Health Equity: Everyone Counts

When data are unavailable for a marginalized racial/ethnic group, their needs are rendered invisible when policies are made, resources are allocated, and programs are designed and implemented.

Regardless of intentions, the ways in which data are collected, analyzed, and reported may have inequitable consequences. The effects of policies that make data unavailable on excluded or marginalized groups can put those populations at further disadvantage that may reflect systemic racism.

This report, produced in partnership with the University of California, San Francisco, should be relevant to those planning, conducting, or funding ethnic/racial data collection, analysis, and/ or reporting, for both federally and privately funded data, in all sectors, not only health.

Key Strategies

• Use an equity lens to determine which groups should be represented by disaggregated data. The extent of social and health disadvantage should be the key criterion, not political clout.
  
• Involve—and listen to—the racial/ethnic group(s) of concern for crucial guidance.
  
• Update the OMB standards for racial/ethnic designations. The OMB last updated the Race and Ethnic Standards for Federal Statistics and Administrative Reporting in 1997. These standards need to be updated, with public input, to reflect the shifts in the U.S. population that have occurred during the intervening 24 years.
  
• Further standardize methods of collection of racial/ethnic information. Standardization is essential to share and compare data across studies.
  
• Ensure adequate sample sizes of small, disadvantaged groups to permit meaningful analysis, even if it means more financial resources are needed.
  
• Always consider privacy/confidentiality and community input on issues in design, analysis, and reporting. Privacy concerns must, however, be weighed against the need for an excluded group to be represented.
  
• Commit to using disaggregated data to inform policies, practices, and programs. Data collection and reporting are insufficient without use.

These are just a few ways to support data disaggregation. The full report goes into more detail than possible here and includes an appendix listing organizations that may be resources for additional information; excerpts from major population-based secondary data sources often used in health research that show level of disaggregation of racial/ethnic data; and references.