Evaluating Large Language Models for Drafting Emergency Department Discharge Summaries.

ABSTRACT:

Importance

Large language models (LLMs) possess a range of capabilities which may be applied to the clinical domain, including text summarization. As ambient artificial intelligence scribes and other LLM-based tools begin to be deployed within healthcare settings, rigorous evaluations of the accuracy of these technologies are urgently needed.

Objective

To investigate the performance of GPT-4 and GPT-3.5-turbo in generating Emergency Department (ED) discharge summaries and evaluate the prevalence and type of errors across each section of the discharge summary.

Design

Cross-sectional study.

Setting

University of California, San Francisco ED.

Participants

We identified all adult ED visits from 2012 to 2023 with an ED clinician note. We randomly selected a s

SUBMITTER: Williams CYK 

PROVIDER: S-EPMC11023681 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature