Fairness of the national health service in Italy: a bivariate correlated random effects model
The primary purpose of this paper is to comprehensively assess households' burden due to health payments. Starting from the fairness approach developed by the World Health Organization, we analyse the burden of healthcare payments on Italian households by modeling catastrophic payments and impoverishment due to healthcare expenditures. For this purpose, we propose to extend the analysis of fairness in financing contribution through a generalized linear mixed models by introducing a bivariate correlated random effects model, where association between the outcomes is modeled through individual- and outcome-specific latent effects which are assumed to be correlated. We discuss model parameter estimation in a finite mixture context. By using such model specification, the fairness of the Italian national health service is investigated.
fairness, healthcare, random effects models, binary data, non-parametric maximum likelihood,
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