This brief describes the TANF Data Collaborative (TDC), an innovative approach to increasing data analytics capacity at state Temporary Assistance for Needy Families (TANF) agencies.
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.
U.S. Department of Health and Human Services (HHS)
This resource outlines strategies for cross-enrollment outreach, which can break down silos between programs and reach applicants who may be eligible for under-enrolled benefits programs.
This report explores Michigan’s implementation of the Pandemic Electronic Benefit Transfer (P-EBT) program. Drawing on interviews from individuals within the Michigan Department of Health and Human Services and input from SNAP participants via surveys distributed using the Fresh EBT app, this report provides insights into the strategies that enabled Michigan to roll out an entirely new program quickly and effectively.
This report documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
This is the summary version of a report that documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
This guide highlights best practices in benefits access, showcasing how Michigan, New York City, and San José improve accessibility through plain language, multilingual translation, resident co-creation, and technology tools.
