A recap of the two-day conference focused on charting the course to excellence in digital benefits delivery hosted at Georgetown University and online.
In this blog post, we’ve detailed some of the steps we take to help capture the best data possible when conducting interviews. This post is intended as a guide for people who need to conduct user interviews and for people simply curious about how we work.
This page includes data and observations about authentication and identity proofing steps specifically for online applications that include child care applications.
The "Implementing Paid Family and Medical Leave" report examines New Jersey's experience with paid leave programs, offering insights and recommendations for effective policy design and implementation.
This resource offers practical strategies for early childhood programs to create inclusive, affirming environments for LGBTQIA2S+ families and their children.
U.S. Department of Health and Human Services (HHS)
This playbook outlines the ways Community Action and human services agencies worked together to meet the pandemic challenge—what worked well, obstacles and difficulties, and lessons learned to inform the path forward, partnering to achieve a more equitable recovery. It also explains how communities have leveraged opportunities to partner on approaches that hold the promise of deeper, longer lasting changes for families—work shaped by families’ wishes and strengths and designed to advance both family-level and systems-level change.
American Public Human Services Association (APHSA)
This resource describes how different agencies have updated their systems to increase online and mobile access to benefits information and applications, including using text messages to share benefits information with residents.
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.
The team developed an application to simplify Medicaid and CHIP applications through LLM APIs while addressing limitations such as hallucinations and outdated information by implementing a selective input process for clean and current data.
