Hospital Settings

    OpenAIRE

    Ida Torunn Bjørk; Hamilton, Glenys A.

    2011-01-01

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

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Eyüp AKÇETİN

    2014-06-01

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

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

    Directory of Open Access Journals (Sweden)

    G.Subbalakshmi,

    2011-04-01

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

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    Intelligent decision support should allow integrating human knowledge with efficient algorithms for making interpretable and useful recommendations on real world decision problems. Attitudes and preferences articulate and come together under a decision process that should be explicitly modeled...... for understanding and solving the inherent conflict of decision making. Here, risk attitudes are represented by means of fuzzy-linguistic structures, and an interactive methodology is proposed for learning preferences from a group of decision makers (DMs). The methodology is built on a multi-criteria framework...... allowing imprecise observations/measurements, where DMs reveal their attitudes in linguistic form and receive from the system their associated type, characterized by a preference order of the alternatives, together with the amount of consensus and dissention existing among the group. Following...

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

    Directory of Open Access Journals (Sweden)

    Şükrü Ada

    2015-04-01

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

  1. Conceptual framework of knowledge management for ethical decision-making support in neonatal intensive care.

    Science.gov (United States)

    Frize, Monique; Yang, Lan; Walker, Robin C; O'Connor, Annette M

    2005-06-01

    This research is built on the belief that artificial intelligence estimations need to be integrated into clinical social context to create value for health-care decisions. In sophisticated neonatal intensive care units (NICUs), decisions to continue or discontinue aggressive treatment are an integral part of clinical practice. High-quality evidence supports clinical decision-making, and a decision-aid tool based on specific outcome information for individual NICU patients will provide significant support for parents and caregivers in making difficult "ethical" treatment decisions. In our approach, information on a newborn patient's likely outcomes is integrated with the physician's interpretation and parents' perspectives into codified knowledge. Context-sensitive content adaptation delivers personalized and customized information to a variety of users, from physicians to parents. The system provides structuralized knowledge translation and exchange between all participants in the decision, facilitating collaborative decision-making that involves parents at every stage on whether to initiate, continue, limit, or terminate intensive care for their infant.

  2. Decision support system for the operating room rescheduling problem

    OpenAIRE

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

    2012-01-01

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

  3. Healthcare Decision Support System for Administration of Chronic Diseases

    OpenAIRE

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

    2014-01-01

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

  4. A decision support system to determine optimal ventilator settings

    OpenAIRE

    Akbulut, Fatma Patlar; Akkur, Erkan; Akan, Aydin; Yarman, B Siddik

    2014-01-01

    Background 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 ...

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

    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.

  7. Modular analytics management architecture for interoperability and decision support

    Science.gov (United States)

    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.

  8. Recent developments associated with decision support systems in water resources

    Science.gov (United States)

    Watkins, David W.; McKinney, Daene C.

    1995-07-01

    In order to limit the scope of this review, a working definition of a decision support system is needed. L. Adelman has defined decision support systems (DSSs) as "interactive computer programs that utilize analytical methods, such as decision analysis, optimization algorithms, program scheduling routines, and so on, for developing models to help decision makers formulate alternatives, analyze their impacts, and interpret and select appropriate options for implementation" (Adelman [1992], p. 2). Another definition has been offered by S. J. Andriole, who defined decision support as consisting of "any and all data, information, expertise or activities that contribute to option selection" (Andriole [1989], p. 3). A common idea explicit in each of these definitions is that DSSs integrate various technologies and aid in option selection. Implicit in each definition is that these are options for solving relatively large, unstructured problems. Thus, the following working definition of a DSS will be used in this review: A DSS is an integrated, interactive computer system, consisting of analytical tools and information management capabilities, designed to aid decision makers in solving relatively large, unstructured problems.

  9. Evolution of Decision Support Systems Research Field in Numbers

    Directory of Open Access Journals (Sweden)

    Ana-Maria SUDUC

    2010-01-01

    Full Text Available The scientific production in a certain field shows, in great extent, the research interests in that field. Decision Support Systems are a particular class of information systems which are gaining more popularity in various domains. In order to identify the evolution in time of the publications number, authors, subjects, publications in the Decision Support Systems (DSS field, and therefore the scientific world interest for this field, in November 2010 there have been organized a series of queries on three major international scientific databases: ScienceDirect, IEEE Xplore Digital Library and ACM Digital Library. The results presented in this paper shows that, even the decision support systems research field started in 1960s, the interests for this type of systems grew exponentially with each year in the last decades.

  10. Data Mining for Education Decision Support: A Review

    Directory of Open Access Journals (Sweden)

    Suhirman Suhirman

    2014-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Donnelly Sandra

    2011-02-01

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

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

    Science.gov (United States)

    Rodriquez, Luis F.

    2004-01-01

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

  13. The Intelligent Decision Support System Model of SARS

    Institute of Scientific and Technical Information of China (English)

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

    2004-01-01

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

  14. Decision support system for structure synthesis of monitoring systems

    Directory of Open Access Journals (Sweden)

    Skatkov A. V.

    2008-04-01

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

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    in connection with management of the consequences of other types of contaminating incidents, including ‘dirty bomb’ explosions. This would require a number of new modelling features and parametric changes. Also for nuclear power plant preparedness a number of revisions of the decision support systems are called......The paper presents examples of current needs for improvement and extended applicability of the European decision support systems. The systems were originally created for prediction of the radiological consequences of accidents at nuclear installations. They could however also be of great value...

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

    International Nuclear Information System (INIS)

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

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

    Directory of Open Access Journals (Sweden)

    Tarik A. Rashid

    2016-07-01

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

  18. Automation, decision support, and expert systems in nephrology.

    Science.gov (United States)

    Soman, Sandeep; Zasuwa, Gerard; Yee, Jerry

    2008-01-01

    Increasing data suggest that errors in medicine occur frequently and result in substantial harm to the patient. The Institute of Medicine report described the magnitude of the problem, and public interest in this issue, which was already large, has grown. The traditional approach in medicine has been to identify the persons making the errors and recommend corrective strategies. However, it has become increasingly clear that it is more productive to focus on the systems and processes through which care is provided. If these systems are set up in ways that would both make errors less likely and identify those that do occur and, at the same time, improve efficiency, then safety and productivity would be substantially improved. Clinical decision support systems (CDSSs) are active knowledge systems that use 2 or more items of patient data to generate case specific recommendations. CDSSs are typically designed to integrate a medical knowledge base, patient data, and an inference engine to generate case specific advice. This article describes how automation, templating, and CDSS improve efficiency, patient care, and safety by reducing the frequency and consequences of medical errors in nephrology. We discuss practical applications of these in 3 settings: a computerized anemia-management program (CAMP, Henry Ford Health System, Detroit, MI), vascular access surveillance systems, and monthly capitation notes in the hemodialysis unit.

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

    Science.gov (United States)

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

    2013-12-01

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

  20. Simulation-based decision support for evaluating operational plans

    Directory of Open Access Journals (Sweden)

    Johan Schubert

    2015-12-01

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

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

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

    Kim, Sangkyun

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Sangkyun Kim

    2014-01-01

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

  4. Technology Infusion Challenges from a Decision Support Perspective

    Science.gov (United States)

    Adumitroaie, V.; Weisbin, C. R.

    2009-01-01

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

  5. Neuro computing in knowledge-based decision support systems

    Energy Technology Data Exchange (ETDEWEB)

    Sirola, Miki; Lampi, Golan; Parviainen, Jukka

    2004-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Meliha Handzic

    2001-11-01

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

  7. Generalized Tumor Dose for Treatment Planning Decision Support

    Science.gov (United States)

    Zuniga, Areli A.

    Modern radiation therapy techniques allow for improved target conformity and normal tissue sparing. These highly conformal treatment plans have allowed dose escalation techniques increasing the probability of tumor control. At the same time this conformation has introduced inhomogeneous dose distributions, making delivered dose characterizations more difficult. The concept of equivalent uniform dose (EUD) characterizes a heterogeneous dose distribution within irradiated structures as a single value and has been used in biologically based treatment planning (BBTP); however, there are no substantial validation studies on clinical outcome data supporting EUD's use and therefore has not been widely adopted as decision-making support. These highly conformal treatment plans have also introduced the need for safety margins around the target volume. These margins are designed to minimize geometrical misses, and to compensate for dosimetric and treatment delivery uncertainties. The margin's purpose is to reduce the chance of tumor recurrence. This dissertation introduces a new EUD formulation designed especially for tumor volumes, called generalized Tumor Dose (gTD). It also investigates, as a second objective, margins extensions for potential improvements in local control while maintaining or minimizing toxicity. The suitability of gTD to rank LC was assessed by means of retrospective studies in a head and neck (HN) squamous cell carcinoma (SCC) and non-small cell lung cancer (NSCLC) cohorts. The formulation was optimized based on two datasets (one of each type) and then, model validation was assessed on independent cohorts. The second objective of this dissertation was investigated by ranking the probability of LC of the primary disease adding different margin sizes. In order to do so, an already published EUD formula was used retrospectively in a HN and a NSCLC datasets. Finally, recommendations for the viability to implement this new formulation into a routine treatment

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

    DEFF Research Database (Denmark)

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

    2014-01-01

    The aim of this article is to help confront uncertainty in life cycle assessments (LCAs) used for decision support. LCAs offer a quantitative approach to assess environmental effects of products, technologies, and services and are conducted by an LCA practitioner or analyst (AN) to support...... be described as a variance simulation based on individual data points used in an LCA. This article develops and proposes a taxonomy for LCAs based on extensive research in the LCA, management, and economic literature. This taxonomy can be used ex ante to support planning and communication between an AN and DM...... types of LCA on an expected inherent uncertainty scale that can be used to confront and address potential uncertainty. However, this article does not attempt to offer a quantitative approach for assessing uncertainty in LCAs used for decision support....

  9. Model-based decision support in diabetes care.

    Science.gov (United States)

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

    2011-05-01

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

  10. Decision Support for Flood Event Prediction and Monitoring

    DEFF Research Database (Denmark)

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

    2007-01-01

    In this paper the development of Web GIS based decision support system for flood events is presented. To improve flood prediction we developed the decision support system for flood prediction and monitoring that integrates hydrological modelling and CARIS GIS. We present the methodology for data...... integration, floodplain delineation, and online map interfaces. Our Web-based GIS model can dynamically display observed and predicted flood extents for decision makers and the general public. The users can access Web-based GIS that models current flood events and displays satellite imagery and digital...... elevation model integrated with flood plain area. The system can show how the flooding prediction based on the output from hydrological modeling for the next 48 hours along the lower Saint John River Valley....

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

    Institute of Scientific and Technical Information of China (English)

    FangDebin; WangXianjia

    2005-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-11-01

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

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

    Science.gov (United States)

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

    2015-09-01

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

  14. Report of subgroup epidemiology and decision support systems

    NARCIS (Netherlands)

    Kessel, G.J.T.; Hansen, J.G.

    2010-01-01

    Developments Decision Support Models. In France, the DSS’s Mildi-LIS and MilPV merged to form a new DSS for advisors and potato growers: Mileos. Furthermore, DSS’s for organic production in France (Fredon) and Germany (Oko-SIMPHYT) were developed to help scheduling copper applications within the nat

  15. Decision support for optimising energy consumption in European greenhouses

    NARCIS (Netherlands)

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

    2008-01-01

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

  16. Model based decision support for planning of road maintenance

    NARCIS (Netherlands)

    Worm, J.M.; Harten, van A.

    1996-01-01

    In this article we describe a Decision Support Model, based on Operational Research methods, for the multi-period planning of maintenance of bituminous pavements. This model is a tool for the road manager to assist in generating an optimal maintenance plan for a road. Optimal means: minimising the N

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

    International Nuclear Information System (INIS)

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

  18. PROBLEM DESCRIPTIONS FOR THE DECISION SUPPORT SOFTWARE DEMONSTRATION

    Energy Technology Data Exchange (ETDEWEB)

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

    1998-09-14

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

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

    Science.gov (United States)

    Bergey, Paul; King, Mark

    2014-01-01

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

  20. Real Time Traffic Models, Decision Support for Traffic Management

    NARCIS (Netherlands)

    Wismans, L.; De Romph, E.; Friso, K.; Zantema, K.

    2014-01-01

    Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various con

  1. Decision support system for treatment of dredged sediments

    NARCIS (Netherlands)

    Joziasse, J.; Bakker, T.; Eggels, P.G.

    1998-01-01

    A decision support system for treatment of dredged sediments (DSTS) has been constructed, in which the environmental effects of various treatment options applied can be compared. The effects are evaluated by scores on environmental themes like global warming and acidification, using life cycle asses

  2. New threats and new challenges for radiological decision support

    DEFF Research Database (Denmark)

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

    2011-01-01

    It is described how ongoing work will extend European standard decision support systems currently integrated in the nuclear power plant preparedness in many countries, to enable estimation of the radiological consequences of atmospheric dispersion of contaminants following a terror attack in a city...

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

    OpenAIRE

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

    2015-01-01

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

  4. Decision support system for containment and release management

    Energy Technology Data Exchange (ETDEWEB)

    Oosterhuis, B. [Twente Univ., Enschede (Netherlands). Computer Science Dept.

    1995-09-01

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

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

    DEFF Research Database (Denmark)

    Brodin, N. Patrik; Maraldo, Maja V.; Aznar, Marianne C.;

    2014-01-01

    PURPOSE: To present a novel tool that allows quantitative estimation and visualization of the risk of various relevant normal tissue endpoints to aid in treatment plan comparison and clinical decision making in radiation therapy (RT) planning for Hodgkin lymphoma (HL). METHODS AND MATERIALS......: A decision-support tool for risk-based, individualized treatment plan comparison is presented. The tool displays dose-response relationships, derived from published clinical data, for a number of relevant side effects and thereby provides direct visualization of the trade-off between these endpoints...... of dose-response curves to drive the reoptimization of a volumetric modulated arc therapy treatment plan for an HL patient with head-and-neck involvement. We also use this decision-support tool to visualize and quantitatively evaluate the trade-off between a 3-dimensional conformal RT plan...

  6. A Decision Support System for Concrete Bridge Maintenance

    Science.gov (United States)

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-02-01

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

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

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

    Grembowski, David; And Others

    1989-01-01

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

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

    Directory of Open Access Journals (Sweden)

    White Martha

    2007-03-01

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

  11. Personalized Clinical Diagnosis in Data Bases for Treatment Support in Phthisiology.

    Science.gov (United States)

    Lugovkina, T K; Skornyakov, S N; Golubev, D N; Egorov, E A; Medvinsky, I D

    2016-01-01

    The decision-making is a key event in the clinical practice. The program products with clinical decision support models in electronic data-base as well as with fixed decision moments of the real clinical practice and treatment results are very actual instruments for improving phthisiological practice and may be useful in the severe cases caused by the resistant strains of Mycobacterium tuberculosis. The methodology for gathering and structuring of useful information (critical clinical signals for decisions) is described. Additional coding of clinical diagnosis characteristics was implemented for numeric reflection of the personal situations. The created methodology for systematization and coding Clinical Events allowed to improve the clinical decision models for better clinical results.

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

    Directory of Open Access Journals (Sweden)

    Glyn Elwyn

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

  13. Design document for landfill capping Prototype Decision Support System

    International Nuclear Information System (INIS)

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

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

    CERN Document Server

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

    2009-01-01

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

  15. A Synthesis Of Knowledge About Caregiver Decision Making Finds Gaps In Support For Those Who Care For Aging Loved Ones.

    Science.gov (United States)

    Garvelink, Mirjam M; Ngangue, Patrice A G; Adekpedjou, Rheda; Diouf, Ndeye T; Goh, Larissa; Blair, Louisa; Légaré, France

    2016-04-01

    We conducted a mixed-methods knowledge synthesis to assess the effectiveness of interventions to improve caregivers' involvement in decision making with seniors, and to describe caregivers' experiences of decision making in the absence of interventions. We analyzed forty-nine qualitative, fourteen quantitative, and three mixed-methods studies. The qualitative studies indicated that caregivers had unmet needs for information, discussions of values and needs, and decision support, which led to negative sentiments after decision making. Our results indicate that there have been insufficient quantitative evaluations of interventions to involve caregivers in decision making with seniors and that the evaluations that do exist found few clinically significant effects. Elements of usual care that received positive evaluations were the availability of a decision coach and a supportive decision-making environment. Additional rigorously evaluated interventions are needed to help caregivers be more involved in decision making with seniors.

  16. Decision support for simulation-based operation planning

    Science.gov (United States)

    Schubert, Johan; Hörling, Pontus

    2016-05-01

    In this paper, we develop methods for analyzing large amounts of data from a military ground combat simulation system. Through a series of processes, we focus the big data set on situations that correspond to important questions and show advantageous outcomes. The result is a decision support methodology that provides commanders with results that answer specific questions of interest, such as what the consequences for the Blue side are in various Red scenarios or what a particular Blue force can withstand. This approach is a step toward taking the traditional data farming methodology from its analytical view into a prescriptive operation planning context and a decision making mode.

  17. Impella ventricular support in clinical practice

    DEFF Research Database (Denmark)

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

    2015-01-01

    Mechanical circulatory support represents an evolving field of clinical research and practice. Currently, several cardiac assist devices have been developed but, among different institutions and countries, a large variation in indications for use and device selection exists. The Impella platform ...

  18. Hospital management decision support: a balanced scorecard approach.

    Science.gov (United States)

    Gordon, D; Chapman, R; Kunov, H; Dolan, A; Carter, M

    1998-01-01

    Hospital management teams receive voluminous data from a wide variety of sources, but are unable to distill the essential data they require to make good decisions. We have used a methodology, which helps teams define and use important management data coupled with an information system that makes this data accessible. Results of our evaluation indicate that the process of developing a Balanced Scorecard indicator system helps management teams to define meaningful strategic objectives and measurable performance indicators. The framework combined with the information acts as an integrating force, providing a shared understanding of the unit's goals. We conclude that a customized decision support system, which integrates multiple measures in a balanced Scorecard framework, is a powerful tool for enabling complex decision making by a management team. PMID:10384497

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

    Science.gov (United States)

    Tavana, Madjid

    1995-01-01

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

  20. Audio-video decision support for patients: the documentary genre as a basis for decision aids

    NARCIS (Netherlands)

    Volandes, A.E.; Barry, M.J.; Wood, F.; Elwyn, G.

    2013-01-01

    Objective Decision support tools are increasingly using audio-visual materials. However, disagreement exists about the use of audio-visual materials as they may be subjective and biased. Methods This is a literature review of the major texts for documentary film studies to extrapolate issues of obje

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

    OpenAIRE

    Andrew Coulson; David Glasspool; John Fox; Jon Emery

    2000-01-01

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

  2. Driving and dementia: a clinical decision pathway

    OpenAIRE

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

    2014-01-01

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

  3. Driving and dementia: a clinical decision pathway

    OpenAIRE

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

    2014-01-01

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

  4. Clinical Decision Making in Renal Pain Management

    OpenAIRE

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

    2012-01-01

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

  5. Human Decision Processes: Implications for SSA Support Tools

    Science.gov (United States)

    Picciano, P.

    2013-09-01

    paper), one opinion shared is that the rational, economic, deliberate listing/evaluation of all options is NOT representative of how many decision are made. A framework gaining interest lately describes two systems predominantly at work: intuition and reasoning (Kahneman, 2003). Intuition is fast, automatic, and parallel contrasted with the more effortful, deliberative, and sequential reasoning. One of the issues of contention is that considerable research is stacked supporting both sides claiming that intuition is: • A hallmark of expertise responsible for rapid, optimal decisions in the face of adversity • A vulnerability where biases serve as decision traps leading to wrong choices Using seminal studies from a range of domains and tasking, potential solutions for SSA decision support will be offered. Important issues such as managing uncertainty, framing inquiries, and information architecture, and contextual cues will be discussed. The purpose is to provide awareness of the human limitations and capabilities in complex decision making so engineers and designers can consider such factors in their development of SSA tools.

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

    Science.gov (United States)

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

    2016-04-01

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

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

    Science.gov (United States)

    Aliferis, C F; Miller, R A

    1995-03-01

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

  8. A decision support system for AIDS intervention and prevention.

    Science.gov (United States)

    Xu, L D

    1994-08-01

    In recent years, the importance of information systems has been identified as a vital issue to continuing success in AIDS intervention and prevention (AIP). The advances in information technology have resulted in integrative information systems including decision support systems (DSS). The concept of DSS for AIP was created at the intersection of two trends. The first trend was a growing belief that AIP information systems are successful in automating operations in AIP programs. The second was a continuing improvement in modeling and software development in the AIP area. This paper presents an integrated DSS for AIP. The system is integrated with a database and achieves its efficiency by incorporating various algorithms and models to support AIP decision processes. The application examples include screening AIDS-risky behaviors, evaluating educational interventions, and scheduling AIP sessions. The implementation results present evidence of the usefulness of the system in AIP.

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

    CERN Document Server

    Ali, A; Riaz, Zahid

    2014-01-01

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

  10. Advanced intelligent computational technologies and decision support systems

    CERN Document Server

    Kountchev, Roumen

    2014-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  12. Entrepreneurial decision support engine in forecasting business opportunities

    OpenAIRE

    Burghelea, Madalina

    2014-01-01

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

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

    OpenAIRE

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

    2016-01-01

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

  14. The Heureka forestry decision support system : an overview

    OpenAIRE

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

    2011-01-01

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

  15. Decision support system for structure synthesis of monitoring systems

    OpenAIRE

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

    2008-01-01

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

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

    OpenAIRE

    Tringali, Arthur M

    1997-01-01

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

  17. INTEGRATION OF FORESTRY DECISION SUPPORT SYSTEMS IN GIS

    OpenAIRE

    STEFANIA PIZZIRANI; STEPHEN BATHGATE

    2012-01-01

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

  18. Decision support for optimising energy consumption in European greenhouses

    OpenAIRE

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

    2008-01-01

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

  19. Computation of milestones for decision support during system restoration

    OpenAIRE

    Hou, Y.; Liu, CC; K. Sun; Zhang, P.; Liu, S.; Mizumura, D

    2011-01-01

    System restoration involves status assessment, optimization of generation capability and load pickup. The optimization problem needs to take complex constraints into consideration and, therefore, it is not practical to formulate the problem as one single optimization problem. The other critical consideration for the development of decision support tools is its generality, i.e., the tools should be portable from a system to another with minimal customization. This paper reports a practical met...

  20. Intelligent Decision Support System for Bank Loans Risk Classification

    Institute of Scientific and Technical Information of China (English)

    杨保安; 马云飞; 俞莲

    2001-01-01

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

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

    OpenAIRE

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

    2011-01-01

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

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

    OpenAIRE

    Amouzegar, Mahyar A.; Jacobsen, Stephen E.

    1998-01-01

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

  3. Knowledge Management and Decision Support for Sustainable Land Management

    OpenAIRE

    Liniger, Hanspeter; Schwilch, Gudrun

    2010-01-01

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

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

    OpenAIRE

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

    1995-01-01

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

  5. A Knowledge Management and Decision Support Model for Enterprises

    Directory of Open Access Journals (Sweden)

    Patrizia Ribino

    2011-01-01

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

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

    Science.gov (United States)

    Chen, Y.

    2015-12-01

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

  7. Demonstration of Decision Support Tools for Sustainable Development

    Energy Technology Data Exchange (ETDEWEB)

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

    2000-11-01

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

  8. The economic valuation of improved process plant decision support technology.

    Science.gov (United States)

    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.

  9. An Intelligent Polar Cyberinfrastrucuture to Support Spatiotemporal Decision Making

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Schnabel, William; Brumbelow, Kelly

    2013-03-31

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

  11. Decision support for integrated water-energy planning.

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-10-01

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

  12. Effects on Decision Quality of Supporting Multi-attribute Evaluation in Groups

    Science.gov (United States)

    Timmermans; Vlek

    1996-11-01

    In this study the effectiveness of multi-attribute utility (MAU) decision support in groups is evaluated for personnel selection problems differing in complexity. Subjects were asked to make an initial individual decision with or without MAU decision support. Next individuals formed small groups and were asked to reach a decision about the same problem. Groups received either MAU support or no support. Results show that for relatively simple problems the most effective method is to provide subjects with both individual and group decision support. Here, decision support had a clear impact on subjects' preferences and the level of agreement between group members. In addition, satisfaction with the decision and the decision procedure was relatively high. Overall, decision support improved communication; subjects reported to find the problem easier, to have more influence on the group decision, and to find it easier to express their opinions. For more complex problems, however, decision making without group support (whether preceded by individual support or not) was evaluated most favorably. Individual decision support in this condition was sometimes better than no support; i.e., there was a lower reported problem difficulty, a higher satisfaction with the group decision, and a higher reported influence on the group decision. The effectiveness of group MAU decision support for complex problems was evaluated less favorably.

  13. Education for healthcare clinical support workers.

    Science.gov (United States)

    Lewis, Robin; Kelly, Shona

    2015-12-01

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

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

    Science.gov (United States)

    Trimble, Michael; Hamilton, Paul

    2016-08-01

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

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

    Science.gov (United States)

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

    2012-07-01

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

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

    Science.gov (United States)

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

    2016-08-01

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

  17. Decision Support Tools for Cloud Migration in the Enterprise

    CERN Document Server

    Khajeh-Hosseini, Ali; Bogaerts, Jurgen; Teregowda, Pradeep

    2011-01-01

    This paper describes two tools that aim to support decision making during the migration of IT systems to the cloud. The first is a modeling tool that produces cost estimates of using public IaaS clouds. The tool enables IT architects to model their applications, data and infrastructure requirements in addition to their computational resource usage patterns. The tool can be used to compare the cost of different cloud providers, deployment options and usage scenarios. The second tool is a spreadsheet that outlines the benefits and risks of using IaaS clouds from an enterprise perspective; this tool provides a starting point for risk assessment. Two case studies were used to evaluate the tools. The tools were useful as they informed decision makers about the costs, benefits and risks of using the cloud.

  18. Building a financial decision support system with Oracle

    CERN Document Server

    Angberg, M

    2001-01-01

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

  19. Data assimilation in the decision support system RODOS

    DEFF Research Database (Denmark)

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

    2003-01-01

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

  20. Decision System Integrating Preferences to Support Sleep Staging.

    Science.gov (United States)

    Ugon, Adrien; Sedki, Karima; Kotti, Amina; Seroussi, Brigitte; Philippe, Carole; Ganascia, Jean-Gabriel; Garda, Patrick; Bouaud, Jacques; Pinna, Andrea

    2016-01-01

    Scoring sleep stages can be considered as a classification problem. Once the whole recording segmented into 30-seconds epochs, features, extracted from raw signals, are typically injected into machine learning algorithms in order to build a model able to assign a sleep stage, trying to mimic what experts have done on the training set. Such approaches ignore the advances in sleep medicine, in which guidelines have been published by the AASM, providing definitions and rules that should be followed to score sleep stages. In addition, these approaches are not able to solve conflict situations, in which criteria of different sleep stages are met. This work proposes a novel approach based on AASM guidelines. Rules are formalized integrating, for some of them, preferences allowing to support decision in conflict situations. Applied to a doubtful epoch, our approach has taken the appropriate decision. PMID:27577436

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

    International Nuclear Information System (INIS)

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

  2. A hybrid decision support system for iron ore supply

    Directory of Open Access Journals (Sweden)

    A. Samolejová

    2012-01-01

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

  3. Decision Support System for Maintenance Management Using Bayesian Networks

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

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

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

    DEFF Research Database (Denmark)

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

    2007-01-01

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

  5. Fast Interactive Decision Support for Modifying Stowage Plans Using Binary Decision Diagrams

    DEFF Research Database (Denmark)

    Jensen, Rune Møller; Leknes, Eilif; Bebbington, Thomas

    Low cost containerized shipping requires high quality stowage plans. Scalable stowage planning optimization algorithms have been developed recently. All of these algorithms, however, produce monolithic solutions that are hard for stowage coordinators to modify, which is necessary in practice due ...... fast, complete, and backtrack-free decision support. Our computational results show that the approach can solve real-sized instances when breaking symmetries among similar containers...

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

    OpenAIRE

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

    2011-01-01

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

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

    OpenAIRE

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

    2014-01-01

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

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

    OpenAIRE

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

    2015-01-01

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

  9. U.S. Dept. Veterans Affairs (VA) SMEC-bio Reporting for Leadership Decision Support

    OpenAIRE

    Gamage, Shantini D.; Simbartl, Loretta A.; Kralovic, Stephen M.; Wallace, Katherine S.; Roselle, Gary A.

    2013-01-01

    Objective To assess Reports sent from the United States VA Subject Matter Expertise Center for Biological Events (SMEC-bio) – a proof-of-concept decision support initiative – to the VA Integrated Operations Center (VA IOC). Introduction VA is the U.S. federal agency responsible for providing services to America’s Veterans. Within VA, VHA is the organization responsible for administration of health care services. VHA, with 152 Medical Centers and over 900 outpatient clinics located throughout ...

  10. New Decision Support for Landslide and Other Disaster Events

    Science.gov (United States)

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

    2013-12-01

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

  11. Coordinating complex decision support activities across distributed applications

    Science.gov (United States)

    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.

  12. Calculating Outcrossing Rates used in Decision Support Systems for Ships

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam

    2008-01-01

    Onboard decision support systems (DSS) are used to increase the operational safety of ships. Ideally, DSS can estimate - in the statistical sense - future ship responses on a time scale of the order of 1-3 hours taking into account speed and course changes. The calculations depend on both...... operational and environmental parameters that are known only in the statistical sense. The present paper suggests a procedure to incorporate random variables and associated uncertainties in calculations of outcrossing rates, which are the basis for risk-based DSS. The procedure is based on parallel system...

  13. Collaborative Decision Support Systems for Primary Health care Managers

    Directory of Open Access Journals (Sweden)

    Gunjan Pahuja

    2012-03-01

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

  14. Artificial intelligence based decision support for trumpeter swan management

    Science.gov (United States)

    Sojda, Richard S.

    2002-01-01

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

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

    OpenAIRE

    Agndal, Henrik; Nilsson, Ulf

    2008-01-01

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

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

    OpenAIRE

    Svendsen, Ole-Johan Øby

    2011-01-01

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

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

    Science.gov (United States)

    Marcum, James A

    2013-10-01

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

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

    Science.gov (United States)

    Marcum, James A

    2013-10-01

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

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

    Science.gov (United States)

    Vyazilov, Evgeny; Chunyaev, Nikita

    2013-04-01

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

  20. Decision support methods for finding phenotype--disorder associations in the bone dysplasia domain.

    Directory of Open Access Journals (Sweden)

    Razan Paul

    Full Text Available A lack of mature domain knowledge and well established guidelines makes the medical diagnosis of skeletal dysplasias (a group of rare genetic disorders a very complex process. Machine learning techniques can facilitate objective interpretation of medical observations for the purposes of decision support. However, building decision support models using such techniques is highly problematic in the context of rare genetic disorders, because it depends on access to mature domain knowledge. This paper describes an approach for developing a decision support model in medical domains that are underpinned by relatively sparse knowledge bases. We propose a solution that combines association rule mining with the Dempster-Shafer theory (DST to compute probabilistic associations between sets of clinical features and disorders, which can then serve as support for medical decision making (e.g., diagnosis. We show, via experimental results, that our approach is able to provide meaningful outcomes even on small datasets with sparse distributions, in addition to outperforming other Machine Learning techniques and behaving slightly better than an initial diagnosis by a clinician.

  1. Decision support system for the operating room rescheduling problem.

    Science.gov (United States)

    van Essen, J Theresia; Hurink, Johann L; Hartholt, Woutske; van den Akker, Bernd J

    2012-12-01

    Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three best adjusted OR schedules. The system considers the preferences of all involved stakeholders and only evaluates the OR schedules that satisfy the imposed resource constraints. The decision rules used for this system are based on a thorough analysis of the OR rescheduling problem. We model this problem as an Integer Linear Program (ILP) which objective is to minimize the deviation from the preferences of the considered stakeholders. By applying this ILP to instances from practice, we determined that the given preferences mainly lead to (i) shifting a surgery and (ii) scheduling a break between two surgeries. By using these changes in the DSS, the performed simulation study shows that less surgeries are canceled and patients and wards are more satisfied, but also that the perceived workload of several departments increases to compensate this. The system can also be used to judge the acceptability of a proposed initial OR schedule.

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

    Science.gov (United States)

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

    2013-05-01

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

  3. An Investment Decision Support System for Process Industries

    Institute of Scientific and Technical Information of China (English)

    周章玉; 成思危; 华贲; 曾敏刚; 尹清华

    2001-01-01

    Most studies on investment evaluation mainly focus on enterprise economic benefits only, without process operability and sustainability considered. In this paper, we suggest that investment evaluation in process industries should be executed under three strategic objectives--enterprise benefits, social benefits and customer benefits. A systematic investment evaluation and decision-making method with a four-step procedure based on the analytic hierarchy process (AHP) is proposed to evaluate various qualitative and quantitative elements with various criteria. At the first step, the decision hierarchy is constructed under the three strategic objectives. Second, pair-wise comparison is utilized to evaluate the weights of elements and criteria. Third, qualitative elements are quantified by pair-wise comparison and quantitative elements are re-scaled by a uniform criterion. At the last, the best choice is made through synthesizing values upward in the hierarchy. An investment decision support system (DSS) is developed based on Microsoft Excel, and applied to a retrofit investment of united fluid catalytic cracking(FCC) and liquefied gas separation process in a refinery plant.

  4. Effects of Clinical Decision Topic on Patients' Involvement in and Satisfaction With Decisions and Their Subsequent Implementation

    DEFF Research Database (Denmark)

    Freidl, Marion; Pesola, Francesca; Konrad, Jana;

    2016-01-01

    OBJECTIVE: Clinical decision making is an important aspect of mental health care. Predictors of how patients experience decision making and whether decisions are implemented are underresearched. This study investigated the relationship between decision topic and involvement in the decision......, satisfaction with it, and its subsequent implementation from both staff and patient perspectives. METHODS: As part of the Clinical Decision Making and Outcome in Routine Care for People With Severe Mental Illness study, patients (N=588) and their providers (N=213) were recruited from community-based mental...... health services in six European countries. Both completed bimonthly assessments for one year using the Clinical Decision Making in Routine Care Scale to assess the decision topic and implementation; both also completed the Clinical Decision Making Involvement and Satisfaction Scale. RESULTS: Three...

  5. Decision Support for Integrated Energy-Water Planning

    Science.gov (United States)

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

    2008-12-01

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

  6. Integrated Decision Support for Global Environmental Change Adaptation

    Science.gov (United States)

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

    2011-12-01

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

  7. Comparing decision-support systems in adopting sustainable intensification criteria

    Directory of Open Access Journals (Sweden)

    Bouda eVosough Ahmadi

    2015-02-01

    Full Text Available Sustainable intensification (SI is a multifaceted concept incorporating the ambition to increase or maintain the current level of agricultural yields while reduce negative ecological and environmental impacts. Decision-support systems (DSS that use integrated analytical methods are often used to support decision making processes in agriculture. However, DSS often consist of set of values, objectives and assumptions that may be inconsistent or in conflict with merits and objectives of SI. These potential conflicts will have consequences for adoption and up-take of agricultural research, technologies and related policies and regulations such as genetic technology in pursuit of SI. This perspective paper aimed at comparing a number of frequently used socio-economic DSS with respect to their capacity in incorporating various dimensions of SI, and discussing their application to analyzing farm animal genetic resources (FAnGR policies. The case of FAnGR policies was chosen because of its great potential in delivering merits of SI. It was concluded that flexible DSS, with great integration capacity with various natural and social sciences, are needed to provide guidance on feasibility, practicality and policy implementation for SI.

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

    Directory of Open Access Journals (Sweden)

    Alexandra Ruiz G.

    2010-05-01

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

  9. Retooling institutional support infrastructure for clinical research.

    Science.gov (United States)

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

    2016-05-01

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

  10. Retooling institutional support infrastructure for clinical research.

    Science.gov (United States)

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

    2016-05-01

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

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

    International Nuclear Information System (INIS)

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

  12. Aggregation of Environmental Model Data for Decision Support

    Science.gov (United States)

    Alpert, J. C.

    2013-12-01

    model output offering access to probability and calibrating information for real time decision making. The aggregation content server reports over ensemble component and forecast time in addition to the other data dimensions of vertical layer and position for each variable. The unpacking, organization and reading of many binary packed files is accomplished most efficiently on the server while weather element event probability calculations, the thresholds for more accurate decision support, or display remain for the client. Our goal is to reduce uncertainty for variables of interest, e.g, agricultural importance. The weather service operational GFS model ensemble and short range ensemble forecasts can make skillful probability forecasts to alert users if and when their selected weather events will occur. A description of how this framework operates and how it can be implemented using existing NOMADS content services and applications is described.

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

    Science.gov (United States)

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

    2013-01-01

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

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

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

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

    2009-04-01

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

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

    Science.gov (United States)

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

    2006-12-01

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

  17. Mining balance disorders' data for the development of diagnostic decision support systems.

    Science.gov (United States)

    Exarchos, T P; Rigas, G; Bibas, A; Kikidis, D; Nikitas, C; Wuyts, F L; Ihtijarevic, B; Maes, L; Cenciarini, M; Maurer, C; Macdonald, N; Bamiou, D-E; Luxon, L; Prasinos, M; Spanoudakis, G; Koutsouris, D D; Fotiadis, D I

    2016-10-01

    In this work we present the methodology for the development of the EMBalance diagnostic Decision Support System (DSS) for balance disorders. Medical data from patients with balance disorders have been analysed using data mining techniques for the development of the diagnostic DSS. The proposed methodology uses various data, ranging from demographic characteristics to clinical examination, auditory and vestibular tests, in order to provide an accurate diagnosis. The system aims to provide decision support for general practitioners (GPs) and experts in the diagnosis of balance disorders as well as to provide recommendations for the appropriate information and data to be requested at each step of the diagnostic process. Detailed results are provided for the diagnosis of 12 balance disorders, both for GPs and experts. Overall, the reported accuracy ranges from 59.3 to 89.8% for GPs and from 74.3 to 92.1% for experts. PMID:27619194

  18. Improving life cycle assessment methodology for the application of decision support

    DEFF Research Database (Denmark)

    Herrmann, Ivan Tengbjerg

    for the application of decision support and evaluation of uncertainty in LCA. From a decision maker’s (DM’s) point of view there are at least three main “illness” factors influencing the quality of the information that the DM uses for making decisions. The factors are not independent of each other, but it seems...... the different steps. A deterioration of the quality in each step is likely to accumulate through the statistical value chain in terms of increased uncertainty and bias. Ultimately this can make final decision support problematic. The "Law of large numbers" (LLN) is the methodological tool/probability theory......) refrain from making a decision based on an LCA and thus support a decision on other parameters than the LCA environmental parameters. Conversely, it may in some decision support contexts be acceptable to base a decision on highly uncertain information. This all depends on the specific decision support...

  19. Data assimilation in the decision support system RODOS

    International Nuclear Information System (INIS)

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

  20. Knowledge model-based decision support system for maize management

    Institute of Scientific and Technical Information of China (English)

    GUO Yinqiao; ZHAO Chuande; WANG Wenxin; LI Cundong

    2007-01-01

    Based on the relationship between crops and circumstances,a dynamic knowledge model for maize management with wide applicability was developed using the system method and mathematical modeling technique.With soft component characteristics incorporated,a component and digital knowledge model-based decision support system for maize management was established on the Visual C++platform.This system realized six major functions:target yield calculation,design of pre-sowing plan,prediction of regular indices,real-time management control,expert knowledge reference and system administration.Cases were studied on the target yield knowledge model with data sets that include different eco-sites,yield levels of the last three years,and fertilizer and water management levels.The results indicated that this system overcomes the shortcomings of traditional expert systems and planting patterns,such as sitespecific conditions and narrow applicability,and can be used more under different conditions and environments.This system provides a scientific knowledge system and a broad decision-making tool for maize management.

  1. Integrating Software Repository Mining: A Decision Support Centered Approach

    Directory of Open Access Journals (Sweden)

    Luiz Dourado Dias Junior

    2012-12-01

    Full Text Available Mining software repositories (MSR research had significantly contributed to software engineering.However, MSR results integration across repositories is a recent concern that is getting more attentionfrom researchers each day. Some noticeable research in this sense is related to the approximation betweenMSR and semantic web, specially linked data approaches which makes it possible to integrate repositoriesand mined results. Manifested that way, we believe that current research is not fully addressing thepractical integration of MSR results, specially, in software engineering due to not considering that theseresults needs to be integrated to the tools as assistance to activity performers, as a kind of decision makingsupport. Based on this statement this research describes an approach, named Sambasore, which isconcerned with MSR results inter-repository integration and also to decision making support processes,based on tool assistance modelling. To show its feasibility we describe the main concepts, some relatedworks and also a proof of concept experiment applied to a software process modelling tool named SpiderPM.

  2. Integrated environmental decision support tool based on GIS technology

    International Nuclear Information System (INIS)

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

  3. Query-handling in MLM-based decision support systems.

    Science.gov (United States)

    Arkad, K; Gao, X M; Ahlfeldt, H

    1995-01-01

    Arden Syntax for Medical Logic Modules is a standard specification for creation and sharing of knowledge bases. The standard specification focuses on knowledge that can be represented as a set of independent Medical Logic Modules (MLMs) such as rules, formulas and protocols. The basic functions of an MLM are to retrieve patient data, manipulate the data, come to some decision, and possibly perform an action. All connections to the world outside an MLM are collected in the data-slot of the MLM. The institution specific parts of these connections are inside the notation of curly brackets ([]) to facilitate sharing of MLM between institutions. This paper focuses on some of the problems that occur in relation to Arden Syntax and connections to a patient database such as database queries. Problems related to possibilities of moving one or several module(s) are also discussed, with emphasis on database connections. As an example, an MLM based Decision Support System (DSS) developed at Linköping University is described. PMID:8882561

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

    DEFF Research Database (Denmark)

    Roued-Cunliffe, Henriette

    2011-01-01

    The research presented in this thesis is based in the Humanities discipline of Ancient History and begins by attempting to understand the interpretation process involved in reading ancient documents and how this process can be aided by computer systems such as Decision Support Systems (DSS...... this process in the five areas: remembering complex reasoning, searching huge datasets, international collaboration, publishing editions, and image enhancement. This research contains a large practical element involving the development of a DSS prototype. The prototype is used to illustrate how a DSS...... such as ‘these strokes look like the letter c’ or ‘these five letters must be the word primo’. Furthermore, the thesis demonstrates how technology such as Web Services and XML can be used to make a DSS even more powerful through the development of the APPELLO word search Web Service. Finally, the conclusion...

  5. Visitor schedule management system- an intelligent decision support system

    CERN Document Server

    Nidhra, Srinivas; Ethiraj, Vinay Sudha

    2012-01-01

    Travelling salesman problem is a problem which is of high interest for researchers, industry professionals, and academicians. Visitor or salesman used to face lot of problems with respect to scheduling based on meeting top ranked clients. Even excel sheet made the work tedious. So these flaws propelled us to design an intelligent decision support system. This paper reports the problem definition we tried to address and possible solution to this problem. We even explained the project design and implementation of our visitor schedule management system.. Our system made a major contribution in terms of valuable resources such as time and satisfying high ranked clients efficiently. We used optimization via mathematical programming to solve these issues.

  6. New decision support tool for acute lymphoblastic leukemia classification

    Science.gov (United States)

    Madhukar, Monica; Agaian, Sos; Chronopoulos, Anthony T.

    2012-03-01

    In this paper, we build up a new decision support tool to improve treatment intensity choice in childhood ALL. The developed system includes different methods to accurately measure furthermore cell properties in microscope blood film images. The blood images are exposed to series of pre-processing steps which include color correlation, and contrast enhancement. By performing K-means clustering on the resultant images, the nuclei of the cells under consideration are obtained. Shape features and texture features are then extracted for classification. The system is further tested on the classification of spectra measured from the cell nuclei in blood samples in order to distinguish normal cells from those affected by Acute Lymphoblastic Leukemia. The results show that the proposed system robustly segments and classifies acute lymphoblastic leukemia based on complete microscopic blood images.

  7. Decision Support for Iteration Scheduling in Agile Environments

    Science.gov (United States)

    Szőke, Ákos

    Today’s software business development projects often lay claim to low-risk value to the customers in order to be financed. Emerging agile processes offer shorter investment periods, faster time-to-market and better customer satisfaction. To date, however, in agile environments there is no sound methodological schedule support contrary to the traditional plan-based approaches. To address this situation, we present an agile iteration scheduling method whose usefulness is evaluated with post-mortem simulation. It demonstrates that the method can significantly improve load balancing of resources (cca. 5×), produce higher quality and lower-risk feasible schedule, and provide more informed and established decisions by optimized schedule production. Finally, the paper analyzes benefits and issues from the use of this method.

  8. NOAA Climate Information and Tools for Decision Support Services

    Science.gov (United States)

    Timofeyeva, M. M.; Higgins, W.; Strager, C.; Horsfall, F. M.

    2013-12-01

    NOAA is an active participant of the Global Framework for Climate Services (GFCS) contributing data, information, analytical capabilities, forecasts, and decision support services to the Climate Services Partnership (CSP). These contributions emerge from NOAA's own climate services, which have evolved to respond to the urgent and growing need for reliable, trusted, transparent, and timely climate information across all sectors of the U.S. economy. Climate services not only enhance development opportunities in many regions, but also reduce vulnerability to climate change around the world. The NOAA contribution lies within the NOAA Climate Goal mission, which is focusing its efforts on four key climate priority areas: water, extremes, coastal inundation, and marine ecosystems. In order to make progress in these areas, NOAA is exploiting its fundamental capabilities, including foundational research to advance understanding of the Earth system, observations to preserve and build the climate data record and monitor changes in climate conditions, climate models to predict and project future climate across space and time scales, and the development and delivery of decision support services focused on risk management. NOAA's National Weather Services (NWS) is moving toward provision of Decision Support Services (DSS) as a part of the Roadmap on the way to achieving a Weather Ready National (WRN) strategy. Both short-term and long-term weather, water, and climate information are critical for DSS and emergency services and have been integrated into NWS in the form of pilot projects run by National and Regional Operations Centers (NOC and ROCs respectively) as well as several local offices. Local offices with pilot projects have been focusing their efforts on provision of timely and actionable guidance for specific tasks such as DSS in support of Coastal Environments and Integrated Environmental Studies. Climate information in DSS extends the concept of climate services to

  9. Fundamental research of decision support systems: Final report

    International Nuclear Information System (INIS)

    Through an iterative application of Decision Support Systems (DSS) apparatus and evolution of DSS concepts, we redefined DSS from a systems perspective. By focusing on successful DSS and the definition of success for the newly-defined DSS, we generated a paradigm for understanding, applying, and improving DSS. The significance of the research is that we now: (1) understand the various roles management tools play within the new DSS concept; (2) recognize the need for characterizing the domain of responsibility of a manager to obtain a successful DSS; and (3) have learned special characteristics of government agencies like Nuclear Materials (NM) to identify what features of the new DSS concept can be expected to improve performance

  10. Decision Support System for Blockage Management in Fire Service

    Directory of Open Access Journals (Sweden)

    Krasuski Adam

    2014-08-01

    Full Text Available In this article we present the foundations of a decision support system for blockage management in Fire Service. Blockage refers to the situation when all fire units are out and a new incident occurs. The approach is based on two phases: off-line data preparation and online blockage estimation. The off-line phase consists of methods from data mining and natural language processing and results in semantically coherent information granules. The online phase is about building the probabilistic models that estimate the block-age probability based on these granules. Finally, the selected classifier judges whether a blockage can occur and whether the resources from neighbour fire stations should be asked for assistance.

  11. Decision support systems and methods for complex networks

    Science.gov (United States)

    Huang, Zhenyu; Wong, Pak Chung; Ma, Jian; Mackey, Patrick S; Chen, Yousu; Schneider, Kevin P

    2012-02-28

    Methods and systems for automated decision support in analyzing operation data from a complex network. Embodiments of the present invention utilize these algorithms and techniques not only to characterize the past and present condition of a complex network, but also to predict future conditions to help operators anticipate deteriorating and/or problem situations. In particular, embodiments of the present invention characterize network conditions from operation data using a state estimator. Contingency scenarios can then be generated based on those network conditions. For at least a portion of all of the contingency scenarios, risk indices are determined that describe the potential impact of each of those scenarios. Contingency scenarios with risk indices are presented visually as graphical representations in the context of a visual representation of the complex network. Analysis of the historical risk indices based on the graphical representations can then provide trends that allow for prediction of future network conditions.

  12. AQUAZONE: A Spatial Decision Support System for Aquatic Zone Management

    Directory of Open Access Journals (Sweden)

    Sekhri A. Arezki

    2015-03-01

    Full Text Available During the last years, the Sebkha Lake of Oran (Algeria has been the subject of many studies for its protection and recovery. Many environmental and wetlands experts are a hope on the integration of this rich and fragile space, ecologically, as a pilot project in "management of water tides". Support the large of Sebkha (Lake of Oran is a major concern for governments looking to make this a protected natural area and viable place. It was a question of putting in place a management policy to respond to the requirements of economic, agricultural and urban development and the preservation of this natural site through management of its water and the preservation of its quality. The objective of this study is to design and develop a Spatial Decision Support System, namely AQUAZONE, able to assist decision makers in various natural resource management projects. The proposed system integrates remote sensing image processing methods, from display operations, to analysis results, in order to extract useful knowledge to best natural resource management, and in particular define the extension of Sebkha Lake of Oran (Algeria. Two methods were applied to classify LANDSAT 5 TM images of Oran (Algeria: Fuzzy C-Means (FCM applied on multi spectral images, and the other that comes with the manual which is the Ordered Queue-based Watershed (OQW. The FCM will serve as initialization phase, to automatically discover the different classes (urban, forest, water, etc.. from a LANDSAT 5 TM images, and also minimize ambiguity in grayscale and establish Land cover map of this region.

  13. SERVIR: A Regional Monitoring and Decision Support System for Mesoamerica

    Science.gov (United States)

    Irwin, D.; Hardin, D. M.; Sever, T.; Graves, S.

    2008-05-01

    Mesoamerica is a prime example of a multi-national region with natural and human induced stresses that benefits from information provided by observation systems. The region is severely threatened by extensive deforestation, illegal logging, water pollution, and uncontrolled slash and burn agriculture. Additionally, Mesoamerica's distinct geology and geography result in disproportionate vulnerability of its population to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, the University of Alabama in Huntsville and numerous SERVIR* partners are developing data products, knowledge extraction methods and decision support tools for environmental monitoring, disaster response and sustainable growth planning in Mesoamerica. The combination of space- based observations from NASA's Earth Observing Satellites with information management and knowledge extraction technologies has yielded a robust system for use by scientists, educators, environmental ministers and policy makers. These resources enhance the ability to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. Now in its fourth year SERVIR has become a partner in the International Space and Major Disasters Charter. In the past year the Charter provided commercial satellite imagery to aid in disaster response to Hurricanes Dean, Felix and Noel. Overcoming roadblocks to coordination and data sharing between countries, organizations and disciplines SERVIR is providing environmental monitoring and decision support products and applications that directly map to several Observation GEOSS societal benefit areas. This paper provides an overview of the ongoing accomplishments of the SERVIR project. *SERVIR is a Spanish verb meaning "to serve" or "be useful" is also an acronym for the Spanish name of the capability: Sistema Regional de Visualizacion y Monitero.

  14. Decision tools for coral reef managers: Using participatory decision support to integrate potential climate impacts and informed decision making

    Directory of Open Access Journals (Sweden)

    Pamela J. Fletcher

    2015-07-01

    Full Text Available The decline in coral reef health presents a complex management issue. While several causes of decline have been identified and are under continued study, it is often difficult to discern management actions necessary to address multiple near- and far-field stressors to these ecosystems. As a result, resource managers seek tools to improve the understanding of ecosystem condition and to develop management responses to reduce local and regional pressures in the wake of larger, global impacts. A research study conducted from 2010 to 2014 in southeast Florida, USA consisted of two objectives: (1 conduct a needs assessment survey with coral reef and marine resource managers to identify data needs and the preferred design and delivery of climate information; and (2 develop and evaluate prototype decision support tools. The needs assessment process was helpful for identifying the types of climate information managers would like to obtain to inform decision making and to specify the preferred format for the delivery of that information. Three prototype tools were evaluated by managers using pre/post surveys that included hands-on tutorials to explore the functionality of each. Manager responses were recorded using a five-point scale with 1 being No or Not Useful to 5 being Absolutely or Very Useful. The median responses rated the usefulness of the tools (4, if they would consider using the tool (4, and if they would recommend using the tool to other managers (4 or 5. The median response for increasing manager’s knowledge about climate impacts after completing a tutorial of each of the climate tools was a 3 (moderately useful. Of the managers surveyed in the pre/post-survey, all but one stated they believed they would use the decision support tools in the future with the single response due to wealth of data availability in their institution.

  15. Observations to support adaptation: Principles, scales and decision-making

    Science.gov (United States)

    Pulwarty, R. S.

    2012-12-01

    As has been long noted, a comprehensive, coordinated observing system is the backbone of any Earth information system. Demands are increasingly placed on earth observation and prediction systems and attendant services to address the needs of economically and environmentally vulnerable sectors and investments, including energy, water, human health, transportation, agriculture, fisheries, tourism, biodiversity, and national security. Climate services include building capacity to interpret information and recognize standards and limitations of data in the promotion of social and economic development in a changing climate. This includes improving the understanding of climate in the context of a variety of temporal and spatial scales (including the influence of decadal scale forcings and land surface feedbacks on seasonal forecast reliability). Climate data and information are central for developing decision options that are sensitive to climate-related uncertainties and the design of flexible adaptation pathways. Ideally monitoring should be action oriented to support climate risk assessment and adaptation including informing robust decision making to multiple risks over the long term. Based on the experience of global observations programs and empirical research we outline- Challenges in developing effective monitoring and climate information systems to support adaptation. The types of observations of critical importance needed for sector planning to enhance food, water and energy security, and to improve early warning for disaster risk reduction Observations needed for ecosystem-based adaptation including the identification of thresholds, maintenance of biological diversity and land degradation The benefits and limits of linking regional model output to local observations including analogs and verification for adaptation planning To support these goals a robust systems of integrated observations are needed to characterize the uncertainty surrounding emergent risks

  16. Supporting Clinical Cognition: A Human-Centered Approach to a Novel ICU Information Visualization Dashboard

    OpenAIRE

    Faiola, Anthony; Srinivas, Preethi; Duke, Jon

    2015-01-01

    Advances in intensive care unit bedside displays/interfaces and electronic medical record (EMR) technology have not adequately addressed the topic of visual clarity of patient data/information to further reduce cognitive load during clinical decision-making. We responded to these challenges with a human-centered approach to designing and testing a decision-support tool: MIVA 2.0 (Medical Information Visualization Assistant, v.2). Envisioned as an EMR visualization dashboard to support rapid a...

  17. Improvements in agricultural water decision support using remote sensing

    Science.gov (United States)

    Marshall, M. T.

    2012-12-01

    Population driven water scarcity, aggravated by climate-driven evaporative demand in dry regions of the world, has the potential of transforming ecological and social systems to the point of armed conflict. Water shortages will be most severe in agricultural areas, as the priority shifts to urban and industrial use. In order to design, evaluate, and monitor appropriate mitigation strategies, predictive models must be developed that quantify exposure to water shortage. Remote sensing data has been used for more than three decades now to parametrize these models, because field measurements are costly and difficult in remote regions of the world. In the past decade, decision-makers for the first time can make accurate and near real-time evaluations of field conditions with the advent of hyper- spatial and spectral and coarse resolution continuous remote sensing data. Here, we summarize two projects representing diverse applications of remote sensing to improve agricultural water decision support. The first project employs MODIS (coarse resolution continuous data) to drive an evapotranspiration index, which is combined with the Standardized Precipitation Index driven by meteorological satellite data to improve famine early warning in Africa. The combined index is evaluated using district-level crop yield data from Kenya and Malawi and national-level crop yield data from the United Nations Food and Agriculture Organization. The second project utilizes hyper- spatial (GeoEye 1, Quickbird, IKONOS, and RapidEye) and spectral (Hyperion/ALI), as well as multi-spectral (Landsat ETM+, SPOT, and MODIS) data to develop biomass estimates for key crops (alfalfa, corn, cotton, and rice) in the Central Valley of California. Crop biomass is an important indicator of crop water productivity. The remote sensing data is combined using various data fusion techniques and evaluated with field data collected in the summer of 2012. We conclude with a brief discussion on implementation of

  18. Knowledge Driven HealthCare Decision Support System using Distributed Data Mining

    OpenAIRE

    P.T.Kavitha; Dr.T.Sasipraba

    2012-01-01

    this paper focuses on a web based decision support system which is based on distributed data mining and designed for the healthcare industry. Innumerable Decision Support Systems are prevailingin the market to cater the needs of the various industries based on various purposes. The importance of any Decision Support System resides on the quality of information it provides compared to otherinformation system which leads to take effective decision making. As most of the records in the healthcar...

  19. FRAMEWORK FOR DECISION SUPPORT USED IN CONTAMINATED LAND MANAGEMENT IN EUROPE AND NORTH AMERICA.

    Energy Technology Data Exchange (ETDEWEB)

    SULLIVAN,T.; BARDOS,R.P.; MAROT,C.; MARIOTTI,R.

    2000-06-01

    Effective contaminated land management requires a number of decisions addressing a suite of technical, economic and social concerns. This paper offers a common framework and terminology for describing decision support approaches, along with an overview of recent applications of decision support tools in Europe and the USA. A common problem with work on decision support approaches is a lack of a common framework and terminology to describe the process. These have been proposed in this paper.

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

    Directory of Open Access Journals (Sweden)

    Huser V

    2014-09-01

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

  1. The Aegean Sea marine security decision support system

    Directory of Open Access Journals (Sweden)

    L. Perivoliotis

    2011-05-01

    Full Text Available As part of the integrated ECOOP (European Coastal Sea Operational observing and Forecasting System project, HCMR upgraded the already existing standalone Oil Spill Forecasting System for the Aegean Sea, initially developed for the Greek Operational Oceanography System (POSEIDON, into an active element of the European Decision Support System (EuroDeSS. The system is accessible through a user friendly web interface where the case scenarios can be fed into the oil spill drift model component, while the synthetic output contains detailed information about the distribution of oil spill particles and the oil spill budget and it is provided both in text based ECOOP common output format and as a series of sequential graphics. The main development steps that were necessary for this transition were the modification of the forcing input data module in order to allow the import of other system products which are usually provided in standard formats such as NetCDF and the transformation of the model's calculation routines to allow use of current, density and diffusivities data in z instead of sigma coordinates. During the implementation of the Aegean DeSS, the system was used in operational mode in order support the Greek marine authorities in handling a real accident that took place in North Aegean area. Furthermore, the introduction of common input and output files by all the partners of EuroDeSS extended the system's interoperability thus facilitating data exchanges and comparison experiments.

  2. The Aegean sea marine security decision support system

    Directory of Open Access Journals (Sweden)

    L. Perivoliotis

    2011-10-01

    Full Text Available As part of the integrated ECOOP (European Coastal Sea Operational observing and Forecasting System project, HCMR upgraded the already existing standalone Oil Spill Forecasting System for the Aegean Sea, initially developed for the Greek Operational Oceanography System (POSEIDON, into an active element of the European Decision Support System (EuroDeSS. The system is accessible through a user friendly web interface where the case scenarios can be fed into the oil spill drift model component, while the synthetic output contains detailed information about the distribution of oil spill particles and the oil spill budget and it is provided both in text based ECOOP common output format and as a series of sequential graphics. The main development steps that were necessary for this transition were the modification of the forcing input data module in order to allow the import of other system products which are usually provided in standard formats such as NetCDF and the transformation of the model's calculation routines to allow use of current, density and diffusivities data in z instead of sigma coordinates. During the implementation of the Aegean DeSS, the system was used in operational mode in order to support the Greek marine authorities in handling a real accident that took place in North Aegean area. Furthermore, the introduction of common input and output files by all the partners of EuroDeSS extended the system's interoperability thus facilitating data exchanges and comparison experiments.

  3. Marketing Decision Support System - As a Factor for Effective Marketing Management

    OpenAIRE

    Karolina Ilieska

    2013-01-01

    Strategic decisions are made in uncertain conditions and high risk. Systems of supporting strategic decision contributed to minimizing the risk in making the decision. They offer possibilities for modern communication, model’s experiments, before testing of ideas, surveillance of effects of strategic decisions.

  4. Documentation of a decision framework to support enhanced sludge washing

    Energy Technology Data Exchange (ETDEWEB)

    Brothers, A.J.

    1995-12-31

    This document describes a proposed decision model that, if developed to its fullest, can provide a wide range of analysis options and insights to pretreatment/sludge washing alternatives. A recent decision has been made to terminate this work

  5. The development of a disease oriented eFolder for multiple sclerosis decision support

    Science.gov (United States)

    Ma, Kevin; Jacobs, Colin; Fernandez, James; Amezcua, Lilyana; Liu, Brent

    2010-03-01

    Multiple sclerosis (MS) is a demyelinating disease of the central nervous system. The chronic nature of MS necessitates multiple MRI studies to track disease progression. Currently, MRI assessment of multiple sclerosis requires manual lesion measurement and yields an estimate of lesion volume and change that is highly variable and user-dependent. In the setting of a longitudinal study, disease trends and changes become difficult to extrapolate from the lesions. In addition, it is difficult to establish a correlation between these imaged lesions and clinical factors such as treatment course. To address these clinical needs, an MS specific e-Folder for decision support in the evaluation and assessment of MS has been developed. An e-Folder is a disease-centric electronic medical record in contrast to a patient-centric electronic health record. Along with an MS lesion computer aided detection (CAD) package for lesion load, location, and volume, clinical parameters such as patient demographics, disease history, clinical course, and treatment history are incorporated to make the e-Folder comprehensive. With the integration of MRI studies together with related clinical data and informatics tools designed for monitoring multiple sclerosis, it provides a platform to improve the detection of treatment response in patients with MS. The design and deployment of MS e-Folder aims to standardize MS lesion data and disease progression to aid in decision making and MS-related research.

  6. Decision Support Tool for Prioritization of Surveillance and Maintenance Investment

    International Nuclear Information System (INIS)

    The Department of Energy (DOE) currently faces a difficult task in the disposition of the numerous excess or to-be excessed facilities owned by the Department. Many of these facilities are in various physical conditions and contain potentially hazardous nuclear, chemical, radiological or industrial materials left behind as a byproduct of nuclear weapons production, nuclear powered naval vessels and commercial nuclear energy production. During the last period of a facility's life cycle, it is important that surveillance and maintenance (S and M) be adequate to maintain the facility within an appropriate safety envelope. Inadequate investment in maintenance can cause facilities to deteriorate to the point they are unsafe for human entry. Too often this can mean tremendous increases to cost during deactivation and decommissioning (D and D). However, experiences often show that once buildings have been declared excess and enter the transition phase (as defined in DOE G 430.1-5 Transition Implementation Guide), maintenance budgets are drastically reduced. This is justified by the desire to not spend money 'on a building that is being torn down'. The objective of this study was to provide the U.S. Department of Energy (DOE) Environmental Management (EM) federal project directors and their contractors with a decision support tool to aid in prioritizing S and M investment across a site's excess facilities so that the limited budget available can be used most effectively. The analytical hierarchy process (AHP), a multi-criteria decision making method developed by Dr. Thomas Saaty in the 1970's, was used to derive the weight of importance of a defined list of risk-based criteria and typical S and M activities. A total of 10 facilities at the Oak Ridge National Laboratory (ORNL) varying in perceived hazards and conditions were chosen to test the tool by evaluating them with respect to each risk criterion and combining these results with the weight of importance of the S and M

  7. Developing a Software for Fuzzy Group Decision Support System: A Case Study

    Science.gov (United States)

    Baba, A. Fevzi; Kuscu, Dincer; Han, Kerem

    2009-01-01

    The complex nature and uncertain information in social problems required the emergence of fuzzy decision support systems in social areas. In this paper, we developed user-friendly Fuzzy Group Decision Support Systems (FGDSS) software. The software can be used for multi-purpose decision making processes. It helps the users determine the main and…

  8. Effects on decision quality of supporting multi-attribute evaluation in groups

    NARCIS (Netherlands)

    Vlek, C.A.J.; Timmermans, D.

    1996-01-01

    In this study the effectiveness of multi-attribute utility (MAU) decision support in groups is evaluated for personnel selection problems differing in complexity. Subjects were asked to make an initial individual decision with or without MAU decision support. Next individuals formed small groups and

  9. NWS Alaska Sea Ice Program: Operations and Decision Support Services

    Science.gov (United States)

    Schreck, M. B.; Nelson, J. A., Jr.; Heim, R.

    2015-12-01

    The National Weather Service's Alaska Sea Ice Program is designed to service customers and partners operating and planning operations within Alaska waters. The Alaska Sea Ice Program offers daily sea ice and sea surface temperature analysis products. The program also delivers a five day sea ice forecast 3 times each week, provides a 3 month sea ice outlook at the end of each month, and has staff available to respond to sea ice related information inquiries. These analysis and forecast products are utilized by many entities around the state of Alaska and nationally for safety of navigation and community strategic planning. The list of current customers stem from academia and research institutions, to local state and federal agencies, to resupply barges, to coastal subsistence hunters, to gold dredgers, to fisheries, to the general public. Due to a longer sea ice free season over recent years, activity in the waters around Alaska has increased. This has led to a rise in decision support services from the Alaska Sea Ice Program. The ASIP is in constant contact with the National Ice Center as well as the United States Coast Guard (USCG) for safety of navigation. In the past, the ASIP provided briefings to the USCG when in support of search and rescue efforts. Currently, not only does that support remain, but our team is also briefing on sea ice outlooks into the next few months. As traffic in the Arctic increases, the ASIP will be called upon to provide more and more services on varying time scales to meet customer needs. This talk will address the many facets of the current Alaska Sea Ice Program as well as delve into what we see as the future of the ASIP.

  10. Future of medical knowledge management and decision support.

    Science.gov (United States)

    Greenes, Robert A

    2002-01-01

    Attempts to predict the future are typically off the mark. Beyond the challenges of forecasting the stock market or the weather, dramatic instances of notoriously inaccurate prognostications have been those by the US patent office in the late 1800s about the future of inventions, by Thomas Watson in the 1930s about the market for large computers, and by Bill Gates in the early 1990s about the significance of the Internet. When one seeks to make predictions about health care, one finds that, beyond the usual uncertainties regarding the future, additional impediments to forecasting are the discontinuities introduced by advances in biomedical science and technology, the impact of information technology, and the reorganizations and realignments attending various approaches to health care delivery and finance. Changes in all three contributing areas themselves can be measured in "PSPYs", or paradigm shifts per year. Despite these risks in forecasting, I believe that certain trends are sufficiently clear that I am willing to venture a few predictions. Further, the predictions I wish to make suggest a goal for the future that can be achieved, if we can align the prevailing political, financial, biomedical, and technical forces toward that end. Thus, in a sense this is a call to action, to shape the future rather than just let it happen. This chapter seeks to lay out the direction we are heading in knowledge management and decision support, and to delineate an information technology framework that appears desirable. I believe the framework to be discussed is of importance to the health care-related knowledge management and decision making activities of the consumer and patient, the health care provider, and health care delivery organizations and insurers. The approach is also relevant to the other dimensions of academic health care institution activities, notably the conduct of research and the processes of education and learning. PMID:12026135

  11. Flight Deck Weather Avoidance Decision Support: Implementation and Evaluation

    Science.gov (United States)

    Wu, Shu-Chieh; Luna, Rocio; Johnson, Walter W.

    2013-01-01

    Weather related disruptions account for seventy percent of the delays in the National Airspace System (NAS). A key component in the weather plan of the Next Generation of Air Transportation System (NextGen) is to assimilate observed weather information and probabilistic forecasts into the decision process of flight crews and air traffic controllers. In this research we explore supporting flight crew weather decision making through the development of a flight deck predicted weather display system that utilizes weather predictions generated by ground-based radar. This system integrates and presents this weather information, together with in-flight trajectory modification tools, within a cockpit display of traffic information (CDTI) prototype. that the CDTI features 2D and perspective 3D visualization models of weather. The weather forecast products that we implemented were the Corridor Integrated Weather System (CIWS) and the Convective Weather Avoidance Model (CWAM), both developed by MIT Lincoln Lab. We evaluated the use of CIWS and CWAM for flight deck weather avoidance in two part-task experiments. Experiment 1 compared pilots' en route weather avoidance performance in four weather information conditions that differed in the type and amount of predicted forecast (CIWS current weather only, CIWS current and historical weather, CIWS current and forecast weather, CIWS current and forecast weather and CWAM predictions). Experiment 2 compared the use of perspective 3D and 21/2D presentations of weather for flight deck weather avoidance. Results showed that pilots could take advantage of longer range predicted weather forecasts in performing en route weather avoidance but more research will be needed to determine what combinations of information are optimal and how best to present them.

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

    Science.gov (United States)

    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

  13. WSN Configuration using Agent Modeling and Hybrid Intelligent Decision Support System

    OpenAIRE

    Alshahrany, F; Hussein Zedan; Idir Moualek

    2014-01-01

    A conceptual multi-agent framework based on a knowledge-based collaborative decision support is proposed in this paper to design hybrid intelligent decision support systems (HIDSS) based on policy settings for the support of intelligent and pro-active decision making activities. An example of HIDSS has been developed to support the design and configuration of small wireless sensor networks (WSN). A WSN prototype is designed in this research to supply real time environmental and context rel...

  14. Towards a Decision Support System for Space Flight Operations

    Science.gov (United States)

    Meshkat, Leila; Hogle, Charles; Ruszkowski, James

    2013-01-01

    The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The discrepancy of the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of

  15. Decision support and data warehousing tools boost competitive advantage.

    Science.gov (United States)

    Waldo, B H

    1998-01-01

    The ability to communicate across the care continuum is fast becoming an integral component of the successful health enterprise. As integrated delivery systems are formed and patient care delivery is restructured, health care professionals must be able to distribute, access, and evaluate information across departments and care settings. The Aberdeen Group, a computer and communications research and consulting organization, believes that "the single biggest challenge for next-generation health care providers is to improve on how they consolidate and manage information across the continuum of care. This involves building a strategic warehouse of clinical and financial information that can be shared and leveraged by health care professionals, regardless of the location or type of care setting" (Aberdeen Group, Inc., 1997). The value and importance of data and systems integration are growing. Organizations that create a strategy and implement DSS tools to provide decision-makers with the critical information they need to face the competition and maintain quality and costs will have the advantage. PMID:9592525

  16. AN IMPROVED MEDICAL DECISION SUPPORT SYSTEM TO GRADING THE DIABETIC RETINOPATHY USING FUNDUS IMAGES

    Directory of Open Access Journals (Sweden)

    M. Madheswaran

    2012-11-01

    Full Text Available An improved Computer Aided Clinical Decision Support System has been developed for grading the retinal images using neural network and presented in this paper. Hard exudates, Cotton wool spots, large plaque hard exudates, Microaneurysms and Hemorrhages have been extracted. SVM classifiers have been used for classification. Further rule based classifiers have been used to grade the retinal images. The percentages of sensitivity, specificity have been found for both bright lesions and dark lesions. The accuracy of the proposed method is capable of detecting the bright and dark lesions sharply with an average accuracy of 98.19% and 97.51% respectively.

  17. Decision support system for the selection of an ITE or a BTE hearing aid

    OpenAIRE

    Anwar, Naveed; Oakes, Michael

    2013-01-01

    The purpose of this research is to mine a large set of heterogeneous audiology data to create a decision support system (DSS) to choose between two hearing aid types (ITE and BTE aid). This research is based on the data analysis of audiology data using various statistical and data mining techniques. It uses the data of a large NHS (National Health Services, UK) facility. It uses 180,000 records (covering more than 23,000 different patients) from a hearing aid clinic. The developed system u...

  18. Decision support system for a reactive management of disaster-caused supply chain disturbances

    OpenAIRE

    Schätter, Frank

    2016-01-01

    This research contribution presents the Reactive Disaster and supply chain Risk decision Support System ReDRiSS which supports decision-makers of logistical disaster management in the immediate aftermath of a supply chain disturbance. ReDRiSS suggests a methodology which combines approaches from scenario techniques, operations research and decision theory. Two case studies are provided which focus on decision situations of humanitarian logistics and of business continuity management.

  19. Why decision support systems are important for medical education.

    Science.gov (United States)

    Konstantinidis, Stathis Th; Bamidis, Panagiotis D

    2016-03-01

    During the last decades, the inclusion of digital tools in health education has rapidly lead to a continuously enlarging digital era. All the online interactions between learners and tutors, the description, creation, reuse and sharing of educational digital resources and the interlinkage between them in conjunction with cheap storage technology has led to an enormous amount of educational data. Medical education is a unique type of education due to accuracy of information needed, continuous changing competences required and alternative methods of education used. Nowadays medical education standards provide the ground for organising the educational data and the paradata. Analysis of such education data through education data mining techniques is in its infancy, but decision support systems (DSSs) for medical education need further research. To the best of our knowledge, there is a gap and a clear need for identifying the challenges for DSSs in medical education in the era of medical education standards. Thus, in this Letter the role and the attributes of such a DSS for medical education are delineated and the challenges and vision for future actions are identified. PMID:27222734

  20. Why decision support systems are important for medical education.

    Science.gov (United States)

    Konstantinidis, Stathis Th; Bamidis, Panagiotis D

    2016-03-01

    During the last decades, the inclusion of digital tools in health education has rapidly lead to a continuously enlarging digital era. All the online interactions between learners and tutors, the description, creation, reuse and sharing of educational digital resources and the interlinkage between them in conjunction with cheap storage technology has led to an enormous amount of educational data. Medical education is a unique type of education due to accuracy of information needed, continuous changing competences required and alternative methods of education used. Nowadays medical education standards provide the ground for organising the educational data and the paradata. Analysis of such education data through education data mining techniques is in its infancy, but decision support systems (DSSs) for medical education need further research. To the best of our knowledge, there is a gap and a clear need for identifying the challenges for DSSs in medical education in the era of medical education standards. Thus, in this Letter the role and the attributes of such a DSS for medical education are delineated and the challenges and vision for future actions are identified.

  1. Decision Support Facility for the APS Control System

    CERN Document Server

    Dohan, D A

    2001-01-01

    The Advanced Photon Source is now in its fifth year of routine beam production. The EPICS-based [1] control system has entered the phase in its life cycle where new control algorithms must be implemented under increasingly stringent operational and reliability requirements. The sheer volume of the control system (~270,000 records, ~145 VME-based input-output controllers (IOCs), and ~7,000,000 lines of EPICS ASCII configuration code), presents a daunting challenge for code maintenance. The present work describes a relational database that provides an integrated view of the interacting components of the entire APS control system, including the IOC low-level logic, the physical wiring documentation, and high-level client applications. The database is extracted (booted) from the same operational CVS repository as that used to load the active IOCs. It provides site-wide decision support facilities to inspect and trace control flow and to identify client (e.g., user interface) programs involved at any selected poin...

  2. Decision support facility for the APS control system.

    Energy Technology Data Exchange (ETDEWEB)

    Dohan, D. A.

    2001-11-12

    The Advanced Photon Source is now in its fifth year of routine beam production. The EPICS-based [1] control system has entered the phase in its life cycle where new control algorithms must be implemented under increasingly stringent operational and reliability requirements. The sheer volume of the control system ({approx}270,000 records, {approx}145 VME-based input-output controllers (IOCs), and {approx}7,000,000 lines of EPICS ASCII configuration code), presents a daunting challenge for code maintenance. The present work describes a relational database that provides an integrated view of the interacting components of the entire APS control system, including the IOC low-level logic, the physical wiring documentation, and high-level client applications. The database is extracted (booted) from the same operational CVS repository as that used to load the active IOCs. It provides site-wide decision support facilities to inspect and trace control flow and to identify client (e.g., user interface) programs involved at any selected point in the front-end logic. The relational database forms a basis for generalized documentation of global control logic and its connection with both the physical I/O and with external high-level applications.

  3. Probabilistic source term predictions for use with decision support systems

    International Nuclear Information System (INIS)

    Full text: Decision Support Systems for use in off-site emergency management, following an incident at a Nuclear Power Plant (NPP) within Europe, are becoming accepted as a useful and appropriate tool to aid decision makers. An area which is not so well developed is the 'upstream' prediction of the source term released into the environment. Rapid prediction of this source term is crucial to the appropriate early management of a nuclear emergency. The initial source term prediction would today be typically based on simple tabulations taking little, or no, account of plant status. It is the interface between the inward looking plant control room team and the outward looking off-site emergency management team that needs to be addressed. This is not an easy proposition as these two distinct disciplines have little common basis from which to communicate their immediate findings and concerns. Within the Euratom Fifth Framework Programme (FP5), complementary approaches are being developed to the pre-release stage; each based on software tools to help bridge this gap. Traditionally source terms (or releases into the environment) provided for use with Decision Support Systems are estimated on a deterministic basis. These approaches use a single, deterministic assumption about plant status. The associated source term represents the 'best estimate' based an available information. No information is provided an the potential for uncertainty in the source term estimate. Using probabilistic methods the outcome is typically a number of possible plant states each with an associated source term and probability. These represent both the best estimate and the spread of the likely source term. However, this is a novel approach and the usefulness of such source term prediction tools is yet to be tested on a wide scale. The benefits of probabilistic source term estimation are presented here; using, as an example, the SPRINT tool developed within the FP5 STERPS project. System for the

  4. Agricultural Model for the Nile Basin Decision Support System

    Science.gov (United States)

    van der Bolt, Frank; Seid, Abdulkarim

    2014-05-01

    To analyze options for increasing food supply in the Nile basin the Nile Agricultural Model (AM) was developed. The AM includes state-of-the-art descriptions of biophysical, hydrological and economic processes and realizes a coherent and consistent integration of hydrology, agronomy and economics. The AM covers both the agro-ecological domain (water, crop productivity) and the economic domain (food supply, demand, and trade) and allows to evaluate the macro-economic and hydrological impacts of scenarios for agricultural development. Starting with the hydrological information from the NileBasin-DSS the AM calculates the available water for agriculture, the crop production and irrigation requirements with the FAO-model AquaCrop. With the global commodity trade model MAGNET scenarios for land development and conversion are evaluated. The AM predicts consequences for trade, food security and development based on soil and water availability, crop allocation, food demand and food policy. The model will be used as a decision support tool to contribute to more productive and sustainable agriculture in individual Nile countries and the whole region.

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

    Science.gov (United States)

    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). PMID:25662862

  6. Research on decision support systems in the current economic context

    OpenAIRE

    Florin BOGHEAN

    2014-01-01

    The complexity of economic activities in terms of the competition imposed by the current economy acts to increase the role of economic financial information in decision-making.The quality of information is paramount for the quality of current and long-term decisions, and therefore for the entity's forecast results.In this article, we intend to perform an analysis of the usefulness of the information provided by the accounting department in decision making processes.The research typology emplo...

  7. Computer aided decision support system for cervical cancer classification

    Science.gov (United States)

    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

  8. Adoption of Web-based Group Decision Support Systems: Conditions for Growth

    NARCIS (Netherlands)

    Hillegersberg, van Jos; Koenen, Sebastiaan

    2014-01-01

    While organizations have massively adopted enterprise information systems to support business processes, business meetings in which key decisions are made about products, services and processes are usually held without much support of information systems. This is remarkable as group decision support

  9. Can a structured electronic medical record with decision-making support improve nursing home quality? Healthcare administration through structured records

    OpenAIRE

    Krüger, Kjell

    2013-01-01

    Background: Nursing homes face challenges in the coming years due to the increased number of elderly. A new law in force from Jan 2012 (“Samhandlingsreformen”) places more responsibilities on the counties running the nursing homes. Quality will come under pressure, expectations of services will rise and clinical complexity will grow. New strategies are needed to meet this situation. Modern clinical information systems with decision-making support may be part of that. In additio...

  10. Information and decision support needs in patients with type 2 diabetes.

    Science.gov (United States)

    Weymann, Nina; Härter, Martin; Dirmaier, Jörg

    2016-03-01

    Diabetes and its sequelae cause a growing burden of morbidity and mortality. For many patients living with diabetes, the Internet is an important source of health information and support. In the course of the development of an Interactive Health Communication Application, combining evidence-based information with behavior change and decision support, we assessed the characteristics, information, and decision support needs of patients with type 2 diabetes.The needs assessment was performed in two steps. First, we conducted semi-structured interviews with 10 patients and seven physicians. In the second step, we developed a self-assessment questionnaire based on the results of the interviews and administered it to a new and larger sample of diabetes patients (N = 178). The questionnaire comprised four main sections: (1) Internet use and Internet experience, (2) diabetes knowledge, (3) relevant decisions and decision preferences, and (4) online health information needs. Descriptive data analyses were performed.In the questionnaire study, the patient sample was heterogeneous in terms of age, time since diagnosis, and glycemic control. (1) Most participants (61.7%) have searched the web for health information at least once. The majority (62%) of those who have used the web use it at least once per month. (2) Diabetes knowledge was scarce: Only a small percentage (1.9%) of the respondents answered all items of the knowledge questionnaire correctly. (3) The most relevant treatment decisions concerned glycemic control, oral medication, and acute complications. The most difficult treatment decision was whether to start insulin treatment. Of the respondents, 69.4 percent thought that medical decisions should be made by them and their doctor together. (4) The most important information needs concerned sequelae of diabetes, blood glucose control, and basic diabetes information.The Internet seems to be a feasible way to reach people with type 2 diabetes. The heterogeneity of the

  11. Informing physicians using a situated decision support system: Disease management for the smart city

    Directory of Open Access Journals (Sweden)

    Raafat George Saade

    2014-12-01

    Full Text Available We are in the midst of a healthcare paradigm shift driven by the wide adoption of ubiquitous computing and various modes of information communications technologies. As a result, cities worldwide are undergoing a major process of urbanization with ever increasing wealth of sensing capabilities – hence the Internet of Things (IoT. These trends impose great pressure on how healthcare is done. This paper describes the design and implementation of a situated clinical decision support (SCDSS system, most appropriate for smart cities. The SCDSS was prototyped and enhanced in a clinic. The SCDSS was then used in a clinic as well as in a university hospital centre. In this article, the system’s architecture, subcomponents and integrated workflow are described. The systems’ design was the result of a knowledge acquisition process involving interviews with five specialists and testing with 50 patients. The reports (specialist consultation report generated by the SCDSS were shown to general practitioners who were not able to distinguish them from human specialist reports. We propose a context-aware CDSS and assess its effectiveness in managing a wide medical range of patients. Five different patient cases were identified for analysis. The SCDSS was used to produce draft electronic specialist consultations, which were then compared to the original specialists’ consultations. It was found that the SCDSS-generated consults were of better quality for a number of reasons discussed herein. SCDSSs have great promise for their use in the clinical environment of smart cities. Valuable insights into the integration and use of situated clinical decision support systems are highlighted and suggestions for future research are given.

  12. Optimization-based decision support systems for planning problems in processing industries

    OpenAIRE

    Claassen, G.D.H.

    2014-01-01

    Summary Optimization-based decision support systems for planning problems in processing industries Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in practice. The tremendous progress in hard- and software of the past decades was an important gateway for developing computerized systems that are able to support decision making on different levels within enterprises. T...

  13. Supporting a distributed execution of clinical guidelines.

    Science.gov (United States)

    Bottrighi, Alessio; Molino, Gianpaolo; Montani, Stefania; Terenziani, Paolo; Torchio, Mauro

    2013-10-01

    Clinical guidelines (GL) play an important role in medical practice: the one of optimizing the quality of patient care on the basis of evidence based medicine. In order to achieve this goal, the interaction between different agents, who cooperate in the execution of the same GL, is a crucial issue. As a matter of fact, in many cases (e.g. in chronic disorders) the GL execution requires that patient treatment is not performed/completed in the hospital, but is continued in different contexts (e.g. at home, or in the general practitioner's ambulatory), under the responsibility of different agents. In this situation, the correct interaction and communication between the agents themselves is critical for the quality of care, and human resources coordination is a key issue to be addressed by the managers of the involved healthcare services. In this paper we describe how GLARE (Guideline Acquisition, Representation, and Execution), a computerized GL management system, has been extended in order to support such a need. In particular, we have provided: (i) an extension to GL actions representation languages, (ii) proper scheduling and (iii) querying services. By means of these enhancements we aimed at guaranteeing (1) treatment continuity and (2) responsibility assignment support in the various steps of a coordinated and distributed patient care process. We illustrate our approach by means of a practical case study. PMID:23942331

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

    Science.gov (United States)

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

    2015-10-01

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

  15. An Oceanographic Decision Support System for Scientific Field Experiments

    Science.gov (United States)

    Maughan, T.; Das, J.; McCann, M. P.; Rajan, K.

    2011-12-01

    Thom Maughan, Jnaneshwar Das, Mike McCann, Danelle Cline, Mike Godin, Fred Bahr, Kevin Gomes, Tom O'Reilly, Frederic Py, Monique Messie, John Ryan, Francisco Chavez, Jim Bellingham, Maria Fox, Kanna Rajan Monterey Bay Aquarium Research Institute Moss Lading, California, United States Many of the coastal ocean processes we wish to observe in order to characterize marine ecosystems have large spatial extant (tens of square km) and are dynamic moving kilometers in a day with biological processes spanning anywhere from minutes to days. Some like harmful algal blooms generate toxins which can significantly impact human health and coastal economies. In order to obtain a viable understanding of the biogeochemical processes which define their dynamics and ecology, it is necessary to persistently observe, track and sample within and near the dynamic fields using augmented methods of observation such as autonomous platforms like AUVs, gliders and surface craft. Field experiments to plan, execute and manage such multitude of assets are challenging. To alleviate this problem the autonomous systems group with its collaborators at MBARI and USC designed, built and fielded a prototype Oceanographic Decision Support System (ODSS) that provides situational awareness and a single portal to visualize and plan deployments for the large scale October 2010 CANON field program as well as a series of 2 week field programs in 2011. The field programs were conducted in Monterey Bay, a known 'red tide' incubator, and varied from as many as twenty autonomous platforms, four ships and 2 manned airplanes to coordinated AUV operations, drifters and a single ship. The ODSS web-based portal was used to assimilate information from a collection of sources at sea, including AUVs, moorings, radar data as well as remote sensing products generated by partner organizations to provide a synthesis of views useful to predict the movement of a chlorophyll patch in the confines of the northern Monterey Bay

  16. A decision support system for managing forest fire casualties.

    Science.gov (United States)

    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. PMID:16928418

  17. Decision support system for monitoring environmental-human interactions.

    Science.gov (United States)

    Delavari-Edalat, Farideh; Abdi, M Reza

    2009-06-01

    The specific aim of this study is to investigate popular attitudes toward trees. The paper is involved the understanding of biophilia tendencies with respect to people's views in an urban area. Biophilia is considered as the idea insisting on the dependency of human identity on his relationship with nature. The biophilia fundamental tendencies were explored to establish a biological framework for valuing and affiliating the natural world. Accordingly, the nine tendencies i.e. utilitarian, naturalistic, ecologistic-scientific, aesthetic, symbolic, humanistic, moralistic, dominionistic, and negativistic were investigate to find out how people relate to the nature especially trees. The investigation was based on a quantitative interview which was applied to the public population in the Liverpool urban parks. Data collected from the designed questionnaire was followed by analysis of the data to identify people's attitudes towards trees. The results indicated how important the physical appeal and beauty of trees was for the people and also showed the people's emotional attachments to trees. Furthermore, a decision support model was proposed to evaluate human instincts and preferences in relation to their surrounding areas using the Analytical Hierarchical Process (AHP). The proposed model composed the environmental factors and the biophilia tendencies as the criteria of evaluating environmental-human interactions. A case study was then conducted in Liverpool parks to examine theses interactions. The data gathered was used as the input to the AHP model for the attribute analysis. The AHP model would enable environment managers to compose the relevant information via a link between human feelings about urban trees, and environmental factors for monitoring purposes and performance analysis.

  18. CLIPS based decision support system for water distribution networks

    Directory of Open Access Journals (Sweden)

    K. Sandeep

    2011-10-01

    Full Text Available The difficulty in knowledge representation of a water distribution network (WDN problem has contributed to the limited use of artificial intelligence (AI based expert systems (ES in the management of these networks. This paper presents a design of a Decision Support System (DSS that facilitates "on-demand'' knowledge generation by utilizing results of simulation runs of a suitably calibrated and validated hydraulic model of an existing aged WDN corresponding to emergent or even hypothetical but likely scenarios. The DSS augments the capability of a conventional expert system by integrating together the hydraulic modelling features with heuristics based knowledge of experts under a common, rules based, expert shell named CLIPS (C Language Integrated Production System. In contrast to previous ES, the knowledge base of the DSS has been designed to be dynamic by superimposing CLIPS on Structured Query Language (SQL. The proposed ES has an inbuilt calibration module that enables calibration of an existing (aged WDN for the unknown, and unobservable, Hazen-Williams C-values. In addition, the daily run and simulation modules of the proposed ES further enable the CLIPS inference engine to evaluate the network performance for any emergent or suggested test scenarios. An additional feature of the proposed design is that the DSS integrates computational platforms such as MATLAB, open source Geographical Information System (GIS, and a relational database management system (RDBMS working under the umbrella of the Microsoft Visual Studio based common user interface. The paper also discusses implementation of the proposed framework on a case study and clearly demonstrates the utility of the application as an able aide for effective management of the study network.

  19. The Usability of Agent-Based Simulation in Decision Support System of E-Commerce Architecture

    Directory of Open Access Journals (Sweden)

    ŠPERKA Roman

    2012-02-01

    Full Text Available Electronic commerce (e-commerce has the potential to improve the competitiveness of the enterprises. A decision support system, used in e-commerce, is a term used to describe any software engine that enhances the user’s ability to make decisions. The paper presents a new approach for decision support system modeling. This approach is applied by a modification and extension of existing decision support system architecture by multi-agent technology and agent-based simulation models. Multi-agent technology is one of the fastest growing fields of information and communication technology – new agent-based services, products, and applications are being developed almost every day. Agent-based simulation model is applied to coordinate, control, and simulate the architecture of decision support system, used in e-commerce. The proposed architecture improves the existing decision support systems and gains competitive advantage.

  20. Implications of caries diagnostic strategies for clinical management decisions

    DEFF Research Database (Denmark)

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

    2012-01-01

    in a low-caries population. METHODS: Each of four examiners independently examined preselected contacting interproximal surfaces in 53 dental students aged 20-37 years using a visual-tactile examination and bitewing radiography. The visual-tactile examination distinguished between noncavitated......OBJECTIVES: In clinical practice, a visual-tactile caries examination is frequently supplemented by bitewing radiography. This study evaluated strategies for combining visual-tactile and radiographic caries detection methods and determined their implications for clinical management decisions......-specificity) were calculated for each diagnostic strategy. RESULTS: Visual-tactile examination provided a true-positive rate of 34.2% and a false-positive rate of 1.5% for the detection of a cavity. The combination of a visual-tactile and a radiographic examination using the lesion in dentin threshold...