Right home, right time on track: - nebraska DHHS will develop and implement a statewide predictive analytics system to improve child welfare decision-making, and strengthen permanency outcomes. -…

The Department of Health and Human Services Administration for Children and Families awarded a $595,800 cooperative agreement to the Nebraska Department of Health and Human Services on September 30, 2026, under the Child Abuse and Neglect Discretionary Activities program (CFDA 93.670).

Nebraska DHHS will develop and implement TRACK (Timely Review, Analytics, and Coordination for Kids): Right Home, Right Time, a statewide predictive analytics system designed to strengthen child welfare decision-making and improve permanency outcomes. The initiative will integrate predictive modeling, interactive dashboards, and data visualization tools into existing child welfare practice to identify patterns associated with key outcomes, support earlier intervention, improve resource allocation, and enhance case planning. A core feature of the project is Nebraska's commitment to developing and sustaining the system internally using existing DHHS leadership and technical staff rather than relying on external vendors or proprietary platforms.

The award funds work performed in Nebraska with a period of performance extending from September 30, 2026, through September 29, 2029. The program supports efforts to strengthen prevention, identification, and treatment of child abuse and neglect services at the national, state, and community level through research, demonstration, and service improvement initiatives.

Right home, right time on track: - nebraska DHHS will develop and implement a statewide predictive analytics system to improve child welfare decision-making, and strengthen permanency outcomes. - the nebraska department of health and human services (DHHS), division of children and family services (CFS), proposes to develop and implement track (timely review, analytics, and coordination for kids): right home, right time, a statewide predictive analytics initiative designed to strengthen child welfare decision-making, improve permanency outcomes, and establish sustainable internal analytics capacity. Submitted under the children's bureau predictive analytics in child welfare demonstration grants program, track will provide child welfare professionals with data-informed decision-support tools that complement professional judgment while promoting transparency, accountability, and the responsible use of predictive analytics. Nebraska's child welfare system serves children and families with complex needs requiring timely, informed, and consistent decisions regarding safety, placement, permanency, and service delivery. Although nebraska has invested in continuous quality improvement, performance management, and evidence-informed initiatives such as safely, timely, and accelerated reunification (STAR), opportunities remain to strengthen decision support through advanced analytics. Track will integrate predictive modeling, interactive dashboards, and data visualization tools into existing child welfare practice to identify patterns associated with key outcomes, support earlier intervention, improve resource allocation, and enhance case planning. A distinguishing feature of this proposal is nebraska's commitment to developing and sustaining track internally rather than relying on external vendors or proprietary predictive analytics platforms. Existing DHHS leadership and technical staff will lead project implementation, supported by a graduate research assistant and targeted investments in technology infrastructure, workforce development, evaluation, and stakeholder engagement. Throughout the project, nebraska will establish a governance framework to guide the ethical, transparent, and responsible use of predictive analytics while ensuring that predictive insights remain advisory and continue to support-not replace-the professional judgment of child welfare staff. Major project activities include developing predictive models and decision-support dashboards; strengthening data integration and quality; establishing governance policies and implementation procedures; providing statewide workforce training; evaluating implementation, model performance, and project outcomes; and disseminating lessons learned to support adoption of responsible predictive analytics practices across the child welfare community. By the conclusion of the three-year demonstration project, nebraska DHHS will have established a sustainable, internally managed predictive analytics capability that strengthens organizational decision-making, enhances support for children and families, improves permanency outcomes, and creates a scalable foundation for future innovation within nebraska's child welfare system. The project will also generate practical implementation guidance that can inform other child welfare agencies seeking to responsibly integrate predictive analytics into public-sector practice.