Optimal Pharmaceutical Replenishment Policy: The Case of Selected Health Centers in Addis Ababa
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Date
2023
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Addis Ababa University
Abstract
Background: The primary goal of inventory management is to establish a replenishment policy
that informs when and how much to order and how to maintain an appropriate stock level while
optimizing various tradeoffs, such as carrying and re-ordering costs. The need for the healthcare
sector to reduce costs has motivated many hospitals to adopt new technology to enhance existing
operations. Since 2009, Integrated Pharmaceuticals Logistics System (IPLS) has been used in
Ethiopian public health facilities to manage inventory. To the investigator's knowledge, the
optimality of the replenishment system to the respective health facilities was not well investigated.
Objectives: This study aimed to determine an optimal replenishment policy for managing inventory
for selected health centers in Addis Ababa, Ethiopia.
Methods: A multiple case study design was used in ten selected health centers. This study primarily
uses quantitative data from the pharmacy stores’ database system. Three years of data were
extracted from the digital bin card and entered into the pre-tested excel-data extraction tool. Once
the data was sufficiently cleaned, a descriptive statistic and correlation using Microsoft Excel
2019 and IBM SPSS version 26. A simulation-optimization approach was used to show the current
total inventory cost and develop an optimal replenishment policy.
Result: The monetary amount of the program medicines issued from the health centers within three
years was 93,922,330.05 ETB, in which Anti-retroviral treatments took the highest percentage,
78.69%, followed by Mother and child health products, 10.8%. When the demand frequency is
observed, there is zero demand 50% of the time; this shows high intermittent demand. Demand
variability significantly correlates (𝑟 = 0.84) with the health centers' total cost. The lowest total
cost was observed in the replenishment policy of every other month with a target customer service
level of 90% and realized customer service level of 92.7%. The highest total cost was observed
in the replenishment policy of every month with target customer service level of 99% with a total
cost of 141,706.4 ETB with realized customer service level of 99.4%.
Conclusion: The analysis showed the segregation of products based on their characteristics has
a potential advantage since the demand pattern significantly varies among products. The study
showed the current IPLS method of determining order up to level resulted in less customer service
level and increased the likelihood of overstock. Based on the simulation-optimization model, the
less costly replenishment model is 90% target customer service level and every other month
replenishment, but it is important to set a target service level based on product characteristics and
integrate segregation of products, including the price and demand variability to achieve the
optimal replenishment.
Recommendation: Health centers may integrate characteristics of products, financial parameters,
longer historical data and standard deviation of demand to identify order quantity and review
period. The findings from this study can be used to commence further investigation in the fitness
of IPLS inventory control system by considering other alternatives with technical and financial
feasibility.
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Keywords
Replenishment, Inventory, Optimization, Pharmaceutical, Health Center