title: Building a Natural Language Processing Tool to Identify Patients With High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes.
abstract: Delayed diagnosis of Kawasaki disease (KD) may lead to serious cardiac complications. We sought to create and test the performance of a natural language processing (NLP) tool, the KD-NLP, in the identification of emergency department (ED) patients for whom the diagnosis of KD should be considered.
  
  
  
  We developed an NLP tool that recognizes the KD diagnostic criteria based on standard clinical terms and medical word usage using 22 pediatric ED notes augmented by Unified Medical Language System vocabulary. With high suspicion for KD defined as fever and three or more KD clinical signs, KD-NLP was applied to 253 ED notes from children ultimately diagnosed with either KD or another febrile illness. We evaluated KD-NLP performance against ED notes manually reviewed by clinicians and compared the results to a simple keyword search.
  
  
  
  KD-NLP identified high-suspicion patients with a sensitivity of 93.6% and specificity of 77.5% compared to notes manually reviewed by clinicians. The tool outperformed a simple keyword search (sensitivity = 41.0%; specificity = 76.3%).
  
  
  
  KD-NLP showed comparable performance to clinician manual chart review for identification of pediatric ED patients with a high suspicion for KD. This tool could be incorporated into the ED electronic health record system to alert providers to consider the diagnosis of KD. KD-NLP could serve as a model for decision support for other conditions in the ED.
authors.affiliation: Department of Biomedical Informatics, University of California, San Diego, CA.
authors.forename: Son
authors.initials: S
authors.lastname: Doan
authors.affiliation: Department of Biomedical Informatics, University of California, San Diego, CA.
authors.forename: Cleo K
authors.initials: CK
authors.lastname: Maehara
authors.affiliation: Department of Biomedical Informatics, University of California, San Diego, CA.
authors.forename: Juan D
authors.initials: JD
authors.lastname: Chaparro
authors.affiliation: Department of Computer Science, University of Pittsburgh, Pittsburgh, PA.
authors.forename: Sisi
authors.initials: S
authors.lastname: Lu
authors.affiliation: The University of Texas Health Science Center at Houston, Houston, TX.
authors.forename: Ruiling
authors.initials: R
authors.lastname: Liu
authors.affiliation: Children's Healthcare of Atlanta, Atlanta, GA.
authors.forename: Amanda
authors.initials: A
authors.lastname: Graham
authors.affiliation: Department of Pediatrics, University of California at San Diego, La Jolla, CA.
authors.forename: Erika
authors.initials: E
authors.lastname: Berry
authors.affiliation: Department of Biomedical Informatics, University of California, San Diego, CA.
authors.forename: Chun-Nan
authors.initials: CN
authors.lastname: Hsu
authors.affiliation: Department of Pediatrics, University of California at San Diego, La Jolla, CA.|Rady Children's Hospital San Diego, San Diego, CA.
authors.forename: John T
authors.initials: JT
authors.lastname: Kanegaye
authors.affiliation: Children's Healthcare of Atlanta, Atlanta, GA.|Emory University School of Medicine, Atlanta, GA.
authors.forename: David D
authors.initials: DD
authors.lastname: Lloyd
authors.affiliation: Department of Biomedical Informatics, University of California, San Diego, CA.
authors.forename: Lucila
authors.initials: L
authors.lastname: Ohno-Machado
authors.affiliation: Department of Pediatrics, University of California at San Diego, La Jolla, CA.|Rady Children's Hospital San Diego, San Diego, CA.
authors.forename: Jane C
authors.initials: JC
authors.lastname: Burns
authors.affiliation: Department of Pediatrics, University of California at San Diego, La Jolla, CA.|Rady Children's Hospital San Diego, San Diego, CA.
authors.forename: Adriana H
authors.initials: AH
authors.lastname: Tremoulet
mesh_terms: D002648:Child; D057225:Data Mining / Q000379:methods; D057286:Electronic Health Records; D004636:Emergency Service, Hospital; D006801:Humans; D009080:Mucocutaneous Lymph Node Syndrome / Q000175:diagnosis* / Q000628:therapy; D009323:Natural Language Processing; D012680:Sensitivity and Specificity
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