Adoption & Foster Care

The Office of the Assistant Secretary for Planning and Evaluation in the U.S. Department of Health and Human Services has been working with researchers, human services agency leaders, and persons with lived experience to visualize, describe, and document models of primary prevention within human services.

This one-pager describes the research questions and objectives of a project exploring the use of custody relinquishment, or when children enter foster care primarily to obtain behavioral health or disability services.

This two-pager describes several child welfare and Medicaid data linking projects and lessons learned from those projects. For example, the brief highlights key lessons such as the value in providing states with support in navigating data governance and in strengthening and harmonizing data infrastructure on child welfare service.

Children and youth involved with the child welfare system frequently have behavioral health conditions and are high users of behavioral health services compared to children and youth in other Medicaid eligibility categories.

Increasing availability of linked child welfare and Medicaid data can advance research on the intersections of child welfare and Medicaid. The project, Child and Caregiver Outcomes Using Linked Data (CCOULD), developed a research-use dataset combining child welfare records and Medicaid claims for children and families involved in child welfare systems in Florida and Kentucky.

This brief describes progress in the Child Welfare and Health Infrastructure for Linking and Data Analysis of Resources, Effectiveness, and Needs (CHILDREN) Initiative, which is entering its second year. At this time, four jurisdictions have been selected for participation in the CHILDREN Initiative and are engaging in feasibility studies to determine readiness for linking data.

This research brief uses claims data from the Medicaid and Children's Health Insurance Programs to examine the behavioral health diagnoses and treatment services received by children and youth involved with the child welfare system in 2019.

In recent years several researchers and child welfare agencies have begun developing predictive risk models to support child welfare decision-making. Predictive analytics is a sophisticated form of risk modeling that uses historical data to understand relationships between myriad factors to estimate a probability score for the outcome of interest.

This practice guide is a resource for a broad range of human services programs aiming to be more inclusive of and responsive to fathers. Building on literature from the field and interviews with human services providers that engage fathers in services, this guide outlines strategies for advancing equity in human services programs:

This brief summarizes an environmental scan and series of key informant interviews describing the challenges that human services programs face in identifying participants with substance use disorders (SUD), and subsequently referring them to treatment. The review focused on child welfare services, domestic violence services, Head Start, and Temporary Assistance for Needy Families.