This page includes data and observations about authentication and identity proofing steps specifically for online applications that include child care applications.
As a part of Benefit Data Trust (BDT)’s Medicaid Churn Learning Collaborative, BDT has created a memo describing strategies for states to collect current mailing addresses of Medicaid beneficiaries in advance of the Medicaid continuous coverage requirement — in effect under the federal public health emergency — unwinding.
Together, the Kansas Department for Children and Families (DCF) and Department of Health and Environment (KDHE) are working to design and build a sustainable process to improve cross-enrollment for families eligible for both the Supplemental Nutrition Assistance Program (SNAP) and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). This report outlines how Kansas will integrate data matches between SNAP and WIC—as well as targeted outreach— within the ongoing business processes of the agencies to help streamline the experience of accessing nutrition supports for clients. These functions will contribute to the agencies’ shared goal of reducing rates of food insecurity in Kansas.
American Public Human Services Association (APHSA)
As a part of Benefit Data Trust (BDT)’s Medicaid Churn Learning Collaborative, BDT has created a memo describing policy options and state examples for Medicaid administrators to reduce churn for non-MAGI Medicaid enrollees when the federal public health emergency ends.
This policy brief outlines how improved data sharing between federal agencies, state and local governments, and institutions can leverage existing data from other benefits programs to streamline eligibility processes and benefits uptake for the Affordable Connectivity Program (ACP) and other programs.
This is a modular, dynamic roadmap guides the U.S. HHS's ongoing implementation of open data policies while inviting public collaboration and feedback.
U.S. Department of Health and Human Services (HHS)
A case study documenting how a modular API layer was built to support a state-level paid family and medical leave program, improving interoperability, scalability, and user experience.
This report warns that federal data collection is being undermined by budget cuts, political interference, and leadership changes that threaten the reliability of core economic and social statistics.
