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Advantages of Using the Net-Benefit Approach for Analysing Uncertainty in Economic Evaluation Studies

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  • Niklas Zethraeus
  • Magnus Johannesson
  • Bengt Jönsson
  • Mickael Löthgren
  • Magnus Tambour

Abstract

No consensus has yet been reached on how to analyse uncertainty in economic evaluation studies where individual patient data are available for costs and health effects. This paper summarises the available results regarding the analysis of uncertainty on the cost-effectiveness plane and argues for using the net-benefit approach when analysing uncertainty in cost-effectiveness studies. The net-benefit approach avoids the interpretation and statistical problems related to the incremental cost effectiveness ratio and implies several advantages. First, traditional statistical methods can be used for confidence-interval estimation and hypothesis testing. Second, calculation of the optimal sample size and the power of the study are facilitated allowing the correlation between costs and effects to vary within and between patient groups. Third, the use of a Bayesian approach to cost-effectiveness analysis is facilitated. Fourth, a formal relation between cost-effectiveness acceptability curves and statistical inference is provided. Finally, the net-benefit approach gives the Fieller’s limits of the confidence interval for the incremental cost-effectiveness ratio in the cost-effectiveness plane. Based on these advantages the net-benefit approach should strongly be considered when analysing uncertainty in cost-effectiveness analyses. Copyright Adis International Limited 2003

Suggested Citation

  • Niklas Zethraeus & Magnus Johannesson & Bengt Jönsson & Mickael Löthgren & Magnus Tambour, 2003. "Advantages of Using the Net-Benefit Approach for Analysing Uncertainty in Economic Evaluation Studies," PharmacoEconomics, Springer, vol. 21(1), pages 39-48, January.
  • Handle: RePEc:spr:pharme:v:21:y:2003:i:1:p:39-48
    DOI: 10.2165/00019053-200321010-00003
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    References listed on IDEAS

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    1. Tambour, Magnus & Zethraeus, Niklas & Johannesson, Magnus, 1997. "A Note on Confidence Intervals in Cost-Effectiveness Analysis," SSE/EFI Working Paper Series in Economics and Finance 181, Stockholm School of Economics.
    2. Claxton, Karl, 1999. "The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies," Journal of Health Economics, Elsevier, vol. 18(3), pages 341-364, June.
    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. 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:

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    2. Nikki McCaffrey & Meera Agar & Janeane Harlum & Jonathon Karnon & David Currow & Simon Eckermann, 2015. "Better Informing Decision Making with Multiple Outcomes Cost-Effectiveness Analysis under Uncertainty in Cost-Disutility Space," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-19, March.
    3. Phillip Dinh & Xiao-Hua Zhou, 2006. "Nonparametric Statistical Methods for Cost-Effectiveness Analyses," Biometrics, The International Biometric Society, vol. 62(2), pages 576-588, June.
    4. Christian Brettschneider & Sebastian Kohlmann & Benjamin Gierk & Bernd Löwe & Hans-Helmut König, 2017. "Depression screening with patient-targeted feedback in cardiology: The cost-effectiveness of DEPSCREEN-INFO," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-15, August.

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