Litcius/Paper detail

The effect of using a large language model to respond to patient messages

Shan Chen, Marco Guevara-Vega, Shalini Moningi, Frank Hoebers, Hesham Elhalawani, Benjamin H. Kann, Fallon Chipidza, Jonathan Leeman, Hugo J.W.L. Aerts, Timothy Miller, Guergana K Savova, Jack Gallifant, Leo A Celi, Raymond H Mak, Maryam B. Lustberg, Majid Afshar, Danielle S. Bitterman

2024The Lancet Digital Health125 citationsDOIOpen Access PDF

Abstract

The relentless increase in administrative responsibilities, amplified by electronic health record (EHR) systems, has diverted clinician attention from direct patient care, fuelling burnout.1 In response, large language models (LLMs) are being adopted to streamline clinical and administrative tasks. Notably, Epic is currently leveraging OpenAI's ChatGPT models, including GPT-4, for electronic messaging via online portals.2 The volume of patient portal messaging has escalated in the past 5–10 years,3 and general-purpose LLMs are being deployed to manage this burden.

Topics & Concepts

Computer sciencePsychologyNatural language processingArtificial Intelligence in Healthcare and EducationElectronic Health Records SystemsPatient-Provider Communication in Healthcare