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Healthy Years Equivalents (HYEs) and Decision Trees: A Simple, Two-Stage, Lottery-based Algorithm

Author

Listed:
  • Amiram Gafni

    (Department of Clinical Epidemiology & Biostatistics, Centre for Health Economics and Policy Analysis, McMaster University)

  • Stephen Birch

    (Department of Clinical Epidemiology & Biostatistics, Centre for Health Economics and Policy Analysis, McMaster University)

  • Bernie O'Brien

    (Department of Clinical Epidemiology & Biostatistics, McMaster University, Centre for Evaluation of Medicines, St. Joseph's Hospital)

Abstract

Recent publications have acknowledged the theoretical superiority of the healthy years equivalent (HYE) concept over quality-adjusted life-years (QALYs), but have raised questions about the practicality of measuring them. We describe a simple, two-stage, lottery-based approach to measure HYEs for the case of a decision tree type analysis. The suggested algorithm follows the general approach to HYE measurement suggested by Mehrez and Gafni, and is based on the standard gamble (SG) method, which is well-established and empirically well-tested. We further discuss issues relating to the burden (i.e., number and complexity of questions posed) the measurement process imposes on the respondent. We show that there is no a priori reason why HYE must always involve greater measurement burden than QALYs. Moreover, for many treatment alternatives in which death is not a realistic option, HYE also offers an empirical advantage of reduced cognitive burdens for respondents.

Suggested Citation

  • Amiram Gafni & Stephen Birch & Bernie O'Brien, 1995. "Healthy Years Equivalents (HYEs) and Decision Trees: A Simple, Two-Stage, Lottery-based Algorithm," Centre for Health Economics and Policy Analysis Working Paper Series 1995-04, Centre for Health Economics and Policy Analysis (CHEPA), McMaster University, Hamilton, Canada.
    • Handle: RePEc:hpa:wpaper:199504
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    File URL: http://www.chepa.org/Files/Working%20Papers/WP%2095-04.pdf
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