Data and Measurement Issues in the Analysis of Health Disparities

A successful method for identifying health inequities must assess health care, housing, transportation, education and other community characteristics.

Health policy now distinguishes between health disparities and inequities: disparities are statistical differences in rates of illness, disease and other conditions; health inequities refer to social, economic and environmental factors that affect health.

The goal of Healthy People 2020, a national initiative, is the correction of health inequities. However, ineffective data collection has prevented researchers from identifying both health disparities and inequities.

This article explores methods for researching health disparities and inequities. The authors describe research methods that might overcome small-sampling size, a difficulty in past research. Promising data collections include: oversampling, pooled data, targeted periodic surveys, multiple frame sample designs, modeling approaches, mixed mode surveys, regulations and incentives for providers, and granular data collection.

Key Findings:

  • In order to overcome the limitations of small-sample size, studies have combined data from several years and conducted targeted studies within racial and ethnic communities.
  • A nationwide health information infrastructure that makes use of electronic health records could facilitate research into health disparities.
  • Indirect estimation techniques have been a useful tool for assessing health disparities.

In 1985, the U.S. Department of Health and Human Services reported high mortality rates among African-Americans. Since then, health disparities have become a focus of public policy. The goal of Healthy People 2020, a recent national initiative, is to correct inequities—a complex measure of social, economic and environmental health factors. This article explores strategies for improving research of health disparities and inequities.