Evaluation and implementation of a Just-In-Time bed-assignment strategy to reduce wait times for surgical inpatients

Aleida Braaksma (), Martin S. Copenhaver (), Ana C. Zenteno (), Elizabeth Ugarph, Retsef Levi, Bethany J. Daily, Benjamin Orcutt, Kathryn M. Turcotte and Peter F. Dunn
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Aleida Braaksma: Massachusetts Institute of Technology
Martin S. Copenhaver: Massachusetts General Hospital
Ana C. Zenteno: Massachusetts General Hospital
Elizabeth Ugarph: Massachusetts Institute of Technology
Retsef Levi: Massachusetts Institute of Technology
Bethany J. Daily: Massachusetts General Hospital
Benjamin Orcutt: Massachusetts General Hospital
Kathryn M. Turcotte: Massachusetts General Hospital
Peter F. Dunn: Massachusetts General Hospital

Health Care Management Science, 2023, vol. 26, issue 3, No 7, 515 pages

Abstract: Abstract Early bed assignments of elective surgical patients can be a useful planning tool for hospital staff; they provide certainty in patient placement and allow nursing staff to prepare for patients’ arrivals to the unit. However, given the variability in the surgical schedule, they can also result in timing mismatches—beds remain empty while their assigned patients are still in surgery, while other ready-to-move patients are waiting for their beds to become available. In this study, we used data from four surgical units in a large academic medical center to build a discrete-event simulation with which we show how a Just-In-Time (JIT) bed assignment, in which ready-to-move patients are assigned to ready-beds, would decrease bed idle time and increase access to general care beds for all surgical patients. Additionally, our simulation demonstrates the potential synergistic effects of combining the JIT assignment policy with a strategy that co-locates short-stay surgical patients out of inpatient beds, increasing the bed supply. The simulation results motivated hospital leadership to implement both strategies across these four surgical inpatient units in early 2017. In the several months post-implementation, the average patient wait time decreased 25.0% overall, driven by decreases of 32.9% for ED-to-floor transfers (from 3.66 to 2.45 hours on average) and 37.4% for PACU-to-floor transfers (from 2.36 to 1.48 hours), the two major sources of admissions to the surgical floors, without adding additional capacity.

Keywords: Bed assignment; Patient flow; Discrete-event simulation; Just-in-time; Hospital operations; Hospital capacity management; ARIMA model; Operations research; Operations management (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10729-023-09638-3

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