Comparison of physician-authored and artificial intelligence-generated after-visit summaries: A blinded comparative study.

Milla Kviatkovsky¹, Caden Stewart², Annalise McDonald¹, Yan Xing¹, Sara Gianella¹, Anna Gelberg¹, Bryan Huang¹, Shadi Mayasy¹, Kristina Djekic¹, Maryann Ally¹, Ian Jenkins¹, Benjamin Smarr^2,3, Karandeep Singh¹, Robert El-Kareh¹

¹Department of Medicine, Division of Hospital Medicine, University of California San Diego, La Jolla, California, USA.

²The Halıcıoğlu Data Science Institute, La Jolla, California, USA.

³The Shu Chien-Gene Lay Department of Bioengineering, La Jolla, California, USA.

PubMed DOI

Abstract

BACKGROUND: After-visit summaries (AVSs) are essential for a safe hospital discharge, yet are often written above literacy levels, omit key information, and are produced under substantial clinical time pressure. Large language models (LLMs) offer a potential solution, while performance and safety in real clinical workflows remain uncertain. OBJECTIVE: To compare the quality, understandability, ac…

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