Patient Assignment and Prioritization for Multi-Stage Care with Reentrance
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866910491891204096 |
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| author | Liu, Wei Lu, Mengshi Shi, Pengyi |
| author_facet | Liu, Wei Lu, Mengshi Shi, Pengyi |
| contents | In this paper, we study a queueing model that incorporates patient reentrance to reflect patients' recurring requests for nurse care and their rest periods between these requests. Within this framework, we address two levels of decision-making: the priority discipline decision for each nurse and the nurse-patient assignment problem. We introduce the shortest-first and longest-first rules in the priority discipline decision problem and show the condition under which each policy excels through theoretical analysis and comprehensive simulations. For the nurse-patient assignment problem, we propose two heuristic policies. We show that the policy maximizing the immediate decrease in holding costs outperforms the alternative policy, which considers the long-term aggregate holding cost. Additionally, both proposed policies significantly surpass the benchmark policy, which does not utilize queue length information. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2406_12135 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Patient Assignment and Prioritization for Multi-Stage Care with Reentrance Liu, Wei Lu, Mengshi Shi, Pengyi Optimization and Control In this paper, we study a queueing model that incorporates patient reentrance to reflect patients' recurring requests for nurse care and their rest periods between these requests. Within this framework, we address two levels of decision-making: the priority discipline decision for each nurse and the nurse-patient assignment problem. We introduce the shortest-first and longest-first rules in the priority discipline decision problem and show the condition under which each policy excels through theoretical analysis and comprehensive simulations. For the nurse-patient assignment problem, we propose two heuristic policies. We show that the policy maximizing the immediate decrease in holding costs outperforms the alternative policy, which considers the long-term aggregate holding cost. Additionally, both proposed policies significantly surpass the benchmark policy, which does not utilize queue length information. |
| title | Patient Assignment and Prioritization for Multi-Stage Care with Reentrance |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2406.12135 |