A machine learning approach for identifying predictors of success in a Medicaid-funded, community-based behavioral health program using the Child and Adolescent Needs and Strengths (CANS)

Jesse D. Troy, Ryan M. Torrie and Daniel N. Warner

Children and Youth Services Review, 2021, vol. 126, issue C

Abstract: The CANS is the most popular measurement tool in the System of Care (SoC), with the potential to generate an estimated 1.9 million evaluations per year in the United States. This dataset has broad potential for decision support and outcomes monitoring, yet many SoC services do not yet leverage this information asset. We report here the results of a pilot project in which we applied machine learning methods to CANS data for the purpose of identifying clinical profiles associated with improvement in a public community-based behavioral health program in Pennsylvania.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:cysrev:v:126:y:2021:i:c:s019074092100089x

DOI: 10.1016/j.childyouth.2021.106010

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