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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
Completed
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT06815562
Enrollment
213
Registered
2025-02-07
Start date
2025-02-03
Completion date
2026-01-26
Last updated
2026-07-08

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Adolescent Well-Being, Mental Health Wellness

Brief 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 were 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.

Interventions

PSP is a machine-learning based clinical decision support tool that is designed to assist clinical team members in making placement decisions for youth.

Sponsors

Outcome Referrals, Inc.
Lead SponsorINDUSTRY
National Institute of Mental Health (NIMH)
CollaboratorNIH
State of Iowa Department of Health and Human Services
CollaboratorUNKNOWN

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE

Intervention model description

Efficacy (randomized clinical trial) study

Eligibility

Sex/Gender
ALL
Healthy volunteers
No

Inclusion criteria

* Completed TOP CS assessment

Exclusion criteria

* None

Design outcomes

Primary

MeasureTime frameDescription
Mean Difference in Average Domain Z-scores Across Raters Within Two Weeks on the Clinical Scale of the Treatment Outcome Package (TOP-CS) Between a) Baseline and b) Follow-up.At baseline (within 2 weeks of study start) and approximately 60-120 days laterThe Child Treatment Outcome Package (TOP-CS) is a 48-item scale for children (ages 3 - 18) that assesses 13 domains. The Adolescent TOP-CS is a 58-item scale for adolescents (ages 11 - 21) that assesses 12 domains. TOP-CS assesses the client's past 2-week experience on domains including Depression, Violence, and Suicidality (scores are risk-adjusted for case mix variables assessed via 37 items on the companion TOP-Case Mix form regarding stressful life events, comorbidity). Participants answer "All" to "None of the Time" for each item on a 6-point Likert scale. A domain z-score of 0 represents the general population mean. Domain z-scores are averaged into a summary score per participant. Higher (more positive) average z-scores indicate greater symptom severity and lower behavioral well-being (a worse outcome). The value reported is the mean difference in this average z-score between baseline and follow-up; a negative mean difference indicates improvement (reduced severity).

Secondary

MeasureTime frameDescription
Mean Difference Between the Average Risk-adjusted Predicted TOP-CS Total Score Across Raters at Study Baseline and the Actual Average TOP-CS Total Score Across Raters at Follow-upAt baseline (within 2 weeks of study start) and approximately 60-120 days laterThe Child Treatment Outcome Package (TOP-CS) is a 48-item scale for children (ages 3 - 18) that assesses 13 domains. The Adolescent TOP-CS is a 58-item scale for adolescents (ages 11 - 21) that assesses 12 behavioral health domains. Participants answer "All" to "None of the Time" for each item on a 6-point Likert scale. The TOP-CS Total Score is computed by averaging item responses. The range is 48 to 288 for the Child TOP-CS and 56 to 336 for the Adolescent TOP-CS. Higher Total Scores represent better behavioral well-being (a better outcome). Total Scores are averaged across raters per participant. The value reported is the mean difference between each participant's model-predicted, risk-adjusted Total Score (the outcome expected given their baseline profile) and their actual observed Total Score at follow-up. A positive mean difference indicates that the actual follow-up outcome exceeded the model-predicted outcome (i.e., the participant did better than predicted).

Countries

United States

Participant flow

Recruitment details

Data were collected from all clients as part of standard clinical practice. Only clients with valid data at baseline and follow-up were included in these samples.

Baseline characteristics

Characteristic
Age, Continuous15.4 years
STANDARD_DEVIATION 2.08
Ethnicity (NIH/OMB)
Hispanic or Latino
2 Participants
Ethnicity (NIH/OMB)
Not Hispanic or Latino
33 Participants
Ethnicity (NIH/OMB)
Unknown or Not Reported
0 Participants
Race (NIH/OMB)
American Indian or Alaska Native
8 Participants
Race (NIH/OMB)
Asian
2 Participants
Race (NIH/OMB)
Black or African American
30 Participants
Race (NIH/OMB)
More than one race
0 Participants
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
0 Participants
Race (NIH/OMB)
Unknown or Not Reported
1 Participants
Race (NIH/OMB)
White
148 Participants
Sex/Gender, Customized
Female
37 Participants
Sex/Gender, Customized
Male
14 Participants
Sex/Gender, Customized
Unknown/Unreported
1 Participants

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
EG002
affected / at risk
EG003
affected / at risk
deaths
Total, all-cause mortality
0 / 350 / 270 / 760 / 75
other
Total, other adverse events
0 / 350 / 270 / 760 / 75
serious
Total, serious adverse events
0 / 350 / 270 / 760 / 75

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Jul 9, 2026