**3. Research on the efficiency of health‐care systems**

and in the EECA countries, it was equal to 43.5%. The share of funding from government social health insurance in general averaged 63.2% and increased by 5.8 percentage points (p.p.) over the period of 14 years. In the CE countries, it averaged 73.8%, and in the EECA countries, the average amounted to 29.7%. In contrast, only in the former Soviet Union, where the budget system prevails, SHI amounted to 36.3%. In most analysed countries, the share of private and out‐of‐pocket funding is high. The average share of private expenditure in total expenditure on health amounted to 41.2%—in the case of the CE countries, it amounted to 34.0%, and in the case of the EECA countries, it was equal to 56.5%. The share of out‐of‐pocket expenditure in private spending averaged 88.6%, while in the case of the CE countries, it was lower by 1.3 p.p., and in the EECA countries, it was higher by 4.2 p.p. In most post‐communist coun‐ tries, even those where public funding is very low, citizens do not show interest in additional health insurance. In 2013, private prepaid plans accounted for 6% of expenditure on average: 6.9% in the CE countries and 4% in the EECA countries. In the Central Europe, almost 50% of the Slovenian, 40% of Croatian, 7% of Hungarian and 4% Latvian population have prepaid private insurance. In the Eastern Europe and Central Asia, prepaid health insurance was used

by 12% of Georgian, 6% of Armenian and Uzbek as well as 4% of Russian population.

other countries not listed above.

96 Advances in Health Management

The insurance type of health system is not the classic Bismarck model but its modification. The noticeable majority of Central Europe and Balkan peninsula adopted only the method of funding (health insurance contributions), while the organization and governance of health care are organized differently in each of the countries. The health systems in which there are several third‐party payers operate in Czech Republic, Lithuania and Slovakia. Most mecha‐ nisms of the Bismarck model were introduced in the health‐care system of the Czech Republic and Slovakia. The payers in the system are sickness funds, which conclude contracts with ser‐ vice providers. The patients are free to choose the insurance company, and the largest insurer in each of the countries has over 60% market share. In both countries, there are mechanisms of pooling and (re)allocation of contributions ex ante referred to as risk adjustment of contri‐ butions. Only in the Czech system, there is a mechanism to retrospective risk sharing [12]. In Lithuania, there are sickness funds, but their membership is territorial. There is no competition between insurers nor any mechanism of risk adjustment of contributions. On the other hand, health‐care insurance systems with a single payer prevail in Albania, Bosnia and Herzegovina, Bulgaria, Estonia, Hungary, Macedonia, Moldova, Montenegro, Poland, Romania, Serbia and Slovenia. In the post‐Soviet countries of Eastern Europe and Central Asia, centrally planned health systems with less public funding than in the countries of Central Europe prevail—the examples include Azerbaijan, Georgia and Tajikistan. The tendency of the public to purchase prepaid private insurance is not significant, which makes it difficult to access to health care due to lack of financial resources in households. In Kyrgyzstan and Russia, mandatory health insurance was introduced; however, these are supply systems financed from the budget, as in

Kyrgyzstan is the only example of a Central Asian country where the introduction of a health insurance system was successful. SHI is a system complementary in relation to budget financ‐ ing and supplements public funding. In the analysed period, the share of public funds from health insurance increased. At the same time, a successful reform the health infrastructure was implemented—some facilities were closed, but the overall access to health care for all Measuring the efficiency of health‐care systems is not an easy task, and the main difficulty is the correct measurement of the outcomes of the system operation. The most frequently used approach is based on the measurable indirect indicators of services, which by definition have a fundamental effect on the health of the population. The outcomes of the health‐care system can be defined as the change in the state population health that can be attributed to health‐care spending, e.g. life expectancy, infant mortality, inequality in access, incidence of certain diseases, etc. [1]. Although there may be some controversy as to the suitability of some of these variables as important outcomes of health care, most of the analyses conducted on the level of systems use life expectancy and infant mortality to assess the performance of health systems (e.g. Refs. [3, 16–19]). Infant mortality is not a dramatic problem in the developed countries. However, even among members of the Organisation for Economic Co‐operation and Development (OECD), such as Mexico, Chile or Turkey, or in former Soviet republics such as Tajikistan, Turkmenistan or Uzbekistan, this indicator is still high. It is much easier to define the inputs, which, when used properly, determine the overall efficiency. Usually the resource approach is used, based on quantifiable inputs such as the number of physicians or available infrastructure (e.g. number of beds, diagnostic equipment, financial resources, etc.). It is also a common practice to base models on variables indirectly reflecting outputs and inputs, proxies, which is a consequence of the limited availability of relevant data [20].

Given the purpose of this chapter, the review of the literature focuses on the studies of the effectiveness of health systems conducted in the world, treating expenditure and its structure as input and using the DEA method.

The share of public spending in total health‐care expenditure was included as one of the inputs in the study of differences in physicians' effectiveness of improving public health in OECD countries [21]. In addition, the analysis takes into account the number of physicians, the level of GDP per capita, the level of education of the society as well as environmental vari‐ ables: the consumption of alcohol and smoking. The results were based on the life expectancy at birth and at 65 years of age and the number of years of life lost due to heart diseases (for men and women separately) and infant mortality. These variables are commonly used as the outcomes of health‐care systems.

The analysis carried out for the 165 countries for which data were available in the WHO data‐ base shows that the share of public health‐care spending and the size of health‐care spending in public budgets are two factors positively related to the functioning of health‐care systems [1]. A modified DEA model was used, allowing for the introduction of weight restrictions, which increases the discriminatory strength of the method. Two kinds of input, the total expenditure on health per capita and the expected length of education (as an environmental factor), as well as two outputs—good‐health life expectancy and the number of years lost due to disability or premature death—were taken into account. The level of public financing reached 64% in the most effective countries from the sample, whereas in the least efficient ones, the public fund‐ ing did not exceed 50%. It can be said that in the countries whose governments show com‐ mitment to the development and financing of health‐care systems, the available resources are used more effectively while allowing for achieving adequate health outcomes.

A similar approach to creating models of technical effectiveness of health‐care systems can be found in other publications. In the case of OECD countries, a study of the effectiveness of health‐care resources usage, measured by such parameters as the number of physicians, the number of beds per 1000 inhabitants, the number of units of magnetic resonance imag‐ ing (MRI) per million inhabitants or health‐care spending as the percentage of GDP, was conducted [16]. The authors adopted infant mortality rate and life expectancy at birth as the results of such inputs. The extended analyses also take into account the social and environ‐ mental factors, such as the Gini coefficient, school expectancy or tobacco consumption. Two models were built separately for each outcome. Two countries, Iceland and Luxembourg, were eliminated from the analysis due to missing data. An interesting observation is that among the fully efficient countries, such as Sweden, Norway and Japan, there are also those with weak health outcomes, such as Turkey and Mexico. This is due to the fact that the poor performance of these countries is related to their low consumption of resources. This shows that at every level of the achieved health outcomes, a country may be technically efficient or inefficient as regards the use of its resources.

It is emphasized that the maximization of health system outcomes requires a good under‐ standing of the factors included in the health production function. Such an analysis can help the decision makers to understand the conditions for a more efficient operation of health‐care systems better. In their study [19], they used output‐oriented BCC and super efficiency mod‐ els, both with variable returns to scale. As outcomes, the infant mortality rate (IMR) and life expectancy at birth were adopted. As inputs, the number of doctors per 1000 inhabitants, the number of hospital beds per 1000 inhabitants, health expenditure per capita, GDP per capita and consumption of fruit and vegetables per capita were adopted. Two models were built, with different inputs in order to achieve different objectives of the study, i.e. to differentiate the production function, which is mainly based on the expenditure deemed discretionary, that is possible to be controlled by the health system, and the production function, which includes the inputs that are non‐discretionary, that is outside of the possibility of control by the health‐care system. The authors also conducted a regression analysis of the results of measurements of the efficiency, using such explanatory variables as, fat intake as a proxy for the style of life of residents and their behaviours and the unemployment rates and the Gini index as the variables representing the degree of the challenges associated with changes in the social environment affecting the health of the population. Based on the results of the analysis, it can be determined that health‐care systems in nine countries with large and stable economies were identified as efficient when the evaluation of their functioning was based on discretionary inputs (con‐ trolled by health systems), whereas inefficiency was observed when the assessment was based on non‐discretionary inputs that are largely beyond the control of health‐care systems.

the level of GDP per capita, the level of education of the society as well as environmental vari‐ ables: the consumption of alcohol and smoking. The results were based on the life expectancy at birth and at 65 years of age and the number of years of life lost due to heart diseases (for men and women separately) and infant mortality. These variables are commonly used as the

The analysis carried out for the 165 countries for which data were available in the WHO data‐ base shows that the share of public health‐care spending and the size of health‐care spending in public budgets are two factors positively related to the functioning of health‐care systems [1]. A modified DEA model was used, allowing for the introduction of weight restrictions, which increases the discriminatory strength of the method. Two kinds of input, the total expenditure on health per capita and the expected length of education (as an environmental factor), as well as two outputs—good‐health life expectancy and the number of years lost due to disability or premature death—were taken into account. The level of public financing reached 64% in the most effective countries from the sample, whereas in the least efficient ones, the public fund‐ ing did not exceed 50%. It can be said that in the countries whose governments show com‐ mitment to the development and financing of health‐care systems, the available resources are

A similar approach to creating models of technical effectiveness of health‐care systems can be found in other publications. In the case of OECD countries, a study of the effectiveness of health‐care resources usage, measured by such parameters as the number of physicians, the number of beds per 1000 inhabitants, the number of units of magnetic resonance imag‐ ing (MRI) per million inhabitants or health‐care spending as the percentage of GDP, was conducted [16]. The authors adopted infant mortality rate and life expectancy at birth as the results of such inputs. The extended analyses also take into account the social and environ‐ mental factors, such as the Gini coefficient, school expectancy or tobacco consumption. Two models were built separately for each outcome. Two countries, Iceland and Luxembourg, were eliminated from the analysis due to missing data. An interesting observation is that among the fully efficient countries, such as Sweden, Norway and Japan, there are also those with weak health outcomes, such as Turkey and Mexico. This is due to the fact that the poor performance of these countries is related to their low consumption of resources. This shows that at every level of the achieved health outcomes, a country may be technically efficient or

It is emphasized that the maximization of health system outcomes requires a good under‐ standing of the factors included in the health production function. Such an analysis can help the decision makers to understand the conditions for a more efficient operation of health‐care systems better. In their study [19], they used output‐oriented BCC and super efficiency mod‐ els, both with variable returns to scale. As outcomes, the infant mortality rate (IMR) and life expectancy at birth were adopted. As inputs, the number of doctors per 1000 inhabitants, the number of hospital beds per 1000 inhabitants, health expenditure per capita, GDP per capita and consumption of fruit and vegetables per capita were adopted. Two models were built, with different inputs in order to achieve different objectives of the study, i.e. to differentiate the production function, which is mainly based on the expenditure deemed discretionary, that is

used more effectively while allowing for achieving adequate health outcomes.

outcomes of health‐care systems.

98 Advances in Health Management

inefficient as regards the use of its resources.

Some publications that apply to researching the effectiveness of health systems in post‐ communist countries are discussed below. The analysis covered the health outcomes of Croatia and Slovak Republic in the context of other countries from Central and Eastern Europe (CEE). Although the overall health spending efficiency of the CEE countries is on par with that of the OECD, substantial inefficiencies occur in the process of transforming intermediate health inputs into health outcomes. High levels of cost‐effectiveness reflect relatively low prices for labour; hence despite the low level of spending, the resources of health care are relatively high. Given the favourable ratio of public to private spending and available resources, it can be said that the health outcomes of the populations could be improved. The authors propose a stimulated development of private insurance by restricting the basic benefit package pro‐ vided by public spending. Also the costs of pharmaceuticals should be restricted by replacing the original drugs with their generic counterparts and negotiating prices for the reimbursed drugs. Efficiency may also be enhanced by reducing reliance on hospital care. This can be done through the better use of hospital beds and outpatient contacts, as well as by reducing the number of beds [22–24].

S. Mirmirani, H. Li and A. Ilacqua compared the efficiency of health systems in eight selected post‐Soviet countries with average results for the OECD countries. The study was conducted for the years 1997–2001. The inputs used included per capita health‐care expenditure in USD, PPP, number of inpatient hospital beds per thousand population, number of physicians per thousand population and the percentage of children with measles inoculation. The "immu‐ nization" is used as a proxy variable. The average life expectancy of both sexes at birth and infant mortality rates is used as output variables [18].
