Analysis of Emergency Department Queue System Performance: Simulation Approach Based on Experiment Design
Background: Simulation is an appropriate technique for analyzing and evaluating the dynamic behavior of complex systems. The present study aimed to develop an integrated model using a simulation approach based on designing experiments to analyze performance of the admission queue system of patients, who referred to the emergency department of the Modarres hospital.
Methods: In this descriptive-analytical research, effective variables on resource efficiency empowerment were identified and analyzed using inferential statistics and one-way ANOVA. Later, effects of the effective factors were estimated. Furthermore, performance of the emergency department system was simulated using the Visual Paradigm software. Results obtained from implementation of the simulation model were used as input for designing an experiment. A fully factorial 2-level experiment design was also used with central points. The independent variables studied in the simulation model included practical nurse, emergency secretary, nurse, cardiologist, and hospital bed. The dependent variable was the patients' waiting queue in the studied emergency department.
Results: According to , the acceptable effects were determined based on the results of variance analysis for the model. The value of indicated that 82.35% of the model explains all variability of the response-level data around the mean. Therefore, it can be concluded that the design space was in accordance with the estimated model based on the results of variance analysis.
Conclusion: In the present study, performance analysis of the emergency department queue system was conducted using simulation and experiment design. The nonlinear regression model was able to predict the queue length. Moreover, this model can be used to predict dependent variables considering acceptable factors. According to the results, minimum length of the queue is obtained when the number of emergency secretaries is at a high level and the number of practical nurses and nurses is at a low level.