Automated extraction of ejection fraction for quality measurement using regular expressions in Unstructured Information Management Architecture (UIMA) for heart failure.
| Autor: | Garvin JH; IDEAS Center, SLC VA Healthcare System, Salt Lake City, Utah 84148, USA. jennifer.garvin@va.gov, DuVall SL, South BR, Bray BE, Bolton D, Heavirland J, Pickard S, Heidenreich P, Shen S, Weir C, Samore M, Goldstein MK |
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| Jazyk: | angličtina |
| Zdroj: | Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2012 Sep-Oct; Vol. 19 (5), pp. 859-66. Date of Electronic Publication: 2012 Mar 21. |
| DOI: | 10.1136/amiajnl-2011-000535 |
| Abstrakt: | 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. |
| Databáze: | MEDLINE |
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