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Related Experiment Videos

Time preference for health in cost-effectiveness analysis.

J Lipscomb1

  • 1Departments of Public Policy Studies and Community and Family Medicine, Duke University, Durham, NC 27706.

Medical Care
|March 1, 1989
PubMed
Summary
This summary is machine-generated.

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Valuing future health gains requires considering both intergenerational equity and individual time preferences. A new two-step "scenario strategy" method helps evaluate multiperiod health outcomes more accurately.

Area of Science:

  • Health Economics
  • Program Evaluation
  • Decision Analysis

Background:

  • Cost-effectiveness analyses frequently evaluate future health gains.
  • Standard models struggle to simultaneously account for intergenerational equity and individual time preferences.

Purpose of the Study:

  • To address the challenge of valuing future quality-adjusted life year (QALY) gains in program evaluations.
  • To introduce a novel method for incorporating distinct time preferences into multiperiod health outcome assessments.

Main Methods:

  • Proposed a two-step evaluation procedure incorporating the "scenario strategy."
  • Utilized a holistic multiattribute preference approach for multiperiod health outcomes.
  • Employed a survey-based example to illustrate the methodology.

Related Experiment Videos

Main Results:

  • Identified two distinct interpretations of time preference relevant to program evaluation: intergenerational equity and individual time preference.
  • Demonstrated that standard discounting models inadequately address both interpretations simultaneously.
  • The "scenario strategy" allows for statistical isolation and incorporation of individual time preference effects.

Conclusions:

  • A nuanced approach is needed to value future health gains, accounting for both societal and individual time perspectives.
  • The proposed "scenario strategy" offers a more comprehensive framework for evaluating multiperiod health outcomes in program and cost-effectiveness analyses.
  • This method enhances the accuracy of resource allocation decisions by better reflecting diverse time preferences.