Estimating Health Utility Decrements Associated With Chronic Disease Outcomes Using MEPS
Author(s)
Piaopiao Li, MS1, Hui Shao, MHA, PhD, MD2.
1PhD candidate, University of Florida, Gainesville, FL, USA, 2Emory University, Atlanta, GA, USA.
1PhD candidate, University of Florida, Gainesville, FL, USA, 2Emory University, Atlanta, GA, USA.
OBJECTIVES: To estimate the health-related quality of life utility decrements associated with common chronic conditions in a nationally representative U.S. population using the Medical Expenditure Panel Survey (MEPS).
METHODS: We used data from the Full-Year Consolidated and Medical Conditions Files of MEPS to construct a longitudinal dataset of U.S. adults aged 18 and older (2016-2022). Medical conditions were identified using ICD-9 and ICD-10 codes and grouped into clinically meaningful disease categories. Health utility scores were derived by mapping SF-12 responses to SF-6D scores using a validated regression-based algorithm. We estimated the association between individual chronic conditions and utility scores using multivariable linear regression. The dependent variable was the SF-6D utility score, and independent variables included binary indicators for disease categories, adjusted for age group, sex, race/ethnicity, education, marital status, insurance type, and income level. Regression coefficients for disease indicators were interpreted as utility decrements associated with each condition.
RESULTS: The analytic sample included 29,210 individuals with a mean SF-6D utility score of 0.72 (standard deviation: 0.09). Depression, pain, and end-stage renal disease were associated with the largest utility decrements, with estimated reductions of 0.048, 0.023, and 0.031, respectively, all statistically significant at p < 0.001. Additional significant utility decrements were observed for type 2 diabetes (−0.012), post-traumatic stress disorder (−0.019), chronic kidney disease (−0.018), apnea (−0.018), myocardial infarction (−0.016), and gout (−0.009). Public insurance coverage and low-income status were also independently associated with lower utility scores. Most demographic and socioeconomic covariates showed statistically significant associations with utility.
CONCLUSIONS: This study provides estimates of health utility decrements associated with a wide range of chronic conditions in the U.S. population. Mental health and cardiometabolic conditions are particularly impactful on quality of life. These utility estimates provide the necessary inputs to calculate quality-adjusted life years, which are essential for health economic evaluations.
METHODS: We used data from the Full-Year Consolidated and Medical Conditions Files of MEPS to construct a longitudinal dataset of U.S. adults aged 18 and older (2016-2022). Medical conditions were identified using ICD-9 and ICD-10 codes and grouped into clinically meaningful disease categories. Health utility scores were derived by mapping SF-12 responses to SF-6D scores using a validated regression-based algorithm. We estimated the association between individual chronic conditions and utility scores using multivariable linear regression. The dependent variable was the SF-6D utility score, and independent variables included binary indicators for disease categories, adjusted for age group, sex, race/ethnicity, education, marital status, insurance type, and income level. Regression coefficients for disease indicators were interpreted as utility decrements associated with each condition.
RESULTS: The analytic sample included 29,210 individuals with a mean SF-6D utility score of 0.72 (standard deviation: 0.09). Depression, pain, and end-stage renal disease were associated with the largest utility decrements, with estimated reductions of 0.048, 0.023, and 0.031, respectively, all statistically significant at p < 0.001. Additional significant utility decrements were observed for type 2 diabetes (−0.012), post-traumatic stress disorder (−0.019), chronic kidney disease (−0.018), apnea (−0.018), myocardial infarction (−0.016), and gout (−0.009). Public insurance coverage and low-income status were also independently associated with lower utility scores. Most demographic and socioeconomic covariates showed statistically significant associations with utility.
CONCLUSIONS: This study provides estimates of health utility decrements associated with a wide range of chronic conditions in the U.S. population. Mental health and cardiometabolic conditions are particularly impactful on quality of life. These utility estimates provide the necessary inputs to calculate quality-adjusted life years, which are essential for health economic evaluations.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
EE419
Topic
Clinical Outcomes, Economic Evaluation, Health Technology Assessment
Disease
No Additional Disease & Conditions/Specialized Treatment Areas