Volume : 13, Issue : 09, September – 2026
Title:
ARTIFICIAL INTELLIGENCE–DRIVEN TRIAGE IN MASS-CASUALTY INCIDENTS: A NARRATIVE REVIEW OF ETHICAL, CLINICAL, AND OPERATIONAL CONSIDERATION
Authors :
Hadi Abbas Ahmed Zamkah, Mansour Abdulghani Abdullah AlZahrani, Jaber Yahya Jaber Albarqi, Abdulaziz Abdullah Hamed Alghamdi, Mohammed Hassan Esmat, Saif Abdulhamid Alsulami, Hussam Hassan Ali Bagash, Abdulrahman Saleh Abdu Alharbi, Isamil Abdulmatlob Hamadi Aljedani, Abdullah Abdulmughni Abdulghani Alshaikh
Abstract :
Background: Mass-casualty incidents (MCIs) create a critical mismatch between patient volume and available resources, forcing rapid triage decisions under extreme pressure. Artificial intelligence (AI) has emerged as a promising adjunct to traditional triage protocols, yet ethical, clinical, and operational implications remain incompletely understood.
Objective: This narrative review synthesized evidence on the ethical, clinical, and operational considerations of AI-driven triage in MCIs.
Methods: Following PRISMA 2020 guidelines, a systematic search of PubMed/MEDLINE, Scopus, Embase, CINAHL, IEEE Xplore, and Web of Science was conducted for studies published between 2015 and 2026. Two reviewers independently screened records, extracted data, and assessed quality using RoB 2, JBI tools, and the Newcastle–Ottawa Scale. Narrative synthesis was performed.
Results: Of 2,630 records, 19 studies met inclusion criteria. AI-driven triage showed variable accuracy, with multimodal Bayesian networks improving triage accuracy from 14% to 53%, while large language models demonstrated inconsistent performance (26.67%–63.9%). Ethical concerns regarding algorithmic bias, accountability, and automation bias remain largely unresolved. Operational barriers, including infrastructure limitations, training deficits, and poor workflow integration, remain the rate-limiting factors for real-world deployment. No studies assessed transfer to clinical practice or patient outcomes.
Conclusions: AI-driven triage remains promising but immature. It should be positioned as a decision-support tool rather than an autonomous agent, with rigorous validation, equity-focused design, and robust governance frameworks.
Keywords: artificial intelligence; mass-casualty incidents; triage; disaster medicine; medical ethics
Cite This Article:
Please cite this article in press Hadi Abbas Ahmed Zamkah et al., Artificial Intelligence–Driven Triage In Mass-Casualty Incidents: A Narrative Review Of Ethical, Clinical, And Operational Consideration..,. Indo Am. J. P. Sci, 2026; 13(09).
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