Workload balancing for the nurse scheduling problem: A real-world case study from a French hospital

Yasmine Alaouchiche, Ouazene Yassine (), Farouk Yalaoui and Chehade Hicham
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Yasmine Alaouchiche: LIST3N - OPTI - LIST3N - Optimisation - LIST3N - Laboratoire Informatique et Société Numérique - UTT - Université de Technologie de Troyes, OPTACARE
Ouazene Yassine: LIST3N - OPTI - LIST3N - Optimisation - LIST3N - Laboratoire Informatique et Société Numérique - UTT - Université de Technologie de Troyes
Farouk Yalaoui: LIST3N - OPTI - LIST3N - Optimisation - LIST3N - Laboratoire Informatique et Société Numérique - UTT - Université de Technologie de Troyes
Chehade Hicham: OPTACARE

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Abstract: To improve the efficiency and viability of healthcare organizations, it is crucial to enhance both the quality of patient care and the well-being of healthcare staff, particularly nurses. They play a vital role as a key human resource in healthcare, and their well-being and job satisfaction are significantly influenced by effective scheduling. Improved scheduling practices not only enhance the quality of care provided but also contribute to better job satisfaction and overall well-being of the nursing staff. Despite the importance of this task, nurse scheduling is often conducted manually by head nurses, which is both challenging and time-consuming. This study proposes a mathematical model that addresses the nurse scheduling problem, with a specific application in a French hospital department. The objectives of the model are to accommodate a wide range of constraints flexibly, ensure balanced workloads and shifts, and align with the preferences of the nursing staff. A significant contribution of this research is the theoretical investigation and comparison of various workload balancing criteria tailored to the specific context of the problem. The study analyzes different workload balancing criteria to formulate an efficient scheduling solution. The effectiveness of the proposed approach is demonstrated through large experiments and practice feedback, confirming its potential to enhance both healthcare efficiency and nurses' well-being.

Keywords: Nurse rostering problem; Healthcare; Staff planning; Workload balancing; Mixed integer programming (search for similar items in EconPapers)
Date: 2024-10
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Published in Socio-Economic Planning Sciences, 2024, 95, pp.102046. ⟨10.1016/j.seps.2024.102046⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05485166

DOI: 10.1016/j.seps.2024.102046

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