Mean wait time (MWT) in emergency departments refer to the average time patients spend undergoingevaluation, or treatment at each stage, which can be significantly affected by sudden onsets of adisaster. Agent-based modelling (ABM) is a computational technique that simulates the interactions andbehaviours of individual agents in a defined environment and enables the study of complex systems byobserving the emergent outcomes of agent-agent and agent-environment interactions. This studyexamines the capability of ABMs in assessing the impact of response operations on hospital emergencydepartments mean wait time in a post-explosion scenario for an oil and gas industry. The methodologyof this study involves the use of an agent-based modelling and simulation tool (NetLogo 6.3.0) torepresent the interaction of agents within an emergency response system defined by rules, goals anddecision protocols. The response policy includes both a traditional approach and a collaborativeintervention through the use of a mobile field hospital (MFH). The dataset was generated, sampled andanalysed using the BehaviorSpace and Pandas tools, respectively. The results of the simulation studyshow that the strategic use of MFH for a collaborative response resulted in lower MWT, indicating highereffectiveness and efficiency of response efforts. This study highlights the need to generate potentialresults and test how response strategies might influence emergency department wait times anddemonstrates the capability of simulation techniques in modelling complex systems. This could serveas an important tool for training health workers and disaster managers on emergency response and preparedness