Child Maltreatment

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 prevention within human services.

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 prevention within human services.

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 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.

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.

This report provides information to state, tribal, and local child welfare and behavioral health agencies that are interested in linking their Medicaid and child welfare data.

This brief presents estimates of the number and percentage of children whose parents engage in problematic substance use, including past-year substance use and SUD by substance type and child demographics. Key findings include:

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.