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Reporting Uncertainty Around Health-State Values: A Standard Method and Worked Example.

Nancy J Devlin1, Giselle Abangma2, Andrew Lloyd2

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Value in Health : the Journal of the International Society for Pharmacoeconomics and Outcomes Research
|December 18, 2024
PubMed
Summary
This summary is machine-generated.

Researchers demonstrate calculating standard errors (SEs) for health-related quality of life values. This provides crucial uncertainty information for cost-effectiveness models, enhancing sensitivity analyses.

Keywords:
EQ-5DHRQoLQALYshealth-state preferencesuncertaintyutilitiesvalue setsvalues

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Area of Science:

  • Health Economics
  • Psychometrics
  • Biostatistics

Background:

  • Value sets are crucial for cost-effectiveness analysis, typically reporting coefficient standard errors (SEs).
  • Existing reporting practices lack information on health-state value uncertainty, hindering sensitivity analyses in economic modeling.
  • Standard errors for health-related quality of life values are essential for robust economic evaluations.

Purpose of the Study:

  • To demonstrate a method for calculating SEs for all health-state values within a value set.
  • To provide a practical example using the UK EQ-5D-3L value set.
  • To advocate for routine reporting of SEs for health-state values.

Main Methods:

  • Utilizing the variance/covariance matrix from value set models to estimate SEs.
  • Applying the method to replicate the UK EQ-5D-3L value set and its associated variance/covariance matrix.
  • Calculating SEs for all 243 EQ-5D-3L health states using data from the Measurement and Valuation of Health study.

Main Results:

  • Successfully calculated SEs for all health states within the UK EQ-5D-3L value set.
  • The range of SEs was found to be small relative to the health-state values.
  • The calculated SEs are conditional on model specification and may vary with alternative specifications.

Conclusions:

  • Routine reporting of SEs for health-state values should be adopted to inform users about parameter uncertainty.
  • These SEs represent a significant step towards a comprehensive understanding of uncertainty in preference weights.
  • Improved reporting of uncertainty in value sets will enhance the reliability of quality-adjusted life-year (QALY) estimations.