A regular expression-based natural language processing algorithm accurately extracted left ventricular ejection fraction from echocardiogram reports with an accuracy of 1.0.
Observational (n=24,605)
No
A regular expression-based algorithm can accurately extract LVEF from free-text echocardiography reports to identify patients with HFrEF.
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.
Wagholikar et al. (Tue,) conducted a observational in Heart Failure (n=24,605). Regular expression-based NLP algorithm vs. Manual annotation was evaluated on Accuracy of LVEF extraction. A regular expression-based natural language processing algorithm accurately extracted left ventricular ejection fraction from echocardiogram reports with an accuracy of 1.0.