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Representing uncertainty: the role of cost-effectiveness acceptability curves


  • Elisabeth Fenwick

    (Centre for Health Economics, University of York, York, UK)

  • Karl Claxton

    (Department of Economics and Related Studies, University of York, York, UK)

  • Mark Sculpher

    (Centre for Health Economics, University of York, York, UK)


Decision-making in health care is inevitably undertaken in a context of uncertainty concerning the effectiveness and costs of health care interventions and programmes. One method that has been suggested to represent this uncertainty is the cost-effectiveness acceptability curve. This technique, which directly addresses the decision-making problem, has advantages over confidence interval estimation for incremental cost-effectiveness ratios. However, despite these advantages, cost-effectiveness acceptability curves have yet to be widely adopted within the field of economic evaluation of health care technologies. In this paper we consider the relationship between cost-effectiveness acceptability curves and decision-making in health care, suggest the introduction of a new concept more relevant to decision-making, that of the cost-effectiveness frontier, and clarify the use of these techniques when considering decisions involving multiple interventions. We hope that as a result we can encourage the greater use of these techniques. Copyright © 2001 John Wiley & Sons, Ltd.

Suggested Citation

  • Elisabeth Fenwick & Karl Claxton & Mark Sculpher, 2001. "Representing uncertainty: the role of cost-effectiveness acceptability curves," Health Economics, John Wiley & Sons, Ltd., vol. 10(8), pages 779-787.
  • Handle: RePEc:wly:hlthec:v:10:y:2001:i:8:p:779-787 DOI: 10.1002/hec.635

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    References listed on IDEAS

    1. Johannesson, Magnus & Weinstein, Milton C., 1993. "On the decision rules of cost-effectiveness analysis," Journal of Health Economics, Elsevier, vol. 12(4), pages 459-467, December.
    2. 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.
    3. Elizabeth Fenwick & Karl Claxton & Mark Sculpher & Andrew Briggs, 2000. "Improving the efficiency and relevance of health technology assessent: the role of iterative decision analytic modelling," Working Papers 179chedp, Centre for Health Economics, University of York.
    4. Palmer, Stephen & Smith, Peter C., 2000. "Incorporating option values into the economic evaluation of health care technologies," Journal of Health Economics, Elsevier, vol. 19(5), pages 755-766, September.
    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. Karl Claxton & John Posnett, "undated". "An Economic Approach to Clinical Trial Design and Research Priority Setting," Discussion Papers 96/19, Department of Economics, University of York.
    7. Andrew H. Briggs, 1999. "A Bayesian approach to stochastic cost-effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 257-261.
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