Summary: Despite decades of research exposing health disparities between populations and communities in the U.S., health equity goals remain largely unfulfilled. Authors argue these failures call for applying an equity lens in the way data systems are approached, from collection and analysis to interpretation and distribution. Hence, health equity requires data equity.
Findings: There is notable federal interest in policy changes and federal investments to improve health equity. Authors outline the opportunities to align these health equity goals with data equity by improving the way communities are engaged and how population data are collected, analyzed, interpreted, made accessible, and distributed. Policy priority areas for data equity include increasing the use of disaggregated data, increasing the use of currently underused federal data, building capacity for equity assessments, developing partnerships between government and community, and increasing data accountability to the public.
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Summary: Despite decades of research exposing health disparities between populations and communities in the U.S., health equity goals remain largely unfulfilled. Authors argue these failures call for applying an equity lens in the way data systems are approached, from collection and analysis to interpretation and distribution. Hence, health equity requires data equity.
Findings: There is notable federal interest in policy changes and federal investments to improve health equity. Authors outline the opportunities to align these health equity goals with data equity by improving the way communities are engaged and how population data are collected, analyzed, interpreted, made accessible, and distributed. Policy priority areas for data equity include increasing the use of disaggregated data, increasing the use of currently underused federal data, building capacity for equity assessments, developing partnerships between government and community, and increasing data accountability to the public.
Read the Publication