TY - GEN
T1 - Identifying peripheral arterial disease cases using natural language processing of clinical notes
AU - Afzal, Naveed
AU - Sohn, Sunghwan
AU - Abram, Sara
AU - Liu, Hongfang
AU - Kullo, Iftikhar J.
AU - Arruda-Olson, Adelaide M.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/4/18
Y1 - 2016/4/18
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84968571757&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84968571757&partnerID=8YFLogxK
U2 - 10.1109/BHI.2016.7455851
DO - 10.1109/BHI.2016.7455851
M3 - Conference contribution
AN - SCOPUS:84968571757
T3 - 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016
SP - 126
EP - 131
BT - 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016
Y2 - 24 February 2016 through 27 February 2016
ER -