Healthcare simulation modeling and optimization using MedModel
Proceedings of the 30th conference on Winter simulation
Birth of a new maternity process
Proceedings of the 30th conference on Winter simulation
Emergency department simulation and determination of optimal attending physician staffing schedules
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 2
Introduction to Simulation Using SIMAN
Introduction to Simulation Using SIMAN
Healthcare I: a discrete-event simulation application for clinics serving the poor
Proceedings of the 33nd conference on Winter simulation
The use of simulation for process improvement at an ambulatory surgery center
Proceedings of the 33nd conference on Winter simulation
Simulation with Arena
Simulation analysis of an outpatient department of internal medicine in a university hospital
Proceedings of the 38th conference on Winter simulation
Optimizing staffing schedule in light of patient satisfaction for the whole outpatient hospital ward
Proceedings of the 40th Conference on Winter Simulation
An application of discrete-event simulation to an outpatient healthcare clinic with batch arrivals
Proceedings of the Winter Simulation Conference
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The health service center is considering modification of the current doctor schedule to decrease the average time patients spend in the facility. A new schedule, which on average has an extra doctor added for each time slot, has been suggested by the preliminary queueing analysis. It is anticipated that the schedule will improve the system performance but has yet to be verified by a discrete event simulation model. The shifting bottleneck issue has to be considered as well. Increasing the resource capacity of the current bottleneck (believed to be the doctor resource) might trigger a new bottleneck and could possibly worsen the current situation. In this study, the current and proposed doctor schedules are tested on the simulation model created using SIMAN language and simulated on Arena. The output from the simulation just verifies the preliminary queueing analysis that the proposed schedule decreases the average time patients spend in the facility. Sensitivity analysis is performed as well, and the next bottleneck resource is identified.