Race, Ethnicity, and Language Data Collection: Comments on the IOM Report (Text Version)

Slide presentation from the AHRQ 2009 conference

On September 19, 2009, Cara James made this presentation at the 2009 Annual Conference. Select to access the PowerPoint® presentation (89 KB) (Plugin Software Help).


Slide 1

Slide 1. Race, Ethnicity, and Language Data Collection: Comments on the IOM Report

Race, Ethnicity, and Language Data Collection: Comments on the IOM Report

Cara V. James, Ph.D.

Senior Policy Analyst
Kaiser Family Foundation

September 15, 2009

Slide 2

Slide 2. Project's Scope

Project's Scope

  • Committee was asked to "focus on defining a standard set of race/ethnicity and language categories and methods for obtaining this information to serve as a standard."

Slide 3

Slide 3. Exactly What are Race and Ethnicity Measuring?

Exactly What are Race and Ethnicity Measuring?

Slide 4

Slide 4. Race and Ethnicity are Somewhat Fluid Concepts

Race and Ethnicity are Somewhat Fluid Concepts

  • The report states that race "is considered a socioeconomic concept wherein groups of people sharing certain physical characteristics are treated differently based on stereotypical thinking, discriminatory institutions and social structures, a shared worldview, and social myths."
  • Ethnicity "represents a common ancestral heritage that gives social groups a shared sense of identity that exists even though a particular ethnic group may contain persons who self-identify with different race categories."

Slide 5

Slide 5. Some Examples from Other Diverse Countries

Some Examples from Other Diverse Countries

  • Canada and the United Kingdom do not ask about race, just ethnicity.
    • Canada includes 12 population groups and includes visible minority, and about 200 ethnicities
    • UK has 5 broad ethnic categories (White, Mixed, Asian or Asian British, Black or British Black, and Chinese or other ethnic group), with subcategories for each and a write-in option. Question varies by geography.
  • Brazil has 5 racial groups: white, black, brown/mestizo, yellow/East Asian, and native American. According to them, racial categories are used fluidly in Brazil, reflecting the social trends more than the biological.

Slide 6

Slide 6. Race and Ethnicity Questions

Race and Ethnicity Questions

  • Given recommendation to use OMB guideline, and to collect granular ethnicity, would have like some conversation on mechanics.
    • Should this be three questions (e.g. race, ethnicity, and granular ethnicity)?
    • Should we include other "macro" ethnicities in the Hispanic ethnicity question (e.g. Caribbean or Middle Eastern)?

Slide 7

Slide 7. Hispanic/Latino Ethnicity or Race?

Hispanic/Latino Ethnicity or Race?

  • The committee acknowledged that outside of the U.S. Hispanic is meaningless. It also acknowledged that the origins for collection were largely political.
  • Many Hispanics don't identify with a racial group and don't like being forced to choose.
  • Was there thought to including Hispanic as part of the racial groups?

Slide 8

Slide 8. Multiracial Individuals

Multiracial Individuals

  • Currently over 5 million individuals self-identify as bi- or multiracial, and by 2050 we expect more than 16 million
  • Would have liked more discussion and guidance as what to do with these individuals (e.g. should there be prioritization scheme)

Slide 9

Slide 9. Recommendations Should Extend Beyond Health and Human Services, Veterans Affairs and Department of Defense

Recommendations Should Extend Beyond Health and Human Services, Veterans Affairs and Department of Defense

Slide 10

Slide 10. Recommendations Should be the Standard for All Federal Datasets that Capture Race/Ethnicity

Recommendations Should be the Standard for All Federal Datasets that Capture Race/Ethnicity

  • Taking the broad view
    • Employment data collected by Department of Labor has implications for access to care via coverage
    • Department of Justice provides health care to prisoners
    • Department of Education

Slide 11

Slide 11. Implications for My Work

Implications for My Work

Slide 12

Slide 12. Data Sources

Data Sources

  • Recommendations didn't focus on research, but research helps inform practice.
  • Will wait to see what is implemented in various datasets I work with.
  • Slightly concerned that local flexibility will lead to inaction.

Slide 13

Slide 13. Where do We Go from Here?

Where do We Go from Here?

Slide 14

Slide 14. Next Steps

Next Steps

  • Time is of the Essence
    • ARRA dollars and HIT - Systems are being built with varying levels of thought to these issues.
  • Enforcement of Guidelines
    • OMB adopted policies in 1997, yet not all federal health data adhere to these standards, what will be different this time?

Slide 15

Slide 15. More Next Steps

More Next Steps

  • Include Indian Health Services in federal datasets
  • Develop guidelines for measuring Health Literacy
  • Obtain a better understanding of what we think race and ethnicity are proxies for and develop measures for that

Slide 16

Slide 16. Thank You!

Thank You!

Contact Information
Cara James, Ph.D.
Senior Policy Analyst
Kaiser Family Foundation
cjames@kff.org

Current as of December 2009
Internet Citation: Race, Ethnicity, and Language Data Collection: Comments on the IOM Report (Text Version). December 2009. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/news/events/conference/2009/james/index.html