Automated identification of patients with a diagnosis of binge eating disorder from narrative electronic health records.

Brandon K Bellows, Joanne LaFleur, Aaron W C Kamauu, Thomas Ginter, Tyler B Forbush, Stephen Agbor, Dylan Supina, Paul Hodgkins, Scott L DuVall
Author Information
  1. Brandon K Bellows: VA Salt Lake City Health Care System, Salt Lake City, Utah, USA.

Abstract

Binge eating disorder (BED) does not have an International Classification of Diseases, 9th or 10th edition code, but is included under 'eating disorder not otherwise specified' (EDNOS). This historical cohort study identified patients with clinician-diagnosed BED from electronic health records (EHR) in the Department of Veterans Affairs between 2000 and 2011 using natural language processing (NLP) and compared their characteristics to patients identified by EDNOS diagnosis codes. NLP identified 1487 BED patients with classification accuracy of 91.8% and sensitivity of 96.2% compared to human review. After applying study inclusion criteria, 525 patients had NLP-identified BED only, 1354 had EDNOS only, and 68 had both BED and EDNOS. Patient characteristics were similar between the groups. This is the first study to use NLP as a method to identify BED patients from EHR data and will allow further epidemiological study of patients with BED in systems with adequate clinical notes.

Keywords

References

  1. Yearb Med Inform. 2008;:128-44 [PMID: 18660887]
  2. J Am Med Inform Assoc. 2012 Sep-Oct;19(5):859-66 [PMID: 22437073]
  3. Psychol Med. 2005 Nov;35(11):1543-51 [PMID: 16219112]
  4. J Consult Clin Psychol. 2001 Apr;69(2):317-22 [PMID: 11393608]
  5. Biol Psychiatry. 2013 May 1;73(9):904-14 [PMID: 23290497]
  6. Obes Surg. 2001 Oct;11(5):576-80 [PMID: 11594098]
  7. Int J Eat Disord. 2012 Apr;45(3):353-61 [PMID: 22506283]
  8. PLoS One. 2012;7(11):e48450 [PMID: 23144886]
  9. Am J Manag Care. 2007 Jun;13(6 Part 1):281-8 [PMID: 17567225]
  10. Soc Psychiatry Psychiatr Epidemiol. 2012 Oct;47(10):1669-73 [PMID: 22237718]
  11. J Biomed Inform. 2009 Oct;42(5):839-51 [PMID: 19435614]
  12. BMJ. 2003 Jun 28;326(7404):1439-43 [PMID: 12829558]
  13. Braz J Med Biol Res. 2005 Nov;38(11):1663-7 [PMID: 16258636]
  14. Obes Res. 2001 Jul;9(7):418-22 [PMID: 11445665]
  15. J Med Internet Res. 2005 Mar 14;7(1):e3 [PMID: 15829475]
  16. JAMA. 2001 Apr 4;285(13):1766 [PMID: 11277836]
  17. BMC Med Inform Decis Mak. 2012 Jul 11;12:34 [PMID: 22533507]
  18. Eat Weight Disord. 2012 Sep;17(3):e185-93 [PMID: 23086254]
  19. Int J Eat Disord. 2011 Sep;44(6):524-30 [PMID: 21823138]
  20. Int J Eat Disord. 2012 May;45(4):531-6 [PMID: 21882218]
  21. Compr Psychiatry. 2000 Mar-Apr;41(2):111-5 [PMID: 10741889]
  22. J Am Med Inform Assoc. 1997 Sep-Oct;4(5):342-55 [PMID: 9292840]
  23. Biol Psychiatry. 2007 Feb 1;61(3):348-58 [PMID: 16815322]
  24. Curr Psychiatry Rep. 2012 Aug;14(4):406-14 [PMID: 22644309]
  25. Ann Intern Med. 1995 May 1;122(9):681-8 [PMID: 7702231]

MeSH Term

Algorithms
Binge-Eating Disorder
Electronic Health Records
Humans
Narration
Natural Language Processing

Word Cloud

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