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This paper presents new international comparative evidence on the factors driving inequalities in the use of GP and specialist services in 12 EU member states. The data are taken from the 1996 wave of the European Community Household Panel (ECHP). We examine two types of utilisation (the probability of a visit and the conditional number of positive visits) for two types of medical care: general practitioner and medical specialist visits using probit, truncated Negbin and generalised Negbin models. We find little or no evidence of income-related inequity in the probability of a GP visit in these countries. Conditional upon at least one visit, there is even evidence of a somewhat pro-poor distribution. By contrast, substantial pro-rich inequity emerges in virtually every country with respect to the probability of contacting a medical specialist. Despite their lower needs for such care, wealthier and higher educated individuals appear to be much more likely to see a specialist than the less well-off. This phenomenon is universal in Europe, but stronger in countries where either private insurance cover or private practice options are offered to purchase quicker and/or preferential access. Pro-rich inequity in subsequent visits adds to this access inequity but appears more related to regional disparities in utilisation than to other factors. Despite decades of universal and fairly comprehensive coverage in European countries, utilisation patterns suggest that rich and poor are not treated equally.

This paper provides new evidence on the sources of differences in the degree of income-related inequalities in self-assessed health in 13 European Union member states. It goes beyond earlier work by measuring health using an interval regression approach to compute concentration indices and by decomposing inequality into its determining factors. New and more comparable data were used, taken from the 1996 wave of the European Community Household Panel. Significant inequalities in health (utility) favouring the higher income groups emerge in all countries, but are particularly high in Portugal and - to a lesser extent - in the UK and in Denmark. By contrast, relatively low health inequality is observed in the Netherlands and Germany, and also in Italy, Belgium, Spain Austria and Ireland. There is a positive correlation with income inequality per se but the relationship is weaker than in previous research. Health inequality is not merely a reflection of income inequality. A decomposition analysis shows that the (partial) income elasticities of the explanatory variables are generally more important than their unequal distribution by income in explaining the cross-country differences in income-related health inequality. Especially the relative health and income position of non-working Europeans like the retired and disabled explains a great deal of 'excess inequality'. We also find a substantial contribution of regional health disparities to socio-economic inequalities, primarily in the Southern European countries.

This paper aims to add a more intuitive understanding to the concept of a concentration index for measuring relative inequality with an application of health-related measures by income. A new redistribution interpretation and an existing redistribution interpretation of the Gini are presented and applied to the concentration index. Both indicate the share of the total amount of any variable that needs redistributing in a particular way from rich to poor (or vice versa) to achieve a concentration index equal to zero. The characteristics of these redistribution schemes are compared. The paper also draws attention to the relationship between a concentration index, a correlation coefficient with relative income rank and a coefficient of variation of the variable of interest. These relationships are illustrated using data on inequality in dental care utilisation in European countries taken from the European Community Household Panel survey.

Patients and physicians put considerable value on pregnancy rates. However, physicians significantly undervalue the importance of patient-centredness to patients. Clinics aiming to optimize the quality of their services should be aware of the substantial importance their patients assign to patient-centredness.

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The paper considers health-related non-response in the first 11 waves of the British Household Panel Survey and the full eight waves of the European Community Household Panel and explores its consequences for dynamic models of the association between socioeconomic status and self-assessed health. We describe the pattern of health-related non-response that is revealed by the British Household Panel Survey and European Community Household Panel data. We both test and correct for non-response in empirical models of the effect of socioeconomic status on self-assessed health. Descriptive evidence shows that there is health-related non-response in the data, with those in very poor initial health more likely to drop out, and variable addition tests provide evidence of non-response bias in the panel data models of self-reported health. Nevertheless a comparison of estimates-based on the balanced sample, the unbalanced sample and corrected for non-response by using inverse probability weights-shows that, on the whole, there are not substantive differences in the average partial effects of the variables of interest. The main differences are between unweighted and one form of inverse-probability-weighted estimates for the average partial effects of income and education in those countries that have fewer than eight waves of data. Similar findings have been reported concerning the limited influence of non-response bias in models of various labour market outcomes; we discuss possible explanations for our results. Copyright 2006 Royal Statistical Society.

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