Why do users override alerts? Utilizing large language model to summarize comments and optimize clinical decision support

Siru Liu, Allison B. McCoy, Aileen P. Wright, Scott D. Nelson, Sean S Huang, Hasan B. Ahmad, Stefano Carro, Jacob Franklin et al.

Journal of the American Medical Informatics Association 2024 article cited by 35

importance 4/10 ai assisted Artificial Intelligence in Healthcare and Education clinical decision support stage: research proprietary model

Understanding why clinicians override CDS alerts required summarizing large volumes of user alert comments.

Alert overrides and poorly designed alerts can cause clinicians to ignore safety warnings.

GPT-4 independently summarized alert comments, and five CDS experts rated AI-generated versus physician-generated summaries on clarity, completeness, accuracy, and usefulness.

Among the top 8 rated summaries, five were GPT-4-generated; AI summaries showed high clarity, accuracy, and usefulness.

AI summaries were rated comparably to physician summaries by CDS experts in this study.

Venue Journal of the American Medical Informatics Association
Published 2024
Work type article
Authors Siru Liu, Allison B. McCoy, Aileen P. Wright, Scott D. Nelson, Sean S Huang, Hasan B. Ahmad, Stefano Carro, Jacob Franklin et al.
Citations 35 (OpenAlex, at import time)
References 21
Model or method GPT-4
Organization Vanderbilt University Medical Center
Primary source https://doi.org/10.1093/jamia/ocae041
Open access hybrid
Keywords GPT-4, alert override, clinical decision support, summarization
4 / 10

real but narrower advance

Alert overrides and poorly designed alerts can cause clinicians to ignore safety warnings; study covers one medical center and 8 alerts, a real but narrow patient-safety advance.

Basis: inferred. Judged from the source text, which gives no explicit scale. Stated scale: not stated in source. Method and limits.

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