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Fieller's method and net health benefits

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  • Daniel F. Heitjan

Abstract

Statistical and conceptual difficulties complicate the estimation of the incremental cost‐effectiveness ratio (ICER). An alternative approach is to measure cost‐effectiveness by the incremental net health benefit (INHB), defined as the difference in mean effectiveness of a new treatment compared with a standard, adjusted for cost difference by subtracting the health foregone if purchasing care at the rate of a marginally cost‐effective therapy. Because net health benefit (NHB) is dependent on this threshold rate, one can construct confidence intervals for the INHB at various values of the rate. It turns out that the set of rates where new and standard are not significantly different is equal to the Fieller's method confidence set for the ICER. We review the derivation of the Fieller's method confidence set, present numerical examples, and discuss the implications of our result for the calculation and interpretation of NHB analyses. Copyright © 2000 John Wiley & Sons, Ltd.

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  • Daniel F. Heitjan, 2000. "Fieller's method and net health benefits," Health Economics, John Wiley & Sons, Ltd., vol. 9(4), pages 327-335, June.
    • Handle: RePEc:wly:hlthec:v:9:y:2000:i:4:p:327-335
    DOI: 10.1002/1099-1050(200006)9:4<327::AID-HEC517>3.0.CO;2-S
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    References listed on IDEAS

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    1. 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.
    2. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits," Medical Decision Making, , vol. 18(2_suppl), pages 68-80, April.
    3. 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, December.
    4. 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.
    5. 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.
    6. Daniel F. Heitjan & Alan J. Moskowitz & William Whang, 1999. "Problems with Interval Estimates of the Incremental Cost—Effectiveness Ratio," Medical Decision Making, , vol. 19(1), pages 9-15, January.
    7. 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.
    8. 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. Morris Meisner & Eugene M. Laska & Carole Siegel & Joseph Wanderling, 2002. "The familywise error rate of a simultaneous confidence band for the incremental net health benefit," Health Economics, John Wiley & Sons, Ltd., vol. 11(3), pages 275-280, April.
    2. Nandita Mitra & Alka Indurkhya, 2005. "A propensity score approach to estimating the cost–effectiveness of medical therapies from observational data," Health Economics, John Wiley & Sons, Ltd., vol. 14(8), pages 805-815, August.
    3. Hawre Jalal & Jeremy D. Goldhaber-Fiebert & Karen M. Kuntz, 2015. "Computing Expected Value of Partial Sample Information from Probabilistic Sensitivity Analysis Using Linear Regression Metamodeling," Medical Decision Making, , vol. 35(5), pages 584-595, July.
    4. Andrew Briggs, 2012. "Statistical Methods for Cost-effectiveness Analysis Alongside Clinical Trials," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 50, Edward Elgar Publishing.
    5. Richard M. Nixon & David Wonderling & Richard D. Grieve, 2010. "Non‐parametric methods for cost‐effectiveness analysis: the central limit theorem and the bootstrap compared," Health Economics, John Wiley & Sons, Ltd., vol. 19(3), pages 316-333, March.
    6. 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.
    7. 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.
    8. Andrew R. Willan & Andrew H. Briggs & Jeffrey S. Hoch, 2004. "Regression methods for covariate adjustment and subgroup analysis for non‐censored cost‐effectiveness data," Health Economics, John Wiley & Sons, Ltd., vol. 13(5), pages 461-475, May.
    9. 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.
    10. Quang Dang Nguyen & Mikhail Prokopenko, 2022. "A general framework for optimising cost-effectiveness of pandemic response under partial intervention measures," Papers 2205.08996, arXiv.org, revised Nov 2022.
    11. 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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