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Inaccuracies in Medicare’s race and ethnicity data hinder the ability to assess health disparities
Inaccuracies in Medicare’s race and ethnicity data hinder the ability to assess health disparities
- Collection:
- Health Policy and Services Research
- Series Title(s):
- Data brief (United States. Department of Health and Human Services. Office of Inspector General)
- Contributor(s):
- United States. Department of Health and Human Services. Office of Inspector General. Office of Evaluation and Inspections, issuing body.
- Publication:
- Washington, D.C. : U.S. Department of Health and Human Services, Office of Inspector General, June 2022
- Language(s):
- English
- Format:
- Text
- Subject(s):
- Data Accuracy
Ethnicity
Government Regulation
Health Impact Assessment
Healthcare Disparities
Medicare -- organization & administration
Medicare -- statistics & numerical data
Racial Groups
United States - Genre(s):
- Technical Report
- Abstract:
- Why OIG Did This Review. The disparate impacts of the COVID-19 pandemic on various racial and ethnic groups have brought health disparities to the forefront. Health disparities are differences in health that adversely affect certain groups. People of color have been found to experience disparities in areas such as access to health care and quality of health care. Such disparities have profound implications for the health and well-being of these individuals. Medicare is an essential part of the Nation’s health care system, with 66 million beneficiaries enrolled. The Centers for Medicare & Medicaid Services (CMS) has made advancing health equity a top priority. Ensuring that Medicare is able to assess disparities is key to this goal. The ability to assess health disparities hinges on the quality of the underlying race and ethnicity data. How OIG Did This Review. We analyzed the race and ethnicity data in Medicare’s enrollment database, the only source of this information for all enrolled beneficiaries. These race and ethnicity data are derived from source data from the Social Security Administration (SSA) and the results of an algorithm that CMS applies to the source data. We assessed the accuracy of Medicare’s enrollment race and ethnicity data for different groups by comparing them to self-reported data for a subset of beneficiaries who reside in nursing homes. Race and ethnicity data that are self-reported are considered the most accurate. We also assessed the adequacy of Medicare’s data using the Federal standards for collecting race and ethnicity data as a benchmark. What OIG Found. Medicare’s enrollment race and ethnicity data are less accurate for some groups, particularly for beneficiaries identified as American Indian/Alaska Native, Asian/Pacific Islander, or Hispanic. Data that are not accurate limit the ability to assess health disparities. Limited race and ethnicity categories and missing information contribute to inaccuracies in the enrollment data. Although the use of an algorithm improves the existing data to some extent, it falls short of self-reported data. Finally, Medicare’s enrollment data on race and ethnicity are inconsistent with Federal data collection standards; these inconsistencies inhibit the work of identifying and improving health disparities within the Medicare population.
- Copyright:
- The National Library of Medicine believes this item to be in the public domain. (More information)
- Extent:
- 1 online resource (1 PDF file (24 pages))
- Illustrations:
- Illustrations
- NLM Unique ID:
- 9918715886806676 (See catalog record)
- Permanent Link:
- http://resource.nlm.nih.gov/9918715886806676