Report finds flaws in Medicare race, ethnicity data

Errors impede efforts to overcome disparities in health care access and outcomes

A new government report finds that data on the race and ethnicity of Medicare beneficiaries is often inaccurate, hindering the program’s ability to assess disparities in access to and quality of care among its 66 million participants.

The report from the Department of Health and Human Services’ Office of the Inspector General (OIG) says that race and ethnicity data for beneficiaries identified as American Indian/Alaska Native, Asian/Pacific Islander or Hispanic is less accurate than for other groups.

“The Centers for Medicare & Medicaid Services has made advancing health equity a top priority,” the report states. “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.”

The OIG arrived at its findings by analyzing race and ethnicity data in Medicare’s enrollment database and comparing them to self-reported race and ethnicity data—considered the “gold standard” of such data—for about five million beneficiaries who’ve been in nursing homes. Medicare derives its enrollment data from data provided by the Social Security Administration (SSA) and applying the Research Triangle Institute algorithm to improve its accuracy.

The report finds two broad categories of errors in Medicare’s data. The first is individuals listed as part of a race or ethnicity with which they don’t identify on the nursing home assessment. That error applies to 28% of beneficiaries identified as Hispanic in the enrollment data, 46% of those identified as American Indian/Alaska Native and 17 percent of those identified as Asian/Pacific Islander.

Second is that the data don’t accurately depict the race and ethnicity with which beneficiaries in the groups do identify. Thirteen percent of beneficiaries who self-identified as Hispanic on the nursing home surveys are not so identified in the enrollment data. The same error occurs for 35% of those who self-identified as American Indian/Alaska Native on the nursing home assessment and 24% identifying as Asian/Pacific Islander.

The report notes that Medicare uses data on the race and ethnicity of beneficiaries to address issues such as disparities in the long-term impacts of COVID-19, access to care providers, and quality of services provided.

“However, inaccurate race and ethnicity data can raise concerns that efforts to address disparities …. would be targeted at the wrong beneficiaries,” according to the report. “Further, using inaccurate data to try to measure the effects of these efforts could produce misleading results.”

The OIG report offers several recommendations for improving the accuracy of Medicare’s data. Among them:

  • Transitioning away from the current practice of using SSA data and developing its own source of information
  • Incorporating existing data from the nursing home and other post-acute assessments into the enrollment data for current beneficiaries where available
  • Exploring other ways of collecting self-reported data from beneficiaries who don’t have post-acute care assessments by, for example, adding race/ethnicity questions to beneficiaries’ online accounts
  • Developing a process for making the race and ethnicity data it collects as standardized as possible and able to be incorporated into the enrollment database, and
  • Educating beneficiaries about CMS’s efforts to improve the quality of its race and ethnicity information

The full report is available at https://oig.hhs.gov/oei/reports/OEI-02-21-00100.pdf

This was originally posted on Medical Economics.