A Bayesian approach to modelling inpatient expenditure

This paper introduces a model for representing patient survival and cost. An extension of Bayesian network (BN) theory is developed to represent such a model whereby patient's continuous survival time in hospital is modelled with respect to the graphical and probabilistic representation of the interrelationships between the patient's clinical variables. Unlike previously defined BN techniques, this extended model can accommodate continuous times that are skewed in nature. This paper presents the theory behind such an approach and extends it by attaching a cost variable to the survival times, enabling the costing and efficient management of groups of patients in hospital The model, applied to 4722 patients admitted into a geriatric ward of a U.K. hospital between 1994 and 1997, could be beneficial to hospital managers as a method for investigating the influence of future decisions and policy changes on the hospital expenditure.