This document introduces child welfare administrators and policy makers to the benefits and challenges faced in using predictive analytics to improve child welfare practice. It suggests questions that administrators and policy makers considering a predictive analytics effort can use to improve the likelihood that the effort will produce useful information and improve outcomes for children and families. Issues discussed include: data sufficiency; data quantity; the identification of a well-considered implementation strategy; resource requirements; stakeholder support; model validation; model accuracy; and model precision. Each criterion is described, with examples, to demonstrate how they may be used to inform planning for a predictive analytics project.
Publication DateNov 2, 2017
TopicsEvaluation Methods | Child Welfare