How should we measure and interpret racial and ethnic disparities in health care?
- Collection:
- Health Policy and Services Research
- Series Title(s):
- Urban Institute research report
- Author(s):
- Clemans-Cope, Lisa, author Garrett, Bowen, author McMorrow, Stacey, author
- Contributor(s):
- Health Policy Center (Urban Institute), issuing body. Robert Wood Johnson Foundation, issuing body.
- Publication:
- Washington, DC : Urban Institute, January 2023
- Language(s):
- English
- Format:
- Text
- Subject(s):
- Health Equity -- economics Health Policy Healthcare Disparities -- ethnology Racism -- prevention & control Social Determinants of Health -- classification United States
- Genre(s):
- Technical Report
- Abstract:
- Racial disparities in health and health care are well documented and long-standing in the US health care system. Efforts to eliminate disparities are a critical national priority, and quantifying and interpreting measures of disparities in health care are important but challenging parts of that effort. Broadly, a health care disparity can be defined as a difference in health care access or use between two population subgroups because of which the less socially advantaged group underperforms compared with its more advantaged counterpart for reasons deemed avoidable, unnecessary, or unjust. In 2003, the Institute of Medicine (IOM) offered a more specific definition of disparity in health care access and use when evaluating health care system performance. Under the IOM definition, racial and ethnic differences in health care access and use for reasons outside of clinical need and patient preferences are considered unjustifiable and thus constitute a disparity. Under this definition, differences due to age, sex, health status, and patient preferences are considered acceptable or just. Though this is not the only valid definition, it provides a clear example of how to explicitly define a disparity and use a conceptual framework that defines just and unjust drivers of differences to guide interpretation. Many studies of health care disparities fail to use such a clear disparity definition and framework for analysis, however, and this can result in estimates that are ill defined and subject to misinterpretation. For example, when studies provide multiple estimates of disparities that control for different sets of covariates without a strong justification for each or an a priori statement of their preferred approach, interpretation is challenging. We provide an example of such a study that includes four estimation approaches resulting in disparity estimates that vary considerably. The most heavily adjusted estimates are reported in the abstract, without justification for the chosen approach or sufficient guidance for interpreting the other estimates. Furthermore, many studies fail to consider or incorporate the role of systemic racism within a conceptual framework used to interpret disparity estimates. Though systemic racism may be difficult to measure, it is critical to discuss its role in driving disparities in the context of any study and to what extent it is correlated with other measured drivers or captured in a residual.
- Copyright:
- Reproduced with permission of the copyright holder. Further use of the material is subject to CC BY-NC-DC license. (More information)
- Extent:
- 1 online resource (1 PDF file (vii, 59 pages))
- Illustrations:
- Illustrations
- NLM Unique ID:
- 9918591682906676 (See catalog record)
- Permanent Link:
- http://resource.nlm.nih.gov/9918591682906676