Identifying peripheral arterial disease cases using natural language processing of clinical notes

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

5 Scopus citations

Abstract

Peripheral arterial disease (PAD) is a chronic disease that affects millions of people worldwide. Ascertaining PAD status from clinical notes by manual chart review is labor intensive and time consuming. In this paper, we describe a natural language processing (NLP) algorithm for automated ascertainment of PAD status from clinical notes using predetermined criteria. We developed and evaluated our system against a gold standard that was created by medical experts based on manual chart review. Our system ascertained PAD status from clinical notes with high sensitivity (0.96), positive predictive value (0.92), negative predictive value (0.99) and specificity (0.98). NLP approaches can be used for rapid, efficient and automated ascertainment of PAD cases with implications for patient care and epidemiologic research.

Original languageEnglish (US)
Title of host publication3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages126-131
Number of pages6
ISBN (Print)9781509024551
DOIs
StatePublished - Apr 18 2016
Event3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016 - Las Vegas, United States
Duration: Feb 24 2016Feb 27 2016

Other

Other3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016
CountryUnited States
CityLas Vegas
Period2/24/162/27/16

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ASJC Scopus subject areas

  • Health Informatics
  • Health Information Management

Cite this

Afzal, N., Sohn, S., Abram, S., Liu, H. D., Kullo, I. J., & Arruda-Olson, A. M. (2016). Identifying peripheral arterial disease cases using natural language processing of clinical notes. In 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016 (pp. 126-131). [7455851] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BHI.2016.7455851