The University of Southampton
University of Southampton Institutional Repository

Fairness of National Health Service in Italy: a bivariate correlated random effects model

Fairness of National Health Service in Italy: a bivariate correlated random effects model
Fairness of 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
0266-4763
709-722
Maruotti, Antonello
7096256c-fa1b-4cc1-9ca4-1a60cc3ee12e
Maruotti, Antonello
7096256c-fa1b-4cc1-9ca4-1a60cc3ee12e

Maruotti, Antonello (2009) Fairness of National Health Service in Italy: a bivariate correlated random effects model. Journal of Applied Statistics, 36 (7), 709-722. (doi:10.1080/02664760802499311).

Record type: Article

Abstract

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.

This record has no associated files available for download.

More information

e-pub ahead of print date: 18 June 2009
Published date: July 2009
Keywords: fairness, healthcare, random effects models, binary data, non-parametric maximum likelihood
Organisations: Statistics, Statistical Sciences Research Institute

Identifiers

Local EPrints ID: 345967
URI: http://eprints.soton.ac.uk/id/eprint/345967
ISSN: 0266-4763
PURE UUID: 16158826-5603-4ad3-af36-97aab58b7a08

Catalogue record

Date deposited: 10 Dec 2012 12:26
Last modified: 14 Mar 2024 12:31

Export record

Altmetrics

Contributors

Author: Antonello Maruotti

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×