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Keeping pace with the ebbs and flows in daily nursing home operations

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  • René Bekker

    (Vrije Universiteit Amsterdam)

  • Dennis Moeke

    (HAN University of Applied Sciences)

  • Bas Schmidt

    (Deloitte)

Abstract

Nursing homes are challenged to develop staffing strategies that enable them to efficiently meet the healthcare demand of their residents. In this study, we investigate how demand for care and support fluctuates over time and during the course of a day, using demand data from three independent nursing home departments of a single Dutch nursing home. This demand data is used as input for an optimization model that provides optimal staffing patterns across the day. For the optimization we use a Lindley-type equation and techniques from stochastic optimization to formulate a Mixed-Integer Linear Programming (MILP) model. The impact of both the current and proposed staffing patterns, in terms of waiting time and service level, are investigated. The results show substantial improvements for all three departments both in terms of average waiting time as well as in 15 minutes service level. Especially waiting during rush hours is significantly reduced, whereas there is only a slight increase in waiting time during non-rush hours.

Suggested Citation

  • René Bekker & Dennis Moeke & Bas Schmidt, 2019. "Keeping pace with the ebbs and flows in daily nursing home operations," Health Care Management Science, Springer, vol. 22(2), pages 350-363, June.
    • Handle: RePEc:kap:hcarem:v:22:y:2019:i:2:d:10.1007_s10729-018-9442-x
    DOI: 10.1007/s10729-018-9442-x
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    Cited by:

    1. Manion Anderson & Merve Bodur & Scott Rathwell & Vahid Sarhangian, 2023. "Optimization Helps Scheduling Nursing Staff at the Long-Term Care Homes of the City of Toronto," Interfaces, INFORMS, vol. 53(2), pages 133-154, March.
    2. Forbes, M.A. & Harris, M.G. & Jansen, H.M. & van der Schoot, F.A. & Taimre, T., 2024. "Combining optimisation and simulation using logic-based Benders decomposition," European Journal of Operational Research, Elsevier, vol. 312(3), pages 840-854.

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