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Impact of Smoothing and Modeling Approach on Quality-Adjusted Life Expectancy Estimates
Hosein Ameri1, Thomas G Poder2
1Department of Social and Preventive Medicine, Faculty of Medicine, Laval University, Québec City, QC, Canada; Centre de recherche de l'IUSMM, CIUSSS de l'Est de l'Île de Montréal, Montreal, QC, Canada.
Summary
This study compared the Sullivan method and Markov modeling for estimating Quality-Adjusted Life Expectancy (QALE) in Quebec. Both methods produced highly consistent and reliable QALE estimates, supporting their use in health assessments.
Area of Science:
- Health Economics
- Biostatistics
- Public Health
Background:
- Quality-Adjusted Life Expectancy (QALE) integrates life expectancy and health utility.
- Traditional Sullivan method vs. flexible Markov modeling for QALE estimation.
- Need for age- and sex-specific QALE norms.
Purpose of the Study:
- Estimate age- and sex-specific QALE for Quebec.
- Compare QALE results from Sullivan and Markov modeling approaches.
- Evaluate the impact of cubic polynomial fitting on age-specific utilities.
Main Methods:
- Utilized EQ-5D-5L data (2016-2024) and life tables (2021-2023).
- Applied Sullivan method and Markov microsimulation with cubic polynomial smoothing.
- Employed Monte Carlo simulations for uncertainty quantification and t-tests for comparison.
Main Results:
- Cubic polynomial regression yielded excellent fits for age-utility curves (R²=0.86).
- Sullivan and Markov QALE estimates showed high consistency (R²=0.99) with minor differences.
- Markov estimates were slightly higher than Sullivan estimates, but differences were not clinically significant.
Conclusions:
- Both Sullivan and Markov methods provide valid and reliable QALE estimates.
- Findings support the use of either method for population health assessment.
- The chosen method depends on specific study needs and flexibility requirements.
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