Resources and Toolkits
Risk Assessment Tools
Video outlining best practices for states to improve their risk assessment and error detection processes, including model design, review sequencing, feature engineering, review process optimization, and quick wins
NGA Statement on SNAP Payment Error Rates Data
Statement on FY25 SNAP Payment Error Rates, timing, and state cost-sharing
These 5 Million People Are About to Lose Their Medicaid — But They Don’t Have To
Tools for data-driven understanding Medicaid work requirements, including information about who’s at risk, automatic verification pathways, ex parte capability by state, coverage loss, and maps
Introducing Our User Experience Guide for Medicaid Work Requirements
Guide about the member-facing side of implementation, and why user experience is just as important as what happens on the backend
SNAP PER Analytics Workgroup
Workshop examining how predictive analytics and risk scoring can improve SNAP implementation and evaluation, using Conneticut as a case study.
Predictive Analytics for SNAP PER Reduction QC Data Workshop Summary
Workshop to foster collaboration and share modeling practices among state agencies in response to HR1’s new SNAP PER cost share requirements. Gathering encompassed convened a group of nearly 40 research and data analytics staff from across 15 states involved in SNAP QC data modeling.
Is This Working? Data-Driven Strategies to Reduce SNAP Payment Error Rates
States can act to reduce their SNAP PERs but must move quickly for their efforts to impact their share of program costs in 2027.