Multilevel modeling of regional variation in equity in health care.
BACKGROUND
The use of a concentration index is recommended to estimate socioeconomic equity in health and health services. Methods for the analysis of concentration indices have been developed in several studies. However, these methods do not take into consideration clustering within areas, which is necessary in a comprehensive study of regional variations in equity.


OBJECTIVE
The study aims to develop a statistical method to assess variations in socioeconomic inequities in the use of health services in relation to need in different regions.


METHODS
Concentration index methods were developed further and the advantages of multilevel modeling were exploited. As an empirical example we analyzed revascularizations in 2001-2003 among the Finnish population.


RESULTS
The average inequity indices for the income distribution of revascularizations in Finland obtained with multilevel and standard regression modeling were comparable, but confidence intervals were smaller with multilevel modeling. Inequity indices for different areas estimated using multilevel modeling were more conservative and had smaller confidence intervals than indices estimated using the standard approach.


CONCLUSIONS
The proposed approach is an efficient way of estimating regional variations in the socioeconomic equity of health care use. It enables the inclusion of need in the model and takes into account the varying need for services in different population groups and areas. In addition, the advantages of using multilevel modeling to estimate indices include the possibility to take into account dependence between observations within regions and to overcome the problems associated with random error in small regions.
Lumme
Sonja
S
National Research and Development Centre for Welfare and Health, Health Services Research, Helsinki, Finland. sonja.lumme@stakes.fi
Leyland
Alastair H
AH
Keskimäki
Ilmo
I
D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D005260:Female; D005387:Finland; D006297:Health Services Accessibility / Q000706:statistics & numerical data; D006301:Health Services Needs and Demand / Q000706:statistics & numerical data; D006302:Health Services Research / Q000706:statistics & numerical data; D054625:Healthcare Disparities / Q000706:statistics & numerical data*; D006801:Humans; D016014:Linear Models; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009204:Myocardial Revascularization / Q000706:statistics & numerical data; D044382:Population Groups / Q000706:statistics & numerical data; D012041:Regional Medical Programs / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D014600:Utilization Review / Q000706:statistics & numerical data