At Rules as Code Demo Day Executive Director Zareena Mayn and Chief Technology Officer Dize Hacioglu of mRelief demoed the code for their Supplemental Nutrition Assistance Program (SNAP) eligibility screener. mRelief is a women-led team that provides a web-based and text message-based SNAP eligibility screener to all 53 states and territories that participate in SNAP. They demonstrated how they have modularized their code to host federal program rules and state-specific rules.
This report examines how state governments organize and manage human services programs, analyzing various agency structures and their impact on service delivery and coordination with the health care sector.
The Technology Transformation Service at GSA recently created a new Public Benefits Studio to focus on fostering a more cohesive, coordinated experience for the public, across programs.
On July 16, members of the Digital Identity Community of practice gathered to learn how peers are gathering beneficiary feedback on their experiences with accounts and proving their identity.
The team examined how AI, specifically LLMs, could streamline the case review process for SNAP applications to alleviate the burden on case workers while potentially improving accuracy.
This study investigates how administrative burdens influence differential receipt of income transfers after a family member loses a job, looking at Unemployment Insurance, Temporary Assistance for Needy Families, and the Supplemental Nutrition Assistance Program.
Benefits Data Trust (BDT), in collaboration with the Center for Health Care Strategies (CHCS), conducted a nationwide analysis of how states coordinate across Medicaid and SNAP programs to streamline access to benefits.
The Better Government Lab at the McCourt School of Public Policy at Georgetown University has developed a new scale for measuring the experience of burden when accessing public benefits. They offer both a three-item scale and a single-item scale, which can be utilized for any public benefit program. The shorter scales provide a less burdensome way to measure by requiring less information from users.
