Predictive analytics for ohio child protection and success which will explore using data to identify higher risk for RE-entry, school failure, and needed higher-level supervision - ohio will use the…

The Department of Health and Human Services Administration for Children and Families awarded the Ohio Department of Children and Youth a cooperative agreement totaling $599,580 on September 30, 2026, under the Child Abuse and Neglect Discretionary Activities program (CFDA 93.670).

The award funds the development and implementation of predictive analytics to strengthen child protection decision-making and outcomes in Ohio. Year 1 activities include problem identification, environmental scoping, model specification, and development. Year 2 will focus on training county agency staff to use the predictive model and accompanying tools. Subsequent years will involve monitoring and recalibration of the models alongside evaluation of outcomes and impact. The predictive analytics system will identify children and youth at elevated risk for re-entry into care, predict school failure, support higher-level case supervision decisions, and identify predictors for needed services and supports, with specific emphasis on middle and high school age youth at risk for re-entry and off-track for graduation. Expected outcomes include improved consistency and quality of decision-making, workforce efficiency, and proactive connection to support and needed interventions for families and youth.

Performance occurs in Ohio, with a period of performance running from September 30, 2026 through September 29, 2029.

Predictive analytics for ohio child protection and success which will explore using data to identify higher risk for RE-entry, school failure, and needed higher-level supervision - ohio will use the funds and timeline of this opportunity to align with the administration for children's priorities of evidenced-based and outcome-informed approaches; coordinate with community partners; strengthen families, promote safe and stable home environments, and improve outcomes for children and youth; and support pathways to employment, job retention, and economic independence for individuals. Specifically, we will explore the establishment and use of predictive analytics to (1) elevate cases for higher-level supervision, (2) identify children and youth at risk for RE-entry into care, and (3) identify predictors for needed services and supports, with a special emphasis on middle to high school age youth at risk for RE-entry into care and off-track for graduating high school. Year 1 will include problem identification and environmental scoping as well as model specification and development. Year 2 will see ohio training staff in county agencies on how to use the model and accompanying tools. The remainder of the project timeline will be used for monitoring and recalibration of the predictive models alongside the evaluation and monitoring of outcomes and impact. Outcomes are expected to include consistency and quality of decision-making, workforce efficiency, proactive connection to support and needed interventions for families and youth.