The dynamic interdependence in the demand of primary and emergency secondary care: A hidden Markov approach

Mauro Laudicella, Paolo Li Donni

Research output: Working paperResearch

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Abstract

Abstract. This paper develops an extension of the class of finite mixture models for longitudinal count data to the bivariate case by using a trivariate reduction technique and a hidden Markov chain approach. The model allows for disentangling unobservable time-varying heterogeneity from the dynamic effect of utilisation of primary and secondary care and measuring their potential substitution effect. Three points of supports adequately describe the distribution of the latent states suggesting the existence of three profiles of low, medium and high users who shows persistency in their behaviour, but not permanence as some switch to their neighbour's profile.
Original languageEnglish
PublisherSyddansk Universitet
Pages1-35
DOIs
Publication statusPublished - 2021
SeriesDaCHE Discussion Papers
Number1
Volume2021
ISSN2246-3097

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