Methods Inf Med 2007; 46(04): 399-405
DOI: 10.1160/ME0385
 
Schattauer GmbH

An Objective Method for Bed Capacity Planning in a Hospital Department

A Comparison with Target Ratio Methods
J. M. Nguyen
1   PIMESP, CHU Nantes, rue Saint Jacques, Nantes, France
,
P. Six
2   Département de l’Information Médicale, CHU Angers, Angers, France
,
T. Chaussalet
3   School of Informatics, University of Westminster, London, UK
,
D. Antonioli
1   PIMESP, CHU Nantes, rue Saint Jacques, Nantes, France
,
P. Lombrail
1   PIMESP, CHU Nantes, rue Saint Jacques, Nantes, France
,
P. Le Beux
4   Laboratoire d’Informatique Médicale, CHU Rennes, Rennes, France
› Author Affiliations
Further Information

Publication History

Publication Date:
20 January 2018 (online)

Summary

Objectives: To propose an objective approach in order to determine the number of beds required for a hospital department by considering how recruitment fluctuates over time. To compare this approach with classical bed capacity planning techniques.

Methods: Asimulated data-based evaluation of the impact that the variability in hospital department activity produces upon the performance of methods used for determining the number of beds required. The evaluation criteria included productive efficiency measured bythe bed occupancy rate, accessibility measured by the transfer rate of patients due to lack of available beds and a proxy of clinical effectiveness, by the proportion of days during which there is no possibility forunscheduled admission.

Results: When the variability of the number of daily patients increases, the Target Occupancy Rate favors productive efficiency at the expense of accessibility and proxy clinical effectiveness. On the contrary, when the variability of the department activity is marginal, the Target Activity Rate penalizes the proxy of clinical effectiveness, and the Target Occupancy Rate under-optimizes productive efficiency.

The method we propose led to a superior performance in terms of accessibility and proxy of clinical effectiveness at the expense of productive efficiency. Such a situation is suitable for intensive care units. In the case of other departments, a weighting procedure should be used to improve productive efficiency.

Conclusions: This approach could be considered as the first step of a family of methods for quantitative healthcare planning.

 
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