Proceedings of the 5 th NA International Conference on Industrial Engineering and Operations Management Detroit, Michigan, USA, August 10 - 14, 2020 © IEOM Society International Modelling and Optimizing Hospital Emergency Department Workflow Ichraq Mohammed Ouhmidou, Ghaida Qadim Bait Kulaib, and Emad Summad Department of Mechanical and Industrial Engineering Sultan Qaboos University Muscat, Oman s117436@student.squ.edu.om, s116470@student.squ.edu.om, esummad@squ.edu.om Abstract Emergency department (ED) is a complex system that falls under the category of acute healthcare institutions where health services are provided intensively regardless of the unknowingness of the severity of the medical cases and their spontaneous arrivals. Accordingly, developing a simulation model that exhibits the incurred interactions in ED will lend a hand in supporting the management of the ED in dealing with all those uncertainties. The model performs as a decision-making tool addressing the randomness nature of such an environment. Agent-based modeling simulation was preferred to model the interaction of ED elements using a computer language called Netlogo. And this selection was agreed upon after considering several literature reviews. The ED of Sultan Qaboos University Hospital was monitored, and the medical staff was also interviewed too to gain the required information to build up the model. A conceptual model of the ED was formulated Then, a simulation model was developed. Keywords Emergency department, Agent-based modeling, Patients flow, Overall performance 1. Introduction Emergency department is one of the main components of the healthcare system since it is providing non-stop services during 24 hours per day to patients with different needs. Moreover, the efficiency of this department has a major impact on the entire system (Liu, Z., et al., 2014). Overcrowding in ED has been intensively investigated in the past decade as an international problem. This issue has significant consequences on medical staff, patients as well on the whole hospital (Vanbrabant, L., et al., 2019). Furthermore, this is also considered to be a challenge to hospital managers and decision-makers because of the limited budget and resources. In order to reduce the congestion in ED without affecting patients’ lives, an optimum planning of resources is required to ensure an efficient control of the entire system through finding the best way to allocate those available resources. However, analyzing such complex system is not an effortless thing due to the randomness and the presence of several random variables such as patients’ arrival and interarrival times. Over and above that, the time to diagnose patients and identify their proper medical care 2964