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
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.
Data and Analytic Approaches for Medical Frailty Exemptions
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.
Eligibility Made Easy (Emmy)
A CMS-developed suite of open-source tools that streamlines income and community engagement reporting for Medicaid applicants and enrollees
Promising Practices in SNAP PER Reduction: A State Case Study
By Sarah Esty (Aspen Institute Financial Security Program) Phase 1: Preauthorization with simple rules, targeted reviews One state has been able to achieve a PER close to 6% through use of a preauthorization review (before cases are finalized) for all new applications, reinstatements, or cases adding a person. They have historically picked cases to review…
Promising Practices in SNAP PER Reduction: Data-Driven Preauthorization Reviews
By Sarah Esty (Aspen Institute Financial Security Program) and Eric Giannella (Georgetown University Better Government Lab) To assist states working to rapidly reduce SNAP payment error rates to avoid new cost-share requirements, the Safety Net Response Network has been convening monthly meetings of state data practitioners for peer learning around successful error reduction strategies. Through…
Integration Guide for Implementing System Changes
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.
