Monitoring Report: GLP-1 RA Prescribing Trends – December 2025 Data

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

Background

Limited recent data exist on prescribing patterns and patient characteristics for glucagon-like peptide 1 receptor agonists (GLP-1 RAs), an important drug class used as anti-diabetic medication (ADM) for patients with type 2 diabetes mellitus (T2D) and/or anti-obesity medication (AOM) in patients with overweight or obesity.

For brevity, we use the term GLP-1 RA to refer to both GLP-1 RA and dual GLP-1 RA/GIP medications.

Objective

To describe recent trends in prescribing and dispensing of GLP-1-based medications in the US.

Methods

Using a subset of real-world electronic health record (EHR) data from Truveta, a growing collective of health systems that provide more than 18% of all daily clinical care in the US, we identified people who were prescribed a GLP-1-based medication between January 01, 2019 and December 31, 2025. We describe prescribing volumes and patient characteristics over time, by medication, and by FDA-labeled use. Among the subset of patients for whom post-prescription dispensing data is available, we describe the proportion and characteristics of patients who were and were not dispensed a GLP-1 RA following their prescription.

Results

2,185,238 patients were prescribed a GLP-1 RA between January 2019 and December 2025, with 11,194,909 total prescriptions during this period. Among first-time prescriptions for which use could be established, 69.1% were ADMs and 30.9% were AOMs. Overall prescribing rates (GLP-1 RA prescriptions per total prescriptions) increased slightly from September to December 2025 (+5.02%); however, first-time prescribing rates declined over the same period (-6.62%). As of December 2025, GLP-1 RA prescriptions account for more than 7% of all prescriptions.

Article activity feed