Predicting the Impact of Mobile Field Hospital Deployment in Reducing Patients Mean Wait Times in Emergency Departments: An Agent-Based Simulation Approach

Abstract Mean wait time (MWT) in emergency departments refer to the average time patients spend undergoing evaluation, or treatment at each stage, which can be significantly affected by sudden onsets of a disaster. Agent-based modeling (ABM) is a computational technique that simulates the interactions and behaviors of individual agents in a defined environment and enables the study of complex systems by observing the emergent outcomes of agent-agent and agent-environment interactions. This study examines the capability of ABMs in assessing the impact of response operations on hospital emergency departments mean wait time in a post-explosion scenario for an oil and gas industry. The methodology of this study involves the use of an agent-based modelling and simulation tool (NetLogo 6.3.0) to represent the interaction of agents within an emergency response system defined by rules, goals and decision protocols. The response policy includes both a traditional approach and a collaborative intervention through the use of a mobile field hospital (MFH). The dataset was generated, sampled and analyzed using the BehaviorSpace and Pandas tools, respectively. The results of the simulation study show that the strategic use of MFH for a collaborative response resulted in lower MWT, indicating higher effectiveness and efficiency of response efforts. This study highlights the need to generate potential results and test how response strategies might influence emergency department wait times and demonstrates the capability of simulation techniques in modeling complex systems. This could serve as an important tool for training health workers and disaster managers on emergency response and preparedness.