Socioeconomic inequality of diabetes patients' health care utilization in Denmark

Camilla Sortsø, Jørgen Lauridsen, Martha Emneus, Anders Green, Peter Bjødstrup Jensen, Camilla Sortsø, Jørgen Lauridsen, Martha Emneus, Anders Green, Peter Bjødstrup Jensen

Abstract

Understanding socioeconomic inequalities in health care is critical for achieving health equity. The aim of this paper is threefold: 1) to quantify inequality in diabetes health care service utilization; 2) to understand determinants of these inequalities in relation to socio-demographic and clinical morbidity factors; and 3) to compare the empirical outcome of using income level and educational level as proxies for Socio Economic Status (SES).Data on the entire Danish population of diabetes patients in 2011 (N = 318,729) were applied. Patients' unique personal identification number enabled individual patient data from several national registers to be linked. A concentration index approach with decomposition into contributing factors was applied. Differences in diabetes patients' health care utilization patterns suggest that use of services differ among patients of lower and higher SES, despite the Danish universal health care system. Especially, out-patient services, rehabilitation and specialists in primary care show different utilization patterns according to SES. Comparison of the empirical outcome from using educational level and income level as proxy for patients' SES indicate important differences in inequality estimates. While income, alike other measures of labor market attachment, to a certain extent is explained by morbidity and thus endogenous, education is more decisive for patients' ability to take advantage of the more specialized services provided in a universal health care system.

Figures

Fig. 1
Fig. 1
Concentration index (observed and predicted by determinants) of income-related inequalities in cost outcomes Legend: Ciy = Observed concentration index for the outcome variable Ciy predicted = Concentration index predicted by the included determinants for the outcome variable
Fig. 2
Fig. 2
Decomposition of income-related inequality in in-patient care costs
Fig. 3
Fig. 3
Concentration indices of health care and pharmaceutical usage based on ranking by income and educational level respectively
Fig. 4
Fig. 4
Decomposition of education related inequality in costs for specialists in primary care

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