Educational Software Applied in Teaching Electrocardiogram: A Systematic Review

Biomed Res Int. 2018 Mar 15:2018:8203875. doi: 10.1155/2018/8203875. eCollection 2018.

Abstract

Background: The electrocardiogram (ECG) is the most used diagnostic tool in medicine; in this sense, it is essential that medical undergraduates learn how to interpret it correctly while they are still on training. Naturally, they go through classic learning (e.g., lectures and speeches). However, they are not often efficiently trained in analyzing ECG results. In this regard, methodologies such as other educational support tools in medical practice, such as educational software, should be considered a valuable approach for medical training purposes.

Methods: We performed a literature review in six electronic databases, considering studies published before April 2017. The resulting set comprises 2,467 studies. From this collection, 12 studies have been selected, initially, whereby we carried out a snowballing process to identify other relevant studies through the reference lists of these studies, resulting in five relevant studies, making up a total of 17 articles that passed all stages and criteria.

Results: The results show that 52.9% of software types were tutorial and 58.8% were designed to be run locally on a computer. The subjects were discussed together with a greater focus on the teaching of electrophysiology and/or cardiac physiology, identifying patterns of ECG and/or arrhythmias.

Conclusions: We found positive results with the introduction of educational software for ECG teaching. However, there is a clear need for using higher quality research methodologies and the inclusion of appropriate controls, in order to obtain more precise conclusions about how beneficial the inclusion of such tools can be for the practices of ECG interpretation.

Publication types

  • Review
  • Systematic Review

MeSH terms

  • Arrhythmias, Cardiac / diagnostic imaging
  • Arrhythmias, Cardiac / physiopathology*
  • Clinical Competence
  • Education*
  • Electrocardiography*
  • Humans
  • Learning
  • Software*