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.

Webinar featuring an in-depth walk through of the screening questionnaire, highlighting design and content decisions made based on feedback from SNAP clients and advocates. Passcode: &Hd64icK

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.

Human-centered design best practices to screen for Medicaid work requirement exemptions

Guide on how state agencies can develop legible and flexible metrics to assess implementation of new work requirements, outlining how to build, capture, and effectively utilize metrics to monitor impact for operational awareness and decisionmaking.

Repository of resources for state administrators to support the implementation of work requirement policies through overview of implications and recommendations of smart system designs and processes.

Key strategies to improve accuracy and efficiency of SNAP program delivery, including evaluating intervention impacts independently, developing strong proxy metrics, watching for unintended consequences, strategically reviewing most error-prone case elements and actions, leveraging new technology for caseworkers, and improving client communication and outreach.

Outlines four proactive strategies to design resilient and adaptable technical systems including feature flags, modularity, configurability, and phased approaches.