Improving medication error classification using a reasoning large language model
This validated AI-driven method can be integrated directly into clinical informatics workflows, enabling healthcare organizations to rapidly and consistently identify medication errors, ultimately enhancing patient safety outcomes.
Authors
- Kristian Sandström (ORCID: https://orcid.org/0000-0002-3375-6766)
- Anders Krifors (ORCID: https://orcid.org/0000-0003-1230-0492)
- Karl-Johan Lindner
- Theodor Beskow
- Jenny Calås
- Veronica Arwsbo
- Christer Norström
- Magnus Jonsson
Institutions
- Karolinska Institutet (SE)
- Västmanlands sjukhus Västerås (SE)
- Västerås Municipality (SE)
- Mälardalen University (SE)
- County Administrative Board (SE)
- Image Intelligence (Sweden) (SE)
Publication Details
- Journal
- JAMIA Open
- Published
- 2026-01-06
- DOI
- https://doi.org/10.1093/jamiaopen/ooag004
- Primary Topic
- Pharmacovigilance and Adverse Drug Reactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00