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What's Missing from Data Modernization? A Focus on Structural Racism
Jamila M Porter1, Brian C Castrucci1, Jacquelynn Y Orr2
1Office of the CEO, de Beaumont Foundation, Bethesda, Maryland, USA.
Abstract:
Public health data modernization efforts frequently overlook the far-reaching effects of structural racism across the data life cycle. Modernizing data requires creating data ecosystems grounded in six principles: dismantling structural racism and building community power explicitly; centering justice in all stages of data collection and analysis; ensuring communities can govern their data; driving positive population-level change; engaging nonprofit organizations; and obtaining commitments from governments to make changes in policy and practice. As government agencies spearhead and finance data modernization initiatives, it is imperative that they address structural racism head-on and integrate these principles into all aspects of their work.
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