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Attitudes of Germans towards distributive issues in the German health system

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Abstract

Social health care systems are inevitably confronted with the scarcity of resources and the resulting distributional challenges. Since prioritization implies distributional effects, decisions regarding respective rules should take citizens’ preferences into account. In this study we concentrate on two distributive issues in the German health system: firstly, we analyze the acceptance of prioritizing decisions concerning the treatment of certain patient groups, in this case patients who all need a heart operation. We focus on the patient criteria smoking behavior, age and whether the patient has or does not have young children. Secondly, we investigate Germans’ opinions towards income-dependent health services. The results reveal the strong effects of individuals’ attitudes regarding general aspects of the health system on priorities, e.g. that individuals with an unhealthy lifestyle should not be prioritized. In addition, experience of limited access to health services is found to have a strong influence on citizens’ attitudes, too. Finally, decisions on different prioritization criteria are found to be not independent.

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Notes

  1. The translation of the respective German questions into English can be found in Appendix 2.

  2. The translation of the German question into English can be found in Appendix 2.

  3. The issue is discussed by the German public under the term “two-tier medicine”. For a reflection on arguments related to this issue, cf. Breyer and Kliemt [11].

  4. We do not take further aspects of the respondent’s situation into account that may influence her egoistic view, like e.g. experiences with illnesses or the impact of some reference point. We focus solely on a similarity to one of the characteristics of the patients described in the questionnaire.

  5. The exact wording in the questionnaire of the ISSP survey is: “Is it fair or unfair that people with higher incomes can afford better health care than people with lower incomes? (1) very fair, (2) somewhat fair, (3) neither fair nor unfair, (4) somewhat unfair and (5) very unfair”, with “can’t choose” also admissible (about 57 observations). However, the latter are disregarded from the regression.

  6. Although variables within this group seem to be highly correlated with each other, the correlation matrix as well as the variance inflation factor (VIF) does not indicate any problems of multicollinearity in the estimations. The correlation matrix and the VIF statistics are available upon request. We have also tested whether the inclusion or deletion of one or more variables affect our results. However, the results prove robust.

  7. We have also tested whether these variables affect prioritizing decisions but found no significant effects.

  8. The correlation between the variables no access health care and reason: unhealthy behavior is 0.08. Though both variables seem to measure nearly the same, they are distinctly different. Whereas no access health care covers attitudes about who should receive publicly funded health services, the variable reason: unhealthy behavior reflects individuals’ conviction of the causes of severe health problems.

  9. Although the number of households with three or more children is very low, results of the empirical analysis do not change if alternative specifications are used. Results are available upon request.

  10. This reduces the sample by 36 observations.

  11. We do not expect a potential endogeneity of either of the dependent variables. Thus, we refrain from estimating a recursive multivariate probit model [29] as this would require some theoretical advice on the dependency of the prioritizing decision questions.

  12. We also tested whether the parallel lines assumption of the standard ordered probit model holds or whether to apply a generalized ordered probit model. However, results of a likelihood-ratio test and a Brant test were not able to reject the hypothesis of equal coefficients. Thus, we proceed with the standard ordered probit model.

  13. Results of the restricted model as well as the full estimation results of the full specified model can be found in the Appendix.

  14. We have also run separate binary probit models of the three dependent variables. Results of these models can be found in the Appendix. Comparing the results of the multivariate probit models to the estimation of single probit models shows some differences regarding the level of significance of the coefficients while the magnitude of the coefficients are almost unchanging. This figure supports the use of multivariate probit models to estimate the underlying prioritizing decisions.

  15. We have also tested whether a specification with the original 5-item Likert scale (without combining categories one and two) changes the findings. However, the results prove very robust whether we use a 4-item or 5-item scale of the dependent variable inequality reduction. Results are available upon request.

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Acknowledgments

We thank two anonymous referees for very helpful comments and suggestions. The authors thank Mathias Kifmann, Robert Nuscheler, Lars Schwettmann, and the participants of the Annual Meeting of the German Association of Health Economics (dggö) in Munich 2014 and the 10th World Congress of iHEA and ECHE in Dublin 2014. All remaining errors are ours.

Author information

Authors and Affiliations

  1. Department of Economics, Microeconomics and Public Finance, Martin-Luther-University of Halle Wittenberg, Halle (Saale), Germany

    Marlies Ahlert

  2. Department of Law and Economics, Institute of Public Finance, University of Bayreuth, Bayreuth, Germany

    Christian Pfarr

Authors
  1. Marlies Ahlert
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  2. Christian Pfarr
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Correspondence to Christian Pfarr.

Appendices

Appendix 1

See Tables 6, 7, 8, 9, 10, 11 and 12.

Table 6 Estimation results single probit models—non-smoker vs no-difference
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Table 7 Estimation results single probit models—young vs no-difference
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Table 8 Estimation results single probit models—having children vs. no-difference
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Table 9 Full estimation results of the multivariate probit model—restricted specification
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Table 10 Full estimation results of the multivariate probit model—full specification
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Table 11 Estimation results of ordered probit models for judgment of inequality
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Table 12 Estimation results of a binary probit model for general prioritizing behavior
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Appendix 2: questions for the dependent variables

Prioritization criterion: smoking behavior

“Suppose two equally sick people need the same heart operation. One does not smoke, the other is a heavy smoker. In your opinion who should get the operation first?”

Answers: (1) the non-smoker, (2) the heavy smoker, (3) their smoking habits should make no difference and (4), can’t choose

Prioritization criterion: age

“Now, suppose two equally sick people need the same heart operation. One is aged 30, the other 70. In your opinion who should get the operation first?”

Answers: (1) the 30 year old, (2) the 70 year old, (3) their ages should make no difference and (4), can’t choose

Prioritization criterion: children

“Now, suppose two other equally sick people need the same heart operation. One has young children, the other does not have young children. In your opinion who should get the operation first?”

Answers: (1) the one who has young children, (2) the one who has no young children, (3) having young children should make no difference and (4), can’t choose

Judgment of inequality:

“Is it fair or unfair that people with higher incomes can afford better health care than people with lower incomes?”

Answers: (1) very fair, (2) somewhat fair, (3) neither fair nor unfair, (4) somewhat unfair, (5) very unfair and (6), can’t choose.

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Ahlert, M., Pfarr, C. Attitudes of Germans towards distributive issues in the German health system. Eur J Health Econ 17, 471–496 (2016). https://doi.org/10.1007/s10198-015-0693-x

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  • DOI: https://doi.org/10.1007/s10198-015-0693-x

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