OBJECTIVE To assess clinical, economic, and social impacts of treating obesity among adult Medicaid beneficiaries, including budget implications and value of intensive lifestyle management, obesity medications, and metabolic/bariatric surgery. RESEARCH DESIGN AND METHODS A Markov-based microsimulation model estimated 5-year (2025–2029) outcomes associated with evidence-based obesity treatments. The model simulated changes in body weight and cardiometabolic risk factors, projecting impacts on disease incidence and resulting social benefits, including medical cost savings, productivity improvements, quality-adjusted life-years, and mortality reductions. Model inputs were informed by clinical trials, economic studies, and nationally representative data sets. RESULTS Obesity treatment could generate social return on investment of 3. 81 per dollar nationally and 8. 57 from states’ perspective. Among 9. 6 million Medicaid adult beneficiaries with obesity lacking qualifying obesity-related complications, 5. 9 million could be referred for intervention, yielding ∼2 million treatment person-years over 5 years. Treatment would produce 75, 800 quality-adjusted life-years (7 billion value), 11. 8 billion in mortality reductions, 847 million in productivity benefits, and nearly 1 billion in medical cost savings, totaling 15 billion in net social value nationally. Based on modeled treatment initiation and continuation rates, achieving these benefits would cost 5. 4 billion nationally (2. 3 billion for states). CONCLUSIONS While medical savings offset only a portion of treatment costs, obesity interventions generate substantial social value through improved long-term health and productivity. These findings support expanded Medicaid coverage as a strategic investment in population health, demonstrating value that challenges conventional short-term, budget-focused coverage decisions which currently limit access to evidence-based obesity treatments for millions of adults.
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T. Livingston
GE Global Research (United States)
Timothy M. Dall
Murata (Japan)
Fang Chen
Harvard University
Boston University
Tufts University
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Livingston et al. (Tue,) studied this question.
synapsesocial.com/papers/69730f78c8125b09b0d1f3b1 — DOI: https://doi.org/10.2337/doci25-0005