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

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.

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

Open-source community engagement reporting (OSCER) tool enables states to achieve work requirements compliance automatically using client and ex parte data, or otherwise provide link for manual certification or exemption application. Provides staff with case management and reporting tools, and sends results to state Medicaid agencies for issuance or disenrollment.