Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Dec;20(4):453-466.
doi: 10.1007/s10729-016-9364-4. Epub 2016 Apr 8.

Flexible bed allocations for hospital wards

Affiliations

Flexible bed allocations for hospital wards

René Bekker et al. Health Care Manag Sci. 2017 Dec.

Abstract

Flexibility in the usage of clinical beds is considered to be a key element to efficiently organize critical capacity. However, full flexibility can have some major drawbacks as large systems are more difficult to manage, lack effective care delivery due to absence of focus and require multi-skilled medical teams. In this paper, we identify practical guidelines on how beds should be allocated to provide both flexibility and utilize specialization. Specifically, small scale systems can often benefit from full flexibility. Threshold type of control is then effective to prioritize patient types and to cope with patients having diverse lengths of stay. For large scale systems, we assert that a little flexibility is generally sufficient to take advantage of most of the economies of scale. Bed reservation (earmarking) or, equivalently, organizing a shared ward of overflow, then performs well. The theoretical models and guidelines are illustrated with numerical examples. Moreover, we address a key question stemming from practice: how to distribute a fixed number of hospital beds over the different units?

Keywords: Bed pooling; Clinical capacity; Earmarking; Flexible bed allocation; Optimization; Queueing model.

PubMed Disclaimer

Figures

Fig. 1
Fig. 1
Efficiency frontier in case of specialized care at one ward
Fig. 2
Fig. 2
Efficiency frontier for two wards with different ALOS
Fig. 3
Fig. 3
Relative difference in average costs for simple merging (a), earmarking policy (b) and threshold policy (c) compared to the average costs for the optimal policy
Fig. 4
Fig. 4
Blocking probability as a function of the number of flexible beds

References

    1. Altman E, Jiminez T, Koole GM. On optimal call admission control in a resource-sharing system. IEEE Trans Commun. 2001;49:1659–1668. doi: 10.1109/26.950352. - DOI
    1. Bonald T (2006) Insensitive Queueing models for communication networks (2006). In: Proceedings of the Valuetools
    1. Borst SC, Mandelbaum A, Reiman MI. Dimensioning large call centers. Oper Res. 2004;52:17–34. doi: 10.1287/opre.1030.0081. - DOI
    1. de Bruin AM, Bekker R, van Zanten L, Koole GM. Dimensioning clinical wards using the Erlang loss model. Ann Oper Res. 2010;178:23–43. doi: 10.1007/s10479-009-0647-8. - DOI
    1. Burke EK, de Causmaecker P, Berghe GV, van Landeghem H. The state of the art of nurse rostering. J Sched. 2004;7:441–499. doi: 10.1023/B:JOSH.0000046076.75950.0b. - DOI

LinkOut - more resources