Queueing theory and simulation for reducing patient waiting time in emergency departments - Aminah, Aminah; Manalu, Harauly Lady Lusiana; Silaban, Verawaty Fitrinelda; Munthe, Dewi Sartika; Harahap, Rahmaini Fitri (Institute of Computer Science (IOCS), 2025)
Emergency Departments (EDs) are increasingly overwhelmed by rising patient volumes and limited service capacity, leading to long waiting times and reduced care quality. This study addresses the inefficiencies of conventional queue policies by proposing a dynamic scheduling approach known as the Accumulative Priority Queue with Finite Horizon (APQ-h). APQ-h integrates time-based priority accumulation with triage thresholds, allowing for a more realistic representation of how clinicians manage patient flow. Using discrete-event simulation and simulation-based optimization, the research calibrates accumulation rate parameters (β) to minimize total waiting time (TWT) and ensure compliance with clinical response time targets (APT). A real-world case study and sensitivity analysis reveal that optimal configurations of β enable balanced and adaptive queue management without disadvantaging any patient group. The findings contribute a hybrid queue discipline that bridges mathematical modeling and clinical practice, offering practical implications for improving ED throughput and resource utilization. Although the simulation relies on stylized assumptions, it opens avenues for real-time validation, integration with adaptive triage systems, and scalability across diverse healthcare settings.