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

Resource to explore and compare state-by-state data on eligibility processing, payment accuracy, and policy options

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

Guide about the member-facing side of implementation, and why user experience is just as important as what happens on the backend

Conversation sharing drivers and targeted interventions to reduce SNAP Payment Error Rates, drawing on six months of hands-on research with Arizona, North Carolina, and Maryland

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

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.

A free resource that focuses on strategies that states can test immediately to reduce PER and lessen the burden on frontline eligibility workers

A CMS-developed suite of open-source tools that streamlines income and community engagement reporting for Medicaid applicants and enrollees