A blog post outlining key strategies states can use to lower SNAP payment error rates, a priority given new fiscal penalties tied to error rates under recent federal law.
Louisiana issued an RFI to identify solutions that can provide a technology platform for determining eligibility and managing cases across multiple human services programs.
This publication explains current state integrated eligibility and enrollment (IEE) system implementation processes, approaches, and opportunities for future processes and technologies. It is a resource for state officials, advocates, funders, and tech partners working to implement these systems.
A detailed guide outlining how states can minimize coverage losses and administrative burden while implementing new Medicaid work requirements established under the 2025 federal reconciliation law.
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
Led by the Digital Benefits Network in partnership with Public Policy Lab, the Digital Doorways research project amplifies the lived experiences of beneficiaries to provides new insights into people’s experiences with digital identity processes and technology in public benefits. This executive summary gives an overview of the project’s findings.
This report explores how public benefit systems can better support young adults by addressing the barriers they face in accessing and maintaining vital services like SNAP, Medicaid, and WIC.
This article emphasizes the need for local leaders to prioritize disability equity in advancing upward mobility, addressing systemic barriers that hinder disabled individuals' escape from poverty.
This session from FormFest 2024 focused on how governments are scaling their SNAP benefits programs, with Maryland’s improved integrated benefits application and the Office of Evaluation Sciences’ changes to questions on the SNAP application.
The team aimed to automate applying rules efficiently by creating computable policies, recognizing the need for AI tools to convert legacy policy content into automated business rules using Decision Model Notation (DMN) for effective processing and monitoring.
