Examining Placement Disruption in Child Welfare

Abstract

Child welfare systems in the United States are increasingly focused on reducing the number of children who come into care, reducing the length of time that those children are in care, and reducing the use of more restrictive placements such as residential treatment. In this context, child welfare systems are increasingly interested in supporting placement decision making with standardized assessments and decision tools. The current article describes an analysis of information from the Tennessee child welfare system demonstrating that the placements of children whose first placement is consistent with an assessment-based decision support algorithm are more stable than the placements of children whose first placement is not consistent with the algorithm recommendation. These results add to the growing body of literature suggesting that such decision supports are associated with improved outcomes and the implications for child welfare system design are briefly discussed.