This report analyzes how administrative burdens in SNAP caused one in eight working-age adults to lose benefits in 2024, with future federal policy changes expected to worsen disruptions
Initially created to inform federal staff at the U.S. Department of Health and Human Services, this tip sheet provides key considerations for how organizations can identify potential diverse external partners, conduct outreach to them, and build and sustain productive relationships with them.
Office of the Assistant Secretary for Planning and Evaluation (ASPE)
This report presents evidence on the use of algorithmic accountability policies in different contexts from the perspective of those implementing these tools, and explores the limits of legal and policy mechanisms in ensuring safe and accountable algorithmic systems.
This paper discusses the country’s chronic underinvestment in children and resulting outcomes, including new data on poverty rates among young children, is inextricable from the prospects of young children; and the remarkably comprehensive pandemic-era response policies, including which changes contributed most to reducing child poverty.
This blog presents a service blueprint that maps how expanded SNAP work requirements will affect the application, eligibility, and maintenance processes—and offers design recommendations to reduce administrative burden.
This event convened policy experts and state leaders to explore how states can operationalize new Medicaid work reporting mandates—covering technical, legal, and implementation challenges.
This webinar session discusses the importance of using CX metrics to guide agency-level decisions and how to gather, analyze, and apply customer feedback to optimize products and services.
Sharing lessons learned via the Medicaid Churn Learning Collaborative, which is working to reduce Medicaid churn, improve renewal processes for administrators, and protect health insurance coverage for children and families.
This report provides an overview of artificial intelligence (AI), key policy considerations, and federal government activities related to AI development and regulation.
