Journal article
Ankle- and Toe-Brachial Index for Peripheral Artery Disease Identification: Unlocking Clinical Data Through Novel Methods
Circulation. Cardiovascular interventions, Vol.15(3), pp.e011092-e011092
03/2022
DOI: 10.1161/CIRCINTERVENTIONS.121.011092
PMCID: PMC10807980
PMID: 35176872
Abstract
Despite its high prevalence and clinical impact, research on peripheral artery disease (PAD) remains limited due to poor accuracy of billing codes. Ankle-brachial index (ABI) and toe-brachial index can be used to identify PAD patients with high accuracy within electronic health records.
We developed a novel natural language processing (NLP) algorithm for extracting ABI and toe-brachial index values and laterality (right or left) from ABI reports. A random sample of 800 reports from 94 Veterans Affairs facilities during 2015 to 2017 was selected and annotated by clinical experts. We trained the NLP system using random forest models and optimized it through sequential iterations of 10-fold cross-validation and error analysis on 600 test reports and evaluated its final performance on a separate set of 200 reports. We also assessed the accuracy of NLP-extracted ABI and toe-brachial index values for identifying patients with PAD in a separate cohort undergoing ABI testing.
The NLP system had an overall precision (positive predictive value) of 0.85, recall (sensitivity) of 0.93, and F1 measure (accuracy) of 0.89 to correctly identify ABI/toe-brachial index values and laterality. Among 261 patients with ABI testing (49% PAD), the NLP system achieved a positive predictive value of 92.3%, sensitivity of 83.1%, and specificity of 93.1% to identify PAD when compared with a structured chart review. The above findings were consistent in a range of sensitivity analysis.
We successfully developed and validated an NLP system for identifying patients with PAD within the Veterans Affairs electronic health record. Our findings have broad implications for PAD research and quality improvement.
Details
- Title: Subtitle
- Ankle- and Toe-Brachial Index for Peripheral Artery Disease Identification: Unlocking Clinical Data Through Novel Methods
- Creators
- Julia E Friberg - University of IowaAbdul H Qazi - Massachusetts General HospitalBrenden Boyle - University of MinnesotaCarrie Franciscus - Roy J. and Lucille A. Carver College of MedicineMary Vaughan-Sarrazin - Roy J. and Lucille A. Carver College of MedicineDax Westerman - Vanderbilt University Medical CenterOlga V Patterson - Veterans Health AdministrationSharidan K Parr - Vanderbilt University Medical CenterMichael E Matheny - VA Tennessee Valley Healthcare SystemShipra Arya - Stanford UniversityKim G Smolderen - Yale UniversityBrian C Lund - University of IowaGlenn T Gobbel - VA Tennessee Valley Healthcare SystemSaket Girotra - Roy J. and Lucille A. Carver College of Medicine
- Resource Type
- Journal article
- Publication Details
- Circulation. Cardiovascular interventions, Vol.15(3), pp.e011092-e011092
- DOI
- 10.1161/CIRCINTERVENTIONS.121.011092
- PMID
- 35176872
- PMCID
- PMC10807980
- ISSN
- 1941-7640
- eISSN
- 1941-7632
- Language
- English
- Date published
- 03/2022
- Academic Unit
- Health Management and Policy; Epidemiology; Cardiovascular Medicine; General Internal Medicine; Internal Medicine
- Record Identifier
- 9984359697402771
Metrics
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