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Predicting Health Utilities Using Health Administrative Data: Leveraging Survey-linked Health Administrative Data
Yue Niu1, Nazire Begen1, Guangyong Zou1
1Department of Epidemiology and Biostatistics, Western Centre for Public Health and Family Medicine, Schulich School of Medicine & Dentistry, Western University, London, ON, N6G 2M1, Canada.
Applied Health Economics and Health Policy
|February 6, 2025
Summary
We developed a predictive model for health utilities using health administrative data. This model accurately predicts health utilities when preference-based data are unavailable, aiding health outcome measurement.
Area of Science:
- Health Economics
- Biostatistics
- Public Health
Background:
- Quality-adjusted life year (QALY) measurement requires health utilities, derived from health-related quality of life (HRQoL) data.
- Preference-based utility data are often unavailable, creating a gap in reliable QALY calculations.
- This study addresses the need for predictive models for health utilities.
Purpose of the Study:
- To develop a predictive model for health utilities.
- Utilize demographic and morbidity variables from health administrative data.
- Focus on non-institutionalized populations in Ontario, Canada.
Main Methods:
- Data from the 2009-2010 Canadian Community Health Survey linked with Ontario health administrative (OHA) data.
- Inclusion of the Health Utilities Index Mark3 (HUI3) instrument.
- Comparison of four regression models (linear, Tobit, single-part beta mixture, two-part beta mixture) and calibration techniques.
Main Results:
- The two-part beta mixture model demonstrated the best fit for predicting health utilities.
- The developed model accurately reflects the original distribution of HUI3 in the population.
- The predictive model provides reasonably accurate health utility predictions from OHA data.
Conclusions:
- A novel predictive model for health utilities has been successfully developed.
- This model offers a practical solution for situations lacking preference-based utility data.
- The approach is valuable for real-world health economic evaluations and policy-making.
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