Development of a Discrete Event Simulation Model to Minimize the Waiting Time of Patients in Hospitals

Gholam Reza Jamali, Payam Farhadi, Elham Behbudi


Introduction: Proper management of health systems requires the use of a suitable decision making logic. Simulation is a good tool for accurate and evidence-based decision making. The main objective of this study was to developing a simulation model to minimize the waiting time of patients in the cardiac subspecality clinic of Kowsar Hospital.

Methods: This is a cross-sectional study. The statistical population consisted of 576 patients, referring to Kowsar cardiac clinic in the morning and afternoon shifts. Data collection was conducted according to a designed timetable form. Scenarios were defined to receive the best answer. These scenarios were as follows: scenario A: decrease of the average of the service time; scenario B: increase of the mean time between the two entries; and scenario C: decrease of the service time and increase of the time between two entries. ARENA software was used to simulate and review the scenarios and General Algebraic Modeling System (GAMS) softwarewas used to obtain a definite answer.

Results: Simulation results showed that in scenario A the mean time spent in the system was 85.55 minutes in the morning and 77.05 minutes in the evening shifts. In scenario B, the average time spent in the system was 65.95 minutes in the morning and 79.63 in the evening shifts. In scenario C, the mean time spent in the system was 73.90 minutes in the morning and 61.17 minutes in the evening shifts. The result of the final model showed that the average time spent in the system was 97.33 min in the morning and 86.85 min in the evening.

Conclusion: According to the results obtained from the use of the definitive and simulated models, it was found that the simulation model, due to its probability, faces a percentage of error. Comparison of the definitive and simulated models revealed that the best scenario to the definitive answer was scenario B (increasing the mean time between the two logs).

Keywords: Clinic, Waiting time, Queuing theory, Simulation

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