Optimizing experimental simulation design for the emergency departments - (:unkn) unknown (ASSOC BRASILEIRA ENGENHARIA PRODUCAO-ABEPRO, 2020)
Goal: this research aims to use the experimental simulation method is to obtain the optimum results by using the simulation technique of the models which are modeled mathematically but not solved. Design/Methodology/Approach: a case study was conducted to apply discrete-event simulation (DES) approach based on design of experiment (DOE) technique to derive strategies and analyze situations in an emergency department (ED). Results: by integrating the DOE approach with the DES technique for the ED, the average waiting time of a patient in a small ED was reduced from 40.09 minutes to 9.83 minutes (75.48%), resulting in a significant result. The number of patients treated was increased from 132 to 147 (11.37%) by increasing the capacity of resources without increasing the number of resources for ED in daily. Additionally, optimum the numbers of resources of the healthcare were calculated to employ in EDs. Limitations of the investigation: there is no shift system for the resources of healthcare in the DES model. Since the ED was considered in this study, the same number of resources were run during the working hours of the DES model. Practical implications: for researches and healthcare professionals, the developed method is used to provide the possibility of obtaining the results which cannot be obtained by mathematical modeling of the healthcare problems. The results of the changes made in health resources on the outputs are obtained by this method as the shortest and lowest cost. Originality/Value: there is almost no detailed study of DES with DOE. Providing high reliability has resulted for the optimum values by integrating the DOE approach with the DES technique in healthcare area. It is very difficult to get accurate results everywhere where the human factor is.
Keywords: Discrete-event Simulation; Design of Experiment; Emergency Department; Resources of Healthcare; HEALTH-CARE; OPTIMIZATION; UNIT