Using the queuing model to evaluate and predict optimum outpatient pharmacy dispensing service in Lagos University Teaching Hospital
Waheed A. Adeoye , Patrick O. Erah , Babafemi O. Macauley
1Department of Pharmacy (Drug Production / In-Patient), Lagos University Teaching Hospital, Idi – Araba, Lagos, Nigeria;
2Department of Clinical Pharmacy and Pharmacy Practice, Faculty of Pharmacy, University of Benin, Benin City, Nigeria;
3School of Health Information Management, Lagos University Teaching Hospital, Idi – Araba, Lagos, Nigeria
Corresponding author: Waheed A. Adeoye
E-mail: adeoyew@yahoo.com Phone: +2348037165058
ABSTRACT
Background: Waiting times for health services arise because capacity does not match demand or capacity or demand is not well managed. Queuing theory is a powerful operational research tool which assists managers to make vital decisions capable of optimizing the performance of a health system facility, minimize operational costs and enhance the satisfaction of all interest groups.
Objective: To simulate the queuing model in the outpatient pharmacy in order to evaluate its performance and to develop necessary strategies for optimizing dispensing service.
Methods: The study was carried out at the Pharmacy Unit of Family Medicine / General Outpatient Department (GOPD) of Lagos University Teaching Hospital employing workflow analysis and time study. A sample size of 123 Ambulatory Patients was studied and data were collected daily over a period of four weeks. Data analysis was done using SPSS version 10.0 to determine waiting time for prescription validation and assessment, payment, filling, collection and counselling. The queuing system in Pharmacy was then simulated to determine measures such as Service Utilization Factor, Average Queuing Time in the queue and in the system, Average number of patients in queue and in the system, Waiting cost and Service cost all of which are necessary for evaluating service delivery in the outpatient setting.
Results: The study revealed a total patient waiting time of 79.24 min with the process component accounting for 7.9 ± 5.58 min (9.97%) and delay component responsible for 71.34 ± 66.93 min (90.03%). It was established that optimal service delivery would be achieved with two service points requiring six pharmacists in the pharmacy unit. This arrangement is expected to give an 88.1% reduction in mean total patient waiting time and 50% deduction in total cost when compared with existing system.
Conclusion: Significant reduction in waiting time can be made by facilitating service delivery at the prescription validation and assessment point. The excessive waiting time contributed by delay components underscored the need to employ more pharmacists to improve on the service system. Service efficiency would be optimized by increasing the number of service points to two in order to minimize the total operating costs.
Keywords: Waiting time, Queuing model, Outpatient pharmacy, Optimizing dispensing service.