Discrete Event Simulation and Data Envelopment Analysis to Improve the Performance of Hospital Emergency Department

Abstract

Objective: This study applies a discrete event simulation to improve the performance of hospital emergency department in order to reduce the waiting time for patients and optimize the resources. Methods: First, a simulation model is developed based on flow of patients in an emergency department using ARENA software; then, the simulation model is run 180 times for any feasible scenario including some physicians, emergency medicine specialists, nurses, acute phase cure unit, injection unit, supervised ward, and ICU unit. In the next step, two data envelopment analysis methods are used for ranking the scenarios. Results: Ranking of DEA methods showed that the scenario number 39 is the best choice in both methods. Non-parametric Spearman-Row and Kendal-Tau tests were used to determine the correlation among the results of ranking methods. The results of the two tests (0.93 and 0.81, respectively) indicated a significant correlation among DEA ranking methods. Conclusion: The results of case study showed that the scenario 39 is the best scenario among all the 44 feasible scenarios defined in both DEA methods; that is, there should be 2 general physicians, 1 emergency medicine specialist, 16 nurses in the supervised ward, 5 nurses in the acute care unit, 2 beds in the injection room, 22 beds in the supervised ward and 16 beds in the acute care unit.

Keywords

• discrete event simulation
• data envelopment analysis
• hospital emergency
• patient waiting time
• nonparametric correlation tests