Extracting sexual trauma mentions from electronic medical notes using natural language processing

Guy Divita, Emily Brignone, Marjorie E. Carter, Ying Suo, Rebecca K. Blais, Matthew H. Samore, Jamison D. Fargo, Adi V. Gundlapalli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Patient history of sexual trauma is of clinical relevance to healthcare providers as survivors face adverse health-related outcomes. This paper describes a method for identifying mentions of sexual trauma within the free text of electronic medical notes. A natural language processing pipeline for information extraction was developed and scaled to handle a large corpus of electronic medical notes used for this study from US Veterans Health Administration medical facilities. The tool was used to identify sexual trauma mentions and create snippets around every asserted mention based on a domain-specific lexicon developed for this purpose. All snippets were evaluated by trained human reviewers. An overall positive predictive value (PPV) of 0.90 for identifying sexual trauma mentions from the free text and a PPV of 0.71 at the patient level are reported. The metrics are superior for records from female patients.

Original languageEnglish (US)
Title of host publicationMEDINFO 2017
Subtitle of host publicationPrecision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics
EditorsAdi V. Gundlapalli, Jaulent Marie-Christine, Zhao Dongsheng
PublisherIOS Press BV
Pages351-355
Number of pages5
ISBN (Electronic)9781614998297
DOIs
StatePublished - 2017
Externally publishedYes
Event16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017 - Hangzhou, China
Duration: Aug 21 2017Aug 25 2017

Publication series

NameStudies in Health Technology and Informatics
Volume245
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Other

Other16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017
Country/TerritoryChina
CityHangzhou
Period8/21/178/25/17

Keywords

  • Information retrieval
  • Natural language processing
  • Trauma and stressor related disorders

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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