The Wildland Fire Decision Support System: Integrating science, technology, and fire management

Treesearch

Morgan Pence; Tom Zimmerman

2011-01-01

Federal agency policy requires documentation and analysis of all wildland fire response decisions. In the past, planning and decision documentation for fires were completed using multiple unconnected processes, yielding many limitations. In response, interagency fire management executives chartered the development of the Wildland Fire Decision Support System (WFDSS)....

Integrated Energy Solutions Research | Integrated Energy Solutions | NREL

Science.gov Websites

that spans the height and width of the wall they are facing. Decision Science and Informatics Enabling decision makers with rigorous, technology-neutral, data-backed decision support to maximize the impact of security in energy systems through analysis, decision support, advanced energy technology development, and

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

PubMed

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

2016-04-01

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

Using the Situated Clinical Decision-Making framework to guide analysis of nurses' clinical decision-making.

PubMed

Gillespie, Mary

2010-11-01

Nurses' clinical decision-making is a complex process that holds potential to influence the quality of care provided and patient outcomes. The evolution of nurses' decision-making that occurs with experience has been well documented. In addition, literature includes numerous strategies and approaches purported to support development of nurses' clinical decision-making. There has been, however, significantly less attention given to the process of assessing nurses' clinical decision-making and novice clinical educators are often challenged with knowing how to best support nurses and nursing students in developing their clinical decision-making capacity. The Situated Clinical Decision-Making framework is presented for use by clinical educators: it provides a structured approach to analyzing nursing students' and novice nurses' decision-making in clinical nursing practice, assists educators in identifying specific issues within nurses' clinical decision-making, and guides selection of relevant strategies to support development of clinical decision-making. A series of questions is offered as a guide for clinical educators when assessing nurses' clinical decision-making. The discussion presents key considerations related to analysis of various decision-making components, including common sources of challenge and errors that may occur within nurses' clinical decision-making. An exemplar illustrates use of the framework and guiding questions. Implications of this approach for selection of strategies that support development of clinical decision-making are highlighted. Copyright © 2010 Elsevier Ltd. All rights reserved.

The application of decision analysis to life support research and technology development

NASA Technical Reports Server (NTRS)

Ballin, Mark G.

1994-01-01

Applied research and technology development is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Decision making regarding which technologies to advance and what resources to devote to them is a challenging but essential task. In the application of life support technology to future manned space flight, new technology concepts typically are characterized by nonexistent data and rough approximations of technology performance, uncertain future flight program needs, and a complex, time-intensive process to develop technology to a flight-ready status. Decision analysis is a quantitative, logic-based discipline that imposes formalism and structure to complex problems. It also accounts for the limits of knowledge that may be available at the time a decision is needed. The utility of decision analysis to life support technology R & D was evaluated by applying it to two case studies. The methodology was found to provide insight that is not possible from more traditional analysis approaches.

Knowledge-Based Information Management in Decision Support for Ecosystem Management

Treesearch

Keith Reynolds; Micahel Saunders; Richard Olson; Daniel Schmoldt; Michael Foster; Donald Latham; Bruce Miller; John Steffenson; Lawrence Bednar; Patrick Cunningham

1995-01-01

The Pacific Northwest Research Station (USDA Forest Service) is developing a knowledge-based information management system to provide decision support for watershed analysis in the Pacific Northwest region of the U.S. The decision support system includes: (1) a GIS interface that allows users to graphically navigate to specific provinces and watersheds and display a...

Demonstration of the application of traffic management center decision support tools.

DOT National Transportation Integrated Search

2013-03-01

Decision support tools were developed in previous Florida Department of Transportation (FDOT) : research projects to allow for better analysis and visualization of historical traffic and incident : data, in support of incident management and traffic ...

Analysis and Design of a Decision Support System for Silas B. Hays Army Community Hospital

DTIC Science & Technology

1988-09-01

develop the DSS. This collaboration allows the user to learn about the power decision support can give to the decision maker and... projects under their control. A DSS is developed to provide decision support for a specific manager or group , and con- sequently falls under the ... It is possible the first iteration could be developed in more than one programming language and results compared . Once the first

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

PubMed

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

2014-06-01

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

Decision Support System Requirements Definition for Human Extravehicular Activity Based on Cognitive Work Analysis

PubMed Central

Miller, Matthew James; McGuire, Kerry M.; Feigh, Karen M.

2016-01-01

The design and adoption of decision support systems within complex work domains is a challenge for cognitive systems engineering (CSE) practitioners, particularly at the onset of project development. This article presents an example of applying CSE techniques to derive design requirements compatible with traditional systems engineering to guide decision support system development. Specifically, it demonstrates the requirements derivation process based on cognitive work analysis for a subset of human spaceflight operations known as extravehicular activity. The results are presented in two phases. First, a work domain analysis revealed a comprehensive set of work functions and constraints that exist in the extravehicular activity work domain. Second, a control task analysis was performed on a subset of the work functions identified by the work domain analysis to articulate the translation of subject matter states of knowledge to high-level decision support system requirements. This work emphasizes an incremental requirements specification process as a critical component of CSE analyses to better situate CSE perspectives within the early phases of traditional systems engineering design. PMID:28491008

Decision Support System Requirements Definition for Human Extravehicular Activity Based on Cognitive Work Analysis.

PubMed

Miller, Matthew James; McGuire, Kerry M; Feigh, Karen M

2017-06-01

The design and adoption of decision support systems within complex work domains is a challenge for cognitive systems engineering (CSE) practitioners, particularly at the onset of project development. This article presents an example of applying CSE techniques to derive design requirements compatible with traditional systems engineering to guide decision support system development. Specifically, it demonstrates the requirements derivation process based on cognitive work analysis for a subset of human spaceflight operations known as extravehicular activity . The results are presented in two phases. First, a work domain analysis revealed a comprehensive set of work functions and constraints that exist in the extravehicular activity work domain. Second, a control task analysis was performed on a subset of the work functions identified by the work domain analysis to articulate the translation of subject matter states of knowledge to high-level decision support system requirements. This work emphasizes an incremental requirements specification process as a critical component of CSE analyses to better situate CSE perspectives within the early phases of traditional systems engineering design.

Development of an evidence-based decision pathway for vestibular schwannoma treatment options.

PubMed

Linkov, Faina; Valappil, Benita; McAfee, Jacob; Goughnour, Sharon L; Hildrew, Douglas M; McCall, Andrew A; Linkov, Igor; Hirsch, Barry; Snyderman, Carl

To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS). This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS. Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model. The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives. Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2016-01-01

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

The potential for meta-analysis to support decision analysis in ecology.

PubMed

Mengersen, Kerrie; MacNeil, M Aaron; Caley, M Julian

2015-06-01

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable expectations that benefits would be derived from doing so. Meta-analysis combines information from multiple studies to provide more accurate parameter estimates and to reduce the uncertainty surrounding them. Decision analysis involves selecting among alternative choices using statistical information that helps to shed light on the uncertainties involved. By linking meta-analysis to decision analysis, improved decisions can be made, with quantification of the costs and benefits of alternate decisions supported by a greater density of information. Here, we briefly review concepts of both meta-analysis and decision analysis, illustrating the natural linkage between them and the benefits from explicitly linking one to the other. We discuss some examples in which this linkage has been exploited in the medical arena and how improvements in precision and reduction of structural uncertainty inherent in a meta-analysis can provide substantive improvements to decision analysis outcomes by reducing uncertainty in expected loss and maximising information from across studies. We then argue that these significant benefits could be translated to ecology, in particular to the problem of making optimal ecological decisions in the face of uncertainty. Copyright © 2013 John Wiley & Sons, Ltd.

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

PubMed

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

2015-11-01

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

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

PubMed

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

2017-08-01

A growing literature has demonstrated the ability of user-centered design to make clinical decision support systems more effective and easier to use. However, studies of user-centered design have rarely examined more than a handful of sites at a time, and have frequently neglected the implementation climate and organizational resources that influence clinical decision support. The inclusion of such factors was identified by a systematic review as "the most important improvement that can be made in health IT evaluations." (1) Identify the prevalence of four user-centered design practices at United States Veterans Affairs (VA) primary care clinics and assess the perceived utility of clinical decision support at those clinics; (2) Evaluate the association between those user-centered design practices and the perceived utility of clinical decision support. We analyzed clinic-level survey data collected in 2006-2007 from 170 VA primary care clinics. We examined four user-centered design practices: 1) pilot testing, 2) provider satisfaction assessment, 3) formal usability assessment, and 4) analysis of impact on performance improvement. We used a regression model to evaluate the association between user-centered design practices and the perceived utility of clinical decision support, while accounting for other important factors at those clinics, including implementation climate, available resources, and structural characteristics. We also examined associations separately at community-based clinics and at hospital-based clinics. User-centered design practices for clinical decision support varied across clinics: 74% conducted pilot testing, 62% conducted provider satisfaction assessment, 36% conducted a formal usability assessment, and 79% conducted an analysis of impact on performance improvement. Overall perceived utility of clinical decision support was high, with a mean rating of 4.17 (±.67) out of 5 on a composite measure. "Analysis of impact on performance improvement" was the only user-centered design practice significantly associated with perceived utility of clinical decision support, b=.47 (p<.001). This association was present in hospital-based clinics, b=.34 (p<.05), but was stronger at community-based clinics, b=.61 (p<.001). Our findings are highly supportive of the practice of analyzing the impact of clinical decision support on performance metrics. This was the most common user-centered design practice in our study, and was the practice associated with higher perceived utility of clinical decision support. This practice may be particularly helpful at community-based clinics, which are typically less connected to VA medical center resources. Published by Elsevier B.V.

Sbexpert users guide (version 1.0): A knowledge-based decision-support system for spruce beetle management. Forest Service general technical report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reynolds, K.M.; Holsten, E.H.; Werner, R.A.

1995-03-01

SBexpert version 1.0 is a knowledge-based decision-support system for management of spruce beetle developed for use in Microsoft Windows. The users guide provides detailed instructions on the use of all SBexpert features. SBexpert has four main subprograms; introduction, analysis, textbook, and literature. The introduction is the first of the five subtopics in the SBexpert help system. The analysis topic is an advisory system for spruce beetle management that provides recommendation for reducing spruce beetle hazard and risk to spruce stands and is the main analytical topic in SBexpert. The textbook and literature topics provide complementary decision support for analysis.

Data for Renewable Energy Planning, Policy, and Investment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cox, Sarah L

Reliable, robust, and validated data are critical for informed planning, policy development, and investment in the clean energy sector. The Renewable Energy (RE) Explorer was developed to support data-driven renewable energy analysis that can inform key renewable energy decisions globally. This document presents the types of geospatial and other data at the core of renewable energy analysis and decision making. Individual data sets used to inform decisions vary in relation to spatial and temporal resolution, quality, and overall usefulness. From Data to Decisions, a complementary geospatial data and analysis decision guide, provides an in-depth view of these and other considerationsmore » to enable data-driven planning, policymaking, and investment. Data support a wide variety of renewable energy analyses and decisions, including technical and economic potential assessment, renewable energy zone analysis, grid integration, risk and resiliency identification, electrification, and distributed solar photovoltaic potential. This fact sheet provides information on the types of data that are important for renewable energy decision making using the RE Data Explorer or similar types of geospatial analysis tools.« less

AN EPA SPONSORED LITERATURE REVIEW DATABASE TO SUPPORT STRESSOR IDENTIFICATION

EPA Science Inventory

The Causal Analysis/Diagnosis Decision Information System (CADDIS) is an EPA decision-support system currently under development for evaluating the biological impact of stressors on water bodies. In support of CADDIS, EPA is developing CADLIT, a searchable database of the scient...

Pattern Analysis and Decision Support for Cancer through Clinico-Genomic Profiles

NASA Astrophysics Data System (ADS)

Exarchos, Themis P.; Giannakeas, Nikolaos; Goletsis, Yorgos; Papaloukas, Costas; Fotiadis, Dimitrios I.

Advances in genome technology are playing a growing role in medicine and healthcare. With the development of new technologies and opportunities for large-scale analysis of the genome, genomic data have a clear impact on medicine. Cancer prognostics and therapeutics are among the first major test cases for genomic medicine, given that all types of cancer are related with genomic instability. In this paper we present a novel system for pattern analysis and decision support in cancer. The system integrates clinical data from electronic health records and genomic data. Pattern analysis and data mining methods are applied to these integrated data and the discovered knowledge is used for cancer decision support. Through this integration, conclusions can be drawn for early diagnosis, staging and cancer treatment.

Modelling elderly cardiac patients decision making using Cognitive Work Analysis: identifying requirements for patient decision aids.

PubMed

Dhukaram, Anandhi Vivekanandan; Baber, Chris

2015-06-01

Patients make various healthcare decisions on a daily basis. Such day-to-day decision making can have significant consequences on their own health, treatment, care, and costs. While decision aids (DAs) provide effective support in enhancing patient's decision making, to date there have been few studies examining patient's decision making process or exploring how the understanding of such decision processes can aid in extracting requirements for the design of DAs. This paper applies Cognitive Work Analysis (CWA) to analyse patient's decision making in order to inform requirements for supporting self-care decision making. This study uses focus groups to elicit information from elderly cardiovascular disease (CVD) patients concerning a range of decision situations they face on a daily basis. Specifically, the focus groups addressed issues related to the decision making of CVD in terms of medication compliance, pain, diet and exercise. The results of these focus groups are used to develop high level views using CWA. CWA framework decomposes the complex decision making problem to inform three approaches to DA design: one design based on high level requirements; one based on a normative model of decision-making for patients; and the third based on a range of heuristics that patients seem to use. CWA helps in extracting and synthesising decision making from different perspectives: decision processes, work organisation, patient competencies and strategies used in decision making. As decision making can be influenced by human behaviour like skills, rules and knowledge, it is argued that patients require support to different types of decision making. This paper also provides insights for designers in using CWA framework for the design of effective DAs to support patients in self-management. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

How to use multi-criteria decision analysis methods for reimbursement decision-making in healthcare: a step-by-step guide.

PubMed

Diaby, Vakaramoko; Goeree, Ron

2014-02-01

In recent years, the quest for more comprehensiveness, structure and transparency in reimbursement decision-making in healthcare has prompted the research into alternative decision-making frameworks. In this environment, multi-criteria decision analysis (MCDA) is arising as a valuable tool to support healthcare decision-making. In this paper, we present the main MCDA decision support methods (elementary methods, value-based measurement models, goal programming models and outranking models) using a case study approach. For each family of methods, an example of how an MCDA model would operate in a real decision-making context is presented from a critical perspective, highlighting the parameters setting, the selection of the appropriate evaluation model as well as the role of sensitivity and robustness analyses. This study aims to provide a step-by-step guide on how to use MCDA methods for reimbursement decision-making in healthcare.

PATIENT-CENTERED DECISION MAKING: LESSONS FROM MULTI-CRITERIA DECISION ANALYSIS FOR QUANTIFYING PATIENT PREFERENCES.

PubMed

Marsh, Kevin; Caro, J Jaime; Zaiser, Erica; Heywood, James; Hamed, Alaa

2018-01-01

Patient preferences should be a central consideration in healthcare decision making. However, stories of patients challenging regulatory and reimbursement decisions has led to questions on whether patient voices are being considered sufficiently during those decision making processes. This has led some to argue that it is necessary to quantify patient preferences before they can be adequately considered. This study considers the lessons from the use of multi-criteria decision analysis (MCDA) for efforts to quantify patient preferences. It defines MCDA and summarizes the benefits it can provide to decision makers, identifies examples of MCDAs that have involved patients, and summarizes good practice guidelines as they relate to quantifying patient preferences. The guidance developed to support the use of MCDA in healthcare provide some useful considerations for the quantification of patient preferences, namely that researchers should give appropriate consideration to: the heterogeneity of patient preferences, and its relevance to decision makers; the cognitive challenges posed by different elicitation methods; and validity of the results they produce. Furthermore, it is important to consider how the relevance of these considerations varies with the decision being supported. The MCDA literature holds important lessons for how patient preferences should be quantified to support healthcare decision making.

An Environmental Decision Support System for Spatial Assessment and Selective Remediation

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates environmental assessment tools for effective problem-solving. The software integrates modules for GIS, visualization, geospatial analysis, statistical analysis, human health and ecolog...

Non-monetary valuation using Multi-Criteria Decision Analysis: Sensitivity of additive aggregation methods to scaling and compensation assumptions

EPA Science Inventory

Analytical methods for Multi-Criteria Decision Analysis (MCDA) support the non-monetary valuation of ecosystem services for environmental decision making. Many published case studies transform ecosystem service outcomes into a common metric and aggregate the outcomes to set land ...

Decision Support Framework Implementation Of The Web-Based Environmental Decision Analysis DASEES: Decision Analysis For A Sustainable Environment, Economy, And Society

EPA Science Inventory

Solutions to pervasive environmental problems often are not amenable to a straightforward application of science-based actions. These problems encompass large-scale environmental policy questions where environmental concerns, economic constraints, and societal values conflict ca...

Decision analysis framing study; in-valley drainage management strategies for the western San Joaquin Valley, California

USGS Publications Warehouse

Presser, Theresa S.; Jenni, Karen E.; Nieman, Timothy; Coleman, James

2010-01-01

Constraints on drainage management in the western San Joaquin Valley and implications of proposed approaches to management were recently evaluated by the U.S. Geological Survey (USGS). The USGS found that a significant amount of data for relevant technical issues was available and that a structured, analytical decision support tool could help optimize combinations of specific in-valley drainage management strategies, address uncertainties, and document underlying data analysis for future use. To follow-up on USGS's technical analysis and to help define a scientific basis for decisionmaking in implementing in-valley drainage management strategies, this report describes the first step (that is, a framing study) in a Decision Analysis process. In general, a Decision Analysis process includes four steps: (1) problem framing to establish the scope of the decision problem(s) and a set of fundamental objectives to evaluate potential solutions, (2) generation of strategies to address identified decision problem(s), (3) identification of uncertainties and their relationships, and (4) construction of a decision support model. Participation in such a systematic approach can help to promote consensus and to build a record of qualified supporting data for planning and implementation. In December 2008, a Decision Analysis framing study was initiated with a series of meetings designed to obtain preliminary input from key stakeholder groups on the scope of decisions relevant to drainage management that were of interest to them, and on the fundamental objectives each group considered relevant to those decisions. Two key findings of this framing study are: (1) participating stakeholders have many drainage management objectives in common; and (2) understanding the links between drainage management and water management is necessary both for sound science-based decisionmaking and for resolving stakeholder differences about the value of proposed drainage management solutions. Citing ongoing legal processes associated with drainage management in the western San Joaquin Valley, the U.S. Bureau of Reclamation (USBR) withdrew from the Decision Analysis process early in the proceedings. Without the involvement of the USBR, the USGS discontinued further development of this study.

GET SMARTE: A DECISION SUPPORT SYSTEM TO REVITALIZE COMMUNITIES - CABERNET 2007

EPA Science Inventory

Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains information and analysis tools for all a...

Developing an Ecosystem Services online Decision Support Tool to Assess the Impacts of Climate Change and Urban Growth in the Santa Cruz Watershed; Where We Live, Work, and Play

EPA Science Inventory

Processes through which ecosystems provide goods or benefit people can be referred to as "ecosystems services”, which may be quantified to clarify decision-making, with techniques including cost-benefit analysis. We are developing an online decision support tool, the Santa Cruz W...

Framing of Uncertainty in Scientific Publications: Towards Recommendations for Decision Support

NASA Astrophysics Data System (ADS)

Guillaume, J. H. A.; Helgeson, C.; Elsawah, S.; Jakeman, A. J.; Kummu, M.

2016-12-01

Uncertainty is recognised as an essential issue in environmental decision making and decision support. As modellers, we notably use a variety of tools and techniques within an analysis, for example related to uncertainty quantification and model validation. We also address uncertainty by how we present results. For example, experienced modellers are careful to distinguish robust conclusions from those that need further work, and the precision of quantitative results is tailored to their accuracy. In doing so, the modeller frames how uncertainty should be interpreted by their audience. This is an area which extends beyond modelling to fields such as philosophy of science, semantics, discourse analysis, intercultural communication and rhetoric. We propose that framing of uncertainty deserves greater attention in the context of decision support, and that there are opportunities in this area for fundamental research, synthesis and knowledge transfer, development of teaching curricula, and significant advances in managing uncertainty in decision making. This presentation reports preliminary results of a study of framing practices. Specifically, we analyse the framing of uncertainty that is visible in the abstracts from a corpus of scientific articles. We do this through textual analysis of the content and structure of those abstracts. Each finding that appears in an abstract is classified according to the uncertainty framing approach used, using a classification scheme that was iteratively revised based on reflection and comparison amongst three coders. This analysis indicates how frequently the different framing approaches are used, and provides initial insights into relationships between frames, how the frames relate to interpretation of uncertainty, and how rhetorical devices are used by modellers to communicate uncertainty in their work. We propose initial hypotheses for how the resulting insights might influence decision support, and help advance decision making to better address uncertainty.

Analysis of the risk management decisionmaking processes and the decision support systems in the wildland fire agencies

Treesearch

Patrick Withen

2007-01-01

This paper offers an analysis of the strengths, weaknesses, opportunities, and threats in the risk management process, decision support systems (DSSs), and other types of decisionmaking, including recognition primed decisionmaking, bricolage with the goal of improving DSSs and decisionmaking. DSSs may be thought of as any technology or knowledge that is used as an aid...

Multi-criteria decision making to support waste management: A critical review of current practices and methods.

PubMed

Goulart Coelho, Lineker M; Lange, Liséte C; Coelho, Hosmanny Mg

2017-01-01

Solid waste management is a complex domain involving the interaction of several dimensions; thus, its analysis and control impose continuous challenges for decision makers. In this context, multi-criteria decision-making models have become important and convenient supporting tools for solid waste management because they can handle problems involving multiple dimensions and conflicting criteria. However, the selection of the multi-criteria decision-making method is a hard task since there are several multi-criteria decision-making approaches, each one with a large number of variants whose applicability depends on information availability and the aim of the study. Therefore, to support researchers and decision makers, the objectives of this article are to present a literature review of multi-criteria decision-making applications used in solid waste management, offer a critical assessment of the current practices, and provide suggestions for future works. A brief review of fundamental concepts on this topic is first provided, followed by the analysis of 260 articles related to the application of multi-criteria decision making in solid waste management. These studies were investigated in terms of the methodology, including specific steps such as normalisation, weighting, and sensitivity analysis. In addition, information related to waste type, the study objective, and aspects considered was recorded. From the articles analysed it is noted that studies using multi-criteria decision making in solid waste management are predominantly addressed to problems related to municipal solid waste involving facility location or management strategy.

Seismic slope-performance analysis: from hazard map to decision support system

USGS Publications Warehouse

Miles, Scott B.; Keefer, David K.; Ho, Carlton L.

1999-01-01

In response to the growing recognition of engineers and decision-makers of the regional effects of earthquake-induced landslides, this paper presents a general approach to conducting seismic landslide zonation, based on the popular Newmark's sliding block analogy for modeling coherent landslides. Four existing models based on the sliding block analogy are compared. The comparison shows that the models forecast notably different levels of slope performance. Considering this discrepancy along with the limitations of static maps as a decision tool, a spatial decision support system (SDSS) for seismic landslide analysis is proposed, which will support investigations over multiple scales for any number of earthquake scenarios and input conditions. Most importantly, the SDSS will allow use of any seismic landslide analysis model and zonation approach. Developments associated with the SDSS will produce an object-oriented model for encapsulating spatial data, an object-oriented specification to allow construction of models using modular objects, and a direct-manipulation, dynamic user-interface that adapts to the particular seismic landslide model configuration.

A Decision Support Framework For Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

EPA Science Inventory

We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environ...

Enhancement of the EPA Stormwater BMP Decision-Support Tool (SUSTAIN)

EPA Science Inventory

U.S. Environmental Protection Agency (EPA) has been developing and improving a decision-support tool for placement of stormwater best management practices (BMPs) at strategic locations in urban watersheds. The tool is called the System for Urban Stormwater Treatment and Analysis...

A study on spatial decision support systems for HIV/AIDS prevention based on COM GIS technology

NASA Astrophysics Data System (ADS)

Yang, Kun; Luo, Huasong; Peng, Shungyun; Xu, Quanli

2007-06-01

Based on the deeply analysis of the current status and the existing problems of GIS technology applications in Epidemiology, this paper has proposed the method and process for establishing the spatial decision support systems of AIDS epidemic prevention by integrating the COM GIS, Spatial Database, GPS, Remote Sensing, and Communication technologies, as well as ASP and ActiveX software development technologies. One of the most important issues for constructing the spatial decision support systems of AIDS epidemic prevention is how to integrate the AIDS spreading models with GIS. The capabilities of GIS applications in the AIDS epidemic prevention have been described here in this paper firstly. Then some mature epidemic spreading models have also been discussed for extracting the computation parameters. Furthermore, a technical schema has been proposed for integrating the AIDS spreading models with GIS and relevant geospatial technologies, in which the GIS and model running platforms share a common spatial database and the computing results can be spatially visualized on Desktop or Web GIS clients. Finally, a complete solution for establishing the decision support systems of AIDS epidemic prevention has been offered in this paper based on the model integrating methods and ESRI COM GIS software packages. The general decision support systems are composed of data acquisition sub-systems, network communication sub-systems, model integrating sub-systems, AIDS epidemic information spatial database sub-systems, AIDS epidemic information querying and statistical analysis sub-systems, AIDS epidemic dynamic surveillance sub-systems, AIDS epidemic information spatial analysis and decision support sub-systems, as well as AIDS epidemic information publishing sub-systems based on Web GIS.

Web-services-based spatial decision support system to facilitate nuclear waste siting

NASA Astrophysics Data System (ADS)

Huang, L. Xinglai; Sheng, Grant

2006-10-01

The availability of spatial web services enables data sharing among managers, decision and policy makers and other stakeholders in much simpler ways than before and subsequently has created completely new opportunities in the process of spatial decision making. Though generally designed for a certain problem domain, web-services-based spatial decision support systems (WSDSS) can provide a flexible problem-solving environment to explore the decision problem, understand and refine problem definition, and generate and evaluate multiple alternatives for decision. This paper presents a new framework for the development of a web-services-based spatial decision support system. The WSDSS is comprised of distributed web services that either have their own functions or provide different geospatial data and may reside in different computers and locations. WSDSS includes six key components, namely: database management system, catalog, analysis functions and models, GIS viewers and editors, report generators, and graphical user interfaces. In this study, the architecture of a web-services-based spatial decision support system to facilitate nuclear waste siting is described as an example. The theoretical, conceptual and methodological challenges and issues associated with developing web services-based spatial decision support system are described.

Decision Support Methods and Tools

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

Enhancement of the EPA Stormwater BMP Decision-Support Tool (SUSTAIN) - slides

EPA Science Inventory

U.S. Environmental Protection Agency (EPA) has been developing and improving a decision-support tool for placement of stormwater best management practices (BMPs) at strategic locations in urban watersheds. The tool is called the System for Urban Stormwater Treatment and Analysis...

Cognitive Analysis of Decision Support for Antibiotic Prescribing at the Point of Ordering in a Neonatal Intensive Care Unit

PubMed Central

Sheehan, Barbara; Kaufman, David; Stetson, Peter; Currie, Leanne M.

2009-01-01

Computerized decision support systems have been used to help ensure safe medication prescribing. However, the acceptance of these types of decision support has been reported to be low. It has been suggested that decreased acceptance may be due to lack of clinical relevance. Additionally, cognitive fit between the user interface and clinical task may impact the response of clinicians as they interact with the system. In order to better understand clinician responses to such decision support, we used cognitive task analysis methods to evaluate clinical alerts for antibiotic prescribing in a neonatal intensive care unit. Two methods were used: 1) a cognitive walkthrough; and 2) usability testing with a ‘think-aloud’ protocol. Data were analyzed for impact on cognitive effort according to categories of cognitive distance. We found that responses to alerts may be context specific and that lack of screen cues often increases cognitive effort required to use a system. PMID:20351922

Will Decision Support in Medications Order Entry Save Money? A Return On Investment Analysis of the Case of the Hong Kong Hospital Authority

PubMed Central

Fung, Kin Wah; Vogel, Lynn Harold

2003-01-01

The computerized medications order entry system currently used in the public hospitals of Hong Kong does not have decision support features. Plans are underway to add decision support to this system to alert physicians on drug-allergy conflicts, drug-lab result conflicts, drug-drug interactions and atypical dosages. A return on investment analysis is done on this enhancement, both as an examination of whether there is a positive return on the investment and as a contribution to the ongoing discussion of the use of return on investment models in health care information technology investments. It is estimated that the addition of decision support will reduce adverse drug events by 4.2 – 8.4%. Based on this estimate, a total net saving of $44,000 – $586,000 is expected over five years. The breakeven period is estimated to be between two to four years. PMID:14728171

Decision support tools for proton therapy ePR: intelligent treatment planning navigator and radiation toxicity tool for evaluating of prostate cancer treatment

NASA Astrophysics Data System (ADS)

Le, Anh H.; Deshpande, Ruchi; Liu, Brent J.

2010-03-01

The electronic patient record (ePR) has been developed for prostate cancer patients treated with proton therapy. The ePR has functionality to accept digital input from patient data, perform outcome analysis and patient and physician profiling, provide clinical decision support and suggest courses of treatment, and distribute information across different platforms and health information systems. In previous years, we have presented the infrastructure of a medical imaging informatics based ePR for PT with functionality to accept digital patient information and distribute this information across geographical location using Internet protocol. In this paper, we present the ePR decision support tools which utilize the imaging processing tools and data collected in the ePR. The two decision support tools including the treatment plan navigator and radiation toxicity tool are presented to evaluate prostate cancer treatment to improve proton therapy operation and improve treatment outcomes analysis.

DISPLA: decision information system for procurement and logistics analysis

NASA Astrophysics Data System (ADS)

Calvo, Alberto B.; Danish, Alexander J.; Lamonakis, Gregory G.

2002-08-01

This paper describes an information-exchange system for Display systems acquisition and logistics support. DISPLA (Decision Information System for Procurement and Logistics Analysis) is an Internet-based system concept for bringing sellers (display system and component suppliers) and buyers (Government Program Offices and System Integrators) together in an electronic exchange to improve the acquisition and logistics analysis support of Flat Panel Displays for the military. A proof-of-concept demonstration is presented in this paper using sample data from vendor Web sites and Government data sources.

Organic Versus Contractor Logistics Support For Depot-Level Repair: Factors That Drive Sub-Optimal Decisions

DTIC Science & Technology

2016-02-16

Considerations in Using CLS or Organic Support Break-Even Analysis in the Decision Process When a business decision is made in an ideal environment, all costs...Line B). The break-even point (Point C) is the production quantity where the advantage moves to a different cost curve. For a business decision...the Services to provide regular reporting to them on contractor versus organic workload and money .1415 In sum, there are laws that mandate 50/50

Multiple Criteria Decision Analysis for Health Care Decision Making--Emerging Good Practices: Report 2 of the ISPOR MCDA Emerging Good Practices Task Force.

PubMed

Marsh, Kevin; IJzerman, Maarten; Thokala, Praveen; Baltussen, Rob; Boysen, Meindert; Kaló, Zoltán; Lönngren, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Devlin, Nancy

2016-01-01

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making. A set of techniques, known under the collective heading, multiple criteria decision analysis (MCDA), are useful for this purpose. In 2014, ISPOR established an Emerging Good Practices Task Force. The task force's first report defined MCDA, provided examples of its use in health care, described the key steps, and provided an overview of the principal methods of MCDA. This second task force report provides emerging good-practice guidance on the implementation of MCDA to support health care decisions. The report includes: a checklist to support the design, implementation and review of an MCDA; guidance to support the implementation of the checklist; the order in which the steps should be implemented; illustrates how to incorporate budget constraints into an MCDA; provides an overview of the skills and resources, including available software, required to implement MCDA; and future research directions. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Developing an Interactive Data Visualization Tool to Assess the Impact of Decision Support on Clinical Operations.

PubMed

Huber, Timothy C; Krishnaraj, Arun; Monaghan, Dayna; Gaskin, Cree M

2018-05-18

Due to mandates from recent legislation, clinical decision support (CDS) software is being adopted by radiology practices across the country. This software provides imaging study decision support for referring providers at the point of order entry. CDS systems produce a large volume of data, providing opportunities for research and quality improvement. In order to better visualize and analyze trends in this data, an interactive data visualization dashboard was created using a commercially available data visualization platform. Following the integration of a commercially available clinical decision support product into the electronic health record, a dashboard was created using a commercially available data visualization platform (Tableau, Seattle, WA). Data generated by the CDS were exported from the data warehouse, where they were stored, into the platform. This allowed for real-time visualization of the data generated by the decision support software. The creation of the dashboard allowed the output from the CDS platform to be more easily analyzed and facilitated hypothesis generation. Integrating data visualization tools into clinical decision support tools allows for easier data analysis and can streamline research and quality improvement efforts.

A decision support framework for characterizing and managing dermal exposures to chemicals during Emergency Management and Operations.

PubMed

Dotson, G Scott; Hudson, Naomi L; Maier, Andrew

2015-01-01

Emergency Management and Operations (EMO) personnel are in need of resources and tools to assist in understanding the health risks associated with dermal exposures during chemical incidents. This article reviews available resources and presents a conceptual framework for a decision support system (DSS) that assists in characterizing and managing risk during chemical emergencies involving dermal exposures. The framework merges principles of three decision-making techniques: 1) scenario planning, 2) risk analysis, and 3) multicriteria decision analysis (MCDA). This DSS facilitates dynamic decision making during each of the distinct life cycle phases of an emergency incident (ie, preparedness, response, or recovery) and identifies EMO needs. A checklist tool provides key questions intended to guide users through the complexities of conducting a dermal risk assessment. The questions define the scope of the framework for resource identification and application to support decision-making needs. The framework consists of three primary modules: 1) resource compilation, 2) prioritization, and 3) decision. The modules systematically identify, organize, and rank relevant information resources relating to the hazards of dermal exposures to chemicals and risk management strategies. Each module is subdivided into critical elements designed to further delineate the resources based on relevant incident phase and type of information. The DSS framework provides a much needed structure based on contemporary decision analysis principles for 1) documenting key questions for EMO problem formulation and 2) a method for systematically organizing, screening, and prioritizing information resources on dermal hazards, exposures, risk characterization, and management.

A decision support framework for characterizing and managing dermal exposures to chemicals during Emergency Management and Operations

PubMed Central

Dotson, G. Scott; Hudson, Naomi L.; Maier, Andrew

2016-01-01

Emergency Management and Operations (EMO) personnel are in need of resources and tools to assist in understanding the health risks associated with dermal exposures during chemical incidents. This article reviews available resources and presents a conceptual framework for a decision support system (DSS) that assists in characterizing and managing risk during chemical emergencies involving dermal exposures. The framework merges principles of three decision-making techniques: 1) scenario planning, 2) risk analysis, and 3) multicriteria decision analysis (MCDA). This DSS facilitates dynamic decision making during each of the distinct life cycle phases of an emergency incident (ie, preparedness, response, or recovery) and identifies EMO needs. A checklist tool provides key questions intended to guide users through the complexities of conducting a dermal risk assessment. The questions define the scope of the framework for resource identification and application to support decision-making needs. The framework consists of three primary modules: 1) resource compilation, 2) prioritization, and 3) decision. The modules systematically identify, organize, and rank relevant information resources relating to the hazards of dermal exposures to chemicals and risk management strategies. Each module is subdivided into critical elements designed to further delineate the resources based on relevant incident phase and type of information. The DSS framework provides a much needed structure based on contemporary decision analysis principles for 1) documenting key questions for EMO problem formulation and 2) a method for systematically organizing, screening, and prioritizing information resources on dermal hazards, exposures, risk characterization, and management. PMID:26312660

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

PubMed

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

2016-03-01

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

Designing Colorectal Cancer Screening Decision Support: A Cognitive Engineering Enterprise

PubMed Central

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

2016-01-01

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

A decision support system for technology R&D planning: connecting the dots from information to innovation

NASA Technical Reports Server (NTRS)

Smith, Jeffrey H.; Wertz, Julie; Weisbin, Charles

2004-01-01

This paper describes an information technology innovation developed to assist decision makers faced with complex R&D tasks. The decision support system (DSS) was developed and applied to the analysis of a 10-year, 700 million dollar technology program for the exploration of Mars. The technologies were to enable a 4.8 billion dollar portfolio of exploration flight missions to Mars.

Applications of urban tree canopy assessment and prioritization tools: supporting collaborative decision making to achieve urban sustainability goals

Treesearch

Dexter H. Locke; J. Morgan Grove; Michael Galvin; Jarlath P.M. ONeil-Dunne; Charles Murphy

2013-01-01

Urban Tree Canopy (UTC) Prioritizations can be both a set of geographic analysis tools and a planning process for collaborative decision-making. In this paper, we describe how UTC Prioritizations can be used as a planning process to provide decision support to multiple government agencies, civic groups and private businesses to aid in reaching a canopy target. Linkages...

Flu Diagnosis System Using Jaccard Index and Rough Set Approaches

NASA Astrophysics Data System (ADS)

Efendi, Riswan; Azah Samsudin, Noor; Mat Deris, Mustafa; Guan Ting, Yip

2018-04-01

Jaccard index and rough set approaches have been frequently implemented in decision support systems with various domain applications. Both approaches are appropriate to be considered for categorical data analysis. This paper presents the applications of sets operations for flu diagnosis systems based on two different approaches, such as, Jaccard index and rough set. These two different approaches are established using set operations concept, namely intersection and subset. The step-by-step procedure is demonstrated from each approach in diagnosing flu system. The similarity and dissimilarity indexes between conditional symptoms and decision are measured using Jaccard approach. Additionally, the rough set is used to build decision support rules. Moreover, the decision support rules are established using redundant data analysis and elimination of unclassified elements. A number data sets is considered to attempt the step-by-step procedure from each approach. The result has shown that rough set can be used to support Jaccard approaches in establishing decision support rules. Additionally, Jaccard index is better approach for investigating the worst condition of patients. While, the definitely and possibly patients with or without flu can be determined using rough set approach. The rules may improve the performance of medical diagnosis systems. Therefore, inexperienced doctors and patients are easier in preliminary flu diagnosis.

Decision support models for solid waste management: Review and game-theoretic approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karmperis, Athanasios C., E-mail: athkarmp@mail.ntua.gr; Army Corps of Engineers, Hellenic Army General Staff, Ministry of Defence; Aravossis, Konstantinos

Highlights: ► The mainly used decision support frameworks for solid waste management are reviewed. ► The LCA, CBA and MCDM models are presented and their strengths, weaknesses, similarities and possible combinations are analyzed. ► The game-theoretic approach in a solid waste management context is presented. ► The waste management bargaining game is introduced as a specific decision support framework. ► Cooperative and non-cooperative game-theoretic approaches to decision support for solid waste management are discussed. - Abstract: This paper surveys decision support models that are commonly used in the solid waste management area. Most models are mainly developed within three decisionmore » support frameworks, which are the life-cycle assessment, the cost–benefit analysis and the multi-criteria decision-making. These frameworks are reviewed and their strengths and weaknesses as well as their critical issues are analyzed, while their possible combinations and extensions are also discussed. Furthermore, the paper presents how cooperative and non-cooperative game-theoretic approaches can be used for the purpose of modeling and analyzing decision-making in situations with multiple stakeholders. Specifically, since a waste management model is sustainable when considering not only environmental and economic but also social aspects, the waste management bargaining game is introduced as a specific decision support framework in which future models can be developed.« less

The Potential for Meta-Analysis to Support Decision Analysis in Ecology

ERIC Educational Resources Information Center

Mengersen, Kerrie; MacNeil, M. Aaron; Caley, M. Julian

2015-01-01

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable…

A systematic review of online resources to support patient decision-making for full-thickness rectal prolapse surgery.

PubMed

Fowler, G E; Baker, D M; Lee, M J; Brown, S R

2017-11-01

The internet is becoming an increasingly popular resource to support patient decision-making outside of the clinical encounter. The quality of online health information is variable and largely unregulated. The aim of this study was to assess the quality of online resources to support patient decision-making for full-thickness rectal prolapse surgery. This systematic review was registered on the PROSPERO database (CRD42017058319). Searches were performed on Google and specialist decision aid repositories using a pre-defined search strategy. Sources were analysed according to three measures: (1) their readability using the Flesch-Kincaid Reading Ease score, (2) DISCERN score and (3) International Patient Decision Aids Standards (IPDAS) minimum standards criteria score (IPDASi, v4.0). Overall, 95 sources were from Google and the specialist decision aid repositories. There were 53 duplicates removed, and 18 sources did not meet the pre-defined eligibility criteria, leaving 24 sources included in the full-text analysis. The mean Flesch-Kincaid Reading Ease score was higher than recommended for patient education materials (48.8 ± 15.6, range 25.2-85.3). Overall quality of sources supporting patient decision-making for full-thickness rectal prolapse surgery was poor (median DISCERN score 1/5 ± 1.18, range 1-5). No sources met minimum decision-making standards (median IPDASi score 5/12 ± 2.01, range 1-8). Currently, easily accessible online health information to support patient decision-making for rectal surgery is of poor quality, difficult to read and does not support shared decision-making. It is recommended that professional bodies and medical professionals seek to develop decision aids to support decision-making for full-thickness rectal prolapse surgery.

Characterizing uncertain sea-level rise projections to support investment decisions.

PubMed

Sriver, Ryan L; Lempert, Robert J; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions.

Characterizing uncertain sea-level rise projections to support investment decisions

PubMed Central

Lempert, Robert J.; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions. PMID:29414978

The assisted prediction modelling frame with hybridisation and ensemble for business risk forecasting and an implementation

NASA Astrophysics Data System (ADS)

Li, Hui; Hong, Lu-Yao; Zhou, Qing; Yu, Hai-Jie

2015-08-01

The business failure of numerous companies results in financial crises. The high social costs associated with such crises have made people to search for effective tools for business risk prediction, among which, support vector machine is very effective. Several modelling means, including single-technique modelling, hybrid modelling, and ensemble modelling, have been suggested in forecasting business risk with support vector machine. However, existing literature seldom focuses on the general modelling frame for business risk prediction, and seldom investigates performance differences among different modelling means. We reviewed researches on forecasting business risk with support vector machine, proposed the general assisted prediction modelling frame with hybridisation and ensemble (APMF-WHAE), and finally, investigated the use of principal components analysis, support vector machine, random sampling, and group decision, under the general frame in forecasting business risk. Under the APMF-WHAE frame with support vector machine as the base predictive model, four specific predictive models were produced, namely, pure support vector machine, a hybrid support vector machine involved with principal components analysis, a support vector machine ensemble involved with random sampling and group decision, and an ensemble of hybrid support vector machine using group decision to integrate various hybrid support vector machines on variables produced from principle components analysis and samples from random sampling. The experimental results indicate that hybrid support vector machine and ensemble of hybrid support vector machines were able to produce dominating performance than pure support vector machine and support vector machine ensemble.

Evaluation of the Effectiveness of Stormwater Decision Support Tools for Infrastructure Selection and the Barriers to Implementation

NASA Astrophysics Data System (ADS)

Spahr, K.; Hogue, T. S.

2016-12-01

Selecting the most appropriate green, gray, and / or hybrid system for stormwater treatment and conveyance can prove challenging to decision markers across all scales, from site managers to large municipalities. To help streamline the selection process, a multi-disciplinary team of academics and professionals is developing an industry standard for selecting and evaluating the most appropriate stormwater management technology for different regions. To make the tool more robust and comprehensive, life-cycle cost assessment and optimization modules will be included to evaluate non-monetized and ecosystem benefits of selected technologies. Initial work includes surveying advisory board members based in cities that use existing decision support tools in their infrastructure planning process. These surveys will qualify the decisions currently being made and identify challenges within the current planning process across a range of hydroclimatic regions and city size. Analysis of social and other non-technical barriers to adoption of the existing tools is also being performed, with identification of regional differences and institutional challenges. Surveys will also gage the regional appropriateness of certain stormwater technologies based off experiences in implementing stormwater treatment and conveyance plans. In additional to compiling qualitative data on existing decision support tools, a technical review of components of the decision support tool used will be performed. Gaps in each tool's analysis, like the lack of certain critical functionalities, will be identified and ease of use will be evaluated. Conclusions drawn from both the qualitative and quantitative analyses will be used to inform the development of the new decision support tool and its eventual dissemination.

An innovative approach to addressing childhood obesity: a knowledge-based infrastructure for supporting multi-stakeholder partnership decision-making in Quebec, Canada.

PubMed

Addy, Nii Antiaye; Shaban-Nejad, Arash; Buckeridge, David L; Dubé, Laurette

2015-01-23

Multi-stakeholder partnerships (MSPs) have become a widespread means for deploying policies in a whole of society strategy to address the complex problem of childhood obesity. However, decision-making in MSPs is fraught with challenges, as decision-makers are faced with complexity, and have to reconcile disparate conceptualizations of knowledge across multiple sectors with diverse sets of indicators and data. These challenges can be addressed by supporting MSPs with innovative tools for obtaining, organizing and using data to inform decision-making. The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process assessment was conducted to understand the needs of communities as they collect, organize, and analyze data to make decisions about their priorities. The result of this process is a "portrait", which is an epidemiological profile of health and nutrition in their community. Portraits inform strategic planning and development of interventions, and are used to assess the impact of interventions. Our key findings indicate ambiguities and disagreement among MSP decision-makers regarding causal relationships between actions and outcomes, and the relevant data needed for making decisions. MSP decision-makers expressed a desire for easy-to-use tools that facilitate the collection, organization, synthesis, and analysis of data, to enable decision-making in a timely manner. Findings inform conceptual modeling and ontological analysis to capture the domain knowledge and specify relationships between actions and outcomes. This modeling and analysis provide the foundation for an ontology, encoded using OWL 2 Web Ontology Language. The ontology is developed to provide semantic support for the MSP process, defining objectives, strategies, actions, indicators, and data sources. In the future, software interacting with the ontology can facilitate interactive browsing by decision-makers in the MSP in the form of concepts, instances, relationships, and axioms. Our ontology also facilitates the integration and interpretation of community data, and can help in managing semantic interoperability between different knowledge sources. Future work will focus on defining specifications for the development of a database of indicators and an information system to help decision-makers to view, analyze and organize indicators for their community. This work should improve MSP decision-making in the development of interventions to address childhood obesity.

An Innovative Approach to Addressing Childhood Obesity: A Knowledge-Based Infrastructure for Supporting Multi-Stakeholder Partnership Decision-Making in Quebec, Canada

PubMed Central

Addy, Nii Antiaye; Shaban-Nejad, Arash; Buckeridge, David L.; Dubé, Laurette

2015-01-01

Multi-stakeholder partnerships (MSPs) have become a widespread means for deploying policies in a whole of society strategy to address the complex problem of childhood obesity. However, decision-making in MSPs is fraught with challenges, as decision-makers are faced with complexity, and have to reconcile disparate conceptualizations of knowledge across multiple sectors with diverse sets of indicators and data. These challenges can be addressed by supporting MSPs with innovative tools for obtaining, organizing and using data to inform decision-making. The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process assessment was conducted to understand the needs of communities as they collect, organize, and analyze data to make decisions about their priorities. The result of this process is a “portrait”, which is an epidemiological profile of health and nutrition in their community. Portraits inform strategic planning and development of interventions, and are used to assess the impact of interventions. Our key findings indicate ambiguities and disagreement among MSP decision-makers regarding causal relationships between actions and outcomes, and the relevant data needed for making decisions. MSP decision-makers expressed a desire for easy-to-use tools that facilitate the collection, organization, synthesis, and analysis of data, to enable decision-making in a timely manner. Findings inform conceptual modeling and ontological analysis to capture the domain knowledge and specify relationships between actions and outcomes. This modeling and analysis provide the foundation for an ontology, encoded using OWL 2 Web Ontology Language. The ontology is developed to provide semantic support for the MSP process, defining objectives, strategies, actions, indicators, and data sources. In the future, software interacting with the ontology can facilitate interactive browsing by decision-makers in the MSP in the form of concepts, instances, relationships, and axioms. Our ontology also facilitates the integration and interpretation of community data, and can help in managing semantic interoperability between different knowledge sources. Future work will focus on defining specifications for the development of a database of indicators and an information system to help decision-makers to view, analyze and organize indicators for their community. This work should improve MSP decision-making in the development of interventions to address childhood obesity. PMID:25625409

Advanced Economic Analysis

NASA Technical Reports Server (NTRS)

Greenberg, Marc W.; Laing, William

2013-01-01

An Economic Analysis (EA) is a systematic approach to the problem of choosing the best method of allocating scarce resources to achieve a given objective. An EA helps guide decisions on the "worth" of pursuing an action that departs from status quo ... an EA is the crux of decision-support.

Career exploration behavior of Korean medical students

PubMed Central

2017-01-01

Purpose This study is to analyze the effects of medical students’ social support and career barriers on career exploration behavior mediated by career decision-making self-efficacy. Methods We applied the t-test to investigate the difference among the variables based on gender and admission types. Also, we performed path analysis to verify the effect of perceived career barriers and social support on career exploration behavior with career decision efficacy as a mediator. Results First, we noted statistically significant gender and admission type difference in social support, career barriers and career exploration behaviors. Second, social support and career barriers were found to influence career exploration behavior as a mediating variable for career decision-making self-efficacy. Conclusion Social support and career barriers as perceived by medical students influenced their career exploration behavior, with their decision-making self-efficacy serving as a full mediator. Therefore, this study has educational implications for career program development and educational training for career decision-making self-efficacy. PMID:28870020

Clinical decision support provided within physician order entry systems: a systematic review of features effective for changing clinician behavior.

PubMed

Kawamoto, Kensaku; Lobach, David F

2003-01-01

Computerized physician order entry (CPOE) systems represent an important tool for providing clinical decision support. In undertaking this systematic review, our objective was to identify the features of CPOE-based clinical decision support systems (CDSSs) most effective at modifying clinician behavior. For this review, two independent reviewers systematically identified randomized controlled trials that evaluated the effectiveness of CPOE-based CDSSs in changing clinician behavior. Furthermore, each included study was assessed for the presence of 14 CDSS features. We screened 10,023 citations and included 11 studies. Of the 10 studies comparing a CPOE-based CDSS intervention against a non-CDSS control group, 7 reported a significant desired change in professional practice. Moreover, meta-regression analysis revealed that automatic provision of the decision support was strongly associated with improved professional practice (adjusted odds ratio, 23.72; 95% confidence interval, 1.75-infiniti). Thus, we conclude that automatic provision of decision support is a critical feature of successful CPOE-based CDSS interventions.

The design of patient decision support interventions: addressing the theory-practice gap.

PubMed

Elwyn, Glyn; Stiel, Mareike; Durand, Marie-Anne; Boivin, Jacky

2011-08-01

Although an increasing number of decision support interventions for patients (including decision aids) are produced, few make explicit use of theory. We argue the importance of using theory to guide design. The aim of this work was to address this theory-practice gap and to examine how a range of selected decision-making theories could inform the design and evaluation of decision support interventions. We reviewed the decision-making literature and selected relevant theories. We assessed their key principles, theoretical pathways and predictions in order to determine how they could inform the design of two core components of decision support interventions, namely, information and deliberation components and to specify theory-based outcome measures. Eight theories were selected: (1) the expected utility theory; (2) the conflict model of decision making; (3) prospect theory; (4) fuzzy-trace theory; (5) the differentiation and consolidation theory; (6) the ecological rationality theory; (7) the rational-emotional model of decision avoidance; and finally, (8) the Attend, React, Explain, Adapt model of affective forecasting. Some theories have strong relevance to the information design (e.g. prospect theory); some are more relevant to deliberation processes (conflict theory, differentiation theory and ecological validity). None of the theories in isolation was sufficient to inform the design of all the necessary components of decision support interventions. It was also clear that most work in theory-building has focused on explaining or describing how humans think rather than on how tools could be designed to help humans make good decisions. It is not surprising therefore that a large theory-practice gap exists as we consider decision support for patients. There was no relevant theory that integrated all the necessary contributions to the task of making good decisions in collaborative interactions. Initiatives such as the International Patient Decision Aids Standards Collaboration influence standards for the design of decision support interventions. However, this analysis points to the need to undertake more work in providing theoretical foundations for these interventions. © 2010 Blackwell Publishing Ltd.

Towards Supporting Patient Decision-making In Online Diabetes Communities

PubMed Central

Zhang, Jing; Marmor, Rebecca; Huh, Jina

2017-01-01

As of 2014, 29.1 million people in the US have diabetes. Patients with diabetes have evolving information needs around complex lifestyle and medical decisions. As their conditions progress, patients need to sporadically make decisions by understanding alternatives and comparing options. These moments along the decision-making process present a valuable opportunity to support their information needs. An increasing number of patients visit online diabetes communities to fulfill their information needs. To understand how patients attempt to fulfill the information needs around decision-making in online communities, we reviewed 801 posts from an online diabetes community and included 79 posts for in-depth content analysis. The findings revealed motivations for posters’ inquiries related to decision-making including the changes in disease state, increased self-awareness, and conflict of information received. Medication and food were the among the most popular topics discussed as part of their decision-making inquiries. Additionally, We present insights for automatically identifying those decision-making inquiries to efficiently support information needs presented in online health communities. PMID:29854261

Distributed collaborative environments for predictive battlespace awareness

NASA Astrophysics Data System (ADS)

McQuay, William K.

2003-09-01

The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, make quick-response decisions, and quantify the effects of those decisions in the face of uncertainty. Situational assessment is crucial in understanding the battlespace. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Decision support technologies can semi-automate activities, such as analysis and planning, that have a reasonably well-defined process and provide machine-level interfaces to refine the myriad of information that the commander must fused. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing AFRL research efforts in applying distributed collaborative environments to predictive battlespace awareness.

Best-worst scaling to assess the most important barriers and facilitators for the use of health technology assessment in Austria.

PubMed

Feig, Chiara; Cheung, Kei Long; Hiligsmann, Mickaël; Evers, Silvia M A A; Simon, Judit; Mayer, Susanne

2018-04-01

Although Health Technology Assessment (HTA) is increasingly used to support evidence-based decision-making in health care, several barriers and facilitators for the use of HTA have been identified. This best-worst scaling (BWS) study aims to assess the relative importance of selected barriers and facilitators of the uptake of HTA studies in Austria. A BWS object case survey was conducted among 37 experts in Austria to assess the relative importance of HTA barriers and facilitators. Hierarchical Bayes estimation was applied, with the best-worst count analysis as sensitivity analysis. Subgroup analyses were also performed on professional role and HTA experience. The most important barriers were 'lack of transparency in the decision-making process', 'fragmentation', 'absence of appropriate incentives', 'no explicit framework for decision-making process', and 'insufficient legal support'. The most important facilitators were 'transparency in the decision-making process', 'availability of relevant HTA research for policy makers', 'availability of explicit framework for decision-making process', 'sufficient legal support', and 'appropriate incentives'. This study suggests that HTA barriers and facilitators related to the context of decision makers, especially 'policy characteristics' and 'organization and resources' are the most important in Austria. A transparent and participatory decision-making process could improve the adoption of HTA evidence.

Applications of Formal Methods to Specification and Safety of Avionics Software

NASA Technical Reports Server (NTRS)

Hoover, D. N.; Guaspari, David; Humenn, Polar

1996-01-01

This report treats several topics in applications of formal methods to avionics software development. Most of these topics concern decision tables, an orderly, easy-to-understand format for formally specifying complex choices among alternative courses of action. The topics relating to decision tables include: generalizations fo decision tables that are more concise and support the use of decision tables in a refinement-based formal software development process; a formalism for systems of decision tables with behaviors; an exposition of Parnas tables for users of decision tables; and test coverage criteria and decision tables. We outline features of a revised version of ORA's decision table tool, Tablewise, which will support many of the new ideas described in this report. We also survey formal safety analysis of specifications and software.

Negotiated autonomy in diabetes self-management: the experiences of adults with intellectual disability and their support workers.

PubMed

Whitehead, L C; Trip, H T; Hale, L A; Conder, J

2016-02-02

The basic human right of autonomy is underpinned by the ability to practice decision-making. The rights of people with disabilities to engage in autonomous decision-making are promoted as best practice and includes decisions around health and self-care. Little is known about autonomy in the field of long-term condition management. This paper explores how people with intellectual disabilities (ID) and their support workers experience and practice autonomy in relation to the management of diabetes. Semi-structured interviews were completed in residential and independent living settings with people living with an ID and type 1 (N = 8) or type 2 (N = 6) diabetes and their support workers (N = 17). The participant with ID's support worker was present as requested; however, the interviews were run separately with each participant rather than jointly. Thematic analysis was undertaken, and a constructivist lens informed both data collection and analysis. The analysis revealed a strong process of negotiated autonomy between people with ID and their support workers in relation to the daily management of diabetes. During times of transition, roles in relation to diabetes management were renegotiated, and the promotion of autonomy was prefaced within the context of risk and client safety. Goals to increase independence were drivers for negotiating greater autonomy. The successful negotiation of autonomy in relation to diabetes illustrates the potential for people with ID to play a key role in the management of long-term health conditions. The study highlights the primacy of developing decision-making skills among people with ID. Promoting opportunities for decision-making and an ethos of supported decision-making through person-centred planning are all vital in working towards enhancing autonomy. © 2016 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Shared decision-making and decision support: their role in obstetrics and gynecology.

PubMed

Tucker Edmonds, Brownsyne

2014-12-01

To discuss the role for shared decision-making in obstetrics/gynecology and to review evidence on the impact of decision aids on reproductive health decision-making. Among the 155 studies included in a 2014 Cochrane review of decision aids, 31 (29%) addressed reproductive health decisions. Although the majority did not show evidence of an effect on treatment choice, there was a greater uptake of mammography in selected groups of women exposed to decision aids compared with usual care; and a statistically significant reduction in the uptake of hormone replacement therapy among detailed decision aid users compared with simple decision aid users. Studies also found an effect on patient-centered outcomes of care, such as medication adherence, quality-of-life measures, and anxiety scores. In maternity care, only decision analysis tools affected final treatment choice, and patient-directed aids yielded no difference in planned mode of birth after cesarean. There is untapped potential for obstetricians/gynecologists to optimize decision support for reproductive health decisions. Given the limited evidence-base guiding practice, the preference-sensitive nature of reproductive health decisions, and the increase in policy efforts and financial incentives to optimize patients' satisfaction, it is increasingly important for obstetricians/gynecologists to appreciate the role of shared decision-making and decision support in providing patient-centered reproductive healthcare.

Radiological emergency response for community agencies with cognitive task analysis, risk analysis, and decision support framework.

PubMed

Meyer, Travis S; Muething, Joseph Z; Lima, Gustavo Amoras Souza; Torres, Breno Raemy Rangel; del Rosario, Trystyn Keia; Gomes, José Orlando; Lambert, James H

2012-01-01

Radiological nuclear emergency responders must be able to coordinate evacuation and relief efforts following the release of radioactive material into populated areas. In order to respond quickly and effectively to a nuclear emergency, high-level coordination is needed between a number of large, independent organizations, including police, military, hazmat, and transportation authorities. Given the complexity, scale, time-pressure, and potential negative consequences inherent in radiological emergency responses, tracking and communicating information that will assist decision makers during a crisis is crucial. The emergency response team at the Angra dos Reis nuclear power facility, located outside of Rio de Janeiro, Brazil, presently conducts emergency response simulations once every two years to prepare organizational leaders for real-life emergency situations. However, current exercises are conducted without the aid of electronic or software tools, resulting in possible cognitive overload and delays in decision-making. This paper describes the development of a decision support system employing systems methodologies, including cognitive task analysis and human-machine interface design. The decision support system can aid the coordination team by automating cognitive functions and improving information sharing. A prototype of the design will be evaluated by plant officials in Brazil and incorporated to a future trial run of a response simulation.

DEVELOPMENT PLAN FOR THE CAUSAL ANALYSIS / DIAGNOSIS DECISION INFORMATION SYSTEM (CADDIS) 2001-2004

EPA Science Inventory

The Causal Analysis/Diagnosis Decision Information System (CADDIS) is a web-based system that provides technical support for states, tribes and other users of the Office of Water's Stressor Identification Guidance. The Stressor Identific...

Amy Rose | NREL

Science.gov Websites

Rose is a member of the Markets & Policy Analysis Group in the Strategic Energy Analysis Center integration of renewable energy Research Interests Energy policy and regulation Decision support tools to inform power sector policy and regulatory decisions Energy and development International energy policy

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

PubMed

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

2016-06-01

Red blood cell transfusion is the most common procedure in hospitalized patients in the US. Growing evidence suggests that a sizeable percentage of these transfusions are inappropriate, putting patients at significant risk and increasing costs to the health care system. We performed a retrospective quasi-experimental study from November 2008 until November 2014 in a 576-bed tertiary care hospital. The intervention consisted of an interruptive clinical decision support alert shown to a provider when a red blood cell transfusion was ordered in a patient whose most recent hematocrit was ≥21%. We used interrupted time series analysis to determine whether our primary outcome of interest, rate of red blood cell transfusion in patients with hematocrit ≥21% per 100 patient (pt) days, was reduced by the implementation of the clinical decision support tool. The rate of platelet transfusions was used as a nonequivalent dependent control variable. A total of 143,000 hospital admissions were included in our analysis. Red blood cell transfusions decreased from 9.4 to 7.8 per 100 pt days after the clinical decision support intervention was implemented. Interrupted time series analysis showed that significant decline of 0.05 (95% confidence interval [CI], 0.03-0.07; P < .001) units of red blood cells transfused per 100 pt days per month was already underway in the preintervention period. This trend accelerated to 0.1 (95% CI, 0.09-0.12; P < .001) units of red blood cells transfused per 100 pt days per month following the implementation of the clinical decision support tool. There was no statistical change in the rate of platelet transfusion resulting from the intervention. The implementation of an evidence-based clinical decision support tool was associated with a significant decline in the overuse of red blood cell transfusion. We believe this intervention could be easily replicated in other hospitals using commercial electronic health records and a similar reduction in overuse of red blood cell transfusions achieved. Copyright © 2016 Elsevier Inc. All rights reserved.

Computer Based Decision Support Tool for Helicopter Mission Planning in Disaster Relief and Military Operations (Outil informatique d’aide a la decision pour la planification des missions d’helicopteres dans des operations militaires et de secours en cas de catastrophe)

DTIC Science & Technology

2008-06-01

capacity planning; • Electrical generation capacity planning; • Machine scheduling; • Freight scheduling; • Dairy farm expansion planning...Support Systems and Multi Criteria Decision Analysis Products A.2.11.2.2.1 ELECTRE IS ELECTRE IS is a generalization of ELECTRE I. It is a...criteria, ELECTRE IS supports the user in the process of selecting one alternative or a subset of alternatives. The method consists of two parts

Extensions to regret-based decision curve analysis: an application to hospice referral for terminal patients.

PubMed

Tsalatsanis, Athanasios; Barnes, Laura E; Hozo, Iztok; Djulbegovic, Benjamin

2011-12-23

Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed. We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed regret based decision curve analysis (regret DCA). We extend the regret DCA methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care. The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, regret DCA is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available. We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned.

Extensions to Regret-based Decision Curve Analysis: An application to hospice referral for terminal patients

PubMed Central

2011-01-01

Background Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed. Methods We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed regret based decision curve analysis (regret DCA). We extend the regret DCA methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care. Results The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, regret DCA is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available. Conclusions We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned. PMID:22196308

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

PubMed

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

2015-07-01

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

An Integrated Web-based Decision Support System in Disaster Risk Management

NASA Astrophysics Data System (ADS)

Aye, Z. C.; Jaboyedoff, M.; Derron, M. H.

2012-04-01

Nowadays, web based decision support systems (DSS) play an essential role in disaster risk management because of their supporting abilities which help the decision makers to improve their performances and make better decisions without needing to solve complex problems while reducing human resources and time. Since the decision making process is one of the main factors which highly influence the damages and losses of society, it is extremely important to make right decisions at right time by combining available risk information with advanced web technology of Geographic Information System (GIS) and Decision Support System (DSS). This paper presents an integrated web-based decision support system (DSS) of how to use risk information in risk management efficiently and effectively while highlighting the importance of a decision support system in the field of risk reduction. Beyond the conventional systems, it provides the users to define their own strategies starting from risk identification to the risk reduction, which leads to an integrated approach in risk management. In addition, it also considers the complexity of changing environment from different perspectives and sectors with diverse stakeholders' involvement in the development process. The aim of this platform is to contribute a part towards the natural hazards and geosciences society by developing an open-source web platform where the users can analyze risk profiles and make decisions by performing cost benefit analysis, Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) with the support of others tools and resources provided. There are different access rights to the system depending on the user profiles and their responsibilities. The system is still under development and the current version provides maps viewing, basic GIS functionality, assessment of important infrastructures (e.g. bridge, hospital, etc.) affected by landslides and visualization of the impact-probability matrix in terms of socio-economic dimension.

Advancing beyond the system: telemedicine nurses' clinical reasoning using a computerised decision support system for patients with COPD - an ethnographic study.

PubMed

Barken, Tina Lien; Thygesen, Elin; Söderhamn, Ulrika

2017-12-28

Telemedicine is changing traditional nursing care, and entails nurses performing advanced and complex care within a new clinical environment, and monitoring patients at a distance. Telemedicine practice requires complex disease management, advocating that the nurses' reasoning and decision-making processes are supported. Computerised decision support systems are being used increasingly to assist reasoning and decision-making in different situations. However, little research has focused on the clinical reasoning of nurses using a computerised decision support system in a telemedicine setting. Therefore, the objective of the study is to explore the process of telemedicine nurses' clinical reasoning when using a computerised decision support system for the management of patients with chronic obstructive pulmonary disease. The factors influencing the reasoning and decision-making processes were investigated. In this ethnographic study, a combination of data collection methods, including participatory observations, the think-aloud technique, and a focus group interview was employed. Collected data were analysed using qualitative content analysis. When telemedicine nurses used a computerised decision support system for the management of patients with complex, unstable chronic obstructive pulmonary disease, two categories emerged: "the process of telemedicine nurses' reasoning to assess health change" and "the influence of the telemedicine setting on nurses' reasoning and decision-making processes". An overall theme, termed "advancing beyond the system", represented the connection between the reasoning processes and the telemedicine work and setting, where being familiar with the patient functioned as a foundation for the nurses' clinical reasoning process. In the telemedicine setting, when supported by a computerised decision support system, nurses' reasoning was enabled by the continuous flow of digital clinical data, regular video-mediated contact and shared decision-making with the patient. These factors fostered an in-depth knowledge of the patients and acted as a foundation for the nurses' reasoning process. Nurses' reasoning frequently advanced beyond the computerised decision support system recommendations. Future studies are warranted to develop more accurate algorithms, increase system maturity, and improve the integration of the digital clinical information with clinical experiences, to support telemedicine nurses' reasoning process.

A framework to support decision making in the selection of sustainable drainage system design alternatives.

PubMed

Wang, Mingming; Sweetapple, Chris; Fu, Guangtao; Farmani, Raziyeh; Butler, David

2017-10-01

This paper presents a new framework for decision making in sustainable drainage system (SuDS) scheme design. It integrates resilience, hydraulic performance, pollution control, rainwater usage, energy analysis, greenhouse gas (GHG) emissions and costs, and has 12 indicators. The multi-criteria analysis methods of entropy weight and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) were selected to support SuDS scheme selection. The effectiveness of the framework is demonstrated with a SuDS case in China. Indicators used include flood volume, flood duration, a hydraulic performance indicator, cost and resilience. Resilience is an important design consideration, and it supports scheme selection in the case study. The proposed framework will help a decision maker to choose an appropriate design scheme for implementation without subjectivity. Copyright © 2017 Elsevier Ltd. All rights reserved.

FRAMEWORK FOR ENVIRONMENTAL DECISION-MAKING, FRED: A TOOL FOR ENVIRONMENTALLY-PREFERABLE PURCHASING

EPA Science Inventory

In support of the Environmentally Preferable Purchasing Program of the US EPA, the Systems Analysis Branch has developed a decision-making tool based on life cycle assessment. This tool, the Framework for Responsible Environmental Decision-making or FRED streamlines LCA by choosi...

End of life decisions: nurses perceptions, feelings and experiences.

PubMed

McMillen, Rachel E

2008-08-01

Decisions to withdraw treatment are made on a regular basis in intensive care units. While nurses play a central role in patient care, previous studies have found that they are not always involved in withdrawal decisions. To explore the experiences of ICU nurses caring for patients who have had their treatment withdrawn and to answer two research questions: what role do nurses play and how does this affect them? Constructivist grounded theory was used to explore the experiences and feelings of ICU nurses. A purposive sample of eight ICU nurses participated and semi-structured interviews were used to collect data. Framework analysis was used to facilitate systematic analysis. The analysis revealed two major themes (1) the nurse's role: experience counts, not really a nurse's decision, planting the seed, supporting the family and being a patient advocate and (2) perceptions of the withdrawal of treatment: getting the timing right and emotional labour. Nurses make an important contribution to end of life decisions and care. Guidelines recommend they have input into withdrawal decisions, therefore it is imperative that nurses are supported in this role and their responsibilities to continue to provide care during withdrawal.

EnviroAtlas Webinar

EPA Pesticide Factsheets

EnviroAtlas is a web-based decision support tool that combines maps, analysis tools, downloadable data and informational resources that states, tribes and communities can use to help inform policy and planning decisions impacting their surroundings.

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

PubMed

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.

Treatment decision-making in ductal carcinoma in situ: A mixed methods systematic review of women's experiences and information needs.

PubMed

Rutherford, Claudia; Mercieca-Bebber, Rebecca; Butow, Phyllis; Wu, Jenny Liang; King, Madeleine T

2017-09-01

Decision-making in ductal carcinoma in situ (DCIS) is complex due to the heterogeneity of the disease. This study aimed to understand women's experience of making treatment decisions for DCIS, their information and support needs, and factors that influenced decisions. We searched six electronic databases, conference proceedings, and key authors. Two reviewers independently applied inclusion and quality criteria, and extracted findings. Thematic analysis was used to combine and summarise findings. We identified six themes and 28 subthemes from 18 studies. Women with DCIS have knowledge deficits about DCIS, experience anxiety related to information given at diagnosis and the complexity of decision-making, and have misconceptions regarding risks and outcomes of treatment. Women's decisions are influenced by their understanding of risk, the clinical features of their DCIS, and the benefits and harms of treatment options. Women are dissatisfied with the decisional support available. Informed and shared decision-making in this complex decision setting requires clear communication of information specific to DCIS and individual's, as well as decision support for patients and clinicians. This approach would educate patients and clinicians, and assist clinicians in supporting patients to an evidence-based treatment plan that aligns with individual values and pReferences. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of an intervention to support patients and clinicians with advanced lung cancer when considering systematic anticancer therapy: protocol for the PACT study.

PubMed

Anagnostou, Despina; Sivell, Stephanie; Noble, Simon; Lester, Jason; Byrne, Anthony; Sampson, Catherine; Longo, Mirella; Nelson, Annmarie

2017-07-12

Patient-centred care is essential to the delivery of healthcare; however, this necessitates direct patient involvement in clinical decision-making and can be challenging for patients diagnosed with advanced non-small cell lung cancer where there may be misunderstanding of the extent of disease, prognosis and aims of treatment. In this context, decisions are complex and there is a need to balance the risks and benefits, including treatment with palliative intent. The aim of the PACT study is to identify the information and decision support needs of patients, leading to the development of an intervention to support patients with advanced lung cancer when considering treatment options. PACT is a five-stage, multimethod and multicentre study. Participants : Patients and health professionals will be recruited from three health boards. Methods : Non-participant observation of multidisciplinary team meetings (n=12) will be used to determine patients' allocation to treatment pathways (stage I). Non-participant observation of patient-clinician consultations (n=20-30) will be used to explore communication of treatment options and decision-making. Extent of participation in decision-making will be assessed using the Observing Patient Involvement in Shared Decision-Making tool. Interviews with patients (stage III) and their clinicians (stage IV) will explore the perception of treatment options and involvement in decision-making. Based on stages I-IV, an expert consensus meeting will finalise the content and format of the intervention. Cognitive interviews with patients will then determine the face validity of the intervention (stage V). Analysis : analysis will be according to data type and research question and will include mediated discourse analysis, thematic analysis, framework analysis and interpretative phenomenological analysis. Ethical approval has been granted. The study findings will contribute to and promote shared and informed decision-making in the best interest of patients and prudent healthcare. We therefore aim to disseminate results via relevant respiratory, oncology and palliative care journals and conferences. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

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

PubMed

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

2017-05-01

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

E-DECIDER Decision Support Gateway For Earthquake Disaster Response

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

A multimedia electronic patient record (ePR) system to improve decision support in pre- and rehabilitation through clinical and movement analysis

NASA Astrophysics Data System (ADS)

Liu, Brent; Documet, Jorge; McNitt-Gray, Sarah; Requejo, Phil; McNitt-Gray, Jill

2011-03-01

Clinical decisions for improving motor function in patients both with disability as well as improving an athlete's performance are made through clinical and movement analysis. Currently, this analysis facilitates identifying abnormalities in a patient's motor function for a large amount of neuro-musculoskeletal pathologies. However definitively identifying the underlying cause or long-term consequences of a specific abnormality in the patient's movement pattern is difficult since this requires information from multiple sources and formats across different times and currently relies on the experience and intuition of the expert clinician. In addition, this data must be persistent for longitudinal outcomes studies. Therefore a multimedia ePR system integrating imaging informatics data could have a significant impact on decision support within this clinical workflow. We present the design and architecture of such an ePR system as well as the data types that need integration in order to develop relevant decision support tools. Specifically, we will present two data model examples: 1) A performance improvement project involving volleyball athletes and 2) Wheelchair propulsion evaluation of patients with disabilities. The end result is a new frontier area of imaging informatics research within rehabilitation engineering and biomechanics.

Agent-based Decision Support System for the Third Generation Distributed Dynamic Decision-making (DDD-III) Simulator

DTIC Science & Technology

2004-06-01

suitable form of organizational adaptation is effective organizational diagnosis and analysis. The organizational diagnosis and analysis involve...related to the mission environment, organizational structure, and strategy is imperative for an effective and efficient organizational diagnosis . The...not easily articulated nor expressed otherwise. These displays are crucial to facilitate effective organizational diagnosis and analysis, and

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Malley, Daniel; Vesselinov, Velimir V.

MADSpython (Model analysis and decision support tools in Python) is a code in Python that streamlines the process of using data and models for analysis and decision support using the code MADS. MADS is open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11-035). MADS can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. The Python scripts in MADSpython facilitate the generation of input and output file needed by MADS as wells as the external simulators which include FEHM and PFLOTRAN. MADSpython enables a number of data-more » and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. MADSpython will be released under GPL V3 license. MADSpython will be distributed as a Git repo at gitlab.com and github.com. MADSpython manual and documentation will be posted at http://madspy.lanl.gov.« less

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis

PubMed Central

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine

2018-01-01

Background Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. Objective The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. Methods The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Results Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. Conclusions MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians’ skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. PMID:29720361

Nurse managers' decision-making in daily unit operation in peri-operative settings: a cross-sectional descriptive study.

PubMed

Siirala, Eriikka; Peltonen, Laura-Maria; Lundgrén-Laine, Heljä; Salanterä, Sanna; Junttila, Kristiina

2016-09-01

To describe the tactical and the operational decisions made by nurse managers when managing the daily unit operation in peri-operative settings. Management is challenging as situations change rapidly and decisions are constantly made. Understanding decision-making in this complex environment helps to develop decision support systems to support nurse managers' operative and tactical decision-making. Descriptive cross-sectional design. Data were collected from 20 nurse managers with the think-aloud method during the busiest working hours and analysed using thematic content analysis. Nurse managers made over 700 decisions; either ad hoc (n = 289), near future (n = 268) or long-term (n = 187) by nature. Decisions were often made simultaneously with many interruptions. Ad hoc decisions covered staff allocation, ensuring adequate staff, rescheduling surgical procedures, confirmation tangible resources and following-up the daily unit operation. Decisions in the near future were: planning of surgical procedures and tangible resources, and planning staff allocation. Long-term decisions were: human recourses, nursing development, supplies and equipment, and finances in the unit. Decision-making was vulnerable to interruptions, which sometimes complicated the managing tasks. The results can be used when planning decision support systems and when defining the nurse managers' tasks in peri-operative settings. © 2016 John Wiley & Sons Ltd.

Insurance Contract Analysis for Company Decision Support in Acquisition Management

NASA Astrophysics Data System (ADS)

Chernovita, H. P.; Manongga, D.; Iriani, A.

2017-01-01

One of company activities to retain their business is marketing the products which include in acquisition management to get new customers. Insurance contract analysis using ID3 to produce decision tree and rules to be decision support for the insurance company. The decision tree shows 13 rules that lead to contract termination claim. This could be a guide for the insurance company in acquisition management to prevent contract binding with these contract condition because it has a big chance for the customer to terminate their insurance contract before its expired date. As the result, there are several strong points that could be the determinant of contract termination such as: 1) customer age whether too young or too old, 2) long insurance period (above 10 years), 3) big insurance amount, 4) big amount of premium charges, and 5) payment method.

Analytical and CASE study on Limited Search, ID3, CHAID, C4.5, Improved C4.5 and OVA Decision Tree Algorithms to design Decision Support System

NASA Astrophysics Data System (ADS)

Kaur, Parneet; Singh, Sukhwinder; Garg, Sushil; Harmanpreet

2010-11-01

In this paper we study about classification algorithms for farm DSS. By applying classification algorithms i.e. Limited search, ID3, CHAID, C4.5, Improved C4.5 and One VS all Decision Tree on common data set of crop with specified class, results are obtained. The tool used to derive results is SPINA. The graphical results obtained from tool are compared to suggest best technique to develop farm Decision Support System. This analysis would help to researchers to design effective and fast DSS for farmer to take decision for enhancing their yield.

Decision science: a scientific approach to enhance public health budgeting.

PubMed

Honoré, Peggy A; Fos, Peter J; Smith, Torney; Riley, Michael; Kramarz, Kim

2010-01-01

The allocation of resources for public health programming is a complicated and daunting responsibility. Financial decision-making processes within public health agencies are especially difficult when not supported with techniques for prioritizing and ranking alternatives. This article presents a case study of a decision analysis software model that was applied to the process of identifying funding priorities for public health services in the Spokane Regional Health District. Results on the use of this decision support system provide insights into how decision science models, which have been used for decades in business and industry, can be successfully applied to public health budgeting as a means of strengthening agency financial management processes.

A multicriteria decision making model for assessment and selection of an ERP in a logistics context

NASA Astrophysics Data System (ADS)

Pereira, Teresa; Ferreira, Fernanda A.

2017-07-01

The aim of this work is to apply a methodology of decision support based on a multicriteria decision analyses (MCDA) model that allows the assessment and selection of an Enterprise Resource Planning (ERP) in a Portuguese logistics company by Group Decision Maker (GDM). A Decision Support system (DSS) that implements a MCDA - Multicriteria Methodology for the Assessment and Selection of Information Systems / Information Technologies (MMASSI / IT) is used based on its features and facility to change and adapt the model to a given scope. Using this DSS it was obtained the information system that best suited to the decisional context, being this result evaluated through a sensitivity and robustness analysis.

Predicting species distributions for conservation decisions

PubMed Central

Guisan, Antoine; Tingley, Reid; Baumgartner, John B; Naujokaitis-Lewis, Ilona; Sutcliffe, Patricia R; Tulloch, Ayesha I T; Regan, Tracey J; Brotons, Lluis; McDonald-Madden, Eve; Mantyka-Pringle, Chrystal; Martin, Tara G; Rhodes, Jonathan R; Maggini, Ramona; Setterfield, Samantha A; Elith, Jane; Schwartz, Mark W; Wintle, Brendan A; Broennimann, Olivier; Austin, Mike; Ferrier, Simon; Kearney, Michael R; Possingham, Hugh P; Buckley, Yvonne M

2013-01-01

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of ‘translators’ between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes. PMID:24134332

Developing Digital Dashboard Management for Learning System Dynamic Cooperative Simulation Behavior of Indonesia. (Study on Cooperative Information Organization in the Ministry of Cooperatives and SME)

NASA Astrophysics Data System (ADS)

Eni, Yuli; Aryanto, Rudy

2014-03-01

There are problems being experienced by the Ministry of cooperatives and SME (Small and Medium Enterprise) including the length of time in the decision by the Government to establish a policy that should be taken for local cooperatives across the province of Indonesia. The decision-making process is still analyzed manually, so that sometimes the decisions taken are also less appropriate, effective and efficient. The second problem is the lack of monitoring data cooperative process province that is too much, making it difficult for the analysis of dynamic information to be useful. Therefore the authors want to fix the system that runs by using digital dashboard management system supported by the modeling of system dynamics. In addition, the author also did the design of a system that can support the system. Design of this system is aimed to ease the experts, head, and the government to decide (DSS - Decision Support System) accurately effectively and efficiently, because in the system are raised alternative simulation in a description of the decision to be taken and the result from the decision. The system is expected to be designed dan simulated can ease and expedite the decision making. The design of dynamic digital dashboard management conducted by method of OOAD (Objects Oriented Analysis and Design) complete with UML notation.

Decision problems in management of construction projects

NASA Astrophysics Data System (ADS)

Szafranko, E.

2017-10-01

In a construction business, one must oftentimes make decisions during all stages of a building process, from planning a new construction project through its execution to the stage of using a ready structure. As a rule, the decision making process is made more complicated due to certain conditions specific for civil engineering. With such diverse decision situations, it is recommended to apply various decision making support methods. Both, literature and hands-on experience suggest several methods based on analytical and computational procedures, some less and some more complex. This article presents the methods which can be helpful in supporting decision making processes in the management of civil engineering projects. These are multi-criteria methods, such as MCE, AHP or indicator methods. Because the methods have different advantages and disadvantages, whereas decision situations have their own specific nature, a brief summary of the methods alongside some recommendations regarding their practical applications has been given at the end of the paper. The main aim of this article is to review the methods of decision support and their analysis for possible use in the construction industry.

Decision making by relatives about brain death organ donation: an integrative review.

PubMed

de Groot, Jack; Vernooij-Dassen, Myrra; Hoedemaekers, Cornelia; Hoitsma, Andries; Smeets, Wim; van Leeuwen, Evert

2012-06-27

Deciding about the organ donation of one's brain-dead beloved often occurs in an unexpected and delicate situation. We explored the decision making of the relatives of potential brain-dead donors, its evaluation, and the factors influencing decision making. We used the integrative review method. Our search included 10 databases. Inclusion criteria were presence of the donation request or the subsequent decision process. Three authors independently assessed the eligibility of identified articles. Content analysis of 70 included articles led to three themes: decision, evaluation, and support. We extracted results and recommendations concerning these three themes. The timing of the request and understandable information influence the decision. The relatives evaluate their decision differently: in case of refusal, approximately one third regret their decision, and in case of consent, approximately one tenth mention regret. The relatives are often ambivalent about their values (protection, altruism, and respect) and the deceased's wishes, not wanting additional suffering either for their beloved or for themselves. Support is mainly focused on increasing consent rates and less on satisfaction with the decision. Evaluation of decision making by the relatives of potential brain-dead donors reveals possibilities for improving the decision process. Special skills of the requester, attention to the circumstances, and unconditional support for the relatives might prevent the relatives' regret about refusal and unnecessary loss of organs. We hypothesize that support in exploring the relatives' values and the deceased's wishes can lead to stable decisions. This hypothesis deserves further investigation.

How Socio-Emotional Support Affects Post-Compulsory Education Decisions in Rural China

ERIC Educational Resources Information Center

Yao, Haogen

2017-01-01

This study develops a sequential mixed model of Delphi-Propensity Score Matching to discuss how an NGO's socio-emotional support affects the decisions of dropout, work, and two types of upper secondary schooling in rural China. Data were collected from 6,298 students in 2012 after a subgroup of them were treated. The analysis shows that…

Environmental Scanning in Support of Planning and Decision Making: Case Studies at Selected Institutions of Higher Education. AIR 1990 Annual Forum Paper.

ERIC Educational Resources Information Center

Pritchett, Mark S.

This paper presents a comprehensive case analysis of formal environmental scanning processes in three different institutions of higher education. The study focuses on how environmental scanning activities are organized and used to support institutional planning and decision-making. Special emphasis is placed on describing how environmental…

Searching for Tools versus Asking for Answers: A Taxonomy of Counselee Behavioral Styles during Career Counseling.

ERIC Educational Resources Information Center

Sagiv, Lilach

1999-01-01

A taxonomy of decision behavior styles (independence/dependence, active/passive, insightful/not) tested with 372 career counseling clients was supported by similar structure analysis and confirmatory factor analysis. Counselors were more likely to be satisfied with decisions of clients they perceived to be insightful. (SK)

A proposal for a computer-based framework of support for public health in the management of biological incidents: the Czech Republic experience.

PubMed

Bures, Vladimír; Otcenásková, Tereza; Cech, Pavel; Antos, Karel

2012-11-01

Biological incidents jeopardising public health require decision-making that consists of one dominant feature: complexity. Therefore, public health decision-makers necessitate appropriate support. Based on the analogy with business intelligence (BI) principles, the contextual analysis of the environment and available data resources, and conceptual modelling within systems and knowledge engineering, this paper proposes a general framework for computer-based decision support in the case of a biological incident. At the outset, the analysis of potential inputs to the framework is conducted and several resources such as demographic information, strategic documents, environmental characteristics, agent descriptors and surveillance systems are considered. Consequently, three prototypes were developed, tested and evaluated by a group of experts. Their selection was based on the overall framework scheme. Subsequently, an ontology prototype linked with an inference engine, multi-agent-based model focusing on the simulation of an environment, and expert-system prototypes were created. All prototypes proved to be utilisable support tools for decision-making in the field of public health. Nevertheless, the research revealed further issues and challenges that might be investigated by both public health focused researchers and practitioners.

Education and parental involvement in decision-making about newborn screening: understanding goals to clarify content.

PubMed

Potter, Beth K; Etchegary, Holly; Nicholls, Stuart G; Wilson, Brenda J; Craigie, Samantha M; Araia, Makda H

2015-06-01

A challenge in designing effective education for parents about newborn screening (NBS) has been uncertainty about appropriate content. Arguing that the goals of education may be usefully tied to parental decision-making, we sought to: (1) explore how different ways of implementing NBS differ in their approaches to parental engagement in decision-making; (2) map the potential goals of education onto these "implementation models"; and (3) consider the content that may be needed to support these goals. The resulting conceptual framework supports the availability of comprehensive information about NBS for parents, irrespective of the model of implementation. This is largely because we argue that meeting parental expectations and preferences for communication is an important goal regardless of whether or notparents are actively involved in making a decision. Our analysis supports a flexible approach, in which some educational messages are emphasized as important for all parents to understand while others are made available depending on parents' preferences. We have begun to define the content of NBS education for parents needed to support specific goals. Further research and discussion is important to determine the most appropriate strategies for delivering the tailored approach to education that emerged from our analysis.

Using Cognitive Work Analysis to Fit Decision Support Tools to Nurse Managers’ Work Flow

PubMed Central

Brewer, Barbara B.; Logue, Melanie D.; Gephart, Sheila; Verran, Joyce A.

2011-01-01

Purpose To better understand the environmental constraints on nurse managers that impact their need for and use of decision support tools, we conducted a Cognitive Work Analysis (CWA). A complete CWA includes system analyses at five levels: work domain, decision-making procedures, decision-making strategies, social organization/collaboration, and worker skill level. Here we describe the results of the Work Domain Analysis (WDA) portion in detail then integrate the WDA with other portions of the CWA, reported previously, to generate a more complete picture of the nurse manager’s work domain. Methods Data for the WDA were obtained from semi-structured interviews with nurse managers, division directors, CNOs, and other managers (n = 20) on 10 patient care units in 3 Arizona hospitals. The WDA described the nurse manager’s environment in terms of the constraints it imposes on the nurse manager’s ability to achieve targeted outcomes through organizational goals and priorities, functions, processes, as well as work objects and resources (e.g., people, equipment, technology, and data). Constraints were identified and summarized through qualitative thematic analysis. Results The results highlight the competing priorities, and external and internal constraints that today’s nurse managers must satisfy as they try to improve quality and safety outcomes on their units. Nurse managers receive a great deal of data, much in electronic format. Although dashboards were perceived as helpful because they integrated some data elements, no decision support tools were available to help nurse managers with planning or answering “what if” questions. The results suggest both the need for additional decision support to manage the growing complexity of the environment, and the constraints the environment places on the design of that technology if it is to be effective. Limitations of the study include the small homogenous sample and the reliance on interview data targeting safety and quality. PMID:21862397

Using Cognitive Work Analysis to fit decision support tools to nurse managers' work flow.

PubMed

Effken, Judith A; Brewer, Barbara B; Logue, Melanie D; Gephart, Sheila M; Verran, Joyce A

2011-10-01

To better understand the environmental constraints on nurse managers that impact their need for and use of decision support tools, we conducted a Cognitive Work Analysis (CWA). A complete CWA includes system analyses at five levels: work domain, decision-making procedures, decision-making strategies, social organization/collaboration, and worker skill level. Here we describe the results of the Work Domain Analysis (WDA) portion in detail then integrate the WDA with other portions of the CWA, reported previously, to generate a more complete picture of the nurse manager's work domain. Data for the WDA were obtained from semi-structured interviews with nurse managers, division directors, CNOs, and other managers (n = 20) on 10 patient care units in three Arizona hospitals. The WDA described the nurse manager's environment in terms of the constraints it imposes on the nurse manager's ability to achieve targeted outcomes through organizational goals and priorities, functions, processes, as well as work objects and resources (e.g., people, equipment, technology, and data). Constraints were identified and summarized through qualitative thematic analysis. The results highlight the competing priorities, and external and internal constraints that today's nurse managers must satisfy as they try to improve quality and safety outcomes on their units. Nurse managers receive a great deal of data, much in electronic format. Although dashboards were perceived as helpful because they integrated some data elements, no decision support tools were available to help nurse managers with planning or answering "what if" questions. The results suggest both the need for additional decision support to manage the growing complexity of the environment, and the constraints the environment places on the design of that technology if it is to be effective. Limitations of the study include the small homogeneous sample and the reliance on interview data targeting safety and quality. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Systems Analysis - a new paradigm and decision support tools for the water framework directive

NASA Astrophysics Data System (ADS)

Bruen, M.

2008-05-01

In the early days of Systems Analysis the focus was on providing tools for optimisation, modelling and simulation for use by experts. Now there is a recognition of the need to develop and disseminate tools to assist in making decisions, negotiating compromises and communicating preferences that can easily be used by stakeholders without the need for specialist training. The Water Framework Directive (WFD) requires public participation and thus provides a strong incentive for progress in this direction. This paper places the new paradigm in the context of the classical one and discusses some of the new approaches which can be used in the implementation of the WFD. These include multi-criteria decision support methods suitable for environmental problems, adaptive management, cognitive mapping, social learning and cooperative design and group decision-making. Concordance methods (such as ELECTRE) and the Analytical Hierarchy Process (AHP) are identified as multi-criteria methods that can be readily integrated into Decision Support Systems (DSS) that deal with complex environmental issues with very many criteria, some of which are qualitative. The expanding use of the new paradigm provides an opportunity to observe and learn from the interaction of stakeholders with the new technology and to assess its effectiveness.

An Overview of R in Health Decision Sciences.

PubMed

Jalal, Hawre; Pechlivanoglou, Petros; Krijkamp, Eline; Alarid-Escudero, Fernando; Enns, Eva; Hunink, M G Myriam

2017-10-01

As the complexity of health decision science applications increases, high-level programming languages are increasingly adopted for statistical analyses and numerical computations. These programming languages facilitate sophisticated modeling, model documentation, and analysis reproducibility. Among the high-level programming languages, the statistical programming framework R is gaining increased recognition. R is freely available, cross-platform compatible, and open source. A large community of users who have generated an extensive collection of well-documented packages and functions supports it. These functions facilitate applications of health decision science methodology as well as the visualization and communication of results. Although R's popularity is increasing among health decision scientists, methodological extensions of R in the field of decision analysis remain isolated. The purpose of this article is to provide an overview of existing R functionality that is applicable to the various stages of decision analysis, including model design, input parameter estimation, and analysis of model outputs.

Comparison of risk-based decision-support systems for brownfield site rehabilitation: DESYRE and SADA applied to a Romanian case study.

PubMed

Stezar, I C; Pizzol, L; Critto, A; Ozunu, A; Marcomini, A

2013-12-15

Brownfield rehabilitation is an essential step for sustainable land-use planning and management in the European Union. In brownfield regeneration processes, the legacy contamination plays a significant role, firstly because of the persistent contaminants in soil or groundwater which extends the existing hazards and risks well into the future; and secondly, problems from historical contamination are often more difficult to manage than contamination caused by new activities. Due to the complexity associated with the management of brownfield site rehabilitation, Decision Support Systems (DSSs) have been developed to support problem holders and stakeholders in the decision-making process encompassing all phases of the rehabilitation. This paper presents a comparative study between two DSSs, namely SADA (Spatial Analysis and Decision Assistance) and DESYRE (Decision Support System for the Requalification of Contaminated Sites), with the main objective of showing the benefits of using DSSs to introduce and process data and then to disseminate results to different stakeholders involved in the decision-making process. For this purpose, a former car manufacturing plant located in the Brasov area, Central Romania, contaminated chiefly by heavy metals and total petroleum hydrocarbons, has been selected as a case study to apply the two examined DSSs. Major results presented here concern the analysis of the functionalities of the two DSSs in order to identify similarities, differences and complementarities and, thus, to provide an indication of the most suitable integration options. Copyright © 2013 Elsevier Ltd. All rights reserved.

Integrating conflict analysis and consensus reaching in a decision support system for water resource management.

PubMed

Giordano, R; Passarella, G; Uricchio, V F; Vurro, M

2007-07-01

The importance of shared decision processes in water management derives from the awareness of the inadequacy of traditional--i.e. engineering--approaches in dealing with complex and ill-structured problems. It is becoming increasingly obvious that traditional problem solving and decision support techniques, based on optimisation and factual knowledge, have to be combined with stakeholder based policy design and implementation. The aim of our research is the definition of an integrated decision support system for consensus achievement (IDSS-C) able to support a participative decision-making process in all its phases: problem definition and structuring, identification of the possible alternatives, formulation of participants' judgments, and consensus achievement. Furthermore, the IDSS-C aims at structuring, i.e. systematising the knowledge which has emerged during the participative process in order to make it comprehensible for the decision-makers and functional for the decision process. Problem structuring methods (PSM) and multi-group evaluation methods (MEM) have been integrated in the IDSS-C. PSM are used to support the stakeholders in providing their perspective of the problem and to elicit their interests and preferences, while MEM are used to define not only the degree of consensus for each alternative, highlighting those where the agreement is high, but also the consensus label for each alternative and the behaviour of individuals during the participative decision-making. The IDSS-C is applied experimentally to a decision process regarding the use of treated wastewater for agricultural irrigation in the Apulia Region (southern Italy).

An Intelligent Polar Cyberinfrastrucuture to Support Spatiotemporal Decision Making

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Web-based health services and clinical decision support.

PubMed

Jegelevicius, Darius; Marozas, Vaidotas; Lukosevicius, Arunas; Patasius, Martynas

2004-01-01

The purpose of this study was the development of a Web-based e-health service for comprehensive assistance and clinical decision support. The service structure consists of a Web server, a PHP-based Web interface linked to a clinical SQL database, Java applets for interactive manipulation and visualization of signals and a Matlab server linked with signal and data processing algorithms implemented by Matlab programs. The service ensures diagnostic signal- and image analysis-sbased clinical decision support. By using the discussed methodology, a pilot service for pathology specialists for automatic calculation of the proliferation index has been developed. Physicians use a simple Web interface for uploading the pictures under investigation to the server; subsequently a Java applet interface is used for outlining the region of interest and, after processing on the server, the requested proliferation index value is calculated. There is also an "expert corner", where experts can submit their index estimates and comments on particular images, which is especially important for system developers. These expert evaluations are used for optimization and verification of automatic analysis algorithms. Decision support trials have been conducted for ECG and ophthalmology ultrasonic investigations of intraocular tumor differentiation. Data mining algorithms have been applied and decision support trees constructed. These services are under implementation by a Web-based system too. The study has shown that the Web-based structure ensures more effective, flexible and accessible services compared with standalone programs and is very convenient for biomedical engineers and physicians, especially in the development phase.

Distributed Cognition in Cancer Treatment Decision Making: An Application of the DECIDE Decision-Making Styles Typology.

PubMed

Krieger, Janice L; Krok-Schoen, Jessica L; Dailey, Phokeng M; Palmer-Wackerly, Angela L; Schoenberg, Nancy; Paskett, Electra D; Dignan, Mark

2017-07-01

Distributed cognition occurs when cognitive and affective schemas are shared between two or more people during interpersonal discussion. Although extant research focuses on distributed cognition in decision making between health care providers and patients, studies show that caregivers are also highly influential in the treatment decisions of patients. However, there are little empirical data describing how and when families exert influence. The current article addresses this gap by examining decisional support in the context of cancer randomized clinical trial (RCT) decision making. Data are drawn from in-depth interviews with rural, Appalachian cancer patients ( N = 46). Analysis of transcript data yielded empirical support for four distinct models of health decision making. The implications of these findings for developing interventions to improve the quality of treatment decision making and overall well-being are discussed.

Web-Based Versus Usual Care and Other Formats of Decision Aids to Support Prostate Cancer Screening Decisions: Systematic Review and Meta-Analysis.

PubMed

Baptista, Sofia; Teles Sampaio, Elvira; Heleno, Bruno; Azevedo, Luís Filipe; Martins, Carlos

2018-06-26

Prostate cancer is a leading cause of cancer among men. Because screening for prostate cancer is a controversial issue, many experts in the field have defended the use of shared decision making using validated decision aids, which can be presented in different formats (eg, written, multimedia, Web). Recent studies have concluded that decision aids improve knowledge and reduce decisional conflict. This meta-analysis aimed to investigate the impact of using Web-based decision aids to support men's prostate cancer screening decisions in comparison with usual care and other formats of decision aids. We searched PubMed, CINAHL, PsycINFO, and Cochrane CENTRAL databases up to November 2016. This search identified randomized controlled trials, which assessed Web-based decision aids for men making a prostate cancer screening decision and reported quality of decision-making outcomes. Two reviewers independently screened citations for inclusion criteria, extracted data, and assessed risk of bias. Using a random-effects model, meta-analyses were conducted pooling results using mean differences (MD), standardized mean differences (SMD), and relative risks (RR). Of 2406 unique citations, 7 randomized controlled trials met the inclusion criteria. For risk of bias, selective outcome reporting and participant/personnel blinding were mostly rated as unclear due to inadequate reporting. Based on seven items, two studies had high risk of bias for one item. Compared to usual care, Web-based decision aids increased knowledge (SMD 0.46; 95% CI 0.18-0.75), reduced decisional conflict (MD -7.07%; 95% CI -9.44 to -4.71), and reduced the practitioner control role in the decision-making process (RR 0.50; 95% CI 0.31-0.81). Web-based decision aids compared to printed decision aids yielded no differences in knowledge, decisional conflict, and participation in decision or screening behaviors. Compared to video decision aids, Web-based decision aids showed lower average knowledge scores (SMD -0.50; 95% CI -0.88 to -0.12) and a slight decrease in prostate-specific antigen screening (RR 1.12; 95% CI 1.01-1.25). According to this analysis, Web-based decision aids performed similarly to alternative formats (ie, printed, video) for the assessed decision-quality outcomes. The low cost, readiness, availability, and anonymity of the Web can be an advantage for increasing access to decision aids that support prostate cancer screening decisions among men. ©Sofia Baptista, Elvira Teles Sampaio, Bruno Heleno, Luís Filipe Azevedo, Carlos Martins. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 26.06.2018.

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

PubMed Central

2010-01-01

Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research. PMID:20920289

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support.

PubMed

Gibert, Karina; García-Alonso, Carlos; Salvador-Carulla, Luis

2010-09-30

Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.

Harnessing ecosystem models and multi-criteria decision analysis for the support of forest management.

PubMed

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Harnessing Ecosystem Models and Multi-Criteria Decision Analysis for the Support of Forest Management

NASA Astrophysics Data System (ADS)

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Advancements in Risk-Informed Performance-Based Asset Management for Commercial Nuclear Power Plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liming, James K.; Ravindra, Mayasandra K.

2006-07-01

Over the past several years, ABSG Consulting Inc. (ABS Consulting) and the South Texas Project Nuclear Operating Company (STPNOC) have developed a decision support process and associated software for risk-informed, performance-based asset management (RIPBAM) of nuclear power plant facilities. RIPBAM applies probabilistic risk assessment (PRA) tools and techniques in the realm of plant physical and financial asset management. The RIPBAM process applies a tiered set of models and supporting performance measures (or metrics) that can ultimately be applied to support decisions affecting the allocation and management of plant resources (e.g., funding, staffing, scheduling, etc.). In general, the ultimate goal ofmore » the RIPBAM process is to continually support decision-making to maximize a facility's net present value (NPV) and long-term profitability for its owners. While the initial applications of RIPBAM have been for nuclear power stations, the methodology can easily be adapted to other types of power station or complex facility decision-making support. RIPBAM can also be designed to focus on performance metrics other than NPV and profitability (e.g., mission reliability, operational availability, probability of mission success per dollar invested, etc.). Recent advancements in the RIPBAM process focus on expanding the scope of previous RIPBAM applications to include not only operations, maintenance, and safety issues, but also broader risk perception components affecting plant owner (stockholder), operator, and regulator biases. Conceptually, RIPBAM is a comprehensive risk-informed cash flow model for decision support. It originated as a tool to help manage plant refueling outage scheduling, and was later expanded to include the full spectrum of operations and maintenance decision support. However, it differs from conventional business modeling tools in that it employs a systems engineering approach with broadly based probabilistic analysis of organizational 'value streams'. The scope of value stream inclusion in the process can be established by the user, but in its broadest applications, RIPBAM can be used to address how risk perceptions of plant owners and regulators are impacted by plant performance. Plant staffs can expand and refine RIPBAM models scope via a phased program of activities over time. This paper shows how the multi-metric uncertainty analysis feature of RIPBAM can apply a wide spectrum of decision-influencing factors to support decisions designed to maximize the probability of achieving, maintaining, and improving upon plant goals and objectives. In this paper, the authors show how this approach can be extremely valuable to plant owners and operators in supporting plant value-impacting decision-making processes. (authors)« less

Identifying the decision to be supported: a review of papers from environmental modelling and software

USGS Publications Warehouse

Sojda, Richard S.; Chen, Serena H.; El Sawah, Sondoss; Guillaume, Joseph H.A.; Jakeman, A.J.; Lautenbach, Sven; McIntosh, Brian S.; Rizzoli, A.E.; Seppelt, Ralf; Struss, Peter; Voinov, Alexey; Volk, Martin

2012-01-01

Two of the basic tenets of decision support system efforts are to help identify and structure the decisions to be supported, and to then provide analysis in how those decisions might be best made. One example from wetland management would be that wildlife biologists must decide when to draw down water levels to optimise aquatic invertebrates as food for breeding ducks. Once such a decision is identified, a system or tool to help them make that decision in the face of current and projected climate conditions could be developed. We examined a random sample of 100 papers published from 2001-2011 in Environmental Modelling and Software that used the phrase “decision support system” or “decision support tool”, and which are characteristic of different sectors. In our review, 41% of the systems and tools related to the water resources sector, 34% were related to agriculture, and 22% to the conservation of fish, wildlife, and protected area management. Only 60% of the papers were deemed to be reporting on DSS. This was based on the papers reviewed not having directly identified a specific decision to be supported. We also report on the techniques that were used to identify the decisions, such as formal survey, focus group, expert opinion, or sole judgment of the author(s). The primary underlying modelling system, e.g., expert system, agent based model, Bayesian belief network, geographical information system (GIS), and the like was categorised next. Finally, since decision support typically should target some aspect of unstructured decisions, we subjectively determined to what degree this was the case. In only 23% of the papers reviewed, did the system appear to tackle unstructured decisions. This knowledge should be useful in helping workers in the field develop more effective systems and tools, especially by being exposed to the approaches in different, but related, disciplines. We propose that a standard blueprint for reporting on DSS be developed for consideration by journal editors to aid them in filtering papers that use the term, “decision support”.

Developing a Value Framework: The Need to Reflect the Opportunity Costs of Funding Decisions.

PubMed

Sculpher, Mark; Claxton, Karl; Pearson, Steven D

2017-02-01

A growing number of health care systems internationally use formal economic evaluation methods to support health care funding decisions. Recently, a range of organizations have been advocating forms of analysis that have been termed "value frameworks." There has also been a push for analytical methods to reflect a fuller range of benefits of interventions through multicriteria decision analysis. A key principle that is invariably neglected in current and proposed frameworks is the need to reflect evidence on the opportunity costs that health systems face when making funding decisions. The mechanisms by which opportunity costs are realized vary depending on the system's financial arrangements, but they always mean that a decision to fund a specific intervention for a particular patient group has the potential to impose costs on others in terms of forgone benefits. These opportunity costs are rarely explicitly reflected in analysis to support decisions, but recent developments to quantify benefits forgone make more appropriate analyses feasible. Opportunity costs also need to be reflected in decisions if a broader range of attributes of benefit is considered, and opportunity costs are a key consideration in determining the appropriate level of total expenditure in a system. The principles by which opportunity costs can be reflected in analysis are illustrated in this article by using the example of the proposed methods for value-based pricing in the United Kingdom. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Use of multicriteria decision analysis to address conservation conflicts.

PubMed

Davies, A L; Bryce, R; Redpath, S M

2013-10-01

Conservation conflicts are increasing on a global scale and instruments for reconciling competing interests are urgently needed. Multicriteria decision analysis (MCDA) is a structured, decision-support process that can facilitate dialogue between groups with differing interests and incorporate human and environmental dimensions of conflict. MCDA is a structured and transparent method of breaking down complex problems and incorporating multiple objectives. The value of this process for addressing major challenges in conservation conflict management is that MCDA helps in setting realistic goals; entails a transparent decision-making process; and addresses mistrust, differing world views, cross-scale issues, patchy or contested information, and inflexible legislative tools. Overall we believe MCDA provides a valuable decision-support tool, particularly for increasing awareness of the effects of particular values and choices for working toward negotiated compromise, although an awareness of the effect of methodological choices and the limitations of the method is vital before applying it in conflict situations. © 2013 Society for Conservation Biology.

Decision Modeling Framework to Minimize Arrival Delays from Ground Delay Programs

NASA Astrophysics Data System (ADS)

Mohleji, Nandita

Convective weather and other constraints create uncertainty in air transportation, leading to costly delays. A Ground Delay Program (GDP) is a strategy to mitigate these effects. Systematic decision support can increase GDP efficacy, reduce delays, and minimize direct operating costs. In this study, a decision analysis (DA) model is constructed by combining a decision tree and Bayesian belief network. Through a study of three New York region airports, the DA model demonstrates that larger GDP scopes that include more flights in the program, along with longer lead times that provide stakeholders greater notice of a pending program, trigger the fewest average arrival delays. These findings are demonstrated to result in a savings of up to $1,850 per flight. Furthermore, when convective weather is predicted, forecast weather confidences remain the same level or greater at least 70% of the time, supporting more strategic decision making. The DA model thus enables quantification of uncertainties and insights on causal relationships, providing support for future GDP decisions.

Application of GIS in foreign direct investment decision support system

NASA Astrophysics Data System (ADS)

Zhou, Jianlan; Sun, Koumei

2007-06-01

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

Modeling Opponents in Adversarial Risk Analysis.

PubMed

Rios Insua, David; Banks, David; Rios, Jesus

2016-04-01

Adversarial risk analysis has been introduced as a framework to deal with risks derived from intentional actions of adversaries. The analysis supports one of the decisionmakers, who must forecast the actions of the other agents. Typically, this forecast must take account of random consequences resulting from the set of selected actions. The solution requires one to model the behavior of the opponents, which entails strategic thinking. The supported agent may face different kinds of opponents, who may use different rationality paradigms, for example, the opponent may behave randomly, or seek a Nash equilibrium, or perform level-k thinking, or use mirroring, or employ prospect theory, among many other possibilities. We describe the appropriate analysis for these situations, and also show how to model the uncertainty about the rationality paradigm used by the opponent through a Bayesian model averaging approach, enabling a fully decision-theoretic solution. We also show how as we observe an opponent's decision behavior, this approach allows learning about the validity of each of the rationality models used to predict his decision by computing the models' (posterior) probabilities, which can be understood as a measure of their validity. We focus on simultaneous decision making by two agents. © 2015 Society for Risk Analysis.

Modeling as a Decision-Making Process

ERIC Educational Resources Information Center

Bleiler-Baxter, Sarah K.; Stephens, D. Christopher; Baxter, Wesley A.; Barlow, Angela T.

2017-01-01

The goal in this article is to support teachers in better understanding what it means to model with mathematics by focusing on three key decision-making processes: Simplification, Relationship Mapping, and Situation Analysis. The authors use the Theme Park task to help teachers develop a vision of how students engage in these three decision-making…

Benefit-Risk Analysis for Decision-Making: An Approach.

PubMed

Raju, G K; Gurumurthi, K; Domike, R

2016-12-01

The analysis of benefit and risk is an important aspect of decision-making throughout the drug lifecycle. In this work, the use of a benefit-risk analysis approach to support decision-making was explored. The proposed approach builds on the qualitative US Food and Drug Administration (FDA) approach to include a more explicit analysis based on international standards and guidance that enables aggregation and comparison of benefit and risk on a common basis and a lifecycle focus. The approach is demonstrated on six decisions over the lifecycle (e.g., accelerated approval, withdrawal, and traditional approval) using two case studies: natalizumab for multiple sclerosis (MS) and bedaquiline for multidrug-resistant tuberculosis (MDR-TB). © 2016 American Society for Clinical Pharmacology and Therapeutics.

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

PubMed

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

2014-07-01

Although computerized decision support for imaging is often recommended for optimizing computed tomography (CT) use, no studies have evaluated emergency physicians' (EPs') preferences regarding computerized decision support in the emergency department (ED). In this needs assessment, the authors sought to determine if EPs view overutilization as a problem, if they want decision support, and if so, the kinds of support they prefer. A 42-item, Web-based survey of EPs was developed and used to measure EPs' attitudes, preferences, and knowledge. Key contacts at local EDs sent letters describing the study to their physicians. Exploratory principal components analysis (PCA) was used to determine the underlying factor structure of multi-item scales, Cronbach's alpha was used to measure internal consistency of items on a scale, Spearman correlations were used to describe bivariate associations, and multivariable linear regression analysis was used to identify variables independently associated with physician interest in decision support. Of 235 surveys sent, 155 (66%) EPs responded. Five factors emerged from the PCA. EPs felt that: 1) CT overutilization is a problem in the ED (α = 0.75); 2) a patient's cumulative CT study count affects decisions of whether and what type of imaging study to order only some of the time (α = 0.75); 3) knowledge that a patient has had prior CT imaging for the same indication makes EPs less likely to order a CT (α = 0.42); 4) concerns about malpractice, patient satisfaction, or insistence on CTs affect CT ordering decisions (α = 0.62); and 5) EPs want decision support before ordering CTs (α = 0.85). Performance on knowledge questions was poor, with only 18% to 39% correctly responding to each of the three multiple-choice items about effective radiation doses of chest radiograph and single-pass abdominopelvic CT, as well as estimated increased risk of cancer from a 10-mSv exposure. Although EPs wanted information on patients' cumulative exposures, they feel inadequately familiar with this information to make use of it clinically. If provided with patients' cumulative radiation exposures from CT, 87% of EPs said that they would use this information to discuss imaging options with their patients. In the multiple regression model, which included all variables associated with interest in decision support at p < 0.10 in bivariate tests, items independently associated with EPs' greater interest in all types of decision support proposed included lower total knowledge scores, greater frequency that cumulative CT study count affects EP's decision to order CTs, and greater agreement that overutilization of CT is a problem and that awareness of multiple prior CTs for a given indication affects CT ordering decisions. Emergency physicians view overutilization of CT scans as a problem with potential for improvement in the ED and would like to have more information to discuss risks with their patients. EPs are interested in all types of imaging decision support proposed to help optimize imaging ordering in the ED and to reduce radiation to their patients. Findings reveal several opportunities that could potentially affect CT utilization. © 2014 by the Society for Academic Emergency Medicine.

Emergency Physicians’ Attitudes and Preferences Regarding Computed Tomography, Radiation Exposure, and Imaging Decision Support

PubMed Central

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

2014-01-01

Objectives Although computerized decision support for imaging is often recommended for optimizing computed tomography (CT) use, no studies have evaluated emergency physicians’ (EPs’) preferences regarding computerized decision support in the emergency department (ED). In this needs assessment, the authors sought to determine if EPs view overutilization as a problem, if they want decision support, and if so, the kinds of support they prefer. Methods A 42-item, Web-based survey of EPs was developed and used to measure EPs’ attitudes, preferences, and knowledge. Key contacts at local EDs sent letters describing the study to their physicians. Exploratory principal components analysis (PCA) was used to determine the underlying factor structure of multi-item scales, Cronbach’s alpha was used to measure internal consistency of items on a scale, Spearman correlations were used to describe bivariate associations, and multivariable linear regression analysis was used to identify variables independently associated with physician interest in decision support. Results Of 235 surveys sent, 155 (66%) EPs responded. Five factors emerged from the PCA. EPs felt that: 1) CT overutilization is a problem in the ED (α = 0.75); 2) a patient’s cumulative CT study count affects decisions of whether and what type of imaging study to order only some of the time (α = 0.75); 3) knowledge that a patient has had prior CT imaging for the same indication makes EPs less likely to order a CT (α = 0.42); 4) concerns about malpractice, patient satisfaction, or insistence on CTs affect CT ordering decisions (α = 0.62); and 5) EPs want decision support before ordering CTs (α = 0.85). Performance on knowledge questions was poor, with only 18% to 39% correctly responding to each of the three multiple-choice items about effective radiation doses of chest radiograph and single-pass abdominopelvic CT, as well as estimated increased risk of cancer from a 10-mSv exposure. Although EPs wanted information on patients’ cumulative exposures, they feel inadequately familiar with this information to make use of it clinically. If provided with patients’ cumulative radiation exposures from CT, 87% of EPs said that they would use this information to discuss imaging options with their patients. In the multiple regression model, which included all variables associated with interest in decision support at p < 0.10 in bivariate tests, items independently associated with EPs’ greater interest in all types of decision support proposed included lower total knowledge scores, greater frequency that cumulative CT study count affects EP’s decision to order CTs, and greater agreement that overutilization of CT is a problem and that awareness of multiple prior CTs for a given indication affects CT ordering decisions. Conclusions Emergency physicians view overutilization of CT scans as a problem with potential for improvement in the ED and would like to have more information to discuss risks with their patients. EPs are interested in all types of imaging decision support proposed to help optimize imaging ordering in the ED and to reduce radiation to their patients. Findings reveal several opportunities that could potentially affect CT utilization. PMID:25125272

Computational Support for Technology- Investment Decisions

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

GET SMARTE: DECISION TOOLS TO REVITALIZE BROWNFIELDS

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is an open-source, web-based, decision-support system for developing and evaluating future use scenarios for potentially contaminated sites (i.e., brownfields). It contains resources and analysis tools...

SADA: Ecological Risk Based Decision Support System for Selective Remediation

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

Spatial decision support system to evaluate crop residue energy potential by anaerobic digestion.

PubMed

Escalante, Humberto; Castro, Liliana; Gauthier-Maradei, Paola; Rodríguez De La Vega, Reynel

2016-11-01

Implementing anaerobic digestion (AD) in energy production from crop residues requires development of decision tools to assess its feasibility and sustainability. A spatial decision support system (SDSS) was constructed to assist decision makers to select appropriate feedstock according to biomethanation potential, identify the most suitable location for biogas facilities, determine optimum plant capacity and supply chain, and evaluate associated risks and costs. SDSS involves a spatially explicit analysis, fuzzy multi-criteria analysis, and statistical and optimization models. The tool was validated on seven crop residues located in Santander, Colombia. For example, fique bagasse generates about 0.21millionm(3)CH4year(-1) (0.329m(3)CH4kg(-1) volatile solids) with a minimum profitable plant of about 2000tonyear(-1) and an internal rate of return of 10.5%. SDSS can be applied to evaluate other biomass resources, availability periods, and co-digestion potential. Copyright © 2016. Published by Elsevier Ltd.

Decision support tool for used oil regeneration technologies assessment and selection.

PubMed

Khelifi, Olfa; Dalla Giovanna, Fabio; Vranes, Sanja; Lodolo, Andrea; Miertus, Stanislav

2006-09-01

Regeneration is the most efficient way of managing used oil. It saves money by preventing costly cleanups and liabilities that are associated with mismanagement of used oil, it helps to protect the environment and it produces a technically renewable resource by enabling an indefinite recycling potential. There are a variety of processes and licensors currently offering ways to deal with used oils. Selecting a regeneration technology for used oil involves "cross-matching" key criteria. Therefore, the first prototype of spent oil regeneration (SPORE), a decision support tool, has been developed to help decision-makers to assess the available technologies and select the preferred used oil regeneration options. The analysis is based on technical, economical and environmental criteria. These criteria are ranked to determine their relative importance for a particular used oil regeneration project. The multi-criteria decision analysis (MCDA) is the core of the SPORE using the PROMETHEE II algorithm.

Behavioral and Organizational Considerations in the Design of Information Systems and Processes for Planning and Decision Support,

DTIC Science & Technology

1981-06-01

analysis and display capability provided by management information systems to include interpretation and aggregation of information and values such as...accomplishment of these) 2. analysis of the issue d) systems analysis and modeling (determination of the structure of the decision situation, the...existingltrtie2) Surveying lsata i situation’ alternatives I altraivDsad Is this alternative -" altrnav acceptable? ANALYSIS o NOYES SHave a sufficient

Image analysis approach for development of a decision support system for detection of malaria parasites in thin blood smear images.

PubMed

Prasad, Keerthana; Winter, Jan; Bhat, Udayakrishna M; Acharya, Raviraja V; Prabhu, Gopalakrishna K

2012-08-01

This paper describes development of a decision support system for diagnosis of malaria using color image analysis. A hematologist has to study around 100 to 300 microscopic views of Giemsa-stained thin blood smear images to detect malaria parasites, evaluate the extent of infection and to identify the species of the parasite. The proposed algorithm picks up the suspicious regions and detects the parasites in images of all the views. The subimages representing all these parasites are put together to form a composite image which can be sent over a communication channel to obtain the opinion of a remote expert for accurate diagnosis and treatment. We demonstrate the use of the proposed technique for use as a decision support system by developing an android application which facilitates the communication with a remote expert for the final confirmation on the decision for treatment of malaria. Our algorithm detects around 96% of the parasites with a false positive rate of 20%. The Spearman correlation r was 0.88 with a confidence interval of 0.838 to 0.923, p<0.0001.

Decision Support System for Coastal Protection Layout Design (DSS4CPD) Using Genetic Algorithm (ga) and Multicriteria Analysis (mca)

NASA Astrophysics Data System (ADS)

Jinchai, Phinai; Chittaladakorn, Suwatana

This research has its objective to develop the decision support system on GIS to be used in the coastal erosion protection management. The developed model in this research is called Decision Support System for Coastal Protection Layout Design (DSS4CPD). It has created both for systematic protection and solution measures to the problem by using Genetic Algorithm (GA) and Multicriteria Analysis (MCA) for finding the coastal structure layout optimal solution. In this research, three types of coastal structures were used as structure alternatives for the layout, which are seawall, breakwater, and groin. The coastal area in Nakornsrithammaraj, Thailand was used as the case study. The studied result has found the appropriate position of coastal structures considering the suitable rock size relied on the wave energy, and the appropriate coastal structure position based on the wave breaking line. Using GA and MCA in DSS4CPD, it found the best layout in this project. This DSS4CPD will be used by the authorized decision makers to find the most suitable erosion problem solution.

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

ERIC Educational Resources Information Center

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…

Application of the principles of evidence-based practice in decision making among senior management in Nova Scotia's addiction services agencies.

PubMed

Murphy, Matthew; MacCarthy, M Jayne; McAllister, Lynda; Gilbert, Robert

2014-12-05

Competency profiles for occupational clusters within Canada's substance abuse workforce (SAW) define the need for skill and knowledge in evidence-based practice (EBP) across all its members. Members of the Senior Management occupational cluster hold ultimate responsibility for decisions made within addiction services agencies and therefore must possess the highest level of proficiency in EBP. The objective of this study was to assess the knowledge of the principles of EBP, and use of the components of the evidence-based decision making (EBDM) process in members of this occupational cluster from selected addiction services agencies in Nova Scotia. A convenience sampling method was used to recruit participants from addiction services agencies. Semi-structured qualitative interviews were conducted with eighteen Senior Management. The interviews were audio-recorded, transcribed verbatim and checked by the participants. Interview transcripts were coded and analyzed for themes using content analysis and assisted by qualitative data analysis software (NVivo 9.0). Data analysis revealed four main themes: 1) Senior Management believe that addictions services agencies are evidence-based; 2) Consensus-based decision making is the norm; 3) Senior Management understand the principles of EBP and; 4) Senior Management do not themselves use all components of the EBDM process when making decisions, oftentimes delegating components of this process to decision support staff. Senior Management possess an understanding of the principles of EBP, however, when making decisions they often delegate components of the EBDM process to decision support staff. Decision support staff are not defined as an occupational cluster in Canada's SAW and have not been ascribed a competency profile. As such, there is no guarantee that this group possesses competency in EBDM. There is a need to advocate for the development of a defined occupational cluster and associated competency profile for this critical group.

School Mapping and Geospatial Analysis of the Schools in Jasra Development Block of India

NASA Astrophysics Data System (ADS)

Agrawal, S.; Gupta, R. D.

2016-06-01

GIS is a collection of tools and techniques that works on the geospatial data and is used in the analysis and decision making. Education is an inherent part of any civil society. Proper educational facilities generate the high quality human resource for any nation. Therefore, government needs an efficient system that can help in analysing the current state of education and its progress. Government also needs a system that can support in decision making and policy framing. GIS can serve the mentioned requirements not only for government but also for the general public. In order to meet the standards of human development, it is necessary for the government and decision makers to have a close watch on the existing education policy and its implementation condition. School mapping plays an important role in this aspect. School mapping consists of building the geospatial database of schools that supports in the infrastructure development, policy analysis and decision making. The present research work is an attempt for supporting Right to Education (RTE) and Sarv Sikha Abhiyaan (SSA) programmes run by Government of India through the use of GIS. School mapping of the study area is performed which is followed by the geospatial analysis. This research work will help in assessing the present status of educational infrastructure in Jasra block of Allahabad district, India.

Decision support for evidence-based integration of disease control: A proof of concept for malaria and schistosomiasis

PubMed Central

Graeden, Ellie; Kerr, Justin; Sorrell, Erin M.; Katz, Rebecca

2018-01-01

Managing infectious disease requires rapid and effective response to support decision making. The decisions are complex and require understanding of the diseases, disease intervention and control measures, and the disease-relevant characteristics of the local community. Though disease modeling frameworks have been developed to address these questions, the complexity of current models presents a significant barrier to community-level decision makers in using the outputs of the most scientifically robust methods to support pragmatic decisions about implementing a public health response effort, even for endemic diseases with which they are already familiar. Here, we describe the development of an application available on the internet, including from mobile devices, with a simple user interface, to support on-the-ground decision-making for integrating disease control programs, given local conditions and practical constraints. The model upon which the tool is built provides predictive analysis for the effectiveness of integration of schistosomiasis and malaria control, two diseases with extensive geographical and epidemiological overlap, and which result in significant morbidity and mortality in affected regions. Working with data from countries across sub-Saharan Africa and the Middle East, we present a proof-of-principle method and corresponding prototype tool to provide guidance on how to optimize integration of vertical disease control programs. This method and tool demonstrate significant progress in effectively translating the best available scientific models to support practical decision making on the ground with the potential to significantly increase the efficacy and cost-effectiveness of disease control. Author summary Designing and implementing effective programs for infectious disease control requires complex decision-making, informed by an understanding of the diseases, the types of disease interventions and control measures available, and the disease-relevant characteristics of the local community. Though disease modeling frameworks have been developed to address these questions and support decision-making, the complexity of current models presents a significant barrier to on-the-ground end users. The picture is further complicated when considering approaches for integration of different disease control programs, where co-infection dynamics, treatment interactions, and other variables must also be taken into account. Here, we describe the development of an application available on the internet with a simple user interface, to support on-the-ground decision-making for integrating disease control, given local conditions and practical constraints. The model upon which the tool is built provides predictive analysis for the effectiveness of integration of schistosomiasis and malaria control, two diseases with extensive geographical and epidemiological overlap. This proof-of-concept method and tool demonstrate significant progress in effectively translating the best available scientific models to support pragmatic decision-making on the ground, with the potential to significantly increase the impact and cost-effectiveness of disease control. PMID:29649260

A methodology and decision support tool for informing state-level bioenergy policymaking: New Jersey biofuels as a case study

NASA Astrophysics Data System (ADS)

Brennan-Tonetta, Margaret

This dissertation seeks to provide key information and a decision support tool that states can use to support long-term goals of fossil fuel displacement and greenhouse gas reductions. The research yields three outcomes: (1) A methodology that allows for a comprehensive and consistent inventory and assessment of bioenergy feedstocks in terms of type, quantity, and energy potential. Development of a standardized methodology for consistent inventorying of biomass resources fosters research and business development of promising technologies that are compatible with the state's biomass resource base. (2) A unique interactive decision support tool that allows for systematic bioenergy analysis and evaluation of policy alternatives through the generation of biomass inventory and energy potential data for a wide variety of feedstocks and applicable technologies, using New Jersey as a case study. Development of a database that can assess the major components of a bioenergy system in one tool allows for easy evaluation of technology, feedstock and policy options. The methodology and decision support tool is applicable to other states and regions (with location specific modifications), thus contributing to the achievement of state and federal goals of renewable energy utilization. (3) Development of policy recommendations based on the results of the decision support tool that will help to guide New Jersey into a sustainable renewable energy future. The database developed in this research represents the first ever assessment of bioenergy potential for New Jersey. It can serve as a foundation for future research and modifications that could increase its power as a more robust policy analysis tool. As such, the current database is not able to perform analysis of tradeoffs across broad policy objectives such as economic development vs. CO2 emissions, or energy independence vs. source reduction of solid waste. Instead, it operates one level below that with comparisons of kWh or GGE generated by different feedstock/technology combinations at the state and county level. Modification of the model to incorporate factors that will enable the analysis of broader energy policy issues as those mentioned above, are recommended for future research efforts.

Decision Trajectories in Dementia Care Networks: Decisions and Related Key Events.

PubMed

Groen-van de Ven, Leontine; Smits, Carolien; Oldewarris, Karen; Span, Marijke; Jukema, Jan; Eefsting, Jan; Vernooij-Dassen, Myrra

2017-10-01

This prospective multiperspective study provides insight into the decision trajectories of people with dementia by studying the decisions made and related key events. This study includes three waves of interviews, conducted between July 2010 and July 2012, with 113 purposefully selected respondents (people with beginning to advanced stages of dementia and their informal and professional caregivers) completed in 12 months (285 interviews). Our multilayered qualitative analysis consists of content analysis, timeline methods, and constant comparison. Four decision themes emerged-managing daily life, arranging support, community living, and preparing for the future. Eight key events delineate the decision trajectories of people with dementia. Decisions and key events differ between people with dementia living alone and living with a caregiver. Our study clarifies that decisions relate not only to the disease but to living with the dementia. Individual differences in decision content and sequence may effect shared decision-making and advance care planning.

Group decision making with the analytic hierarchy process in benefit-risk assessment: a tutorial.

PubMed

Hummel, J Marjan; Bridges, John F P; IJzerman, Maarten J

2014-01-01

The analytic hierarchy process (AHP) has been increasingly applied as a technique for multi-criteria decision analysis in healthcare. The AHP can aid decision makers in selecting the most valuable technology for patients, while taking into account multiple, and even conflicting, decision criteria. This tutorial illustrates the procedural steps of the AHP in supporting group decision making about new healthcare technology, including (1) identifying the decision goal, decision criteria, and alternative healthcare technologies to compare, (2) structuring the decision criteria, (3) judging the value of the alternative technologies on each decision criterion, (4) judging the importance of the decision criteria, (5) calculating group judgments, (6) analyzing the inconsistency in judgments, (7) calculating the overall value of the technologies, and (8) conducting sensitivity analyses. The AHP is illustrated via a hypothetical example, adapted from an empirical AHP analysis on the benefits and risks of tissue regeneration to repair small cartilage lesions in the knee.

Using real options analysis to support strategic management decisions

NASA Astrophysics Data System (ADS)

Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

2013-12-01

Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.

History matching through dynamic decision-making

PubMed Central

Maschio, Célio; Santos, Antonio Alberto; Schiozer, Denis; Rocha, Anderson

2017-01-01

History matching is the process of modifying the uncertain attributes of a reservoir model to reproduce the real reservoir performance. It is a classical reservoir engineering problem and plays an important role in reservoir management since the resulting models are used to support decisions in other tasks such as economic analysis and production strategy. This work introduces a dynamic decision-making optimization framework for history matching problems in which new models are generated based on, and guided by, the dynamic analysis of the data of available solutions. The optimization framework follows a ‘learning-from-data’ approach, and includes two optimizer components that use machine learning techniques, such as unsupervised learning and statistical analysis, to uncover patterns of input attributes that lead to good output responses. These patterns are used to support the decision-making process while generating new, and better, history matched solutions. The proposed framework is applied to a benchmark model (UNISIM-I-H) based on the Namorado field in Brazil. Results show the potential the dynamic decision-making optimization framework has for improving the quality of history matching solutions using a substantial smaller number of simulations when compared with a previous work on the same benchmark. PMID:28582413

Development of a support tool for complex decision-making in the provision of rural maternity care.

PubMed

Hearns, Glen; Klein, Michael C; Trousdale, William; Ulrich, Catherine; Butcher, David; Miewald, Christiana; Lindstrom, Ronald; Eftekhary, Sahba; Rosinski, Jessica; Gómez-Ramírez, Oralia; Procyk, Andrea

2010-02-01

Decisions in the organization of safe and effective rural maternity care are complex, difficult, value laden and fraught with uncertainty, and must often be based on imperfect information. Decision analysis offers tools for addressing these complexities in order to help decision-makers determine the best use of resources and to appreciate the downstream effects of their decisions. To develop a maternity care decision-making tool for the British Columbia Northern Health Authority (NH) for use in low birth volume settings. Based on interviews with community members, providers, recipients and decision-makers, and employing a formal decision analysis approach, we sought to clarify the influences affecting rural maternity care and develop a process to generate a set of value-focused objectives for use in designing and evaluating rural maternity care alternatives. Four low-volume communities with variable resources (with and without on-site births, with or without caesarean section capability) were chosen. Physicians (20), nurses (18), midwives and maternity support service providers (4), local business leaders, economic development officials and elected officials (12), First Nations (women [pregnant and non-pregnant], chiefs and band members) (40), social workers (3), pregnant women (2) and NH decision-makers/administrators (17). We developed a Decision Support Manual to assist with assessing community needs and values, context for decision-making, capacity of the health authority or healthcare providers, identification of key objectives for decision-making, developing alternatives for care, and a process for making trade-offs and balancing multiple objectives. The manual was deemed an effective tool for the purpose by the client, NH. Beyond assisting the decision-making process itself, the methodology provides a transparent communication tool to assist in making difficult decisions. While the manual was specifically intended to deal with rural maternity issues, the NH decision-makers feel the method can be easily adapted to assist decision-making in other contexts in medicine where there are conflicting objectives, values and opinions. Decisions on the location of new facilities or infrastructure, or enhancing or altering services such as surgical or palliative care, would be examples of complex decisions that might benefit from this methodology.

Development of a Support Tool for Complex Decision-Making in the Provision of Rural Maternity Care

PubMed Central

Hearns, Glen; Klein, Michael C.; Trousdale, William; Ulrich, Catherine; Butcher, David; Miewald, Christiana; Lindstrom, Ronald; Eftekhary, Sahba; Rosinski, Jessica; Gómez-Ramírez, Oralia; Procyk, Andrea

2010-01-01

Context: Decisions in the organization of safe and effective rural maternity care are complex, difficult, value laden and fraught with uncertainty, and must often be based on imperfect information. Decision analysis offers tools for addressing these complexities in order to help decision-makers determine the best use of resources and to appreciate the downstream effects of their decisions. Objective: To develop a maternity care decision-making tool for the British Columbia Northern Health Authority (NH) for use in low birth volume settings. Design: Based on interviews with community members, providers, recipients and decision-makers, and employing a formal decision analysis approach, we sought to clarify the influences affecting rural maternity care and develop a process to generate a set of value-focused objectives for use in designing and evaluating rural maternity care alternatives. Setting: Four low-volume communities with variable resources (with and without on-site births, with or without caesarean section capability) were chosen. Participants: Physicians (20), nurses (18), midwives and maternity support service providers (4), local business leaders, economic development officials and elected officials (12), First Nations (women [pregnant and non-pregnant], chiefs and band members) (40), social workers (3), pregnant women (2) and NH decision-makers/administrators (17). Results: We developed a Decision Support Manual to assist with assessing community needs and values, context for decision-making, capacity of the health authority or healthcare providers, identification of key objectives for decision-making, developing alternatives for care, and a process for making trade-offs and balancing multiple objectives. The manual was deemed an effective tool for the purpose by the client, NH. Conclusions: Beyond assisting the decision-making process itself, the methodology provides a transparent communication tool to assist in making difficult decisions. While the manual was specifically intended to deal with rural maternity issues, the NH decision-makers feel the method can be easily adapted to assist decision-making in other contexts in medicine where there are conflicting objectives, values and opinions. Decisions on the location of new facilities or infrastructure, or enhancing or altering services such as surgical or palliative care, would be examples of complex decisions that might benefit from this methodology. PMID:21286270

How stakeholder roles, power, and negotiation impact natural resource policy: A political economy view

USGS Publications Warehouse

Caughlan, L.

2002-01-01

Natural resource management decisions are complicated by multiple property rights, management objectives, and stakeholders with varying degrees of influence over the decision making process. In order to make efficient decisions, managers must incorporate the opinions and values of the involved stakeholders as well as understand the complex institutional constraints and opportunities that influence the decision-making process. Often this type of information is not understood until after a decision has been made, which can result in wasted time and effort.The purpose of my dissertation was to show how institutional frameworks and stakeholder involvement influence the various phases of the resource management decision-making process in a public choice framework. The intent was to assist decision makers and stakeholders by developing a methodology for formally incorporating stakeholders'' objectives and influence into the resource management planning process and to predict the potential success of rent-seeking activity based on stakeholder preferences and level of influence. Concepts from decision analysis, institutional analysis, and public choice economics were used in designing this interdisciplinary framework. The framework was then applied to an actual case study concerning elk and bison management on the National Elk Refuge and Grand Teton National Park near Jackson, Wyoming. The framework allowed for the prediction of the level of support and conflict for all relevant policy decisions, and the identification of each stakeholder''s level of support or opposition for each management decision.

GET SMARTE: DECISION TOOLS TO REVITALIZE COMMUNITIES (MAY 2006)

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is an open-source, web-based, decision-support system for developing and evaluating future use scenarios for potentially contaminated sites (i.e., brownfields). It contains resources and analysis tools...

The Use of Geoprocessing in Educational Research and Decision Support.

ERIC Educational Resources Information Center

Sexton, Porter

1982-01-01

Discusses geoprocessing, a computer mapping technique used by the Portland (Oregon) School District in which geographic analysis and data processing are combined. Several applications for administrative decision-making are discussed, including bus routing and redistricting. (JJD)

Accommodating complexity and human behaviors in decision analysis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Backus, George A.; Siirola, John Daniel; Schoenwald, David Alan

2007-11-01

This is the final report for a LDRD effort to address human behavior in decision support systems. One sister LDRD effort reports the extension of this work to include actual human choices and additional simulation analyses. Another provides the background for this effort and the programmatic directions for future work. This specific effort considered the feasibility of five aspects of model development required for analysis viability. To avoid the use of classified information, healthcare decisions and the system embedding them became the illustrative example for assessment.

Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department: a sociotechnical analysis.

PubMed

Sheehan, Barbara; Nigrovic, Lise E; Dayan, Peter S; Kuppermann, Nathan; Ballard, Dustin W; Alessandrini, Evaline; Bajaj, Lalit; Goldberg, Howard; Hoffman, Jeffrey; Offerman, Steven R; Mark, Dustin G; Swietlik, Marguerite; Tham, Eric; Tzimenatos, Leah; Vinson, David R; Jones, Grant S; Bakken, Suzanne

2013-10-01

Integration of clinical decision support services (CDSS) into electronic health records (EHRs) may be integral to widespread dissemination and use of clinical prediction rules in the emergency department (ED). However, the best way to design such services to maximize their usefulness in such a complex setting is poorly understood. We conducted a multi-site cross-sectional qualitative study whose aim was to describe the sociotechnical environment in the ED to inform the design of a CDSS intervention to implement the Pediatric Emergency Care Applied Research Network (PECARN) clinical prediction rules for children with minor blunt head trauma. Informed by a sociotechnical model consisting of eight dimensions, we conducted focus groups, individual interviews and workflow observations in 11 EDs, of which 5 were located in academic medical centers and 6 were in community hospitals. A total of 126 ED clinicians, information technology specialists, and administrators participated. We clustered data into 19 categories of sociotechnical factors through a process of thematic analysis and subsequently organized the categories into a sociotechnical matrix consisting of three high-level sociotechnical dimensions (workflow and communication, organizational factors, human factors) and three themes (interdisciplinary assessment processes, clinical practices related to prediction rules, EHR as a decision support tool). Design challenges that emerged from the analysis included the need to use structured data fields to support data capture and re-use while maintaining efficient care processes, supporting interdisciplinary communication, and facilitating family-clinician interaction for decision-making. Copyright © 2013 Elsevier Inc. All rights reserved.

A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.

PubMed

Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe

2011-05-30

Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.

Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.

PubMed

Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E

2012-01-01

In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

Cost-effectiveness and value of information analysis of nutritional support for preventing pressure ulcers in high-risk patients: implement now, research later.

PubMed

Tuffaha, Haitham W; Roberts, Shelley; Chaboyer, Wendy; Gordon, Louisa G; Scuffham, Paul A

2015-04-01

Pressure ulcers are a major cause of mortality, morbidity, and increased healthcare cost. Nutritional support may reduce the incidence of pressure ulcers in hospitalised patients who are at risk of pressure ulcer and malnutrition. To evaluate the cost-effectiveness of nutritional support in preventing pressure ulcers in high-risk hospitalised patients, and to assess the value of further research to inform the decision to implement this intervention using value of information analysis (VOI). The analysis was from the perspective of Queensland Health, Australia using a decision model with evidence derived from a systematic review and meta-analysis. Resources were valued using 2014 prices and the time horizon of the analysis was one year. Monte Carlo simulation was used to estimate net monetary benefits (NB) and to calculate VOI measures. Compared with standard hospital diet, nutritional support was cost saving at AU$425 per patient, and more effective with an average 0.005 quality-adjusted life years (QALY) gained. At a willingness-to-pay of AU$50,000 per QALY, the incremental NB was AU$675 per patient, with a probability of 87 % that nutritional support is cost-effective. The expected value of perfect information was AU$5 million and the expected value of perfect parameter information was highest for the relative risk of developing a pressure ulcer at AU$2.5 million. For a future trial investigating the relative effectiveness of the interventions, the expected net benefit of research would be maximised at AU$100,000 with 1,200 patients in each arm if nutritional support was perfectly implemented. The opportunity cost of withholding the decision to implement the intervention until the results of the future study are available would be AU$14 million. Nutritional support is cost-effective in preventing pressure ulcers in high-risk hospitalised patients compared with standard diet. Future research to reduce decision uncertainty is worthwhile; however, given the opportunity losses associated with delaying the implementation, "implement and research" is the approach recommended for this intervention.

Multiple Criteria Decision Analysis for Health Care Decision Making--An Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force.

PubMed

Thokala, Praveen; Devlin, Nancy; Marsh, Kevin; Baltussen, Rob; Boysen, Meindert; Kalo, Zoltan; Longrenn, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Ijzerman, Maarten

2016-01-01

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting, objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making and a set of techniques, known under the collective heading multiple criteria decision analysis (MCDA), are useful for this purpose. MCDA methods are widely used in other sectors, and recently there has been an increase in health care applications. In 2014, ISPOR established an MCDA Emerging Good Practices Task Force. It was charged with establishing a common definition for MCDA in health care decision making and developing good practice guidelines for conducting MCDA to aid health care decision making. This initial ISPOR MCDA task force report provides an introduction to MCDA - it defines MCDA; provides examples of its use in different kinds of decision making in health care (including benefit risk analysis, health technology assessment, resource allocation, portfolio decision analysis, shared patient clinician decision making and prioritizing patients' access to services); provides an overview of the principal methods of MCDA; and describes the key steps involved. Upon reviewing this report, readers should have a solid overview of MCDA methods and their potential for supporting health care decision making. Copyright © 2016. Published by Elsevier Inc.

Multi Criteria Evaluation Module for RiskChanges Spatial Decision Support System

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; Jaboyedoff, Michel; van Westen, Cees; Bakker, Wim

2015-04-01

Multi-Criteria Evaluation (MCE) module is one of the five modules of RiskChanges spatial decision support system. RiskChanges web-based platform aims to analyze changes in hydro-meteorological risk and provides tools for selecting the best risk reduction alternative. It is developed under CHANGES framework (changes-itn.eu) and INCREO project (increo-fp7.eu). MCE tool helps decision makers and spatial planners to evaluate, sort and rank the decision alternatives. The users can choose among different indicators that are defined within the system using Risk and Cost Benefit analysis results besides they can add their own indicators. Subsequently the system standardizes and prioritizes them. Finally, the best decision alternative is selected by using the weighted sum model (WSM). The Application of this work is to facilitate the effect of MCE for analyzing changing risk over the time under different scenarios and future years by adopting a group decision making into practice and comparing the results by numeric and graphical view within the system. We believe that this study helps decision-makers to achieve the best solution by expressing their preferences for strategies under future scenarios. Keywords: Multi-Criteria Evaluation, Spatial Decision Support System, Weighted Sum Model, Natural Hazard Risk Management

Cue acquisition: A feature of Malawian midwives decision making process to support normality during the first stage of labour.

PubMed

Chodzaza, Elizabeth; Haycock-Stuart, Elaine; Holloway, Aisha; Mander, Rosemary

2018-03-01

to explore Malawian midwives decision making when caring for women during the first stage of labour in the hospital setting. this focused ethnographic study examined the decision making process of 9 nurse-midwives with varying years of clinical experience in the real world setting of an urban and semi urban hospital from October 2013 to May 2014.This was done using 27 participant observations and 27 post-observation in-depth interviews over a period of six months. Qualitative data analysis software, NVivo 10, was used to assist with data management for the analysis. All data was analysed using the principle of theme and category formation. analysis revealed a six-stage process of decision making that include a baseline for labour, deciding to admit a woman to labour ward, ascertaining the normal physiological progress of labour, supporting the normal physiological progress of labour, embracing uncertainty: the midwives' construction of unusual labour as normal, dealing with uncertainty and deciding to intervene in unusual labour. This six-stage process of decision making is conceptualised as the 'role of cue acquisition', illustrating the ways in which midwives utilise their assessment of labouring women to reason and make decisions on how to care for them in labour. Cue acquisition involved the midwives piecing together segments of information they obtained from the women to formulate an understanding of the woman's birthing progress and inform the midwives decision making process. This understanding of cue acquisition by midwives is significant for supporting safe care in the labour setting. When there was uncertainty in a woman's progress of labour, midwives used deductive reasoning, for example, by cross-checking and analysing the information obtained during the span of labour. Supporting normal labour physiological processes was identified as an underlying principle that shaped the midwives clinical judgement and decision making when they cared for women in labour. the significance of this study is in the new understanding and insight into the process of midwifery decision making. Whilst the approach to decision making by the midwives requires further testing and refinement in order to explore implications for practice, the findings here provide new conceptual and practical clarity of midwifery decision making. The work contributes to the identified lack of knowledge of how midwives working clinically, in the 'real world setting. These findings therefore, contribute to this body of knowledge with regards to our understanding of decision making of midwives. Copyright © 2017 Elsevier Ltd. All rights reserved.

Techno-Economic Analysis | Energy Analysis | NREL

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Technology Cost and Performance Data for Distributed Generation Explore our capital cost and performance analysis yields insights to support industry decisions about R&D targets, investment strategies, and

Value of information analysis in healthcare: a review of principles and applications.

PubMed

Tuffaha, Haitham W; Gordon, Louisa G; Scuffham, Paul A

2014-06-01

Economic evaluations are increasingly utilized to inform decisions in healthcare; however, decisions remain uncertain when they are not based on adequate evidence. Value of information (VOI) analysis has been proposed as a systematic approach to measure decision uncertainty and assess whether there is sufficient evidence to support new technologies. The objective of this paper is to review the principles and applications of VOI analysis in healthcare. Relevant databases were systematically searched to identify VOI articles. The findings from the selected articles were summarized and narratively presented. Various VOI methods have been developed and applied to inform decision-making, optimally designing research studies and setting research priorities. However, the application of this approach in healthcare remains limited due to technical and policy challenges. There is a need to create more awareness about VOI analysis, simplify its current methods, and align them with the needs of decision-making organizations.

System for decision analysis support on complex waste management issues

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shropshire, D.E.

1997-10-01

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

Class Evolution Tree: A Graphical Tool to Support Decisions on the Number of Classes in Exploratory Categorical Latent Variable Modeling for Rehabilitation Research

ERIC Educational Resources Information Center

Kriston, Levente; Melchior, Hanne; Hergert, Anika; Bergelt, Corinna; Watzke, Birgit; Schulz, Holger; von Wolff, Alessa

2011-01-01

The aim of our study was to develop a graphical tool that can be used in addition to standard statistical criteria to support decisions on the number of classes in explorative categorical latent variable modeling for rehabilitation research. Data from two rehabilitation research projects were used. In the first study, a latent profile analysis was…

Supporting multi-stakeholder environmental decisions.

PubMed

Hajkowicz, Stefan A

2008-09-01

This paper examines how multiple criteria analysis (MCA) can be used to support multi-stakeholder environmental management decisions. It presents a study through which 48 stakeholders from environmental, primary production and community interest groups used MCA to prioritise 30 environmental management problems in the Mackay-Whitsunday region of Queensland, Australia. The MCA model, with procedures for aggregating multi-stakeholder output, was used to inform a final decision on the priority of the region's environmental management problems. The result was used in the region's environmental management plan as required under Australia's Natural Heritage Trust programme. The study shows how relatively simple MCA methods can help stakeholders make group decisions, even when they hold strongly conflicting preferences.

Graduate Education in Risk Analysis for Food, Agriculture, and Veterinary Medicine: Challenges and Opportunities

ERIC Educational Resources Information Center

Correia, Ana-Paula; Wolt, Jeffrey D.

2010-01-01

The notion of risk in relation to food and food production has heightened the need to educate students to effectively deal with risk in relation to decision making from a science-based perspective. Curricula and related materials were developed and adopted to support graduate learning opportunities in risk analysis and decision making as applied…

Next generation data systems and knowledge products to support agricultural producers and science-based policy decision making.

PubMed

Capalbo, Susan M; Antle, John M; Seavert, Clark

2017-07-01

Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions. This paper presents a framework for the use of farm-level and landscape-scale models and data to provide analysis that could be used in NextGen knowledge products, such as mobile applications or personal computer data analysis and visualization software. We describe two analytical tools - AgBiz Logic and TOA-MD - that demonstrate the current capability of farmlevel and landscape-scale models. The use of these tools is explored with a case study of an oilseed crop, Camelina sativa , which could be used to produce jet aviation fuel. We conclude with a discussion of innovations needed to facilitate the use of farm and policy-level models to generate data and analysis for improved knowledge products.

Conceptualizing surrogate decision making at end of life in the intensive care unit using cognitive task analysis.

PubMed

Dionne-Odom, J Nicholas; Willis, Danny G; Bakitas, Marie; Crandall, Beth; Grace, Pamela J

2015-01-01

Surrogate decision makers (SDMs) face difficult decisions at end of life (EOL) for decisionally incapacitated intensive care unit (ICU) patients. To identify and describe the underlying psychological processes of surrogate decision making for adults at EOL in the ICU. Qualitative case study design using a cognitive task analysis interviewing approach. Participants were recruited from October 2012 to June 2013 from an academic tertiary medical center's ICU located in the rural Northeastern United States. Nineteen SDMs for patients who had died in the ICU completed in-depth semistructured cognitive task analysis interviews. The conceptual framework formulated from data analysis reveals that three underlying, iterative, psychological dimensions (gist impressions, distressing emotions, and moral intuitions) impact an SDM's judgment about the acceptability of either the patient's medical treatments or his or her condition. The framework offers initial insights about the underlying psychological processes of surrogate decision making and may facilitate enhanced decision support for SDMs. Copyright © 2015 Elsevier Inc. All rights reserved.

Choosing treatment and screening options congruent with values: Do decision aids help? Sub-analysis of a systematic review.

PubMed

Munro, Sarah; Stacey, Dawn; Lewis, Krystina B; Bansback, Nick

2016-04-01

To understand how well patients make value congruent decisions with and without patient decision aids (PtDAs) for screening and treatment options, and identify issues with its measurement and evaluation. A sub-analysis of trials included in the 2014 Cochrane Review of Decision Aids. Eligible trials measured value congruence with chosen option. Two reviewers independently screened 115 trials. Among 18 included trials, 8 (44%) measured value congruence using the Multidimensional Measure of Informed Choice (MMIC), 7 (39%) used heterogeneous methods, and 3 (17%) used unclear methods. Pooled results of trials that used heterogeneous measures were statistically non-significant (n=3). Results from trials that used the MMIC suggest patients are 48% more likely to make value congruent decisions when exposed to a PtDA for a screening decision (RR 1.48, 95% CI 1.01 to 2.16, n=8). Patients struggle to make value congruent decisions, but PtDAs may help. While the absolute improvement is relatively small it may be underestimated due to sample size issues, definitions, and heterogeneity of measures. Current approaches are inadequate to support patients making decisions that are consistent with their values. There is some evidence that PtDAs support patients with achieving values congruent decisions for screening choices. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Evaluation of SOVAT: an OLAP-GIS decision support system for community health assessment data analysis.

PubMed

Scotch, Matthew; Parmanto, Bambang; Monaco, Valerie

2008-06-09

Data analysis in community health assessment (CHA) involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS) enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture.On-Line Analytical Processing (OLAP) is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT) currently used by many public health professionals. SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS"). Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (alpha = .01) from SPSS-GIS for satisfaction and time (p < .002). Descriptive results indicated that participants had greater success in answering the tasks when using SOVAT as compared to SPSS-GIS. Using SOVAT, tasks were completed more efficiently, with a higher rate of success, and with greater satisfaction, than the combined use of SPSS and GIS. The results from this study indicate a potential for OLAP-GIS decision support systems as a valuable tool for CHA data analysis.

Evaluation of SOVAT: An OLAP-GIS decision support system for community health assessment data analysis

PubMed Central

Scotch, Matthew; Parmanto, Bambang; Monaco, Valerie

2008-01-01

Background Data analysis in community health assessment (CHA) involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS) enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture. On-Line Analytical Processing (OLAP) is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT) currently used by many public health professionals. Methods SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS"). Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Results Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (α = .01) from SPSS-GIS for satisfaction and time (p < .002). Descriptive results indicated that participants had greater success in answering the tasks when using SOVAT as compared to SPSS-GIS. Conclusion Using SOVAT, tasks were completed more efficiently, with a higher rate of success, and with greater satisfaction, than the combined use of SPSS and GIS. The results from this study indicate a potential for OLAP-GIS decision support systems as a valuable tool for CHA data analysis. PMID:18541037

Creating an advance-care-planning decision aid for high-risk surgery: a qualitative study

PubMed Central

2014-01-01

Background High-risk surgery patients may lose decision-making capacity as a result of surgical complications. Advance care planning prior to surgery may be beneficial, but remains controversial and is hindered by a lack of appropriate decision aids. This study sought to examine stakeholders’ views on the appropriateness of using decision aids, in general, to support advance care planning among high-risk surgery populations and the design of such a decision aid. Methods Key informants were recruited through purposive and snowball sampling. Semi-structured interviews were conducted by phone until data collected reached theoretical saturation. Key informants were asked to discuss their thoughts about advance care planning and interventions to support advance care planning, particularly for this population. Researchers took de-identified notes that were analyzed for emerging concordant, discordant, and recurrent themes using interpretative phenomenological analysis. Results Key informants described the importance of initiating advance care planning preoperatively, despite potential challenges present in surgical settings. In general, decision aids were viewed as an appropriate approach to support advance care planning for this population. A recipe emerged from the data that outlines tools, ingredients, and tips for success that are needed to design an advance care planning decision aid for high-risk surgical settings. Conclusions Stakeholders supported incorporating advance care planning in high-risk surgical settings and endorsed the appropriateness of using decision aids to do so. Findings will inform the next stages of developing the first advance care planning decision aid for high-risk surgery patients. PMID:25067908

Creating an advance-care-planning decision aid for high-risk surgery: a qualitative study.

PubMed

Schuster, Anne Lr; Aslakson, Rebecca A; Bridges, John Fp

2014-01-01

High-risk surgery patients may lose decision-making capacity as a result of surgical complications. Advance care planning prior to surgery may be beneficial, but remains controversial and is hindered by a lack of appropriate decision aids. This study sought to examine stakeholders' views on the appropriateness of using decision aids, in general, to support advance care planning among high-risk surgery populations and the design of such a decision aid. Key informants were recruited through purposive and snowball sampling. Semi-structured interviews were conducted by phone until data collected reached theoretical saturation. Key informants were asked to discuss their thoughts about advance care planning and interventions to support advance care planning, particularly for this population. Researchers took de-identified notes that were analyzed for emerging concordant, discordant, and recurrent themes using interpretative phenomenological analysis. Key informants described the importance of initiating advance care planning preoperatively, despite potential challenges present in surgical settings. In general, decision aids were viewed as an appropriate approach to support advance care planning for this population. A recipe emerged from the data that outlines tools, ingredients, and tips for success that are needed to design an advance care planning decision aid for high-risk surgical settings. Stakeholders supported incorporating advance care planning in high-risk surgical settings and endorsed the appropriateness of using decision aids to do so. Findings will inform the next stages of developing the first advance care planning decision aid for high-risk surgery patients.

On the suitability of fast and frugal heuristics for designing values clarification methods in patient decision aids: a critical analysis.

PubMed

Pieterse, Arwen H; de Vries, Marieke

2013-09-01

Increasingly, patient decision aids and values clarification methods (VCMs) are being developed to support patients in making preference-sensitive health-care decisions. Many VCMs encourage extensive deliberation about options, without solid theoretical or empirical evidence showing that deliberation is advantageous. Research suggests that simple, fast and frugal heuristic decision strategies sometimes result in better judgments and decisions. Durand et al. have developed two fast and frugal heuristic-based VCMs. To critically analyse the suitability of the 'take the best' (TTB) and 'tallying' fast and frugal heuristics in the context of patient decision making. Analysis of the structural similarities between the environments in which the TTB and tallying heuristics have been proven successful and the context of patient decision making and of the potential of these heuristic decision processes to support patient decision making. The specific nature of patient preference-sensitive decision making does not seem to resemble environments in which the TTB and tallying heuristics have proven successful. Encouraging patients to consider less rather than more relevant information potentially even deteriorates their values clarification process. Values clarification methods promoting the use of more intuitive decision strategies may sometimes be more effective. Nevertheless, we strongly recommend further theoretical thinking about the expected value of such heuristics and of other more intuitive decision strategies in this context, as well as empirical assessments of the mechanisms by which inducing such decision strategies may impact the quality and outcome of values clarification. © 2011 John Wiley & Sons Ltd.

On the suitability of fast and frugal heuristics for designing values clarification methods in patient decision aids: a critical analysis

PubMed Central

Pieterse, Arwen H.; de Vries, Marieke

2011-01-01

Abstract Background  Increasingly, patient decision aids and values clarification methods (VCMs) are being developed to support patients in making preference‐sensitive health‐care decisions. Many VCMs encourage extensive deliberation about options, without solid theoretical or empirical evidence showing that deliberation is advantageous. Research suggests that simple, fast and frugal heuristic decision strategies sometimes result in better judgments and decisions. Durand et al. have developed two fast and frugal heuristic‐based VCMs. Objective  To critically analyse the suitability of the ‘take the best’ (TTB) and ‘tallying’ fast and frugal heuristics in the context of patient decision making. Strategy  Analysis of the structural similarities between the environments in which the TTB and tallying heuristics have been proven successful and the context of patient decision making and of the potential of these heuristic decision processes to support patient decision making. Conclusion  The specific nature of patient preference‐sensitive decision making does not seem to resemble environments in which the TTB and tallying heuristics have proven successful. Encouraging patients to consider less rather than more relevant information potentially even deteriorates their values clarification process. Values clarification methods promoting the use of more intuitive decision strategies may sometimes be more effective. Nevertheless, we strongly recommend further theoretical thinking about the expected value of such heuristics and of other more intuitive decision strategies in this context, as well as empirical assessments of the mechanisms by which inducing such decision strategies may impact the quality and outcome of values clarification. PMID:21902770

The Role of the Technical Specialist in Disaster Response and Recovery

NASA Astrophysics Data System (ADS)

Curtis, J. C.

2017-12-01

Technical Specialists provide scientific expertise for making operational decisions during natural hazards emergencies. Technical Specialists are important members of any Incident Management Team (IMT) as is described in in the National Incident Management System (NIMS) that has been designed to respond to emergencies. Safety for the responders and the threatened population is the foremost consideration in command decisions and objectives, and the Technical Specialist is on scene and in the command post to support and promote safety while aiding decisions for incident objectives. The Technical Specialist's expertise can also support plans, logistics, and even finance as well as operations. This presentation will provide actual examples of the value of on-scene Technical Specialists, using National Weather Service "Decision Support Meteorologists" and "Incident Meteorologists". These examples will demonstrate the critical role of scientists that are trained in advising and presenting life-critical analysis and forecasts during emergencies. A case will be made for local, state, and/or a national registry of trained and deployment-ready scientists that can support emergency response.

Bibliometrics as a Tool for Supporting Prospective R&D Decision-Making in the Health Sciences

PubMed Central

Ismail, Sharif; Nason, Edward; Marjanovic, Sonja; Grant, Jonathan

2012-01-01

Abstract Bibliometric analysis is an increasingly important part of a broader “toolbox” of evaluation methods available to research and development (R&D) policymakers to support decision-making. In the US, UK and Australia, for example, there is evidence of gradual convergence over the past ten years towards a model of university research assessment and ranking incorporating the use of bibliometric measures. In Britain, the Department of Health (England) has shown growing interest in using bibliometric analysis to support prospective R&D decision-making, and has engaged RAND Europe's expertise in this area through a number of exercises since 2005. These range from the macro-level selection of potentially high impact institutions, to micro-level selection of high impact individuals for the National Institute for Health Research's faculty of researchers. The aim of this study is to create an accessible, “beginner's guide” to bibliometric theory and application in the area of health R&D decision-making. The study also aims to identify future directions and possible next steps in this area, based on RAND Europe's work with the Department of Health to date. It is targeted at a range of audiences, and will be of interest to health and biomedical researchers, as well as R&D decision-makers in the UK and elsewhere. The study was completed with funding support from RAND Europe's Health R&D Policy Research Unit with the Department of Health. PMID:28083218

Research evidence utilization in policy development by child welfare administrators.

PubMed

Jack, Susan; Dobbins, Maureen; Tonmyr, Lil; Dudding, Peter; Brooks, Sandy; Kennedy, Betty

2010-01-01

An exploratory qualitative study was conducted to explore how child welfare administrators use research evidence in decision-making. Content analysis revealed that a cultural shift toward evidence-based practice (EBP) is occurring in Canadian child welfare organizations and multiple types of evidence inform policy decisions. Barriers to using evidence include individual, organizational, and environmental factors. Facilitating factors include the development of internal champions and organizational cultures that value EBP. Integrating research into practice and policy decisions requires a multifaceted approach of creating organizational cultures that support research utilization and supporting senior bureaucrats to use research evidence in policy development.

Data warehousing as a healthcare business solution.

PubMed

Scheese, R

1998-02-01

Because of the trend toward consolidation in the healthcare field, many organizations have massive amounts of data stored in various information systems organizationwide, but access to the data by end users may be difficult. Healthcare organizations are being pressured to provide managers easy access to the data needed for critical decision making. One solution many organizations are turning to is implementing decision-support data warehouses. A data warehouse instantly delivers information directly to end users, freeing healthcare information systems staff for strategic operations. If designed appropriately, data warehouses can be a cost-effective tool for business analysis and decision support.

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis.

PubMed

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine; Peet, Andrew

2018-05-02

Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians' skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. ©Niloufar Zarinabad, Emma M Meeus, Karen Manias, Katharine Foster, Andrew Peet. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 02.05.2018.

Ending on a positive: Examining the role of safety leadership decisions, behaviours and actions in a safety critical situation.

PubMed

Donovan, Sarah-Louise; Salmon, Paul M; Horberry, Timothy; Lenné, Michael G

2018-01-01

Safety leadership is an important factor in supporting safe performance in the workplace. The present case study examined the role of safety leadership during the Bingham Canyon Mine high-wall failure, a significant mining incident in which no fatalities or injuries were incurred. The Critical Decision Method (CDM) was used in conjunction with a self-reporting approach to examine safety leadership in terms of decisions, behaviours and actions that contributed to the incidents' safe outcome. Mapping the analysis onto Rasmussen's Risk Management Framework (Rasmussen, 1997), the findings demonstrate clear links between safety leadership decisions, and emergent behaviours and actions across the work system. Communication and engagement based decisions featured most prominently, and were linked to different leadership practices across the work system. Further, a core sub-set of CDM decision elements were linked to the open flow and exchange of information across the work system, which was critical to supporting the safe outcome. The findings provide practical implications for the development of safety leadership capability to support safety within the mining industry. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-criteria development and incorporation into decision tools for health technology adoption.

PubMed

Poulin, Paule; Austen, Lea; Scott, Catherine M; Waddell, Cameron D; Dixon, Elijah; Poulin, Michelle; Lafrenière, René

2013-01-01

When introducing new health technologies, decision makers must integrate research evidence with local operational management information to guide decisions about whether and under what conditions the technology will be used. Multi-criteria decision analysis can support the adoption or prioritization of health interventions by using criteria to explicitly articulate the health organization's needs, limitations, and values in addition to evaluating evidence for safety and effectiveness. This paper seeks to describe the development of a framework to create agreed-upon criteria and decision tools to enhance a pre-existing local health technology assessment (HTA) decision support program. The authors compiled a list of published criteria from the literature, consulted with experts to refine the criteria list, and used a modified Delphi process with a group of key stakeholders to review, modify, and validate each criterion. In a workshop setting, the criteria were used to create decision tools. A set of user-validated criteria for new health technology evaluation and adoption was developed and integrated into the local HTA decision support program. Technology evaluation and decision guideline tools were created using these criteria to ensure that the decision process is systematic, consistent, and transparent. This framework can be used by others to develop decision-making criteria and tools to enhance similar technology adoption programs. The development of clear, user-validated criteria for evaluating new technologies adds a critical element to improve decision-making on technology adoption, and the decision tools ensure consistency, transparency, and real-world relevance.

Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2014-05-01

Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in this case study namely: construction of defense structures, relocation, implementation of an early warning system and spatial planning regulations. Some of the criteria are determined partly in other modules of the CHANGES SDSS, such as the costs for implementation, the risk reduction in monetary values, and societal risk. Other criteria, which could be environmental, economic, cultural, perception in nature, are defined by different stakeholders such as local authorities, expert organizations, private sector, and local public. In the next step, the stakeholders weight the importance of the criteria by pairwise comparison and visualize the decision matrix, which is a matrix based on criteria versus alternatives values. Finally alternatives are ranked by Analytic Hierarchy Process (AHP) method. We expect that this approach will help the decision makers to ease their works and reduce their costs, because the process is more transparent, more accurate and involves a group decision. In that way there will be more confidence in the overall decision making process. Keywords: MCDM, Analytic Hierarchy Process (AHP), SDSS, Natural Hazard Risk Management

Analysis And Assistant Planning System Ofregional Agricultural Economic Inform

NASA Astrophysics Data System (ADS)

Han, Jie; Zhang, Junfeng

For the common problems existed in regional development and planning, we try to design a decision support system for assisting regional agricultural development and alignment as a decision-making tool for local government and decision maker. The analysis methods of forecast, comparative advantage, liner programming and statistical analysis are adopted. According to comparative advantage theory, the regional advantage can be determined by calculating and comparing yield advantage index (YAI), Scale advantage index (SAI), Complicated advantage index (CAI). Combining with GIS, agricultural data are presented as a form of graph such as area, bar and pie to uncover the principle and trend for decision-making which can't be found in data table. This system provides assistant decisions for agricultural structure adjustment, agro-forestry development and planning, and can be integrated to information technologies such as RS, AI and so on.

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

PubMed

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.

Less is sometimes more: a comparison of distance-control and navigated-control concepts of image-guided navigation support for surgeons.

PubMed

Luz, Maria; Manzey, Dietrich; Modemann, Susanne; Strauss, Gero

2015-01-01

Image-guided navigation (IGN) systems provide automation support of intra-operative information analysis and decision-making for surgeons. Previous research showed that navigated-control (NC) systems which represent high levels of decision-support and directly intervene in surgeons' workflow provide benefits with respect to patient safety and surgeons' physiological stress but also involve several cost effects (e.g. prolonged surgery duration, reduced secondary-task performance). It was hypothesised that less automated distance-control (DC) systems would provide a better solution in terms of human performance consequences. N = 18 surgeons performed a simulated mastoidectomy with NC, DC and without IGN assistance. Effects on surgical performance, physiological effort, workload and situation awareness (SA) were compared. As expected, DC technology had the same benefits as the NC system but also led to less unwanted side effects on surgery duration, subjective workload and SA. This suggests that IGN systems just providing information analysis support are overall more beneficial than higher automated decision-support. This study investigates human performance consequences of different concepts of IGN support for surgeons. Less automated DC systems turned out to provide advantages for patient safety and surgeons' stress similar to higher automated NC systems with, at the same time, reduced negative consequences on surgery time and subjective workload.

Patient and provider perceptions of decision making about use of epidural analgesia during childbirth: a thematic analysis.

PubMed

Goldberg, Holly Bianca; Shorten, Allison

2014-01-01

This study examines the nature of differences in perceptions of decision making between patients and providers about use of epidural analgesia during labor. Thematic analysis was used to identify patterns in written survey responses from 14 patients, 13 labor nurses, and 7 obstetrician-gynecologists. Results revealed patients attempted to place themselves in an informed role in decision making and sought respect for their decisions. Some providers demonstrated paternalism and a tendency to steer patients in the direction of their own preferences. Nurses observed various pressures on decision making, reinforcing the importance of patients being supported to make an informed choice. Differences in perceptions suggest need for improvement in communication and shared decision-making practices related to epidural analgesia use in labor.

Utilization of multiple-criteria decision analysis (MCDA) to support healthcare decision-making FIFARMA, 2016

PubMed Central

Drake, Julia I.; de Hart, Juan Carlos Trujillo; Monleón, Clara; Toro, Walter; Valentim, Joice

2017-01-01

ABSTRACT Background and objectives:   MCDA is a decision-making tool with increasing use in the healthcare sector, including HTA (Health Technology Assessment). By applying multiple criteria, including innovation, in a comprehensive, structured and explicit manner, MCDA fosters a transparent, participative, consistent decision-making process taking into consideration values of all stakeholders. This paper by FIFARMA (Latin American Federation of Pharmaceutical Industry) proposes the deliberative (partial) MCDA as a more pragmatic, agile approach, especially when newly implemented. Methods: Literature review including real-world examples of effective MCDA implementation in healthcare decision making in both the public and private sector worldwide and in LA. Results and conclusion: It is the view of FIFARMA that MCDA should strongly be considered as a tool to support HTA and broader healthcare decision making such as the contracts and tenders process in order to foster transparency, fairness, and collaboration amongst stakeholders. PMID:29081919

Use of PRA in Shuttle Decision Making Process

NASA Technical Reports Server (NTRS)

Boyer, Roger L.; Hamlin, Teri L.

2010-01-01

How do you use PRA to support an operating program? This presentation will explore how the Shuttle Program Management has used the Shuttle PRA in its decision making process. It will reveal how the PRA has evolved from a tool used to evaluate Shuttle upgrades like Electric Auxiliary Power Unit (EAPU) to a tool that supports Flight Readiness Reviews (FRR) and real-time flight decisions. Specific examples of Shuttle Program decisions that have used the Shuttle PRA as input will be provided including how it was used in the Hubble Space Telescope (HST) manifest decision. It will discuss the importance of providing management with a clear presentation of the analysis, applicable assumptions and limitations, along with estimates of the uncertainty. This presentation will show how the use of PRA by the Shuttle Program has evolved overtime and how it has been used in the decision making process providing specific examples.

Understanding the stakeholders' intention to use economic decision-support tools: A cross-sectional study with the tobacco return on investment tool.

PubMed

Cheung, Kei Long; Evers, Silvia M A A; Hiligsmann, Mickaël; Vokó, Zoltán; Pokhrel, Subhash; Jones, Teresa; Muñoz, Celia; Wolfenstetter, Silke B; Józwiak-Hagymásy, Judit; de Vries, Hein

2016-01-01

Despite an increased number of economic evaluations of tobacco control interventions, the uptake by stakeholders continues to be limited. Understanding the underlying mechanism in adopting such economic decision-support tools by stakeholders is therefore important. By applying the I-Change Model, this study aims to identify which factors determine potential uptake of an economic decision-support tool, i.e., the Return on Investment tool. Stakeholders (decision-makers, purchasers of services/pharma products, professionals/service providers, evidence generators and advocates of health promotion) were interviewed in five countries, using an I-Change based questionnaire. MANOVA's were conducted to assess differences between intenders and non-intenders regarding beliefs. A multiple regression analysis was conducted to identify the main explanatory variables of intention to use an economic decision-support tool. Ninety-three stakeholders participated. Significant differences in beliefs were found between non-intenders and intenders: risk perception, attitude, social support, and self-efficacy towards using the tool. Regression showed that demographics, pre-motivational, and motivational factors explained 69% of the variation in intention. This study is the first to provide a theoretical framework to understand differences in beliefs between stakeholders who do or do not intend to use economic decision-support tools, and empirically corroborating the framework. This contributes to our understanding of the facilitators and barriers to the uptake of these studies. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

How can we make progress with decision support systems in landscape and river basin management? Lessons learned from a comparative analysis of four different decision support systems.

PubMed

Volk, Martin; Lautenbach, Sven; van Delden, Hedwig; Newham, Lachlan T H; Seppelt, Ralf

2010-12-01

This article analyses the benefits and shortcomings of the recently developed decision support systems (DSS) FLUMAGIS, Elbe-DSS, CatchMODS, and MedAction. The analysis elaborates on the following aspects: (i) application area/decision problem, (ii) stakeholder interaction/users involved, (iii) structure of DSS/model structure, (iv) usage of the DSS, and finally (v) most important shortcomings. On the basis of this analysis, we formulate four criteria that we consider essential for the successful use of DSS in landscape and river basin management. The criteria relate to (i) system quality, (ii) user support and user training, (iii) perceived usefulness and (iv) user satisfaction. We can show that the availability of tools and technologies for DSS in landscape and river basin management is good to excellent. However, our investigations indicate that several problems have to be tackled. First of all, data availability and homogenisation, uncertainty analysis and uncertainty propagation and problems with model integration require further attention. Furthermore, the appropriate and methodological stakeholder interaction and the definition of 'what end-users really need and want' have been documented as general shortcomings of all four examples of DSS. Thus, we propose an iterative development process that enables social learning of the different groups involved in the development process, because it is easier to design a DSS for a group of stakeholders who actively participate in an iterative process. We also identify two important lines of further development in DSS: the use of interactive visualization tools and the methodology of optimization to inform scenario elaboration and evaluate trade-offs among environmental measures and management alternatives.

How Can We Make Progress with Decision Support Systems in Landscape and River Basin Management? Lessons Learned from a Comparative Analysis of Four Different Decision Support Systems

NASA Astrophysics Data System (ADS)

Volk, Martin; Lautenbach, Sven; van Delden, Hedwig; Newham, Lachlan T. H.; Seppelt, Ralf

2010-12-01

This article analyses the benefits and shortcomings of the recently developed decision support systems (DSS) FLUMAGIS, Elbe-DSS, CatchMODS, and MedAction. The analysis elaborates on the following aspects: (i) application area/decision problem, (ii) stakeholder interaction/users involved, (iii) structure of DSS/model structure, (iv) usage of the DSS, and finally (v) most important shortcomings. On the basis of this analysis, we formulate four criteria that we consider essential for the successful use of DSS in landscape and river basin management. The criteria relate to (i) system quality, (ii) user support and user training, (iii) perceived usefulness and (iv) user satisfaction. We can show that the availability of tools and technologies for DSS in landscape and river basin management is good to excellent. However, our investigations indicate that several problems have to be tackled. First of all, data availability and homogenisation, uncertainty analysis and uncertainty propagation and problems with model integration require further attention. Furthermore, the appropriate and methodological stakeholder interaction and the definition of `what end-users really need and want' have been documented as general shortcomings of all four examples of DSS. Thus, we propose an iterative development process that enables social learning of the different groups involved in the development process, because it is easier to design a DSS for a group of stakeholders who actively participate in an iterative process. We also identify two important lines of further development in DSS: the use of interactive visualization tools and the methodology of optimization to inform scenario elaboration and evaluate trade-offs among environmental measures and management alternatives.

Complex Decision-Making in Heart Failure: A Systematic Review and Thematic Analysis.

PubMed

Hamel, Aimee V; Gaugler, Joseph E; Porta, Carolyn M; Hadidi, Niloufar Niakosari

Heart failure follows a highly variable and difficult course. Patients face complex decisions, including treatment with implantable cardiac defibrillators, mechanical circulatory support, and heart transplantation. The course of decision-making across multiple treatments is unclear yet integral to providing informed and shared decision-making. Recognizing commonalities across treatment decisions could help nurses and physicians to identify opportunities to introduce discussions and support shared decision-making. The specific aims of this review are to examine complex treatment decision-making, specifically implantable cardiac defibrillators, ventricular assist device, and cardiac transplantation, and to recognize commonalities and key points in the decisional process. MEDLINE, CINAHL, PsycINFO, and Web of Science were searched for English-language studies that included qualitative findings reflecting the complexity of heart failure decision-making. Using a 3-step process, findings were synthesized into themes and subthemes. Twelve articles met criteria for inclusion. Participants included patients, caregivers, and clinicians and included decisions to undergo and decline treatment. Emergent themes were "processing the decision," "timing and prognostication," and "considering the future." Subthemes described how participants received and understood information about the therapy, making and changing a treatment decision, timing their decision and gauging health status outcomes in the context of their decision, the influence of a life or death decision, and the future as a factor in their decisional process. Commonalities were present across therapies, which involved the timing of discussions, the delivery of information, and considerations of the future. Exploring this further could help support patient-centered care and optimize shared decision-making interventions.

Perceived risks around choice and decision making at end-of-life: a literature review.

PubMed

Wilson, F; Gott, M; Ingleton, C

2013-01-01

the World Health Organization identifies meeting patient choice for care as central to effective palliative care delivery. Little is known about how choice, which implies an objective balancing of options and risks, is understood and enacted through decision making at end-of-life. to explore how perceptions of 'risk' may inform decision-making processes at end-of-life. an integrative literature review was conducted between January and February 2010. Papers were reviewed using Hawker et al.'s criteria and evaluated according to clarity of methods, analysis and evidence of ethical consideration. All literature was retained as background data, but given the significant international heterogeneity the final analysis specifically focused on the UK context. the databases Medline, PsycINFO, Assia, British Nursing Index, High Wire Press and CINAHL were explored using the search terms decision*, risk, anxiety, hospice and palliative care, end-of-life care and publication date of 1998-2010. thematic analysis of 25 papers suggests that decision making at end-of-life is multifactorial, involving a balancing of risks related to caregiver support; service provider resources; health inequalities and access; challenges to information giving; and perceptions of self-identity. Overall there is a dissonance in understandings of choice and decision making between service providers and service users. the concept of risk acknowledges the factors that shape and constrain end-of-life choices. Recognition of perceived risks as a central factor in decision making would be of value in acknowledging and supporting meaningful decision making processes for patients with palliative care needs and their families.

Renewable Energy Data, Analysis, and Decisions: A Guide for Practitioners

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cox, Sarah L; Lopez, Anthony J; Watson, Andrea C

High-quality renewable energy resource data and other geographic information system (GIS) data are essential for the transition to a clean energy economy that prioritizes local resources, improves resiliency, creates jobs, and promotes energy independence. This guide is intended to support policymakers and planners, as well as technical experts, consultants, and academics in incorporating improved data and analysis into renewable energy decision-making.

Deployed Analyst History Report, Volume 2. Analytic Support to Combat Operations in the Philippines (2011-2014)

DTIC Science & Technology

2015-12-01

Army Training and Doctrine Command (TRADOC) Analysis Center (TRAC) to the Philippines for Operation ENDURING FREEDOM – Philippines (OEF-P). PROJECT...management, doctrine and force development, training management, system testing, system acquisition, decision analysis, and resource management, as...influenced procurement decisions and reshaped Army doctrine . Additionally, CAA itself has benefited in numerous ways. Combat experience provides analysts

Risk-Based Prioritization of Research for Aviation Security Using Logic-Evolved Decision Analysis

NASA Technical Reports Server (NTRS)

Eisenhawer, S. W.; Bott, T. F.; Sorokach, M. R.; Jones, F. P.; Foggia, J. R.

2004-01-01

The National Aeronautics and Space Administration is developing advanced technologies to reduce terrorist risk for the air transportation system. Decision support tools are needed to help allocate assets to the most promising research. An approach to rank ordering technologies (using logic-evolved decision analysis), with risk reduction as the metric, is presented. The development of a spanning set of scenarios using a logic-gate tree is described. Baseline risk for these scenarios is evaluated with an approximate reasoning model. Illustrative risk and risk reduction results are presented.

Developing Cost Accounting and Decision Support Software for Comprehensive Community-Based Support Systems: An Analysis of Needs, Interest, and Readiness in the Field.

ERIC Educational Resources Information Center

Harrington, Robert; Jenkins, Peter; Marzke, Carolyn; Cohen, Carol

Prominent among the new models of social service delivery are organizations providing comprehensive, community-based supports and services (CCBSS) to children and their families. A needs analysis explored CCBSS sites' interest in and readiness to use a software tool designed to help them make more effective internal resource allocation decisions…

'Walking the tightrope': The role of peer support workers in facilitating consumers' participation in decision-making.

PubMed

Cleary, Michelle; Raeburn, Toby; Escott, Phil; West, Sancia; Lopez, Violeta

2018-05-09

In adult mental health services, the participation of consumers is essential. The aim of this study was to explore the challenges faced by peer support workers when involving mental health consumers in decision-making about their care and the strategies they employed to overcome these challenges so as to improve mental health consumers' participation in decision-making and recovery. Semi-structured individual interviews were conducted with six peer support workers currently employed in psychiatric hospitals and/or community mental health systems. Thematic analysis identified challenges related to role definition, power imbalance, doctor-centric medical approaches to care, and lack of resources. Strategies to overcome these challenges that were reported, included the following: facilitating meaningful involvement for service users, appropriate use of the lived experience, building relationships and communication, promoting rights and advocacy, and promoting professionalism of peer support workers (PSWs). Nursing staff need ongoing support and education to understand and value the varied roles of PSWs and thereby empower PSWs to engage in enhancing consumer decision-making. The roles of the PSWs should be viewed as complementary, and greater appreciation and understanding of roles would better support recovery-oriented care. © 2018 Australian College of Mental Health Nurses Inc.

Patients' perceptions and attitudes on recurrent prostate cancer and hormone therapy: Qualitative comparison between decision-aid and control groups.

PubMed

Gorawara-Bhat, Rita; O'Muircheartaigh, Siobhan; Mohile, Supriya; Dale, William

2017-09-01

To compare patients' attitudes towards recurrent prostate cancer (PCa) and starting hormone therapy (HT) treatment in two groups-Decision-Aid (DA) (intervention) and Standard-of-care (SoC) (Control). The present research was conducted at three academic clinics-two in the Midwest and one in the Northeast U.S. Patients with biochemical recurrence of PCa (n=26) and follow-up oncology visits meeting inclusion criteria were randomized to either the SoC or DA intervention group prior to their consultation. Analysts were blinded to group assignment. Semi-structured phone interviews with patients were conducted 1-week post consultation. Interviews were audio-taped and transcribed. Qualitative analytic techniques were used to extract salient themes and conduct a comparative analysis of the two groups. Four salient themes emerged-1) knowledge acquisition, 2) decision-making style, 3) decision-making about timing of HT, and 4) anxiety-coping mechanisms. A comparative analysis showed that patients receiving the DA intervention had a better comprehension of Prostate-specific antigen (PSA), an improved understanding of HT treatment implications, an external locus-of-control, participation in shared decision-making and, support-seeking for anxiety reduction. In contrast, SoC patients displayed worse comprehension of PSA testing and HT treatment implications, internal locus-of-control, unilateral involvement in knowledge-seeking and decision-making, and no support-seeking for anxiety-coping. The DA was more effective than the SoC group in helping PCa patients understand the full implications of PSA testing and treatment; motivating shared decision-making, and support-seeking for anxiety relief. DA DVD interventions can be a useful patient education tool for bringing higher quality decision-making to prostate cancer care. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

PubMed Central

2011-01-01

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular. PMID:22206355

Market analysis of collecting fundamental roadway data elements to support the highway safety improvement program.

DOT National Transportation Integrated Search

2011-06-01

Quality data are the foundation for making important decisions regarding the design, operation, and safety of : roadways. Using roadway and traffic data together with crash data can help agencies to make decisions that are : fiscally responsible and ...

Shaping the Conversation: A Secondary Analysis of Reproductive Decision-Making Among Black Mothers with HIV.

PubMed

Amutah, Ndidiamaka N; Gifuni, Jacqueline; Wesley, Yvonne

2016-01-01

The purpose of this qualitative secondary data analysis is to examine the major influencers on mothers with HIV in their childbearing decisions, as well as how those influencers shape conversations with clinicians and health-care providers regarding HIV treatment and prevention. The original study gained insight into the reproductive decision-making of mothers with HIV. By analyzing a subsample of 15 interviews from an original cohort of 25 participants in the earlier study, three major themes were identified as follows: (1) family members, not health-care providers, influence reproductive decisions; (2) negative attitudes toward subsequent pregnancies are mainly due to HIV transmission; and (3) birth control decisions were predominately supported by family members, while health-care providers were not consulted.

Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.

PubMed

Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana

2016-01-01

The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.

Decision analysis to support development of the Glen Canyon Dam long-term experimental and management plan

USGS Publications Warehouse

Runge, Michael C.; LaGory, Kirk E.; Russell, Kendra; Balsom, Janet R.; Butler, R. Alan; Coggins,, Lewis G.; Grantz, Katrina A.; Hayse, John; Hlohowskyj, Ihor; Korman, Josh; May, James E.; O'Rourke, Daniel J.; Poch, Leslie A.; Prairie, James R.; VanKuiken, Jack C.; Van Lonkhuyzen, Robert A.; Varyu, David R.; Verhaaren, Bruce T.; Veselka, Thomas D.; Williams, Nicholas T.; Wuthrich, Kelsey K.; Yackulic, Charles B.; Billerbeck, Robert P.; Knowles, Glen W.

2016-01-07

The results of the decision analysis are meant to serve as only one of many sources of information that can be used to evaluate the alternatives proposed in the Environmental Impact Statement. These results only focus on those resource goals for which quantitative performance metrics could be formulated and evaluated; there are other important aspects of the resource goals that also need to be considered. Not all the stakeholders who were invited to participate in the decision analysis chose to do so; thus, the Bureau of Reclamation, National Park Service, and U.S. Department of Interior may want to consider other input.

Effects of imperfect automation on decision making in a simulated command and control task.

PubMed

Rovira, Ericka; McGarry, Kathleen; Parasuraman, Raja

2007-02-01

Effects of four types of automation support and two levels of automation reliability were examined. The objective was to examine the differential impact of information and decision automation and to investigate the costs of automation unreliability. Research has shown that imperfect automation can lead to differential effects of stages and levels of automation on human performance. Eighteen participants performed a "sensor to shooter" targeting simulation of command and control. Dependent variables included accuracy and response time of target engagement decisions, secondary task performance, and subjective ratings of mental work-load, trust, and self-confidence. Compared with manual performance, reliable automation significantly reduced decision times. Unreliable automation led to greater cost in decision-making accuracy under the higher automation reliability condition for three different forms of decision automation relative to information automation. At low automation reliability, however, there was a cost in performance for both information and decision automation. The results are consistent with a model of human-automation interaction that requires evaluation of the different stages of information processing to which automation support can be applied. If fully reliable decision automation cannot be guaranteed, designers should provide users with information automation support or other tools that allow for inspection and analysis of raw data.

"I've never been a yes person": Decision-making participation and self-conceptualization after severe traumatic brain injury.

PubMed

Knox, Lucy; Douglas, Jacinta M; Bigby, Christine

2017-11-01

Although adults who sustain a severe traumatic brain injury (TBI) require support to make decisions in their lives, little is known about their experience of this process. The aim of this study was to explore how participation in decision making contributes to self-conceptualization in adults with severe TBI. We used constructivist grounded theory methods. Data included 20 in-depth interviews with adults with severe TBI. Through a process of constant comparison, analysis involved open and focused coding until clear categories emerged and data saturation was achieved. Self-conceptualization emerged as a complex and multifaceted process, as individuals with TBI aimed to reestablish a sense of autonomy. We describe a recursive relationship in which decision-making participation assists the dynamic construction of self, and self-concept contributes to the experience of making decisions. The role of an individual's social support network in acting as a bridge between participation and self-conceptualization is presented. Findings emphasize that contributing to decisions about one's own goals across a range of life areas can reinforce a positive self-concept. It is vital that supporters understand that participation in decision making provides a pathway to conceptualizing self and aim to maximize the person's participation in the decision-making process. Implications for Rehabilitation Previous research has identified that the experience of sustaining TBI has a significant impact on a person's conceptualization of self. This study identified that decision-making experiences play an important role in the ongoing process of self-conceptualization after injury. Decision-making experiences can reinforce a person's self-concept or lead them to revise (positively or negatively) their sense of self. By maximizing the person's decision-making participation, those around them can support them to develop positive self-attributes and contribute to shaping their future goals.

Theory-based design and field-testing of an intervention to support women choosing surgery for breast cancer: BresDex.

PubMed

Sivell, Stephanie; Marsh, William; Edwards, Adrian; Manstead, Antony S R; Clements, Alison; Elwyn, Glyn

2012-02-01

Design and undertake usability and field-testing evaluation of a theory-guided decision aid (BresDex) in supporting women choosing surgery for early breast cancer. An extended Theory of Planned Behavior (TPB) and the Common Sense Model of Illness Representations (CSM) guided the design of BresDex. BresDex was evaluated and refined across 3 cycles by interviewing 6 women without personal history of breast cancer, 8 women with personal history of breast cancer who had completed treatment and 11 women newly diagnosed with breast cancer. Participants were interviewed for views on content, presentation (usability) and perceived usefulness towards deciding on treatment (utility). Framework analysis was used, guided by the extended TPB and the CSM. BresDex was positively received in content and presentation (usability). It appeared an effective support to decision-making and useful source for further information, particularly in clarifying attitudes, social norms and perceived behavioral control, and presenting consequences of decisions (utility). This study illustrates the potential benefit of the extended TPB and CSM in designing a decision aid to support women choosing breast cancer surgery. BresDex could provide decision-making support and serve as an additional source of information, to complement the care received from the clinical team. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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).

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

PubMed Central

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) PMID:21394218

Making Sense of Sensemaking: Requirements of a Cognitive Analysis to Support C2 Decision Support System Design

DTIC Science & Technology

2006-06-01

heart of a distinction within the CSE community with respect to the differences between Cognitive Task Analysis (CTA) and Cognitive Work Analysis...Wesley. Pirolli, P. and Card, S. (2005). The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis . In...D. D., and Elm, W. C. (2000). Cognitive task analysis as bootstrapping multiple converging techniques. In Schraagen, Chipman, and Shalin (Eds

Integrating complex business processes for knowledge-driven clinical decision support systems.

PubMed

Kamaleswaran, Rishikesan; McGregor, Carolyn

2012-01-01

This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS.

A Digital Framework to Support Providers and Patients in Diabetes Related Behavior Modification.

PubMed

Abidi, Samina; Vallis, Michael; Piccinini-Vallis, Helena; Imran, Syed Ali; Abidi, Syed Sibte Raza

2017-01-01

We present Diabetes Web-Centric Information and Support Environment (D-WISE) that features: (a) Decision support tool to assist family physicians to administer Behavior Modification (BM) strategies to patients; and (b) Patient BM application that offers BM strategies and motivational interventions to engage patients. We take a knowledge management approach, using semantic web technologies, to model the social cognition theory constructs, Canadian diabetes guidelines and BM protocols used locally, in terms of a BM ontology that drives the BM decision support to physicians and BM strategy adherence monitoring and messaging to patients. We present the qualitative analysis of D-WISE usability by both physicians and patients.

Trusted Advisors, Decision Models and Other Keys to Communicating Science to Decision Makers

NASA Astrophysics Data System (ADS)

Webb, E.

2006-12-01

Water resource management decisions often involve multiple parties engaged in contentious negotiations that try to navigate through complex combinations of legal, social, hydrologic, financial, and engineering considerations. The standard approach for resolving these issues is some form of multi-party negotiation, a formal court decision, or a combination of the two. In all these cases, the role of the decision maker(s) is to choose and implement the best option that fits the needs and wants of the community. However, each path to a decision carries the risk of technical and/or financial infeasibility as well as the possibility of unintended consequences. To help reduce this risk, decision makers often rely on some type of predictive analysis from which they can evaluate the projected consequences of their decisions. Typically, decision makers are supported in the analysis process by trusted advisors who engage in the analysis as well as the day to day tasks associated with multi-party negotiations. In the case of water resource management, the analysis is frequently a numerical model or set of models that can simulate various management decisions across multiple systems and output results that illustrate the impact on areas of concern. Thus, in order to communicate scientific knowledge to the decision makers, the quality of the communication between the analysts, the trusted advisor, and the decision maker must be clear and direct. To illustrate this concept, a multi-attribute decision analysis matrix will be used to outline the value of computer model-based collaborative negotiation approaches to guide water resources decision making and communication with decision makers. In addition, the critical role of the trusted advisor and other secondary participants in the decision process will be discussed using examples from recent water negotiations.

Automatic Decision Support for Clinical Diagnostic Literature Using Link Analysis in a Weighted Keyword Network.

PubMed

Li, Shuqing; Sun, Ying; Soergel, Dagobert

2017-12-23

We present a novel approach to recommending articles from the medical literature that support clinical diagnostic decision-making, giving detailed descriptions of the associated ideas and principles. The specific goal is to retrieve biomedical articles that help answer questions of a specified type about a particular case. Based on the filtered keywords, MeSH(Medical Subject Headings) lexicon and the automatically extracted acronyms, the relationship between keywords and articles was built. The paper gives a detailed description of the process of by which keywords were measured and relevant articles identified based on link analysis in a weighted keywords network. Some important challenges identified in this study include the extraction of diagnosis-related keywords and a collection of valid sentences based on the keyword co-occurrence analysis and existing descriptions of symptoms. All data were taken from medical articles provided in the TREC (Text Retrieval Conference) clinical decision support track 2015. Ten standard topics and one demonstration topic were tested. In each case, a maximum of five articles with the highest relevance were returned. The total user satisfaction of 3.98 was 33% higher than average. The results also suggested that the smaller the number of results, the higher the average satisfaction. However, a few shortcomings were also revealed since medical literature recommendation for clinical diagnostic decision support is so complex a topic that it cannot be fully addressed through the semantic information carried solely by keywords in existing descriptions of symptoms. Nevertheless, the fact that these articles are actually relevant will no doubt inspire future research.

Using social network analysis to examine the decision-making process on new vaccine introduction in Nigeria.

PubMed

Wonodi, C B; Privor-Dumm, L; Aina, M; Pate, A M; Reis, R; Gadhoke, P; Levine, O S

2012-05-01

The decision-making process to introduce new vaccines into national immunization programmes is often complex, involving many stakeholders who provide technical information, mobilize finance, implement programmes and garner political support. Stakeholders may have different levels of interest, knowledge and motivations to introduce new vaccines. Lack of consensus on the priority, public health value or feasibility of adding a new vaccine can delay policy decisions. Efforts to support country-level decision-making have largely focused on establishing global policies and equipping policy makers with the information to support decision-making on new vaccine introduction (NVI). Less attention has been given to understanding the interactions of policy actors and how the distribution of influence affects the policy process and decision-making. Social network analysis (SNA) is a social science technique concerned with explaining social phenomena using the structural and relational features of the network of actors involved. This approach can be used to identify how information is exchanged and who is included or excluded from the process. For this SNA of vaccine decision-making in Nigeria, we interviewed federal and state-level government officials, officers of bilateral and multilateral partner organizations, and other stakeholders such as health providers and the media. Using data culled from those interviews, we performed an SNA in order to map formal and informal relationships and the distribution of influence among vaccine decision-makers, as well as to explore linkages and pathways to stakeholders who can influence critical decisions in the policy process. Our findings indicate a relatively robust engagement of key stakeholders in Nigeria. We hypothesized that economic stakeholders and implementers would be important to ensure sustainable financing and strengthen programme implementation, but some economic and implementation stakeholders did not appear centrally on the map; this may suggest a need to strengthen the decision-making processes by engaging these stakeholders more centrally and earlier.

THE CAUSAL ANALYSIS / DIAGNOSIS DECISION INFORMATION SYSTEM (CADDIS) - 2007 UPDATE

EPA Science Inventory

CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based ...

ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT, ENVIRONMENTAL DECISION SUPPORT SOFTWARE, UNIVERSITY OF TENNESSEE RESEARCH CORPORATION, SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA)

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) has created the Environmental Technology Verification Program (ETV) to facilitate the deployment of innovative or improved environmental technologies through performance verification and dissemination of information. The goal of the...

What supports do health system organizations have in place to facilitate evidence-informed decision-making? a qualitative study

PubMed Central

2013-01-01

Background Decisions regarding health systems are sometimes made without the input of timely and reliable evidence, leading to less than optimal health outcomes. Healthcare organizations can implement tools and infrastructures to support the use of research evidence to inform decision-making. Objectives The purpose of this study was to profile the supports and instruments (i.e., programs, interventions, instruments or tools) that healthcare organizations currently have in place and which ones were perceived to facilitate evidence-informed decision-making. Methods In-depth semi-structured telephone interviews were conducted with individuals in three different types of positions (i.e., a senior management team member, a library manager, and a ‘knowledge broker’) in three types of healthcare organizations (i.e., regional health authorities, hospitals and primary care practices) in two Canadian provinces (i.e., Ontario and Quebec). The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. Results A total of 57 interviews were conducted in 25 organizations in Ontario and Quebec. The main findings suggest that, for the healthcare organizations that participated in this study, the following supports facilitate evidence-informed decision-making: facilitating roles that actively promote research use within the organization; establishing ties to researchers and opinion leaders outside the organization; a technical infrastructure that provides access to research evidence, such as databases; and provision and participation in training programs to enhance staff’s capacity building. Conclusions This study identified the need for having a receptive climate, which laid the foundation for the implementation of other tangible initiatives and supported the use of research in decision-making. This study adds to the literature on organizational efforts that can increase the use of research evidence in decision-making. Some of the identified supports may increase the use of research evidence by decision-makers, which may then lead to more informed decisions, and hopefully to a strengthened health system and improved health. PMID:23915278

What supports do health system organizations have in place to facilitate evidence-informed decision-making? A qualitative study.

PubMed

Ellen, Moriah E; Léon, Gregory; Bouchard, Gisèle; Lavis, John N; Ouimet, Mathieu; Grimshaw, Jeremy M

2013-08-06

Decisions regarding health systems are sometimes made without the input of timely and reliable evidence, leading to less than optimal health outcomes. Healthcare organizations can implement tools and infrastructures to support the use of research evidence to inform decision-making. The purpose of this study was to profile the supports and instruments (i.e., programs, interventions, instruments or tools) that healthcare organizations currently have in place and which ones were perceived to facilitate evidence-informed decision-making. In-depth semi-structured telephone interviews were conducted with individuals in three different types of positions (i.e., a senior management team member, a library manager, and a 'knowledge broker') in three types of healthcare organizations (i.e., regional health authorities, hospitals and primary care practices) in two Canadian provinces (i.e., Ontario and Quebec). The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. A total of 57 interviews were conducted in 25 organizations in Ontario and Quebec. The main findings suggest that, for the healthcare organizations that participated in this study, the following supports facilitate evidence-informed decision-making: facilitating roles that actively promote research use within the organization; establishing ties to researchers and opinion leaders outside the organization; a technical infrastructure that provides access to research evidence, such as databases; and provision and participation in training programs to enhance staff's capacity building. This study identified the need for having a receptive climate, which laid the foundation for the implementation of other tangible initiatives and supported the use of research in decision-making. This study adds to the literature on organizational efforts that can increase the use of research evidence in decision-making. Some of the identified supports may increase the use of research evidence by decision-makers, which may then lead to more informed decisions, and hopefully to a strengthened health system and improved health.

Systems analysis - a new paradigm and decision support tools for the water framework directive

NASA Astrophysics Data System (ADS)

Bruen, M.

2007-06-01

In the early days of Systems Analysis the focus was on providing tools for optimisation, modelling and simulation for use by experts. Now there is a recognition of the need to develop and disseminate tools to assist in making decisions, negotiating compromises and communicating preferences that can easily be used by stakeholders without the need for specialist training. The Water Framework Directive (WFD) requires public participation and thus provides a strong incentive for progress in this direction. This paper places the new paradigm in the context of the classical one and discusses some of the new approaches which can be used in the implementation of the WFD. These include multi-criteria decision support methods suitable for environmental problems, adaptive management, cognitive mapping, social learning and cooperative design and group decision-making. Concordance methods (such as ELECTRE) and the Analytical Hierarchy Process (AHP) are identified as multi-criteria methods that can be readily integrated into Decision Support Systems (DSS) that deal with complex environmental issues with very many criteria, some of which are qualitative. The expanding use of the new paradigm provides an opportunity to observe and learn from the interaction of stakeholders with the new technology and to assess its effectiveness. This is best done by trained sociologists fully integrated into the processes. The WINCOMS research project is an example applied to the implementation of the WFD in Ireland.

Interactive decision support in hepatic surgery

PubMed Central

Dugas, Martin; Schauer, Rolf; Volk, Andreas; Rau, Horst

2002-01-01

Background Hepatic surgery is characterized by complicated operations with a significant peri- and postoperative risk for the patient. We developed a web-based, high-granular research database for comprehensive documentation of all relevant variables to evaluate new surgical techniques. Methods To integrate this research system into the clinical setting, we designed an interactive decision support component. The objective is to provide relevant information for the surgeon and the patient to assess preoperatively the risk of a specific surgical procedure. Based on five established predictors of patient outcomes, the risk assessment tool searches for similar cases in the database and aggregates the information to estimate the risk for an individual patient. Results The physician can verify the analysis and exclude manually non-matching cases according to his expertise. The analysis is visualized by means of a Kaplan-Meier plot. To evaluate the decision support component we analyzed data on 165 patients diagnosed with hepatocellular carcinoma (period 1996–2000). The similarity search provides a two-peak distribution indicating there are groups of similar patients and singular cases which are quite different to the average. The results of the risk estimation are consistent with the observed survival data, but must be interpreted with caution because of the limited number of matching reference cases. Conclusion Critical issues for the decision support system are clinical integration, a transparent and reliable knowledge base and user feedback. PMID:12003639

GIS, modeling, and politics: on the tensions of collaborative decision support.

PubMed

Ramsey, Kevin

2009-05-01

A tension exists at the heart of efforts to support collaboration with GIS. Many scholars and practitioners seek to support two separate objectives: (1) problem solving and (2) the exploration of diverse problem understandings. GIS applications designed for problem solving often pre-define the problem space by structuring the kind of information that can be considered or the way in which the problem is conceptualized. In doing so, they necessarily privilege particular perspectives and understandings of the problem while marginalizing others. As a result, these initiatives undermine their second objective. This is problematic in the context of contentious environmental decisions which have broad-reaching impacts on people with diverse perspectives and interests. In such contexts, I argue that equitable collaboration is impossible without first emphasizing the exploration of diverse problem understandings. I support this argument theoretically by turning to the literatures on collaborative planning and spatial decision support, and empirically in my analysis of a case study of an effort to construct a GIS for supporting collaborative water resource management in rural Idaho. Reflecting upon the case, I provide a set of recommendations to those seeking to better negotiate the tensions of supporting collaboration with GIS in the context of contentious environmental and natural resource decisions.

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

Balaji, S. Arun

2010-11-01

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

Using Decision Analysis to Improve Malaria Control Policy Making

PubMed Central

Kramer, Randall; Dickinson, Katherine L.; Anderson, Richard M.; Fowler, Vance G.; Miranda, Marie Lynn; Mutero, Clifford M.; Saterson, Kathryn A.; Wiener, Jonathan B.

2013-01-01

Malaria and other vector-borne diseases represent a significant and growing burden in many tropical countries. Successfully addressing these threats will require policies that expand access to and use of existing control methods, such as insecticide-treated bed nets and artemesinin combination therapies for malaria, while weighing the costs and benefits of alternative approaches over time. This paper argues that decision analysis provides a valuable framework for formulating such policies and combating the emergence and re-emergence of malaria and other diseases. We outline five challenges that policy makers and practitioners face in the struggle against malaria, and demonstrate how decision analysis can help to address and overcome these challenges. A prototype decision analysis framework for malaria control in Tanzania is presented, highlighting the key components that a decision support tool should include. Developing and applying such a framework can promote stronger and more effective linkages between research and policy, ultimately helping to reduce the burden of malaria and other vector-borne diseases. PMID:19356821

Conceptualizing Surrogate Decision-Making at End of Life in the Intensive Care Unit using Cognitive Task Analysis

PubMed Central

Dionne-Odom, J. Nicholas; Willis, Danny G.; Bakitas, Marie; Crandall, Beth; Grace, Pamela J.

2014-01-01

Background Surrogate decision-makers (SDMs) face difficult decisions at end of life (EOL) for decisionally incapacitated intensive care unit (ICU) patients. Purpose Identify and describe the underlying psychological processes of surrogate decision-making for adults at EOL in the ICU. Method Qualitative case study design using a cognitive task analysis (CTA) interviewing approach. Participants were recruited from October 2012 to June 2013 from an academic tertiary medical center’s ICU located in the rural Northeastern United States. Nineteen SDMs for patients who had died in the ICU completed in-depth semi-structured CTA interviews. Discussion The conceptual framework formulated from data analysis reveals that three underlying, iterative, psychological dimensions: gist impressions, distressing emotions, and moral intuitions impact a SDM’s judgment about the acceptability of either the patient’s medical treatments or his or her condition. Conclusion The framework offers initial insights about the underlying psychological processes of surrogate decision-making and may facilitate enhanced decision support for SDMs. PMID:25982772

Decision Support Preferences Among Hispanic and Non-Hispanic White Older Adults With Chronic Musculoskeletal Pain.

PubMed

Riffin, Catherine; Pillemer, Karl; Reid, Manny C; Lӧckenhoff, Corinna E

2016-09-01

Despite broad recognition that social networks play a key role in the management of chronic musculoskeletal pain (CMP), little is known about when and why older adults with CMP choose to involve others in treatment decisions. This study investigates the types (i.e., informational, emotional, and instrumental) and sources (i.e., formal and informal) of support Hispanic and non-Hispanic White CMP patients desire and receive when making decisions about their pain care. Semi-structured interviews were conducted with Hispanic and non-Hispanic White older adults with CMP (N = 63) recruited from one medical center and one senior center in New York City. Interviews were transcribed and then analyzed using content analysis. CMP patients sought network members who supported their emotional well-being throughout the decision-making process. When considering high-stakes treatment decisions, participants selectively involved individuals who had similar pain conditions or first-hand experience with the procedure. Participants' perceptions of the decision-making process were contingent upon the congruence between the decision they made and the support they received for it. For Spanish-speaking participants, positive perceptions were linked with satisfactory language competence by their providers. On the other hand, lack of language competence among providers hindered Spanish speakers' ability to obtain adequate informational support. Results reveal the importance of empathic patient-provider exchanges across diverse patient populations and cultural sensitivity for Spanish-speaking patients. Findings suggest that social networks beyond the patient-provider dyad influence patients' decision-making satisfaction. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Economic analyses to support decisions about HPV vaccination in low- and middle-income countries: a consensus report and guide for analysts.

PubMed

Jit, Mark; Levin, Carol; Brisson, Marc; Levin, Ann; Resch, Stephen; Berkhof, Johannes; Kim, Jane; Hutubessy, Raymond

2013-01-30

Low- and middle-income countries need to consider economic issues such as cost-effectiveness, affordability and sustainability before introducing a program for human papillomavirus (HPV) vaccination. However, many such countries lack the technical capacity and data to conduct their own analyses. Analysts informing policy decisions should address the following questions: 1) Is an economic analysis needed? 2) Should analyses address costs, epidemiological outcomes, or both? 3) If costs are considered, what sort of analysis is needed? 4) If outcomes are considered, what sort of model should be used? 5) How complex should the analysis be? 6) How should uncertainty be captured? 7) How should model results be communicated? Selecting the appropriate analysis is essential to ensure that all the important features of the decision problem are correctly represented, but that the analyses are not more complex than necessary. This report describes the consensus of an expert group convened by the World Health Organization, prioritizing key issues to be addressed when considering economic analyses to support HPV vaccine introduction in these countries.

Life support technology investment strategies for flight programs: An application of decision analysis

NASA Technical Reports Server (NTRS)

Schlater, Nelson J.; Simonds, Charles H.; Ballin, Mark G.

1993-01-01

Applied research and technology development (R&TD) is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Given the increased awareness of limitations in resources, effective R&TD today needs a method for up-front assessment of competing technologies to help guide technology investment decisions. Such an assessment approach must account for uncertainties in system performance parameters, mission requirements and architectures, and internal and external events influencing a development program. The methodology known as decision analysis has the potential to address these issues. It was evaluated by performing a case study assessment of alternative carbon dioxide removal technologies for NASA"s proposed First Lunar Outpost program. An approach was developed that accounts for the uncertainties in each technology's cost and performance parameters as well as programmatic uncertainties such as mission architecture. Life cycle cost savings relative to a baseline, adjusted for the cost of money, was used as a figure of merit to evaluate each of the alternative carbon dioxide removal technology candidates. The methodology was found to provide a consistent decision-making strategy for the develpoment of new life support technology. The case study results provided insight that was not possible from more traditional analysis approaches.

Life support technology investment strategies for flight programs: An application of decision analysis

NASA Technical Reports Server (NTRS)

Schlater, Nelson J.; Simonds, Charles H.; Ballin, Mark G.

1993-01-01

Applied research and technology development (R&TD) is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Given the increased awareness of limitations in resources, effective R&TD today needs a method for up-front assessment of competing technologies to help guide technology investment decisions. Such an assessment approach must account for uncertainties in system performance parameters, mission requirements and architectures, and internal and external events influencing a development program. The methodology known as decision analysis has the potential to address these issues. It was evaluated by performing a case study assessment of alternative carbon dioxide removal technologies for NASA's proposed First Lunar Outpost program. An approach was developed that accounts for the uncertainties in each technology's cost and performance parameters as well as programmatic uncertainties such as mission architecture. Life cycle cost savings relative to a baseline, adjusted for the cost of money, was used as a figure of merit to evaluate each of the alternative carbon dioxide removal technology candidates. The methodology was found to provide a consistent decision-making strategy for development of new life support technology. The case study results provided insight that was not possible from more traditional analysis approaches.

A Participants' DSS for a Management Game with a DSS Generator.

ERIC Educational Resources Information Center

Yeo, Gee Kin; Nah, Fui Hoon

1992-01-01

Describes the design of a decision support system (DSS) for a management game called MAGNUS (Management Game for National University of Singapore). Built-in models for performance analysis and decision making are explained; database query and model building are described; and future work is discussed. (11 references) (LRW)

SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING AND RISK ASSESSMENT (SLIDE PRESENTATION)

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CHICAGO: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND ENVIRONMENTAL RISK ASSESSMENT

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CZECH REPUBLIC: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND RISK ASSESSMENT

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

Triple Value System Dynamics Modeling to Help Stakeholders Engage with Food-Energy-Water Problems

EPA Science Inventory

Triple Value (3V) Community scoping projects and Triple Value Simulation (3VS) models help decision makers and stakeholders apply systems-analysis methodology to complex problems related to food production, water quality, and energy use. 3VS models are decision support tools that...

Examining One High School's Restructuring Efforts within "Garbage Can" Decision Making Theory.

ERIC Educational Resources Information Center

Shindler, John V.

A study examined decision making within one large urban high school's restructuring efforts, using an emergent qualitative case-study design. Data, collected over a 2-year period, included formal and informal interviews, participant and nonparticipant observations, surveys, and documents. Results of data analysis supported matching the…

REGIONAL VULNERABILITY ASSESSMENT (REVA) IMPROVING ENVIRONMENTAL DECISION MAKING THROUGH CLIENT PARTNERSHIPS

EPA Science Inventory

The Regional Vulnerability Assessment (ReV A) Program is an applied research program t,1at is focusing on using spatial information and model results to support environmental decision-making at regional- down to local-scales. Re VA has developed analysis and assessment methods to...

A matter of tradeoffs: reintroduction as a multiple objective decision

USGS Publications Warehouse

Converse, Sarah J.; Moore, Clinton T.; Folk, Martin J.; Runge, Michael C.

2013-01-01

Decision making in guidance of reintroduction efforts is made challenging by the substantial scientific uncertainty typically involved. However, a less recognized challenge is that the management objectives are often numerous and complex. Decision makers managing reintroduction efforts are often concerned with more than just how to maximize the probability of reintroduction success from a population perspective. Decision makers are also weighing other concerns such as budget limitations, public support and/or opposition, impacts on the ecosystem, and the need to consider not just a single reintroduction effort, but conservation of the entire species. Multiple objective decision analysis is a powerful tool for formal analysis of such complex decisions. We demonstrate the use of multiple objective decision analysis in the case of the Florida non-migratory whooping crane reintroduction effort. In this case, the State of Florida was considering whether to resume releases of captive-reared crane chicks into the non-migratory whooping crane population in that state. Management objectives under consideration included maximizing the probability of successful population establishment, minimizing costs, maximizing public relations benefits, maximizing the number of birds available for alternative reintroduction efforts, and maximizing learning about the demographic patterns of reintroduced whooping cranes. The State of Florida engaged in a collaborative process with their management partners, first, to evaluate and characterize important uncertainties about system behavior, and next, to formally evaluate the tradeoffs between objectives using the Simple Multi-Attribute Rating Technique (SMART). The recommendation resulting from this process, to continue releases of cranes at a moderate intensity, was adopted by the State of Florida in late 2008. Although continued releases did not receive support from the International Whooping Crane Recovery Team, this approach does provide a template for the formal, transparent consideration of multiple, potentially competing, objectives in reintroduction decision making.

Accelerating policy decisions to adopt haemophilus influenzae type B vaccine: a global, multivariable analysis.

PubMed

Shearer, Jessica C; Stack, Meghan L; Richmond, Marcie R; Bear, Allyson P; Hajjeh, Rana A; Bishai, David M

2010-03-16

Adoption of new and underutilized vaccines by national immunization programs is an essential step towards reducing child mortality. Policy decisions to adopt new vaccines in high mortality countries often lag behind decisions in high-income countries. Using the case of Haemophilus influenzae type b (Hib) vaccine, this paper endeavors to explain these delays through the analysis of country-level economic, epidemiological, programmatic and policy-related factors, as well as the role of the Global Alliance for Vaccines and Immunisation (GAVI Alliance). Data for 147 countries from 1990 to 2007 were analyzed in accelerated failure time models to identify factors that are associated with the time to decision to adopt Hib vaccine. In multivariable models that control for Gross National Income, region, and burden of Hib disease, the receipt of GAVI support speeded the time to decision by a factor of 0.37 (95% CI 0.18-0.76), or 63%. The presence of two or more neighboring country adopters accelerated decisions to adopt by a factor of 0.50 (95% CI 0.33-0.75). For each 1% increase in vaccine price, decisions to adopt are delayed by a factor of 1.02 (95% CI 1.00-1.04). Global recommendations and local studies were not associated with time to decision. This study substantiates previous findings related to vaccine price and presents new evidence to suggest that GAVI eligibility is associated with accelerated decisions to adopt Hib vaccine. The influence of neighboring country decisions was also highly significant, suggesting that approaches to support the adoption of new vaccines should consider supply- and demand-side factors.

A qualitative study of professional and client perspectives on information flows and decision aid use.

PubMed

Stirling, Christine; Lloyd, Barbara; Scott, Jenn; Abbey, Jenny; Croft, Toby; Robinson, Andrew

2012-03-29

This paper explores the meanings given by a diverse range of stakeholders to a decision aid aimed at helping carers of people in early to moderate stages of dementia (PWD) to select community based respite services. Decision aids aim to empower clients to share decision making with health professionals. However, the match between health professionals' perspectives on decision support needs and their clients' perspective is an important and often unstudied aspect of decision aid use. A secondary analysis was undertaken of qualitative data collected as part of a larger study. The data included twelve interviews with carers of people with dementia, three interviews with expert advisors, and three focus groups with health professionals. A theoretical analysis was conducted, drawing on theories of 'positioning' and professional identity. Health professionals are seen to hold varying attitudes and beliefs about carers' decision support needs, and these appeared to be grounded in the professional identity of each group. These attitudes and beliefs shaped their attitudes towards decision aids, the information they believed should be offered to dementia carers, and the timing of its offering. Some groups understood carers as needing to be protected from realistic information and consequently saw a need to filter information to carer clients. Health professionals' beliefs may cause them to restrict information flows, which can limit carers' ability to make decisions, and limit health services' ability to improve partnering and shared decision making. In an era where information is freely available to those with the resources to access it, we question whether health professionals should filter information.

Psychosocial work environment and mental health--a meta-analytic review.

PubMed

Stansfeld, Stephen; Candy, Bridget

2006-12-01

To clarify the associations between psychosocial work stressors and mental ill health, a meta-analysis of psychosocial work stressors and common mental disorders was undertaken using longitudinal studies identified through a systematic literature review. The review used a standardized search strategy and strict inclusion and quality criteria in seven databases in 1994-2005. Papers were identified from 24,939 citations covering social determinants of health, 50 relevant papers were identified, 38 fulfilled inclusion criteria, and 11 were suitable for a meta-analysis. The Comprehensive Meta-analysis Programme was used for decision authority, decision latitude, psychological demands, and work social support, components of the job-strain and iso-strain models, and the combination of effort and reward that makes up the effort-reward imbalance model and job insecurity. Cochran's Q statistic assessed the heterogeneity of the results, and the I2 statistic determined any inconsistency between studies. Job strain, low decision latitude, low social support, high psychological demands, effort-reward imbalance, and high job insecurity predicted common mental disorders despite the heterogeneity for psychological demands and social support among men. The strongest effects were found for job strain and effort-reward imbalance. This meta-analysis provides robust consistent evidence that (combinations of) high demands and low decision latitude and (combinations of) high efforts and low rewards are prospective risk factors for common mental disorders and suggests that the psychosocial work environment is important for mental health. The associations are not merely explained by response bias. The impact of work stressors on common mental disorders differs for women and men.

Shaping the Conversation: A Secondary Analysis of Reproductive Decision-Making Among Black Mothers with HIV

PubMed Central

Amutah, Ndidiamaka N.; Gifuni, Jacqueline; Wesley, Yvonne

2016-01-01

The purpose of this qualitative secondary data analysis is to examine the major influencers on mothers with HIV in their childbearing decisions, as well as how those influencers shape conversations with clinicians and health-care providers regarding HIV treatment and prevention. The original study gained insight into the reproductive decision-making of mothers with HIV. By analyzing a subsample of 15 interviews from an original cohort of 25 participants in the earlier study, three major themes were identified as follows: (1) family members, not health-care providers, influence reproductive decisions; (2) negative attitudes toward subsequent pregnancies are mainly due to HIV transmission; and (3) birth control decisions were predominately supported by family members, while health-care providers were not consulted. PMID:27158227

Barriers, facilitators and views about next steps to implementing supports for evidence-informed decision-making in health systems: a qualitative study.

PubMed

Ellen, Moriah E; Léon, Grégory; Bouchard, Gisèle; Ouimet, Mathieu; Grimshaw, Jeremy M; Lavis, John N

2014-12-05

Mobilizing research evidence for daily decision-making is challenging for health system decision-makers. In a previous qualitative paper, we showed the current mix of supports that Canadian health-care organizations have in place and the ones that are perceived to be helpful to facilitate the use of research evidence in health system decision-making. Factors influencing the implementation of such supports remain poorly described in the literature. Identifying the barriers to and facilitators of different interventions is essential for implementation of effective, context-specific, supports for evidence-informed decision-making (EIDM) in health systems. The purpose of this study was to identify (a) barriers and facilitators to implementing supports for EIDM in Canadian health-care organizations, (b) views about emerging development of supports for EIDM, and (c) views about the priorities to bridge the gaps in the current mix of supports that these organizations have in place. This qualitative study was conducted in three types of health-care organizations (regional health authorities, hospitals, and primary care practices) in two Canadian provinces (Ontario and Quebec). Fifty-seven in-depth semi-structured telephone interviews were conducted with senior managers, library managers, and knowledge brokers from health-care organizations that have already undertaken strategic initiatives in knowledge translation. The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. Limited resources (i.e., money or staff), time constraints, and negative attitudes (or resistance) toward change were the most frequently identified barriers to implementing supports for EIDM. Genuine interest from health system decision-makers, notably their willingness to invest money and resources and to create a knowledge translation culture over time in health-care organizations, was the most frequently identified facilitator to implementing supports for EIDM. The most frequently cited views about emerging development of supports for EIDM were implementing accessible and efficient systems to support the use of research in decision-making (e.g., documentation and reporting tools, communication tools, and decision support tools) and developing and implementing an infrastructure or position where the accountability for encouraging knowledge use lies. The most frequently stated priorities for bridging the gaps in the current mix of supports that these organizations have in place were implementing technical infrastructures to support research use and to ensure access to research evidence and establishing formal or informal ties to researchers and knowledge brokers outside the organization who can assist in EIDM. These results provide insights on the type of practical implementation imperatives involved in supporting EIDM.

ENABLING SMART MANUFACTURING TECHNOLOGIES FOR DECISION-MAKING SUPPORT

PubMed Central

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

2017-01-01

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

A work-centered cognitively based architecture for decision support: the work-centered infomediary layer (WIL) model

NASA Astrophysics Data System (ADS)

Zachary, Wayne; Eggleston, Robert; Donmoyer, Jason; Schremmer, Serge

2003-09-01

Decision-making is strongly shaped and influenced by the work context in which decisions are embedded. This suggests that decision support needs to be anchored by a model (implicit or explicit) of the work process, in contrast to traditional approaches that anchor decision support to either context free decision models (e.g., utility theory) or to detailed models of the external (e.g., battlespace) environment. An architecture for cognitively-based, work centered decision support called the Work-centered Informediary Layer (WIL) is presented. WIL separates decision support into three overall processes that build and dynamically maintain an explicit context model, use the context model to identify opportunities for decision support and tailor generic decision-support strategies to the current context and offer them to the system-user/decision-maker. The generic decision support strategies include such things as activity/attention aiding, decision process structuring, work performance support (selective, contextual automation), explanation/ elaboration, infosphere data retrieval, and what if/action-projection and visualization. A WIL-based application is a work-centered decision support layer that provides active support without intent inferencing, and that is cognitively based without requiring classical cognitive task analyses. Example WIL applications are detailed and discussed.

Soft System Analysis to Integrate Technology & Human in Controller Workstation

DOT National Transportation Integrated Search

2011-10-16

Computer-based decision support tools (DST), : shared information, and other forms of automation : are increasingly being planned for use by controllers : and pilots to support Air Traffic Management (ATM) : and Air Traffic Control (ATC) in the Next ...

Arctic Collaborative Environment: A New Multi-National Partnership for Arctic Science and Decision Support

NASA Technical Reports Server (NTRS)

Laymon, Charles A,; Kress, Martin P.; McCracken, Jeff E.; Spehn, Stephen L.; Tanner, Steve

2011-01-01

The Arctic Collaborative Environment (ACE) project is a new international partnership for information sharing to meet the challenges of addressing Arctic. The goal of ACE is to create an open source, web-based, multi-national monitoring, analysis, and visualization decision-support system for Arctic environmental assessment, management, and sustainability. This paper will describe the concept, system architecture, and data products that are being developed and disseminated among partners and independent users through remote access.

Sustainability Tools Inventory - Initial Gaps Analysis | Science ...

EPA Pesticide Factsheets

This report identifies a suite of tools that address a comprehensive set of community sustainability concerns. The objective is to discover whether "gaps" exist in the tool suite’s analytic capabilities. These tools address activities that significantly influence resource consumption, waste generation, and hazard generation including air pollution and greenhouse gases. In addition, the tools have been evaluated using four screening criteria: relevance to community decision making, tools in an appropriate developmental stage, tools that may be transferrable to situations useful for communities, and tools with requiring skill levels appropriate to communities. This document provides an initial gap analysis in the area of community sustainability decision support tools. It provides a reference to communities for existing decision support tools, and a set of gaps for those wishing to develop additional needed tools to help communities to achieve sustainability. It contributes to SHC 1.61.4

Overcoming barriers to cancer-helpline professionals providing decision support for callers: an implementation study.

PubMed

Stacey, Dawn; Chambers, Suzanne K; Jacobsen, Mary Jane; Dunn, Jeff

2008-11-01

To evaluate the effect of an intervention on healthcare professionals' perceptions of barriers influencing their provision of decision support for callers facing cancer-related decisions. A pre- and post-test study guided by the Ottawa Model of Research Use. Australian statewide cancer call center that provides public access to information and supportive cancer services. 34 nurses, psychologists, and other allied healthcare professionals at the cancer call center. Participants completed baseline measures and, subsequently, were exposed to an intervention that included a decision support tutorial, coaching protocol, and skill-building workshop. Strategies were implemented to address organizational barriers. Perceived barriers and facilitators influencing provision of decision support, decision support knowledge, quality of decision support provided to standardized callers, and call length. Postintervention participants felt more prepared, confident in providing decision support, and aware of decision support resources. They had a stronger belief that providing decision support was within their role. Participants significantly improved their knowledge and provided higher-quality decision support to standardized callers without changing call length. The implementation intervention overcame several identified barriers that influenced call center professionals when providing decision support. Nurses and other helpline professionals have the potential to provide decision support designed to help callers understand cancer information, clarify their values associated with their options, and reduce decisional conflict. However, they require targeted education and organizational interventions to reduce their perceived barriers to providing decision support.

Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model

PubMed Central

2016-01-01

The omnipresent need for optimisation requires constant improvements of companies’ business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and “what-if” scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results. PMID:26871694

A pathway to personalization of integrated treatment: informatics and decision science in psychiatric rehabilitation.

PubMed

Spaulding, William; Deogun, Jitender

2011-09-01

Personalization of treatment is a current strategic goal for improving health care. Integrated treatment approaches such as psychiatric rehabilitation benefit from personalization because they involve matching diverse arrays of treatment options to individually unique profiles of need. The need for personalization is evident in the heterogeneity of people with severe mental illness and in the findings of experimental psychopathology. One pathway to personalization lies in analysis of the judgments and decision making of human experts and other participants as they respond to complex circumstances in pursuit of treatment and rehabilitation goals. Such analysis is aided by computer simulation of human decision making, which in turn informs development of computerized clinical decision support systems. This inspires a research program involving concurrent development of databases, domain ontology, and problem-solving algorithms, toward the goal of personalizing psychiatric rehabilitation through human collaboration with intelligent cyber systems. The immediate hurdle is to demonstrate that clinical decisions beyond diagnosis really do affect outcome. This can be done by supporting the hypothesis that a human treatment team with access to a reasonably comprehensive clinical database that tracks patient status and treatment response over time achieves better outcome than a treatment team without such access, in a controlled experimental trial. Provided the hypothesis can be supported, the near future will see prototype systems that can construct an integrated assessment, formulation, and rehabilitation plan from clinical assessment data and contextual information. This will lead to advanced systems that collaborate with human decision makers to personalize psychiatric rehabilitation and optimize outcome.

Identifying components in consent information needed to support informed decision making about trial participation: An interview study with women managing cancer.

PubMed

Abhyankar, Purva; Velikova, Galina; Summers, Barbara; Bekker, Hilary L

2016-07-01

Research governance requires patients give informed consent to participate in clinical trials. However, there are concerns that consent information may not support patient participation decisions. This study investigates the utility of consent information in supporting women's trial participation decisions when receiving treatment for cancer. An interview study with women receiving cancer treatments at a medical oncology outpatient clinic in Yorkshire (UK). All women over 18 years, not admitted to a hospital ward and who had currently or previously been invited to take part in a trial were invited to take part in the study over a three month period. Interviews were audio-tape recorded, transcribed and analysed using thematic analysis. Of those eligible (n = 41), 21 women with breast (n = 11), ovarian (n = 8) and endometrial (n = 2) cancer participated (mean age = 57 years). Eighteen had made at least one trial decision and three were considering taking part in a trial. Findings are synthesised under two analytical themes: 1) Influence of the cancer and cancer treatment context on decision making for trial participation; and 2) Experiences of the consenting process and their influence on decision making. Designing trial information to represent explicitly the trial participation decision as being between standard care and study-related care options is more likely to effectively support patients in making informed decisions between standard care treatments and taking part in a trial. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

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.

Data Mashups: Potential Contribution to Decision Support on Climate Change and Health

PubMed Central

Fleming, Lora E.; Haines, Andy; Golding, Brian; Kessel, Anthony; Cichowska, Anna; Sabel, Clive E.; Depledge, Michael H.; Sarran, Christophe; Osborne, Nicholas J.; Whitmore, Ceri; Cocksedge, Nicola; Bloomfield, Daniel

2014-01-01

Linking environmental, socioeconomic and health datasets provides new insights into the potential associations between climate change and human health and wellbeing, and underpins the development of decision support tools that will promote resilience to climate change, and thus enable more effective adaptation. This paper outlines the challenges and opportunities presented by advances in data collection, storage, analysis, and access, particularly focusing on “data mashups”. These data mashups are integrations of different types and sources of data, frequently using open application programming interfaces and data sources, to produce enriched results that were not necessarily the original reason for assembling the raw source data. As an illustration of this potential, this paper describes a recently funded initiative to create such a facility in the UK for use in decision support around climate change and health, and provides examples of suitable sources of data and the purposes to which they can be directed, particularly for policy makers and public health decision makers. PMID:24499879

Data mashups: potential contribution to decision support on climate change and health.

PubMed

Fleming, Lora E; Haines, Andy; Golding, Brian; Kessel, Anthony; Cichowska, Anna; Sabel, Clive E; Depledge, Michael H; Sarran, Christophe; Osborne, Nicholas J; Whitmore, Ceri; Cocksedge, Nicola; Bloomfield, Daniel

2014-02-04

Linking environmental, socioeconomic and health datasets provides new insights into the potential associations between climate change and human health and wellbeing, and underpins the development of decision support tools that will promote resilience to climate change, and thus enable more effective adaptation. This paper outlines the challenges and opportunities presented by advances in data collection, storage, analysis, and access, particularly focusing on "data mashups". These data mashups are integrations of different types and sources of data, frequently using open application programming interfaces and data sources, to produce enriched results that were not necessarily the original reason for assembling the raw source data. As an illustration of this potential, this paper describes a recently funded initiative to create such a facility in the UK for use in decision support around climate change and health, and provides examples of suitable sources of data and the purposes to which they can be directed, particularly for policy makers and public health decision makers.

Teenagers' perceptions of factors affecting decision-making competence in the management of type 1 diabetes.

PubMed

Viklund, Gunnel; Wikblad, Karin

2009-12-01

Decision-making is an important prerequisite for empowerment. The aim of this study was to explore teenagers' perceptions of factors affecting decision-making competence in diabetes management. A previous study that assessed an empowerment programme for teenagers with diabetes showed no effects on metabolic control or empowerment outcomes, which is not in accordance with results from studies on adult diabetes patients. The definition of empowerment highlights the patient's own responsibility for decision-making. Earlier studies have shown that many teenagers' may not be mature in decision-making competence until late adolescence. To explore the significance of decision-making competence on the effectiveness of empowerment education we wanted to explore teenagers' own view on factors affecting this competence. An explorative, qualitative interview study was conducted with 31 teenagers with type 1 diabetes, aged 12-17 years. The teenagers were interviewed two weeks after completing an empowerment education programme. The interviews were analysed using qualitative content analysis. Five categories stood out as important for decision-making competence: cognitive maturity, personal qualities, experience, social network and parent involvement. Based on the content in the interviews and the five categories, we made an interpretation and formulated an overall theme: 'Teenagers deserve respect and support for their short-comings during the maturity process'. Our conclusion is that teenagers deserve respect for their immature decision-making competence. Decision-making competence was described as cognitive abilities, personal qualifications and experience. To compensate for the deficiencies the teenagers deserve constructive support from their social network and the essential support is expected to come from their parents. These findings can be useful for diabetes team members in supporting teenagers with diabetes and their parents both in individual meetings and when planning and delivering group education.

Temporal reasoning for decision support in medicine.

PubMed

Augusto, Juan Carlos

2005-01-01

Handling time-related concepts is essential in medicine. During diagnosis it can make a substantial difference to know the temporal order in which some symptoms occurred or for how long they lasted. During prognosis the potential evolutions of a disease are conceived as a description of events unfolding in time. In therapy planning the different steps of treatment must be applied in a precise order, with a given frequency and for a certain span of time in order to be effective. This article offers a survey on the use of temporal reasoning for decision support-related tasks in medicine. Key publications of the area, mainly circumscribed to the latest two decades, are reviewed and classified according to three important stages of patient treatment requiring decision support: diagnosis, prognosis and therapy planning/management. Other complementary publications, like those on time-centered information storage and retrieval, are also considered as they provide valuable support to the above mentioned three stages. Key areas are highlighted and used to organize the latest contributions. The survey of previous research is followed by an analysis of what can still be improved and what is needed to make the next generation of decision support systems for medicine more effective. It can be observed that although the area has been considerably developed, there are still areas where more research is needed to make time-based systems of widespread use in decision support-related areas of medicine. Several suggestions for further exploration are proposed as a result of the survey.

Towards generic online multicriteria decision support in patient-centred health care.

PubMed

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

2015-10-01

To introduce a new online generic decision support system based on multicriteria decision analysis (MCDA), implemented in practical and user-friendly software (Annalisa©). All parties in health care lack a simple and generic way to picture and process the decisions to be made in pursuit of improved decision making and more informed choice within an overall philosophy of person- and patient-centred care. The MCDA-based system generates patient-specific clinical guidance in the form of an opinion as to the merits of the alternative options in a decision, which are all scored and ranked. The scores for each option combine, in a simple expected value calculation, the best estimates available now for the performance of those options on patient-determined criteria, with the individual patient's preferences, expressed as importance weightings for those criteria. The survey software within which the Annalisa file is embedded (Elicia©) customizes and personalizes the presentation and inputs. Principles relevant to the development of such decision-specific MCDA-based aids are noted and comparisons with alternative implementations presented. The necessity to trade-off practicality (including resource constraints) with normative rigour and empirical complexity, in both their development and delivery, is emphasized. The MCDA-/Annalisa-based decision support system represents a prescriptive addition to the portfolio of decision-aiding tools available online to individuals and clinicians interested in pursuing shared decision making and informed choice within a commitment to transparency in relation to both the evidence and preference bases of decisions. Some empirical data establishing its usability are provided. © 2013 The Authors. Health Expectations published by John Wiley & Sons Ltd.

Advanced Satellite Workstation - An integrated workstation environment for operational support of satellite system planning and analysis

NASA Astrophysics Data System (ADS)

Hamilton, Marvin J.; Sutton, Stewart A.

A prototype integrated environment, the Advanced Satellite Workstation (ASW), which was developed and delivered for evaluation and operator feedback in an operational satellite control center, is described. The current ASW hardware consists of a Sun Workstation and Macintosh II Workstation connected via an ethernet Network Hardware and Software, Laser Disk System, Optical Storage System, and Telemetry Data File Interface. The central objective of ASW is to provide an intelligent decision support and training environment for operator/analysis of complex systems such as satellites. Compared to the many recent workstation implementations that incorporate graphical telemetry displays and expert systems, ASW provides a considerably broader look at intelligent, integrated environments for decision support, based on the premise that the central features of such an environment are intelligent data access and integrated toolsets.

Managerial Analysis and Decision Support: A Guidebook and Case Studies

ERIC Educational Resources Information Center

National Association of College and University Business Officers (NJ3), 2004

2004-01-01

Developed and edited by the National Association of College and University Business Officers' (NACUBO's) Accounting Principles Council, this guidebook, written by highly experienced, seasoned college and university leaders, is designed to help readers make sense of today's world and provide the right tools to make the right decisions. The book,…

Analysis of Wastewater and Water System Renewal Decision-Making Tools and Approaches

EPA Science Inventory

In regards to the development of software for decision support for pipeline renewal, most of the attention to date has been paid to the development of asset management models which help an owner decide on which portions of a system to prioritize for needed actions. There has not ...

A Cross-National CAI Tool To Support Learning Operations Decision-Making and Market Analysis.

ERIC Educational Resources Information Center

Mockler, Robert J.; Afanasiev, Mikhail Y.; Dologite, Dorothy G.

1999-01-01

Describes bicultural (United States and Russia) development of a computer-aided instruction (CAI) tool to learn management decision-making using information systems technologies. The program has been used with undergraduate and graduate students in both countries; it integrates free and controlled market concepts and combines traditional computer…

Scenario Analysis: Evaluating Biodiversity Response to Forecasted Land-Use Change in the San Pedro River Basin (U.S.-Mexico)

EPA Science Inventory

Envisioning and evaluating future scenarios has emerged as a critical component of both science and social decision-making. The ability to assess, report, map, and forecast the life support functions of ecosystems is absolutely critical to our capacity to make informed decisions...

Season ending events, a matter of perspective

Treesearch

Laurie L. Kurth

2010-01-01

Agency managers are often faced with making difficult wildland fire management decisions based on collating a significant amount of information regarding a fire. Supporting the decisions is understanding how long an incident may persist, especially if the fire has potential for resource benefits. Analysis of historical season ending events has occurred since the mid-...

Applying air pollution modelling within a multi-criteria decision analysis framework to evaluate UK air quality policies

NASA Astrophysics Data System (ADS)

Chalabi, Zaid; Milojevic, Ai; Doherty, Ruth M.; Stevenson, David S.; MacKenzie, Ian A.; Milner, James; Vieno, Massimo; Williams, Martin; Wilkinson, Paul

2017-10-01

A decision support system for evaluating UK air quality policies is presented. It combines the output from a chemistry transport model, a health impact model and other impact models within a multi-criteria decision analysis (MCDA) framework. As a proof-of-concept, the MCDA framework is used to evaluate and compare idealized emission reduction policies in four sectors (combustion in energy and transformation industries, non-industrial combustion plants, road transport and agriculture) and across six outcomes or criteria (mortality, health inequality, greenhouse gas emissions, biodiversity, crop yield and air quality legal compliance). To illustrate a realistic use of the MCDA framework, the relative importance of the criteria were elicited from a number of stakeholders acting as proxy policy makers. In the prototype decision problem, we show that reducing emissions from industrial combustion (followed very closely by road transport and agriculture) is more advantageous than equivalent reductions from the other sectors when all the criteria are taken into account. Extensions of the MCDA framework to support policy makers in practice are discussed.

Development, deployment and usability of a point-of-care decision support system for chronic disease management using the recently-approved HL7 decision support service standard.

PubMed

Lobach, David F; Kawamoto, Kensaku; Anstrom, Kevin J; Russell, Michael L; Woods, Peter; Smith, Dwight

2007-01-01

Clinical decision support is recognized as one potential remedy for the growing crisis in healthcare quality in the United States and other industrialized nations. While decision support systems have been shown to improve care quality and reduce errors, these systems are not widely available. This lack of availability arises in part because most decision support systems are not portable or scalable. The Health Level 7 international standard development organization recently adopted a draft standard known as the Decision Support Service standard to facilitate the implementation of clinical decision support systems using software services. In this paper, we report the first implementation of a clinical decision support system using this new standard. This system provides point-of-care chronic disease management for diabetes and other conditions and is deployed throughout a large regional health system. We also report process measures and usability data concerning the system. Use of the Decision Support Service standard provides a portable and scalable approach to clinical decision support that could facilitate the more extensive use of decision support systems.

Development of a decision support system for monitoring, reporting and forecasting ecological conditions of the Appalachian Trail

USGS Publications Warehouse

Wang, Yeqiao; Nemani, Ramakrishna; Dieffenbach, Fred; Stolte, Kenneth; Holcomb, Glenn B.; Robinson, Matt; Reese, Casey C.; McNiff, Marcia; Duhaime, Roland; Tierney, Geri; Mitchell, Brian; August, Peter; Paton, Peter; LaBash, Charles

2010-01-01

This paper introduces a collaborative multi-agency effort to develop an Appalachian Trail (A.T.) MEGA-Transect Decision Support System (DSS) for monitoring, reporting and forecasting ecological conditions of the A.T. and the surrounding lands. The project is to improve decisionmaking on management of the A.T. by providing a coherent framework for data integration, status reporting and trend analysis. The A.T. MEGA-Transect DSS is to integrate NASA multi-platform sensor data and modeling through the Terrestrial Observation and Prediction System (TOPS) and in situ measurements from A.T. MEGA-Transect partners to address identified natural resource priorities and improve resource management decisions.

Nursing in general practice: organizational possibilities for decision latitude, created skill, social support and identity derived from role.

PubMed

Merrick, Eamon; Duffield, Christine; Baldwin, Richard; Fry, Margaret

2012-03-01

This article is a report of a study to describe the factors that support organizational opportunities for practice nurse decision-making and skill development for nurses employed in general practice in New South Wales, Australia. Corresponding to the availability of subsidies from the Australian universal health insurer (Medicare), there has been an increase in the number of nurses employed in general practice. Currently, there is no Australian evidence as to the organizational possibilities for these practice nurses to make decisions, develop their own skills and abilities, derive identity from their role or how their role is influenced by social support. Over a 8-month period in 2008 practice, nurses employed in general practice in the State of New South Wales were invited to complete a 26-item self-administered online questionnaire utilizing constructs from Karaseks (1998) Job Content Questionnaire (valid n = 160). Confirmatory Factor Analysis indicated that all scales demonstrated acceptable levels of internal consistency. Sequential regression models revealed that social support exerts a weak influence on decision latitude (R(2) = 0·07); the addition of self-identity through work significantly improved the predictive ability of the model (R(2) = 0·16). Social support and self-identity through work exerted a negative influence on created skill (R(2) = 0·347), whereas social support was effective in predicting self-identity through work (R(2) = 0·148).   Collegial and supervisory support in the work environment predicts organizational possibilities for practice nurse decision-making. © 2011 Blackwell Publishing Ltd.

Compilation of Theses Abstracts

DTIC Science & Technology

2005-06-01

allies; 2) institutes that focus on the integration of teaching and research in direct support of the four pillars of Joint Visions 2010 and 2020 and...in Performance Based Contracts ................. 7 An Analysis of the Marriage and Dependency Premium Among Active Duty Navy Personnel...Decision Support Tool MASTER OF BUSINESS ADMINISTRATION 8 AN ANALYSIS OF THE MARRIAGE AND DEPENDENCY PREMIUM AMONG ACTIVE DUTY NAVY

Empirical evaluation of decision support systems: Needs, definitions, potential methods, and an example pertaining to waterfowl management

USGS Publications Warehouse

Sojda, R.S.

2007-01-01

Decision support systems are often not empirically evaluated, especially the underlying modelling components. This can be attributed to such systems necessarily being designed to handle complex and poorly structured problems and decision making. Nonetheless, evaluation is critical and should be focused on empirical testing whenever possible. Verification and validation, in combination, comprise such evaluation. Verification is ensuring that the system is internally complete, coherent, and logical from a modelling and programming perspective. Validation is examining whether the system is realistic and useful to the user or decision maker, and should answer the question: “Was the system successful at addressing its intended purpose?” A rich literature exists on verification and validation of expert systems and other artificial intelligence methods; however, no single evaluation methodology has emerged as preeminent. At least five approaches to validation are feasible. First, under some conditions, decision support system performance can be tested against a preselected gold standard. Second, real-time and historic data sets can be used for comparison with simulated output. Third, panels of experts can be judiciously used, but often are not an option in some ecological domains. Fourth, sensitivity analysis of system outputs in relation to inputs can be informative. Fifth, when validation of a complete system is impossible, examining major components can be substituted, recognizing the potential pitfalls. I provide an example of evaluation of a decision support system for trumpeter swan (Cygnus buccinator) management that I developed using interacting intelligent agents, expert systems, and a queuing system. Predicted swan distributions over a 13-year period were assessed against observed numbers. Population survey numbers and banding (ringing) studies may provide long term data useful in empirical evaluation of decision support.

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

PubMed

Allen, Will; Cruz, Jennyffer; Warburton, Bruce

2017-06-01

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

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

NASA Astrophysics Data System (ADS)

Allen, Will; Cruz, Jennyffer; Warburton, Bruce

2017-06-01

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

Implementation of a web-based national child health-care programme in a local context: A complex facilitator role.

PubMed

Tell, Johanna; Olander, Ewy; Anderberg, Peter; Berglund, Johan Sanmartin

2018-02-01

The aim of this study was to investigate child health-care coordinators' experiences of being a facilitator for the implementation of a new national child health-care programme in the form of a web-based national guide. The study was based on eight remote, online focus groups, using Skype for Business. A qualitative content analysis was performed. The analysis generated three categories: adapt to a local context, transition challenges and led by strong incentives. There were eight subcategories. In the latent analysis, the theme 'Being a facilitator: a complex role' was formed to express the child health-care coordinators' experiences. Facilitating a national guideline or decision support in a local context is a complex task that requires an advocating and mediating role. For successful implementation, guidelines and decision support, such as a web-based guide and the new child health-care programme, must match professional consensus and needs and be seen as relevant by all. Participation in the development and a strong bottom-up approach was important, making the web-based guide and the programme relevant to whom it is intended to serve, and for successful implementation. The study contributes valuable knowledge when planning to implement a national web-based decision support and policy programme in a local health-care context.

Risk assessment and decision making about in-labour transfer from rural maternity care: a social judgment and signal detection analysis

PubMed Central

2012-01-01

Background The importance of respecting women’s wishes to give birth close to their local community is supported by policy in many developed countries. However, persistent concerns about the quality and safety of maternity care in rural communities have been expressed. Safe childbirth in rural communities depends on good risk assessment and decision making as to whether and when the transfer of a woman in labour to an obstetric led unit is required. This is a difficult decision. Wide variation in transfer rates between rural maternity units have been reported suggesting different decision making criteria may be involved; furthermore, rural midwives and family doctors report feeling isolated in making these decisions and that staff in urban centres do not understand the difficulties they face. In order to develop more evidence based decision making strategies greater understanding of the way in which maternity care providers currently make decisions is required. This study aimed to examine how midwives working in urban and rural settings and obstetricians make intrapartum transfer decisions, and describe sources of variation in decision making. Methods The study was conducted in three stages. 1. 20 midwives and four obstetricians described factors influencing transfer decisions. 2. Vignettes depicting an intrapartum scenario were developed based on stage one data. 3. Vignettes were presented to 122 midwives and 12 obstetricians who were asked to assess the level of risk in each case and decide whether to transfer or not. Social judgment analysis was used to identify the factors and factor weights used in assessment. Signal detection analysis was used to identify participants’ ability to distinguish high and low risk cases and personal decision thresholds. Results When reviewing the same case information in vignettes midwives in different settings and obstetricians made very similar risk assessments. Despite this, a wide range of transfer decisions were still made, suggesting that the main source of variation in decision making and transfer rates is not in the assessment but the personal decision thresholds of clinicians. Conclusions Currently health care practice focuses on supporting or improving decision making through skills training and clinical guidelines. However, these methods alone are unlikely to be effective in improving consistency of decision making. PMID:23114289

Environmental impact assessment of transportation projects: An analysis using an integrated GIS, remote sensing, and spatial modeling approach

NASA Astrophysics Data System (ADS)

El-Gafy, Mohamed Anwar

Transportation projects will have impact on the environment. The general environmental pollution and damage caused by roads is closely associated with the level of economic activity. Although Environmental Impact Assessments (EIAs) are dependent on geo-spatial information in order to make an assessment, there are no rules per se how to conduct an environmental assessment. Also, the particular objective of each assessment is dictated case-by-case, based on what information and analyses are required. The conventional way of Environmental Impact Assessment (EIA) study is a time consuming process because it has large number of dependent and independent variables which have to be taken into account, which also have different consequences. With the emergence of satellite remote sensing technology and Geographic Information Systems (GIS), this research presents a new framework for the analysis phase of the Environmental Impact Assessment (EIA) for transportation projects based on the integration between remote sensing technology, geographic information systems, and spatial modeling. By integrating the merits of the map overlay method and the matrix method, the framework analyzes comprehensively the environmental vulnerability around the road and its impact on the environment. This framework is expected to: (1) improve the quality of the decision making process, (2) be applied both to urban and inter-urban projects, regardless of transport mode, and (3) present the data and make the appropriate analysis to support the decision of the decision-makers and allow them to present these data to the public hearings in a simple manner. Case studies, transportation projects in the State of Florida, were analyzed to illustrate the use of the decision support framework and demonstrate its capabilities. This cohesive and integrated system will facilitate rational decisions through cost effective coordination of environmental information and data management that can be tailored to specific projects. The framework would facilitate collecting, organizing, analyzing, archiving, and coordinating the information and data necessary to support technical and policy transportation decisions.

The conceptual foundation of environmental decision support.

PubMed

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

2015-05-01

Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how societal preferences can be described and elicited, and (iii) how these concepts can best be used to support communication with authorities, politicians, and the public in environmental management. The goal of this paper is to discuss key requirements for a conceptual framework to address these issues and to suggest how these can best be met. We argue that a combination of probability theory and scenario planning with multi-attribute utility theory fulfills these requirements, and discuss adaptations and extensions of these theories to improve their application for supporting environmental decision making. With respect to (i) we suggest the use of intersubjective probabilities, if required extended to imprecise probabilities, to describe the current state of scientific knowledge. To address (ii), we emphasize the importance of value functions, in addition to utilities, to support decisions under risk. We discuss the need for testing "non-standard" value aggregation techniques, the usefulness of flexibility of value functions regarding attribute data availability, the elicitation of value functions for sub-objectives from experts, and the consideration of uncertainty in value and utility elicitation. With respect to (iii), we outline a well-structured procedure for transparent environmental decision support that is based on a clear separation of scientific prediction and societal valuation. We illustrate aspects of the suggested methodology by its application to river management in general and with a small, didactical case study on spatial river rehabilitation prioritization. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Hydra: A web-based system for cardiovascular analysis, diagnosis and treatment.

PubMed

Novo, J; Hermida, A; Ortega, M; Barreira, N; Penedo, M G; López, J E; Calvo, C

2017-02-01

Cardiovascular (CV) risk stratification is a highly complex process involving an extensive set of clinical trials to support the clinical decision-making process. There are many clinical conditions (e.g. diabetes, obesity, stress, etc.) that can lead to the early diagnosis or establishment of cardiovascular disease. In order to determine all these clinical conditions, a complete set of clinical patient analyses is typically performed, including a physical examination, blood analysis, electrocardiogram, blood pressure (BP) analysis, etc. This article presents a web-based system, called Hydra, which integrates a full and detailed set of services and functionalities for clinical decision support in order to help and improve the work of clinicians in cardiovascular patient diagnosis, risk assessment, treatment and monitoring over time. Hydra integrates a number of different services: a service for inputting all the information gathered by specialists (physical examination, habits, BP, blood analysis, electrocardiogram, etc.); a tool to automatically determine the CV risk stratification, including well-known standard risk stratification tables; and, finally, various tools to incorporate, analyze and graphically present the records of the ambulatory BP monitoring that provides BP analysis over a given period of time (24 or 48 hours). In addition, the platform presents a set of reports derived from all the information gathered from the patient in order to support physicians in their clinical decisions. Hydra was tested and validated in a real domain. In particular, internal medicine specialists at the Hypertension Unit of the Santiago de Compostela University Hospital (CHUS) validated the platform and used it in different clinical studies to demonstrate its utility. It was observed that the platform increased productivity and accuracy in the assessment of patient data yielding a cost reduction in clinical practice. This paper proposes a complete platform that includes different services for cardiovascular clinical decision support. It was also run as a web-based application to facilitate its use by clinicians, who can access the platform from any remote computer with Internet access. Hydra also includes different automated methods to facilitate the physicians' work and avoid potential errors in the analysis of patient data. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

ENERGY PRODUCTION AND RESIDENTIAL HEATING: TAXATION, SUBSIDIES, AND COMPARATIVE COSTS

EPA Science Inventory

This analysis is in support of the Ohio River Basin Energy Study (ORBES), a multidisciplinary policy research program supported by the Environmental Protection Agency. It examines the effect of economic incentives on public and private decisions affecting energy production and us...

Attitudes towards poverty, organizations, ethics and morals: Israeli social workers' shared decision making.

PubMed

Levin, Lia; Schwartz-Tayri, Talia

2017-06-01

Partnerships between service users and social workers are complex in nature and can be driven by both personal and contextual circumstances. This study sought to explore the relationship between social workers' involvement in shared decision making with service users, their attitudes towards service users in poverty, moral standards and health and social care organizations' policies towards shared decision making. Based on the responses of 225 licensed social workers from health and social care agencies in the public, private and third sectors in Israel, path analysis was used to test a hypothesized model. Structural attributions for poverty contributed to attitudes towards people who live in poverty, which led to shared decision making. Also, organizational support in shared decision making, and professional moral identity, contributed to ethical behaviour which led to shared decision making. The results of this analysis revealed that shared decision making may be a scion of branched roots planted in the relationship between ethics, organizations and Stigma. © 2016 The Authors. Health Expectations Published by John Wiley & Sons Ltd.

Patient and caregiver perspectives on decision support for symptom and quality of life management during cancer treatment: Implications for eHealth.

PubMed

Cooley, Mary E; Nayak, Manan M; Abrahm, Janet L; Braun, Ilana M; Rabin, Michael S; Brzozowski, Jane; Lathan, Christopher; Berry, Donna L

2017-08-01

Adequate symptom and quality-of-life (SQL) management is a priority during cancer treatment. eHealth is a timely way to enhance patient-engagement, facilitate communication, and improve health outcomes. The objectives of this study were to describe patient and caregivers' perspectives for providing, processing, and managing SQL data to enhance communication and identify desired components for decision support. Data were collected from 64 participants through questionnaires and focus groups. Analysis was conducted using NVivo. Open and axial coding was completed, grouping commonalities and large constructs into nodes to identify and synthesize themes. Face-to-face meetings with clinicians were the prime time to communicate, and patients strove to understand treatment options and the effect on SQL by bringing caregivers to their visits, taking notes, tracking symptoms, and creating portable health records. Patients/caregivers struggled to self-manage their symptoms and were uncertain when to contact clinicians when experiencing uncontrolled symptoms. Most participants identified eHealth solutions for decision support. However, 38% of participants (n = 24) rarely used computers and identified non-eHealth options for decision support. Core components for both eHealth and non-eHealth systems were access to (1) cancer information, (2) medical records, (3) peer support, and (4) improved support and understanding on when to contact clinicians. Patients were faced with an overwhelming amount of information and relied on their caregivers to help navigate the complexities of cancer care and self-manage SQL. Health technologies can provide informational support; however, decision support needs to span multiple venues to avoid increasing disparities caused by a digital divide. Copyright © 2017 John Wiley & Sons, Ltd.

Decision Support | Solar Research | NREL

Science.gov Websites

informed solar decision making with credible, objective, accessible, and timely resources. Solar Energy Decision Support Decision Support NREL provides technical and analytical support to support provide unbiased information on solar policies and issues for state and local government decision makers

Using systematic reviews and meta-analyses to support regulatory decision making for neurotoxicants: lessons learned from a case study of PCBs.

PubMed

Goodman, Michael; Squibb, Katherine; Youngstrom, Eric; Anthony, Laura Gutermuth; Kenworthy, Lauren; Lipkin, Paul H; Mattison, Donald R; Lakind, Judy S

2010-06-01

Epidemiologic weight-of-evidence reviews to support regulatory decision making regarding the association between environmental chemical exposures and neurodevelopmental outcomes in children are often complicated by lack of consistency across studies. We examined prospective cohort studies evaluating the relation between prenatal and neonatal exposure to polychlorinated biphenyls (PCBs) and neurodevelopment in children to assess the feasibility of conducting a meta-analysis to support decision making. We described studies in terms of exposure and end point categorization, statistical analysis, and reporting of results. We used this evaluation to assess the feasibility of grouping studies into reasonably uniform categories. The current literature includes 11 cohorts of children for whom effects from prenatal or neonatal PCB exposures were assessed. The most consistently used tests included Brazelton's Neonatal Behavioral Assessment Scale, the neurologic optimality score in the neonatal period, the Bayley Scales of Infant Development at 5-8 months of age, and the McCarthy Scales of Children's Abilities in 5-year-olds. Despite administering the same tests at similar ages, the studies were too dissimilar to allow a meaningful quantitative examination of outcomes across cohorts. These analyses indicate that our ability to conduct weight-of-evidence assessments of the epidemiologic literature on neurotoxicants may be limited, even in the presence of multiple studies, if the available study methods, data analysis, and reporting lack comparability. Our findings add support to previous calls for establishing consensus standards for the conduct, analysis, and reporting of epidemiologic studies in general, and for those evaluating the effects of potential neurotoxic exposures in particular.

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

PubMed

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.

Performance evaluation of the machine learning algorithms used in inference mechanism of a medical decision support system.

PubMed

Bal, Mert; Amasyali, M Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse

2014-01-01

The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis

PubMed Central

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization. PMID:29377956

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis.

PubMed

Zu, Xianghuan; Yang, Chuanlei; Wang, Hechun; Wang, Yinyan

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization.

Development of a Reference Image Collection Library for Histopathology Image Processing, Analysis and Decision Support Systems Research.

PubMed

Kostopoulos, Spiros; Ravazoula, Panagiota; Asvestas, Pantelis; Kalatzis, Ioannis; Xenogiannopoulos, George; Cavouras, Dionisis; Glotsos, Dimitris

2017-06-01

Histopathology image processing, analysis and computer-aided diagnosis have been shown as effective assisting tools towards reliable and intra-/inter-observer invariant decisions in traditional pathology. Especially for cancer patients, decisions need to be as accurate as possible in order to increase the probability of optimal treatment planning. In this study, we propose a new image collection library (HICL-Histology Image Collection Library) comprising 3831 histological images of three different diseases, for fostering research in histopathology image processing, analysis and computer-aided diagnosis. Raw data comprised 93, 116 and 55 cases of brain, breast and laryngeal cancer respectively collected from the archives of the University Hospital of Patras, Greece. The 3831 images were generated from the most representative regions of the pathology, specified by an experienced histopathologist. The HICL Image Collection is free for access under an academic license at http://medisp.bme.teiath.gr/hicl/ . Potential exploitations of the proposed library may span over a board spectrum, such as in image processing to improve visualization, in segmentation for nuclei detection, in decision support systems for second opinion consultations, in statistical analysis for investigation of potential correlations between clinical annotations and imaging findings and, generally, in fostering research on histopathology image processing and analysis. To the best of our knowledge, the HICL constitutes the first attempt towards creation of a reference image collection library in the field of traditional histopathology, publicly and freely available to the scientific community.

A multiobjective decision support/numerical modeling approach for design and evaluation of shallow landfill burial systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ascough, II, James Clifford

1992-05-01

The capability to objectively evaluate design performance of shallow landfill burial (SLB) systems is of great interest to diverse scientific disciplines, including hydrologists, engineers, environmental scientists, and SLB regulators. The goal of this work was to develop and validate a procedure for the nonsubjective evaluation of SLB designs under actual or simulated environmental conditions. A multiobjective decision module (MDM) based on scoring functions (Wymore, 1988) was implemented to evaluate SLB design performance. Input values to the MDM are provided by hydrologic models. The MDM assigns a total score to each SLB design alternative, thereby allowing for rapid and repeatable designmore » performance evaluation. The MDM was validated for a wide range of SLB designs under different climatic conditions. Rigorous assessment of SLB performance also requires incorporation of hydrologic probabilistic analysis and hydrologic risk into the overall design. This was accomplished through the development of a frequency analysis module. The frequency analysis module allows SLB design event magnitudes to be calculated based on the hydrologic return period. The multiobjective decision and freqeuncy anslysis modules were integrated in a decision support system (DSS) framework, SLEUTH (Shallow Landfill Evaluation Using Transport and Hydrology). SLEUTH is a Microsoft Windows {trademark} application, and is written in the Knowledge Pro Windows (Knowledge Garden, Inc., 1991) development language.« less

Reconciling uncertain costs and benefits in bayes nets for invasive species management

USGS Publications Warehouse

Burgman, M.A.; Wintle, B.A.; Thompson, C.A.; Moilanen, A.; Runge, M.C.; Ben-Haim, Y.

2010-01-01

Bayes nets are used increasingly to characterize environmental systems and formalize probabilistic reasoning to support decision making. These networks treat probabilities as exact quantities. Sensitivity analysis can be used to evaluate the importance of assumptions and parameter estimates. Here, we outline an application of info-gap theory to Bayes nets that evaluates the sensitivity of decisions to possibly large errors in the underlying probability estimates and utilities. We apply it to an example of management and eradication of Red Imported Fire Ants in Southern Queensland, Australia and show how changes in management decisions can be justified when uncertainty is considered. ?? 2009 Society for Risk Analysis.

Using decision analysis to support proactive management of emerging infectious wildlife diseases

USGS Publications Warehouse

Grant, Evan H. Campbell; Muths, Erin L.; Katz, Rachel A.; Canessa, Stefano; Adams, Michael J.; Ballard, Jennifer R.; Berger, Lee; Briggs, Cheryl J.; Coleman, Jeremy; Gray, Matthew J.; Harris, M. Camille; Harris, Reid N.; Hossack, Blake R.; Huyvaert, Kathryn P.; Kolby, Jonathan E.; Lips, Karen R.; Lovich, Robert E.; McCallum, Hamish I.; Mendelson, Joseph R.; Nanjappa, Priya; Olson, Deanna H.; Powers, Jenny G.; Richgels, Katherine L. D.; Russell, Robin E.; Schmidt, Benedikt R.; Spitzen-van der Sluijs, Annemarieke; Watry, Mary Kay; Woodhams, Douglas C.; White, C. LeAnn

2017-01-01

Despite calls for improved responses to emerging infectious diseases in wildlife, management is seldom considered until a disease has been detected in affected populations. Reactive approaches may limit the potential for control and increase total response costs. An alternative, proactive management framework can identify immediate actions that reduce future impacts even before a disease is detected, and plan subsequent actions that are conditional on disease emergence. We identify four main obstacles to developing proactive management strategies for the newly discovered salamander pathogen Batrachochytrium salamandrivorans (Bsal). Given that uncertainty is a hallmark of wildlife disease management and that associated decisions are often complicated by multiple competing objectives, we advocate using decision analysis to create and evaluate trade-offs between proactive (pre-emergence) and reactive (post-emergence) management options. Policy makers and natural resource agency personnel can apply principles from decision analysis to improve strategies for countering emerging infectious diseases.

Assessing the value of healthcare interventions using multi-criteria decision analysis: a review of the literature.

PubMed

Marsh, Kevin; Lanitis, Tereza; Neasham, David; Orfanos, Panagiotis; Caro, Jaime

2014-04-01

The objective of this study is to support those undertaking a multi-criteria decision analysis (MCDA) by reviewing the approaches adopted in healthcare MCDAs to date, how these varied with the objective of the study, and the lessons learned from this experience. Searches of EMBASE and MEDLINE identified 40 studies that provided 41 examples of MCDA in healthcare. Data were extracted on the objective of the study, methods employed, and decision makers' and study authors' reflections on the advantages and disadvantages of the methods. The recent interest in MCDA in healthcare is mirrored in an increase in the application of MCDA to evaluate healthcare interventions. Of the studies identified, the first was published in 1990, but more than half were published since 2011. They were undertaken in 18 different countries, and were designed to support investment (coverage and reimbursement), authorization, prescription, and research funding allocation decisions. Many intervention types were assessed: pharmaceuticals, public health interventions, screening, surgical interventions, and devices. Most used the value measurement approach and scored performance using predefined scales. Beyond these similarities, a diversity of different approaches were adopted, with only limited correspondence between the approach and the type of decision or product. Decision makers consulted as part of these studies, as well as the authors of the studies are positive about the potential of MCDA to improve decision making. Further work is required, however, to develop guidance for those undertaking MCDA.

Combining multi-criteria decision analysis and mini-health technology assessment: A funding decision-support tool for medical devices in a university hospital setting.

PubMed

Martelli, Nicolas; Hansen, Paul; van den Brink, Hélène; Boudard, Aurélie; Cordonnier, Anne-Laure; Devaux, Capucine; Pineau, Judith; Prognon, Patrice; Borget, Isabelle

2016-02-01

At the hospital level, decisions about purchasing new and oftentimes expensive medical devices must take into account multiple criteria simultaneously. Multi-criteria decision analysis (MCDA) is increasingly used for health technology assessment (HTA). One of the most successful hospital-based HTA approaches is mini-HTA, of which a notable example is the Matrix4value model. To develop a funding decision-support tool combining MCDA and mini-HTA, based on Matrix4value, suitable for medical devices for individual patient use in French university hospitals - known as the IDA tool, short for 'innovative device assessment'. Criteria for assessing medical devices were identified from a literature review and a survey of 18 French university hospitals. Weights for the criteria, representing their relative importance, were derived from a survey of 25 members of a medical devices committee using an elicitation technique involving pairwise comparisons. As a test of its usefulness, the IDA tool was applied to two new drug-eluting beads (DEBs) for transcatheter arterial chemoembolization. The IDA tool comprises five criteria and weights for each of two over-arching categories: risk and value. The tool revealed that the two new DEBs conferred no additional value relative to DEBs currently available. Feedback from participating decision-makers about the IDA tool was very positive. The tool could help to promote a more structured and transparent approach to HTA decision-making in French university hospitals. Copyright © 2015 Elsevier Inc. All rights reserved.

Methods Used to Support a Life Cycle of Complex Engineering Products

NASA Astrophysics Data System (ADS)

Zakharova, Alexandra A.; Kolegova, Olga A.; Nekrasova, Maria E.; Eremenko, Andrey O.

2016-08-01

Management of companies involved in the design, development and operation of complex engineering products recognize the relevance of creating systems for product lifecycle management. A system of methods is proposed to support life cycles of complex engineering products, based on fuzzy set theory and hierarchical analysis. The system of methods serves to demonstrate the grounds for making strategic decisions in an environment of uncertainty, allows the use of expert knowledge, and provides interconnection of decisions at all phases of strategic management and all stages of a complex engineering product lifecycle.

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

PubMed

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.

Integrated Modeling and Simulation Verification, Validation, and Accreditation Strategy for Exploration Systems Mission Directorate

NASA Technical Reports Server (NTRS)

Hale, Joseph P.

2006-01-01

Models and simulations (M&S) are critical resources in the exploration of space. They support program management, systems engineering, integration, analysis, test, and operations and provide critical information and data supporting key analyses and decisions (technical, cost and schedule). Consequently, there is a clear need to establish a solid understanding of M&S strengths and weaknesses, and the bounds within which they can credibly support decision-making. Their usage requires the implementation of a rigorous approach to verification, validation and accreditation (W&A) and establishment of formal process and practices associated with their application. To ensure decision-making is suitably supported by information (data, models, test beds) from activities (studies, exercises) from M&S applications that are understood and characterized, ESMD is establishing formal, tailored W&A processes and practices. In addition, to ensure the successful application of M&S within ESMD, a formal process for the certification of analysts that use M&S is being implemented. This presentation will highlight NASA's Exploration Systems Mission Directorate (ESMD) management approach for M&S W&A to ensure decision-makers receive timely information on the model's fidelity, credibility, and quality.

Supporting Valid Decision Making: Uses and Misuses of Assessment Data within the Context of RtI

ERIC Educational Resources Information Center

Ball, Carrie R.; Christ, Theodore J.

2012-01-01

Within an RtI problem-solving context, assessment and decision making generally center around the tasks of problem identification, problem analysis, progress monitoring, and program evaluation. We use this framework to discuss the current state of the literature regarding curriculum based measurement, its technical properties, and its utility for…

An Intelligent Decision Support System for Workforce Forecast

DTIC Science & Technology

2011-01-01

ARIMA ) model to forecast the demand for construction skills in Hong Kong. This model was based...Decision Trees ARIMA Rule Based Forecasting Segmentation Forecasting Regression Analysis Simulation Modeling Input-Output Models LP and NLP Markovian...data • When results are needed as a set of easily interpretable rules 4.1.4 ARIMA Auto-regressive, integrated, moving-average ( ARIMA ) models

Postoptimality analysis in the selection of technology portfolios

NASA Technical Reports Server (NTRS)

Adumitroaie, Virgil; Shelton, Kacie; Elfes, Alberto; Weisbin, Charles R.

2006-01-01

This paper describes an approach for qualifying optimal technology portfolios obtained with a multi-attribute decision support system. The goal is twofold: to gauge the degree of confidence in the optimal solution and to provide the decision-maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy non-technical constraints.

Generalized Cartographic and Simultaneous Representation of Utility Networks for Decision-Support Systems and Crisis Management in Urban Environments

NASA Astrophysics Data System (ADS)

Becker, T.; König, G.

2015-10-01

Cartographic visualizations of crises are used to create a Common Operational Picture (COP) and enforce Situational Awareness by presenting relevant information to the involved actors. As nearly all crises affect geospatial entities, geo-data representations have to support location-specific analysis throughout the decision-making process. Meaningful cartographic presentation is needed for coordinating the activities of crisis manager in a highly dynamic situation, since operators' attention span and their spatial memories are limiting factors during the perception and interpretation process. Situational Awareness of operators in conjunction with a COP are key aspects in decision-making process and essential for making well thought-out and appropriate decisions. Considering utility networks as one of the most complex and particularly frequent required systems in urban environment, meaningful cartographic presentation of multiple utility networks with respect to disaster management do not exist. Therefore, an optimized visualization of utility infrastructure for emergency response procedures is proposed. The article will describe a conceptual approach on how to simplify, aggregate, and visualize multiple utility networks and their components to meet the requirements of the decision-making process and to support Situational Awareness.

Defining the optimal therapy sequence in synchronous resectable liver metastases from colorectal cancer: a decision analysis approach.

PubMed

Van Dessel, E; Fierens, K; Pattyn, P; Van Nieuwenhove, Y; Berrevoet, F; Troisi, R; Ceelen, W

2009-01-01

Approximately 5%-20% of colorectal cancer (CRC) patients present with synchronous potentially resectable liver metastatic disease. Preclinical and clinical studies suggest a benefit of the 'liver first' approach, i.e. resection of the liver metastasis followed by resection of the primary tumour. A formal decision analysis may support a rational choice between several therapy options. Survival and morbidity data were retrieved from relevant clinical studies identified by a Web of Science search. Data were entered into decision analysis software (TreeAge Pro 2009, Williamstown, MA, USA). Transition probabilities including the risk of death from complications or disease progression associated with individual therapy options were entered into the model. Sensitivity analysis was performed to evaluate the model's validity under a variety of assumptions. The result of the decision analysis confirms the superiority of the 'liver first' approach. Sensitivity analysis demonstrated that this assumption is valid on condition that the mortality associated with the hepatectomy first is < 4.5%, and that the mortality of colectomy performed after hepatectomy is < 3.2%. The results of this decision analysis suggest that, in patients with synchronous resectable colorectal liver metastases, the 'liver first' approach is to be preferred. Randomized trials will be needed to confirm the results of this simulation based outcome.

Benefit-cost analysis framework for evaluating inter-city transit investment.

DOT National Transportation Integrated Search

2008-10-01

This report describes the development and application of a benefit/cost analysis (BCA) model to support the evaluation of investment decisions for intercity bus services. The model recognizes two principle types of intercity bus benefits: benefits th...

Clinical intuition in the nursing process and decision-making-A mixed-studies review.

PubMed

Melin-Johansson, Christina; Palmqvist, Rebecca; Rönnberg, Linda

2017-12-01

To review what is characteristic of registered nurses' intuition in clinical settings, in relationships and in the nursing process. Intuition is a controversial concept and nurses believe that there are difficulties in how they should explain their nursing actions or decisions based on intuition. Much of the evidence from the body of research indicates that nurses value their intuition in a variety of clinical settings. More information on how nurses integrate intuition as a core element in daily clinical work would contribute to an improved understanding on how they go about this. Intuition deserves a place in evidence-based activities, where intuition is an important component associated with the nursing process. An integrative review strengthened with a mixed-studies review. Literature searches were conducted in the databases CINAHL, PubMed and PsycINFO, and literature published 1985-2016 were included. The findings in the studies were analysed with content analysis, and the synthesis process entailed a reasoning between the authors. After a quality assessment, 16 studies were included. The analysis and synthesis resulted in three categories. The characteristics of intuition in the nurse's daily clinical activities include application, assertiveness and experiences; in the relationships with patients' intuition include unique connections, mental and bodily responses, and personal qualities; and in the nursing process include support and guidance, component and clues in decision-making, and validating decisions. Intuition is more than simply a "gut feeling," and it is a process based on knowledge and care experience and has a place beside research-based evidence. Nurses integrate both analysis and synthesis of intuition alongside objective data when making decisions. They should rely on their intuition and use this knowledge in clinical practice as a support in decision-making, which increases the quality and safety of patient care. We find that intuition plays a key role in more or less all of the steps in the nursing process as a base for decision-making that supports safe patient care, and is a validated component of nursing clinical care expertise. © 2017 John Wiley & Sons Ltd.

Adult-Onset Type 1 Diabetes: A Qualitative Study of Decision-Making Needs.

PubMed

Jull, Janet; Witteman, Holly O; Ferne, Judi; Yoganathan, Manosila; Stacey, Dawn

2016-04-01

Type 1 diabetes is an autoimmune disease resulting from insulin deficiency and must be carefully managed to prevent serious health complications. Diabetes education and management strategies usually focus on meeting the decision-making needs of children and their families, but little is known about the decisional needs of people with adult-onset type 1 diabetes. The aim of this study was to explore the diabetes-related decision-making needs of people diagnosed with adult-onset type 1 diabetes. An interpretive descriptive qualitative study was conducted. Participants who self-identified as having adult-onset type 1 diabetes were interviewed using a semistructured interview guide. Transcripts were coded to identify needs, supports and barriers using thematic analysis. Participating in the study were 8 adults (2 men, 6 women), ages 33 to 57, with type 1 diabetes for durations of 1 to 20 or more years. Their decision-making needs are summarized in 6 broad themes: 1) people diagnosed with type 1 diabetes are launched into a process of decision-making; 2) being diagnosed with type 1 diabetes means you will always have to make decisions; 3) knowledge is crucial; 4) personal preferences matter; 5) support is critical for decisions about self-care in type 1 diabetes; 6) living with type 1 diabetes means making very individualized decisions about daily life. The findings describe the sudden and ubiquitous nature of type 1 diabetes decision-making and the need to tailor approaches for making care decisions in type 1 diabetes. People diagnosed with adult-onset type 1 diabetes require access to reliable information, support and opportunities for participation in decision-making. Copyright © 2016 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

Implementing EVM Data Analysis Adding Value from a NASA Project Manager's Perspective

NASA Technical Reports Server (NTRS)

Counts, Stacy; Kerby, Jerald

2006-01-01

Data Analysis is one of the keys to an effective Earned Value Management (EVM) Process. Project Managers (PM) must continually evaluate data in assessing the health of their projects. Good analysis of data can assist PMs in making better decisions in managing projects. To better support our P Ms, National Aeronautics and Space Administration (NASA) - Marshall Space Flight Center (MSFC) recently renewed its emphasis on sound EVM data analysis practices and processes, During this presentation we will discuss the approach that MSFC followed in implementing better data analysis across its Center. We will address our approach to effectively equip and support our projects in applying a sound data analysis process. In addition, the PM for the Space Station Biological Research Project will share her experiences of how effective data analysis can benefit a PM in the decision making process. The PM will discuss how the emphasis on data analysis has helped create a solid method for assessing the project s performance. Using data analysis successfully can be an effective and efficient tool in today s environment with increasing workloads and downsizing workforces

More Money for More Opportunity: Financial Support of Community College Systems.

ERIC Educational Resources Information Center

Wattenbarger, James L.; Cage, Bob N.

The main thesis presented is that the need for state-level planning for the community college requires increased state-level financial support, yet, at the same time essential local autonomy must be preserved. Areas such as cost-analysis and program-budgeting techniques that govern state support, the way cost-benefit decisions affect the ideal of…

Development of an integrated medical supply information system

NASA Astrophysics Data System (ADS)

Xu, Eric; Wermus, Marek; Blythe Bauman, Deborah

2011-08-01

The integrated medical supply inventory control system introduced in this study is a hybrid system that is shaped by the nature of medical supply, usage and storage capacity limitations of health care facilities. The system links demand, service provided at the clinic, health care service provider's information, inventory storage data and decision support tools into an integrated information system. ABC analysis method, economic order quantity model, two-bin method and safety stock concept are applied as decision support models to tackle inventory management issues at health care facilities. In the decision support module, each medical item and storage location has been scrutinised to determine the best-fit inventory control policy. The pilot case study demonstrates that the integrated medical supply information system holds several advantages for inventory managers, since it entails benefits of deploying enterprise information systems to manage medical supply and better patient services.

Minimising farm crop protection pressure supported by the multiple functionalities of the DISCUSS indicator set.

PubMed

Wustenberghs, Hilde; Fevery, Davina; Lauwers, Ludwig; Marchand, Fleur; Spanoghe, Pieter

2018-03-15

Sustainable crop protection (SCP) has many facets. Farmers may therefore perceive transition to SCP as very complex. The Dual Indicator Set for Crop Protection Sustainability (DISCUSS) can handle this complexity. To provide targeted support throughout the transition to SCP, complexity capture must be synchronised with the time course of on-farm decision-making. Tool use must be tuned to farmer awareness and appropriate level of data in consecutive stages. This paper thus explores the potential functionalities of DISCUSS in relation to both complexity and time. Results from apple and potato crop protection show three potential functions: DISCUSS can be used as (1) a simulation tool for communication and decision support, (2) an assessment and monitoring tool, and (3) a discussion support tool for farmer groups. Analysis of these functionalities using a framework for guiding on-farm sustainability assessment and strategic decision-making shows how each functionality can support the consecutive steps of transition to SCP, i.e. using the right tool functionality at the right time. Copyright © 2017 Elsevier B.V. All rights reserved.

Utilization of a Multi-Disciplinary Approach to Building Effective Command Centers: Process and Products

DTIC Science & Technology

2005-06-01

cognitive task analysis , organizational information dissemination and interaction, systems engineering, collaboration and communications processes, decision-making processes, and data collection and organization. By blending these diverse disciplines command centers can be designed to support decision-making, cognitive analysis, information technology, and the human factors engineering aspects of Command and Control (C2). This model can then be used as a baseline when dealing with work in areas of business processes, workflow engineering, information management,

[Research applications in digital radiology. Big data and co].

PubMed

Müller, H; Hanbury, A

2016-02-01

Medical imaging produces increasingly complex images (e.g. thinner slices and higher resolution) with more protocols, so that image reading has also become much more complex. More information needs to be processed and usually the number of radiologists available for these tasks has not increased to the same extent. The objective of this article is to present current research results from projects on the use of image data for clinical decision support. An infrastructure that can allow large volumes of data to be accessed is presented. In this way the best performing tools can be identified without the medical data having to leave secure servers. The text presents the results of the VISCERAL and Khresmoi EU-funded projects, which allow the analysis of previous cases from institutional archives to support decision-making and for process automation. The results also represent a secure evaluation environment for medical image analysis. This allows the use of data extracted from past cases to solve information needs occurring when diagnosing new cases. The presented research prototypes allow direct extraction of knowledge from the visual data of the images and to use this for decision support or process automation. Real clinical use has not been tested but several subjective user tests showed the effectiveness and efficiency of the process. The future in radiology will clearly depend on better use of the important knowledge in clinical image archives to automate processes and aid decision-making via big data analysis. This can help concentrate the work of radiologists towards the most important parts of diagnostics.

Neurocognitive Enhancement or Impairment? A Systematic Meta-Analysis of Prescription Stimulant Effects on Processing Speed, Decision-Making, Planning, and Cognitive Perseveration

PubMed Central

Marraccini, Marisa E.; Weyandt, Lisa L.; Rossi, Joseph S.; Gudmundsdottir, Bergljot Gyda

2016-01-01

Increasing numbers of adults, particularly college students, are misusing prescription stimulants primarily for cognitive/academic enhancement, so it is critical to explore whether empirical findings support neurocognitive benefits of prescription stimulants. Previous meta-analytic studies have supported small benefits from prescription stimulants for the cognitive domains of inhibitory control and memory; however, no meta-analytic studies have examined the effects on processing speed or the potential impairment on other domains of cognition, including planning, decision-making, and cognitive perseveration. Therefore, the present study conducted a meta-analysis of the available literature examining the effects of prescription stimulants on specific measures of processing speed, planning, decision-making, and cognitive perseveration among healthy adult populations. The meta-analysis results indicated a positive influence of prescription stimulant medication on processing speed accuracy, with an overall mean effect size of g = 0.282 (95% CI 0.077, 0.488; n = 345). Neither improvements nor impairments were revealed for planning time, planning accuracy, advantageous decision-making, or cognitive perseveration; however findings are limited by the small number of studies examining these outcomes. Findings support that prescription stimulant medication may indeed act as a neurocognitive enhancer for accuracy measures of processing speed without impeding other areas of cognition. Considering that adults are already engaging in illegal use of prescription stimulants for academic enhancement, as well as the potential for stimulant misuse to have serious side effects, the establishment of public policies informed by interdisciplinary research surrounding this issue, whether restrictive or liberal, is of critical importance. PMID:27454675

What Goes Into a Decision? How Nursing Faculty Decide Which Best Practices to Use for Classroom Testing.

PubMed

Killingsworth, Erin; Kimble, Laura P; Sudia, Tanya

2015-01-01

To explore the decision-making process of BSN faculty when determining which best practices to use for classroom testing. A descriptive, correlational study was conducted with a national sample (N = 127) of full-time BSN faculty. Participants completed a web-based survey incorporating instruments that measured beliefs about evaluation, decision-making, and best practices for item analysis and constructing and revising classroom tests. Study participants represented 31 states and were primarily middle-aged white women. In multiple linear regression analyses, faculty beliefs, contextual factors for decision-making, and decision-making processes accounted for statistically significant amounts of the variance in item analysis and test construction and revision. Strong faculty beliefs that rules were important when evaluating students was a significant predictor of increased use of best practices. Results support that understanding faculty beliefs around classroom testing is important in promoting the use of best practices.

Electronic decision support for diagnostic imaging in a primary care setting

PubMed Central

Reed, Martin H

2011-01-01

Methods Clinical guideline adherence for diagnostic imaging (DI) and acceptance of electronic decision support in a rural community family practice clinic was assessed over 36 weeks. Physicians wrote 904 DI orders, 58% of which were addressed by the Canadian Association of Radiologists guidelines. Results Of those orders with guidelines, 76% were ordered correctly; 24% were inappropriate or unnecessary resulting in a prompt from clinical decision support. Physicians followed suggestions from decision support to improve their DI order on 25% of the initially inappropriate orders. The use of decision support was not mandatory, and there were significant variations in use rate. Initially, 40% reported decision support disruptive in their work flow, which dropped to 16% as physicians gained experience with the software. Conclusions Physicians supported the concept of clinical decision support but were reluctant to change clinical habits to incorporate decision support into routine work flow. PMID:21486884

The Three Gorges Project: How sustainable?

NASA Astrophysics Data System (ADS)

Kepa Brian Morgan, Te Kipa; Sardelic, Daniel N.; Waretini, Amaria F.

2012-08-01

SummaryIn 1984 the Government of China approved the decision to construct the Three Gorges Dam Project, the largest project since the Great Wall. The project had many barriers to overcome, and the decision was made at a time when sustainability was a relatively unknown concept. The decision to construct the Three Gorges Project remains contentious today, especially since Deputy Director of the Three Gorges Project Construction Committee, Wang Xiaofeng, stated that "We absolutely cannot relax our guard against ecological and environmental security problems sparked by the Three Gorges Project" (Bristow, 2007; McCabe, 2007). The question therefore was posed: how sustainable is the Three Gorges Project? Conventional approaches to sustainability assessment tend to use monetary based assessment aligned to triple bottom line thinking. That is, projects are evaluated as trade-offs between economic, environmental and social costs and benefits. The question of sustainability is considered using such a traditional Cost-Benefit Analysis approach, as undertaken in 1988 by a CIPM-Yangtze Joint Venture, and the Mauri Model Decision Making Framework (MMDMF). The Mauri Model differs from other approaches in that sustainability performance indicators are considered independently from any particular stakeholder bias. Bias is then introduced subsequently as a sensitivity analysis on the raw results obtained. The MMDMF is unique in that it is based on the Māori concept of Mauri, the binding force between the physical and the spiritual attributes of something, or the capacity to support life in the air, soil, and water. This concept of Mauri is analogous to the Chinese concept of Qi, and there are many analogous concepts in other cultures. It is the universal relevance of Mauri that allows its use to assess sustainability. This research identified that the MMDMF was a strong complement to Cost-Benefit Analysis, which is not designed as a sustainability assessment tool in itself. The MMDMF does have relevance in identifying areas of conflict, and it can support the Cost-Benefit Analysis in assessing sustainability, as a Decision Support Tool. The research concluded that, based on both models, the Three Gorges Project as understood in 1988, and incorporating more recent sustainability analysis is contributing to enhanced sustainability.

Supporting end of life decision making: Case studies of relational closeness in supported decision making for people with severe or profound intellectual disability.

PubMed

Watson, Joanne; Wilson, Erin; Hagiliassis, Nick

2017-11-01

The United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) promotes the use of supported decision making in lieu of substitute decision making. To date, there has been a lack of focus on supported decision making for people with severe or profound intellectual disability, including for end of life decisions. Five people with severe or profound intellectual disability's experiences of supported decision making were examined. This article is particularly focused on one participant's experiences at the end of his life. All five case studies identified that supporters were most effective in providing decision-making support for participants when they were relationally close to the person and had knowledge of the person's life story, particularly in relation to events that demonstrated preference. Findings from this study provide new understandings of supported decision making for people with severe or profound intellectual disability and have particular relevance for supporting decision making at the end of life. © 2017 John Wiley & Sons Ltd.

Development of a model-based flood emergency management system in Yujiang River Basin, South China

NASA Astrophysics Data System (ADS)

Zeng, Yong; Cai, Yanpeng; Jia, Peng; Mao, Jiansu

2014-06-01

Flooding is the most frequent disaster in China. It affects people's lives and properties, causing considerable economic loss. Flood forecast and operation of reservoirs are important in flood emergency management. Although great progress has been achieved in flood forecast and reservoir operation through using computer, network technology, and geographic information system technology in China, the prediction accuracy of models are not satisfactory due to the unavailability of real-time monitoring data. Also, real-time flood control scenario analysis is not effective in many regions and can seldom provide online decision support function. In this research, a decision support system for real-time flood forecasting in Yujiang River Basin, South China (DSS-YRB) is introduced in this paper. This system is based on hydrological and hydraulic mathematical models. The conceptual framework and detailed components of the proposed DSS-YRB is illustrated, which employs real-time rainfall data conversion, model-driven hydrologic forecasting, model calibration, data assimilation methods, and reservoir operational scenario analysis. Multi-tiered architecture offers great flexibility, portability, reusability, and reliability. The applied case study results show the development and application of a decision support system for real-time flood forecasting and operation is beneficial for flood control.

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

NASA Astrophysics Data System (ADS)

Kacprzyk, Janusz; Zadrożny, Sławomir

2010-05-01

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

Spatial decision support system for tobacco enterprise based on spatial data mining

NASA Astrophysics Data System (ADS)

Mei, Xin; Liu, Junyi; Zhang, Xuexia; Cui, Weihong

2007-11-01

Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique and spatial data mining (SDM) to construct spatial decision support system (SDSS) of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision based on SDM is given. This paper describes how to use spatial analysis and data mining to realize the spatial decision processing such as monitoring tobacco planted acreage, analyzing and planning the cigarette sale network and so on.

A Decision Support System for Evaluating and Selecting Information Systems Projects

NASA Astrophysics Data System (ADS)

Deng, Hepu; Wibowo, Santoso

2009-01-01

This chapter presents a decision support system (DSS) for effectively solving the information systems (IS) project selection problem. The proposed DSS recognizes the multidimensional nature of the IS project selection problem, the availability of multicriteria analysis (MA) methods, and the preferences of the decision-maker (DM) on the use of specific MA methods in a given situation. A knowledge base consisting of IF-THEN production rules is developed for assisting the DM with a systematic adoption of the most appropriate method with the efficient use of the powerful reasoning and explanation capabilities of intelligent DSS. The idea of letting the problem to be solved determines the method to be used is incorporated into the proposed DSS. As a result, effective decisions can be made for solving the IS project selection problem. An example is presented to demonstrate the applicability of the proposed DSS for solving the problem of selecting IS projects in real world situations.

Information and decision support needs of parents considering amniocentesis: interviews with pregnant women and health professionals.

PubMed

Durand, Marie-Anne; Stiel, Mareike; Boivin, Jacky; Elwyn, Glyn

2010-06-01

Our aim was to clarify and categorize information and decision support needs of pregnant women deciding about amniocentesis. Prenatal screening for Down's syndrome (implemented in routine practice) generates a quantifiable risk of chromosome abnormality. To increase certainty, chromosomal material needs to be obtained through amniocentesis or other diagnostic test. Amniocentesis carries risks of pregnancy loss. Semi-structured interviews were conducted with health professionals and pregnant women who had considered amniocentesis. The data were qualitatively analysed using a two-step thematic content analysis. A sample of 17 health professionals and 17 pregnant women were interviewed. Professionals demonstrated little consensus regarding the miscarriage rate, the potential consequences of amniocentesis testing and the uncertainty associated with the tests. Furthermore, methods employed to communicate risks varied between professionals. Pregnant women reported heightened stress and anxiety. Twelve out of 17 women described the decision as complex and difficult to make while five participants were satisfied with the information and support provided. Women would have liked more information about the risks involved, the results, the consequences of an amniocentesis and associated emotional difficulties. Women highlighted the need for personalized information, presented in multiple ways, while remaining simple and unbiased. There is variation in the provision of information related to amniocentesis testing. The majority of pregnant women reported difficulties making a decision and identified dimensions of information and decision support where improvements were needed.

Putting children forward for epilepsy surgery: A qualitative study of UK parents' and health professionals' decision-making experiences.

PubMed

Heath, Gemma; Abdin, Shanara; Begum, Rahima; Kearney, Shauna

2016-08-01

Against a backdrop of recommendations for increasing access to and uptake of early surgical intervention for children with medically intractable epilepsy, it is important to understand how parents and professionals decide to put children forward for epilepsy surgery and what their decisional support needs are. The aim of this study was to explore how parents and health professionals make decisions regarding putting children forward for pediatric epilepsy surgery. Individual interviews were conducted with nine parents of children who had undergone pediatric epilepsy surgery at a specialist children's hospital and ten healthcare professionals who made up the children's epilepsy surgery service multidisciplinary healthcare team (MDT). Three MDT meetings were also observed. Data were analyzed thematically. Four themes were generated from analysis of interviews with parents: presentation of surgery as a treatment option, decision-making, looking back, and interventions. Three themes were generated from analysis of interviews/observations with health professionals: triangulating information, team working, and patient and family perspectives. Parents wanted more information and support in deciding to put their child forward for epilepsy surgery. They attempted to balance the potential benefits of surgery against any risks of harm. For health professionals, a multidisciplinary approach was seen as crucial to the decision-making process. Advocating for the family was perceived to be the responsibility of nonmedical professionals. Decision-making can be supported by incorporating families into discussions regarding epilepsy surgery as a potential treatment option earlier in the process and by providing families with additional information and access to other parents with similar experiences. Copyright © 2016 Elsevier Inc. All rights reserved.

Strategic Planning in Population Health and Public Health Practice: A Call to Action for Higher Education

PubMed Central

PHELPS, CHARLES; RAPPUOLI, RINO; LEVIN, SCOTT; SHORTLIFFE, EDWARD; COLWELL, RITA

2016-01-01

Policy Points: Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning.Public health agencies’ current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost‐effectiveness.As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost‐effectiveness analyses widely recommended and used for public health planning.Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Context Strategic planning in population health and public health practice often uses single indicators of success or, when using multiple indicators, provides no mechanism for coherently combining the assessments. Cost‐effectiveness analysis, the most complex strategic planning tool commonly applied in public health, uses only a single metric to evaluate programmatic choices, even though other factors often influence actual decisions. Methods Our work employed a multicriteria systems analysis approach—specifically, multiattribute utility theory—to assist in strategic planning and priority setting in a particular area of health care (vaccines), thereby moving beyond the traditional cost‐effectiveness analysis approach. Findings (1) Multicriteria systems analysis provides more flexibility, transparency, and clarity in decision support for public health issues compared with cost‐effectiveness analysis. (2) More sophisticated systems‐level analyses will become increasingly important to public health as disease burdens increase and the resources to deal with them become scarcer. Conclusions The teaching of strategic planning in public health must be expanded in order to fill a void in the profession's planning capabilities. Public health training should actively incorporate model building, promote the interactive use of software tools, and explore planning approaches that transcend restrictive assumptions of cost‐effectiveness analysis. The Strategic Multi‐Attribute Ranking Tool for Vaccines (SMART Vaccines), which was recently developed by the Institute of Medicine and the National Academy of Engineering to help prioritize new vaccine development, is a working example of systems analysis as a basis for decision support. PMID:26994711

Strategic Planning in Population Health and Public Health Practice: A Call to Action for Higher Education.

PubMed

Phelps, Charles; Madhavan, Guruprasad; Rappuoli, Rino; Levin, Scott; Shortliffe, Edward; Colwell, Rita

2016-03-01

Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning. Public health agencies' current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost-effectiveness. As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost-effectiveness analyses widely recommended and used for public health planning. Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Strategic planning in population health and public health practice often uses single indicators of success or, when using multiple indicators, provides no mechanism for coherently combining the assessments. Cost-effectiveness analysis, the most complex strategic planning tool commonly applied in public health, uses only a single metric to evaluate programmatic choices, even though other factors often influence actual decisions. Our work employed a multicriteria systems analysis approach--specifically, multiattribute utility theory--to assist in strategic planning and priority setting in a particular area of health care (vaccines), thereby moving beyond the traditional cost-effectiveness analysis approach. (1) Multicriteria systems analysis provides more flexibility, transparency, and clarity in decision support for public health issues compared with cost-effectiveness analysis. (2) More sophisticated systems-level analyses will become increasingly important to public health as disease burdens increase and the resources to deal with them become scarcer. The teaching of strategic planning in public health must be expanded in order to fill a void in the profession's planning capabilities. Public health training should actively incorporate model building, promote the interactive use of software tools, and explore planning approaches that transcend restrictive assumptions of cost-effectiveness analysis. The Strategic Multi-Attribute Ranking Tool for Vaccines (SMART Vaccines), which was recently developed by the Institute of Medicine and the National Academy of Engineering to help prioritize new vaccine development, is a working example of systems analysis as a basis for decision support. © 2016 Milbank Memorial Fund.

Preliminary Work Domain Analysis for Human Extravehicular Activity

NASA Technical Reports Server (NTRS)

McGuire, Kerry; Miller, Matthew; Feigh, Karen

2015-01-01

A work domain analysis (WDA) of human extravehicular activity (EVA) is presented in this study. A formative methodology such as Cognitive Work Analysis (CWA) offers a new perspective to the knowledge gained from the past 50 years of living and working in space for the development of future EVA support systems. EVA is a vital component of human spaceflight and provides a case study example of applying a work domain analysis (WDA) to a complex sociotechnical system. The WDA presented here illustrates how the physical characteristics of the environment, hardware, and life support systems of the domain guide the potential avenues and functional needs of future EVA decision support system development.

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

PubMed

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

2013-09-01

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

HPV vaccine introduction at the local level in a developing country: attitudes and criteria among key actors.

PubMed

Piñeros, Marion; Wiesner, Carolina; Cortés, Claudia; Trujillo, Lina María

2010-05-01

In most developing countries, HPV vaccines have been licensed but there are no national policy recommendations, nor is it clear how decisions on the introduction of this new vaccine are made. Decentralization processes in many Latin American countries favor decision-making at the local level. Through a qualitative study we explored knowledge regarding the HPV vaccine and the criteria that influence decision-making among local health actors in four regions of Colombia. We conducted a total of 14 in-depths interviews with different actors; for the analysis we performed content analysis. Results indicate that decision-making on the HPV vaccine at the local level has mainly been driven by pressure from local political actors, in a setting where there is low technical knowledge of the vaccine. This increases the risk of initiatives that may foster inequity. Local decisions and initiatives need to be strengthened technically and supported by national-level decisions, guidelines and follow-up.

Environmental and economic assessment methods for waste management decision-support: possibilities and limitations.

PubMed

Finnveden, Göran; Björklund, Anna; Moberg, Asa; Ekvall, Tomas

2007-06-01

A large number of methods and approaches that can be used for supporting waste management decisions at different levels in society have been developed. In this paper an overview of methods is provided and preliminary guidelines for the choice of methods are presented. The methods introduced include: Environmental Impact Assessment, Strategic Environmental Assessment, Life Cycle Assessment, Cost-Benefit Analysis, Cost-effectiveness Analysis, Life-cycle Costing, Risk Assessment, Material Flow Accounting, Substance Flow Analysis, Energy Analysis, Exergy Analysis, Entropy Analysis, Environmental Management Systems, and Environmental Auditing. The characteristics used are the types of impacts included, the objects under study and whether the method is procedural or analytical. The different methods can be described as systems analysis methods. Waste management systems thinking is receiving increasing attention. This is, for example, evidenced by the suggested thematic strategy on waste by the European Commission where life-cycle analysis and life-cycle thinking get prominent positions. Indeed, life-cycle analyses have been shown to provide policy-relevant and consistent results. However, it is also clear that the studies will always be open to criticism since they are simplifications of reality and include uncertainties. This is something all systems analysis methods have in common. Assumptions can be challenged and it may be difficult to generalize from case studies to policies. This suggests that if decisions are going to be made, they are likely to be made on a less than perfect basis.

Bayesian Decision Support for Adaptive Lung Treatments

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

A decision support for an integrated multi-scale analysis of irrigation: DSIRR.

PubMed

Bazzani, Guido M

2005-12-01

The paper presents a decision support designed to conduct an economic-environmental assessment of the agricultural activity focusing on irrigation called 'Decision Support for IRRigated Agriculture' (DSIRR). The program describes the effect at catchment scale of choices taken at micro scale by independent actors, the farmers, by simulating their decision process. The decision support (DS) has been thought of as a support tool for participatory water policies as requested by the Water Framework Directive and it aims at analyzing alternatives in production and technology, according to different market, policy and climate conditions. The tool uses data and models, provides a graphical user interface and can incorporate the decision makers' own insights. Heterogeneity in preferences is admitted since it is assumed that irrigators try to optimize personal multi-attribute utility functions, subject to a set of constraints. Consideration of agronomic and engineering aspects allows an accurate description of irrigation. Mathematical programming techniques are applied to find solutions. The program has been applied in the river Po basin (northern Italy) to analyze the impact of a pricing policy in a context of irrigation technology innovation. Water demand functions and elasticity to water price have been estimated. Results demonstrate how different areas and systems react to the same policy in quite a different way. While in the annual cropping system pricing seems effective to save the resource at the cost of impeding Water Agencies cost recovery, the same policy has an opposite effect in the perennial fruit system which shows an inelastic response to water price. The multidimensional assessment conducted clarified the trades-off among conflicting economic-social-environmental objectives, thus generating valuable information to design a more tailored mix of measures.

Everyday decision-making in dementia: findings from a longitudinal interview study of people with dementia and family carers.

PubMed

Samsi, Kritika; Manthorpe, Jill

2013-06-01

Exercising choice and control over decisions is central to quality of life. The Mental Capacity Act 2005 (England and Wales) provides a legal framework to safeguard the rights of people with dementia to make their own decisions for as long as possible. The impact of this on long-term planning has been investigated; everyday decision-making in people's own homes remains unexplored. Using a phenomenological approach, we interviewed 12 dyads (one person with dementia + one carer) four times over one year to ascertain experience of decision-making, how decisions were negotiated, and how dynamics changed. Qualitative interviews were conducted in people's own homes, and thematic analysis was applied to transcripts. Respecting autonomy, decision-specificity and best interests underlay most everyday decisions in this sample. Over time, dyads transitioned from supported decision-making, where person with dementia and carer made decisions together, to substituted decision-making, where carers took over much decision-making. Points along this continuum represented carers' active involvement in retaining their relative's engagement through providing cues, reducing options, using retrospective information, and using the best interests principle. Long-term spouse carers seemed most equipped to make substitute decisions for their spouses; adult children and friend carers struggled with this. Carers may gradually take on decision-making for people with dementia. This can bring with it added stresses, such as determining their relative's decision-making capacity and weighing up what is in their best interests. Practitioners and support services should provide timely advice to carers and people with dementia around everyday decision-making, and be mindful how abilities may change.

Conceptual and Empirical Approaches to Financial Decision-making by Older Adults: Results from a Financial Decision-making Rating Scale.

PubMed

Lichtenberg, Peter A; Ocepek-Welikson, Katja; Ficker, Lisa J; Gross, Evan; Rahman-Filipiak, Analise; Teresi, Jeanne A

2018-01-01

The objectives of this study were threefold: (1) to empirically test the conceptual model proposed by the Lichtenberg Financial Decision-making Rating Scale (LFDRS); (2) to examine the psychometric properties of the LFDRS contextual factors in financial decision-making by investigating both the reliability and convergent validity of the subscales and total scale, and (3) extending previous work on the scale through the collection of normative data on financial decision-making. A convenience sample of 200 independent function and community dwelling older adults underwent cognitive and financial management testing and were interviewed using the LFDRS. Confirmatory factor analysis, internal consistency measures, and hierarchical regression were used in a sample of 200 community-dwelling older adults, all of whom were making or had recently made a significant financial decision. Results confirmed the scale's reliability and supported the conceptual model. Convergent validity analyses indicate that as hypothesized, cognition is a significant predictor of risk scores. Financial management scores, however, were not predictive of decision-making risk scores. The psychometric properties of the LFDRS support the scale's use as it was proposed. The LFDRS instructions and scale are provided for clinicians to use in financial capacity assessments.

Strategic Analysis Overview

NASA Technical Reports Server (NTRS)

Cirillo, William M.; Earle, Kevin D.; Goodliff, Kandyce E.; Reeves, J. D.; Stromgren, Chel; Andraschko, Mark R.; Merrill, R. Gabe

2008-01-01

NASA s Constellation Program employs a strategic analysis methodology in providing an integrated analysis capability of Lunar exploration scenarios and to support strategic decision-making regarding those scenarios. The strategic analysis methodology integrates the assessment of the major contributors to strategic objective satisfaction performance, affordability, and risk and captures the linkages and feedbacks between all three components. Strategic analysis supports strategic decision making by senior management through comparable analysis of alternative strategies, provision of a consistent set of high level value metrics, and the enabling of cost-benefit analysis. The tools developed to implement the strategic analysis methodology are not element design and sizing tools. Rather, these models evaluate strategic performance using predefined elements, imported into a library from expert-driven design/sizing tools or expert analysis. Specific components of the strategic analysis tool set include scenario definition, requirements generation, mission manifesting, scenario lifecycle costing, crew time analysis, objective satisfaction benefit, risk analysis, and probabilistic evaluation. Results from all components of strategic analysis are evaluated a set of pre-defined figures of merit (FOMs). These FOMs capture the high-level strategic characteristics of all scenarios and facilitate direct comparison of options. The strategic analysis methodology that is described in this paper has previously been applied to the Space Shuttle and International Space Station Programs and is now being used to support the development of the baseline Constellation Program lunar architecture. This paper will present an overview of the strategic analysis methodology and will present sample results from the application of the strategic analysis methodology to the Constellation Program lunar architecture.

Decision support system in an international-voice-services business company

NASA Astrophysics Data System (ADS)

Hadianti, R.; Uttunggadewa, S.; Syamsuddin, M.; Soewono, E.

2017-01-01

We consider a problem facing by an international telecommunication services company in maximizing its profit. From voice services by controlling cost and business partnership. The competitiveness in this industry is very high, so that any efficiency from controlling cost and business partnership can help the company to survive in the very high competitiveness situation. The company trades voice traffic with a large number of business partners. There are four trading schemes that can be chosen by this company, namely, flat rate, class tiering, volume commitment, and revenue capped. Each scheme has a specific characteristic on the rate and volume deal, where the last three schemes are regarded as strategic schemes to be offered to business partner to ensure incoming traffic volume for both parties. This company and each business partner need to choose an optimal agreement in a certain period of time that can maximize the company’s profit. In this agreement, both parties agree to use a certain trading scheme, rate and rate/volume/revenue deal. A decision support system is then needed in order to give a comprehensive information to the sales officers to deal with the business partners. This paper discusses the mathematical model of the optimal decision for incoming traffic volume control, which is a part of the analysis needed to build the decision support system. The mathematical model is built by first performing data analysis to see how elastic the incoming traffic volume is. As the level of elasticity is obtained, we then derive a mathematical modelling that can simulate the impact of any decision on trading to the revenue of the company. The optimal decision can be obtained from these simulations results. To evaluate the performance of the proposed method we implement our decision model to the historical data. A software tool incorporating our methodology is currently in construction.

Content Analysis of Social Media Related to Left Ventricular Assist Devices.

PubMed

Kostick, Kristin M; Blumenthal-Barby, Jennifer S; Wilhelms, Lidija A; Delgado, Estevan D; Bruce, Courtenay R

2015-09-01

Social media have the potential to offer important benefits for patient education, support, and shared decision making. Despite the proliferation of social media use during the past decade, little is known about the scope and quality of available information, or the purposes that social media sites serve for patient decisional and support needs. We conducted a mixed method study, including content analysis of social media and principal components analysis analysis of data sites discussing left ventricular assist device treatment for heart failure. This study explored aspects of interactivity, user-friendliness, appeal, medium, purpose, audience, and accuracy of information. Higher levels of interactivity (eg, posting comments) seem to enhance the appeal and usability of available information but also introduce greater potential for inaccuracy and inconsistency. The current lack of oversight into the content and quality of available information constitute a challenge for the reliable use of social media as forums for information-seeking and social network-based support. We conclude that social media outlets constitute a promising source of informational and psychosocial support for patients, caregivers, and candidates, and if used in conjunction with patient-provider dialog, can contribute to informed decision making by facilitating reflection and discussion of personal concerns, values, and informational needs. © 2015 American Heart Association, Inc.

Measuring sustainable development using a multi-criteria model: a case study.

PubMed

Boggia, Antonio; Cortina, Carla

2010-11-01

This paper shows how Multi-criteria Decision Analysis (MCDA) can help in a complex process such as the assessment of the level of sustainability of a certain area. The paper presents the results of a study in which a model for measuring sustainability was implemented to better aid public policy decisions regarding sustainability. In order to assess sustainability in specific areas, a methodological approach based on multi-criteria analysis has been developed. The aim is to rank areas in order to understand the specific technical and/or financial support that they need to develop sustainable growth. The case study presented is an assessment of the level of sustainability in different areas of an Italian Region using the MCDA approach. Our results show that MCDA is a proper approach for sustainability assessment. The results are easy to understand and the evaluation path is clear and transparent. This is what decision makers need for having support to their decisions. The multi-criteria model for evaluation has been developed respecting the sustainable development economic theory, so that final results can have a clear meaning in terms of sustainability. Copyright 2010 Elsevier Ltd. All rights reserved.

A new spatial multi-criteria decision support tool for site selection for implementation of managed aquifer recharge.

PubMed

Rahman, M Azizur; Rusteberg, Bernd; Gogu, R C; Lobo Ferreira, J P; Sauter, Martin

2012-05-30

This study reports the development of a new spatial multi-criteria decision analysis (SMCDA) software tool for selecting suitable sites for Managed Aquifer Recharge (MAR) systems. The new SMCDA software tool functions based on the combination of existing multi-criteria evaluation methods with modern decision analysis techniques. More specifically, non-compensatory screening, criteria standardization and weighting, and Analytical Hierarchy Process (AHP) have been combined with Weighted Linear Combination (WLC) and Ordered Weighted Averaging (OWA). This SMCDA tool may be implemented with a wide range of decision maker's preferences. The tool's user-friendly interface helps guide the decision maker through the sequential steps for site selection, those steps namely being constraint mapping, criteria hierarchy, criteria standardization and weighting, and criteria overlay. The tool offers some predetermined default criteria and standard methods to increase the trade-off between ease-of-use and efficiency. Integrated into ArcGIS, the tool has the advantage of using GIS tools for spatial analysis, and herein data may be processed and displayed. The tool is non-site specific, adaptive, and comprehensive, and may be applied to any type of site-selection problem. For demonstrating the robustness of the new tool, a case study was planned and executed at Algarve Region, Portugal. The efficiency of the SMCDA tool in the decision making process for selecting suitable sites for MAR was also demonstrated. Specific aspects of the tool such as built-in default criteria, explicit decision steps, and flexibility in choosing different options were key features, which benefited the study. The new SMCDA tool can be augmented by groundwater flow and transport modeling so as to achieve a more comprehensive approach to the selection process for the best locations of the MAR infiltration basins, as well as the locations of recovery wells and areas of groundwater protection. The new spatial multicriteria analysis tool has already been implemented within the GIS based Gabardine decision support system as an innovative MAR planning tool. Copyright © 2012 Elsevier Ltd. All rights reserved.

Cost analysis of the development and implementation of a spatial decision support system for malaria elimination in Solomon Islands.

PubMed

Marston, Luke; Kelly, Gerard C; Hale, Erick; Clements, Archie C A; Hodge, Andrew; Jimenez-Soto, Eliana

2014-08-18

The goal of malaria elimination faces numerous challenges. New tools are required to support the scale up of interventions and improve national malaria programme capacity to conduct detailed surveillance. This study investigates the cost factors influencing the development and implementation of a spatial decision support system (SDSS) for malaria elimination in the two elimination provinces of Isabel and Temotu, Solomon Islands. Financial and economic costs to develop and implement a SDSS were estimated using the Solomon Islands programme's financial records. Using an ingredients approach, verified by stakeholders and operational reports, total costs for each province were quantified. A budget impact sensitivity analysis was conducted to investigate the influence of variations in standard budgetary components on the costs and to identify potential cost savings. A total investment of US$ 96,046 (2012 constant dollars) was required to develop and implement the SDSS in two provinces (Temotu Province US$ 49,806 and Isabel Province US$ 46,240). The single largest expense category was for computerized equipment totalling approximately US$ 30,085. Geographical reconnaissance was the most expensive phase of development and implementation, accounting for approximately 62% of total costs. Sensitivity analysis identified different cost factors between the provinces. Reduced equipment costs would deliver a budget saving of approximately 10% in Isabel Province. Combined travel costs represented the greatest influence on the total budget in the more remote Temotu Province. This study provides the first cost analysis of an operational surveillance tool used specifically for malaria elimination in the South-West Pacific. It is demonstrated that the costs of such a decision support system are driven by specialized equipment and travel expenses. Such factors should be closely scrutinized in future programme budgets to ensure maximum efficiencies are gained and available resources are allocated effectively.

The Development and Validation of a Special Education Intelligent Administration Support Program. Final Report.

ERIC Educational Resources Information Center

Utah State Univ., Logan. Center for Persons with Disabilities.

This project studied the effects of implementing a computerized management information system developed for special education administrators. The Intelligent Administration Support Program (IASP), an expert system and database program, assisted in information acquisition and analysis pertaining to the district's quality of decisions and procedures…

Visual Decision Support Tool for Supporting Asset Management Performance, Risk, and Cost Analysis (WERF Report INFR5R12)

EPA Science Inventory

Abstract:Managing urban water infrastructures faces the challenge of jointly dealing with assets of diverse types, useful life, cost, ages and condition. Service quality and sustainability require sound long-term planning, well aligned with tactical and operational planning and m...

Supporting NASA Facilities Through GIS

NASA Technical Reports Server (NTRS)

Ingham, Mary E.

2000-01-01

The NASA GIS Team supports NASA facilities and partners in the analysis of spatial data. Geographic Information System (G[S) is an integration of computer hardware, software, and personnel linking topographic, demographic, utility, facility, image, and other geo-referenced data. The system provides a graphic interface to relational databases and supports decision making processes such as planning, design, maintenance and repair, and emergency response.

Analysis of Advanced Respiratory Support Onboard ISS and CCV

NASA Technical Reports Server (NTRS)

Shah, Ronak V.; Kertsman, Eric L.; Alexander, David J.; Duchesne, Ted; Law, Jennifer; Roden, Sean K.

2014-01-01

NASA is collaborating with private entities for the development of commercial space vehicles. The Space and Clinical Operations Division was tasked to review the oxygen and respiratory support system and recommend what capabilities, if any, the vehicle should have to support the return of an ill or injured crewmember. The Integrated Medical Model (IMM) was utilized as a data source for the development of these recommendations. The Integrated Medical Model (IMM) was used to simulate a six month, six crew, International Space Station (ISS) mission. Three medical system scenarios were considered based on the availability of (1) oxygen only, (2) oxygen and a ventilator, or (3) neither oxygen nor ventilator. The IMM analysis provided probability estimates of medical events that would require either oxygen or ventilator support. It also provided estimates of crew health, the probability of evacuation, and the probability of loss of crew life secondary to medical events for each of the three medical system scenarios. These IMM outputs were used as objective data to enable evidence-based decisions regarding oxygen and respiratory support system requirements for commercial crew vehicles. The IMM provides data that may be utilized to support informed decisions regarding the development of medical systems for commercial crew vehicles.

Mads.jl

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vesselinov, Velimir; O'Malley, Daniel; Lin, Youzuo

2016-07-01

Mads.jl (Model analysis and decision support in Julia) is a code that streamlines the process of using data and models for analysis and decision support. It is based on another open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11- 035). Mads.jl can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. It enables a number of data- and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. The code also can use a series of alternative adaptive computational techniques for Bayesian sampling, Monte Carlo,more » and Bayesian Information-Gap Decision Theory. The code is implemented in the Julia programming language, and has high-performance (parallel) and memory management capabilities. The code uses a series of third party modules developed by others. The code development will also include contributions to the existing third party modules written in Julia; this contributions will be important for the efficient implementation of the algorithm used by Mads.jl. The code also uses a series of LANL developed modules that are developed by Dan O'Malley; these modules will be also a part of the Mads.jl release. Mads.jl will be released under GPL V3 license. The code will be distributed as a Git repo at gitlab.com and github.com. Mads.jl manual and documentation will be posted at madsjulia.lanl.gov.« less

Balance Sheets Versus Decision Dashboards to Support Patient Treatment Choices: A Comparative Analysis.

PubMed

Dolan, James G; Veazie, Peter J

2015-12-01

Growing recognition of the importance of involving patients in preference-driven healthcare decisions has highlighted the need to develop practical strategies to implement patient-centered shared decision-making. The use of tabular balance sheets to support clinical decision-making is well established. More recent evidence suggests that graphic, interactive decision dashboards can help people derive deeper a understanding of information within a specific decision context. We therefore conducted a non-randomized trial comparing the effects of adding an interactive dashboard to a static tabular balance sheet on patient decision-making. The study population consisted of members of the ResearchMatch registry who volunteered to participate in a study of medical decision-making. Two separate surveys were conducted: one in the control group and one in the intervention group. All participants were instructed to imagine they were newly diagnosed with a chronic illness and were asked to choose between three hypothetical drug treatments, which varied with regard to effectiveness, side effects, and out-of-pocket cost. Both groups made an initial treatment choice after reviewing a balance sheet. After a brief "washout" period, members of the control group made a second treatment choice after reviewing the balance sheet again, while intervention group members made a second treatment choice after reviewing an interactive decision dashboard containing the same information. After both choices, participants rated their degree of confidence in their choice on a 1 to 10 scale. Members of the dashboard intervention group were more likely to change their choice of preferred drug (10.2 versus 7.5%; p = 0.054) and had a larger increase in decision confidence than the control group (0.67 versus 0.075; p < 0.03). There were no statistically significant between-group differences in decisional conflict or decision aid acceptability. These findings suggest that clinical decision dashboards may be an effective point-of-care decision-support tool. Further research to explore this possibility is warranted.

Development of the Supported Decision Making Inventory System.

PubMed

Shogren, Karrie A; Wehmeyer, Michael L; Uyanik, Hatice; Heidrich, Megan

2017-12-01

Supported decision making has received increased attention as an alternative to guardianship and a means to enable people with intellectual and developmental disabilities to exercise their right to legal capacity. Assessments are needed that can used by people with disabilities and their systems of supports to identify and plan for needed supports to enable decision making. This article describes the steps taken to develop such an assessment tool, the Supported Decision Making Inventory System (SDMIS), and initial feedback received from self-advocates with intellectual disability. The three sections of the SDMIS (Supported Decision Making Personal Factors Inventory, Supported Decision Making Environmental Demands Inventory, and Decision Making Autonomy Inventory) are described and implications for future research, policy, and practice are discussed.

The role of risk-based prioritization in total quality management

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bennett, C.T.

1994-10-01

The climate in which government managers must make decisions grows more complex and uncertain. All stakeholders - the public, industry, and Congress - are demanding greater consciousness, responsibility, and accountability of programs and their budgets. Yet, managerial decisions have become multifaceted, involve greater risk, and operate over much longer time periods. Over the last four or five decades, as policy analysis and decisions became more complex, scientists from psychology, operations research, systems science, and economics have developed a more or less coherent process called decision analysis to aid program management. The process of decision analysis - a systems theoretic approachmore » - provides the backdrop for this paper. The Laboratory Integrated Prioritization System (LIPS) has been developed as a systems analytic and risk-based prioritization tool to aid the management of the Tri-Labs` (Lawrence Livermore, Los Alamos, and Sandia) operating resources. Preliminary analyses of the effects of LIPS has confirmed the practical benefits of decision and systems sciences - the systematic, quantitative reduction in uncertainty. To date, the use of LIPS - and, hence, its value - has been restricted to resource allocation within the Tri-Labs` operations budgets. This report extends the role of risk-based prioritization to the support of DOE Total Quality Management (TQM) programs. Furthermore, this paper will argue for the requirement to institutionalize an evolutionary, decision theoretic approach to the policy analysis of the Department of Energy`s Program Budget.« less

Study protocol: Improving patient choice in treating low back pain (IMPACT - LBP): A randomised controlled trial of a decision support package for use in physical therapy

PubMed Central

2011-01-01

Background Low back pain is a common and costly condition. There are several treatment options for people suffering from back pain, but there are few data on how to improve patients' treatment choices. This study will test the effects of a decision support package (DSP), designed to help patients seeking care for back pain to make better, more informed choices about their treatment within a physiotherapy department. The package will be designed to assist both therapist and patient. Methods/Design Firstly, in collaboration with physiotherapists, patients and experts in the field of decision support and decision aids, we will develop the DSP. The work will include: a literature and evidence review; secondary analysis of existing qualitative data; exploration of patients' perspectives through focus groups and exploration of experts' perspectives using a nominal group technique and a Delphi study. Secondly, we will carry out a pilot single centre randomised controlled trial within NHS Coventry Community Physiotherapy. We will randomise physiotherapists to receive either training for the DSP or not. We will randomly allocate patients seeking treatment for non specific low back pain to either a physiotherapist trained in decision support or to receive usual care. Our primary outcome measure will be patient satisfaction with treatment at three month follow-up. We will also estimate the cost-effectiveness of the intervention, and assess the value of conducting further research. Discussion Informed shared decision-making should be an important part of any clinical consultation, particularly when there are several treatments, which potentially have moderate effects. The results of this pilot will help us determine the benefits of improving the decision-making process in clinical practice on patient satisfaction. Trial registration Current Controlled Trials ISRCTN46035546 PMID:21352528

Influences on women's decision making about intrauterine device use in Madagascar.

PubMed

Gottert, Ann; Jacquin, Karin; Rahaivondrafahitra, Bakoly; Moracco, Kathryn; Maman, Suzanne

2015-04-01

We explored influences on decision making about intrauterine device (IUD) use among women in the Women's Health Project (WHP), managed by Population Services International in Madagascar. We conducted six small group photonarrative discussions (n=18 individuals) and 12 individual in-depth interviews with women who were IUD users and nonusers. All participants had had contact with WHP counselors in three sites in Madagascar. Data analysis involved creating summaries of each transcript, coding in Atlas.ti and then synthesizing findings in a conceptual model. We identified three stages of women's decision making about IUD use, and specific forms of social support that seemed helpful at each stage. During the first stage, receiving correct information from a trusted source such as a counselor conveys IUD benefits and corrects misinformation, but lingering fears about the method often appeared to delay method adoption among interested women. During the second stage, hearing testimony from satisfied users and receiving ongoing emotional support appeared to help alleviate these fears. During the third stage, accompaniment by a counselor or peer seemed to help some women gain confidence to go to the clinic to receive the IUD. Identifying and supplying the types of social support women find helpful at different stages of the decision-making process could help program managers better respond to women's staged decision-making process about IUD use. This qualitative study suggests that women in Madagascar perceive multiple IUD benefits but also fear the method even after misinformation is corrected, leading to a staged decision-making process about IUD use. Programs should identify and supply the types of social support that women find helpful at each stage of decision making. Copyright © 2015 Elsevier Inc. All rights reserved.

Measuring the impact of diagnostic decision support on the quality of clinical decision making: development of a reliable and valid composite score.

PubMed

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

2003-01-01

Few previous studies evaluating the benefits of diagnostic decision support systems have simultaneously measured changes in diagnostic quality and clinical management prompted by use of the system. This report describes a reliable and valid scoring technique to measure the quality of clinical decision plans in an acute medical setting, where diagnostic decision support tools might prove most useful. Sets of differential diagnoses and clinical management plans generated by 71 clinicians for six simulated cases, before and after decision support from a Web-based pediatric differential diagnostic tool (ISABEL), were used. A composite quality score was calculated separately for each diagnostic and management plan by considering the appropriateness value of each component diagnostic or management suggestion, a weighted sum of individual suggestion ratings, relevance of the entire plan, and its comprehensiveness. The reliability and validity (face, concurrent, construct, and content) of these two final scores were examined. Two hundred fifty-two diagnostic and 350 management suggestions were included in the interrater reliability analysis. There was good agreement between raters (intraclass correlation coefficient, 0.79 for diagnoses, and 0.72 for management). No counterintuitive scores were demonstrated on visual inspection of the sets. Content validity was verified by a consultation process with pediatricians. Both scores discriminated adequately between the plans of consultants and medical students and correlated well with clinicians' subjective opinions of overall plan quality (Spearman rho 0.65, p < 0.01). The diagnostic and management scores for each episode showed moderate correlation (r = 0.51). The scores described can be used as key outcome measures in a larger study to fully assess the value of diagnostic decision aids, such as the ISABEL system.

Family involvement for breast cancer decision making among Chinese-American women.

PubMed

Lee, Shiuyu Katie C; Knobf, M Tish

2016-12-01

To describe family involvement in decision making for primary treatment in Chinese-American women with early-stage breast cancer. Qualitative data were collected in 2003 from semi-structured questions in interviews with a sample of Chinese-American (ChA) women with breast cancer, who were recruited from the metropolitan New York area. Responses to the questions were written in Chinese immediately during the interview and read back to the subject for accuracy and validation. Content analysis was used to inductively code and analyze the data to generate themes. The participants consisted of 123 ChA women with early stage breast cancer with a mean age of 48.7 years (±9.3) and who had lived in the United States a median of 13.6 years. Support and Caring was the major theme that described family involvement in the breast cancer decision-making process. Gathering Information, Being There, Navigating the Health Care System, Maintaining Family Life and Making the Decision described the aspects of family support in the process. The majority of women described the treatment decision making as a collaborative supportive process with the family, but limited English fluency, strong opinions, lack of a shared perspective, distant living proximity and competing work responsibilities of family members were stressful for the women and perceived as non-supportive. Family involvement in health care decision making is culturally embedded in Asian populations. Culturally sensitive patient and family consultation strategies are needed to assist informed treatment decision making in Chinese-American women diagnosed with breast cancer. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Decision Analysis Tools for Volcano Observatories

NASA Astrophysics Data System (ADS)

Hincks, T. H.; Aspinall, W.; Woo, G.

2005-12-01

Staff at volcano observatories are predominantly engaged in scientific activities related to volcano monitoring and instrumentation, data acquisition and analysis. Accordingly, the academic education and professional training of observatory staff tend to focus on these scientific functions. From time to time, however, staff may be called upon to provide decision support to government officials responsible for civil protection. Recognizing that Earth scientists may have limited technical familiarity with formal decision analysis methods, specialist software tools that assist decision support in a crisis should be welcome. A review is given of two software tools that have been under development recently. The first is for probabilistic risk assessment of human and economic loss from volcanic eruptions, and is of practical use in short and medium-term risk-informed planning of exclusion zones, post-disaster response, etc. A multiple branch event-tree architecture for the software, together with a formalism for ascribing probabilities to branches, have been developed within the context of the European Community EXPLORIS project. The second software tool utilizes the principles of the Bayesian Belief Network (BBN) for evidence-based assessment of volcanic state and probabilistic threat evaluation. This is of practical application in short-term volcano hazard forecasting and real-time crisis management, including the difficult challenge of deciding when an eruption is over. An open-source BBN library is the software foundation for this tool, which is capable of combining synoptically different strands of observational data from diverse monitoring sources. A conceptual vision is presented of the practical deployment of these decision analysis tools in a future volcano observatory environment. Summary retrospective analyses are given of previous volcanic crises to illustrate the hazard and risk insights gained from use of these tools.

Multi-criteria multi-stakeholder decision analysis using a fuzzy-stochastic approach for hydrosystem management

NASA Astrophysics Data System (ADS)

Subagadis, Y. H.; Schütze, N.; Grundmann, J.

2014-09-01

The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water-society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA) using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

Supporting End of Life Decision Making: Case Studies of Relational Closeness in Supported Decision Making for People with Severe or Profound Intellectual Disability

ERIC Educational Resources Information Center

Watson, Joanne; Wilson, Erin; Hagiliassis, Nick

2017-01-01

Background: The United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) promotes the use of supported decision making in lieu of substitute decision making. To date, there has been a lack of focus on supported decision making for people with severe or profound intellectual disability, including for end of life decisions.…

Retention payoff-based cost per day open regression equations: Application in a user-friendly decision support tool for investment analysis of automated estrus detection technologies.

PubMed

Dolecheck, K A; Heersche, G; Bewley, J M

2016-12-01

Assessing the economic implications of investing in automated estrus detection (AED) technologies can be overwhelming for dairy producers. The objectives of this study were to develop new regression equations for estimating the cost per day open (DO) and to apply the results to create a user-friendly, partial budget, decision support tool for investment analysis of AED technologies. In the resulting decision support tool, the end user can adjust herd-specific inputs regarding general management, current reproductive management strategies, and the proposed AED system. Outputs include expected DO, reproductive cull rate, net present value, and payback period for the proposed AED system. Utility of the decision support tool was demonstrated with an example dairy herd created using data from DairyMetrics (Dairy Records Management Systems, Raleigh, NC), Food and Agricultural Policy Research Institute (Columbia, MO), and published literature. Resulting herd size, rolling herd average milk production, milk price, and feed cost were 323 cows, 10,758kg, $0.41/kg, and $0.20/kg of dry matter, respectively. Automated estrus detection technologies with 2 levels of initial system cost (low: $5,000 vs. high: $10,000), tag price (low: $50 vs. high: $100), and estrus detection rate (low: 60% vs. high: 80%) were compared over a 7-yr investment period. Four scenarios were considered in a demonstration of the investment analysis tool: (1) a herd using 100% visual observation for estrus detection before adopting 100% AED, (2) a herd using 100% visual observation before adopting 75% AED and 25% visual observation, (3) a herd using 100% timed artificial insemination (TAI) before adopting 100% AED, and (4) a herd using 100% TAI before adopting 75% AED and 25% TAI. Net present value in scenarios 1 and 2 was always positive, indicating a positive investment situation. Net present value in scenarios 3 and 4 was always positive in combinations using a $50 tag price, and in scenario 4, the $5,000, $100, and 80% combination. Overall, the payback period ranged from 1.6 yr to greater than 10 yr. Investment analysis demonstration results were highly dependent on assumptions, especially AED system initial investment and labor costs. Dairy producers can use herd-specific inputs with the cost per day open regression equations and the decision support tool to estimate individual herd results. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Applying the Wildland Fire Decision Support System (WFDSS) to support risk-informed decision making: The Gold Pan Fire, Bitterroot National Forest, Montana, USA

Treesearch

Erin K. Noonan-Wright; Tonja S. Opperman

2015-01-01

In response to federal wildfire policy changes, risk-informed decision-making by way of improved decision support, is increasingly becoming a component of managing wildfires. As fire incidents escalate in size and complexity, the Wildland Fire Decision Support System (WFDSS) provides support with different analytical tools as fire conditions change. We demonstrate the...

Decision support for clinical laboratory capacity planning.

PubMed

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.

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

PubMed

Lee, Seonah

2013-10-01

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

Human/Automation Trade Methodology for the Moon, Mars and Beyond

NASA Technical Reports Server (NTRS)

Korsmeyer, David J.

2009-01-01

It is possible to create a consistent trade methodology that can characterize operations model alternatives for crewed exploration missions. For example, a trade-space that is organized around the objective of maximizing Crew Exploration Vehicle (CEV) independence would have the input as a classification of the category of analysis to be conducted or decision to be made, and a commitment to a detailed point in a mission profile during which the analysis or decision is to be made. For example, does the decision have to do with crew activity planning, or life support? Is the mission phase trans-Earth injection, cruise, or lunar descent? Different kinds of decision analysis of the trade-space between human and automated decisions will occurs at different points in a mission's profile. The necessary objectives at a given point in time during a mission will call for different kinds of response with respect to where and how computers and automation are expected to help provide an accurate, safe, and timely response. In this paper, a consistent methodology for assessing the trades between human and automated decisions on-board will be presented and various examples discussed.

Exploring multicriteria decision strategies in GIS with linguistic quantifiers: A case study of residential quality evaluation

NASA Astrophysics Data System (ADS)

Malczewski, Jacek; Rinner, Claus

2005-06-01

Commonly used GIS combination operators such as Boolean conjunction/disjunction and weighted linear combination can be generalized to the ordered weighted averaging (OWA) family of operators. This multicriteria evaluation method allows decision-makers to define a decision strategy on a continuum between pessimistic and optimistic strategies. Recently, OWA has been introduced to GIS-based decision support systems. We propose to extend a previous implementation of OWA with linguistic quantifiers to simplify the definition of decision strategies and to facilitate an exploratory analysis of multiple criteria. The linguistic quantifier-guided OWA procedure is illustrated using a dataset for evaluating residential quality of neighborhoods in London, Ontario.

Complexity Science: A Mechanism for Strategic Foresight and Resiliency in National Security Decision-Making.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ackermann, Mark R.; Hayden, Nancy Kay; Backus, George A.

Most national policy decisions are complex with a variety of stakeholders, disparate interests and the potential for unintended consequences. While a number of analytical tools exist to help decision makers sort through the mountains of data and myriad of options, decision support teams are increasingly turning to complexity science for improved analysis and better insight into the potential impact of policy decisions. While complexity science has great potential, it has only proven useful in limited case s and when properly applied. In advance of more widespread use, a national - level effort to refine complexity science and more rigorously establishmore » its technical underpinnings is recommended.« less

Using M and S to Improve Human Decision Making and Achieve Effective Problem Solving in an International Environment

NASA Technical Reports Server (NTRS)

Christie, Vanessa L.; Landess, David J.

2012-01-01

In the international arena, decision makers are often swayed away from fact-based analysis by their own individual cultural and political bias. Modeling and Simulation-based training can raise awareness of individual predisposition and improve the quality of decision making by focusing solely on fact vice perception. This improved decision making methodology will support the multinational collaborative efforts of military and civilian leaders to solve challenges more effectively. The intent of this experimental research is to create a framework that allows decision makers to "come to the table" with the latest and most significant facts necessary to determine an appropriate solution for any given contingency.

Comparing a Mobile Decision Support System Versus the Use of Printed Materials for the Implementation of an Evidence-Based Recommendation: Protocol for a Qualitative Evaluation.

PubMed

Camacho, Jhon; Medina Ch, Ana María; Landis-Lewis, Zach; Douglas, Gerald; Boyce, Richard

2018-04-13

The distribution of printed materials is the most frequently used strategy to disseminate and implement clinical practice guidelines, although several studies have shown that the effectiveness of this approach is modest at best. Nevertheless, there is insufficient evidence to support the use of other strategies. Recent research has shown that the use of computerized decision support presents a promising approach to address some aspects of this problem. The aim of this study is to provide qualitative evidence on the potential effect of mobile decision support systems to facilitate the implementation of evidence-based recommendations included in clinical practice guidelines. We will conduct a qualitative study with two arms to compare the experience of primary care physicians while they try to implement an evidence-based recommendation in their clinical practice. In the first arm, we will provide participants with a printout of the guideline article containing the recommendation, while in the second arm, we will provide participants with a mobile app developed after formalizing the recommendation text into a clinical algorithm. Data will be collected using semistructured and open interviews to explore aspects of behavioral change and technology acceptance involved in the implementation process. The analysis will be comprised of two phases. During the first phase, we will conduct a template analysis to identify barriers and facilitators in each scenario. Then, during the second phase, we will contrast the findings from each arm to propose hypotheses about the potential impact of the system. We have formalized the narrative in the recommendation into a clinical algorithm and have developed a mobile app. Data collection is expected to occur during 2018, with the first phase of analysis running in parallel. The second phase is scheduled to conclude in July 2019. Our study will further the understanding of the role of mobile decision support systems in the implementation of clinical practice guidelines. Furthermore, we will provide qualitative evidence to aid decisions made by low- and middle-income countries' ministries of health about investments in these technologies. ©Jhon Camacho, Ana María Medina Ch, Zach Landis-Lewis, Gerald Douglas, Richard Boyce. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 13.04.2018.

What perceptions do patients have of decision making (DM)? Toward an integrative patient-centered care model. A qualitative study using focus-group interviews.

PubMed

Moreau, Alain; Carol, Laurent; Dedianne, Marie Cécile; Dupraz, Christian; Perdrix, Corinne; Lainé, Xavier; Souweine, Gilbert

2012-05-01

To understand patients' perceptions of decision making and identify relationships among decision-making models. This qualitative study was made up of four focus group interviews (elderly persons, users of health support groups, students, and rural inhabitants). Participants were asked to report their perceptions of decision making in three written clinical scenarios (hypertension, breast cancer, prostate cancer). The analysis was based on the principles of grounded theory. Most patients perceived decision making as shared decision making, a deliberative question-response interaction with the physician that allowed patients to be experts in obtaining clearer information, participating in the care process, and negotiating compromises with physician preferences. Requesting second opinions allowed patients to maintain control, even within the paternalistic model preferred by elderly persons. Facilitating factors (trust, qualitative non-verbal communication, time to think) and obstacles (serious/emergency situations, perceived inadequate scientific competence, problems making requests, fear of knowing) were also part of shared decision making. In the global concept of patient-centered care, shared decision making can be flexible and can integrate paternalistic and informative models. Physicians' expertise should be associated with biomedical and relational skills through listening to, informing, and advising patients, and by supporting patients' choices. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

[Shared decision making in breast cancer. Womens' attitudes].

PubMed

Martín-Fernández, Roberto; Abt-Sacks, Analía; Perestelo-Perez, Lilisbeth; Serrano-Aguilar, Pedro

2013-01-01

The patient autonomy and the greater role for women with breast cancer in the decisions about their health are recent issues in healthcare. The objective of this work is to identify and characterize the elements that influence them in treatment decisions. A phenomenological type qualitative study. Theoretical Sampling included 70 women diagnosed with breast cancer. 45 semi structured interviews and 3 focus groups were performed between October 2009 and July 2010 in 15 regions of Spain. The analysis was based on the principles of grounded theory with the support of Atlas.ti v6.1. Patients are likely to take an active or passive role regarding decision-making depending on different variables such as their age, the information available, their self-assessment as capable agents to make decisions and the relative importance given to physical appearance. As the disease progresses, it can cause a change in women attitude, from an initially passive attitude to a more active role. The attitude of health professionals concerning shared decision-making and the information they offer determines patient participation while the family plays an essential role as a support or reinforcement of decisions made by patients. The patients' attitude regarding the decision-making of patients is very variable, becoming increasingly important the emotional status, the level of information available and the influence of the context.

STARS - Supportability Trend Analysis and Reporting System for the National Space Transportation System

NASA Technical Reports Server (NTRS)

Graham, Leroy J.; Doempke, Gerald T.

1990-01-01

The concept, implementation, and long-range goals of a Supportability Trend Analysis and Reporting System (STARS) for the National Space Transportation System (NSTS) are discussed. The requirement was established as a direct result of the recommendations of the Rogers Commission investigation of the circumstances of the Space Shuttle Challenger accident. STARS outlines the requirements for the supportability-trend data collection, analysis, and reporting requirements that each of the project offices supporting the Space Shuttle are required to provide to the NSTS program office. STARS data give the historic and predictive logistics information necessary for all levels of NSTS management to make safe and cost-effective decisions concerning the smooth flow of Space Shuttle turnaround.

Gender Differences in Bladder Cancer Treatment Decision Making.

PubMed

Pozzar, Rachel A; Berry, Donna L

2017-03-01

To explore gender differences in bladder cancer treatment decision making.
. Secondary qualitative analysis of interview transcripts.
. One multidisciplinary genitourinary oncology clinic (Dana-Farber Cancer Institute) and two urology clinics (Brigham and Women's Hospital and Beth Israel Deaconess Medical Center) in Boston, MA.
. As part of the original study, 45 men and 15 women with bladder cancer participated in individual interviews. Participants were primarily Caucasian, and most had at least some college education.
. Word frequency reports were used to identify thematic differences between the men's and women's statements. Line-by-line coding of constructs prevalent among women was then performed on all participants in NVivo 9. Coding results were compared between genders using matrix coding queries.
. The role of family in the decision-making process was found to be a dominant theme for women but not for men. Women primarily described family members as facilitators of bladder cancer treatment-related decisions, but men were more likely to describe family in a nonsupportive role.
. The results suggest that influences on the decision-making process are different for men and women with bladder cancer. Family may play a particularly important role for women faced with bladder cancer treatment-related decisions.
. Clinical nurses who care for individuals with bladder cancer should routinely assess patients' support systems and desired level of family participation in decision making. For some people with bladder cancer, family may serve as a stressor. Nurses should support the decision-making processes of all patients and be familiar with resources that can provide support to patients who do not receive it from family.

Selecting essential information for biosurveillance--a multi-criteria decision analysis.

PubMed

Generous, Nicholas; Margevicius, Kristen J; Taylor-McCabe, Kirsten J; Brown, Mac; Daniel, W Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina

2014-01-01

The National Strategy for Biosurveillance defines biosurveillance as "the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels." However, the strategy does not specify how "essential information" is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being "essential". The question of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of "essential information" for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system.

Registered nurses' decision-making regarding documentation in patients' progress notes.

PubMed

Tower, Marion; Chaboyer, Wendy; Green, Quentine; Dyer, Kirsten; Wallis, Marianne

2012-10-01

To examine registered nurses' decision-making when documenting care in patients' progress notes. What constitutes effective nursing documentation is supported by available guidelines. However, ineffective documentation continues to be cited as a major cause of adverse events for patients. Decision-making in clinical practice is a complex process. To make an effective decision, the decision-maker must be situationally aware. The concept of situation awareness and its implications for making safe decisions has been examined extensively in air safety and more recently is being applied to health. The study was situated in a naturalistic paradigm. Purposive sampling was used to recruit 17 registered nurses who used think-aloud research methods when making decisions about documenting information in patients' progress notes. Follow-up interviews were conducted to validate interpretations. Data were analysed systematically for evidence of cues that demonstrated situation awareness as nurses made decisions about documentation. Three distinct decision-making scenarios were illuminated from the analysis: the newly admitted patient, the patient whose condition was as expected and the discharging patient. Nurses used mental models for decision-making in documenting in progress notes, and the cues nurses used to direct their assessment of patients' needs demonstrated situation awareness at different levels. Nurses demonstrate situation awareness at different levels in their decision-making processes. While situation awareness is important, it is also important to use an appropriate decision-making framework. Cognitive continuum theory is suggested as a decision-making model that could support situation awareness when nurses made decisions about documenting patient care. Because nurses are key decision-makers, it is imperative that effective decisions are made that translate into safe clinical care. Including situation awareness training, combined with employing cognitive continuum theory as a decision-making framework, provides a powerful means of guiding nurses' decision-making. © 2012 Blackwell Publishing Ltd.

An integrated modeling approach to support management decisions of coupled groundwater-agricultural systems under multiple uncertainties

NASA Astrophysics Data System (ADS)

Hagos Subagadis, Yohannes; Schütze, Niels; Grundmann, Jens

2015-04-01

The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational frameworks. Such integrative research to link different knowledge domains faces several practical challenges. Such complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions. A fuzzy-stochastic multiple criteria decision analysis tool was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrated physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework. Subsequently, the proposed new approach is applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structure. Results from the developed method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach has enabled to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. Sensitivity analysis applied within the developed tool has shown that the decision makers' risk aversion and risk taking attitude may yield in different ranking of decision alternatives. The developed approach can be applied to address the complexities and uncertainties inherent in water resources systems to support management decisions, while serving as a platform for stakeholder participation.

SU-E-J-04: A Data-Driven, Response-Based, Multi-Criteria Decision Support System for Personalized Lung Radiation Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Y; McShan, D; Schipper, M

2014-06-01

Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity tomore » different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more patients and demonstrated for use in radiation treatments for other cancers. P01-CA59827;R01CA142840.« less

Network meta-analysis: an introduction for pharmacists.

PubMed

Xu, Yina; Amiche, Mohamed Amine; Tadrous, Mina

2018-05-21

Network meta-analysis is a new tool used to summarize and compare studies for multiple interventions, irrespective of whether these interventions have been directly evaluated against each other. Network meta-analysis is quickly becoming the standard in conducting therapeutic reviews and clinical guideline development. However, little guidance is available to help pharmacists review network meta-analysis studies in their practice. Major institutions such as the Cochrane Collaboration, Agency for Healthcare Research and Quality, Canadian Agency for Drugs and Technologies in Health, and National Institute for Health and Care Excellence Decision Support Unit have endorsed utilizing network meta-analysis to establish therapeutic evidence and inform decision making. Our objective is to introduce this novel technique to pharmacy practitioners, and highlight key assumptions behind network meta-analysis studies.

Stream traffic data archival, querying, and analysis with TransDec.

DOT National Transportation Integrated Search

2011-01-01

The goal of research was to extend the traffic data analysis of the TransDec (short for : Transportation Decision-Making) system, which was developed under METRANS 09-26 : research grant. The TransDec system is a real-data driven system to support de...

Multicriteria decision model for retrofitting existing buildings

NASA Astrophysics Data System (ADS)

Bostenaru Dan, B.

2003-04-01

In this paper a model to decide which buildings from an urban area should be retrofitted is presented. The model has been cast into existing ones by choosing the decision rule, criterion weighting and decision support system types most suitable for the spatial problem of reducing earthquake risk in urban areas, considering existing spatial multiatributive and multiobjective decision methods and especially collaborative issues. Due to the participative character of the group decision problem "retrofitting existing buildings" the decision making model is based on interactivity. Buildings have been modeled following the criteria of spatial decision support systems. This includes identifying the corresponding spatial elements of buildings according to the information needs of actors from different sphaeres like architects, construction engineers and economists. The decision model aims to facilitate collaboration between this actors. The way of setting priorities interactivelly will be shown, by detailing the two phases: judgemental and computational, in this case site analysis, collection and evaluation of the unmodified data and converting survey data to information with computational methods using additional expert support. Buildings have been divided into spatial elements which are characteristic for the survey, present typical damages in case of an earthquake and are decisive for a better seismic behaviour in case of retrofitting. The paper describes the architectural and engineering characteristics as well as the structural damage for constuctions of different building ages on the example of building types in Bucharest, Romania in compressible and interdependent charts, based on field observation, reports from the 1977 earthquake and detailed studies made by the author together with a local engineer for the EERI Web Housing Encyclopedia. On this base criteria for setting priorities flow into the expert information contained in the system.

Reporting Data with "Over-the-Counter" Data Analysis Supports Increases Educators' Analysis Accuracy

ERIC Educational Resources Information Center

Rankin, Jenny Grant

2013-01-01

There is extensive research on the benefits of making data-informed decisions to improve learning, but these benefits rely on the data being effectively interpreted. Despite educators' above-average intellect and education levels, there is evidence many educators routinely misinterpret student data. Data analysis problems persist even at districts…

A Conceptual Framework for Decision-making Support in Uncertainty- and Risk-based Diagnosis of Rare Clinical Cases by Specialist Physicians.

PubMed

Santos, Adriano A; Moura, J Antão B; de Araújo, Joseana Macêdo Fechine Régis

2015-01-01

Mitigating uncertainty and risks faced by specialist physicians in analysis of rare clinical cases is something desired by anyone who needs health services. The number of clinical cases never seen by these experts, with little documentation, may introduce errors in decision-making. Such errors negatively affect well-being of patients, increase procedure costs, rework, health insurance premiums, and impair the reputation of specialists and medical systems involved. In this context, IT and Clinical Decision Support Systems (CDSS) play a fundamental role, supporting decision-making process, making it more efficient and effective, reducing a number of avoidable medical errors and enhancing quality of treatment given to patients. An investigation has been initiated to look into characteristics and solution requirements of this problem, model it, propose a general solution in terms of a conceptual risk-based, automated framework to support rare-case medical diagnostics and validate it by means of case studies. A preliminary validation study of the proposed framework has been carried out by interviews conducted with experts who are practicing professionals, academics, and researchers in health care. This paper summarizes the investigation and its positive results. These results motivate continuation of research towards development of the conceptual framework and of a software tool that implements the proposed model.

Distributed collaborative decision support environments for predictive awareness

NASA Astrophysics Data System (ADS)

McQuay, William K.; Stilman, Boris; Yakhnis, Vlad

2005-05-01

The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, rapidly assess the enemy"s course of action (eCOA) or possible actions and promulgate their own course of action (COA) - a need for predictive awareness. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Revolutionary new approaches to strategy generation and assessment such as Linguistic Geometry (LG) permit the rapid development of COA vs. enemy COA (eCOA). LG tools automatically generate and permit the operators to take advantage of winning strategies and tactics for mission planning and execution in near real-time. LG is predictive and employs deep "look-ahead" from the current state and provides a realistic, reactive model of adversary reasoning and behavior. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing research efforts in applying distributed collaborative environments to decision support for predictive mission awareness.

Seeing the NICE side of cost-effectiveness analysis: a qualitative investigation of the use of CEA in NICE technology appraisals.

PubMed

Bryan, Stirling; Williams, Iestyn; McIver, Shirley

2007-02-01

Resource scarcity is the raison d'être for the discipline of economics. Thus, the primary purpose of economic analysis is to help decision-makers when addressing problems arising due to the scarcity problem. The research reported here was concerned with how cost-effectiveness information is used by the National Institute for Health & Clinical Excellence (NICE) in national technology coverage decisions in the UK, and how its impact might be increased. The research followed a qualitative case study methodology with semi-structured interviews, supported by observation and analysis of secondary sources. Our research highlights that the technology appraisal function of NICE represents an important progression for the UK health economics community: new cost-effectiveness work is commissioned for each technology and that work directly informs national health policy. However, accountability in policy decisions necessitates that the information upon which decisions are based (including cost-effectiveness analysis, CEA) is accessible. This was found to be a serious problem and represents one of the main ongoing challenges. Other issues highlighted include perceived weaknesses in analysis methods and the poor alignment between the health maximisation objectives assumed in economic analyses and the range of other objectives facing decision-makers in reality. Copyright (c) 2006 John Wiley & Sons, Ltd.

The Development of a Humanitarian Health Ethics Analysis Tool.

PubMed

Fraser, Veronique; Hunt, Matthew R; de Laat, Sonya; Schwartz, Lisa

2015-08-01

Introduction Health care workers (HCWs) who participate in humanitarian aid work experience a range of ethical challenges in providing care and assistance to communities affected by war, disaster, or extreme poverty. Although there is increasing discussion of ethics in humanitarian health care practice and policy, there are very few resources available for humanitarian workers seeking ethical guidance in the field. To address this knowledge gap, a Humanitarian Health Ethics Analysis Tool (HHEAT) was developed and tested as an action-oriented resource to support humanitarian workers in ethical decision making. While ethical analysis tools increasingly have become prevalent in a variety of practice contexts over the past two decades, very few of these tools have undergone a process of empirical validation to assess their usefulness for practitioners. A qualitative study consisting of a series of six case-analysis sessions with 16 humanitarian HCWs was conducted to evaluate and refine the HHEAT. Participant feedback inspired the creation of a simplified and shortened version of the tool and prompted the development of an accompanying handbook. The study generated preliminary insight into the ethical deliberation processes of humanitarian health workers and highlighted different types of ethics support that humanitarian workers might find helpful in supporting the decision-making process.

Geospatial decision support systems for societal decision making

USGS Publications Warehouse

Bernknopf, R.L.

2005-01-01

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

Undergraduate Athletic Training Students' Influences on Career Decisions After Graduation

PubMed Central

Mazerolle, Stephanie M.; Gavin, Kerri E.; Pitney, William A.; Casa, Douglas J.; Burton, Laura

2012-01-01

Context Career opportunities for athletic training students (ATSs) have increased substantially over the past few years. However, ATSs commonly appear to be opting for a more diversified professional experience after graduation. With the diversity in available options, an understanding of career decision is imperative. Objective To use the theoretical framework of socialization to investigate the influential factors behind the postgraduation decisions of senior ATSs. Design Qualitative study. Setting Web-based management system and telephone interviews. Patients or Other Participants Twenty-two ATSs (16 females, 6 males; age = 22 ± 2 years) who graduated in May 2010 from 13 different programs accredited by the Commission on Accreditation of Athletic Training Education. Data Collection and Analysis All interviews were transcribed verbatim, and the data were analyzed inductively. Data analysis required independent coding by 2 athletic trainers for specific themes. Credibility of the results was confirmed via peer review, methodologic triangulation, and multiple analyst triangulation. Results Two higher-order themes emerged from the data analysis: persistence in athletic training (AT) and decision to leave AT. Faculty and clinical instructor support, marketability, and professional growth were supporting themes describing persistence in AT. Shift of interest away from AT, lack of respect for the AT profession, compensation, time commitment, and AT as a stepping stone were themes sustaining the reasons that ATSs leave AT. The aforementioned reasons to leave often were discussed collectively, generating a collective undesirable outlook on the AT profession. Conclusions Our results highlight the importance of faculty support, professional growth, and early socialization into AT. Socialization of pre–AT students could alter retention rates by providing in-depth information about the profession before students commit in their undergraduate education and by helping reduce attrition before entrance into the workforce. PMID:23182017

Neurocognitive enhancement or impairment? A systematic meta-analysis of prescription stimulant effects on processing speed, decision-making, planning, and cognitive perseveration.

PubMed

Marraccini, Marisa E; Weyandt, Lisa L; Rossi, Joseph S; Gudmundsdottir, Bergljot Gyda

2016-08-01

Increasing numbers of adults, particularly college students, are misusing prescription stimulants primarily for cognitive/academic enhancement, so it is critical to explore whether empirical findings support neurocognitive benefits of prescription stimulants. Previous meta-analytic studies have supported small benefits from prescription stimulants for the cognitive domains of inhibitory control and memory; however, no meta-analytic studies have examined the effects on processing speed or the potential impairment on other domains of cognition, including planning, decision-making, and cognitive perseveration. Therefore, the present study conducted a meta-analysis of the available literature examining the effects of prescription stimulants on specific measures of processing speed, planning, decision-making, and cognitive perseveration among healthy adult populations. The meta-analysis results indicated a positive influence of prescription stimulant medication on processing speed accuracy, with an overall mean effect size of g = 0.282 (95% CI [0.077, 0.488]; n = 345). Neither improvements nor impairments were revealed for planning time, planning accuracy, advantageous decision-making, or cognitive perseveration; however, findings are limited by the small number of studies examining these outcomes. Findings support that prescription stimulant medication may indeed act as a neurocognitive enhancer for accuracy measures of processing speed without impeding other areas of cognition. Considering that adults are already engaging in illegal use of prescription stimulants for academic enhancement, as well as the potential for stimulant misuse to have serious side effects, the establishment of public policies informed by interdisciplinary research surrounding this issue, whether restrictive or liberal, is of critical importance. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Do personal stories make patient decision aids more effective? A critical review of theory and evidence

PubMed Central

2013-01-01

Background Patient decision aids support people to make informed decisions between healthcare options. Personal stories provide illustrative examples of others’ experiences and are seen as a useful way to communicate information about health and illness. Evidence indicates that providing information within personal stories affects the judgments and values people have, and the choices they make, differentially from facts presented in non-narrative prose. It is unclear if including narrative communications within patient decision aids enhances their effectiveness to support people to make informed decisions. Methods A survey of primary empirical research employing a systematic review method investigated the effect of patient decision aids with or without a personal story on people’s healthcare judgements and decisions. Searches were carried out between 2005-2012 of electronic databases (Medline, PsycINFO), and reference lists of identified articles, review articles, and key authors. A narrative analysis described and synthesised findings. Results Of 734 citations identified, 11 were included describing 13 studies. All studies found participants’ judgments and/or decisions differed depending on whether or not their decision aid included a patient story. Knowledge was equally facilitated when the decision aids with and without stories had similar information content. Story-enhanced aids may help people recall information over time and/or their motivation to engage with health information. Personal stories affected both “system 1” (e.g., less counterfactual reasoning, more emotional reactions and perceptions) and “system 2” (e.g., more perceived deliberative decision making, more stable evaluations over time) decision-making strategies. Findings exploring associations with narrative communications, decision quality measures, and different levels of literacy and numeracy were mixed. The pattern of findings was similar for both experimental and real-world studies. Conclusions There is insufficient evidence that adding personal stories to decision aids increases their effectiveness to support people’s informed decision making. More rigorous research is required to elicit evidence about the type of personal story that a) encourages people to make more reasoned decisions, b) discourages people from making choices based on another’s values, and c) motivates people equally to engage with healthcare resources. PMID:24625283

Fusion Analytics: A Data Integration System for Public Health and Medical Disaster Response Decision Support

PubMed Central

Passman, Dina B.

2013-01-01

Objective The objective of this demonstration is to show conference attendees how they can integrate, analyze, and visualize diverse data type data from across a variety of systems by leveraging an off-the-shelf enterprise business intelligence (EBI) solution to support decision-making in disasters. Introduction Fusion Analytics is the data integration system developed by the Fusion Cell at the U.S. Department of Health and Human Services (HHS), Office of the Assistant Secretary for Preparedness and Response (ASPR). Fusion Analytics meaningfully augments traditional public and population health surveillance reporting by providing web-based data analysis and visualization tools. Methods Fusion Analytics serves as a one-stop-shop for the web-based data visualizations of multiple real-time data sources within ASPR. The 24-7 web availability makes it an ideal analytic tool for situational awareness and response allowing stakeholders to access the portal from any internet-enabled device without installing any software. The Fusion Analytics data integration system was built using off-the-shelf EBI software. Fusion Analytics leverages the full power of statistical analysis software and delivers reports to users in a secure web-based environment. Fusion Analytics provides an example of how public health staff can develop and deploy a robust public health informatics solution using an off-the shelf product and with limited development funding. It also provides the unique example of a public health information system that combines patient data for traditional disease surveillance with manpower and resource data to provide overall decision support for federal public health and medical disaster response operations. Conclusions We are currently in a unique position within public health. One the one hand, we have been gaining greater and greater access to electronic data of all kinds over the last few years. On the other, we are working in a time of reduced government spending to support leveraging this data for decision support with robust analytics and visualizations. Fusion Analytics provides an opportunity for attendees to see how various types of data are integrated into a single application for population health decision support. It also can provide them with ideas of how they can use their own staff to create analyses and reports that support their public health activities.

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

PubMed

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.

Applicability of aquifer impact models to support decisions at CO 2 sequestration sites

DOE PAGES

Keating, Elizabeth; Bacon, Diana; Carroll, Susan; ...

2016-07-25

The National Risk Assessment Partnership has developed a suite of tools to assess and manage risk at CO 2 sequestration sites. This capability includes polynomial or look-up table based reduced-order models (ROMs) that predict the impact of CO 2 and brine leaks on overlying aquifers. The development of these computationally-efficient models and the underlying reactive transport simulations they emulate has been documented elsewhere (Carroll et al., 2014a; Carroll et al., 2014b; Dai et al., 2014 ; Keating et al., 2016). Here in this paper, we seek to demonstrate applicability of ROM-based analysis by considering what types of decisions and aquifermore » types would benefit from the ROM analysis. We present four hypothetical examples where applying ROMs, in ensemble mode, could support decisions during a geologic CO 2 sequestration project. These decisions pertain to site selection, site characterization, monitoring network evaluation, and health impacts. In all cases, we consider potential brine/CO 2 leak rates at the base of the aquifer to be uncertain. We show that derived probabilities provide information relevant to the decision at hand. Although the ROMs were developed using site-specific data from two aquifers (High Plains and Edwards), the models accept aquifer characteristics as variable inputs and so they may have more broad applicability. We conclude that pH and TDS predictions are the most transferable to other aquifers based on the analysis of the nine water quality metrics (pH, TDS, 4 trace metals, 3 organic compounds). Guidelines are presented for determining the aquifer types for which the ROMs should be applicable.« less

Crisis management: an extended reference framework for decision makers.

PubMed

Carone, Alessandro; Iorio, Luigi Di

2013-01-01

The paper discusses a reference framework for capabilities supporting effective crisis management. This framework has been developed by joining experiences in the field and knowledge of organisational models for crisis management, and executives' empowerment, coaching and behavioural analysis. The paper is aimed at offering further insight to executives on critical success factors and means for managing crisis situations by extending the scope of analysis to human behaviour, to emotions and fears and their correlation with decision making. It is further intended to help familiarise them and to facilitate approaching a path towards emotional awareness.

Transportation Big Data: Unbiased Analysis and Tools to Inform Sustainable Transportation Decisions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Today, transportation operation and energy systems data are generated at an unprecedented scale. The U.S. Department of Energy's National Renewable Energy Laboratory (NREL) is the go-to source for expertise in providing data and analysis to inform industry and government transportation decision making. The lab's teams of data experts and engineers are mining and analyzing large sets of complex data -- or 'big data' -- to develop solutions that support the research, development, and deployment of market-ready technologies that reduce fuel consumption and greenhouse gas emissions.

Decision Support System for Medical Care Quality Assessment Based on Health Records Analysis in Russia.

PubMed

Taranik, Maksim; Kopanitsa, Georgy

2017-01-01

The paper presents developed decision system, oriented for healthcare providers. The system allows healthcare providers to detect and decrease nonconformities in health records and forecast the sum of insurance payments taking into account nonconformities. The components are ISO13606, fuzzy logic and case-based reasoning concept. The result of system implementation allowed to 10% increase insurance payments for healthcare provider.

Experimental manipulation of psychosocial exposure and questionnaire sensitivity in a simulated manufacturing setting.

PubMed

Ikuma, Laura H; Babski-Reeves, Kari; Nussbaum, Maury A

2009-05-01

The objectives of this study were to determine the efficacy of experimental manipulations of psychosocial exposures and to evaluate the sensitivity of a psychosocial questionnaire by determining the factors perceived. A 50-item questionnaire was developed from the job content questionnaire (JCQ) and the quality of worklife survey (QWL). The experiment involved simulated work at different physical and psychosocial levels. Forty-eight participants were exposed to two levels of one psychosocial manipulation (job control, job demands, social support, or time pressure). Significantly different questionnaire responses supported the effectiveness of psychosocial manipulations. Exploratory factor analysis revealed five factors: skill discretion and decision authority, stress level and supervisor support, physical demands, quality of coworker support, and decision-making support. These results suggest that psychosocial factors can be manipulated experimentally, and that questionnaires can distinguish perceptions of these factors. These questionnaires may be used to assess perceptions of psychosocial factors in experimental settings.

The role of social support in facilitating postpartum women's return to employment.

PubMed

Killien, Marcia Gruis

2005-01-01

More than half of mothers with infants under 1 year are employed. This study explored the role of social support in facilitating women's return to employment during the 1st year postpartum. Analysis of existing longitudinal, repeated-measures questionnaire data gathered at 4 and 12 months postpartum. 94 postpartum women who were married or partnered, employed, and residing in a large urban area in the northwestern United States. Satisfaction with decision to return to work, role performance, work-family balance. Relationships between indicators of social support and return-to-work experiences were absent to modest. Satisfaction with child care was related to satisfaction with the decision to return to work. Workplace support was related to work-family balance at 12 months postpartum. Satisfactory child care arrangements and supportive relationships in the workplace are the most significant facilitators of women's return to work postpartum.

Reduction in chemotherapy order errors with computerised physician order entry and clinical decision support systems.

PubMed

Aziz, Muhammad Tahir; Ur-Rehman, Tofeeq; Qureshi, Sadia; Bukhari, Nadeem Irfan

Medication errors in chemotherapy are frequent and lead to patient morbidity and mortality, as well as increased rates of re-admission and length of stay, and considerable extra costs. Objective: This study investigated the proposition that computerised chemotherapy ordering reduces the incidence and severity of chemotherapy protocol errors. A computerised physician order entry of chemotherapy order (C-CO) with clinical decision support system was developed in-house, including standardised chemotherapy protocol definitions, automation of pharmacy distribution, clinical checks, labeling and invoicing. A prospective study was then conducted in a C-CO versus paper based chemotherapy order (P-CO) in a 30-bed chemotherapy bay of a tertiary hospital. Both C-CO and P-CO orders, including pharmacoeconomic analysis and the severity of medication errors, were checked and validated by a clinical pharmacist. A group analysis and field trial were also conducted to assess clarity, feasibility and decision making. The C-CO was very usable in terms of its clarity and feasibility. The incidence of medication errors was significantly lower in the C-CO compared with the P-CO (10/3765 [0.26%] versus 134/5514 [2.4%]). There was also a reduction in dispensing time of chemotherapy protocols in the C-CO. The chemotherapy computerisation with clinical decision support system resulted in a significant decrease in the occurrence and severity of medication errors, improvements in chemotherapy dispensing and administration times, and reduction of chemotherapy cost.

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

PubMed Central

2013-01-01

Background In many countries, the responsibility for planning and delivery of health services is devolved to the subnational level. Health programs, however, often fall short of efficient use of data to inform decisions. As a result, programs are not as effective as they can be at meeting the health needs of the populations they serve. In Kenya, a decision-support tool, the District Health Profile (DHP) tool was developed to integrate data from health programs, primarily HIV, at the district level and to enable district health management teams to review and monitor program progress for specific health issues to make informed service delivery decisions. Methods Thirteen in-depth interviews were conducted with ten tool users and three non-users in six districts to qualitatively assess the process of implementing the tool and its effect on data-informed decision making at the district level. The factors that affected use or non-use of the tool were also investigated. Respondents were selected via convenience sample from among those that had been trained to use the DHP tool except for one user who was self-taught to use the tool. Selection criteria also included respondents from urban districts with significant resources as well as respondents from more remote, under-resourced districts. Results Findings from the in-depth interviews suggest that among those who used it, the DHP tool had a positive effect on data analysis, review, interpretation, and sharing at the district level. The automated function of the tool allowed for faster data sharing and immediate observation of trends that facilitated data-informed decision making. All respondents stated that the DHP tool assisted them to better target existing services in need of improvement and to plan future services, thus positively influencing program improvement. Conclusions This paper stresses the central role that a targeted decision-support tool can play in making data aggregation, analysis, and presentation easier and faster. The visual synthesis of data facilitates the use of information in health decision making at the district level of a health system and promotes program improvement. The experience in Kenya can be applied to other countries that face challenges making district-level, data-informed decisions with data from fragmented information systems. PMID:24011028

Psychosocial work environment in school and students' somatic health complaints: An analysis of buffering resources.

PubMed

Sonmark, Kristina; Modin, Bitte

2017-02-01

This study explores the association between the psychosocial work environment in school and students' somatic health complaints. With its point of departure from the Demand-Control-Support (DCS) model, the aim was to examine how aspects of decision control and social support can moderate stress-related health implications of high psychological demands. Data come from two cross-sectional waves of the Swedish version of Health Behaviour in School-aged Children (HBSC 2005/2006 and 2009/2010), which consists of a total of 9427 11-, 13- and 15-year-old students. A two-level random intercept model was applied, with school class as the level 2 unit. Findings showed significant associations between school demands and somatic health complaints for all studied age groups, with a slight increase in strength with age. Decision control as well as social support from teachers, parents and peers consistently predicted a favorable association with health. An age pattern emerged in the analyses of stress-moderating resources. For 11 year olds parental support was the only resource that displayed a significant interaction with demands in relation to somatic health complaints, whereas for 13 year olds, decision control and support from teachers and parents all demonstrated moderating effects on student health. For 15 year olds, however, it was peer support that acted as a buffering resource in the studied relationship. The psychosocial work environment is an important predictor of students' health complaints. Overall, social support was a better stress-moderating resource than decision control, but some "buffers" were more important at certain ages than others.

Overview of NASA Langley's Systems Analysis Capabilities

NASA Technical Reports Server (NTRS)

Cavanaugh, Stephen; Kumar, Ajay; Brewer, Laura; Kimmel, Bill; Korte, John; Moul, Tom

2006-01-01

The Systems Analysis and Concepts Directorate (SACD) has been in the systems analysis business line supporting National Aeronautics and Space Administration (NASA) aeronautics, exploration, space operations and science since the 1960 s. Our current organization structure is shown in Figure 1. SACD mission can be summed up in the following statements: 1. We conduct advanced concepts for Agency decision makers and programs. 2. We provide aerospace systems analysis products such as mission architectures, advanced system concepts, system and technology trades, life cycle cost and risk analysis, system integration and pre-decisional sensitive information. 3. Our work enables informed technical, programmatic and budgetary decisions. SACD has a complement of 114 government employees and approximately 50 on-site contractors which is equally split between supporting aeronautics and exploration. SACD strives for technical excellence and creditability of the systems analysis products delivered to its customers. The Directorate office is continuously building market intelligence and working with other NASA centers and external partners to expand our business base. The Branches strive for technical excellence and credibility of our systems analysis products by seeking out existing and new partnerships that are critical for successful systems analysis. The Directorates long term goal is to grow the amount of science systems analysis business base.

The relationship between social support, shared decision-making and patient's trust in doctors: a cross-sectional survey of 2,197 inpatients using the Cologne Patient Questionnaire.

PubMed

Ommen, Oliver; Thuem, Sonja; Pfaff, Holger; Janssen, Christian

2011-06-01

Empirical studies have confirmed that a trusting physician-patient interaction promotes patient satisfaction, adherence to treatment and improved health outcomes. The objective of this analysis was to investigate the relationship between social support, shared decision-making and inpatient's trust in physicians in a hospital setting. A written questionnaire was completed by 2,197 patients who were treated in the year 2000 in six hospitals in Germany. Logistic regression was performed with a dichotomized index for patient's trust in physicians. The logistic regression model identified significant relationships (p < 0.05) in terms of emotional support (standardized effect coefficient [sc], 3.65), informational support (sc, 1.70), shared decision-making (sc, 1.40), age (sc, 1.14), socioeconomic status (sc, 1.15) and gender (sc, 1.15). We found no significant relationship between 'tendency to excuse' and trust. The last regression model accounted for 49.1% of Nagelkerke's R-square. Insufficient physician communication skills can lead to extensive negative effects on the trust of patients in their physicians. Thus, it becomes clear that medical support requires not only biomedical, but also psychosocial skills.

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

PubMed

Wright, Adam; Sittig, Dean F

2007-10-11

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

Practice of Supporting Young People with Chronic Health Conditions in Hospital and Schools

ERIC Educational Resources Information Center

St Leger, Pamela

2014-01-01

How do health professionals and teachers make decisions about supporting young people whose lives are disrupted by chronic health conditions to stay in touch with schooling? Analysis of the interview and focus group data from health and education professionals who participated in the "Keeping Connected" project reflected common…

Development, Implementation, and Analysis of an Environmental Simulation Information Reference Library and Archive (ESIRLA)

DTIC Science & Technology

1997-12-01

of the DoD environmental science community to identify cloud modeling and other environmental capabilities that support or could potentially support...benefit of the DoD environmental science community. STC determined the detailed requirements for weather effects products and decision aids for specific Air Force operational electro-optical systems.

Future of electronic health records: implications for decision support.

PubMed

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

2012-01-01

The potential benefits of the electronic health record over traditional paper are many, including cost containment, reductions in errors, and improved compliance by utilizing real-time data. The highest functional level of the electronic health record (EHR) is clinical decision support (CDS) and process automation, which are expected to enhance patient health and healthcare. The authors provide an overview of the progress in using patient data more efficiently and effectively through clinical decision support to improve health care delivery, how decision support impacts anesthesia practice, and how some are leading the way using these systems to solve need-specific issues. Clinical decision support uses passive or active decision support to modify clinician behavior through recommendations of specific actions. Recommendations may reduce medication errors, which would result in considerable savings by avoiding adverse drug events. In selected studies, clinical decision support has been shown to decrease the time to follow-up actions, and prediction has proved useful in forecasting patient outcomes, avoiding costs, and correctly prompting treatment plan modifications by clinicians before engaging in decision-making. Clinical documentation accuracy and completeness is improved by an electronic health record and greater relevance of care data is delivered. Clinical decision support may increase clinician adherence to clinical guidelines, but educational workshops may be equally effective. Unintentional consequences of clinical decision support, such as alert desensitization, can decrease the effectiveness of a system. Current anesthesia clinical decision support use includes antibiotic administration timing, improved documentation, more timely billing, and postoperative nausea and vomiting prophylaxis. Electronic health record implementation offers data-mining opportunities to improve operational, financial, and clinical processes. Using electronic health record data in real-time for decision support and process automation has the potential to both reduce costs and improve the quality of patient care. © 2012 Mount Sinai School of Medicine.

Application of a web-based Decision Support System in risk management

NASA Astrophysics Data System (ADS)

Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2013-04-01

Increasingly, risk information is widely available with the help of advanced technologies such as earth observation satellites, global positioning technologies, coupled with hazard modeling and analysis, and geographical information systems (GIS). Even though it exists, no effort will be put into action if it is not properly presented to the decision makers. These information need to be communicated clearly and show its usefulness so that people can make better informed decision. Therefore, communicating available risk information has become an important challenge and decision support systems have been one of the significant approaches which can help not only in presenting risk information to the decision makers but also in making efficient decisions while reducing human resources and time needed. In this study, the conceptual framework of an internet-based decision support system is presented to highlight its importance role in risk management framework and how it can be applied in case study areas chosen. The main purpose of the proposed system is to facilitate the available risk information in risk reduction by taking into account of the changes in climate, land use and socio-economic along with the risk scenarios. It allows the users to formulate, compare and select risk reduction scenarios (mainly for floods and landslides) through an enhanced participatory platform with diverse stakeholders' involvement in the decision making process. It is based on the three-tier (client-server) architecture which integrates web-GIS plus DSS functionalities together with cost benefit analysis and other supporting tools. Embedding web-GIS provides its end users to make better planning and informed decisions referenced to a geographical location, which is the one of the essential factors in disaster risk reduction programs. Different risk reduction measures of a specific area (local scale) will be evaluated using this web-GIS tool, available risk scenarios obtained from Probabilistic Risk Assessment (PRA) model and the knowledge collected from experts. The visualization of the risk reduction scenarios can also be shared among the users on the web to support the on-line participatory process. In addition, cost-benefit ratios of the different risk reduction scenarios can be prepared in order to serve as inputs for high-level decision makers. The most appropriate risk reduction scenarios will be chosen using Multi-Criteria Evaluation (MCE) method by weighting different parameters according to the preferences and criteria defined by the users. The role of public participation has been changing from one-way communication between authorities, experts, stakeholders and citizens towards more intensive two-way interaction. Involving the affected public and interest groups can enhance the level of legitimacy, transparency, and confidence in the decision making process. Due to its important part in decision making, online participatory tool is included in the DSS in order to allow the involved stakeholders interactively in risk reduction and be aware of the existing vulnerability conditions of the community. Moreover, it aims to achieve a more transparent and better informed decision-making process. The system is under in progress and the first tools implemented will be presented showing the wide possibilities of new web technologies which can have a great impact on the decision making process. It will be applied in four pilot areas in Europe: French Alps, North Eastern Italy, Romania and Poland. Nevertheless, the framework will be designed and implemented in a way to be applicable in any other regions.

Comparing multi-criteria decision analysis and integrated assessment to support long-term water supply planning

PubMed Central

Maurer, Max; Lienert, Judit

2017-01-01

We compare the use of multi-criteria decision analysis (MCDA)–or more precisely, models used in multi-attribute value theory (MAVT)–to integrated assessment (IA) models for supporting long-term water supply planning in a small town case study in Switzerland. They are used to evaluate thirteen system scale water supply alternatives in four future scenarios regarding forty-four objectives, covering technical, social, environmental, and economic aspects. The alternatives encompass both conventional and unconventional solutions and differ regarding technical, spatial and organizational characteristics. This paper focuses on the impact assessment and final evaluation step of the structured MCDA decision support process. We analyze the performance of the alternatives for ten stakeholders. We demonstrate the implications of model assumptions by comparing two IA and three MAVT evaluation model layouts of different complexity. For this comparison, we focus on the validity (ranking stability), desirability (value), and distinguishability (value range) of the alternatives given the five model layouts. These layouts exclude or include stakeholder preferences and uncertainties. Even though all five led us to identify the same best alternatives, they did not produce identical rankings. We found that the MAVT-type models provide higher distinguishability and a more robust basis for discussion than the IA-type models. The needed complexity of the model, however, should be determined based on the intended use of the model within the decision support process. The best-performing alternatives had consistently strong performance for all stakeholders and future scenarios, whereas the current water supply system was outperformed in all evaluation layouts. The best-performing alternatives comprise proactive pipe rehabilitation, adapted firefighting provisions, and decentralized water storage and/or treatment. We present recommendations for possible ways of improving water supply planning in the case study and beyond. PMID:28481881

Practical example of game theory application for production route selection

NASA Astrophysics Data System (ADS)

Olender, M.; Krenczyk, D.

2017-08-01

The opportunity which opens before manufacturers on the dynamic market, especially before those from the sector of the small and medium-sized enterprises, is associated with the use of the virtual organizations concept. The planning stage of such organizations could be based on supporting decision-making tasks using the tools and formalisms taken from the game theory. In the paper the model of the virtual manufacturing network, along with the practical example of decision-making situation as two person game and the decision strategies with an analysis of calculation results are presented.

Toward a Multilingual, Experiential Environment for Learning Decision Technology.

ERIC Educational Resources Information Center

Yeo, Gee Kin; Tan, Seng Teen

1999-01-01

Describes work at the National University of Singapore on the Internet in expanding a simulation game used in supporting a course in decision technology. Topics include decision support systems, multilingual support for cross-cultural decision studies, process support in a World Wide Web-enhanced multiuser domain (MUD) learning environment, and…

Maintenance and operations decision support tool : Clarus regional demonstrations.

DOT National Transportation Integrated Search

2011-01-01

Weather affects almost all maintenance activity decisions. The Federal Highway Administration (FHWA) tested a new decision support system for maintenance in Iowa, Indiana, and Illinois called the Maintenance and Operations Decision Support System (MO...

Synthesis of research on work zone delays and simplified application of QuickZone analysis tool.

DOT National Transportation Integrated Search

2010-03-01

The objectives of this project were to synthesize the latest information on work zone safety and management and identify case studies in which FHWAs decision support tool QuickZone or other appropriate analysis tools could be applied. The results ...

Market Analysis for Expansion of Surgical Services at USAF Medical Center Wright-Patterson.

DTIC Science & Technology

1991-04-22

Rockville, Maryland: Aspen Malhotra , Naresh K . (1989) Decision Support Systems for Health Care Marketing Managers, Journal of Health Care Marketing Vol 9...information processing, analysis, storage, and distribution. Authors including Nickels (1978), Kropf and Greenberg (1984), Keckley (1988) and Malhotra (1989

Radiation monitoring systems as a tool for assessment of accidental releases at the Chernobyl and Fukushima NPPs

NASA Astrophysics Data System (ADS)

Shershakov, Vjacheslav; Bulgakov, Vladimir

2013-04-01

The experience gained during mitigation of the consequences of the accidents at the Chernobyl and Fukushima NPPs has shown that what makes different the decision-making in case of nuclear accidents is that the greatest benefit from decision-making can be achieved in the early phase of an accident. Support to such process can be provided only by a real-time decision-making support system. In case of a nuclear accident the analysis of the situation and decision-making is not feasible without an operational radiation monitoring system, international data exchange and automated data processing, and the use of computerized decision-making support systems. With this in mind, in the framework of different international programs on the Chernobyl-related issues numerous projects were undertaken to study and develop a set of methods, algorithms and programs providing effective support to emergency response decision-making, starting from accident occurrence to decision-making regarding countermeasures to mitigate effects of radioactive contamination of the environment. The presentation focuses results of the analysis of radiation monitoring data and, on this basis, refining or, for many short-lived radionuclides, reconstructing the source term, modeling dispersion of radioactivity in the environment and assessing its impacts. The obtained results allowed adding and refining the existing estimates and in some cases reconstructing doses for the public on the territories contaminated as a result of the Chernobyl accident. The activities were implemented in two stages. In the first stage, several scenarios for dispersion of Chernobyl-related radioactivity were developed. For each scenario cesium-137 dispersion was estimated and these estimates were compared with measurement data. In the second stage, the scenario which showed the best agreement of calculations and measurements was used for modeling the dispersion of iodine-131and other short-lived radionuclides. The described approach was used for assessing the consequences at the Fukushima NPP. These results are also provided in the presentation. References 1. Kelly G.N., Ehrhardt J., Shershakov V.M.. Decision Support for Off-Site Emergency Preparedness in Europe. Radiation Protection Dosimetry, Vol. 64 Nos. 1-2, 1996, pp. 129-142. 2. Ehrhardt J., Shershakov V.M. Real-time on-line decision support systems (RODOS) for off-site emergency management following a nuclear accident. EUR 16533, 1996 3. Kelly G.N., Shershakov V.M. (Editors). Environmental contamination, radiation doses and health consequences after the ?hernobyl accident. Radiation Protection Dosimetry. Special Commemorative Issue.Vol. 64, 1996 4. Shershakov V.M. Computer information technology for support of radiation monitoring problems. OECD Proceedings of an International Workshop «Nuclear Emergency Data Management», Zurich, Switzerland, 1998, pp. 377-388 5. Pitkevich V.A., Duba V.V., Ivanov V.K., Tsyb A.F., Shershakov V.M., Golubenkov A.V., Borodin R.V., V.A., Kosykh V.S. Reconstruction of External Dose to the Inhabitants Living in the Contaminated Territory of Russia by the Results of the Accident at the Chernobyl NPP. Health Phys., Vol. 30, No. 1, pp. 54-68, 1995. 6. Shershakov V., Fesenko S., Kryshev I., Semioshkina T. Decision-Aiding Tools for Remediation Strategies. In: Radioactivity in the Environment, Volume 14, Remediation of Contaminated Environments, 2009, pp 41- 120, Elsevier Ltd.

Multi-criteria decision making--an approach to setting priorities in health care.

PubMed

Nobre, F F; Trotta, L T; Gomes, L F

1999-12-15

The objective of this paper is to present a multi-criteria decision making (MCDM) approach to support public health decision making that takes into consideration the fuzziness of the decision goals and the behavioural aspect of the decision maker. The approach is used to analyse the process of health technology procurement in a University Hospital in Rio de Janeiro, Brazil. The method, known as TODIM, relies on evaluating alternatives with a set of decision criteria assessed using an ordinal scale. Fuzziness in generating criteria scores and weights or conflicts caused by dealing with different viewpoints of a group of decision makers (DMs) are solved using fuzzy set aggregation rules. The results suggested that MCDM models, incorporating fuzzy set approaches, should form a set of tools for public health decision making analysis, particularly when there are polarized opinions and conflicting objectives from the DM group. Copyright 1999 John Wiley & Sons, Ltd.

Communication-based behaviour support for adults with intellectual disabilities receiving dental care: A focus group study exploring dentists' decision-making and communication.

PubMed

Phadraig, Caoimhin Mac Giolla; Griffiths, Colin; McCallion, Philip; McCarron, Mary; Nunn, June

2017-01-01

A better understanding of how communication-based behaviour supports are applied with adults with intellectual disabilities may reduce reliance on restrictive practices such as holding, sedation and anaesthesia in dentistry. In this study, we explore how communication is used by dentists who provide treatment for adults with intellectual disabilities. A descriptive qualitative study, adopting synchronous online focus groups, was undertaken with six expert dentists in Ireland. Members were contacted again in pairs or individually for further data collection, analysed using thematic content analysis. Two relevant categories emerged from the data, relating to the selection and application of communication-based behaviour support for adults with intellectual disabilities. Decision-making processes were explored. Building on these categories, a co-regulating process of communication emerged as the means by which dentists iteratively apply and adapt communicative strategies. This exploration revealed rationalist and intuitive decision-making. Implications for education, practice and research are identified.

Integrating cost information with health management support system: an enhanced methodology to assess health care quality drivers.

PubMed

Kohli, R; Tan, J K; Piontek, F A; Ziege, D E; Groot, H

1999-08-01

Changes in health care delivery, reimbursement schemes, and organizational structure have required health organizations to manage the costs of providing patient care while maintaining high levels of clinical and patient satisfaction outcomes. Today, cost information, clinical outcomes, and patient satisfaction results must become more fully integrated if strategic competitiveness and benefits are to be realized in health management decision making, especially in multi-entity organizational settings. Unfortunately, traditional administrative and financial systems are not well equipped to cater to such information needs. This article presents a framework for the acquisition, generation, analysis, and reporting of cost information with clinical outcomes and patient satisfaction in the context of evolving health management and decision-support system technology. More specifically, the article focuses on an enhanced costing methodology for determining and producing improved, integrated cost-outcomes information. Implementation issues and areas for future research in cost-information management and decision-support domains are also discussed.

A new intuitionism: Meaning, memory, and development in Fuzzy-Trace Theory

PubMed Central

Reyna, Valerie F.

2014-01-01

Combining meaning, memory, and development, the perennially popular topic of intuition can be approached in a new way. Fuzzy-trace theory integrates these topics by distinguishing between meaning-based gist representations, which support fuzzy (yet advanced) intuition, and superficial verbatim representations of information, which support precise analysis. Here, I review the counterintuitive findings that led to the development of the theory and its most recent extensions to the neuroscience of risky decision making. These findings include memory interference (worse verbatim memory is associated with better reasoning); nonnumerical framing (framing effects increase when numbers are deleted from decision problems); developmental decreases in gray matter and increases in brain connectivity; developmental reversals in memory, judgment, and decision making (heuristics and biases based on gist increase from childhood to adulthood, challenging conceptions of rationality); and selective attention effects that provide critical tests comparing fuzzy-trace theory, expected utility theory, and its variants (e.g., prospect theory). Surprising implications for judgment and decision making in real life are also discussed, notably, that adaptive decision making relies mainly on gist-based intuition in law, medicine, and public health. PMID:25530822

A new intuitionism: Meaning, memory, and development in Fuzzy-Trace Theory.

PubMed

Reyna, Valerie F

2012-05-01

Combining meaning, memory, and development, the perennially popular topic of intuition can be approached in a new way. Fuzzy-trace theory integrates these topics by distinguishing between meaning-based gist representations, which support fuzzy (yet advanced) intuition, and superficial verbatim representations of information, which support precise analysis. Here, I review the counterintuitive findings that led to the development of the theory and its most recent extensions to the neuroscience of risky decision making. These findings include memory interference (worse verbatim memory is associated with better reasoning); nonnumerical framing (framing effects increase when numbers are deleted from decision problems); developmental decreases in gray matter and increases in brain connectivity; developmental reversals in memory, judgment, and decision making (heuristics and biases based on gist increase from childhood to adulthood, challenging conceptions of rationality); and selective attention effects that provide critical tests comparing fuzzy-trace theory, expected utility theory, and its variants (e.g., prospect theory). Surprising implications for judgment and decision making in real life are also discussed, notably, that adaptive decision making relies mainly on gist-based intuition in law, medicine, and public health.

Radio astronomy Explorer-B in-flight mission control system development effort

NASA Technical Reports Server (NTRS)

Lutsky, D. A.; Bjorkman, W. S.; Uphoff, C.

1973-01-01

A description is given of the development for the Mission Analysis Evaluation and Space Trajectory Operations (MAESTRO) program to be used for the in-flight decision making process during the translunar and lunar orbit adjustment phases of the flight of the Radio Astronomy Explorer-B. THe program serves two functions: performance and evaluation of preflight mission analysis, and in-flight support for the midcourse and lunar insertion command decisions that must be made by the flight director. The topics discussed include: analysis of program and midcourse guidance capabilities; methods for on-line control; printed displays of the MAESTRO program; and in-flight operational logistics and testing.

[Medical expert systems and clinical needs].

PubMed

Buscher, H P

1991-10-18

The rapid expansion of computer-based systems for problem solving or decision making in medicine, the so-called medical expert systems, emphasize the need for reappraisal of their indication and value. Where specialist knowledge is required, in particular where medical decisions are susceptible to error these systems will probably serve as a valuable support. In the near future computer-based systems should be able to aid the interpretation of findings of technical investigations and the control of treatment, especially where rapid reactions are necessary despite the need of complex analysis of investigated parameters. In the distant future complete support of diagnostic procedures from the history to final diagnosis is possible. It promises to be particularly attractive for the diagnosis of seldom diseases, for difficult differential diagnoses, and in the decision making in the case of expensive, risky or new diagnostic or therapeutic methods. The physician needs to be aware of certain dangers, ranging from misleading information up to abuse. Patient information depends often on subjective reports and error-prone observations. Although basing on problematic knowledge computer-born decisions may have an imperative effect on medical decision making. Also it must be born in mind that medical decisions should always combine the rational with a consideration of human motives.

Wildfire Decision Making Under Uncertainty

NASA Astrophysics Data System (ADS)

Thompson, M.

2013-12-01

Decisions relating to wildfire management are subject to multiple sources of uncertainty, and are made by a broad range of individuals, across a multitude of environmental and socioeconomic contexts. In this presentation I will review progress towards identification and characterization of uncertainties and how this information can support wildfire decision-making. First, I will review a typology of uncertainties common to wildfire management, highlighting some of the more salient sources of uncertainty and how they present challenges to assessing wildfire risk. This discussion will cover the expanding role of burn probability modeling, approaches for characterizing fire effects, and the role of multi-criteria decision analysis, and will provide illustrative examples of integrated wildfire risk assessment across a variety of planning scales. Second, I will describe a related uncertainty typology that focuses on the human dimensions of wildfire management, specifically addressing how social, psychological, and institutional factors may impair cost-effective risk mitigation. This discussion will encompass decision processes before, during, and after fire events, with a specific focus on active management of complex wildfire incidents. An improved ability to characterize uncertainties faced in wildfire management could lead to improved delivery of decision support, targeted communication strategies, and ultimately to improved wildfire management outcomes.

Uncertainty and probability in wildfire management decision support: An example from the United States [Chapter 4

Treesearch

Matthew Thompson; David Calkin; Joe H. Scott; Michael Hand

2017-01-01

Wildfire risk assessment is increasingly being adopted to support federal wildfire management decisions in the United States. Existing decision support systems, specifically the Wildland Fire Decision Support System (WFDSS), provide a rich set of probabilistic and risk‐based information to support the management of active wildfire incidents. WFDSS offers a wide range...

Interprofessional practice and decision support: an organizational framework applied to a mental health setting.

PubMed

Campbell, Susan; Stowe, Karen; Ozanne, Elissa M

2011-11-01

Decision support as a means to assist people in making healthcare decisions has been discussed extensively in the medical literature. However, the potential for use of decision support and decision aids with people with psychiatric disabilities in order to promote recovery has only begun to be researched and discussed in the mental health literature. Organizational factors that foster interprofessional practice within a decision support environment focused on mental health issues are examined in this paper.

Analysis of methods of processing of expert information by optimization of administrative decisions

NASA Astrophysics Data System (ADS)

Churakov, D. Y.; Tsarkova, E. G.; Marchenko, N. D.; Grechishnikov, E. V.

2018-03-01

In the real operation the measure definition methodology in case of expert estimation of quality and reliability of application-oriented software products is offered. In operation methods of aggregation of expert estimates on the example of a collective choice of an instrumental control projects in case of software development of a special purpose for needs of institutions are described. Results of operation of dialogue decision making support system are given an algorithm of the decision of the task of a choice on the basis of a method of the analysis of hierarchies and also. The developed algorithm can be applied by development of expert systems to the solution of a wide class of the tasks anyway connected to a multicriteria choice.

Watermark: An Application and Methodology and Application for Interactive and intelligent Decision Support for Groundwater Systems

NASA Astrophysics Data System (ADS)

Pierce, S. A.; Wagner, K.; Schwartz, S.; Gentle, J. N., Jr.

2016-12-01

Critical water resources face the effects of historic drought, increased demand, and potential contamination, the need has never been greater to develop resources to effectively communicate conservation and protection across a broad audience and geographical area. The Watermark application and macro-analysis methodology merges topical analysis of context rich corpus from policy texts with multi-attributed solution sets from integrated models of water resource and other subsystems, such as mineral, food, energy, or environmental systems to construct a scalable, robust, and reproducible approach for identifying links between policy and science knowledge bases. The Watermark application is an open-source, interactive workspace to support science-based visualization and decision making. Designed with generalization in mind, Watermark is a flexible platform that allows for data analysis and inclusion of large datasets with an interactive front-end capable of connecting with other applications as well as advanced computing resources. In addition, the Watermark analysis methodology offers functionality that streamlines communication with non-technical users for policy, education, or engagement with groups around scientific topics of societal relevance. The technology stack for Watermark was selected with the goal of creating a robust and dynamic modular codebase that can be adjusted to fit many use cases and scale to support usage loads that range between simple data display to complex scientific simulation-based modelling and analytics. The methodology uses to topical analysis and simulation-optimization to systematically analyze the policy and management realities of resource systems and explicitly connect the social and problem contexts with science-based and engineering knowledge from models. A case example demonstrates use in a complex groundwater resources management study highlighting multi-criteria spatial decision making and uncertainty comparisons.

The Effects of Perceptions of Organizational Structure on Job Involvement, Job Satisfaction, and Organizational Commitment Among Indian Police Officers.

PubMed

Lambert, Eric G; Qureshi, Hanif; Klahm, Charles; Smith, Brad; Frank, James

2017-12-01

Successful police organizations rely on involved, satisfied, and committed workers. The concepts of job involvement (i.e., connection with the job), job satisfaction (i.e., affective feeling toward the job), and organizational commitment (i.e., bond with the employing organization) have been shown to significantly affect intentions and behaviors of employees. The current study used multivariate ordinary least squares (OLS) regression analysis on survey results from a sample of 827 Indian police officers to explore how perceptions of work environment factors affect officers' job involvement, job satisfaction, and organizational commitment. Organizational support, formalization (i.e., level of codified written rules and guidelines), promotional opportunities, institutional communication (i.e., salient work information is transmitted), and input into decision-making (i.e., having a voice in the process) significantly influenced the job involvement, job satisfaction, and organizational commitment of Indian police officers. Specifically, in the multivariate analysis, perceptions of formalization and instrumental communication had a positive relationship with job involvement; perceptions of organizational support, promotional opportunities, instrumental communication, and input into decision-making had positive associations with job satisfaction; and perceptions of organizational support, formalization, promotional opportunities, instrumental communication, and input into decision-making had positive relationships with organizational commitment.

Use (and abuse) of expert elicitation in support of decision making for public policy

PubMed Central

Morgan, M. Granger

2014-01-01

The elicitation of scientific and technical judgments from experts, in the form of subjective probability distributions, can be a valuable addition to other forms of evidence in support of public policy decision making. This paper explores when it is sensible to perform such elicitation and how that can best be done. A number of key issues are discussed, including topics on which there are, and are not, experts who have knowledge that provides a basis for making informed predictive judgments; the inadequacy of only using qualitative uncertainty language; the role of cognitive heuristics and of overconfidence; the choice of experts; the development, refinement, and iterative testing of elicitation protocols that are designed to help experts to consider systematically all relevant knowledge when they make their judgments; the treatment of uncertainty about model functional form; diversity of expert opinion; and when it does or does not make sense to combine judgments from different experts. Although it may be tempting to view expert elicitation as a low-cost, low-effort alternative to conducting serious research and analysis, it is neither. Rather, expert elicitation should build on and use the best available research and analysis and be undertaken only when, given those, the state of knowledge will remain insufficient to support timely informed assessment and decision making. PMID:24821779

SMARTe 2008

EPA Science Inventory

Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains resources and analysis tools for all asp...

SMARTe 2011

EPA Science Inventory

Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decisions support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains resources and analysis tools for all a...

SMARTE 2007

EPA Science Inventory

Sustainable Management Approaches and Revitalization Tools-electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains guidance and analysis tools for all aspect...

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

PubMed

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

2011-04-10

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

Using wind plant data to increase reliability.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peters, Valerie A.; Ogilvie, Alistair B.; McKenney, Bridget L.

2011-01-01

Operators interested in improving reliability should begin with a focus on the performance of the wind plant as a whole. To then understand the factors which drive individual turbine performance, which together comprise the plant performance, it is necessary to track a number of key indicators. Analysis of these key indicators can reveal the type, frequency, and cause of failures and will also identify their contributions to overall plant performance. The ideal approach to using data to drive good decisions includes first determining which critical decisions can be based on data. When those required decisions are understood, then the analysismore » required to inform those decisions can be identified, and finally the data to be collected in support of those analyses can be determined. Once equipped with high-quality data and analysis capabilities, the key steps to data-based decision making for reliability improvements are to isolate possible improvements, select the improvements with largest return on investment (ROI), implement the selected improvements, and finally to track their impact.« less

An integrated decision support system for diagnosing and managing patients with community-acquired pneumonia.

PubMed Central

Aronsky, D.; Haug, P. J.

1999-01-01

Decision support systems that integrate guidelines have become popular applications to reduce variation and deliver cost-effective care. However, adverse characteristics of decision support systems, such as additional and time-consuming data entry or manually identifying eligible patients, result in a "behavioral bottleneck" that prevents decision support systems to become part of the clinical routine. This paper describes the design and the implementation of an integrated decision support system that explores a novel approach for bypassing the behavioral bottleneck. The real-time decision support system does not require health care providers to enter additional data and consists of a diagnostic and a management component. Images Fig. 1 Fig. 2 Fig. 3 PMID:10566348

Stakeholder views of management and decision support tools to integrate climate change into Great Lakes Lake Whitefish management

USGS Publications Warehouse

Lynch, Abigail J.; Taylor, William W.; McCright, Aaron M.

2016-01-01

Decision support tools can aid decision making by systematically incorporating information, accounting for uncertainties, and facilitating evaluation between alternatives. Without user buy-in, however, decision support tools can fail to influence decision-making processes. We surveyed fishery researchers, managers, and fishers affiliated with the Lake Whitefish Coregonus clupeaformis fishery in the 1836 Treaty Waters of Lakes Huron, Michigan, and Superior to assess opinions of current and future management needs to identify barriers to, and opportunities for, developing a decision support tool based on Lake Whitefish recruitment projections with climate change. Approximately 64% of 39 respondents were satisfied with current management, and nearly 85% agreed that science was well integrated into management programs. Though decision support tools can facilitate science integration into management, respondents suggest that they face significant implementation barriers, including lack of political will to change management and perceived uncertainty in decision support outputs. Recommendations from this survey can inform development of decision support tools for fishery management in the Great Lakes and other regions.

How modifiable factors influence parental decision-making about organ donation.

PubMed

Luberda, Kamila; Cleaver, Karen

2017-11-07

A global shortage of organs from children and adults available for transplantation is compounded by the failure of next of kin to consent for organs to be donated after death. Non-modifiable and modifiable factors influence decision-making in this area. Modifiable factors are of interest when examining families' decision-making about the donation of organs from their deceased child. A scoping review was undertaken to determine how modifiable factors influence parental decision-making about organ donation. Thematic analysis identified two themes: interactions with healthcare professionals and pre-disposition to organ donation. Satisfaction with experiences of hospital care, the information provided and the way it was communicated, as well as interactions pertaining to emotional support were all found to be modifiable factors that influenced decision making. Likewise, a predisposition to organ donation and knowing the deceased's wishes were associated with the consent decision. Nurses working in critical care environments need to be able to support parents during this difficult time. This article aims to raise awareness of modifiable factors that influence parental decision-making, highlighting their relevance for children's nursing practice. ©2017 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.

A risk-based decision support framework for selection of appropriate safety measure system for underground coal mines.

PubMed

Samantra, Chitrasen; Datta, Saurav; Mahapatra, Siba Sankar

2017-03-01

In the context of underground coal mining industry, the increased economic issues regarding implementation of additional safety measure systems, along with growing public awareness to ensure high level of workers safety, have put great pressure on the managers towards finding the best solution to ensure safe as well as economically viable alternative selection. Risk-based decision support system plays an important role in finding such solutions amongst candidate alternatives with respect to multiple decision criteria. Therefore, in this paper, a unified risk-based decision-making methodology has been proposed for selecting an appropriate safety measure system in relation to an underground coal mining industry with respect to multiple risk criteria such as financial risk, operating risk, and maintenance risk. The proposed methodology uses interval-valued fuzzy set theory for modelling vagueness and subjectivity in the estimates of fuzzy risk ratings for making appropriate decision. The methodology is based on the aggregative fuzzy risk analysis and multi-criteria decision making. The selection decisions are made within the context of understanding the total integrated risk that is likely to incur while adapting the particular safety system alternative. Effectiveness of the proposed methodology has been validated through a real-time case study. The result in the context of final priority ranking is seemed fairly consistent.

Conceptual and Empirical Approaches to Financial Decision-making by Older Adults: Results from a Financial Decision-Making Rating Scale

PubMed Central

Lichtenberg, Peter A.; Ocepek-Welikson, Katja; Ficker, Lisa J.; Gross, Evan; Rahman-Filipiak, Analise; Teresi, Jeanne A.

2017-01-01

Objectives The objectives of this study were threefold: (1) to empirically test the conceptual model proposed by the Lichtenberg Financial Decision Rating Scale (LFDRS); (2) to examine the psychometric properties of the LFDRS contextual factors in financial decision-making by investigating both the reliability and convergent validity of the subscales and total scale, and (3) extending previous work on the scale through the collection of normative data on financial decision-making. Methods A convenience sample of 200 independent function and community dwelling older adults underwent cognitive and financial management testing and were interviewed using the LFDRS. Confirmatory factor analysis, internal consistency measures, and hierarchical regression were used in a sample of 200 community-dwelling older adults, all of whom were making or had recently made a significant financial decision. Results Results confirmed the scale’s reliability and supported the conceptual model. Convergent validity analyses indicate that as hypothesized, cognition is a significant predictor of risk scores. Financial management scores, however, were not predictive of decision-making risk scores. Conclusions The psychometric properties of the LFDRS support the scale’s use as it was proposed in Lichtenberg et al., 2015. Clinical Implications The LFDRS instructions and scale are provided for clinicians to use in financial capacity assessments. PMID:29077531

Developing the U.S. Wildland Fire Decision Support System

Treesearch

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

2011-01-01

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

Decision Support for Ecosystem Management (Chapter 28)

Treesearch

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

1999-01-01

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

Two-Stage Fracturing Wastewater Management in Shale Gas Development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Xiaodong; Sun, Alexander Y.; Duncan, Ian J.

Here, management of shale gas wastewater treatment, disposal, and reuse has become a significant environmental challenge, driven by an ongoing boom in development of U.S. shale gas reservoirs. Systems-analysis based decision support is helpful for effective management of wastewater, and provision of cost-effective decision alternatives from a whole-system perspective. Uncertainties are inherent in many modeling parameters, affecting the generated decisions. In order to effectively deal with the recourse issue in decision making, in this work a two-stage stochastic fracturing wastewater management model, named TSWM, is developed to provide decision support for wastewater management planning in shale plays. Using the TSWMmore » model, probabilistic and nonprobabilistic uncertainties are effectively handled. The TSWM model provides flexibility in generating shale gas wastewater management strategies, in which the first-stage decision predefined by decision makers before uncertainties are unfolded is corrected in the second stage to achieve the whole-system’s optimality. Application of the TSWM model to a comprehensive synthetic example demonstrates its practical applicability and feasibility. Optimal results are generated for allowable wastewater quantities, excess wastewater, and capacity expansions of hazardous wastewater treatment plants to achieve the minimized total system cost. The obtained interval solutions encompass both optimistic and conservative decisions. Trade-offs between economic and environmental objectives are made depending on decision makers’ knowledge and judgment, as well as site-specific information. In conclusion, the proposed model is helpful in forming informed decisions for wastewater management associated with shale gas development.« less

Two-Stage Fracturing Wastewater Management in Shale Gas Development

DOE PAGES

Zhang, Xiaodong; Sun, Alexander Y.; Duncan, Ian J.; ...

2017-01-19

Here, management of shale gas wastewater treatment, disposal, and reuse has become a significant environmental challenge, driven by an ongoing boom in development of U.S. shale gas reservoirs. Systems-analysis based decision support is helpful for effective management of wastewater, and provision of cost-effective decision alternatives from a whole-system perspective. Uncertainties are inherent in many modeling parameters, affecting the generated decisions. In order to effectively deal with the recourse issue in decision making, in this work a two-stage stochastic fracturing wastewater management model, named TSWM, is developed to provide decision support for wastewater management planning in shale plays. Using the TSWMmore » model, probabilistic and nonprobabilistic uncertainties are effectively handled. The TSWM model provides flexibility in generating shale gas wastewater management strategies, in which the first-stage decision predefined by decision makers before uncertainties are unfolded is corrected in the second stage to achieve the whole-system’s optimality. Application of the TSWM model to a comprehensive synthetic example demonstrates its practical applicability and feasibility. Optimal results are generated for allowable wastewater quantities, excess wastewater, and capacity expansions of hazardous wastewater treatment plants to achieve the minimized total system cost. The obtained interval solutions encompass both optimistic and conservative decisions. Trade-offs between economic and environmental objectives are made depending on decision makers’ knowledge and judgment, as well as site-specific information. In conclusion, the proposed model is helpful in forming informed decisions for wastewater management associated with shale gas development.« less

Effect of counseling quality on anxiety, grief, and coping after second-trimester abortion for pregnancy complications.

PubMed

Kerns, Jennifer L; Mengesha, Biftu; McNamara, Blair C; Cassidy, Arianna; Pearlson, Geffan; Kuppermann, Miriam

2018-06-01

We sought to explore the relationship between counseling quality, measured by shared decision making and decision satisfaction, and psychological outcomes (anxiety, grief, and posttraumatic stress) after second-trimester abortion for pregnancy complications. We conducted a cross-sectional study of women who underwent second-trimester abortion for complications. We recruited participants from Facebook and online support groups and surveyed them about counseling experiences and psychosocial issues. We used multivariate linear regression to evaluate relationships between counseling quality and psychological outcomes. We analyzed data from 145 respondents. Shared decision making and decision satisfaction scores were positively and strongly correlated in bivariate analysis (r=0.7, p<.0001), as were posttraumatic stress and grief scores (r=0.7, p<.0001). In the adjusted analysis, higher decision satisfaction was associated with lower grief and posttraumatic stress scores (p=.02 and p=.01, respectively) and higher shared decision making was associated with lower posttraumatic stress scores (p=.01). Decision satisfaction and shared decision making have a positive effect on psychological outcomes after second-trimester abortion for pregnancy complications. Counseling quality may be especially important in this setting given the sensitive nature of decisions regarding pregnancy termination for complications. These results highlight the importance of patient-centered counseling for women seeking pregnancy termination. Copyright © 2018. Published by Elsevier Inc.

Scalable methodology for large scale building energy improvement: Relevance of calibration in model-based retrofit analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heo, Yeonsook; Augenbroe, Godfried; Graziano, Diane

2015-05-01

The increasing interest in retrofitting of existing buildings is motivated by the need to make a major contribution to enhancing building energy efficiency and reducing energy consumption and CO2 emission by the built environment. This paper examines the relevance of calibration in model-based analysis to support decision-making for energy and carbon efficiency retrofits of individual buildings and portfolios of buildings. The authors formulate a set of real retrofit decision-making situations and evaluate the role of calibration by using a case study that compares predictions and decisions from an uncalibrated model with those of a calibrated model. The case study illustratesmore » both the mechanics and outcomes of a practical alternative to the expert- and time-intense application of dynamic energy simulation models for large-scale retrofit decision-making under uncertainty.« less

Quick Fix for Managing Risks

NASA Technical Reports Server (NTRS)

2002-01-01

Under a Phase II SBIR contract, Kennedy and Lumina Decision Systems, Inc., jointly developed the Schedule and Cost Risk Analysis Modeling (SCRAM) system, based on a version of Lumina's flagship software product, Analytica(R). Acclaimed as "the best single decision-analysis program yet produced" by MacWorld magazine, Analytica is a "visual" tool used in decision-making environments worldwide to build, revise, and present business models, minus the time-consuming difficulty commonly associated with spreadsheets. With Analytica as their platform, Kennedy and Lumina created the SCRAM system in response to NASA's need to identify the importance of major delays in Shuttle ground processing, a critical function in project management and process improvement. As part of the SCRAM development project, Lumina designed a version of Analytica called the Analytica Design Engine (ADE) that can be easily incorporated into larger software systems. ADE was commercialized and utilized in many other developments, including web-based decision support.

From complex questionnaire and interviewing data to intelligent Bayesian Network models for medical decision support

PubMed Central

Constantinou, Anthony Costa; Fenton, Norman; Marsh, William; Radlinski, Lukasz

2016-01-01

Objectives 1) To develop a rigorous and repeatable method for building effective Bayesian network (BN) models for medical decision support from complex, unstructured and incomplete patient questionnaires and interviews that inevitably contain examples of repetitive, redundant and contradictory responses; 2) To exploit expert knowledge in the BN development since further data acquisition is usually not possible; 3) To ensure the BN model can be used for interventional analysis; 4) To demonstrate why using data alone to learn the model structure and parameters is often unsatisfactory even when extensive data is available. Method The method is based on applying a range of recent BN developments targeted at helping experts build BNs given limited data. While most of the components of the method are based on established work, its novelty is that it provides a rigorous consolidated and generalised framework that addresses the whole life-cycle of BN model development. The method is based on two original and recent validated BN models in forensic psychiatry, known as DSVM-MSS and DSVM-P. Results When employed with the same datasets, the DSVM-MSS demonstrated competitive to superior predictive performance (AUC scores 0.708 and 0.797) against the state-of-the-art (AUC scores ranging from 0.527 to 0.705), and the DSVM-P demonstrated superior predictive performance (cross-validated AUC score of 0.78) against the state-of-the-art (AUC scores ranging from 0.665 to 0.717). More importantly, the resulting models go beyond improving predictive accuracy and into usefulness for risk management purposes through intervention, and enhanced decision support in terms of answering complex clinical questions that are based on unobserved evidence. Conclusions This development process is applicable to any application domain which involves large-scale decision analysis based on such complex information, rather than based on data with hard facts, and in conjunction with the incorporation of expert knowledge for decision support via intervention. The novelty extends to challenging the decision scientists to reason about building models based on what information is really required for inference, rather than based on what data is available and hence, forces decision scientists to use available data in a much smarter way. PMID:26830286

From complex questionnaire and interviewing data to intelligent Bayesian network models for medical decision support.

PubMed

Constantinou, Anthony Costa; Fenton, Norman; Marsh, William; Radlinski, Lukasz

2016-02-01

(1) To develop a rigorous and repeatable method for building effective Bayesian network (BN) models for medical decision support from complex, unstructured and incomplete patient questionnaires and interviews that inevitably contain examples of repetitive, redundant and contradictory responses; (2) To exploit expert knowledge in the BN development since further data acquisition is usually not possible; (3) To ensure the BN model can be used for interventional analysis; (4) To demonstrate why using data alone to learn the model structure and parameters is often unsatisfactory even when extensive data is available. The method is based on applying a range of recent BN developments targeted at helping experts build BNs given limited data. While most of the components of the method are based on established work, its novelty is that it provides a rigorous consolidated and generalised framework that addresses the whole life-cycle of BN model development. The method is based on two original and recent validated BN models in forensic psychiatry, known as DSVM-MSS and DSVM-P. When employed with the same datasets, the DSVM-MSS demonstrated competitive to superior predictive performance (AUC scores 0.708 and 0.797) against the state-of-the-art (AUC scores ranging from 0.527 to 0.705), and the DSVM-P demonstrated superior predictive performance (cross-validated AUC score of 0.78) against the state-of-the-art (AUC scores ranging from 0.665 to 0.717). More importantly, the resulting models go beyond improving predictive accuracy and into usefulness for risk management purposes through intervention, and enhanced decision support in terms of answering complex clinical questions that are based on unobserved evidence. This development process is applicable to any application domain which involves large-scale decision analysis based on such complex information, rather than based on data with hard facts, and in conjunction with the incorporation of expert knowledge for decision support via intervention. The novelty extends to challenging the decision scientists to reason about building models based on what information is really required for inference, rather than based on what data is available and hence, forces decision scientists to use available data in a much smarter way. Copyright © 2016 Elsevier B.V. All rights reserved.

What's the point? The contribution of a sustainability view in contaminated site remediation.

PubMed

Anderson, Robert; Norrman, Jenny; Back, Pär-Erik; Söderqvist, Tore; Rosén, Lars

2018-07-15

Decision support tools (DST) are often used in remediation projects to aid in the complex decision on how best to remediate a contaminated site. In recent years, the sustainable remediation concept has brought increased attention to the often-overlooked contradictory effects of site remediation, with a number of sustainability assessment tools now available. The aim of the present study is twofold: (1) to demonstrate how and when different assessment views affect the decision support outcome on remediation alternatives in a DST, and (2) to demonstrate the contribution of a full sustainability assessment. The SCORE tool was used in the analysis; it is based on a holistic multi-criteria decision analysis (MCDA) approach, assessing sustainability in three dimensions: environmental, social, and economic. Four assessment scenarios, compared to a full sustainability assessment, were considered to reflect different possible assessment views; considering public and private problem owner perspectives, as well as green and traditional assessment scopes. Four real case study sites in Sweden were analyzed. The results show that the decision support outcome from a full sustainability assessment most often differs to that of other assessment views, and results in remediation alternatives which balance trade-offs in most of the scenarios. In relation to the public perspective and traditional scope, which is seen to lead to the most extensive and expensive remediation alternatives, the trade-off is related to less contaminant removal in favour of reduced negative secondary effects such as emissions and waste disposal. Compared to the private perspective, associated with the lowest cost alternatives, the trade-off is higher costs, but more positive environmental and social effects. Generally, both the green and traditional assessment scopes miss out on relevant social and local environmental secondary effects which may ultimately be very important for the actual decision in a remediation project. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

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:

Case based reasoning in criminal intelligence using forensic case data.

PubMed

Ribaux, O; Margot, P

2003-01-01

A model that is based on the knowledge of experienced investigators in the analysis of serial crime is suggested to bridge a gap between technology and methodology. Its purpose is to provide a solid methodology for the analysis of serial crimes that supports decision making in the deployment of resources, either by guiding proactive policing operations or helping the investigative process. Formalisation has helped to derive a computerised system that efficiently supports the reasoning processes in the analysis of serial crime. This novel approach fully integrates forensic science data.

Whose decision is it anyway? How clinicians support decision-making participation after acquired brain injury.

PubMed

Knox, Lucy; Douglas, Jacinta M; Bigby, Christine

2013-01-01

To raise professional awareness of factors that may influence the support offered by clinicians to people with acquired brain injury (ABI), and to consider the potential implications of these factors in terms of post-injury rehabilitation and living. A review of the literature was conducted to identify factors that determine how clinicians provide support and influence opportunities for individuals with ABI to participate in decision making across the rehabilitation continuum. Clinical case studies are used to highlight two specific issues: (1) hidden assumptions on the part of the practitioner, and (2) perceptions of risk operating in clinical practice. There are a range of factors which may influence the decision-making support provided by clinicians and, ultimately, shape lifetime outcomes for individuals with ABI. A multidimensional framework may assist clinicians to identify relevant factors and consider their potential implications including those that influence how clinicians involved in supporting decision making approach this task. Participation in decision making is an undisputed human right and central to the provision of person-centred care. Further research is required to understand how clinical practice can maximise both opportunities and support for increased decision-making participation by individuals with ABI. There is an increasing focus on the rights of all individuals to be supported to participate in decision making about their life. A number of changes associated with ABI mean that individuals with ABI will require support with decision making. Clinicians have a critical role in providing this support over the course of the rehabilitation continuum. Clinicians need to be aware of the range of factors that may influence the decision-making support they provide. A multidimensional framework may be used by clinicians to identify influences on the decision-making support they provide.

Clinical, information and business process modeling to promote development of safe and flexible software.

PubMed

Liaw, Siaw-Teng; Deveny, Elizabeth; Morrison, Iain; Lewis, Bryn

2006-09-01

Using a factorial vignette survey and modeling methodology, we developed clinical and information models - incorporating evidence base, key concepts, relevant terms, decision-making and workflow needed to practice safely and effectively - to guide the development of an integrated rule-based knowledge module to support prescribing decisions in asthma. We identified workflows, decision-making factors, factor use, and clinician information requirements. The Unified Modeling Language (UML) and public domain software and knowledge engineering tools (e.g. Protégé) were used, with the Australian GP Data Model as the starting point for expressing information needs. A Web Services service-oriented architecture approach was adopted within which to express functional needs, and clinical processes and workflows were expressed in the Business Process Execution Language (BPEL). This formal analysis and modeling methodology to define and capture the process and logic of prescribing best practice in a reference implementation is fundamental to tackling deficiencies in prescribing decision support software.

Service users' experiences of participation in decision making in mental health services.

PubMed

Dahlqvist Jönsson, P; Schön, U-K; Rosenberg, D; Sandlund, M; Svedberg, P

2015-11-01

Despite the potential positive impact of shared decision making on service users knowledge and experience of decisional conflict, there is a lack of qualitative research on how participation in decision making is promoted from the perspective of psychiatric service users. This study highlights the desire of users to participate more actively in decision making and demonstrates that persons with SMI struggle to be seen as competent and equal partners in decision-making situations. Those interviewed did not feel that their strengths, abilities and needs were being recognized, which resulted in a feeling of being omitted from involvement in decision-making situations. The service users describe some essential conditions that could work to promote participation in decision making. These included having personal support, having access to knowledge, being involved in a dialogue and clarity about responsibilities. Mental health nurses can play an essential role for developing and implementing shared decision making as a tool to promote recovery-oriented mental health services. Service user participation in decision making is considered an essential component of recovery-oriented mental health services. Despite the potential of shared decision making to impact service users knowledge and positively influence their experience of decisional conflict, there is a lack of qualitative research on how participation in decision making is promoted from the perspective of psychiatric service users. In order to develop concrete methods that facilitate shared decision making, there is a need for increased knowledge regarding the users' own perspective. The aim of this study was to explore users' experiences of participation in decisions in mental health services in Sweden, and the kinds of support that may promote participation. Constructivist Grounded Theory (CGT) was utilized to analyse group and individual interviews with 20 users with experience of serious mental illness. The core category that emerged in the analysis described a 'struggle to be perceived as a competent and equal person' while three related categories including being the underdog, being controlled and being omitted described the difficulties of participating in decisions. The data analysis resulted in a model that describes internal and external conditions that influence the promotion of participation in decision making. The findings offer new insights from a user perspective and these can be utilized to develop and investigate concrete methods in order to promote user's participation in decisions. © 2015 John Wiley & Sons Ltd.

System for Urban Stormwater Treatment and Analysis IntegratioN (SUSTAIN)

EPA Pesticide Factsheets

SUSTAIN is a decision support system that assists stormwater management professionals with developing and implementing plans for flow and pollution control measures to protect source waters and meet water quality goals.

Next generation terminology infrastructure to support interprofessional care planning.

PubMed

Collins, Sarah; Klinkenberg-Ramirez, Stephanie; Tsivkin, Kira; Mar, Perry L; Iskhakova, Dina; Nandigam, Hari; Samal, Lipika; Rocha, Roberto A

2017-11-01

Develop a prototype of an interprofessional terminology and information model infrastructure that can enable care planning applications to facilitate patient-centered care, learn care plan linkages and associations, provide decision support, and enable automated, prospective analytics. The study steps included a 3 step approach: (1) Process model and clinical scenario development, and (2) Requirements analysis, and (3) Development and validation of information and terminology models. Components of the terminology model include: Health Concerns, Goals, Decisions, Interventions, Assessments, and Evaluations. A terminology infrastructure should: (A) Include discrete care plan concepts; (B) Include sets of profession-specific concerns, decisions, and interventions; (C) Communicate rationales, anticipatory guidance, and guidelines that inform decisions among the care team; (D) Define semantic linkages across clinical events and professions; (E) Define sets of shared patient goals and sub-goals, including patient stated goals; (F) Capture evaluation toward achievement of goals. These requirements were mapped to AHRQ Care Coordination Measures Framework. This study used a constrained set of clinician-validated clinical scenarios. Terminology models for goals and decisions are unavailable in SNOMED CT, limiting the ability to evaluate these aspects of the proposed infrastructure. Defining and linking subsets of care planning concepts appears to be feasible, but also essential to model interprofessional care planning for common co-occurring conditions and chronic diseases. We recommend the creation of goal dynamics and decision concepts in SNOMED CT to further enable the necessary models. Systems with flexible terminology management infrastructure may enable intelligent decision support to identify conflicting and aligned concerns, goals, decisions, and interventions in shared care plans, ultimately decreasing documentation effort and cognitive burden for clinicians and patients. Copyright © 2017 Elsevier Inc. All rights reserved.

29 CFR 1926.64 - Process safety management of highly hazardous chemicals.

Code of Federal Regulations, 2011 CFR

2011-07-01

... analysis methodology being used. (5) The employer shall establish a system to promptly address the team's... the decision as to the appropriate PHA methodology to use. All PHA methodologies are subject to... be developed in conjunction with the process hazard analysis in sufficient detail to support the...

29 CFR 1910.119 - Process safety management of highly hazardous chemicals.

Code of Federal Regulations, 2011 CFR

2011-07-01

... complexity of the process will influence the decision as to the appropriate PHA methodology to use. All PHA... process hazard analysis in sufficient detail to support the analysis. (3) Information pertaining to the...) Relief system design and design basis; (E) Ventilation system design; (F) Design codes and standards...

29 CFR 1910.119 - Process safety management of highly hazardous chemicals.

Code of Federal Regulations, 2010 CFR

2010-07-01

... complexity of the process will influence the decision as to the appropriate PHA methodology to use. All PHA... process hazard analysis in sufficient detail to support the analysis. (3) Information pertaining to the...) Relief system design and design basis; (E) Ventilation system design; (F) Design codes and standards...

29 CFR 1926.64 - Process safety management of highly hazardous chemicals.

Code of Federal Regulations, 2010 CFR

2010-07-01

... analysis methodology being used. (5) The employer shall establish a system to promptly address the team's... the decision as to the appropriate PHA methodology to use. All PHA methodologies are subject to... be developed in conjunction with the process hazard analysis in sufficient detail to support the...

A Call for Strategic Planning: The Two-Year College Imperative.

ERIC Educational Resources Information Center

Masoner, David J.; Essex, Nathan, L.

1987-01-01

Addresses the imperative for strategic and tactical planning to support the viability of the two-year college. Describes a process for approaching strategic planning, comprising the following steps: self-identification, self-analysis, analysis of service area, informed decision making, and the development of a marketing plan. (CBC)

An uncertainty analysis of wildfire modeling [Chapter 13

Treesearch

Karin Riley; Matthew Thompson

2017-01-01

Before fire models can be understood, evaluated, and effectively applied to support decision making, model-based uncertainties must be analyzed. In this chapter, we identify and classify sources of uncertainty using an established analytical framework, and summarize results graphically in an uncertainty matrix. Our analysis facilitates characterization of the...

A Framework for the Selection of Electronic Marketplaces: A Content Analysis Approach.

ERIC Educational Resources Information Center

Stockdale, Rosemary; Standing, Craig

2002-01-01

Discussion of electronic marketplaces focuses on a content analysis of research and practitioner articles that evaluated issues that prospective participants, seeking to purchase goods and services online, need to address in their selection process. Proposes a framework to support electronic marketplace decision making that includes internal…

Requirements analysis report for transport estimation, preconstruction, construction, decision support and electronic bidding systems

DOT National Transportation Integrated Search

2009-01-01

Info Tech conducted an on-site visit at the Connecticut Department of Transportation in Newington : from October 27-31, 2008. The purpose of the visit was to conduct an analysis of ConnDOTs : processes and to review the operations and business sys...

A PC-Based Free Text DSS for Health Care

NASA Technical Reports Server (NTRS)

Grams, Ralph R.; Buchanan, Paul; Massey, James K.; Jin, Ming

1987-01-01

A free Decision Support System(DST) has been constructed for health care professional that allows the analysis of complex medical cases and the creation of diagnostic list of potential diseases for clinical evaluation.The system uses a PC-based text management system specifically designed for desktop operation. The texts employed in the decision support package include the Merck Manual (published by Merck Sharpe & Dohme) and Control of Communicable Diseas in Man (published by the American Public Health Association). The background and design of the database are discussed along with a structured analysis procedure for handling free text DSS system. A case study is presented to show the application of this technology and conclusions are drawn in the summary that point to expanded areas of professional intention and new frontiers yet to be explored in this rapidly progressing field.

Methods and decision making on a Mars rover for identification of fossils

NASA Technical Reports Server (NTRS)

Eberlein, Susan; Yates, Gigi

1989-01-01

A system for automated fusion and interpretation of image data from multiple sensors, including multispectral data from an imaging spectrometer is being developed. Classical artificial intelligence techniques and artificial neural networks are employed to make real time decision based on current input and known scientific goals. Emphasis is placed on identifying minerals which could indicate past life activity or an environment supportive of life. Multispectral data can be used for geological analysis because different minerals have characteristic spectral reflectance in the visible and near infrared range. Classification of each spectrum into a broad class, based on overall spectral shape and locations of absorption bands is possible in real time using artificial neural networks. The goal of the system is twofold: multisensor and multispectral data must be interpreted in real time so that potentially interesting sites can be flagged and investigated in more detail while the rover is near those sites; and the sensed data must be reduced to the most compact form possible without loss of crucial information. Autonomous decision making will allow a rover to achieve maximum scientific benefit from a mission. Both a classical rule based approach and a decision neural network for making real time choices are being considered. Neural nets may work well for adaptive decision making. A neural net can be trained to work in two steps. First, the actual input state is mapped to the closest of a number of memorized states. After weighing the importance of various input parameters, the net produces an output decision based on the matched memory state. Real time, autonomous image data analysis and decision making capabilities are required for achieving maximum scientific benefit from a rover mission. The system under development will enhance the chances of identifying fossils or environments capable of supporting life on Mars

Investigation of Capabilities and Technologies Supporting Rapid UAV Launch System Development

DTIC Science & Technology

2015-06-01

NUMBERS 6. AUTHOR(S) Patrick Alan Livesay 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School Monterey, CA 93943 8. PERFORMING ...to operate. This enabled the launcher design team to more clearly determine and articulate system require- ments and performance parameters. Next, a...Process (AHP) was performed to xvii prioritize the capabilities and assist in the decision-making process [1]. The AHP decision-analysis technique is

A Requirements Analysis Model for Selection of Personal Computer (PC) software in Air Force Organizations

DTIC Science & Technology

1988-09-01

Institute of Technology Air University In Partial Fulfillment of the Requirements for the Degree of Master of Science in Systems Management Dexter R... management system software Diag/Prob Diagnosis and problem solving or problem finding GR Graphics software Int/Transp Interoperability and...language software Plan/D.S. Planning and decision support or decision making PM Program management software SC Systems for Command, Control, Communications

Choosing Mars-Time: Analysis of the Mars Exploration Rover Experience

NASA Technical Reports Server (NTRS)

Bass, Deborah S.; Wales,Roxana C.; Shalin, Valerie L.

2004-01-01

This paper focuses on the Mars Exploration Rover (MER) mission decision to work on Mars Time and the implications of that decision on the tactical surface operations process as personnel planned activities and created a new command load for work on each Martian sol. The paper also looks at tools that supported the complexities of Mars Time work, and makes some comparisons between Earth and Mars time scheduling.

It’s Personal: Biology Instructors Prioritize Personal Evidence over Empirical Evidence in Teaching Decisions

PubMed Central

Andrews, Tessa C.; Lemons, Paula P.

2015-01-01

Despite many calls for undergraduate biology instructors to incorporate active learning into lecture courses, few studies have focused on what it takes for instructors to make this change. We sought to investigate the process of adopting and sustaining active-learning instruction. As a framework for our research, we used the innovation-decision model, a generalized model of how individuals adopt innovations. We interviewed 17 biology instructors who were attempting to implement case study teaching and conducted qualitative text analysis on interview data. The overarching theme that emerged from our analysis was that instructors prioritized personal experience—rather than empirical evidence—in decisions regarding case study teaching. We identified personal experiences that promote case study teaching, such as anecdotal observations of student outcomes, and those that hinder case study teaching, such as insufficient teaching skills. By analyzing the differences between experienced and new case study instructors, we discovered that new case study instructors need support to deal with unsupportive colleagues and to develop the skill set needed for an active-learning classroom. We generated hypotheses that are grounded in our data about effectively supporting instructors in adopting and sustaining active-learning strategies. We also synthesized our findings with existing literature to tailor the innovation-decision model. PMID:25713092

Personalized health care and health information technology policy: an exploratory analysis.

PubMed

Wald, Jonathan S; Shapiro, Michael

2013-01-01

Personalized healthcare (PHC) is envisioned to enhance clinical practice decision-making using new genome-driven knowledge that tailors diagnosis, treatment, and prevention to the individual patient. In 2012, we conducted a focused environmental scan and informal interviews with fifteen experts to anticipate how PHC might impact health Information Technology (IT) policy in the United States. Findings indicatedthat PHC has a variable impact on current clinical practice, creates complex questions for providers, patients, and policy-makers, and will require a robust health IT infrastructure with advanced data architecture, clinical decision support, provider workflow tools, and re-use of clinical data for research. A number of health IT challenge areas were identified, along with five policy areas including: interoperable clinical decision support, standards for patient values and preferences, patient engagement, data transparency, and robust privacy and security.

Brain network response underlying decisions about abstract reinforcers.

PubMed

Mills-Finnerty, Colleen; Hanson, Catherine; Hanson, Stephen Jose

2014-12-01

Decision making studies typically use tasks that involve concrete action-outcome contingencies, in which subjects do something and get something. No studies have addressed decision making involving abstract reinforcers, where there are no action-outcome contingencies and choices are entirely hypothetical. The present study examines these kinds of choices, as well as whether the same biases that exist for concrete reinforcer decisions, specifically framing effects, also apply during abstract reinforcer decisions. We use both General Linear Model as well as Bayes network connectivity analysis using the Independent Multi-sample Greedy Equivalence Search (IMaGES) algorithm to examine network response underlying choices for abstract reinforcers under positive and negative framing. We find for the first time that abstract reinforcer decisions activate the same network of brain regions as concrete reinforcer decisions, including the striatum, insula, anterior cingulate, and VMPFC, results that are further supported via comparison to a meta-analysis of decision making studies. Positive and negative framing activated different parts of this network, with stronger activation in VMPFC during negative framing and in DLPFC during positive, suggesting different decision making pathways depending on frame. These results were further clarified using connectivity analysis, which revealed stronger connections between anterior cingulate, insula, and accumbens during negative framing compared to positive. Taken together, these results suggest that not only do abstract reinforcer decisions rely on the same brain substrates as concrete reinforcers, but that the response underlying framing effects on abstract reinforcers also resemble those for concrete reinforcers, specifically increased limbic system connectivity during negative frames. Copyright © 2014 Elsevier Inc. All rights reserved.

Evaluating a Modular Decision Support Application for Colorectal Cancer Screening

PubMed Central

Diiulio, Julie B.; Borders, Morgan R.; Sushereba, Christen E.; Saleem, Jason J.; Haverkamp, Donald; Imperiale, Thomas F.

2017-01-01

Summary Background There is a need for health information technology evaluation that goes beyond randomized controlled trials to include consideration of usability, cognition, feedback from representative users, and impact on efficiency, data quality, and clinical workflow. This article presents an evaluation illustrating one approach to this need using the Decision-Centered Design framework. Objective To evaluate, through a Decision-Centered Design framework, the ability of the Screening and Surveillance App to support primary care clinicians in tracking and managing colorectal cancer testing. Methods We leveraged two evaluation formats, online and in-person, to obtain feedback from a range primary care clinicians and obtain comparative data. Both the online and in-person evaluations used mock patient data to simulate challenging patient scenarios. Primary care clinicians responded to a series of colorectal cancer-related questions about each patient and made recommendations for screening. We collected data on performance, perceived workload, and usability. Key elements of Decision-Centered Design include evaluation in the context of realistic, challenging scenarios and measures designed to explore impact on cognitive performance. Results Comparison of means revealed increases in accuracy, efficiency, and usability and decreases in perceived mental effort and workload when using the Screening and Surveillance App. Conclusion The results speak to the benefits of using the Decision-Centered Design approach in the analysis, design, and evaluation of Health Information Technology. Furthermore, the Screening and Surveillance App shows promise for filling decision support gaps in current electronic health records. PMID:28197619

Toward the Modularization of Decision Support Systems

NASA Astrophysics Data System (ADS)

Raskin, R. G.

2009-12-01

Decision support systems are typically developed entirely from scratch without the use of modular components. This “stovepiped” approach is inefficient and costly because it prevents a developer from leveraging the data, models, tools, and services of other developers. Even when a decision support component is made available, it is difficult to know what problem it solves, how it relates to other components, or even that the component exists, The Spatial Decision Support (SDS) Consortium was formed in 2008 to organize the body of knowledge in SDS within a common portal. The portal identifies the canonical steps in the decision process and enables decision support components to be registered, categorized, and searched. This presentation describes how a decision support system can be assembled from modular models, data, tools and services, based on the needs of the Earth science application.

Development of Decision Support Formulas for the Prediction of Bladder Outlet Obstruction and Prostatic Surgery in Patients With Lower Urinary Tract Symptom/Benign Prostatic Hyperplasia: Part I, Development of the Formula and its Internal Validation.

PubMed

Choo, Min Soo; Yoo, Changwon; Cho, Sung Yong; Jeong, Seong Jin; Jeong, Chang Wook; Ku, Ja Hyeon; Oh, Seung-June

2017-04-01

As the elderly population increases, a growing number of patients have lower urinary tract symptom (LUTS)/benign prostatic hyperplasia (BPH). The aim of this study was to develop decision support formulas and nomograms for the prediction of bladder outlet obstruction (BOO) and for BOO-related surgical decision-making, and to validate them in patients with LUTS/BPH. Patient with LUTS/BPH between October 2004 and May 2014 were enrolled as a development cohort. The available variables included age, International Prostate Symptom Score, free uroflowmetry, postvoid residual volume, total prostate volume, and the results of a pressure-flow study. A causal Bayesian network analysis was used to identify relevant parameters. Using multivariate logistic regression analysis, formulas were developed to calculate the probabilities of having BOO and requiring prostatic surgery. Patients between June 2014 and December 2015 were prospectively enrolled for internal validation. Receiver operating characteristic curve analysis, calibration plots, and decision curve analysis were performed. A total of 1,179 male patients with LUTS/BPH, with a mean age of 66.1 years, were included as a development cohort. Another 253 patients were enrolled as an internal validation cohort. Using multivariate logistic regression analysis, 2 and 4 formulas were established to estimate the probabilities of having BOO and requiring prostatic surgery, respectively. Our analysis of the predictive accuracy of the model revealed area under the curve values of 0.82 for BOO and 0.87 for prostatic surgery. The sensitivity and specificity were 53.6% and 87.0% for BOO, and 91.6% and 50.0% for prostatic surgery, respectively. The calibration plot indicated that these prediction models showed a good correspondence. In addition, the decision curve analysis showed a high net benefit across the entire spectrum of probability thresholds. We established nomograms for the prediction of BOO and BOO-related prostatic surgery in patients with LUTS/BPH. Internal validation of the nomograms demonstrated that they predicted both having BOO and requiring prostatic surgery very well.

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

PubMed

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

2015-11-30

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

Selecting Essential Information for Biosurveillance—A Multi-Criteria Decision Analysis

PubMed Central

Generous, Nicholas; Margevicius, Kristen J.; Taylor-McCabe, Kirsten J.; Brown, Mac; Daniel, W. Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina

2014-01-01

The National Strategy for Biosurveillancedefines biosurveillance as “the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels.” However, the strategy does not specify how “essential information” is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being “essential”. Thequestion of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of “essential information” for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system. PMID:24489748

Prosthodontic decision-making relating to dentitions with compromised molars: the perspective of Swedish General Dental Practitioners.

PubMed

Korduner, E-K; Collin Bagewitz, I; Vult von Steyern, P; Wolf, E

2016-12-01

The aim of this investigation was to study the clinical prosthodontic decision-making process relating to dentitions with compromised molars among Swedish general dental practitioners (GDPs). Eleven Swedish GDPs were purposively selected, and all agreed to participate. Then, in-depth, semi-structured interviews were conducted and covered treatment considerations concerning two authentic patient cases, initially with complete dental arches, and later, a final treatment based on a shortened dental arch (SDA) was discussed. The cases involved patients with compromised teeth situated mainly in the molar regions. One patient suffered from extensive caries and the other from severe periodontal disease. Qualitative content analysis was used to analyse the data. In the systematic analysis, two main categories were identified: holistic and functional approach. Among the interviewed GDPs, focus was put on patients' needs, background history and motivation for treatment as well as the preservation of molar support. Within the limitations of this study, the following can be concluded: keeping a dental arch with molars seems to be important to Swedish general dental practitioners. The SDA concept does not seem to have a substantial impact on the prosthodontic decision-making relating to dentitions with compromised molars. The dentist's experiences, as well as colleagues' or consulting specialist advice together with aetiological factors and the patient's individual situation, influence the decision-making more than the SDA concept. The conflicting results in the prosthetic decision-making process concerning the relevance of age and the need for molar support need further investigation, for example based on decisions made in the dentist's own clinical practice. © 2016 John Wiley & Sons Ltd.

Coaching and guidance with patient decision aids: A review of theoretical and empirical evidence

PubMed Central

2013-01-01

Background Coaching and guidance are structured approaches that can be used within or alongside patient decision aids (PtDAs) to facilitate the process of decision making. Coaching is provided by an individual, and guidance is embedded within the decision support materials. The purpose of this paper is to: a) present updated definitions of the concepts “coaching” and “guidance”; b) present an updated summary of current theoretical and empirical insights into the roles played by coaching/guidance in the context of PtDAs; and c) highlight emerging issues and research opportunities in this aspect of PtDA design. Methods We identified literature published since 2003 on shared decision making theoretical frameworks inclusive of coaching or guidance. We also conducted a sub-analysis of randomized controlled trials included in the 2011 Cochrane Collaboration Review of PtDAs with search results updated to December 2010. The sub-analysis was conducted on the characteristics of coaching and/or guidance included in any trial of PtDAs and trials that allowed the impact of coaching and/or guidance with PtDA to be compared to another intervention or usual care. Results Theoretical evidence continues to justify the use of coaching and/or guidance to better support patients in the process of thinking about a decision and in communicating their values/preferences with others. In 98 randomized controlled trials of PtDAs, 11 trials (11.2%) included coaching and 63 trials (64.3%) provided guidance. Compared to usual care, coaching provided alongside a PtDA improved knowledge and decreased mean costs. The impact on some other outcomes (e.g., participation in decision making, satisfaction, option chosen) was more variable, with some trials showing positive effects and other trials reporting no differences. For values-choice agreement, decisional conflict, adherence, and anxiety there were no differences between groups. None of these outcomes were worse when patients were exposed to decision coaching alongside a PtDA. No trials evaluated the effect of guidance provided within PtDAs. Conclusions Theoretical evidence continues to justify the use of coaching and/or guidance to better support patients to participate in decision making. However, there are few randomized controlled trials that have compared the effectiveness of coaching used alongside PtDAs to PtDAs without coaching, and no trials have compared the PtDAs with guidance to those without guidance. PMID:24624995

An integrated strategy of knowledge application for optimal e-health implementation: A multi-method study protocol

PubMed Central

Gagnon, Marie-Pierre; Légaré, France; Fortin, Jean-Paul; Lamothe, Lise; Labrecque, Michel; Duplantie, Julie

2008-01-01

Background E-health is increasingly valued for supporting: 1) access to quality health care services for all citizens; 2) information flow and exchange; 3) integrated health care services and 4) interprofessional collaboration. Nevertheless, several questions remain on the factors allowing an optimal integration of e-health in health care policies, organisations and practices. An evidence-based integrated strategy would maximise the efficacy and efficiency of e-health implementation. However, decisions regarding e-health applications are usually not evidence-based, which can lead to a sub-optimal use of these technologies. This study aims at understanding factors influencing the application of scientific knowledge for an optimal implementation of e-health in the health care system. Methods A three-year multi-method study is being conducted in the Province of Quebec (Canada). Decision-making at each decisional level (political, organisational and clinical) are analysed based on specific approaches. At the political level, critical incidents analysis is being used. This method will identify how decisions regarding the implementation of e-health could be influenced or not by scientific knowledge. Then, interviews with key-decision-makers will look at how knowledge was actually used to support their decisions, and what factors influenced its use. At the organisational level, e-health projects are being analysed as case studies in order to explore the use of scientific knowledge to support decision-making during the implementation of the technology. Interviews with promoters, managers and clinicians will be carried out in order to identify factors influencing the production and application of scientific knowledge. At the clinical level, questionnaires are being distributed to clinicians involved in e-health projects in order to analyse factors influencing knowledge application in their decision-making. Finally, a triangulation of the results will be done using mixed methodologies to allow a transversal analysis of the results at each of the decisional levels. Results This study will identify factors influencing the use of scientific evidence and other types of knowledge by decision-makers involved in planning, financing, implementing and evaluating e-health projects. Conclusion These results will be highly relevant to inform decision-makers who wish to optimise the implementation of e-health in the Quebec health care system. This study is extremely relevant given the context of major transformations in the health care system where e-health becomes a must. PMID:18435853

Using an ecosystem service decision support tool to support ridge to reef management: An example of sediment reduction in west Maui, Hawaii

NASA Astrophysics Data System (ADS)

Falinski, K. A.; Oleson, K.; Htun, H.; Kappel, C.; Lecky, J.; Rowe, C.; Selkoe, K.; White, C.

2016-12-01

Faced with anthropogenic stressors and declining coral reef states, managers concerned with restoration and resilience of coral reefs are increasingly recognizing the need to take a ridge-to-reef, ecosystem-based approach. An ecosystem services framing can help managers move towards these goals, helping to illustrate trade-offs and opportunities of management actions in terms of their impacts on society. We describe a research program building a spatial ecosystem services-based decision-support tool, and being applied to guide ridge-to-reef management in a NOAA priority site in West Maui. We use multiple modeling methods to link biophysical processes to ecosystem services and their spatial flows and social values in an integrating platform. Modeled services include water availability, sediment retention, nutrient retention and carbon sequestration on land. A coral reef ecosystem service model is under development to capture the linkages between terrestrial and coastal ecosystem services. Valuation studies are underway to quantify the implications for human well-being. The tool integrates techniques from decision science to facilitate decision making. We use the sediment retention model to illustrate the types of analyses the tool can support. The case study explores the tradeoffs between road rehabilitation costs and sediment export avoided. We couple the sediment and cost models with trade-off analysis to identify optimal distributed solutions that are most cost-effective in reducing erosion, and then use those models to estimate sediment exposure to coral reefs. We find that cooperation between land owners reveals opportunities for maximizing the benefits of fixing roads and minimizes costs. This research forms the building blocks of an ecosystem service decision support tool that we intend to continue to test and apply in other Pacific Island settings.

Systematic Review of Medical Informatics-Supported Medication Decision Making.

PubMed

Melton, Brittany L

2017-01-01

This systematic review sought to assess the applications and implications of current medical informatics-based decision support systems related to medication prescribing and use. Studies published between January 2006 and July 2016 which were indexed in PubMed and written in English were reviewed, and 39 studies were ultimately included. Most of the studies looked at computerized provider order entry or clinical decision support systems. Most studies examined decision support systems as a means of reducing errors or risk, particularly associated with medication prescribing, whereas a few studies evaluated the impact medical informatics-based decision support systems have on workflow or operations efficiency. Most studies identified benefits associated with decision support systems, but some indicate there is room for improvement.

Collaborative modelling and integrated decision support system analysis of a developed terminal lake basin

USGS Publications Warehouse

Niswonger, Richard G.; Allander, Kip K.; Jeton, Anne E.

2014-01-01

A terminal lake basin in west-central Nevada, Walker Lake, has undergone drastic change over the past 90 yrs due to upstream water use for agriculture. Decreased inflows to the lake have resulted in 100 km2 decrease in lake surface area and a total loss of fisheries due to salinization. The ecologic health of Walker Lake is of great concern as the lake is a stopover point on the Pacific route for migratory birds from within and outside the United States. Stakeholders, water institutions, and scientists have engaged in collaborative modeling and the development of a decision support system that is being used to develop and analyze management change options to restore the lake. Here we use an integrated management and hydrologic model that relies on state-of-the-art simulation capabilities to evaluate the benefits of using integrated hydrologic models as components of a decision support system. Nonlinear feedbacks among climate, surface-water and groundwater exchanges, and water use present challenges for simulating realistic outcomes associated with management change. Integrated management and hydrologic modeling provides a means of simulating benefits associated with management change in the Walker River basin where drastic changes in the hydrologic landscape have taken place over the last century. Through the collaborative modeling process, stakeholder support is increasing and possibly leading to management change options that result in reductions in Walker Lake salt concentrations, as simulated by the decision support system.

Reward-related decision making in eating and weight disorders: A systematic review and meta-analysis of the evidence from neuropsychological studies.

PubMed

Wu, Mudan; Brockmeyer, Timo; Hartmann, Mechthild; Skunde, Mandy; Herzog, Wolfgang; Friederich, Hans-Christoph

2016-02-01

Eating disorders (EDs) and overweight/obesity (OW/OB) are serious public health concerns that share common neuropsychological features and patterns of disturbed eating. Reward-related decision making as a basic neurocognitive function may trans-diagnostically underlie both pathological overeating and restricted eating. The present meta-analysis synthesizes the evidence from N=82 neuropsychological studies for altered reward-related decision making in all ED subtypes, OW and OB. The overall effect sizes for the differences between currently-ill ED patients and OW/OB people and controls were Hedge's g=-0.49 [CI: -0.63; -0.35], and Hedge's g=-0.39 [CI: -0.53; -0.25], respectively. Decision making was found to be altered to similar degrees in all ED subtypes and OB. Effect sizes, however, diverged for the different measures of decision making. Adolescents appear to be less affected than adults. When foods were used as rewarding stimuli, decision making was found to be intact in OB. The findings support that altered general reward-related decision making is a salient neuropsychological factor across eating and weight disorders in adulthood. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-criteria decision analysis in environmental sciences: ten years of applications and trends.

PubMed

Huang, Ivy B; Keisler, Jeffrey; Linkov, Igor

2011-09-01

Decision-making in environmental projects requires consideration of trade-offs between socio-political, environmental, and economic impacts and is often complicated by various stakeholder views. Multi-criteria decision analysis (MCDA) emerged as a formal methodology to face available technical information and stakeholder values to support decisions in many fields and can be especially valuable in environmental decision making. This study reviews environmental applications of MCDA. Over 300 papers published between 2000 and 2009 reporting MCDA applications in the environmental field were identified through a series of queries in the Web of Science database. The papers were classified by their environmental application area, decision or intervention type. In addition, the papers were also classified by the MCDA methods used in the analysis (analytic hierarchy process, multi-attribute utility theory, and outranking). The results suggest that there is a significant growth in environmental applications of MCDA over the last decade across all environmental application areas. Multiple MCDA tools have been successfully used for environmental applications. Even though the use of the specific methods and tools varies in different application areas and geographic regions, our review of a few papers where several methods were used in parallel with the same problem indicates that recommended course of action does not vary significantly with the method applied. Published by Elsevier B.V.