Resource Data Data Governance

Case Study for the Child Welfare Study to Enhance Equity with Data (CW-SEED): Michigan

This case study examines how Michigan’s Department of Health and Human Services uses data practices to advance racial equity in child welfare through identity-informed data collection and anonymous decision-making.

Organizations: U.S. Department of Health and Human Services (HHS), Administration for Children and Families (ACF), Office of Planning, Research & Evaluation (OPRE), UNC School of Social Work, Center for the Study of Social Policy (CSSP), Mathematica

Authors: Genevieve Caffrey, Jill Spielfogel, Elizabeth Weigensberg, Roseana Bess

Published Year: 2024

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Michigan’s Children’s Services Administration launched two initiatives: the Race Data Collection Project (RDCP), which improves the accuracy and completeness of data on race, ethnicity, culture, and heritage, and anonymous removal meetings in Kent County, which remove identifying information from decisions about removing youth from their homes.

These efforts aim to reduce bias and disproportionality in child welfare decision-making. While anonymous removal meetings improved the quality of decision-making, they did not significantly reduce racial disproportionality, leading to expanded equity efforts earlier in the reporting process.