The report discusses how state Medicaid agencies can utilize Supplemental Nutrition Assistance Program (SNAP) data to streamline the Medicaid renewal process, thereby maintaining coverage for eligible beneficiaries.
This presentation from Steph White, Cross Enrollment Coordinator at the Michigan Department of Health and Human Services offers an in-depth example on implementing cross enrollment with WIC and general tools for cross enrollment.
This report examines the phenomenon of "churn" in public benefit programs, where eligible participants temporarily lose benefits due to administrative processes, analyzing its impact on both recipients and state agencies, and suggesting strategies to reduce its occurrence.
This brief highlights the complex journey that older adults experience when applying for and enrolling in SNAP, including the major barriers and solutions that improve access along the way.
NYC's official resource for teens and young adults, including: peer & professional support, family support, education, health care, housing, employment, and other resources to help young people thrive.
NYC Opportunity collaborated with the Administration for Child Services (ACS) to design a family-centered process for prevention services, addressing confusion and lack of choice in the current system. By creating tools like the Provider Profile and Family Voice booklet, the team empowered families to choose providers based on their needs while ensuring their feedback reaches ACS. The project aims to improve family experiences and communication with ACS, with plans to expand through testing and future innovations like a web portal.
The study investigates how state agencies administering SNAP comply with Title VI of the Civil Rights Act by providing language access for individuals with limited English proficiency (LEP).
The team developed an AI-powered explanation feature that effectively translates complex, multi-program policy calculations into clear and accessible explanations, enabling users to explore "what-if" scenarios and understand key factors influencing benefit amounts and eligibility thresholds.
The article highlights the growing issue of SNAP benefit theft through skimming and advocates for permanent security measures and benefit replacements to protect vulnerable households.
A case study explaining how a predictive, data-driven machine-learning model was developed to detect unauthorized cash benefit withdrawals more quickly and accurately in California.
A report examining how risk assessment tools are used to improve payment accuracy in nutrition assistance programs and identifying effective practices for their design and implementation.
