NCT06815562

Predict the Best Level of Care Placement for Each Child's Behavioral Health Needs - Efficacy Study

Placement Success Predictor: Using Site-Customized Machine Learning Models to Predict the Best Level of Care Placement for Each Child's Behavioral Health Needs

• Status: Enrolling By Invitation
• Phase: N/A
• Study type: Interventional
• Enrollment: 300 (estimated)
• Sponsor: Outcome Referrals, Inc. · Industry
• Sex: All
• Age: —
• Healthy volunteers: Not accepted

Summary

The purpose of this randomized clinical trial is to test the efficacy of a new clinical decision support tool, Placement Success Predictor (PSP). PSP will provide placement-specific predictions about the likelihood of a youth having a good outcome in each placement type using machine learning algorithms. The primary hypothesis is that if clinical team members have access to PSP results for youth in the experimental group, these youth will have better outcomes at the 3-month follow-up compared to youth in the control group.

Detailed description

In 2017, a total of 669,799 children were confirmed victims of maltreatment in the United States; of the 442,733 children in foster care, 34% have been in more than one placement and 11% are in a group home or institution. Stakes are extremely high for making the best out-of-home placement choice per child because some placement types and multiple placements are associated with poor outcomes. In the past few years, legislation has been created to guide placement decisions for children. Federal law 42 U.S. Code 675 requires that children in the care of the state are placed "in a safe setting that is the least restrictive (most family like)." In addition, the Family First Prevention Services Act signed into law by the U.S. Congress in 2018 includes measures to reduce the number of children in long-term residential settings. This study is an effort to develop and test a science-based clinical decision support tool using behavioral health data collected through standard clinical practice. A randomized controlled trial (RCT) design will be used to assess efficacy of clinical team access to Placement Success Predictor (PSP) on child welfare clients' well-being outcomes and healthcare costs. Sample. Clients at the State of Iowa Department of Health and Human Services (Iowa HHS) are the sample for this efficacy study. Randomization. The outcome of a single coin toss was applied to an undisclosed algorithm for the client's record number to determine who gets assigned to the experimental group (i.e., client has PSP results). Methods. The Treatment Outcome Package (TOP), a behavioral health assessment, is a standard part of care delivered in Iowa and its completion is required by the state. Iowa HHS clinical teams will be provided PSP results for clients in the experimental condition. A request for a waiver of consent for this study was approved by the WCG IRB.

Conditions

• Adolescent Well-Being
• Mental Health Wellness

Interventions

Type	Name	Description
OTHER	Clinical team access to Placement Success Predictor (PSP) results	PSP is a machine-learning based clinical decision support tool that is designed to assist clinical team members in making placement decisions for youth.

Timeline

• Start date: 2025-02-03
• Primary completion: 2025-12-31
• Completion: 2025-12-31
• First posted: 2025-02-07
• Last updated: 2025-02-17

Locations

1 site across 1 country: United States