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Social Indicators Research

, Volume 121, Issue 1, pp 149–175 | Cite as

Another Look at the Comparisons of the Health Systems Expenditure Indicators

  • Guillem Lopez-Casasnovas
  • Laia Maynou
  • Marc Saez
Article

Abstract

For policy purposes expenditure in health systems of extremely different natures are often compared without having a clear question to be addressed in such a comparison. For instance, comparisons made among OECD countries which have differing levels of development, and/or where the fusion of public and private finance differ; along with their sources of revenue, their finance levels and their degree of taxes and co-payments. Our objective in this paper is to analyze the factors that complicate international comparisons of health care expenditure across countries. We comment on some of these issues and shows how results and the interpretation of the gaps differ according to the refinements we make to the sampling and sub-sampling, as well as the definition of the variables we adopt. We considered as dependent variables total and health care expenditure per capita and as a percentage of GDP with and without out-of-pocket payments. We analyse the (complete) OECD sample for the period 2000–2010, as well as three sub-samples (European Union, countries with the Bismark model and countries with the Beveridge model). After calculating the means of the dependent variables, both without weights and weighting by GDP and population, we specified two different panel data models to explain the variation in the dependent variables, including as explanatory variables those that are most likely to affect health expenditure. Although other countries are mentioned in this paper, we take Spain as our example. We show how the results and the consequent interpretations of the gaps can differ according to the refinements we introduce into the sample and sub-samples; akin to the adjustments we are willing to make to the definition of the variables we choose to adopt. We show how Spanish ratios, as example, are generally well above those expected. In conclusion, there is a need for a better understanding of the settings of any comparison, along with a more appropriate sub sampling of the systems being analyzed in order to align any demand to the financial capabilities of the health care sector.

Keywords

Health spending Country finance comparisons OECD data 

Notes

Acknowledgments

We appreciate the comments of two anonymous reviewers that, without doubt, help us improve our work.

References

  1. Anderson, G. F., & Frogner, B. K. (2008). Health spending in OECD countries: Obtaining value per dollar. Health Affairs, 27(6), 1718–1727.CrossRefGoogle Scholar
  2. Anderson, G. F., Frogner, B. K., & Reinhardt, U. E. (2007). Health spending in OECD countries in 2004: An update. Health Affairs, 26(5), 1481–1489.CrossRefGoogle Scholar
  3. Anderson, G. F., Hurst, J., Hussey, P. S., & Jee-Hughes, M. (2000). Health spending and outcomes: Trends in OECD countries, 1960–1998. Health Affairs, 19(3), 150–157.CrossRefGoogle Scholar
  4. Anderson, G. F., & Hussey, P. S. (2001). Comparing health system performance in OECD countries. Health Affairs, 20(3), 219–232.CrossRefGoogle Scholar
  5. Baltagi, B. H., & Moscone, F. (2010). Health care expenditure and income in the OECD reconsidered: Evidence from panel data. Economic Modelling, 27(4), 804–811.CrossRefGoogle Scholar
  6. Bloom, D. E., Cafiero, E. T., Jané-Llopis, E., Abrahams-Gessel, S., Bloom, L. R., Fathima, S., et al. (2011). The global economic burden of non-communicable diseases. Geneva: World Economic Forum.Google Scholar
  7. Clairoux, N. (2012) Where is the best health care system in the world?.Medical Library Association (MLA) Annual Blog. http://npc.mlanet.org/mla12/?p=1322, last accessed on August 3, 2013.
  8. Economic Policy Committee and the European Commission (2006). The impact of ageing on public expenditure: projections for the EU25 Member States on pensions, health care, long-term care, education and unemployment transfers (20042050). European Economy. Special Report no 1/2006. Google Scholar
  9. Gerdtham, U. G., & Jönsson, B. (2000). International comparisons of health expenditure: Theory, data and econometric analysis. In A. J. Culyer & J. P. Newhouse (Eds.), Handbook of health economics (Vol. 1, pp. 11–53). Amsterdam: Elsevier.Google Scholar
  10. Getzen, T. E. (2000). Health care is an individual necessity and a national luxury: Applying multilevel decision models to the analysis of health care. Journal of Health Economics, 19, 259–270.CrossRefGoogle Scholar
  11. Hopkins, S. (2010) Health expenditure comparisons: Low, middle and high income countries. The Open Health Services and Policy Journal, 3, 111–117. http://www.benthamscience.com/open/tohspj/articles/V003/111TOHSPJ.pdf. Last accessed on 14 September 2013.
  12. Hsiao, C., & Pesaran, M. H. (2008). Random coefficient panel data models. In L. Mátyás & P. Sevestre (Eds.), The econometrics of panel data. Advances studies in theoretical and applied econometrics (pp. 185–213). Berlin: Springer.Google Scholar
  13. Hsiao, C., Pesaran, M. H., & Tahmiscioglu, A. K. (1999). Bayes estimation of short-run coefficients in dynamic panel data models. In C. Hsiao, K. Lahiri, L. F. Lee, & M. H. Pesaran (Eds.), Analysis of panels and limited dependent variables models (pp. 268–296). Cambridge: Cambridge University Press.Google Scholar
  14. Jönsson, B., & Eckerlund, I. (2003). Why do different countries spend different amounts on health care? In A Disease-based Comparison of Health Systems. What is Best and What Cost? Paris: OECD, pp. 107–120. http://browse.oecdbookshop.org/oecd/pdfs/product/8103031e.pdf, st Accessed 16 January 2014.
  15. Keep, M. (2011) Health Expenditure: International Comparisons. London: House of Commons Library, Standard Notes SN/SG/2584. http://www.parliament.uk/Templates/BriefingPapers/Pages/BPPdfDownload.aspx?bp-id=SN02584. Last accessed on 14 September 2013
  16. Mesa, L. (2011). Determinants of health care expenditure: The Colombian case. Apuntes del CENES, 30(52), 87–102.Google Scholar
  17. OECD Health Data 2001: A comparative analysis of 30 Countries, OECD, Paris, 2001, data sources, definitions and methods. http://stats.oecd.org/glossary/detail.asp?ID=1967. Last accessed on 14 September 2013.
  18. OECD. (2006). Projecting OECD health and long-term care expenditures: what are the main drivers? Economics department Working papers 477. http://www.oecd.org/eco/public-finance/36085940.pdf. Last accessed 16 January 2014.
  19. OECD (2010). Health care systems: Getting more value for money. OECD Economics Department Policy Notes No. 2. http://www.apha.org/NR/rdonlyres/7EE65F33-9F4E−4EBF-8554-DE29461A11F8/0/OECDhealthsystemscompare.pdf. Last accessed on 14 September 2013.Google Scholar
  20. OECD Health Data. (2012). http://stats.oecd.org/Index.aspx?DataSetCode=SHA. Last accessed on 3 August 2013.
  21. OECD Factbook (2012) http://www.oecd-ilibrary.org/economics/oecd-factbook-2011-2012_factbook-2011-en. Last accessed on 3 August 2013.
  22. Oliveira, J., & De la Maisonneuve, C.(2006). The drivers of public expenditure on health and long-termcare: an integrated approach. OECD Economic Studies 43.Google Scholar
  23. Peterson, C. L., & Burton, R. (2007) U.S. Health Care Spending: Comparison with other OECD Countries. Washington DC: Congressional Research Service. digitalcommons.ilr.cornell.edu/key_workplace/311/. Last accessed on 14 September 2013.Google Scholar
  24. Pinheiro, J. C., & Bates, D. (2000). Mixed-effects Models in S and S-PLUS. New York: Springer.CrossRefGoogle Scholar
  25. R Development Core Team (2013). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing, ISBN 3,900051,07,0. http://www.r-project.org/. Last accessed on 3 August 2013.
  26. Reinhardt, U. E., Hussey, P. S., & Anderson, G. F. (2002). Cross-national comparisons of health systems using OECD data, 1999. Health Affairs, 21(3), 169–181.CrossRefGoogle Scholar
  27. Rue, H., Martino, S., & Chopin, N. (2009) Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations (with discussion). Journal of the Royal Statistical Society, Series B, 71, 319–392. http://www.r-inla.org/papers. Last accessed on 3 August 2013.
  28. Schrödle, B., & Held, L. (2011). A premier on disease mapping and ecological regression using INLA. Computational Statistics, 26(2), 241–258.CrossRefGoogle Scholar
  29. Squires, D.A. (2011) The U.S. health system in perspective: A comparison of twelve industrialized nations. The Commonwealth Fund, July 2011, New York.Google Scholar
  30. Squires, D. A. (2012). Explaining high health care spending in the United States: An international comparison of supply, utilization, prices, and quality. The Commonwealth Fund Publication, 1595(10), May 2012, New York http://www.commonwealthfund.org/~/media/Files/Publications/Issue%20Brief/2012/May/1595_Squires_explaining_high_hlt_care_spending_intl_brief.pdf. Last accessed on September 14, 2013.
  31. Sturm, R., An, R., Maroba, J., & Patel, D. (2013). The effects of obesity, smoking, and excessive alcohol intake on healthcare expenditure in a comprehensive medical scheme. South African Medical Journal, 103(11), 840–844.CrossRefGoogle Scholar
  32. The R-INLA project. http://www.r-inla.org/. Last accessed on 3 August 2013.
  33. Thomson, S., Osborn, R., Squires, D. A., & Reed, S. J. (2011). International profiles of health care systems 2011. The Commonwealth Fund, Nov. 2011, New York.Google Scholar
  34. World Health Organization. (2011). Global status report on non-communicable diseases 2010. Geneva: WHO.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Guillem Lopez-Casasnovas
    • 1
    • 2
  • Laia Maynou
    • 3
    • 4
    • 5
    • 6
  • Marc Saez
    • 1
    • 3
    • 4
  1. 1.Center for Research in Health and Economics (CRES)Universitat Pompeu FabraBarcelonaSpain
  2. 2.Department of Economics and BusinessUniversitat Pompeu FabraBarcelonaSpain
  3. 3.Research Group on Statistics, Econometrics and Health (GRECS)University of GironaGironaSpain
  4. 4.CIBER of Epidemiology and Public Health (CIBERESP)BarcelonaSpain
  5. 5.Universitat Autonoma de Barcelona (UAB)Cerdanyola del VallèsSpain
  6. 6.London School of Hygiene and Tropical MedicineLondonUK

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