A deep learning analysis for dual healthcare system users and risk of opioid use disorder
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)....
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| Format: | Article |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-77602-4 |
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| author | Ying Yin Elizabeth Workman Phillip Ma Yan Cheng Yijun Shao Joseph L. Goulet Friedhelm Sandbrink Cynthia Brandt Christopher Spevak Jacob T. Kean William Becker Alexander Libin Nawar Shara Helen M. Sheriff Jorie Butler Rajeev M. Agrawal Joel Kupersmith Qing Zeng-Trietler |
| author_facet | Ying Yin Elizabeth Workman Phillip Ma Yan Cheng Yijun Shao Joseph L. Goulet Friedhelm Sandbrink Cynthia Brandt Christopher Spevak Jacob T. Kean William Becker Alexander Libin Nawar Shara Helen M. Sheriff Jorie Butler Rajeev M. Agrawal Joel Kupersmith Qing Zeng-Trietler |
| author_sort | Ying Yin |
| collection | DOAJ |
| description | 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 previously explored. We conducted a retrospective study of 856,299 patient instances from the Washington DC and Baltimore VA Medical Centers (2012–2019), using a deep neural network (DNN) and explainable Artificial Intelligence to examine the impact of dual-system use on OUD and how demographic and clinical factors interact with it. Of the cohort, 146,688(17%) had OUD, determined through Natural Language Processing of clinical notes and ICD-9/10 diagnoses. The DNN model, with a 78% area under the curve, confirmed that dual-system use is a risk factor for OUD, along with prior opioid use or other substance use. Interestingly, a history of other drug use interacted negatively with dual-system use regarding OUD risk. In contrast, older age was associated with a lower risk of OUD but interacted positively with dual-system use. These findings suggest that within the dual-system users, patients with certain risk profiles warrant special attention. |
| format | Article |
| id | doaj-art-43de9d3be4f6459e957a73cb9bf29d3d |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-43de9d3be4f6459e957a73cb9bf29d3d2025-02-02T12:19:42ZengNature PortfolioScientific Reports2045-23222025-01-011511910.1038/s41598-024-77602-4A deep learning analysis for dual healthcare system users and risk of opioid use disorderYing Yin0Elizabeth Workman1Phillip Ma2Yan Cheng3Yijun Shao4Joseph L. Goulet5Friedhelm Sandbrink6Cynthia Brandt7Christopher Spevak8Jacob T. Kean9William Becker10Alexander Libin11Nawar Shara12Helen M. Sheriff13Jorie Butler14Rajeev M. Agrawal15Joel Kupersmith16Qing Zeng-Trietler17Washington DC VA Medical CenterWashington DC VA Medical CenterWashington DC VA Medical CenterWashington DC VA Medical CenterWashington DC VA Medical CenterVA Connecticut Healthcare SystemWashington DC VA Medical CenterVA Connecticut Healthcare SystemGeorgetown University School of MedicineThe University of UtahVA Connecticut Healthcare SystemGeorgetown University School of MedicineGeorgetown University School of MedicineWashington DC VA Medical CenterThe University of UtahMedStar HealthGeorgetown University School of MedicineWashington DC VA Medical CenterAbstract 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 previously explored. We conducted a retrospective study of 856,299 patient instances from the Washington DC and Baltimore VA Medical Centers (2012–2019), using a deep neural network (DNN) and explainable Artificial Intelligence to examine the impact of dual-system use on OUD and how demographic and clinical factors interact with it. Of the cohort, 146,688(17%) had OUD, determined through Natural Language Processing of clinical notes and ICD-9/10 diagnoses. The DNN model, with a 78% area under the curve, confirmed that dual-system use is a risk factor for OUD, along with prior opioid use or other substance use. Interestingly, a history of other drug use interacted negatively with dual-system use regarding OUD risk. In contrast, older age was associated with a lower risk of OUD but interacted positively with dual-system use. These findings suggest that within the dual-system users, patients with certain risk profiles warrant special attention.https://doi.org/10.1038/s41598-024-77602-4Deep neural networkExplainable AIOpioid use disorderDual-system useInteraction |
| spellingShingle | Ying Yin Elizabeth Workman Phillip Ma Yan Cheng Yijun Shao Joseph L. Goulet Friedhelm Sandbrink Cynthia Brandt Christopher Spevak Jacob T. Kean William Becker Alexander Libin Nawar Shara Helen M. Sheriff Jorie Butler Rajeev M. Agrawal Joel Kupersmith Qing Zeng-Trietler A deep learning analysis for dual healthcare system users and risk of opioid use disorder Scientific Reports Deep neural network Explainable AI Opioid use disorder Dual-system use Interaction |
| title | A deep learning analysis for dual healthcare system users and risk of opioid use disorder |
| title_full | A deep learning analysis for dual healthcare system users and risk of opioid use disorder |
| title_fullStr | A deep learning analysis for dual healthcare system users and risk of opioid use disorder |
| title_full_unstemmed | A deep learning analysis for dual healthcare system users and risk of opioid use disorder |
| title_short | A deep learning analysis for dual healthcare system users and risk of opioid use disorder |
| title_sort | deep learning analysis for dual healthcare system users and risk of opioid use disorder |
| topic | Deep neural network Explainable AI Opioid use disorder Dual-system use Interaction |
| url | https://doi.org/10.1038/s41598-024-77602-4 |
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