Tag: Czech Republic

Managed Competition in Health Insurance Systems in Central and Eastern Europe

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This policy brief summarizes common trends in the development of health care systems in the Czech Republic, Slovakia, and Russia in late 1990s–early 2000s. These countries focused on regulated competition between multiple health insurance companies. However, excessive regulation led to various deficiencies of the model. In particular, improvements in such quality indicators of the three health care systems as infant and under-five mortality are unrelated to the presence of multiple insurers or insurer competition.

A number of transition countries in Central and Eastern Europe and the former Soviet Union introduced health care systems with compulsory enrollment, obligatory insurance contributions unrelated to need and coverage according to a specified package of medical services. This so-called social health insurance (SHI) model (Culyer, 2005) is regarded as a means for achieving universal coverage, stable financial revenues, and consumer equity  (Balabanova et al. 2012; Gordeev et al., 2011; Zweifel and Breyer, 2006; Preker et al., 2002). While most transition countries chose to only have a single health insurance provider on the market, the Czech Republic, Slovakia, and Russia allowed competitive (and often private) insurers in the new system. However, the evidence from the three countries shows excessive regulation of health insurers and limited instruments for insurer competition within indebted post-reform health care systems (Naigovzina and Filatov, 2010; Besstremyannaya, 2009; Medved et al., 2005). Consequently, the three countries may have been over-enthusiastic in putting large emphasis on market forces in the reorganization of health care systems in economies with a legacy of central planning (Diamond, 2002).

This brief addresses the results of Besstremyannaya (2010), which assesses the impact of private health insurance companies on the quality of health care system. While various performance measures reflect different goals of national and regional health care systems (Joumard et al., 2010; Propper and Wilson, 2006; OECD, 2004; WHO, 2000), aggregate health outcomes directly related to the quality of health care are commonly infant and under-five mortality (Lawson et al., 2012; Gottret and Schieber, 2006; Wagstaff and Claeson, 2004; Filmer and Pritchett, 1999). Consequently, Besstremyannaya’s (2010) analysis regards mortality indicators as variables reflecting the overall quality of health care system.

The estimations employ data on Russian regions in 2000-2006. The results indicate that regions with only private health insurers have lower infant and under-five mortality. However, given the low degree of competition on the social health insurance market in Russia, we hypothesize that this effect is mostly driven by positive institutional reforms in those regions. Indeed, incorporating the effect of institutional financial environment, we find that the impact of private health insurers becomes insignificant.

Development of a Social Health Insurance Model in the Czech Republic, Slovakia, and Russia

At the beginning of their economic transition, the Czech Republic, Slovakia, and Russia established a model for universal coverage of citizens by mandatory health insurance (Balabanova et al., 2012; Medved et al., 2005; Sheiman, 1991). The revenues of the new SHI system came from a special payroll tax and from government payments for health care provision to the non-working population. The main reason for combining certain features of taxation-based and insurance-based systems was the desire to establish mandatory health insurance as a reliable source of financing in an environment with unstable budgetary revenues (Lawson and Nemec, 2003; Preker et al., 2002; Sheiman, 1994). The insurance systems instituted in the three transition countries correspond to the major SHI principles implemented in Western Europe: contributions by beneficiaries according to their ability to pay; transparency in the flow of funds; and free access to care based on clinical need (Jacobs and Goddard, 2002).

The Czech Republic, Slovakia, and Russia placed emphasis on regulated competition, decreeing that SHI should be offered by multiple private insurance companies with a free choice of the insurer by consumers. Managers of private insurance companies were assumed to perform better than government executives (Lawson and Nemec, 2003; Sinuraya, 2000; Curtis et al., 1995), so an intermediary role for private insurance companies was seen as a key instrument for introducing market incentives and improving the quality of the health care system (Sheiman, 1991).

However, the activity of health insurance companies in the three countries was heavily regulated, since the content of benefit packages, size of subscriber contributions, and the methods of provider reimbursement were decided by government, and tariffs for health care were frequently revised (Lawson et al., 2012; Rokosova et al., 2005; Zaborovskaya et al., 2005; Praznovcova et al., 2003; Hussey and Anderson, 2003). In particular, Russian health care authorities enforced rigid assignments of areas, whose residents were to be served by a particular health insurance company (Twigg, 1999) and imposed informal agreements with health insurance companies to finance providers regardless of the quality and quantity of the health care (Blam and Kovalev, 2006). As a result, the three countries experienced an initial emergence of a large number of health insurance companies, followed by mergers between them, resulting in high market concentration (Sergeeva, 2006; Zaborovskaya et al., 2005; Medved et al., 2005).

In Russia, the Health Insurance Law (1991) specified that until private insurers appeared in a region, the regional SHI fund or its branches could play the role of insurance companies. Therefore, several types of SHI systems emerged in Russian regions in the 1990s and early 2000s: the regional SHI fund might be the only agent on the SHI market; the regional SHI fund might have branches, acting as insurance companies; SHI might be offered exclusively by private insurance companies; or SHI might be offered by both private insurance companies and branches of the regional SHI fund (Figure 1). The variety of SHI systems reflects the fact that many regions opposed market entry by private insurance companies (Twigg, 1999). Indeed, the boards of directors of regional SHI funds usually included regional government officials (Tompson, 2007; Tragakes and Lessof, 2003) who were reluctant to reduce government control over SHI financing sources (Blam and Kovalev, 2006; Twigg, 2001). The controversy with health insurance legislation created a substantial confusion at the regional and the municipal level (Danishevski et al., 2006).

Figure 1. Health insurance agents in Russia in 2000-2006, (number of regions)

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This context suggests that Russian regions provide an interesting study field to address the impact of private health insurance companies on the quality of health care system. In particular, the wide variety of SHI systems across Russian regions, as well as the gradual introduction of the health insurance model in Russia provide a sufficient degree of variation in practices and outcomes to allow for a well-specified empirical analysis.

Data and Results

In our analysis we use data on Russian regional economies between 2000 and 2006 (as based on data availability). Our measures of health outcomes are given by the pooled regional data on infant and under-five mortality. Our key explanatory variable is the presence of only private health insurers in the region. Arguably, the coexistence of public and private health insurance companies does not enable effective functioning of private health insurers owing to their discrimination by the territorial health insurance fund. Therefore, in the empirical estimations we focus on the presence of only private health insurers in the region, regarding it as a measure of effective health insurance model.    The analysis also employs a variety of important socio-economic and geographic variables influencing health outcomes (per capita gross regional product (GRP), share of private and public health care expenditure in gross regional product, share of urban population, average temperature in January).

The results of the first set of our empirical estimations demonstrate that the presence of only private health insurers in a region leads to lower infant and under-five mortality. Furthermore, an increase in the share of private health care expenditure in GRP leads to a decrease in both mortality indicators. The result is consistent with numerous findings about the association between personal income and health status in Russia (Balabanova et al., 2012; Sparling, 2008).

Prospective reimbursement of health care providers is associated with a decrease in infant and under-five mortality. The finding suggests the existence of a quasi-insurance mechanism in the Russian SHI market. Operating in an institutional environment where provider reimbursement is based on prospective payment, private insurance companies in effect shift a part of their risk to providers (Glied, 2000; Sheiman, 1997; Chernichovsky et al., 1996).

Table 1. Factors leading to decreased infant and under-five mortality in Russia

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Notes: * indicates that the coefficient is statistically significant in a parametric regression

Although our analysis shows that the presence of only private health insurers is statistically associated with improvements in infant and under-five mortality, we believe that the influence is indirect. Namely, the overall positive institutional environment in the region may result in both a decrease of mortality indicators and a lower coercion of regional authorities towards the presence of private health insurance companies.

To test this hypothesis, we use financial risk in a region as a measure of institutional environment and incorporate it in the analysis through an instrumental variable approach. (We measure financial risk by an expertly determined rank ordered variable by RA expert rating agency; this variable reflects the balance of the budgets of enterprises and governments in the region, with lower ranks corresponding to smaller risk.)

In line with our hypothesis, the results suggest that the presence of private health insurance companies now becomes insignificant in explaining infant and under-five mortality.

Discussion

The existing literature suggests that the improvement in infant and under-five mortality in the Czech Republic, Slovakia, and Russia can be attributed primarily to an increase of health care spending (Gordeev et al. 2011; Besstremyannaya, 2009; Lawson and Nemec, 2003) rather than being an effect of the social health insurance model with multiple competing insurers. It should be noted that insufficient government payments for the non-working population and a decline of the gross domestic product in the early transition years left SHI systems in the three countries indebted (Naigovzina and Filatov, 2010; Sheiman, 2006; Medved et al., 2005), which undermined the development of the managed competition in the health care provision.

In Russia (and also in the Czech Republic and Slovakia) there is little competition between insurers, and surveys show that the main factors causing consumers to change their health insurance company are change of work or residence, and not dissatisfaction with the insurer (Baranov and Sklyar, 2009). The fact that law suits on defense of SHI patient rights are rarely submitted to courts through health insurers (Federal Mandatory Health Insurance Fund, 2005) may also be evidence of the failure of Russian health insurance companies to win customers on the basis of their competitive strengths.

Summary and Policy Implications

The above findings as well as the other mentioned literature suggest that improvements of infant and under-five mortality in the Czech Republic, Slovakia, and Russia are not associated with the positive role of managed competition in the social health insurance system. In particular, in Russia the decrease in infant and under-five mortality is likely to be related to financial environment, rather than the existence of insurance mechanisms or competition between health insurance companies. One possible explanation of this absence of effect may come from the excessive regulation of the private insurance markets, as well as the insufficient competition between insurers. Importantly, the health insurance reform, implemented in Russia in 2010, both addressed underfinancing (by raising payroll tax rates) and took a step towards fostering provider competition, by allowing private providers to enter the social health insurance market (Besstremyannaya 2013). However, insurance companies are still not endowed with effective instruments for encouraging quality by providers, which may greatly undermine their efficiency.

References

  • Balabanova D, Roberts B, Richardson E, Haerpfer C, McKee V. 2012. Health Care Reform in the Former Soviet Union: Beyond the Transition. Health Services Research  47(2): 840-864.
  • Baranov IN, Sklyar TM. 2009. Problemy strakhovoi modeli zdravookhraneniya na primere Moskwy i Sankt-Peterburga (Problems of insurance model in health care: the example of Moscow and Saint Petersburg). In X International Conference on the Problems of Development of Economy and Society, Yasin E.G (ed),  Moscow: Higher School of Economics, vol.2.
  • Besstremyannaya GE. 2013. Razvitie systemy obyazatelnogo meditsinskogo strakhovaniya v Rossijskoi Federatsii (Development of the Mandatory Health Insurance system in the Russian Federation)  Federalizm 3: 201-212
  • Besstremyannaya GE. 2010. Essays in Empirical Health Economics. PhD thesis. Keio University (Tokyo).
  • Besstremyannaya GE. 2009. Increased public financing and health care outcomes in Russia. Transition Studies Review 16: 723-734.
  • Blam I, Kovalev S. 2006. Spontaneous commercialization, inequality and the contradictions of the mandatory medical insurance in transitional Russia. Journal of International Development 18: 407–423.
  • Culyer AJ (2005)  The Dictionary of Health Economics, Edward Elgar.
  • Danishevski K, Balabanova D, McKee M, Atkinson S. 2006. The fragmentary federation: experiences with the decentralized health system in Russia. Health Policy and Planning 21: 183–194.
  • Gordeev VS, Pavlova M, Groot W. 2011. Two decades of reforms. Appraisal of the financial reforms in the Russian public healthcare sector. Health Policy 102(2-3): 270-277.
  • Hussey P, Anderson GF. 2003. A comparison of single- and multi-payer health insurance systems and options for reform. Health Policy 66: 215-228.
  • Jacobs R, Goddard M. 2002. Trade-offs in social health insurance systems. International Jthenal of Social Economics 29(11): 861-875.
  • Lawson C, Nemec J, Sagat V. 2012. Health care reforms in the Slovak and Czech Republics 1989-2011: the same or different tracks? Ekonomie a management  1, 19-33.
  • Lawson C, Nemec J. 2003. The political economy of Slovak and Czech health policy: 1989-2000. International Political Science Review 24(2): 219-235.
  • Medved J, Nemec J, Vitek L. 2005. Social health insurance and its failures in the Czech Republic and Slovakia: the role of the state. Prague Economic Papers 1:64-81.
  • Praznovcova L, Suchopar J, Wertheimer AI. 2003. Drug policy in the Czech Republic. Jthenal of Pharmaceutical Finance, Economics and Policy 12(1): 55-75.
  • Preker AS, Jakab M, Schneider M. 2002. Health financing reforms in Central and Eastern Europe and the former Soviet Union, in Funding Health Care: Options for Europe, Mossalos E., Dixon A., Figueras J., Kutzin J. (Eds.), European Observatory on Health Care Systems Series: Open University Press, 2002.
  • Rokosova M, Hava P, Schreyogg J, Busse R. 2005. Health care systems in transition: Czech Republic. Copenhagen, WHO Regional Office for Europe on behalf of the European Observatory on Health Systems and Policies.
  • Sheiman I. 1991. Health care reform in the Russian Federation. Health Policy 19: 45–54.
  • Sheiman I. 2006. O tak nazyvaemoi konkurentnoi modeli obyazatelnogo meditsinskogo strahovaniya (On so-called competitive model of mandatory health insurance). Menedzher Zdravoohraneniya 1: 52-58.
  • Sheiman I. 1997. From Beveridge to Bismarck: Health Financing in the Russian Federation’. In Innovations in Health Care Financing, Schieber G. (ed.), Discussion Paper 365, 1997, Washington DC: The World Bank.
  • Sinuraya T. 2000. Decentralization of the health care system and territorial medical insurance coverage in Russia: friend or foe? European Jthenal of Health Law 7:15–27.
  • Sparling AS. 2008. Income, drug, and health: evidence from Russian elderly women. PhD dissertation. University North Carolina at Chapel Hill, UMI Dissertations Publishing.
  • Tompson W. 2007.  Healthcare reform in Russia: problems and perspectives. Working Papers 538, OECD Economics Department
  • Tragakes E, Lessof S. 2003.Russian Federation, Health Care Systems in Transition, The European Observatory, WHO, Europe.
  • Twigg J. 1999. Obligatory medical insurance in Russia: the participants’ perspective. Social Science and Medicine 49: 371–382.
  • Twigg, JL. 2001. Russian healthcare reform at the regional level: status and impact. Post-Soviet Geography and Economics 42: 202–219.
  • Zaborovskaya AS, Chernets VA, Shishkin SV. 2005. Organizatsiya upravleniya  i finansirovaniya zdravoohraneniyem v subjektah Rossijskoi Federatsii v 2004 godu (Organization of management and finance of healthcare in Russian regions in 2004)
  • Zweifel P, Breyer F. The economics of social health insurance. In The Elgar Companion to Health Economics, Jones A. (ed.), Edward Elgar, 2006.
  • Wagstaff A. 2010. Social health insurance reexamined. Health Economics 19: 503–517.

Old-Age Poverty and Health – How Much Does Income Matter?

20130930 Old-Age Poverty and Health Image 01

The question concerning the material situation of older people and its consequences for their wellbeing seems to be more important than ever. This is especially true given rapid demographic changes in the Western World and economic pressures on governments to reduce public spending.  We use data from the Survey of Health, Ageing and Retirement in Europe (SHARE) to examine different aspects of old-age poverty and its possible effects on deterioration in health. The data contains information on representative samples from 12 European countries including the Czech Republic and Poland. We use the longitudinal dimension of the data to go beyond cross sectional associations and analyze transitions in health status controlling for health in the initial period and material conditions. We find that poverty matters for health outcomes in later life. Wealth-defined and subjective poverty correlates much more strongly with health outcomes than income-defined measure. Importantly subjective poverty significantly increases mortality by 58.3% for those aged 50–64 (for details see Adena and Myck, 2013a and 2013b). 

Measuring Poverty

When measuring poverty, the standard approach is to define the poverty threshold at 60% of median equalized income. This standardized measure offers some advantages, such as simplicity and comparability with already existing studies. However, there are valid arguments against its use when analyzing old-age poverty. The permanent-income theory provides arguments against current income as a major determinant of quality of life of older people. Moreover, poverty defined with respect to current income while taking account of household size through equalization, ignores other important aspects of living costs such as disability or health expenditures. Additionally, most analysis using income-poverty measures ignore such aspects as housing ownership and housing costs.

Our analysis examines different aspects of poor material conditions of the elderly. The first poverty definition refers to respondents’ wealth as an alternative to income-defined poverty. Poor households, defined with reference to wealth (“wealth poverty” – WEALTH), are those that belong to the bottom third of the wealth distribution of the sample in each country. For this purpose, household wealth is the sum of household real assets (net of any debts) and household gross financial assets. Secondly, we compare the above poverty measures to a subjective measure of material well-being. This measure is based on subjective declarations by respondents, in which case (“subjective poverty” – SUB) individuals are identified as poor on the basis of a question of how easily they can make ends meet. If the answer is “with some” or “with great” difficulty, individuals in the household are classified as “poor”.

One reflection of potential problems with the standard income poverty measure becomes visible when it is compared with the subjective measure. The graph below shows the differences in country rankings when using one or the other poverty measure.  The country with the greatest disproportion is Czech Republic. While being ranked as second according to the income measure, it is ninth according to the subjective measure.

Figure 1. Country Ranks in Old-Age Poverty According to an Income versus a Subjective Measure

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Source: Authors’ calculations using SHARE data (Wave 2, release 2.5.0).

Even more striking is the fact that the differences between ranks are not because of over or under classification of individuals as poor, but rather because of misclassification. Figure 2 shows that there is little overlap between different poverty measures. The share of individuals classified as poor according to all three measures is only 7.95%, whereas it is 60% according to at least one of the measures.

Figure 2. Poverty Measure Overlap

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Notes: Data weighted using Wave 2 sample weights. Source: Authors’ calculations using SHARE data (Wave 2, release 2.5.0).
 

Measuring Well-Being

We examine three binary outcomes measuring the well-being of the respondents – two reflecting physical health, and one measuring individuals’ subjective health. The two measures of physical health are generated with reference to the list of twelve symptoms of bad health and the list of twenty-three limitations in activities of daily living (ADLs). In both cases, we define someone to be in a bad state if they have three or more symptoms or limitations. The two definitions are labelled as: “3+SMT” (three or more symptoms) and “3+ADL” (three or more limitations in ADLs). Subjective health “SUBJ” is defined to be bad if the subjective health assessment is “fair” or “poor”. Finally, we also analyze mortality as an “objective” health outcome.

Poverty and Transitions in Well-Being and Health

There is some established evidence in the literature that poverty negatively affects health and other outcomes at different stages of life.[1] At the same time, there is little evidence on how the choice of the poverty measure might result in under- or over-estimation of the effects of poverty. We address this question by examining different poverty measures as potential determinants of transitions from good to bad states of health.

The results confirm that living in poverty increases an individual’s probability of deterioration of health. In a compact form, Figure 3 presents our results from 12 separate regressions (4 outcomes, three poverty measures). Here we report the odds ratios related to the respective estimated poverty dummies. Individuals classified as poor according to the income measure are 37.7% more likely to report bad subjective health in a later wave of the survey than their richer counterparts; they are 4.5% more likely to suffer from 3 or more symptoms; 18.7% more likely to suffer from 3 or more limitations; and 5% more likely to die. The last three effects, however, are not statistically significant.

In contrast, the effects of wealth-defined poverty and subjectively assessed poverty are 2-8 times stronger than those of income poverty, and they are also significant for all outcomes but death. Overall, wealth-defined poverty and subjective assessment of material well-being strongly correlate with deterioration in physical health (exactly the same goes for improvements in health, see Adena and Myck 2013b).

Figure 3. Poverty and Transitions from Good to Bad States Overlap

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Notes: Data weighted using Wave 2 sample weights. Source: Authors’ calculations using SHARE data (Wave 2, release 2.5.0, Wave 3, release 1, Wave 4, release 1).
 

Poverty and Mortality in the Age Group 50-64

Our analysis reveals differences between age groups and confirms the decreasing importance of income (and thus income defined poverty) with age. As compared to the average effects presented in Figure 3, for the younger age group 50–64 income poverty proves more important as a determinant of bad outcomes, with transition probabilities between 20 and 40% for all outcomes (see Figure 4). The magnitudes are closer to those of other poverty measures, but still lower in all cases. Importantly, we find that wealth-defined and subjective poverty is an important determinant of death in the age group 50–64.

Figure 4. Poverty and Transitions from Good to Bad States 50-64 Slide3
Notes: Data weighted using Wave 2 sample weights. Source: Authors’ calculations using SHARE data (Wave 2, release 2.5.0, Wave 3, release 1, Wave 4, release 1).
 

Conclusions

The role of financial conditions for the development of health of older people significantly depends on the measure of material well-being used. In this policy brief, we defined poverty with respect to income, subjective assessment, and relative wealth. Of these three, wealth-defined poverty and subjective assessment of material well-being strongly and consistently correlate with deterioration and improvements in physical and subjective health. We found little evidence that relative income poverty plays a role in changes in physical health of older people. This suggests that the traditional income measure of household material situation may not be appropriate as a proxy for the welfare of older populations, and may perform badly as a measure of improvements in their quality of life or as a target for old-age policies. To be valid, such measures should cover broader aspects of financial well-being than income poverty. They could incorporate aspects of wealth and the subjective assessment of material situations as well as indicators more specifically focused on the consumption baskets of the older population.

References

  • Adena, Maja and Michal Myck (2013a): “Poverty and transitions in key areas of quality of life”, in: Börsch-Supan, Axel,  Brandt, Martina , Litwin, Howard and Guglielmo Weber (eds.) “Active Ageing and Solidarity between Generations in Europe – First Results from SHARE after the Economic Crisis.”
  • Adena, Maja and Michal Myck (2013b) Poverty and Transitions in Health, IZA Discussion Paper 7532, IZA-Bonn.

 


[1] For a literature review, see our publications.