• Rick Kye Gan, Jude Chukwuebuka Ogbodo, Yong Zheng Wee, Ann Zee Gan, and GonzálezPedro ArcosPAUnit for Research in Emergency and Disaster, Faculty of Medicine and Health Sciences, University of Oviedo, Oviedo 33006, Spain..
• Unit for Research in Emergency and Disaster, Faculty of Medicine and Health Sciences, University of Oviedo, Oviedo 33006, Spain. Electronic address: ganrick@uniovi.es.
• Am J Emerg Med. 2024 Jan 1; 75: 727872-78.

AimThe objective of our research is to evaluate and compare the performance of ChatGPT, Google Bard, and medical students in performing START triage during mass casualty situations.MethodWe conducted a cross-sectional analysis to compare ChatGPT, Google Bard, and medical students in mass casualty incident (MCI) triage using the Simple Triage And Rapid Treatment (START) method. A validated questionnaire with 15 diverse MCI scenarios was used to assess triage accuracy and content analysis in four categories: "Walking wounded," "Respiration," "Perfusion," and "Mental Status." Statistical analysis compared the results.ResultGoogle Bard demonstrated a notably higher accuracy of 60%, while ChatGPT achieved an accuracy of 26.67% (p = 0.002). Comparatively, medical students performed at an accuracy rate of 64.3% in a previous study. However, there was no significant difference observed between Google Bard and medical students (p = 0.211). Qualitative content analysis of 'walking-wounded', 'respiration', 'perfusion', and 'mental status' indicated that Google Bard outperformed ChatGPT.ConclusionGoogle Bard was found to be superior to ChatGPT in correctly performing mass casualty incident triage. Google Bard achieved an accuracy of 60%, while chatGPT only achieved an accuracy of 26.67%. This difference was statistically significant (p = 0.002).Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

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