What does this research mean for the field?

A cross-sector, data-driven risk stratification algorithm can successfully identify Medicaid-enrolled children at risk for out-of-home placement, provided that substantial legal, political, and administrative data-sharing challenges are navigated. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

Describe the development and implementation of an expert-derived, data-driven algorithm to identify out-of-home placement risk among pediatric Medicaid enrollees and address interagency data-sharing barriers.

September 10, 2026Medical CareOpen Access

An Expert-Derived Data-Driven Approach to Identifying Medicaid Children at Risk of Out-of-Home Placement

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Authors

RHRose Y. HardyNationwide Children's Hospital DCDavid P. CicconeNationwide Children's Hospital EBEmelie BaileyThe Ohio State University Wexner Medical Center

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Implication

Implementation study demonstrates cross-sector risk stratification for out-of-home placement in pediatric Medicaid enrollees, highlighting the feasibility of multi-agency data linkage.

Key Points

Describe the development and implementation of an expert-derived, data-driven algorithm to identify out-of-home placement risk among pediatric Medicaid enrollees and address interagency data-sharing barriers.
Conducted cross-sector data integration involving academic and government partners for Medicaid-enrolled children across two Ohio counties from 2022 to 2024 (n=27,000).
Constructed a three-category risk stratification algorithm incorporating Medicaid claims, child welfare information systems, area-level social determinants of health, and patient-reported health risk assessments under the Ohio Integrated Care for Kids Model.
Successfully established multi-agency legal frameworks and data use agreements to merge dynamic administrative datasets across healthcare and child welfare sectors.
Identified essential operational requirements, notably establishing adequate retrospective lookback windows to account for retroactively updated administrative data and cultivating sustained interagency relationships.

Cite This Study

Hardy et al. (2026) studied this question.

synapsesocial.com/papers/6aa27ad858559d80afc73ada https://doi.org/10.1097/mlr.0000000000002307

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Implication

Implementation study demonstrates cross-sector risk stratification for out-of-home placement in pediatric Medicaid enrollees, highlighting the feasibility of multi-agency data linkage.

An Expert-Derived Data-Driven Approach to Identifying Medicaid Children at Risk of Out-of-Home Placement

Discussion

Member takes

Implication

Key Points

Cite This Study

An Expert-Derived Data-Driven Approach to Identifying Medicaid Children at Risk of Out-of-Home Placement

Discussion

Member takes

Implication

Key Points

Cite This Study

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