Since its inception, the electrocardiogram (ECG) has been an essential tool in medicine. The ECG is more than a mere tracing of cardiac electrical activity; it can detect and diagnose various pathologies including arrhythmias, pericardial and myocardial disease, electrolyte disturbances, and pulmonary disease. The ECG is a simple, non-invasive, rapid, and cost-effective diagnostic tool in medicine; however, its clinical utility relies on the accuracy of its interpretation. Computer ECG analysis has become so widespread and relied upon that ECG literacy among clinicians is waning. With recent technological advances, the application of artificial intelligence-augmented ECG (AI-ECG) algorithms has demonstrated the potential to risk stratify, diagnose, and even interpret ECGs—all of which can have a tremendous impact on patient care and clinical workflow. In this review, we examine (i) the utility and importance of the ECG in clinical practice, (ii) the accuracy and limitations of current ECG interpretation methods, (iii) existing challenges in ECG education, and (iv) the potential use of AI-ECG algorithms for comprehensive ECG interpretation.

To aid in solving the problem of declining ECG competency, clearly defined skill competencies for all healthcare professionals are needed. Once competency expectations are set, centralised educational resources may be used to achieve these benchmarks. The medical education community has been the driver to spearhead such societal initiatives and will need to be integral in the rejuvenation of proper ECG interpretation. In this context, medical educators ought to inspire the next generation as well as current providers to revisit and reinvigorate the complexities and beauty of ECG interpretation.