Document Type : Original Article(s)
Authors
1
Oral and Dental Diseases Research Center, Kerman University of Medical Sciences, Kerman, Iran.
2
Research Center for Prevention of Oral and Dental Diseases, Baqiyatallah University of Medical Sciences, Tehran, Iran
3
Health Management Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran.
4
Research Center for Prevention of Oral and Dental Diseases, Baqiyatallah University of Medical Sciences, Tehran, Iran.
5
Leishmaniasis Research Center, Kerman University of Medical Sciences, Kerman, Iran.
6
Department of Periodontics, Dental Faculty, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
7
Department of Endodontics, Dental faculty, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
Abstract
Abstract
Background: Patient waiting time is an important factor in the management of the health sector. This study aimed to develop a suitable queuing theory and simulation technique to optimize dental hospital management.
Methods: A descriptive-analytical study was performed in a dental hospital in Tehran, Iran. A sample of 3364 patients referred to the hospital was selected to calculate the patient flow and queuing system performance. After an initial data assessment, the dental hospital queuing system performance indicators were calculated for two shifts. The queuing system of the current situation
was modeled using ARENA software, and two scenarios were examined.
Results: The average number of patients waiting in the queuing system was 38 and 17 in the morning and evening, respectively. The average time patients spend waiting in the system was 110 and 49 minutes in the morning and evening, respectively. The two scenarios, based on the simulated queuing network model, showed that in the first scenario, by using two nurses (one male and one female) as triage clerks for filing requests, one clerk for managing financial records, and one information desk secretary, the average queue length and waiting time were reduced to 0.02 patients and 4 minutes, respectively. In the second scenario, by using two nurses (one male and one female) as triage clerks for filing requests and two secretaries (one male and one female) for financial record management and registration, the average queue length and the waiting time in triage were reduced to 0.03 people and 5 minutes, respectively.
Conclusion: Based on the results, using queuing theory and simulation techniques can improve the queuing status of health centers without any changes in the number of staff and only by implementing a suitable rearrangement in staff duties, establishing parallel service lines in busy service-providing centers, and using nurses able to multitask.
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