This case study highlights how states used data sharing and targeted outreach to boost WIC enrollment among Medicaid and SNAP participants, improving program reach and reducing disparities.
A guide to navigating New York City’s public services. It was made with and for families of students living in temporary housing or experiencing homelessness and the NYC Department of Education’s Office of Students in Temporary Housing (STH).
In this presentation, team members from the North Carolina Department of Health and Human Services provide an overview of the implementation process for cross enrollment with SNAP, WIC, and Medicaid in North Carolina.
North Carolina Department of Health and Human Services
The 2021 President’s Management Agenda identified federal customer experience as a priority area for improvement. GAO was asked to review OMB and selected federal agencies’ efforts to improve federal customer experience.
Digitizing public benefits policy will make the biggest impact for administrators and Americans, but only if it happens at the highest level of government.
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.
This report outlines the guiding principles, policy priorities, and tools for the National Collaborative for Integration of Health and Human Services, aimed at improving health and well-being outcomes through the integration of health care and human services programs.
American Public Human Services Association (APHSA)
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 case study details the development of a document extraction prototype to streamline benefits application processing through automated data capture and classification.
