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 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 plan promotes responsible AI use in public benefits administration by state, local, tribal, and territorial governments, aiming to enhance program effectiveness and efficiency while meeting recipient needs.
U.S. Department of Health and Human Services (HHS)
APHSA explains how certain tools and recommendations about when people apply for help, engage in services, and maintain benefits can have a powerful effect to either counter or exacerbate structural barriers to accessing assistance.
American Public Human Services Association (APHSA)
The examples in this guide describe how peer-to-peer training and updated interview scripts can help connect residents to the benefits they are eligible for.
A case study on how North Carolina leveraged human-centered design, interagency collaboration, and data-sharing strategies to improve cross-enrollment in SNAP, WIC, and Medicaid, aiming to reduce administrative burden and better serve families.
American Public Human Services Association (APHSA)
This timeline outlines key Medicaid policy changes introduced by the One Big Beautiful Bill (OBBBA / H.R. 1) with the greatest operational impact on state and territory agencies and highlights upcoming implementation deadlines.
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.
USDS partnered with CMCS and state Medicaid agencies to improve eligibility and enrollment systems after the COVID-19 Public Health Emergency ended, focusing on health coverage renewals.
This report by EPIC investigates how automated decision-making (ADM) systems are used across Washington, D.C.’s public services and the resulting impacts on equity, privacy, and access to benefits.
