title: Predictive analytics and child protection: constraints and opportunities.
abstract: This paper considers how predictive analytics might inform, assist, and improve decision making in child protection. Predictive analytics represents recent increases in data quantity and data diversity, along with advances in computing technology. While the use of data and statistical modeling is not new to child protection decision making, its use in child protection is experiencing growth, and efforts to leverage predictive analytics for better decision-making in child protection are increasing. Past experiences, constraints and opportunities are reviewed. For predictive analytics to make the most impact on child protection practice and outcomes, it must embrace established criteria of validity, equity, reliability, and usefulness.
authors.affiliation: National Council on Crime and Delinquency, 426 South Yellowstone Drive, Suite 250, Madison, WI 53719, USA.
authors.forename: Jesse
authors.initials: J
authors.lastname: Russell
mesh_terms: D002648:Child; D002649:Child Abuse / Q000517:prevention & control / Q000706:statistics & numerical data*; D000068216:Child Protective Services / Q000379:methods / Q000592:standards*; D003657:Decision Making; D005544:Forecasting; D006801:Humans; D015233:Models, Statistical; D018570:Risk Assessment / Q000379:methods
keywords: Child protection; Decision making; Predictive analytics; Risk assessment