The evaluation of an open source online training system for teaching 12 lead electrocardiographic interpretation.

J Electrocardiol

Department of Biomedical Informatics, Emory University & Georgia Institute of Technology; Department of Biomedical Engineering, Emory University & Georgia Institute of Technology.

Published: November 2017

Introduction: The aim of this study is to present and evaluate the integration of a low resource JavaScript based ECG training interface (CrowdLabel) and a standardised curriculum for self-guided tuition in ECG interpretation.

Methods: Participants practiced interpreting ECGs weekly using the CrowdLabel interface to assist with the learning of the traditional didactic taught course material during a 6 week training period. To determine competency students were tested during week 7.

Results: A total of 245 unique ECG cases were submitted by each student. Accuracy scores during the training period ranged from 0-59.5% (median = 33.3%). Conversely accuracy scores during the test ranged from 30 - 70% (median = 37.5%) (p < 0.05). There was no correlation between students who interpreted high numbers of ECGs during the training period and their marks obtained.

Conclusions: CrowdLabel is shown to be a readily accessible dedicated learning platform to support ECG interpretation competency.

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http://dx.doi.org/10.1016/j.jelectrocard.2016.02.003DOI Listing

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