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Cost‐effectiveness with multiple outcomes

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  • Jakob Bjørner
  • Hans Keiding

Abstract

In a large number of situations, activities in health care have to be measured in terms of outcome and cost. However, the cases where outcome is fully captured by a single measure are rather few, so that one uses some index for outcome, computed by weighing together several outcome measures using subjective and somewhat arbitrary weights. In the paper we propose an approach to cost‐effectiveness analysis where such artificial aggregation is avoided. This is achieved by assigning to each activity the weights which are the most favourable in a comparison with the other options available, so that activities which have a poor score in this method are guaranteed to be inferior. The method corresponds to applying Data envelopment analysis, known from the theory of productivity, to the context of health economic evaluations. The method is applied to an analysis of the cost‐effectiveness of alternative health plans using data from the Medical Outcome Study (JAMA 1996; 276: 1039–1047), where outcome is measured as improvement in mental and physical health. Copyright © 2004 John Wiley & Sons, Ltd.

Suggested Citation

  • Jakob Bjørner & Hans Keiding, 2004. "Cost‐effectiveness with multiple outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 13(12), pages 1181-1190, December.
    • Handle: RePEc:wly:hlthec:v:13:y:2004:i:12:p:1181-1190
    DOI: 10.1002/hec.900
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    References listed on IDEAS

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    1. 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.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    3. 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.
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    Cited by:

    1. Kankana Mukherjee & Rexford Santerre & Ning Jackie Zhang, 2010. "Explaining the efficiency of local health departments in the U.S.: an exploratory analysis," Health Care Management Science, Springer, vol. 13(4), pages 378-387, December.
    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. Amado, Carla Alexandra da Encarnação Filipe & Santos, Sérgio Pereira dos, 2009. "Challenges for performance assessment and improvement in primary health care: The case of the Portuguese health centres," Health Policy, Elsevier, vol. 91(1), pages 43-56, June.
    4. Miguel A. Negrín & Francisco J. Vázquez‐Polo, 2006. "Bayesian cost‐effectiveness analysis with two measures of effectiveness: the cost‐effectiveness acceptability plane," Health Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 363-372, April.

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