This blog explores the rise of person-centered insights in policymaking, featuring an overview of its benefits and expert interviews highlighting its crucial role in effectively delivering public benefits and human services.
This report describes how the government can use widespread social media feedback and begin to build long-term measures to center people’s experience as an important component of policy design
Drawing on the Beeck Center’s research on government, nonprofit, academic, and private sector organizations that are working to improve access to safety net benefits, this report highlights best practices for creating accessible benefits content.
Government leaders discuss how to ensure seamless access to public benefits through breaking down silos, user-friendly digital identities, and privacy-focused security measures.
This brief describes the TANF Data Collaborative (TDC), an innovative approach to increasing data analytics capacity at state Temporary Assistance for Needy Families (TANF) agencies.
This report explores innovative solutions and insights from CMS Innovation Center's Hackathon series to address the unique healthcare challenges faced by rural, Tribal, and geographically isolated communities.
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.
In this report, the U.S. Chamber of Commerce Foundation examines benefits cliffs – the loss of eligibility for public safety-net programs and benefits they provide as income rises above eligibility limits.
Through the ACCESS project, key collaborators have shared insights into current and future opportunities for alignment within their agencies, including potential enablers for and barriers to alignment activities.
American Public Human Services Association (APHSA)
This research study analyzes the structural and budgetary layout of eleven US-based Digital Service Teams (DSTs) at the municipal, county, and state levels. In doing so, it sets out to answer the research question: “How are digital service teams structured and funded?”
This report presents evidence on the use of algorithmic accountability policies in different contexts from the perspective of those implementing these tools, and explores the limits of legal and policy mechanisms in ensuring safe and accountable algorithmic systems.
