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Hospital Costs of Foreign Non-Resident Patients: A Comparative Analysis in Catalonia, Spain

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  • Elena Arroyo-Borrell

    (Health Policy Research Unit (SEPPS), Consortium of Health and Social of Catalonia, 08022 Barcelona, Spain
    Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, Carrer de la Universitat de Girona 10, Campus Montilivi, 17003 Girona, Spain
    CIBER of Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain)

  • Gemma Renart-Vicens

    (Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, Carrer de la Universitat de Girona 10, Campus Montilivi, 17003 Girona, Spain
    CIBER of Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain)

  • Marc Saez

    (Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, Carrer de la Universitat de Girona 10, Campus Montilivi, 17003 Girona, Spain
    CIBER of Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain)

  • Marc Carreras

    (GRESSiRES, Research Group on Health Services and Health Outcomes, Serveis de Salut Integrats Baix Empordà, 17230 Palamós, Spain
    Department of Business Studies, University of Girona, 17004 Girona, Spain)

Abstract

Although patient mobility has increased over the world, in Europe there is a lack of empirical studies. The aim of the study was to compare foreign non-resident patients versus domestic patients for the particular Catalan case, focusing on patient characteristics, hospitalisation costs and differences in costs depending on the typology of the hospital they are treated. We used data from the 2012 Minimum Basic Data Set-Acute Care hospitals (CMBD-HA) in Catalonia. We matched two case-control groups: first, foreign non-resident patients versus domestic patients and, second, foreign non-resident patients treated by Regional Public Hospitals versus other type of hospitals. Hospitalisation costs were modelled using a GLM Gamma with a log-link. Our results show that foreign non-resident patients were significantly less costly than domestic patients (12% cheaper). Our findings also suggested differences in the characteristics of foreign non-resident patients using Regional Public Hospitals or other kinds of hospitals although we did not observe significant differences in the healthcare costs. Nevertheless, women, 15–24 and 35–44 years old patients and the days of stay were less costly in Regional Public Hospitals. In general, acute hospitalizations of foreign non-resident patients while they are on holiday cost substantially less than domestic patients. The typology of hospital is not found to be a relevant factor influencing costs.

Suggested Citation

  • Elena Arroyo-Borrell & Gemma Renart-Vicens & Marc Saez & Marc Carreras, 2017. "Hospital Costs of Foreign Non-Resident Patients: A Comparative Analysis in Catalonia, Spain," IJERPH, MDPI, vol. 14(9), pages 1-13, September.
  • Handle: RePEc:gam:jijerp:v:14:y:2017:i:9:p:1062-:d:111935
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    References listed on IDEAS

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    1. Manning, Willard G. & Basu, Anirban & Mullahy, John, 2005. "Generalized modeling approaches to risk adjustment of skewed outcomes data," Journal of Health Economics, Elsevier, vol. 24(3), pages 465-488, May.
    2. Silvio R. Rendon, 2013. "Fixed and Random Effects in Classical and Bayesian Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(3), pages 460-476, June.
    3. Irene Garcia-Subirats & Ingrid Vargas & Belén Sanz-Barbero & Davide Malmusi & Elena Ronda & Mónica Ballesta & María Luisa Vázquez, 2014. "Changes in Access to Health Services of the Immigrant and Native-Born Population in Spain in the Context of Economic Crisis," IJERPH, MDPI, vol. 11(10), pages 1-20, September.
    4. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
    5. Andrew M. Jones & James Lomas & Peter T. Moore & Nigel Rice, 2016. "A quasi-Monte-Carlo comparison of parametric and semiparametric regression methods for heavy-tailed and non-normal data: an application to healthcare costs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 951-974, October.
    6. Steven C. Hill & G. Edward Miller, 2010. "Health expenditure estimation and functional form: applications of the generalized gamma and extended estimating equations models," Health Economics, John Wiley & Sons, Ltd., vol. 19(5), pages 608-627, May.
    7. Manning, Willard G. & Mullahy, John, 2001. "Estimating log models: to transform or not to transform?," Journal of Health Economics, Elsevier, vol. 20(4), pages 461-494, July.
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