This analysis explores the potential reduction in poverty rates across all U.S. states if every eligible individual received full benefits from seven key safety net programs, highlighting significant decreases in overall and child poverty.
This study evaluates the use of RPA technology by three states to automate SNAP administration, focusing on repetitive tasks previously performed manually.
This landscape analysis examines data, design, technology, and innovation-enabled approaches that make it easier for eligible people to enroll in, and receive, federally-funded social safety net benefits, with a focus on the earliest adaptations during the COVID-19 pandemic.
The New Mexico Human Services Department and Department of Health, as part of the Coordinating SNAP & Nutrition Supports program, leveraged data sharing to align SNAP, Medicaid, TANF, and WIC.
American Public Human Services Association (APHSA)
Code for America’s Integrated Benefits Initiative has been working in partnership with the State of Colorado to demonstrate how user-centered approaches lead to measurably better delivery of safety net programs. This article describes their work with the state of Colorado in simplifying how clients report common life changes that can affect their eligibility.
This report documents best practices and lessons learned from project streamlined data sharing between SNAP and WIC, enhancing cross-enrollment processes
American Public Human Services Association (APHSA)
This case study highlights how Illinois is modernizing its student data infrastructure and interagency data sharing to increase access to SNAP and Summer EBT benefits for eligible children and families, particularly those facing systemic barriers.
American Public Human Services Association (APHSA)
This report provides supplemental estimates on how Public Law 119-21—tied to H.R. 1—will affect SNAP participation, benefits, and state administrative costs over 2025–2034.
This report provides an initial fiscal analysis of how H.R. 1 (the “One Big Beautiful Bill”) will affect the state’s federally funded programs across agencies, estimating multi-billion-dollar reductions in SNAP, Medicaid, education, and infrastructure revenues.
This guide outlines key strategies, definitions, and procedures for improving SNAP payment accuracy and reducing quality control (QC) error rates across states.
