This article is part of the Topical Collection on Systems-Level Quality Improvement
Left ventricular ejection fraction (LVEF) is an important prognostic indicator of cardiovascular outcomes. It is used clinically to determine the indication for several therapeutic interventions. LVEF is most commonly derived using in-line tools and some manual assessment by cardiologists from standardized echocardiographic views. LVEF is typically documented in free-text reports, and variation in LVEF documentation pose a challenge for the extraction and utilization of LVEF in computer-based clinical workflows. To address this problem, we developed a computerized algorithm to extract LVEF from echocardiography reports for the identification of patients having heart failure with reduced ejection fraction (HFrEF) for therapeutic intervention at a large healthcare system. We processed echocardiogram reports for 57,158 patients with coded diagnosis of Heart Failure that visited the healthcare system over a two-year period. Our algorithm identified a total of 3910 patients with reduced ejection fraction. Of the 46,634 echocardiography reports processed, 97% included a mention of LVEF. Of these reports, 85% contained numerical ejection fraction values, 9% contained ranges, and the remaining 6% contained qualitative descriptions. Overall, 18% of extracted numerical LVEFs were ≤ 40%. Furthermore, manual validation for a sample of 339 reports yielded an accuracy of 1.0. Our study demonstrates that a regular expression-based approach can accurately extract LVEF from echocardiograms, and is useful for delineating heart-failure patients with reduced ejection fraction.
Fogel, M. A., Use of ejection fraction (or lack thereof), morbidity/mortality and heart failure drug trials: a review. International Journal of Cardiology 84:119–132, 2002. https://doi.org/10.1016/s0167-5273(02)00134-1. CrossRefPubMed
Sweitzer, N. K., Lopatin, M., Yancy, C. W., Mills, R. M., and Stevenson, L. W., Comparison of Clinical Features and Outcomes of Patients Hospitalized With Heart Failure and Normal Ejection Fraction (≥55%) Versus Those With Mildly Reduced (40% to 55%) and Moderately to Severely Reduced (<40%) Fractions. Am J Cardiol 101:1151–1156, 2008. https://doi.org/10.1016/j.amjcard.2007.12.014. CrossRefPubMedPubMedCentral
Yancy, C. W. et al., 2017 ACC/AHA/HFSA Focused Update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Failure Society of America. Circulation 136, 2017. https://doi.org/10.1161/cir.0000000000000509.
Foley, T. A. et al., Measuring left ventricular ejection fraction-techniques and potential pitfalls. European Cardiology 8:108–114, 2012. CrossRef
Gaasch, W. H., Delorey, D. E., Kueffer, F. J., and Zile, M. R., Distribution of Left Ventricular Ejection Fraction in Patients With Ischemic and Hypertensive Heart Disease and Chronic Heart Failure. Am J Cardiol 104:1413–1415, 2009. https://doi.org/10.1016/j.amjcard.2009.06.064. CrossRefPubMed
Dunlay, S. M., Roger, V. L., Weston, S. A., Jiang, R., and Redfield, M. M., Longitudinal Changes in Ejection Fraction in Heart Failure Patients With Preserved and Reduced Ejection Fraction. Circulation: Heart Failure 5:720–726, 2012. https://doi.org/10.1161/circheartfailure.111.966366. CrossRef
Huang, H. et al., Accuracy of left ventricular ejection fraction by contemporary multiple gated acquisition scanning in patients with cancer: comparison with cardiovascular magnetic resonance. Journal of Cardiovascular Magnetic Resonance 19:34, 2017. https://doi.org/10.1186/s12968-017-0348-4. CrossRefPubMedPubMedCentral
Chung, J., and Murphy, S., Concept-value pair extraction from semi-structured clinical narrative: a case study using echocardiogram reports. American Medical Informatics Association 2005:131–135, 2005.
Garvin, J. H. et al., Automated extraction of ejection fraction for quality measurement using regular expressions in Unstructured Information Management Architecture (UIMA) for heart failure. Journal of the American Medical Informatics Association 19:859–866, 2012. https://doi.org/10.1136/amiajnl-2011-000535. CrossRefPubMedPubMedCentral
Mystre S (2012) Comparing Methods for left Ventricular Ejection Fraction Clinical Information Extraction. TBI_CRI
Kim Y, Garvin J, Heavirland J, Meystre SM (2013) Improving heart failure information extraction by domain adaptation. Stud Health Technol Inform 192:185–189
Gobbel, G. T., Garvin, J., Reeves, R., Cronin, R. M., Heavirland, J., Williams, J., Weaver, A., Jayaramaraja, S., Giuse, D., Speroff, T., Brown, S. H., Xu, H., and Matheny, M. E., Assisted annotation of medical free text using RapTAT. J Am Med Inform Assoc 21(5):833–841, 2014. https://doi.org/10.1136/amiajnl-2013-002255. CrossRefPubMedPubMedCentral
Kim, Y. et al., Extraction of left ventricular ejection fraction information from various types of clinical reports. Journal of biomedical informatics 67:42–48, 2017. https://doi.org/10.1016/j.jbi.2017.01.017. CrossRefPubMedPubMedCentral
Meystre, S. M. et al., Congestive heart failure information extraction framework for automated treatment performance measures assessment. Journal of the American Medical Informatics Association 24, 2017. https://doi.org/10.1093/jamia/ocw097.
Nath, C., Albaghdadi, M. S., and Jonnalagadda, S. R., A Natural Language Processing Tool for Large-Scale Data Extraction from Echocardiography Reports. PLOS ONE 11, 2016. https://doi.org/10.1371/journal.pone.0153749. CrossRef
Anderson, A. E. et al., Electronic health record phenotyping improves detection and screening of type 2 diabetes in the general United States population: A cross-sectional, unselected, retrospective study. Journal of biomedical informatics 60:162–168, 2016. https://doi.org/10.1016/j.jbi.2015.12.006. CrossRefPubMed
Liao, K. P. et al., Methods to Develop an Electronic Medical Record Phenotype Algorithm to Compare the Risk of Coronary Artery Disease across 3 Chronic Disease Cohorts. PLOS ONE 10, 2015. https://doi.org/10.1371/journal.pone.0136651. CrossRef
Lin, J., and Dyer, C., Data-Intensive Text Processing with MapReduce. Synthesis Lectures on Human Language Technologies 3:1–177. https://doi.org/10.2200/s00274ed1v01y201006hlt007. CrossRef
Garvin, J. H. et al., Automated extraction of ejection fraction for quality measurement using regular expressions in Unstructured Information Management Architecture (UIMA) for heart failure. Journal of the American Medical Informatics Association: JAMIA 19:859–866, 2012. https://doi.org/10.1136/amiajnl-2011-000535. CrossRefPubMed
- Extraction of Ejection Fraction from Echocardiography Notes for Constructing a Cohort of Patients having Heart Failure with reduced Ejection Fraction (HFrEF)
Kavishwar B. Wagholikar
Christina M. Fischer
Christopher D. Herrick
Calum A. MacRae
Benjamin M. Scirica
Akshay S. Desai
Shawn N. Murphy
- Springer US