Large language models management of complex medication regimens: a case-based evaluation
Caution is warranted using present LLMs for medication regimens given the number of medication errors that were identified in this pilot study. However, LLMs did demonstrate potential to serve as clinical decision support for the management of complex medication regimens given the need for domain specific prompting and testing.
Authors
- Susan Smith (ORCID: https://orcid.org/0000-0002-5171-8405)
- Brian Murray (ORCID: https://orcid.org/0000-0001-6660-9749)
- Andrea Sikora (ORCID: https://orcid.org/0000-0003-2020-0571)
- Kelli Keats (ORCID: https://orcid.org/0000-0002-6686-1079)
- Aaron Chase (ORCID: https://orcid.org/0000-0002-5891-4492)
- Xianyan Chen (ORCID: https://orcid.org/0000-0002-1806-0883)
- Tanner Hedrick
- Erin Barreto
- Amoreena Most (ORCID: https://orcid.org/0000-0002-1958-5374)
- Sheng Li (ORCID: https://orcid.org/0000-0003-1205-8632)
- Tianming Liu
- Shaochen Xu (ORCID: https://orcid.org/0009-0008-0802-9218)
Institutions
- University of North Carolina at Chapel Hill (US)
- WellStar Health System (US)
- Georgia College & State University (US)
- University of Georgia (US)
- Augusta University (US)
- Augusta University Health (US)
- Mayo Clinic in Arizona (US)
- New Mexico VA Health Care System (US)
- University of Virginia (US)
- University of Montana (US)
- University of Colorado Denver (US)
Publication Details
- Journal
- Frontiers in Pharmacology
- Published
- 2025-11-24
- DOI
- https://doi.org/10.3389/fphar.2025.1514445
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 0.00