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Length of hospital stay (LOS) is an important indicator of the hospitalactivity and management of health care. The skewness in the distribution of LOSposes problems in statistical modelling because it fails to adequately followthe usual traditional distribution such as the log-normal distribution. The aimof this work is to model the variable LOS using the convolution of twodistributions; a technique well known in the signal processing community. Thespecificity of that model is that the variable of interest is considered to bethe resulting sum of two random variables with different distributions. One ofthe variables will feature the patient-related factors in terms their need torecover from their admission condition, while the other models the hospitalmanagement process such as the discharging process. Two estimation proceduresare proposed. One is the classical maximum likelihood, while the other relatesto the expectation maximisation algorithm. We will present some resultsobtained by applying this model to a set of real data from a group of hospitalsin Victoria (Australia).

Modelling Hospital length of stay using convolutive mixtures distributions