Evidence map›Paper›PMID 42789287›Full record

ArticleJAMA health forum2026

GLP-1 Receptor Agonist Coverage for Obesity in Medicaid and Total GLP-1 Receptor Agonist Utilization.

Ritikaa Khanna, Michael C Wang, Atheendar S Venkataramani

Abstract read
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Article in JAMA health forum, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Ritikaa KhannaCorporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania.
Michael C WangCorporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania.
Atheendar S VenkataramaniLeonard David Institute of Health Economics, University of Pennsylvania, Philadelphia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are effective for treating obesity, but few Medicaid programs cover them due to cost concerns with accelerating utilization. However, potential substitution effects between obesity-labeled GLP-1 RAs and diabetes-labeled GLP-1 RAs, which have identical active ingredients and which all states cover, are not well understood. Objective: To determine whether Medicaid coverage of obesity-labeled GLP-1 RAs is associated with obesity-labeled, diabetes-labeled, and total GLP-1 RA utilization. Design, Setting, and Participants: This cross-sectional study used US state-level Medicaid drug utilization data from 2021 to 2024. Synthetic difference-in-differences was used to assess the association of obesity-labeled GLP-1 RA coverage with GLP-1 RA utilization. Exposure: Medicaid program coverage of obesity-labeled GLP-1 RAs. Main Outcomes and Measures: The primary outcome was aggregate quarterly prescriptions per 1000 beneficiaries; secondary outcomes included prescription-months (accounting for duration of fills) and Medicaid reimbursement per 1000 beneficiaries. Results: Of 9 states (n = 89 021 657; mean [SD] of 49.4% [0.5%] were male, 50.6% [0.5%] were female) that began Medicaid coverage of obesity-labeled GLP-1 RAs between 2021 and 2024 and 36 control states (n = 212 786 953; mean [SD] of 49.8% [0.9%] were male, 50.2% [0.9%] were female), overall and diabetes-labeled GLP-1 RA utilization increased substantially in both groups, whereas obesity-labeled GLP-1 RA increased significantly only in treated states. Estimates from synthetic difference-in-differences models demonstrated a mean increase in obesity-labeled GLP-1 RA of 6.48 prescriptions per 1000 beneficiaries (95% CI, 4.00-8.96; P < .001), with estimates increasing nearly each quarter after Medicaid coverage was implemented. By contrast, changes in total GLP-1 RA prescriptions compared with obesity-labeled prescriptions were not statistically significant (4.17 per 1000 beneficiaries [95% CI, -0.33 to 8.67; P = .07]), nor were those for diabetes-labeled GLP-1 RA prescriptions (-2.16 prescriptions per 1000 beneficiaries [95% CI, -5.27 to 0.96; P = .17]). In the subgroup of states with prior authorization requirements more restrictive than the Food and Drug Administration label, there was a significant relative decrease in diabetes-labeled GLP-1 RA utilization of 3.02 prescriptions per 1000 beneficiaries (95% CI, -5.69 to -0.36; P = .03). Conclusions and Relevance: Results of this study suggest that substitution effects are possible between obesity-labeled and diabetes-labeled GLP-1 RAs, varying by state coverage policies, that could impact coverage decisions.

Indexed as

Drug UtilizationGlucagon-Like Peptide-1 Receptor AgonistsInsurance CoverageMedicaidObesityCross-Sectional StudiesHumansHypoglycemic AgentsUnited StatesGlucagon-Like Peptide-1 Receptor AgonistsHypoglycemic Agents

Identifiers

PMID42789287
PMCPMC13615463

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.