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Multicenter Study
. 2012 Sep-Oct;19(5):859-66.
doi: 10.1136/amiajnl-2011-000535. Epub 2012 Mar 21.

Automated extraction of ejection fraction for quality measurement using regular expressions in Unstructured Information Management Architecture (UIMA) for heart failure

Jennifer H Garvin  1 , Scott L DuVall, Brett R South, Bruce E Bray, Daniel Bolton, Julia Heavirland, Steve Pickard, Paul Heidenreich, Shuying Shen, Charlene Weir, Matthew Samore, Mary K Goldstein
Affiliations
Multicenter Study

Automated extraction of ejection fraction for quality measurement using regular expressions in Unstructured Information Management Architecture (UIMA) for heart failure

Jennifer H Garvin et al. J Am Med Inform Assoc. 2012 Sep-Oct.

Abstract

Objectives: Left ventricular ejection fraction (EF) is a key component of heart failure quality measures used within the Department of Veteran Affairs (VA). Our goals were to build a natural language processing system to extract the EF from free-text echocardiogram reports to automate measurement reporting and to validate the accuracy of the system using a comparison reference standard developed through human review. This project was a Translational Use Case Project within the VA Consortium for Healthcare Informatics.

Materials and methods: We created a set of regular expressions and rules to capture the EF using a random sample of 765 echocardiograms from seven VA medical centers. The documents were randomly assigned to two sets: a set of 275 used for training and a second set of 490 used for testing and validation. To establish the reference standard, two independent reviewers annotated all documents in both sets; a third reviewer adjudicated disagreements.

Results: System test results for document-level classification of EF of <40% had a sensitivity (recall) of 98.41%, a specificity of 100%, a positive predictive value (precision) of 100%, and an F measure of 99.2%. System test results at the concept level had a sensitivity of 88.9% (95% CI 87.7% to 90.0%), a positive predictive value of 95% (95% CI 94.2% to 95.9%), and an F measure of 91.9% (95% CI 91.2% to 92.7%).

Discussion: An EF value of <40% can be accurately identified in VA echocardiogram reports.

Conclusions: An automated information extraction system can be used to accurately extract EF for quality measurement.

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Conflict of interest statement

Competing interests: None.

Figures

Figure 1
Figure 1
Degree of structure: unstructured (synthetic document).
Figure 2
Figure 2
Degree of structure: semi-structured (synthetic document).
Figure 3
Figure 3
Degree of structure: structured (synthetic document).
Figure 4
Figure 4
Development of annotation guideline and schema for establishment of a reference standard. IAA, inter-annotator agreement.
Figure 5
Figure 5
EF system components and use. EF, ejection fraction.
Figure 6
Figure 6
Rules and sequence of use. EF, ejection fraction.
See this image and copyright information in PMC

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