This report highlights best practices and lessons learned from Kansas' partnership with Delivering Change to improve SNAP and WIC access in seven counties through innovative data sharing and targeted outreach.
American Public Human Services Association (APHSA)
This post explores the lessons learned and opportunities for improvement from USDR's research on families' experiences as they navigate the child care journey.
The article examines the participation of adults aged 50 and older in the Supplemental Nutrition Assistance Program (SNAP) in 2022, highlighting the program's role in reducing food insecurity and poverty among older adults, especially those with disabilities.
This study explores the causal impacts of income on a rich array of employment outcomes, leveraging an experiment in which 1,000 low-income individuals were randomized into receiving $1,000 per month unconditionally for three years, with a control group of 2,000 participants receiving $50/month.
These fact sheets provide detailed, state-specific data illustrating SNAP's role in reducing hunger and bolstering local economies across the United States
Post-Medicaid continuous enrollment's end in March 2023, states faced renewal challenges through August 2024, seeing improved auto-renewals but persistent procedural disenrollments despite outreach and intervention.
The Temporary Assistance for Needy Families (TANF) Data Collaborative Pilot Initiative is a component of the TANF Data Innovation project. The 30-month pilot offered technical assistance and training to support cross-disciplinary teams of staff at eight state and county TANF programs in the routine use of TANF and other administrative data to inform policy and practice.
This video documents the Digital Benefits Network's Digital Identity Community of Practice launch, covering mission review, 2025 goals, California authentication innovations, and peer networking for equitable and effective digital identity in public benefits.
The team developed an application to simplify Medicaid and CHIP applications through LLM APIs while addressing limitations such as hallucinations and outdated information by implementing a selective input process for clean and current data.
