Improving the performance of a medical imaging center through simulation and fuzzy DEA

Abstract

Given that various operational methods can be considered for a system, applying changes to study the results and determine the best operational technique is costly and disrupts the system. Thus, to analyze and evaluate the outcomes of employing different operational methods, simulation is utilized. In this study, to improve the performance of a medical imaging center (MIC), first, this center was simulated and then, different scenarios were defined and simulated. Subsequently, using the simulation results and for evaluating the scenarios through Data Envelopment Analysis (DEA), each scenario was considered as a decision making unit (DMU). Since simulation results of each scenario are uncertain and differ for different iterations, a method was utilized capable of using the results of all iterations. On the other hand, indexes such as satisfaction, patient’s appropriate waiting, helpful servicing with the least number nurses and the maximum number services that have fuzzy nature, are important factors for MIC. Therefore, using the simulation results and considering the system manager’s idea, a method was proposed for determining the fuzzy values of these indexes. Next, a ranking model and an algorithm were proposed for determining a unique ranking and introducing the best scenario to improve the performance of MIC.