Predicting substance use disorder using long-term attention deficit hyperactivity disorder medication records in Truven

Sajjad Fouladvand, Emily R. Hankosky, Heather Bush, Jin Chen, Linda P. Dwoskin, Patricia R. Freeman, Darren W. Henderson, Kathleen Kantak, Jeffery Talbert, Shiqiang Tao, Guo Qiang Zhang

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

About 20% of individuals with attention deficit hyperactivity disorder are first diagnosed during adolescence. While preclinical experiments suggest that adolescent-onset exposure to attention deficit hyperactivity disorder medication is an important factor in the development of substance use disorder phenotypes in adulthood, the long-term impact of attention deficit hyperactivity disorder medication initiated during adolescence has been largely unexplored in humans. Our analysis of 11,624 adolescent enrollees with attention deficit hyperactivity disorder in the Truven database indicates that temporal medication features, rather than stationary features, are the most important factors on the health consequences related to substance use disorder and attention deficit hyperactivity disorder medication initiation during adolescence.

Original languageEnglish
Pages (from-to)787-802
Number of pages16
JournalHealth Informatics Journal
Volume26
Issue number2
DOIs
StatePublished - Jun 1 2020

Bibliographical note

Publisher Copyright:
© The Author(s) 2019.

Keywords

  • attention deficit hyperactivity disorder
  • big data
  • deep learning
  • long-short term memory model
  • substance use disorder

ASJC Scopus subject areas

  • Health Informatics

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