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Verhoeven, Marijn, Victoria Gunnarsson and Stéphane Carcillo, 2007, “Education and Health in G–7 Countries: Meeting the Challenge of Achieving Better Outcomes with Less Spending,” International Monetary Fund, mimeo
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Prepared by Sergio Lugaresi (fiscal expert), Victoria Gunnarsson, and Marijn Verhoeven (both FAD).
An opinion poll found that 74 percent of respondents disagreed with the introduction of the health care reforms, compared with 35 percent of the respondents opposing pension reform (Jevčák, 2006).
Public expenditure on health care as ratio to GDP is projected at 5.3 percent in 2007 and expected to decline to 5.1 percent during 2008-09 (see Table 3).
After declining slightly in 2007, owing to the reduction in the VAT rate for most pharmaceuticals, the cost of pharmaceuticals is likely to resume its upward trend from 2008 onward, in line with envisaged trends of international pharmaceutical prices.
Spending is measured in PPP terms in order to be able to compare expenditure levels across countries. More conventional measures of spending would bias such a comparison. For example, spending measured as a percent of GDP underestimates the purchasing power of spending in richer countries relative to poorer countries (because a comparable package of health services will cost less as a percent of GDP in the richer country). At the same time, richer countries should be expected to spend more on health care in PPP terms; as populations grow wealthier, they are likely to consume a larger and more varied package of social services leading to increased spending (Wagner effect).
The international comparison of efficiency is carried out using Data Envelope Analysis (DEA). DEA estimates overall spending efficiency of the use of inputs (i.e., health expenditure) in ‘producing’ outputs (i.e., health outcomes). The methodology derives from the literature on the estimation of production functions (See Verhoeven, Gunnarsson, and Carcillo (2007) for a description of the methodology). DEA has the advantage of being sparse in its assumptions about the characteristics of the production technology. This is particularly important for assessing spending efficiency, because little is known about the nature of the relationship between spending, intermediate outputs, and outcomes. The sample of countries included in the analysis are OECD countries (except Mexico and Turkey as their level of health outcomes and spending make them outliers), the EU new member states Bulgaria, Cyprus, Estonia, Latvia, Lithuania, Malta, Romania, Slovenia as well as Croatia, for which data are available. By using average health expenditures over 2000–03 and health outcomes in 2002 and 2004 in the DEA we allow for a time lag between when spending takes place and when health outcomes are measured. The exceptions are maternal mortality where the latest outcome data available are for 2000 and standardized death rates where two countries have data available only for 2001.
It should be noted that simultaneous correlation analysis does not provide estimate of causality. Policy and environmental variables may drive efficiency, but the reverse may also be true, and unobserved variables may drive policy and environmental variables as well as efficiency.
Afonso and St. Aubyn (2007), using bootstrap procedures to assess the impact of exogenous factors on the variation of health efficiency across countries, also find that higher GDP levels are associated with higher system efficiency. They also find that a high level of education attainment in a country improves health system efficiency while the prevalence of obesity and tobacco consumption lower health system efficiency.
Several of the factors that are correlated with relative efficiency are also significantly correlated with GDP. For instance, countries with higher income levels spend more on pharmaceuticals and have higher out-of-pocket expenditures, and better access to medical technology, such as MRI equipment. Simultaneous correlations between these factors and relative efficiency levels may thus simply reflect the strong association between GDP and the efficiency level. Thus, in order to separate the effects between the associated factor and efficiency from the relationship with GDP in cases where the associated factor is significantly correlated with GDP, we ran simple regressions of relative efficiency on the associated factor and GDP per capita. In those cases, the reported correlations are the regression coefficient of the associated factor, and are only reported when the coefficient is statistically significant.
A World Bank and USAID (2000) study and a report by International Business Strategies (2006) show that the Slovak health system suffers from corruption and that individuals may be willing to pay for better health services. However, this is unlikely without an improvement in the quality of health services.
Large hospitals connected to universities are still under central government control and are the main exception.