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Improving Emergency Response: A Comparative Analysis of Traditional vs Artificial Intelligence-assisted Triage
Husain Nadaf1, Mangesh V Jabade2, Khurshid Jamadar3
1Department of Medical Surgical Cardiothoracic Nursing, Symbiosis College of Nursing, Symbiosis International (Deemed University), Pune, Maharashtra, India.
Background And Aims:
This study compares traditional emergency department (ED) triage systems with artificial intelligence (AI)-assisted triage to assess their impact on time to treatment (TTT) and patient outcomes. Emergency departments (EDs) manage high patient volumes and time-critical decisions, necessitating efficient triage. Traditional methods such as the emergency severity index (ESI) and Manchester triage system (MTS) rely on human judgment and may introduce variability. Artificial intelligence (AI)-based systems use machine learning (ML) algorithms to analyze patient data in real time, offering the potential for faster and more consistent decisions.
Patients And Methods:
We conducted a single-center randomized controlled trial (RCT) in a high-volume tertiary hospital in Pune, India. One hundred and five patients were randomized to traditional triage (Group A) or AI-assisted triage (Group B). The primary outcome was TTT, defined as arrival at first medical intervention. Mean TTT was 31.02 minutes with AI vs 44.12 minutes with traditional triage (p < 0.001); variability was lower with AI (standard deviation 7.75 vs 11.69).
Results:
Intensive care unit (ICU) admission rates did not differ. Clinician ratings favored AI in terms of accuracy, workload reduction, and perceived impact. Multiple linear regression estimated an adjusted -13.1-minute effect of AI on TTT, independent of severity (p < 0.001).
Conclusion:
Artificial intelligence (AI)-assisted triage improves ED efficiency by reducing TTT without altering ICU admission rates.
How To Cite This Article:
Nadaf H, Jabade MV, Jamadar K, Jogdeo B, Jamdade V. Improving Emergency Response: A Comparative Analysis of Traditional vs Artificial Intelligence-assisted Triage Systems in Health Care and Their Impact. Indian J Crit Care Med 2025;29(11):925-929.
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