Title | ||
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New results on integrated nurse staffing and scheduling: The medium-term context for intensive care units |
Abstract | ||
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This We examine medium-term integrated nurse staffing policy options for hospital intensive care units (ICU). Our aim is to reduce nurse staffing costs while balancing the under/ over-staffing risks. Medium-term nurse schedules are highly uncertain as they are generated long before actual patient demand is realised. Optimisation models presented in this study allow us to examine fixed versus dynamic nurse staffing policy options for the medical units. In the dynamic nurse staffing, we utilise historical patient data to fit estimates of non-stationary patient demand. We compare the performance of both policy options with the optimal staffing scheme reached by the actual patient data. We generate feasible schedules for nurse sub-groups to avoid complete enumeration. We evaluate the performance of models with the pediatric ICU of a large urban children's hospital. Experiments with the dynamic policy resulted in more than 3% higher average cost savings compared to the fixed staffing policies. |
Year | DOI | Venue |
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2021 | 10.1080/01605682.2020.1806742 | JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY |
Keywords | DocType | Volume |
Nurse scheduling, workforce planning, healthcare services, mixed-integer programming | Journal | 72 |
Issue | ISSN | Citations |
12 | 0160-5682 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Osman T. Aydas | 1 | 0 | 0.34 |
Anthony D. Ross | 2 | 10 | 1.88 |
Matthew C. Scanlon | 3 | 0 | 0.34 |
Buket Aydas | 4 | 0 | 0.34 |