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Development of a Natural Language Processing System to Identify Clinical Documentation of Electronic Cigarette Use
Patrick R. Alba, Qiwei Gan, Mengke Hu, Shu-Hong Zhu, Scott E. Sherman, Scott L. DuVall, Mike Conway
659 - 663
10.3233/SHTI231047
Research Article
Studies in Health Technology and Informatics
Volume 310: MEDINFO 2023 — The Future Is Accessible
Abstract

Electronic Nicotine Delivery Systems (ENDS) use has increased substantially in the United States since 2010. To date, there is limited evidence regarding the nature and extent of ENDS documentation in the clinical note. In this work we investigate the effectiveness of different approaches to identify a patient’s documented ENDS use. We report on the development and validation of a natural language processing system to identify patients with explicit documentation of ENDS using a large national cohort of patients at the United States Department of Veterans Affairs.

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