Structured Abstract

Value of information (VOI) techniques can provide estimates of the expected benefits from clinical research studies. These VOI estimates can inform decisions about the design and priority of those studies. Most VOI studies use decision analytic models to characterize the uncertainty of the effects of interventions on health outcomes. For some potential applications of VOI, the complexity of constructing such models poses barriers to practical application of VOI. However, because some clinical studies can directly characterize uncertainty in health outcomes, it may sometimes be possible to perform VOI analysis with only minimal modeling. This paper (1) develops a framework to define and classify minimal modeling approaches to VOI; (2) reviews existing VOI studies that apply minimal modeling approaches; and (3) illustrates and discusses the application of the minimal modeling to two new clinical applications to which the approach appears well suited because clinical trials with comprehensive outcomes provide preliminary estimates of the uncertainty in outcomes. We conclude that minimal modeling approaches to VOI can be readily applied to in some instances to develop estimates of the expected benefits of clinical research.

Contents

• Preface
• Acknowledgments
• Peer Reviewers
• Introduction
• Theoretical Framework
  • Minimal Modeling Approaches
• Literature Review
  • Search Strategy and Inclusion Criteria
  • Study Classification and Data Extraction
  • Results
  • Comparison of VOI Calculations Using Minimal Modeling
• Applications
  • Application 1: No survival modeling with no survival effects—the case of azithromycin versus amoxicillin and clavulanate in acute bacterial sinusitis
  • Application 2: No survival modeling with survival effects from a randomized, controlled trial—the case of erlotinib and gemcitabine versus gemcitabine in pancreatic cancer
• Conclusions
• References
• Appendixes
  • Appendix A. Details of Application 1 and Application 2
  • Appendix B. Curves for Symptom Resolution
  • Appendix C. Survival Curves

Suggested citation:

Meltzer, DO, Hoomans, T, Chung JW, Basu A. Minimal Modeling Approaches to Value of Information Analysis for Health Research. Methods Future Research Needs Report No. 6 (Prepared by the University of Chicago Medical Center and the Blue Cross and Blue Shield Association Technology Evaluation Center Evidence-Based Practice Center under Contract No. 29007-10058.) AHRQ Publication No. 11-EHC062-EF. Rockville, MD: Agency for Healthcare Research and Quality. June 2011. Available at: www.effectivehealthcare.ahrq.gov/reports/final.cfm.

This report is based on research conducted by the University of Chicago Medical Center through the Blue Cross and Blue Shield Association Technology Evaluation Center Evidence-based Practice Center (EPC) under contract to the Agency for Healthcare Research and Quality (AHRQ), Rockville, MD (Contract No. 290-2007-10058). The findings and conclusions in this document are those of the author(s), who are responsible for its contents; the findings and conclusions do not necessarily represent the views of AHRQ. Therefore, no statement in this report should be construed as an official position of AHRQ or of the U.S. Department of Health and Human Services.

The information in this report is intended to help health care researcher and funders of research make well-informed decisions in designing and funding research and thereby improve the quality of health care services. This report is not intended to be a substitute for the application of scientific judgment. Anyone who makes decisions concerning the provision of clinical care should consider this report in the same way as any medical research and in conjunction with all other pertinent information, i.e., in the context of available resources and circumstances.

This report may be used, in whole or in part, as the basis for research design or funding opportunity announcements. AHRQ or U.S. Department of Health and Human Services endorsement of such derivative products or actions may not be stated or implied.

None of the investigators have any affiliations or financial involvement that conflicts with the material presented in this report.

1

540 Gaither Road, Rockville, MD 20850; www​.ahrq.gov