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.
This is the summary version of a report that 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.
This study uses machine learning models on Medicaid data to estimate that the take-up rate for children's Supplemental Security Income (SSI) is approximately 70%, identifying potentially eligible children who often have higher health care utilization than current SSI recipients.
This page includes data and observations about account creation and identity proofing steps specifically for online applications that include MAGI Medicaid.
This report explores policy options Utah and other states can adopt to mitigate benefit cliffs, which occur when small income increases lead to sudden loss of public assistance.
This study found that using state-specific names for Medicaid programs increased confusion and reduced both positive and negative opinions about the program.
There were over 25 million Medicaid disenrollments in 2023, but national enrollment remained significantly above pre-pandemic levels at over 56 million, with notable state-level variations and near-recovery of child enrollment.
Through deeply reported case studies and insights from focus groups, this report provides an in-depth look at the impact of pandemic-era government spending on families.
This session from FormFest 2024 featured the Department of Homeland Security and the United States Digital Service talking about their work to reduce form burdens for internal and external users.
