Bayesian estimation of cost-effectiveness ratios from clinical trials
Estimation of the incremental cost-effectiveness ratio (ICER) is difficult for several reasons: treatments that decrease both cost and effectiveness and treatments that increase both cost and effectiveness can yield identical values of the ICER; the ICER is a discontinuous function of the mean difference in effectiveness; and the standard estimate of the ICER is a ratio. To address these difficulties, we have developed a Bayesian methodology that involves computing posterior probabilities for the four quadrants and separate interval estimates of ICER for the quadrants of interest. We compute these quantities by simulating draws from the posterior distribution of the cost and effectiveness parameters and tabulating the appropriate posterior probabilities and quantiles. We demonstrate the method by re-analysing three previously published clinical trials. Copyright © 1999 John Wiley & Sons, Ltd.
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Volume (Year): 8 (1999)
Issue (Month): 3 ()
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- 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.
- Daniel F. Heitjan, 2000. "Fieller's method and net health benefits," Health Economics, John Wiley & Sons, Ltd., vol. 9(4), pages 327-335.
- 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.
- 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.
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