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

René Bekker (), Dennis Moeke () and Bas Schmidt ()
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René Bekker: Vrije Universiteit Amsterdam
Dennis Moeke: HAN University of Applied Sciences
Bas Schmidt: Deloitte

Health Care Management Science, 2019, vol. 22, issue 2, No 9, 350-363

Abstract: 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.

Keywords: Nursing home care; Scheduled care; Demand patterns; Staffing; Waiting times; Scheduling (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10729-018-9442-x

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