Simulation modelling of a patient surge in an emergency department under disaster conditions


  • Muhammet Gul Yildiz Technical University
  • Ali Fuat Guneri Yildiz Technical University


The efficiency of emergency departments (EDs) in handling patient surges during disaster times using the available resources is very important. Many EDs require additional resources to overcome the bottlenecks in emergency systems. The assumption is that EDs consider the option of temporary staff dispatching, among other options, in order to respond to an increased demand or even the hiring temporarily non-hospital medical staff. Discrete event simulation (DES), a well-known simulation method and based on the idea of process modeling, is used for establishing ED operations and management related models. In this study, a DES model is developed to investigate and analyze an ED under normal conditions and an ED in a disaster scenario which takes into consideration an increased influx of disaster victims-patients. This will allow early preparedness of emergency departments in terms of physical and human resources. The studied ED is located in an earthquake zone in Istanbul. The report on Istanbul’s disaster preparedness presented by the Japan International Cooperation Agency (JICA) and Istanbul Metropolitan Municipality (IMM), asserts that the district where the ED is located is estimated to have the highest injury rate. Based on real case study information, the study aims to suggest a model on pre-planning of ED resources for disasters. The results indicate that in times of a possible disaster, when the percentage of red patient arrivals exceeds 20% of total patient arrivals, the number of red area nurses and the available space for red area patients will be insufficient for the department to operate effectively. A methodological improvement presented a different distribution function that was tested for service time of the treatment areas. The conclusion is that the Weibull distribution function used in service process of injection room fits the model better than the Gamma distribution function.


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