Computer Science > Machine Learning
arXiv:2311.00696 (cs)
[Submitted on 1 Nov 2023 (v1), last revised 26 Apr 2024 (this version, v2)]
Title:Decision Support Framework for Home Health Caregiver Allocation Using Optimally Tuned Spectral Clustering and Genetic Algorithm
Authors:Seyed Mohammad Ebrahim Sharifnia,Faezeh Bagheri,Rupy Sawhney,John E. Kobza,Enrique Macias De Anda,Mostafa Hajiaghaei-Keshteli,Michael Mirrielees
View a PDF of the paper titled Decision Support Framework for Home Health Caregiver Allocation Using Optimally Tuned Spectral Clustering and Genetic Algorithm, by Seyed Mohammad Ebrahim Sharifnia and 6 other authors
View PDFHTML (experimental)Abstract:Population aging is a global challenge, leading to increased demand for health care and social services for the elderly. Home Health Care (HHC) is a vital solution to serve this segment of the population. Given the increasing demand for HHC, it is essential to coordinate and regulate caregiver allocation efficiently. This is crucial for both budget-optimized planning and ensuring the delivery of high-quality care. This research addresses a fundamental question in home health agencies (HHAs): "How can caregiver allocation be optimized, especially when caregivers prefer flexibility in their visit sequences?". While earlier studies proposed rigid visiting sequences, our study introduces a decision support framework that allocates caregivers through a hybrid method that considers the flexibility in visiting sequences and aims to reduce travel mileage, increase the number of visits per planning period, and maintain the continuity of care; a critical metric for patient satisfaction. Utilizing data from an HHA in Tennessee, United States, our approach led to an impressive reduction in average travel mileage (up to 42%, depending on discipline) without imposing restrictions on caregivers. Furthermore, the proposed framework is used for caregivers' supply analysis to provide valuable insights into caregiver resource management.
| Comments: | The document is written in the Elsevier LaTeX format |
| Subjects: | Machine Learning (cs.LG) |
| Cite as: | arXiv:2311.00696 [cs.LG] |
| (orarXiv:2311.00696v2 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2311.00696 arXiv-issued DOI via DataCite |
Submission history
From: Ebrahim Sharifnia [view email][v1] Wed, 1 Nov 2023 17:54:49 UTC (2,117 KB)
[v2] Fri, 26 Apr 2024 20:10:22 UTC (3,630 KB)
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View a PDF of the paper titled Decision Support Framework for Home Health Caregiver Allocation Using Optimally Tuned Spectral Clustering and Genetic Algorithm, by Seyed Mohammad Ebrahim Sharifnia and 6 other authors
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