AI-Driven Pain Assessment and Departmental Triage in Healthcare Systems

Abstract

Accurate pain assessment and timely triage are essential in high-volume clinical care, yet traditional methods relying on self-reporting and manual judgment are prone to delays and inconsistency. This study evaluates an AI-based system integrating facial expression analysis, physiological biosignals, and natural language processing for pain detection and automated triage. Thirty patients were assessed, with AI-derived scores showing strong correlation with Visual Analog Scale ratings (r = 0.87) and triage accuracy of 90%. Decision-making time was reduced to 19 seconds per case versus 6.4 minutes manually. Findings demonstrate the feasibility of AI-assisted pain management, improving efficiency, accuracy, and consistency. Recommendations include scaling, integration into hospital systems, and ethical deployment, highlighting AI’s transformative potential in healthcare delivery.