Compartimental Models to Predict Hospital Bed Utilisation

Title: Using Compartmental models to predict hospital bed occupancy
Abstract
The use of acute care hospitals is a significant factor in the increasing cost of health care in many developed countries. The modelling of hospital beds should lead to better decision-making in relation to this expensive resource. The average length of stay is inappropriate for such modelling. Millard and others have shown that compartmental models can be used for bed modelling. These models are plausible and easily interpreted.
Little work in relation to generalization and predictability has been undertaken. The purpose of this paper was to consider which methodology is likely to provide the best predictive decision-making in relation to hospital bed use for medical patients based upon the work of Millard and his colleagues. Our results showed that the annual average model performed best and offers a superior predictive capability over one-day census models.
Model creation should be based upon the consideration of as many points as necessary to capture the variation within the data. Improvement in model performance may be obtained by the creation of more complex models. Consideration about the method of optimisation used to create the models is also required to ensure that it coincides with the goals of the users.
Keywords: hospital beds, occupancy, length of stay, modelling, prediction
The Authors:
Mark Mackay BSc(Hons) BEc BComm
PhD Candidate, Department of Psychology
University of Adelaide
And
Principal Project Officer
Department of Human Services
South Australia
Ph: 61 8 8463 6130
Fax: [phone]
Email: [e-mail]
Dr Michael Lee BSc(Ma) BA(Hons) Grad Dip Ed PhD
Senior Lecturer
Department of Psychology
University of Adelaide
South Australia
Ph: 61 8 8303 6096
Fax: [phone]
Email: [e-mail]
Compartmental models of hospital bed occupancy and choice of data
Introduction
In recent years the Australian public

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