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

Mauro Laudicella and Paolo Li Donni ()

No 2021:1, DaCHE discussion papers from University of Southern Denmark, Dache - Danish Centre for Health Economics

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.

Keywords: mixture distributions; hidden Markov models; panel data; primary care; secondary care; Denmark healthcare. (search for similar items in EconPapers)
JEL-codes: C33 D12 I11 I18 (search for similar items in EconPapers)
Pages: 35 pages
Date: 2021-03-25
New Economics Papers: this item is included in nep-hea
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Citations: View citations in EconPapers (1)

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Journal Article: The dynamic interdependence in the demand of primary and emergency secondary care: A hidden Markov approach (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:sduhec:2021_001

DOI: 10.21996/26m8-5r10

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