Resources and Toolkits

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

Workshop examining how predictive analytics and risk scoring can improve SNAP implementation and evaluation, using Conneticut as a case study.

JAMA Health Forum Viewpoint article examining how states can implement the Medicaid “medical frailty” exemptions under HR 1’s new work reporting requirements with recommendations for states to use flexible, clinically driven standards, multiple data sources, and priortize transparency to identify such individuals and prevent harmful coverage disruptions.

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.

Resource outlining data and analytic approaches to support states through the technology implementation and integration process for Medicaid work requirements, with a focus on medical frailty exemptions.

Guide explaining automatic benefit notice generation process while walking through common underlying system errors (e.g. missing or incorrect information) providing insight on how back-end design decisions cause these issues. Provides strategies to improve notice process and output such as targeted questions on system logic, workarounds for caseworkers, and structural reform through data flow, boilerplate language,…

Guide to provide states with policy and technical strategies to reduce procedural terminations under Medicaid work requirements, including simplifying verification processes, mitigating automation risks, managing vendor

States can act to reduce their SNAP PERs but must move quickly for their efforts to impact their share of program costs in 2027.