CT’s Path to Equity: Race, Ethnicity, and Language Measurement

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Authored by Victoria Tran

Race, ethnicity, and language (REL) measurement means collecting, analyzing, and using data to identify and address health disparities. Quality REL data is self-reported using detailed, standardized categories and selecting multiple categories.

To evaluate whether policies and practices promote equity, make informed decisions, and detect inequities where we may not expect them, we must have high-quality and detailed race, ethnicity, and language (REL) data.

In 2021, Connecticut took steps to standardize how this data is collected by some state agencies and health care providers.

To further strengthen REL measurement, Health Equity Solutions recommends:

  • Fully implementing the REL data standards set out in Public Act No. 21-35; these standards apply best practices to improve the quality and completeness of REL data.
  • Applying REL standards outlined in Public Act No. 21-35 to all state agencies, contractors, and vendors collecting demographic data
  • Using disproportionality and disparities indices to contextualize REL data
  • Sharing REL data in all public reports released by the state or explaining why this is not possible
  • Reporting all health metrics (such as quality, access, and outcome measures) by REL and other demographic factors (e.g., sexual orientation, gender identity, and disability status) unless sample sizes are too small to do this while protecting the privacy of state residents

Are you looking for REL data from your town? Check out DataHaven’s reports for each CT municipality here.

How does this image reflect your work? What is missing? Please share your thoughts with us by email or social media (Facebook: @healthequityct; Instagram: @healthequitysolutions; Twitter: @HealthEquityCT). Stay tuned for posts expanding on each section of CT’s Path to Equity.