Quantifying the medical student learning curve for ECG rhythm strip interpretation using deliberate practice

Objectives: Obtaining competency in medical skills such as interpretation of electrocardiograms (ECGs) requires repeated practice and feedback. Structured repeated practice and feedback for ECGs is likely not provided to most medical students, so skill development is dependent on opportunistic training during clinical rotations. Our aim was to describe: 1. the amount of deliberate practice completed for learning ECG rhythm strip diagnoses in first year medical students, ; 2. the learning curve for rhythm strip diagnosis, and 3. student experiences with deliberate practice. Methods: First year medical students from two medical schools were provided with online rhythm strip practice cases. Diagnostic accuracy was measured throughout practice, and students were provided feedback for every case they completed. Total cases practiced and time spent practicing were correlated with their performance during practice and on an exam. Results: 314 of 384 (82%) students consented. The mean number of ECGs each student practiced was 59 (range 0-280), representing 18,466 total instances of deliberate practice. We generated mathematical models that accurately correlated both the number of cases practiced and time spent practicing, with diagnostic accuracy on an exam (p<0.001). For example, students would need to spend on average of 112 minutes and complete 34 practice cases to obtain 75% on an ECG rhythm strip exam. Student satisfaction was high using the online cases. Conclusions: We succeeded in delivering deliberate practice for ECG rhythm strip interpretation to a large cohort of students at 2 medical schools. We quantified a learning curve that estimates the number of cases and practice time required to achieve pre-determined levels of diagnostic accuracy. This data can help inform a competency-based approach to curriculum development.