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Exploring the disparities of regional health care expenditures in Switzerland: some empirical evidence

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Abstract

This study investigates the determinants of regional variations in health care expenditures (HCE) in Switzerland, since there are significant differences between cantons per capita HCE. The empirical analysis contributes to the discussion on the outcome of federalism in the Swiss health care system by improving the understanding of the determinants of the differences in HCE. Our econometric estimations indicate that HCE are significantly related to the density of specialist physicians, density of dispensing doctors, per capita income, proportion of managed care, medical and technological progress and socio-economic factors. Due to the presumptive importance of the organisation of ambulatory care, we suggest policy makers should particularly concentrate on promoting the supply of managed care models in Switzerland. Supporting the development of managed care may help to countervail some of the influences which tend to lead to higher cantonal health expenditures.

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Notes

  1. The 26 Swiss cantons are Aargau (AG), Appenzell Outer-Rhodes (AR), Appenzell Inner-Rhodes (AI), Basel-Land (BL), Basel-City (BS), Berne (BE), Fribourg (FR), Geneva (GE), Glarus (GL), Grisons (GR), Jura (JU), Lucerne (LU), Neuchatel (NE), Nidwalden (NW), Obwalden (OW), Schaffhausen (SH), Schwyz (SZ), Solothurn (SO), St. Gall (SG), Thurgau (TG), Ticino (TI), Uri (UR), Vaud (VD), Valais (VD), Zug (ZG), Zurich (ZH).

  2. The description of the data set is in Sect. “Data and methods”.

  3. Self-assessed health status "good or very good" in % of population over 15 years of age, 2007: Total Switzerland 86.8%, German-speaking region 87.6%, French-speaking region 85.2% and Italian-speaking region 81.3% [13].

  4. A detailed overview of international health economics and health statistical literature can be found in [21] and in the overview presented by Gerdtham and Jönsson [14].

  5. The proportion of the population insured in a managed care model is utilised as a proxy for the positive effect of gatekeeping found by research performed by Gerdtham et al. [19].

  6. Various corrections were performed since part of the data basis was functionally clearly false, due to erroneous data transmission from the cantons. The affected cantons were Appenzell Ausser-Rhodes, Appenzell Inner-Rhodes, Grisons and Jura.

  7. Managed Care models include Health Maintenance Organisations (HMO) and Family doctor models.

  8. Santésuisse is the Association of health insurers in Switzerland.

  9. IHA-IMS Health is one of the largest companies for market intelligence and accountability in global health care.

  10. BAK Basel Economics provides empirical economic research and forecasts for the overall economy.

  11. Since this is the only variable with missing data in 1997, the missing values in 1997 are imputed with the values of 1998 for the analysis.

  12. Since the dummy variable LAT is dichotomous, a log-transformation makes no sense.

  13. Chi-square = 43,9, df = 13, p < 0,000.

  14. A Case-Mix-Index (CMI) variable was estimated in a separate model with the identical variables of the study for the years 2001–2007, since no data was available for prior years. The findings showed the CMI to be not statistically significant. Therefore, we dropped this exogenous variable in favour of a longer time period.

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Author information

Authors and Affiliations

  1. Department for Public Health, Information Systems and HTA, UMIT University of Health Sciences, Medical Informatics and Technology, Eduard Wallnöfer Zentrum 1, 6060, Hall in Tyrol, Austria

    Oliver Reich & Magdalena Thöni

  2. Section Methods and Statistics, Faculty of Social Science, Ruhr-Universität Bochum, 44780, Bochum, Germany

    Cornelia Weins

  3. Department for Medical Sciences and Management, UMIT University of Health Sciences, Medical Informatics and Technology, Eduard Wallnöfer Zentrum 1, 6060, Hall in Tyrol, Austria

    Claudia Schusterschitz

Authors
  1. Oliver Reich
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  2. Cornelia Weins
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  3. Claudia Schusterschitz
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  4. Magdalena Thöni
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Corresponding author

Correspondence to Oliver Reich.

Appendix

Appendix

See Table 3.

Table 3 Econometric results: random-effects model (RE)
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Reich, O., Weins, C., Schusterschitz, C. et al. Exploring the disparities of regional health care expenditures in Switzerland: some empirical evidence. Eur J Health Econ 13, 193–202 (2012). https://doi.org/10.1007/s10198-011-0299-x

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