Presentation (CTI)

OBJECTIVES: Traditional cost-effectiveness analysis (CEA) values quality-adjusted life years (QALYs) equally regardless of recipient socioeconomic status, potentially creating an “equity-trap” in which restrictive coverage of high-cost therapies, such as GLP-1 receptor agonists, may inadvertently widen health disparities among populations bearing disproportionate obesity burdens. We propose a methodological framework that integrates Social Determinants of Health (SDOH) into value assessment using Distributional Cost-Effectiveness Analysis (DCEA) within a Multi-Criteria Decision Analysis (MCDA) structure.
METHODS: The framework was developed through a targeted review of equity-focused health technology assessment (HTA) methodologies and is grounded in prioritarian ethics and Atkinson social welfare theory. It stratifies populations by a composite SDOH vulnerability index encompassing socioeconomic position, geographic access, health literacy, and structural determinants. Equity weights are applied to QALYs based on baseline health distributions, and cost-effectiveness results are integrated within an MCDA framework spanning clinical-effectiveness, economic impact, equity considerations, and implementation feasibility.
RESULTS: The proposed framework specifies five integrated methodological components. First, a composite SDOH vulnerability index is constructed to stratify populations by socioeconomic and structural disadvantage. Second, a Markov cohort model simulates obesity progression and related complications over a 20-year horizon, comparing GLP-1 therapy with standard care using SDOH-stratified transition probabilities, adherence patterns, and access parameters. Third, equity-weighted outcomes are generated using an Atkinson social welfare function, with inequality aversion parameters enabling sensitivity analyses across alternative societal value judgments. Fourth, outcomes are synthesized through MCDA across four weighted domains: clinical effectiveness, economic impact, equity, and implementation feasibility. Fifth, probabilistic sensitivity analysis using Monte Carlo simulation produces distributional impact estimates and equity-impact acceptability frontiers.
CONCLUSIONS: This framework offers a practical methodology for incorporating distributional consequences into GLP-1 value assessment, addressing equity concerns in coverage and reimbursement decisions. Future validation will require empirical application using SDOH-stratified real-world data, stakeholder elicitation of equity preferences, and comparison with observed access patterns and health outcomes.