Hospital Resource Consumption Modelling

Marco Papi, Luca Pontecorvi


Health service researchers frequently study length of hospital stay (LoS) as a health outcome. LoS is a valid proxy to estimate the consumption of hospital resources. Average LoS, however, albeit easy to quantify and calculate, can be misleading if the underlying distribution is not symmetric. Generally originating from heavily skewed distributions, LoS data can be difficult to model with a single parametric model. Mixture models can be quite effective in dealing with such data. In this paper we proposed a generalization of the phase-type distribution in order to capture all the statistical features observed in real situations. We also propose an analysis of the discharge rate and the admission rate. Those proxies provide information on the efficiency of departments and give operational guidelines for medical staff.

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