Simulation of Discharging System with Personal Decision in Khatam Al-Anbia Hospital, Tehran, Iran

One of the major indicators for evaluating the quality of services in medical centers is the waiting time for patients. If the treatment process is prolonged, it can give rise the patients to leave the system before the end of the treatment process and with personal consent. The purpose of this research was to evaluate the service process of a treatment center and improve the treatment process through discrete-event simulation to reduce patient waiting time and reduce the number of patients with discharging by personal satisfaction despite the doctor's advice (DAMA: Discharged against Medical Advice).

This was a descriptive study involving patients referred to Khatam Al-Anbia hospital in Tehran, Iran, in the fall of 2018. Data collection tools were as questionnaires, and face-to-face and telephone interviews with experts and researchers. Content for data collection formats included the patient's arrival time, and the start and end time of receiving services in various departments and units. In the next step, the data were modeled, different scenarios were analyzed, and the best scenario was selected from them.

In the seven proposed studied scenarios, the seventh scenario, which was a combination of the other six proposed scenarios, improved the treatment system. In this scenario, it was observed that the cost of value added with a slight increase from 399807373 in the initial model to 401561100 in the seventh scenario, with a significant decrease in the waiting cost from 2494256 currency units in the initial model to 16472202 currency units in the seventh scenario. Other proposed scenarios were more effective in reducing the total cost, from 649228933 monetary units in the initial model to 418033302 monetary units in the seventh scenario, which ultimately led to proper classification of workflow and improvement of performance indicators studied.

The results reveal that by changing the resources and beds allocated to patients (optimal amount), it is possible to provide better services to patients, eliminate their dissatisfaction, and reduce the number of DAMA patients, waiting time of patients, and the losses in the service process.