Open AccessValidation of a Novel Digital Tool in Automatic Scoring of an Online ECG Examination at an International Cardiology Meeting
Author(s) -
Quinn Kieran L.,
Crystal Eugene,
Lashevsky Ilan,
Arouny Banafsheh,
Baranchuk Adrian
Publication year - 2016
Publication title -
annals of noninvasive electrocardiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.494
H-Index - 48
eISSN - 1542-474X
pISSN - 1082-720X
DOI - 10.1111/anec.12311
Subject(s) - medicine , set (abstract data type) , medical diagnosis , medical physics , electrocardiography , morning , computer science , pathology , programming language
Background We have previously developed a novel digital tool capable of automatically recognizing correct electrocardiography (ECG) diagnoses in an online exam and demonstrated a significant improvement in diagnostic accuracy when utilizing an inductive‐deductive reasoning strategy over a pattern recognition strategy. In this study, we sought to validate these findings from participants at the International Winter Arrhythmia School meeting, one of the foremost electrophysiology events in Canada. Methods Preregistration to the event was sent by e‐mail. The exam was administered on day 1 of the conference. Results and analysis were presented the following morning to participants. Results Twenty‐five attendees completed the exam, providing a total of 500 responses to be marked. The online tool accurately identified 195 of a total of 395 (49%) correct responses (49%). In total, 305 responses required secondary manual review, of which 200 were added to the correct responses pool. The overall accuracy of correct ECG diagnosis for all participants was 69% and 84% when using pattern recognition or inductive‐deductive strategies, respectively. Conclusion Utilization of a novel digital tool to evaluate ECG competency can be set up as a workshop at international meetings or educational events. Results can be presented during the sessions to ensure immediate feedback.