Comparison of Machine Learning Algorithms Identifying Children at Increased Risk of Out-of-Home Placement: Development and Practical Considerations.

Journal: Health services research
Published Date: Mar 6, 2025

Abstract

OBJECTIVE: To develop a machine learning (ML) algorithm capable of identifying children at risk of out-of-home placement among a Medicaid-insured population.

Authors

  • Tyler J Gorham
    IT Research & Innovation, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, Ohio, USA.
  • Rose Y Hardy
    Center for Child Health Equity and Outcomes Research, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, Ohio, USA.
  • David Ciccone
    Center for Child Health Equity and Outcomes Research, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, Ohio, USA.
  • Deena J Chisolm
    Center for Child Health Equity and Outcomes Research, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, Ohio, USA.

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