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Minimal Modeling Approaches to Value of Information Analysis for Health Research

Author

Listed:
  • David O. Meltzer
  • Ties Hoomans
  • Jeanette W. Chung
  • Anirban Basu

Abstract

Value of information (VOI) techniques can provide estimates of the expected benefits from clinical research studies that 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, but the complexity of constructing such models can pose barriers to some practical applications 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 article 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 2 new clinical applications to which the approach appears well suited because clinical trials with comprehensive outcomes provide preliminary estimates of the uncertainty in outcomes. The authors conclude that minimal modeling approaches to VOI can be readily applied in some instances to estimate the expected benefits of clinical research.

Suggested Citation

  • David O. Meltzer & Ties Hoomans & Jeanette W. Chung & Anirban Basu, 2011. "Minimal Modeling Approaches to Value of Information Analysis for Health Research," Medical Decision Making, , vol. 31(6), pages 1-22, November.
    • Handle: RePEc:sae:medema:v:31:y:2011:i:6:p:e1-e22
    DOI: 10.1177/0272989X11412975
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    References listed on IDEAS

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    1. Simon Eckermann & Andrew R. Willan, 2009. "Globally optimal trial design for local decision making," Health Economics, John Wiley & Sons, Ltd., vol. 18(2), pages 203-216, February.
    2. Simon Eckermann & Andrew R. Willan, 2007. "Expected value of information and decision making in HTA," Health Economics, John Wiley & Sons, Ltd., vol. 16(2), pages 195-209, February.
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    Citations

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    Cited by:

    1. David Glynn & Vijay S. Gc & Karl Claxton & Chris Littlewood & Claire Rothery, 2024. "Rapid Assessment of the Need for Evidence: Applying the Principles of Value of Information to Research Prioritisation," PharmacoEconomics, Springer, vol. 42(9), pages 919-928, September.
    2. Blythe Adamson & Dobromir Dimitrov & Beth Devine & Ruanne Barnabas, 2017. "The Potential Cost-Effectiveness of HIV Vaccines: A Systematic Review," PharmacoEconomics - Open, Springer, vol. 1(1), pages 1-12, March.
    3. Anirban Basu & David Meltzer, 2012. "Private Manufacturers’ Thresholds to Invest in Comparative Effectiveness Trials," PharmacoEconomics, Springer, vol. 30(10), pages 859-868, October.
    4. Meltzer David O., 2013. "Opportunities in the Economics of Personalized Health Care and Prevention," Forum for Health Economics & Policy, De Gruyter, vol. 16(2), pages 13-22, June.
    5. Haitham Tuffaha & Claire Rothery & Natalia Kunst & Chris Jackson & Mark Strong & Stephen Birch, 2021. "A Review of Web-Based Tools for Value-of-Information Analysis," Applied Health Economics and Health Policy, Springer, vol. 19(5), pages 645-651, September.
    6. Caroline S. Bennette & David L. Veenstra & Anirban Basu & Laurence H. Baker & Scott D. Ramsey & Josh J. Carlson, 2016. "Development and Evaluation of an Approach to Using Value of Information Analyses for Real-Time Prioritization Decisions Within SWOG, a Large Cancer Clinical Trials Cooperative Group," Medical Decision Making, , vol. 36(5), pages 641-651, July.
    7. Haitham Tuffaha, 2021. "Value of Information Analysis: Are We There Yet?," PharmacoEconomics - Open, Springer, vol. 5(2), pages 139-141, June.

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