Optimizing Nurse Scheduling: A Supply Chain Approach for Healthcare Institutions
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arXiv
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866909256908800000 |
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| author | Thomas, Jubin |
| author_facet | Thomas, Jubin |
| contents | When managing an organization, planners often encounter numerous challenging scenarios. In such instances, relying solely on intuition or managerial experience may not suffice, necessitating a quantitative approach. This demand is further accentuated in the era of big data, where the sheer scale and complexity of constraints pose significant challenges. Therefore, the aim of this study is to provide a foundational framework for addressing personnel scheduling, a critical issue in organizational management. Specifically, we focus on optimizing shift assignments for staff, a task fraught with complexities due to factors such as contractual obligations and mandated rest periods. Moreover, the current landscape is characterized by frequent employee shortages across various industries, with many organizations lacking efficient and dependable management tools to address them. Therefore, our attention is particularly drawn to the nurse rostering problem, a personnel scheduling challenge prevalent in healthcare settings. These issues are characterized by a multitude of variables, given that a single healthcare facility may employ hundreds of nurses, alongside stringent constraints such as the need for adequate staffing levels and rest periods postnight shifts. Furthermore, the ongoing COVID19 pandemic has exacerbated staffing challenges in healthcare institutions, underlining the importance of accurately assessing staffing needs and optimizing shift allocations for effective operation amidst crisis situations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_11195 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Optimizing Nurse Scheduling: A Supply Chain Approach for Healthcare Institutions Thomas, Jubin Computers and Society When managing an organization, planners often encounter numerous challenging scenarios. In such instances, relying solely on intuition or managerial experience may not suffice, necessitating a quantitative approach. This demand is further accentuated in the era of big data, where the sheer scale and complexity of constraints pose significant challenges. Therefore, the aim of this study is to provide a foundational framework for addressing personnel scheduling, a critical issue in organizational management. Specifically, we focus on optimizing shift assignments for staff, a task fraught with complexities due to factors such as contractual obligations and mandated rest periods. Moreover, the current landscape is characterized by frequent employee shortages across various industries, with many organizations lacking efficient and dependable management tools to address them. Therefore, our attention is particularly drawn to the nurse rostering problem, a personnel scheduling challenge prevalent in healthcare settings. These issues are characterized by a multitude of variables, given that a single healthcare facility may employ hundreds of nurses, alongside stringent constraints such as the need for adequate staffing levels and rest periods postnight shifts. Furthermore, the ongoing COVID19 pandemic has exacerbated staffing challenges in healthcare institutions, underlining the importance of accurately assessing staffing needs and optimizing shift allocations for effective operation amidst crisis situations. |
| title | Optimizing Nurse Scheduling: A Supply Chain Approach for Healthcare Institutions |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2407.11195 |