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Optimisation versus certainty: understanding the issue of heterogeneity in economic evaluation

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  • Stevens, Warren
  • Normand, Charles

Abstract

This paper considers how the information provided by economic evaluation for decision-makers can fail to optimise use of health resources and how assessment of the relative cost-effectiveness of health care interventions can be misleading unless heterogeneity within populations is taken into account. The cost-effectiveness of an intervention is not a point estimate but an average chosen from within a distribution of different results. The normal interpretation of the distribution around that point is often mistakenly assumed to be the 'white noise' of measurement error. In reality this variance is a combination of measurement error and true heterogeneity of results. There remains an overemphasis on pursuing certainty which stems from the fact that the methods involved were originally devised to measure dichotomous outcomes not continuous ones such as cost-effectiveness ratios. It is argued in this paper that more consideration be given to the heterogeneous nature of costs and effects across populations in analysis and policy making.

Suggested Citation

  • Stevens, Warren & Normand, Charles, 2004. "Optimisation versus certainty: understanding the issue of heterogeneity in economic evaluation," Social Science & Medicine, Elsevier, vol. 58(2), pages 315-320, January.
    • Handle: RePEc:eee:socmed:v:58:y:2004:i:2:p:315-320
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    Citations

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    Cited by:

    1. Joanne Lord & George Laking & Alastair Fischer, 2006. "Non‐linearity in the cost‐effectiveness frontier," Health Economics, John Wiley & Sons, Ltd., vol. 15(6), pages 565-577, June.
    2. Manuel A. Espinoza & Andrea Manca & Karl Claxton & Mark J. Sculpher, 2014. "The Value of Heterogeneity for Cost-Effectiveness Subgroup Analysis," Medical Decision Making, , vol. 34(8), pages 951-964, November.
    3. Aktas, Emel & Ulengin, Fusun & Onsel Sahin, Sule, 2007. "A decision support system to improve the efficiency of resource allocation in healthcare management," Socio-Economic Planning Sciences, Elsevier, vol. 41(2), pages 130-146, June.
    4. David van Klaveren & John B. Wong & David M. Kent & Ewout W. Steyerberg, 2017. "Biases in Individualized Cost-effectiveness Analysis: Influence of Choices in Modeling Short-Term, Trial-Based, Mortality Risk Reduction and Post-Trial Life Expectancy," Medical Decision Making, , vol. 37(7), pages 770-778, October.

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