Telemedicine and AI-Based Triage: Optimizing Emergency Care Delivery in Rural Healthcare Centers

Abstract

Rural healthcare centers face significant challenges in providing timely, accurate emergency care due to staffing shortages, lack of specialists, and geographical barriers. Integrating telemedicine with AI-based triage systems can potentially address these challenges. This study evaluated the impact of AI-assisted telemedicine on emergency care delivery in three rural hospitals in Pakistan. A total of 400 healthcare professionals, including physicians, nurses, and allied health staff, participated. Key outcomes included triage accuracy, patient throughput, and workflow efficiency. Data were collected pre- and post-intervention over six months and analyzed using descriptive statistics, paired t-tests, and partial least squares structural equation modeling (PLS-SEM). Results indicated significant improvements in triage accuracy (72.5% → 89.7%), reduced length-of-stay (mean −22.4%), and enhanced workflow efficiency. Operational challenges moderated these effects. Findings underscore the feasibility and effectiveness of AI-assisted telemedicine in rural EDs, while emphasizing the importance of infrastructure, staff training, and ethical oversight.