The Resource Evaluating the potential use of modeling and value-of-Information analysis for future research prioritization within the evidence-based practice center program, prepared for Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services ; prepared by Duke Evidence-based Practice Center ; investigators, Evan Myers ... [et al.], (electronic resource)

Evaluating the potential use of modeling and value-of-Information analysis for future research prioritization within the evidence-based practice center program, prepared for Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services ; prepared by Duke Evidence-based Practice Center ; investigators, Evan Myers ... [et al.], (electronic resource)

Label
Evaluating the potential use of modeling and value-of-Information analysis for future research prioritization within the evidence-based practice center program
Title
Evaluating the potential use of modeling and value-of-Information analysis for future research prioritization within the evidence-based practice center program
Statement of responsibility
prepared for Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services ; prepared by Duke Evidence-based Practice Center ; investigators, Evan Myers ... [et al.]
Contributor
Subject
Language
eng
Summary
BACKGROUND: Systematic reviews conducted as part of the Evidence-based Practice Center (EPC) program routinely identify evidence gaps and suggest further research to help close these gaps, but there is little evidence that these suggestions lead to the performance of the needed research. As part of an EPC-wide program to evaluate potential mechanisms for ensuring that research needs identified by systematic reviews are addressed, the Duke EPC reviewed the use of modeling techniques, including value-of-information (VOI) analysis, for prioritizing research gaps, under the assumption that quantitative prioritization could help facilitate the performance of research to address those gaps. METHODS: We first searched PubMed(r) for relevant literature published in English between 1990 and 2010 using search terms related to research prioritization and VOI analysis to understand how modeling and VOI is currently used in research prioritization. Inclusion/exclusion screening criteria were aimed at identifying articles that focused on research prioritization using a formal framework or process and reported specific prioritization recommendations, with a special emphasis on modeling and VOI. To supplement this search, we then conducted a nonsystematic review of research prioritization processes used by major research-sponsoring organizations in the United States and abroad. We searched organization Web sites and the results of our literature search, and contacted the organizations by e-mail and/or telephone. Materials were reviewed for information on the focus of the prioritization process and the methods and criteria used for prioritization, again with a special emphasis on modeling/VOI. Finally, we performed two case studies of the potential use of modeling techniques in research prioritization. First, we developed a model for the use of angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin II receptor antagonists (ARBs) in the management of ischemic heart disease based on the results of a prior comparative effectiveness review, then engaged nine stakeholders in a prioritization process that involved both a consensus-based approach and the use of model results. Second, we adapted a model on the outcomes of treatment of uterine fibroids developed for a previous systematic review and conducted a VOI analysis; these results were then shared with nine participants in a separate consensus-based research prioritization process. In both case studies, we elicited stakeholder feedback on the potential use of modeling and VOI in research prioritization. RESULTS: Only 6 of the 214 papers identified during the literature search reported using a previously published systematic review as the basis for identifying research gaps. Of the 60 unique modeling-based papers, all but 8 used cost-effectiveness analysis and VOI, with most of these focused on the question of immediate adaptation versus future research for a specific health intervention. The United Kingdom (UK) Health Technology Assessment (HTA) program conducted 19 of the 52 VOI analyses. Of the 31 research organizations providing information on prioritization processes, only the UK National Institute for Clinical Excellence (NICE), through the HTA program, explicitly included modeling and VOI in their recommendations for future research. Although the results of the modeling exercises for both case studies provided insight into the underlying decision problems, both models require further development. Despite this, stakeholders from both case study groups reported that the results of the modeling exercises were helpful in thinking about research prioritization, although none thought that modeling alone could substitute for a consensus-based approach. There was some diversity of opinion about the optimal timing of the modeling, with some stakeholders indicating that the results would be more helpful as background to a consensus-based process, while others preferred a parallel, iterative process involving both modeling and consensus. CONCLUSIONS: Outside of the UK NICE/HTA program, systematic reviews were rarely cited as important sources for identifying evidence gaps for research prioritization. Cost-effectiveness and VOI analyses were the most commonly used modeling-based methods, but, outside of the UK, it is unclear to what degree the priorities identified by these methods were translated into actual research funding. Stakeholders in our two case studies found modeling and VOI to be potentially useful tools, but there are a variety of methodological and operational issues that need to be considered and resolved if these methods are to be used to assist with prioritizing research gaps identified through systematic reviews. These include identifying ways to compare the impact of different prioritization methods on the likelihood that priority questions will be answered through research, identifying the appropriate resources (including technical expertise) to conduct the analyses, defining the appropriate timing of the modeling and analyses, and identifying the appropriate level of modeling complexity
Member of
Cataloging source
DNLM
Funding information
Contract No. 290-2007-10066-I
NLM call number
W 84.3
http://library.link/vocab/relatedWorkOrContributorName
  • Myers, Evan R
  • United States
  • Duke University Evidence-based Practice Center
Series statement
  • Methods future research needs reports
  • AHRQ publication
Series volume
  • no. 5
  • no. 11-EHC030-EF
http://library.link/vocab/subjectName
  • Health Services Research
  • Technology Assessment, Biomedical
  • Research Design
  • Evidence-Based Medicine
  • Models, Theoretical
  • Cost-Benefit Analysis
Label
Evaluating the potential use of modeling and value-of-Information analysis for future research prioritization within the evidence-based practice center program, prepared for Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services ; prepared by Duke Evidence-based Practice Center ; investigators, Evan Myers ... [et al.], (electronic resource)
Instantiates
Publication
Note
"June 2011."
Bibliography note
Includes bibliographical references
Control code
OCM1bookssj0000991246
Dimensions
unknown
Specific material designation
remote
System control number
(WaSeSS)bookssj0000991246
Label
Evaluating the potential use of modeling and value-of-Information analysis for future research prioritization within the evidence-based practice center program, prepared for Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services ; prepared by Duke Evidence-based Practice Center ; investigators, Evan Myers ... [et al.], (electronic resource)
Publication
Note
"June 2011."
Bibliography note
Includes bibliographical references
Control code
OCM1bookssj0000991246
Dimensions
unknown
Specific material designation
remote
System control number
(WaSeSS)bookssj0000991246

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