Combining Natural Language Processing of Electronic Medical Notes With Administrative Data to Determine Racial/Ethnic Differences in the Disclosure and Documentation of Military Sexual Trauma in Veterans

Adi V. Gundlapalli, Audrey L. Jones, Andrew Redd, Guy Divita, Emily Brignone, Warren B.P. Pettey, Marjorie E. Carter, Matthew H. Samore, Rebecca K. Blais, Jamison D. Fargo

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Background: Despite national screening efforts, military sexual trauma (MST) is underreported. Little is known of racial/ethnic differences in MST reporting in the Veterans Health Administration (VHA). Objective: This study aimed to compare patterns of MST disclosure in VHA by race/ethnicity. Research Design: Retrospective cohort study of MST disclosures in a national, random sample of Veterans who served in Afghanistan and Iraq and completed MST screens from October 2009 to 2014. We used natural language processing (NLP) to extract MST concepts from electronic medical notes in the year following Veterans' first MST screen. Measure(s): Any evidence of MST (positive MST screen or NLP concepts) and late MST disclosure (NLP concepts following a negative MST screen). Multivariable logistic regressions, stratified by sex, tested racial/ethnic differences in any MST evidence, and late disclosure. Results: Of 6618 male and 6716 female Veterans with MST screen results, 1473 had a positive screen (68 male, 1%; 1405 female, 21%). Of those with a negative screen, 257 evidenced late MST disclosure by NLP (44 male, 39%; 213 female, 13%). Late MST disclosure was usually documented during mental health visits. There were no significant racial/ethnic differences in MST disclosure among men. Among women, blacks were less likely than whites to have any MST evidence (adjusted odds ratio=0.75). In the subsample with any MST evidence, black and Hispanic women were more likely than whites to disclose MST late (adjusted odds ratio=1.89 and 1.59, respectively). Conclusions: Combining NLP results with MST screen data facilitated the identification of under-reported sexual trauma experiences among men and racial/ethnic minority women.

Original languageEnglish (US)
Pages (from-to)S149-S156
JournalMedical care
Volume57
DOIs
StatePublished - Jun 1 2019
Externally publishedYes

Keywords

  • disclosure of trauma
  • informatics
  • military sexual trauma
  • minority health
  • natural language processing
  • veterans

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

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