OPTIMIZING EXPERIMENTAL SIMULATION DESIGN FOR THE EMERGENCY DEPARTMENTS

• Autor(a) principal: Atalan, Abdulkadir
• Data de Publicação: 2020
• Outros Autores: Dönmez, Cem Cagri
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Brazilian Journal of Operations & Production Management (Online)
• Texto Completo: https://bjopm.org.br/bjopm/article/view/854
• topic: Discrete-event Simulation; Design of Experiment; Emergency Department; Resources of Healthcare

Goal: this study aimed to use the experimental simulation method 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 the discrete-event simulation (DES) approach based on the 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 for a patient in a small ED was reduced from 40.09 minutes to 9.83 minutes (75.48%), which is a significant result. Increasing the capacity of the resources without increasing the number of daily resources for the ED resulted in an increase from 133 to 147 (10.53%) in the number of patients treated. Additionally, the optimum number of healthcare resources to employ in EDs was calculated. Limitations: there is no shift system for healthcare resources in the DES model. Since the ED was considered in this study, the same number of resources was run during the working hours of the DES model. Practical implications: for researchers and healthcare professionals, the developed method is used to obtain results that cannot be obtained through the mathematical modeling of healthcare problems. The results of the changes in health resources on the outputs are obtained by this method as the shortest time frame and lowest cost. Originality/Value: there is almost no detailed study of DES with the DOE technique. Providing high reliability has resulted in obtaining optimum values through the integration of the DOE approach with the DES technique in the healthcare area. It is very difficult to get accurate results anywhere where the human factor is present.