An Optimization Model for the Nurse Scheduling Problem Considering Workload Variance
DOI:
https://doi.org/10.31316/j.derivat.v11i3.6899Abstract
The Nurse Scheduling Problem (NSP) is a critical issue in healthcare management, involving the assignment of nurses to shifts while adhering to constraints such as hospital requirements, legal obligations, and nurse preferences. A key objective is to balance workloads among nurses, minimizing variance to prevent burnout and ensure high-quality patient care. Despite various models addressing NSP, such as goal programming and stochastic methods, a significant gap remains in balancing workloads within individual shifts, which is crucial for nurse well-being and operational efficiency. This study develops an optimized nurse scheduling model for the emergency department (ED) of Dr. Saiful Anwar Hospital (RSSA) in Malang, using data from January 2024. The model considers 21 nurses, including 4 chief nurses, and aims to minimize workload variance across shifts while ensuring each nurse works at least 21 days per month. The simulation results show that the optimized schedule achieves a more equitable distribution of shifts and days off compared to the actual January 2024 schedule. The optimized model ensures that all nurses, except chief nurses, are assigned 21 working days with evenly distributed rest days, reducing fatigue and enhancing nurse well-being. This study advances NSP research by focusing on workload balance within shifts, contributing to improved healthcare service quality and nurse satisfaction. Future research should explore adaptive scheduling and incorporate factors like nurse preferences and patient acuity to further enhance scheduling flexibility and efficiency.
Keywords: Nurse Scheduling Problem, Optimization, Scheduling
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