Health AI Central
Peer-Reviewed Publication
Sci Rep2025;15(1):3648.January 29, 2025Journal Article

A deep learning analysis for dual healthcare system users and risk of opioid use disorder.

Ying Yin1,2, Elizabeth Workman1,2, Phillip Ma1,2, Yan Cheng1,2, Yijun Shao1,2, Joseph L Goulet3,4, Friedhelm Sandbrink1, Cynthia Brandt3,4, Christopher Spevak5, Jacob T Kean6, William Becker3,4, Alexander Libin5,7, Nawar Shara5,7, Helen M Sheriff1, Jorie Butler6, Rajeev M Agrawal7, Joel Kupersmith8, Qing Zeng-Trietler9,10
1Washington DC VA Medical Center, Washington, DC, USA.
2Biomedical Informatics Center, George Washington University, Washington, DC, USA.
3VA Connecticut Healthcare System, West Haven, CT, USA.
4Yale School of Medicine, New Haven, CT, USA.
5Georgetown University School of Medicine, Washington, DC, USA.
6The University of Utah, Salt Lake City, UT, USA.
7MedStar Health, Washington, DC, USA.
8Georgetown University School of Medicine, Washington, DC, USA. jk1688@georgetown.edu.
9Washington DC VA Medical Center, Washington, DC, USA. zengq@gwu.edu.
10Biomedical Informatics Center, George Washington University, Washington, DC, USA. zengq@gwu.edu.
PubMed PMC DOI PDF

Abstract

The opioid crisis has disproportionately affected U.S. veterans, leading the Veterans Health Administration to implement opioid prescribing guidelines. Veterans who receive care from both VA and non-VA providers-known as dual-system users-have an increased risk of Opioid Use Disorder (OUD). The interaction between dual-system use and demographic and clinical factors, however, has not been previous…

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