Public health decisions rely on accurate data, yet broad racial and ethnic categories often conceal meaningful differences within communities and perpetuate inequities. This webinar introduces the foundational principles of data disaggregation and highlights how inclusive practices can improve the visibility of health disparities and prevent the statistical erasure of small or historically marginalized groups, particularly American Indian and Alaska Native (AI/AN) populations.

The presenters will share strategies for visualizing and tabulating more inclusive data that better represents the full identities of individuals and examine how racial misclassification in Medicaid data contributes to underreporting of AI/AN populations in Oklahoma. Together, these discussions emphasize the importance of data disaggregation to ensure accurate and equitable data to inform policy and strengthen health outcomes.