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Nurse scheduling with quick-response methods: Improving hospital performance, nurse workload, and patient experience

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  • Schoenfelder, Jan
  • Bretthauer, Kurt M.
  • Wright, P. Daniel
  • Coe, Edwin

Abstract

Hospitals continue to face the challenge of providing high-quality patient care in an environment of rising healthcare costs. In response, a great deal of attention has been given to advance planning decisions such as nurse staffing, bed mix, scheduling, and patient flow. However, less attention has been given to incorporating quick-response methods in the nurse scheduling process by both anticipating and responding to patient demand fluctuations. Therefore, in this paper, we present a model that incorporates two classes of quick-response decisions in hospitals’ nurse scheduling: (i) adjustments to the unit assignments of cross-trained float nurses and (ii) transfers of patients between units and off-unit admissions. Analyzing three hospitals that are subject to different regulations with respect to patient-to-nurse ratios allows us to draw conclusions on how these hotly debated ratios impact hospital performance, nurse workload, and patient experience. We find that quick-response via cross-trained nurses may lead to higher total costs in settings where an upper limit on patient-to-nurse ratios is enforced. This result has significant managerial and political relevance in locations such as California. Another takeaway is that only a small number of patient transfers or off-unit admissions provides close to the full potential benefit, thus minimizing the negative impact on patient satisfaction and quality of care. Moreover, our proposed scheduling approach reduces the number of undesired assigned shifts. Finally, bed and nurse capacity utilization are shown to be important considerations when determining how and whether to use quick-response methods.

Suggested Citation

  • Schoenfelder, Jan & Bretthauer, Kurt M. & Wright, P. Daniel & Coe, Edwin, 2020. "Nurse scheduling with quick-response methods: Improving hospital performance, nurse workload, and patient experience," European Journal of Operational Research, Elsevier, vol. 283(1), pages 390-403.
  • Handle: RePEc:eee:ejores:v:283:y:2020:i:1:p:390-403
    DOI: 10.1016/j.ejor.2019.10.047
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    References listed on IDEAS

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    Cited by:

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    2. David D. Cho & Kurt M. Bretthauer & Jan Schoenfelder, 2023. "Patient-to-nurse ratios: Balancing quality, nurse turnover, and cost," Health Care Management Science, Springer, vol. 26(4), pages 807-826, December.
    3. Nguyen, Hong Ngoc & O’Donnell, Christopher, 2023. "Estimating the cost efficiency of public service providers in the presence of demand uncertainty," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1334-1348.
    4. Kjartan Kastet Klyve & Ilankaikone Senthooran & Mark Wallace, 2023. "Nurse rostering with fatigue modelling," Health Care Management Science, Springer, vol. 26(1), pages 21-45, March.
    5. Andrés Miniguano-Trujillo & Fernanda Salazar & Ramiro Torres & Patricio Arias & Koraima Sotomayor, 2021. "An integer programming model to assign patients based on mental health impact for tele-psychotherapy intervention during the Covid–19 emergency," Health Care Management Science, Springer, vol. 24(2), pages 286-304, June.

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