An analysis of temporal and spatial patterns in Italian hospitalization rates for multiple diagnosis

The analysis is based on a novel model-based clustering approach which enables clustering of spatially registered time series with respect to latent temporal patterns. The clustering result is analyzed to study the spatial distribution of the latent temporal patterns and their trend in order to identify possible critical areas in terms of increasing rates. Additionally, emerging spatial patterns may help common causes driving the hospitalization rates to be identified.