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Bed Census Predictions and Nurse Staffing

In: Handbook of Healthcare Logistics

Author

Listed:
  • Aleida Braaksma

    (University of Twente)

  • Nikky Kortbeek

    (University of Twente
    Rhythm b.v.)

  • Richard J. Boucherie

    (University of Twente)

Abstract

Workloads in nursing wards depend highly on patient arrivals and lengths of stay, both of which are inherently variable. Predicting these workloads and staffing nurses accordingly are essential for guaranteeing quality of care in a cost-effective manner. This chapter describes a stochastic method that uses hourly census predictions to derive efficient nurse staffing policies. The generic analytic approach minimizes staffing levels while satisfying so-called nurse-to-patient ratios. In particular, we explore the potential of flexible staffing policies that allow hospitals to dynamically respond to their fluctuating patient population by employing float nurses. The method is applied to a case study of the surgical inpatient clinic of the Academic Medical Center Amsterdam (AMC).

Suggested Citation

  • Aleida Braaksma & Nikky Kortbeek & Richard J. Boucherie, 2021. "Bed Census Predictions and Nurse Staffing," International Series in Operations Research & Management Science, in: Maartje E. Zonderland & Richard J. Boucherie & Erwin W. Hans & Nikky Kortbeek (ed.), Handbook of Healthcare Logistics, pages 151-180, Springer.
    • Handle: RePEc:spr:isochp:978-3-030-60212-3_9
    DOI: 10.1007/978-3-030-60212-3_9
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