A Queuing Analysis of Medicines Registration System Performance in Ethiopian Food and Drug Authority

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Date

2023

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Addis Ababa University

Abstract

Background: The limited number of approved medicines and long waiting time for registration are the major challenges limiting the performance of the regulatory system in Ethiopia. Queue analysis is used for characterizing and estimating the queue process and operating variables of the system to alleviate the challenges related to target timelines. Objective: To assess the queuing performance of the registration system at the Ethiopian Food and Drug Authority (EFDA). Methods: A mixed sequential explanatory study design was used for the study. Quantitative data collection involved a review of applications submitted to the EFDA from July 8, 2019 to July 7, 2020. Basic operating characteristics of the registration system performance were executed using single queue multiple server model of the queuing analysis. In-depth interviews with purposively selected registration experts from the EFDA and private organizations were done for the qualitative data collection. Analysis of the interviews involved the thematic analysis approach. Results: Mean arrival rate of applications to the registration system (λ=10.99 services per day) was 23.74% higher than the mean effective service rate of the system (cμ=8.38 services/day). Basic system performance average operating characteristics of the system could not be estimated indicating that an infinite queue of applications built up over time and was hard to achieve any target timeline in EFDA’s current registration system. The qualitative study also showed that the system is being frequently challenged with backlogs. Conclusion: The study documented weak system performance with lengthy registration process. Appropriate measures to improve mean effective registration service rate should be introduced to meet international standards and the agreed citizen’s charter of 2016.

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Keywords

Queue analysis, service rate, arrival rate, utilization factor, system performance characteristics.

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