title: Identifying Peripheral Arterial Disease Cases Using Natural Language Processing of Clinical Notes.
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.
authors.affiliation: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester MN.
authors.forename: Naveed
authors.initials: N
authors.lastname: Afzal
authors.affiliation: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester MN.
authors.forename: Sunghwan
authors.initials: S
authors.lastname: Sohn
authors.affiliation: Division of Cardiovascular Diseases, Mayo Clinic, Rochester MN.
authors.forename: Sara
authors.initials: S
authors.lastname: Abram
authors.affiliation: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester MN.
authors.forename: Hongfang
authors.initials: H
authors.lastname: Liu
authors.affiliation: Division of Cardiovascular Diseases, Mayo Clinic, Rochester MN.
authors.forename: Iftikhar J
authors.initials: IJ
authors.lastname: Kullo
authors.affiliation: Division of Cardiovascular Diseases, Mayo Clinic, Rochester MN.
authors.forename: Adelaide M
authors.initials: AM
authors.lastname: Arruda-Olson