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Flexible hospital-wide elective patient scheduling

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  • Daniel Gartner
  • Rema Padman

Abstract

In this paper, we build on and extend Gartner and Kolisch (2014)’s hospital-wide patient scheduling problem. Their contribution margin maximising model decides on the patients’ discharge date and therefore the length of stay. Decisions such as the allocation of scarce hospital resources along the clinical pathways are taken. Our extensions which are modeled as a mathematical program include admission decisions and flexible patient-to-specialty assignments to account for multi-morbid patients. Another flexibility extension is that one out of multiple surgical teams can be assigned to each patient. Furthermore, we consider overtime availability of human resources such as residents and nurses. Finally, we include these extensions in the rolling-horizon approach and account for lognormal distributed recovery times and remaining resource capacity for elective patients. Our computational study on real-world instances reveals that, if overtime flexibility is allowed, up to 5% increase in contribution margin can be achieved by reducing length of stay by up to 30%. At the same time, allowing for overtime can reduce waiting times by up to 33%. Our model can be applied in and generalised towards other patient scheduling problems, for example in cancer care where patients may follow defined cancer pathways.

Suggested Citation

  • Daniel Gartner & Rema Padman, 2020. "Flexible hospital-wide elective patient scheduling," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(6), pages 878-892, June.
  • Handle: RePEc:taf:tjorxx:v:71:y:2020:i:6:p:878-892
    DOI: 10.1080/01605682.2019.1590509
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    Cited by:

    1. José Carlos Ferrão & Mónica Duarte Oliveira & Daniel Gartner & Filipe Janela & Henrique M. G. Martins, 2021. "Leveraging electronic health record data to inform hospital resource management," Health Care Management Science, Springer, vol. 24(4), pages 716-741, December.
    2. Xinyu Yao & Karmel S. Shehadeh & Rema Padman, 2024. "Multi-resource allocation and care sequence assignment in patient management: a stochastic programming approach," Health Care Management Science, Springer, vol. 27(3), pages 352-369, September.

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