Introduction
Emergency departments (EDs) often experience overcrowding due to unpredictable surges in patient demand. This congestion leads to longer waiting times, resource shortages, and decreased quality of care. Understanding the resilience of EDs—their ability to resist and recover from surges—is crucial for improving healthcare efficiency.
Therefore, the researchers developed an AnyLogic healthcare simulation model using discrete-event simulation to analyze an ED's resilience under demand surges. The model evaluates patient flow, resource utilization, and the impact of interventions such as increasing medical staff or bed availability.
Simulation model
The AnyLogic-based healthcare simulation model replicates the patient journey from arrival to discharge, capturing resource constraints and treatment delays. The model incorporates triage and patient prioritization based on urgency, resource allocation, including doctors, nurses, and available beds. It also includes variability in patient arrival rates for both normal and surge conditions and tracking key performance metrics such as waiting times, bed occupancy rates, and system recoverability.
To verify the model, face-to-face verification sessions were conducted with medical personnel from a UAE hospital. These sessions involved detailed discussions and evaluations of the model’s representation of the ED patient flow to ensure that it accurately captured the key operational aspects.
To quantify resilience, the resilience triangle framework was applied, measuring the ED’s ability to handle surges (resistance) and the time required to return to normal operations (recoverability). This healthcare simulation approach provides a detailed representation of how patient flow and resource availability impact system performance under varying demand scenarios.
Read also: Explore additional resources on healthcare simulation.
Results
The healthcare simulation model revealed that under normal conditions, the ED maintains stable patient flow and resource utilization. However, during demand surges, waiting times increased by 60%, and bed occupancy reached critical levels, leading to delays in patient care.
To improve resilience, three intervention scenarios were tested:
- Adding 25% more physicians reduced waiting times by 18% but had minimal impact on bed occupancy.
- Increasing nursing staff by 25% improved throughput by 12% but did not significantly affect surge recoverability.
- Expanding bed capacity by 25% provided the highest improvement, reducing system overload and recovery time by 30%.
These results highlight that increasing bed capacity is the most effective strategy for improving ED resilience, while adding medical staff provides moderate benefits.
The AnyLogic-based healthcare simulation model offered a powerful tool for ED managers to evaluate resilience strategies under different demand conditions. Future research will assess cross-training strategies in emergency departments.