Applying Predictive Analytics: Identifying Family Needs and Improving the Allocation of Resources [Webpage].
Weiner, Dana. Chor, Brian.
Chapin Hall at the University of Chicago.
Chapin Hall at the University of Chicago
1313 East 60th Street
Chicago, IL 60637
This webpage explains Chapin Hall’s Implementation Collaborative’s data analytics team developed predictive analytic models to address risk of repeat reports for child abuse or neglect. Chapin Hall then worked with an agency to incorporate these findings into system operations. With this information, the child welfare agency was able to direct additional and timely resources to families who have the highest indicators of frequent system involvement. It notes by applying methodological expertise and implementation experience to agency operations, Chapin Hall is integrating responsible, rigorous predictive analytic approaches to enhance resource allocation and service effectiveness. This allows service providers to: maximize the potential of evidence-based interventions, make resources available to families based on their level of need, and gauge provider performance equitably. Strategies that are being used to reduce the likelihood of reinforcing systemic bias in the models are also discussed. (Author abstract modified); Conference booklet: https://www.chapinhall.org/wp-content/uploads/Predictive-Analytics-Workshop-SSWR18-1.10.18-FINAL.pdf<.a>
predictive analytics; predictor variables; models; reentry; child abuse; child neglect; indicators; family assessment