Generative AI for Establishing the Chief Complaint

Establishing the chief complaint requires identifying the patient’s main symptoms or concerns. This information is essential for triage and subsequent clinical assessment. However, patients may struggle to describe their symptoms or leave important concerns unspoken. Also, clinicians have limited time to ask further questions during intake. Generative AI could help by asking patients what is troubling them, when their symptoms began, and what other concerns they have. It could prepare a short summary for patients to correct and clinicians to review. Clinical studies of AI-assisted intake have reported shorter physician consultations and more complete recorded histories. These findings do not show whether AI helps clinicians establish the chief complaint more accurately. We propose an evaluation framework centered on the proportion of patients whose main symptoms or concerns are missing or incorrectly described after AI-assisted intake. Studies should compare what patients wanted to discuss with what the AI agent asked about and included in its summary. They should also examine whether concerns requiring urgent assessment were missed. The clinical goal is a clear description of the patient’s main symptoms and concerns that helps clinicians judge urgency and decide what needs attention.

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Publication Details

Journal
Journal of Clinical Medicine
Published
2026-10-13
DOI
https://doi.org/10.3390/jcm15207912
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Generative AI for Establishing the Chief Complaint

Vera Sorin, Eyal Klang
Journal of Clinical Medicine
Artificial Intelligence in Healthcare and Education
article

Generative AI for Establishing the Chief Complaint

Vera Sorin, Eyal Klang
article en

Abstract

Establishing the chief complaint requires identifying the patient’s main symptoms or concerns. This information is essential for triage and subsequent clinical assessment. However, patients may struggle to describe their symptoms or leave important concerns unspoken. Also, clinicians have limited time to ask further questions during intake. Generative AI could help by asking patients what is troubling them, when their symptoms began, and what other concerns they have. It could prepare a short summary for patients to correct and clinicians to review. Clinical studies of AI-assisted intake have reported shorter physician consultations and more complete recorded histories. These findings do not show whether AI helps clinicians establish the chief complaint more accurately. We propose an evaluation framework centered on the proportion of patients whose main symptoms or concerns are missing or incorrectly described after AI-assisted intake. Studies should compare what patients wanted to discuss with what the AI agent asked about and included in its summary. They should also examine whether concerns requiring urgent assessment were missed. The clinical goal is a clear description of the patient’s main symptoms and concerns that helps clinicians judge urgency and decide what needs attention.

Journal of Clinical MedicineVol. 15(20)
Beth Israel Deaconess Medical Center (US), Mayo Clinic (US), Harvard University (US)
Openalex Percentile: Top 20%
Artificial Intelligence in Healthcare and Education
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