Top 10 States by Reported Medicaid GLP-1 Prescriptions in 2025
California leads this comparison of GLP-1 usage by state, with 3,089,327 reported Medicaid GLP-1 prescriptions in 2025; Pennsylvania and New York rank second and third. This comparison covers all four quarters of 2025 and the 50 states, excluding DC, Puerto Rico, and national “XX” rows.
The counts are published values: suppressed counts are not imputed. The ranking describes the order of published counts, not a confirmed ordering of complete totals that would include hidden values. A second measure compares reported GLP-1 prescriptions with all reported Medicaid outpatient prescriptions in each state. It is a prescription-mix measure, not an enrollment-adjusted or per-capita rate.
Table of contents
- The 2025 Medicaid state ranking
- What the 2025 state ranking measures
- How to interpret the prescription-mix measure
- Important limitations in the reported counts
- What the state comparison can and can not tell you
- Frequently asked questions
- Explore structured public healthcare data
- Sources
The 2025 Medicaid state ranking
The table ranks the 50 states by reported Medicaid prescription counts in 2025. The included group covers GLP-1 products plus Mounjaro and Zepbound, which contain the dual GIP/GLP-1 receptor agonist tirzepatide. The selected groups include brand-labelled and ingredient-labelled records: Ozempic, Wegovy, Trulicity, Zepbound, Mounjaro, Rybelsus, Liraglutide-labelled products, Victoza, Saxenda, Bydureon-labelled products, Byetta, Exenatide-labelled products. Fixed insulin combinations, supplements and compounded or unreported products are excluded.
| Rank | State | Reported GLP-1 prescriptions | GLP-1 per 1,000 reported Medicaid outpatient prescriptions | Suppressed GLP-1 rows |
|---|---|---|---|---|
| 1 | California | 3,089,327 | 34.62 | 45 |
| 2 | Pennsylvania | 843,743 | 25.23 | 104 |
| 3 | New York | 815,882 | 11.44 | 64 |
| 4 | Michigan | 607,982 | 21.70 | 95 |
| 5 | North Carolina | 484,401 | 22.03 | 89 |
| 6 | Ohio | 425,301 | 11.42 | 114 |
| 7 | Massachusetts | 399,014 | 27.91 | 84 |
| 8 | Wisconsin | 302,633 | 24.71 | 19 |
| 9 | Illinois | 288,470 | 12.81 | 58 |
| 10 | Missouri | 285,105 | 17.98 | 40 |
What the 2025 state ranking measures
Medicaid State Drug Utilization Data (SDUD) covers information reported by states for covered outpatient drugs paid for by state Medicaid agencies. CMS field definitions describe the prescription count as prescriptions reimbursed by Medicaid to pharmacists for an NDC-level drug during the reporting period. Records can represent Fee-for-Service Utilization or Managed Care Organization Utilization.
The analysis combines records from the first four quarters of 2025 and ranks the 50 states by published GLP-1 prescription counts. It excludes DC and Puerto Rico, as well as national “XX” records. Every state has observations in all four quarters.
The included product group covers single-ingredient GLP-1 products and tirzepatide products, which are dual GIP/GLP-1 receptor agonists. It excludes fixed insulin combinations, supplements, and compounded or unreported products. FDA NDC records inform product and ingredient classification, but a directory listing alone does not establish current marketing or approval.
For a broader view of the medication-level rankings, see GLP-1 drug rankings.
How to interpret the prescription-mix measure
The per-1,000 figure divides reported GLP-1 prescriptions by all reported Medicaid outpatient prescriptions in the same state and year, then multiplies by 1,000. Suppressed records are excluded from both the GLP-1 count and the outpatient-prescription denominator. The result describes prescription mix: reported GLP-1 prescriptions per 1,000 reported Medicaid outpatient prescriptions.
This measure is not per-capita use, enrolled-person prevalence, or an enrollment-adjusted rate. It does not indicate how many distinct people received prescriptions. Nor do the data identify why a prescription was written.
Among the ten states shown, California has the highest prescription-mix measure, at 34.62 per 1,000. Massachusetts follows at 27.91, then Pennsylvania at 25.23 and Wisconsin at 24.71. Ohio and New York have the lowest mix measures among the ten—11.42 and 11.44, respectively—even though they rank sixth and third by published count.
Reading the measures together separates volume from composition. A higher published count means more reported prescriptions in the dataset; a higher mix measure means GLP-1 prescriptions account for a larger share of reported Medicaid outpatient prescriptions. Neither measure provides a count of unique people.
Important limitations in the reported counts
The source is the 2025 Medicaid State Drug Utilization Data CSV, July 2026 revision, retrieved on 21 October 2026. The source counts were not changed.
Suppressed or missing prescription counts are excluded, not set to zero or imputed. The table therefore ranks published counts only. Because the hidden values are not included, the ranking does not establish the complete-data ordering. Readers should not treat the displayed ranks as definitive positions for totals that would include suppressed records.
Geographic scope also matters. DC and Puerto Rico are outside the 50-state ranking, and national “XX” records are not added to state totals. The 50-state sum and CMS national aggregate do not reconcile because of differences in scope and suppression; the national aggregate is not a simple sum of the state results.
These figures count reimbursed prescriptions, not unique patients, 30-day-equivalent fills, sales, manufacturer revenue, or all-payer U.S. market share. They cannot establish clinical superiority, prescribing appropriateness, or a diagnosis. They describe reported Medicaid outpatient prescriptions, not overall GLP-1 use in the general population.
What the state comparison can and can not tell you
For researchers and analysts, the table offers two descriptive views: published prescription volume and the share of reported Medicaid outpatient prescriptions accounted for by the included GLP-1 group. Within the top ten, California has both the highest published count and the highest prescription-mix measure. Differences between count rank and mix measure also show why volume alone does not describe prescription composition.
The per-1,000 figure does not adjust for Medicaid enrollment. An enrollment-adjusted comparison would require an appropriate enrollment denominator and a method aligned with the population and period under study. The measure here is best interpreted as prescription mix, with suppression and reporting scope in view.
Prescription counts and drug prices answer different questions. For related context on reported prices and Medicare changes, see GLP-1 price changes for 2027.
Frequently asked questions
These questions clarify what the reported counts and prescription-mix measure do—and do not—represent.
Does this ranking show how many people used GLP-1 drugs?
No. It counts reported Medicaid prescriptions, not unique patients. The data do not identify the reason a prescription was written.
Is the per-1,000 figure adjusted for Medicaid enrollment?
No. It divides reported GLP-1 prescriptions by all reported Medicaid outpatient prescriptions in the same state and year, then multiplies by 1,000. Suppressed records are excluded from both numerator and denominator. The measure describes prescription mix, not enrollment-adjusted or per-capita use.
Are suppressed prescriptions included in the state counts?
No. Suppressed or missing counts are not imputed. The table ranks published counts, and this ordering does not establish the hidden complete-data ranking.
California ranks first with 3,089,327 published Medicaid GLP-1 prescriptions in 2025, followed by Pennsylvania and New York. The ranking covers all four quarters and the 50 states, excluding DC, Puerto Rico, and national “XX” rows. Its per-1,000 measure compares reported GLP-1 prescriptions with all reported Medicaid outpatient prescriptions, not with people or enrollment. Because suppressed counts are not imputed, the published-count ranking does not establish the hidden complete-data ordering.
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