title: Flexible bed allocations for hospital wards.
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?
authors.affiliation: Department of Mathematics, VU University Amsterdam, De Boelelaan 1081a, 1081, HV, Amsterdam, The Netherlands. r.bekker@vu.nl.
authors.forename: René
authors.initials: R
authors.lastname: Bekker
authors.affiliation: Department of Mathematics, VU University Amsterdam, De Boelelaan 1081a, 1081, HV, Amsterdam, The Netherlands.
authors.forename: Ger
authors.initials: G
authors.lastname: Koole
authors.affiliation: HOTflo Company, Schoutlaan 26, 6002, EA, Weert, The Netherlands.
authors.forename: Dennis
authors.initials: D
authors.lastname: Roubos
mesh_terms: D001509:Bed Occupancy; D003659:Decision Making, Organizational; D017598:Efficiency, Organizational; D006742:Hospital Bed Capacity; D006801:Humans; D007902:Length of Stay; D017146:Models, Organizational; D015233:Models, Statistical; D009426:Netherlands; D040841:Resource Allocation / Q000379:methods*
keywords: Bed pooling; Clinical capacity; Earmarking; Flexible bed allocation; Optimization; Queueing model