What question did this study set out to answer?

The study aims to validate the effectiveness of ChatGPT-4o in detecting surgical site infections (SSI) using electronic health records (EHR).

April 14, 2026International Journal of Infectious Diseases0 citationsOpen Access

Validation of ChatGPT-4o for detecting surgical site infections after colorectal surgery from electronic health records: a large-scale diagnostic accuracy study.

DCDaniel Casanova-Portolés JBJosep M Badia CFCarlos García Forero

Key Points

The study aims to validate the effectiveness of ChatGPT-4o in detecting surgical site infections (SSI) using electronic health records (EHR).
Analyzed EHR narratives to identify surgical site infections post-colorectal surgery.
Evaluated the diagnostic performance metrics including sensitivity and specificity.
Compared performance for different types of SSI: overall, deep incisional, and organ/space SSI.
Overall SSI detection sensitivity was moderate at 21.1%, with high specificity at 98.7%.
Deep incisional SSI sensitivity was also low at 20%, with high specificity at 99.7%.
Organ/space SSI detection showed improved sensitivity at 85.9% and specificity at 84.6%.

Abstract

and deep incisional SSI, sensitivities were low (21.1% and 20%) despite high specificities (98.7% and 99.7%), whereas performance for organ/space SSI was similar to overall SSI (sensitivity 85.9%, specificity 84.6%).Conclusions: Under routine-prevalence conditions, ChatGPT-4o-based analysis of narrative EHR demonstrated good detection of overall SSI and organ/space-SSI, and a high ability to rule out SSI.These findings support its use as a screening layer within semiautomated surveillance workflows.Reliable detection of incisional SSI remains limited and may require improved documentation signals and/or integration of structured data sources.ClinicalTrials.gov

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