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Bayesian estimation of cost‐effectiveness: an importance‐sampling approach

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  • Daniel F. Heitjan
  • Huiling Li

Abstract

We describe a method for estimating the cost‐effectiveness of a new treatment compared to a standard, using data from a comparative clinical trial. We quantify the clinical effectiveness as a binary variable indicating success or failure. The underlying statistical model assumes that costs are uncensored and follow separate gamma distributions in each of the groups defined by the four possible combinations of treatment arm and effectiveness outcome. The method is subjectivist, in that it represents prior uncertainty about model parameters with a probability distribution, which we update via Bayes's theorem to produce a posterior distribution. We approximate the posterior by importance sampling, a straightforward simulation method. We illustrate the method with an analysis of cost (derived from resource usage data) and effectiveness (measured by one‐year survival) in a clinical trial in heart disease. The example demonstrates that the method is practical and provides for a flexible data analysis. Copyright © 2003 John Wiley & Sons, Ltd.

Suggested Citation

  • Daniel F. Heitjan & Huiling Li, 2004. "Bayesian estimation of cost‐effectiveness: an importance‐sampling approach," Health Economics, John Wiley & Sons, Ltd., vol. 13(2), pages 191-198, February.
  • Handle: RePEc:wly:hlthec:v:13:y:2004:i:2:p:191-198
    DOI: 10.1002/hec.825
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    File URL: https://doi.org/10.1002/hec.825
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    References listed on IDEAS

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    1. Eugene M. Laska & Morris Meisner & Carole Siegel & Joseph Wanderling, 2002. "Statistical determination of cost‐effectiveness frontier based on net health benefits," Health Economics, John Wiley & Sons, Ltd., vol. 11(3), pages 249-264, April.
    2. Daniel Polsky & Henry A. Glick & Richard Willke & Kevin Schulman, 1997. "Confidence Intervals for Cost–Effectiveness Ratios: A Comparison of Four Methods," Health Economics, John Wiley & Sons, Ltd., vol. 6(3), pages 243-252, May.
    3. Maiwenn J. Al & Ben A. Van Hout, 2000. "A Bayesian approach to economic analyses of clinical trials: the case of stenting versus balloon angioplasty," Health Economics, John Wiley & Sons, Ltd., vol. 9(7), pages 599-609, October.
    4. Daniel F. Heitjan, 2000. "Fieller's method and net health benefits," Health Economics, John Wiley & Sons, Ltd., vol. 9(4), pages 327-335, June.
    5. Andrew Briggs & Paul Fenn, 1998. "Confidence intervals or surfaces? Uncertainty on the cost-effectiveness plane," Health Economics, John Wiley & Sons, Ltd., vol. 7(8), pages 723-740.
    6. Andrew H. Briggs & David E. Wonderling & Christopher Z. Mooney, 1997. "Pulling cost‐effectiveness analysis up by its bootstraps: A non‐parametric approach to confidence interval estimation," Health Economics, John Wiley & Sons, Ltd., vol. 6(4), pages 327-340, July.
    7. Eugene M. Laska & Morris Meisner & Carole Siegel, 1997. "Statistical Inference for Cost–Effectiveness Ratios," Health Economics, John Wiley & Sons, Ltd., vol. 6(3), pages 229-242, May.
    8. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits: A New Framework for the Analysis of Uncertainty in Cost-Effectiveness Analysis," NBER Technical Working Papers 0227, National Bureau of Economic Research, Inc.
    9. Daniel F. Heitjan & Alan J. Moskowitz & William Whang, 1999. "Bayesian estimation of cost‐effectiveness ratios from clinical trials," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 191-201, May.
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    Cited by:

    1. Moreno, Elías & Girón, F.J. & Vázquez-Polo, F.J. & NegrI´n, M.A., 2010. "Optimal healthcare decisions: Comparing medical treatments on a cost-effectiveness basis," European Journal of Operational Research, Elsevier, vol. 204(1), pages 180-187, July.
    2. Xin Sun & Thomas Faunce, 2008. "Decision-analytical modelling in health-care economic evaluations," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 9(4), pages 313-323, November.

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