A Graphical, Computer-Based Decision-Support Tool to Help Decision Makers Evaluate Policy Options Relating to Physical Activity

2010 ◽  
Vol 39 (3) ◽  
pp. 273-279 ◽  
Author(s):  
Antronette K. Yancey ◽  
Brian L. Cole ◽  
William J. McCarthy
Keyword(s):  
Physical Activity ◽  
Decision Support ◽  
Decision Support Tool ◽  
Decision Makers ◽  
Policy Options ◽  
Support Tool ◽  
Computer Based

scholarly journals A web-based decision support tool for groundwater remediation technologies selection

2006 ◽  
Vol 8 (2) ◽  
pp. 91-100 ◽  
Author(s):  
Olfa Khelifi ◽  
Andrea Lodolo ◽  
Sanja Vranes ◽  
Gabriele Centi ◽  
Stanislav Miertus
Keyword(s):  
Decision Support ◽  
Groundwater Remediation ◽  
Local Community ◽  
Decision Support Tool ◽  
Decision Makers ◽  
Relative Importance ◽  
Problem Complexity ◽  
Web Based ◽  
Support Tool ◽  
Promethee Ii

Groundwater remediation operation involves several considerations in terms of environmental, technological and socio-economic aspects. A decision support tool (DST) becomes therefore necessary in order to manage problem complexity and to define effective groundwater remediation interventions. CCR (Credence Clearwater Revival), a decision support tool for groundwater remediation technologies assessment and selection, has been developed to help decision-makers (site owners, investors, local community representatives, environmentalists, regulators, etc.) to assess the available technologies and select the preferred remedial options. The analysis is based on technical, economical, environmental and social criteria. These criteria are ranked by all involved parties to determine their relative importance for a particular groundwater remediation project. The Multi-Criteria Decision Making (MCDM) is the core of the CCR using the PROMETHEE II algorithm.

scholarly journals DEVELOPMENT AND TEST OF A DECISION SUPPORT TOOL FOR HOSPITAL HEALTH TECHNOLOGY ASSESSMENT

2012 ◽  
Vol 28 (4) ◽  
pp. 460-465 ◽  
Author(s):  
Laura Sampietro-Colom ◽  
Irene Morilla-Bachs ◽  
Santiago Gutierrez-Moreno ◽  
Pedro Gallo
Keyword(s):  
Decision Support ◽  
Platelet Rich Plasma ◽  
Decision Support Tool ◽  
Two Dimensions ◽  
Decision Makers ◽  
Process Of Care ◽  
Support Tool ◽  
Health Technologies ◽  
A Value ◽  
Benefit Patient

Objective: To develop and test a decision-support tool for prioritizing new competing Health Technologies (HTs) after their assessment using the mini-HTA approach.Methods:A two layer value/risk tool was developed based on the mini-HTA. The first layer included 12 mini-HTA variables classified in two dimensions, namely value (safety, clinical benefit, patient impact, cost-effectiveness, quality of the evidence, innovativeness) and risk (staff, space and process of care impacts, incremental costs, net cost, investment effort). Weights given to these variables were obtained from a survey among decision-makers (at National/Regional level and hospital settings). A second layer included results from mini-HTA (scored as higher, equal or lower), which compares the performance of the new HT (in terms of the abovementioned 12 variables) with the available comparator. An algorithm combining the first (weights) and second (scores) layers was developed to obtain an overall score for each HT, which was then plotted in a value/risk matrix. The tool was tested using results from the mini-HTAs for three new HTs (Surgical Robot, Platelet Rich Plasma, Deep Brain Stimulation).Results: No significant differences among decision-makers were observed as regards the weights given to the 12 variables, therefore, the median aggregate weights from decision-makers were introduced in the first layer. The dot plot resulting from the mini-HTA presented good power to visually discriminate between the assessed HTs.Conclusion: The decision-support tool developed here makes possible a robust and straightforward comparison of different competing HTs. This facilitates hospital decision-makers deliberations on the prioritization of competing investments under fixed budgets.

scholarly journals A Pareto Based Multi-Objective Evolutionary Algorithm Approach to Military Installation Rail Infrastructure Investment

2019 ◽  
Vol 7 (2) ◽  
pp. 64-75
Author(s):  
Eugene Lesinski ◽  
Steven Corns
Keyword(s):  
Decision Support ◽  
Evolutionary Algorithm ◽  
Lower Cost ◽  
Decision Support Tool ◽  
Decision Makers ◽  
Support Tool ◽  
Track Maintenance ◽  
Multi Objective ◽  
Military Installation ◽  
Prioritization Scheme

Decision making for military railyard infrastructure is an inherently multi-objective problem, balancing cost versus capability. In this research, a Pareto-based Multi-Objective Evolutionary Algorithm is compared to a military rail inventory and decision support tool (RAILER). The problem is formulated as a multi-objective evolutionary algorithm in which the overall railyard condition is increased while decreasing cost to repair and maintain. A prioritization scheme for track maintenance is introduced that takes into account the volume of materials transported over the track and each rail segment’s primary purpose. Available repair options include repairing current 90 gauge rail, upgrade of rail segments to 115 gauge rail, and the swapping of rail removed during the upgrade. The proposed Multi-Objective Evolutionary Algorithm approach provides several advantages to the RAILER approach. The MOEA methodology allows decision makers to incorporate additional repair options beyond the current repair or do nothing options. It was found that many of the solutions identified by the evolutionary algorithm were both lower cost and provide a higher overall condition that those generated by DoD’s rail inventory and decision support system, RAILER. Additionally, the MOEA methodology generates lower cost, higher capability solutions when reduced sets of repair options are considered. The collection of non-dominated solutions provided by this technique gives decision makers increased flexibility and the ability to evaluate whether an additional cost repair solution is worth the increase in facility rail condition.

scholarly journals Impact of a Computer-Based Diagnostic Decision Support Tool on the Differential Diagnoses of Medicine Residents

2012 ◽  
Vol 4 (2) ◽  
pp. 227-231 ◽  
Author(s):  
Mitchell J. Feldman ◽  
Edward P. Hoffer ◽  
G. Octo Barnett ◽  
Richard J. Kim ◽  
Kathleen T. Famiglietti ◽  
...  
Keyword(s):  
Differential Diagnosis ◽  
Decision Support ◽  
Decision Support Tool ◽  
Differential Diagnoses ◽  
First Year ◽  
Support Tool ◽  
Diagnostic Decision ◽  
Management Plans ◽  
Medical Diagnostic ◽  
Computer Based

Abstract Background Computer-based medical diagnostic decision support systems have been used for decades, initially as stand-alone applications. More recent versions have been tested for their effectiveness in enhancing the diagnostic ability of clinicians. Objective To determine if viewing a rank-ordered list of diagnostic possibilities from a medical diagnostic decision support system improves residents' differential diagnoses or management plans. Method Twenty first-year internal medicine residents at Massachusetts General Hospital viewed 3 deidentified case descriptions of real patients. All residents completed a web-based questionnaire, entering the differential diagnosis and management plan before and after seeing the diagnostic decision support system's suggested list of diseases. In all 3 exercises, the actual case diagnosis was first on the system's list. Each resident served as his or her own control (pretest/posttest). Results For all 3 cases, a substantial percentage of residents changed their primary considered diagnosis after reviewing the system's suggested diagnoses, and a number of residents who had not initially listed a “further action” (laboratory test, imaging study, or referral) added or changed their management options after using the system. Many residents (20% to 65% depending on the case) improved their differential diagnosis from before to after viewing the system's suggestions. The average time to complete all 3 cases was 15.4 minutes. Most residents thought that viewing the medical diagnostic decision support system's list of suggestions was helpful. Conclusion Viewing a rank-ordered list of diagnostic possibilities from a diagnostic decision support tool had a significant beneficial effect on the quality of first-year medicine residents' differential diagnoses and management plans.

scholarly journals Developing a decision support tool for assessing land use change and BMPs in ungauged watersheds based on decision rules provided by SWAT simulation

2018 ◽  
Vol 22 (7) ◽  
pp. 3789-3806 ◽  
Author(s):  
Junyu Qi ◽  
Sheng Li ◽  
Charles P.-A. Bourque ◽  
Zisheng Xing ◽  
Fan-Rui Meng
Keyword(s):  
Land Use ◽  
Decision Support ◽  
Land Use Change ◽  
Best Management Practices ◽  
Management Practices ◽  
Hydrological Modeling ◽  
Decision Support Tool ◽  
Decision Makers ◽  
Support Tool ◽  
Ungauged Watersheds

Abstract. Decision making on water resources management at ungauged, especially large-scale watersheds relies on hydrological modeling. Physically based distributed hydrological models require complicated setup, calibration, and validation processes, which may delay their acceptance among decision makers. This study presents an approach to develop a simple decision support tool (DST) for decision makers and economists to evaluate multiyear impacts of land use change and best management practices (BMPs) on water quantity and quality for ungauged watersheds. The example DST developed in the present study was based on statistical equations derived from Soil and Water Assessment Tool (SWAT) simulations and applied to a small experimental watershed in northwest New Brunswick. The DST was subsequently tested against field measurements and SWAT simulations for a larger watershed. Results from DST could reproduce both field data and model simulations of annual stream discharge and sediment and nutrient loadings. The relative error of mean annual discharge and sediment, nitrate–nitrogen, and soluble-phosphorus loadings were −6, −52, 27, and −16 %, respectively, for long-term simulation. Compared with SWAT, DST has fewer input requirements and can be applied to multiple watersheds without additional calibration. Also, scenario analyses with DST can be directly conducted for different combinations of land use and BMPs without complex model setup procedures. The approach in developing DST can be applied to other regions of the world because of its flexible structure.

Leveraging previously reported research to create a decision support tool for institutional facility maintenance

2019 ◽  
Vol 17 (3) ◽  
pp. 249-266
Author(s):  
Michael A. Beauregard ◽  
Steven K. Ayer
Keyword(s):  
Decision Support ◽  
Literature Review ◽  
Decision Support Tool ◽  
Facility Management ◽  
Decision Makers ◽  
Content Type ◽  
Support Tool ◽  
Facility Maintenance ◽  
K 12 ◽  
Work Orders

Purpose The discretionary expense budget required to maintain public infrastructure has declined in recent years, even as public expectations and accountability for performance have increased. The purpose of this paper is to leverage previously reported research to create a decision support tool (DST) for prioritizing institutional facility maintenance. Design/methodology/approach A structured literature review was developed to identify critical aspects of facility maintenance shown to have a positive relationship with academic performance in K-12 schools within the USA. Analytical hierarchy process (AHP) serves as a framework for a multi-criteria DST based on the findings of the literature review. Finally, a targeted focus group of industry professionals was used to validate the usability of the resulting DST. Findings The framework for the DST developed for this study effectively represents the scale and scope of an institutional facility. Results of the study suggest that when evaluating multi-criteria work orders, the proposed visual AHP methodology can be used to generate usable DSTs to assist with the prioritization of work. Practical implications This study provides a methodology for building a multi-criterion DST leveraging precedent research, using a visual AHP to assist facility management (FM) decision-makers in the prioritization of routine work orders. Originality/value The developed process indicates a practical approach to incorporating disparate research findings into a concise and useable manner to guide FM decision-makers, who have traditionally not been able to explicitly leverage this information to make evidence-based spending decisions.

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