|Title||An Analytical Model to Evaluate the Response Capacity of Emergency Departments in Extreme Situations|
|Publication Type||Conference Proceedings|
|Year of Conference||2015|
|Authors||Bruballa, E, Taboada, M, Wong, A, Rexachs, D, Luque, E|
|Conference Name||The Seventh International Conference on Advances in System Simulation (SIMUL 2015)|
|Conference Location||Barcelona, Spain|
|Keywords||Agent-Based Modeling and Simulation (ABMS), Decision Support Systems (DSS), Emergency Department (ED), Emergency Response Capacity, Knowledge Discovery|
One of the most important current problems in the healthcare system is the saturation of Emergency Departments, due to the increasing demand of the service. Healthcare staff often has no margin to absorb the demand in case of an unexpected increase of patients entering the service caused by an emergency. We aim to evaluate the response capacity of an Emergency Department, specifically of doctors, nurses and specialist technicians that make up a specific sanitary staff configuration, facing an unexpected emergency. Such situations cannot be tested in the real system and simulation is the only way to obtain data about them. We present an analytical model to obtain information from data obtained through the simulation of a Hospital Emergency Department. The model defines how to calculate the theoretical throughput of a particular sanitary staff configuration, that is, the number of patients it can attend per unit time given its composition. This index is a reference in order to measure the emergency response capacity of the system and also other indicators concerning to performance. The data for the analysis will be generated by the simulation of any possible scenario of the real system, taking into account all valid sanitary staff configurations and different number of patients entering into the emergency service. The designed model offers the availability of relevant knowledge to the managers of the service to make decisions concerning the composition of the sanitary staff configuration in anticipation of extraordinary situations.