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Cost-effectiveness analysis with risk aversion.

J G Zivin1

  • 1International Center for Health Outcomes and Innovation Research and Joseph L. Mailman School of Public Health, Columbia University, New York 10032, USA.

Health Economics
|September 11, 2001
PubMed
Summary

Standard cost-effectiveness analysis in healthcare often wrongly assumes risk neutrality. This study introduces a risk-averse framework, finding that only one of two tested medical interventions is cost-effective under reasonable risk aversion levels.

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Area of Science:

  • Health Economics
  • Decision Analysis
  • Medical Intervention Evaluation

Background:

  • Traditional cost-effectiveness (CE) analysis in healthcare assumes a risk-neutral social planner.
  • This assumption may be inappropriate for medical interventions where outcomes can involve significant uncertainty.

Purpose of the Study:

  • To develop a framework for cost-effectiveness analysis that accounts for a risk-averse social planner.
  • To re-evaluate existing medical interventions using this new framework and assess the impact of societal risk aversion.

Main Methods:

  • Developed a cost-effectiveness analysis framework incorporating societal risk aversion.
  • Applied the framework to two previously evaluated medical interventions.
  • Determined the threshold level of societal risk aversion required to reject these interventions.

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Main Results:

  • The risk-neutral approach can incorrectly approve or reject medical interventions depending on their variance.
  • Under reasonable levels of societal risk aversion, only one of the two evaluated interventions remained cost-effective.
  • Significant differences in cost-effectiveness conclusions arise when risk aversion is considered.

Conclusions:

  • Societal risk aversion is a critical factor in healthcare decision-making and cost-effectiveness analysis.
  • The standard risk-neutral assumption can lead to suboptimal resource allocation.
  • Recommends reporting a cut-off risk aversion parameter in future CE studies for greater transparency and accuracy.