title: Differences in nationwide cohorts of acupuncture users identified using structured and free text medical records.
abstract: Integrative medicine including complementary and alternative medicine (CAM) has become more available through mainstream health providers. Acupuncture is one of the most widely used CAM therapies, though its efficacy for treating various conditions requires further investigation. To assist with such investigations, we set out to identify acupuncture patient cohorts using a nationwide clinical data repository. Acupuncture patients were identified using both structured data and unstructured free text notes: 44,960 acupuncture patients were identified using structured data consisting of CPT codes;. Using unstructured free text clinical notes, we trained a support vector classifier with 86% accuracy and was able to identify an additional 101,628 acupuncture patients not identified through structured data (a 226% increase). In addition, characteristics of the patients identified through structured and unstructured data were compared, which show differences in geographic locations and medical service usage patterns. Patients identified with structured data displayed a consistently higher use of the Veterans Health Administration (VHA) medical system.
authors.affiliation: VA Salt Lake City Health Care System, University of Utah, Salt Lake City, Utah ; Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah.
authors.forename: Doug
authors.initials: D
authors.lastname: Redd
authors.affiliation: VA Salt Lake City Health Care System, University of Utah, Salt Lake City, Utah.
authors.forename: Jinqiu
authors.initials: J
authors.lastname: Kuang
authors.affiliation: VA Salt Lake City Health Care System, University of Utah, Salt Lake City, Utah ; Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah.
authors.forename: Qing
authors.initials: Q
authors.lastname: Zeng-Treitler
mesh_terms: D015670:Acupuncture Therapy / Q000706:statistics & numerical data*; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D039702:Current Procedural Terminology; D057286:Electronic Health Records; D006787:Hospitals, Veterans; D006801:Humans; D008297:Male; D008875:Middle Aged; D009323:Natural Language Processing; D010044:Outpatient Clinics, Hospital; D057386:Search Engine; D060388:Support Vector Machine; D014481:United States; D014728:Veterans / Q000706:statistics & numerical data