Design and Implementation of An Automated Scheduler for Pharmacists in A Local Hospital
DOI:
https://doi.org/10.23055/ijietap.2026.33.4.10667Abstract
To deliver adequate healthcare to the community, it is crucial to lower expenses and enhance the working environments for healthcare professionals, such as nurses, doctors, and pharmacists. Traditionally, pharmacists were not considered a significant component of the healthcare system, as their role primarily involved medication delivery. However, over the past few decades, the role of pharmacists has evolved significantly, making them a crucial and integral part of the healthcare staff due to their involvement in new missions. Consequently, the pharmacists' community must be considered within the broader healthcare system. Pharmacists now face new challenges, such as unbalanced workloads and burnout. This paper examines a case study involving pharmacists at a local hospital. Pharmacist scheduling was traditionally performed manually, a process that proved both time-consuming and error-prone. Moreover, the resulting schedules often failed to meet pharmacists’ preferences, leading to dissatisfaction. A decision support system (DSS) for optimizing pharmacist scheduling in a hospital is developed in this paper. This DSS aims to automatically and efficiently generate well-balanced schedules that satisfy the pharmacists as much as possible. Balancing workload, considering pharmacist preferences, and meeting daily coverage requirements are challenging tasks that are difficult to accomplish manually without the assistance of a computer. Therefore, a mathematical model, specifically a Mixed Integer Programming (MIP) model, was developed to generate an optimal schedule for pharmacists. This model considers individual pharmacists’ preferences, their ability to fulfill duties, workload balancing, and annual leave requirements. The model has been implemented, and a graphical user interface has been developed. This interface allows users to input the required number of pharmacists needed each month, the preferences and also allows automatic generation of the schedules. An experimental study was conducted to evaluate the proposed DSS's performance. As a result of the automated schedules, overtime has been eliminated completely, and pharmacists' preferences have been accommodated. The proposed DSS automates pharmacist scheduling while considering human preferences and fairness criteria, offering a practical tool for hospital administrators to enhance efficiency and staff satisfaction.
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