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ECG Interpretation Proficiency of Healthcare Professionals

Introduction: ECG interpretation is essential in modern medicine, yet achieving and maintaining competency can be challenging for healthcare professionals. Quantifying proficiency gaps can inform educational interventions for addressing these challenges.

Methods: Medical professionals from diverse disciplines and training levels interpreted 30 12-lead ECGs with common urgent and non-urgent findings. Average accuracy (percentage of correctly identified findings), interpretation time per ECG, and self-reported confidence (rated on a scale of 0 [not confident], 1 [somewhat confident], or 2 [confident]) were evaluated.

Results: Among the 1206 participants, there were 72 (6%) primary care physicians (PCPs), 146 (12%) cardiology fellows-in-training (FITs), 353 (29%) resident physicians, 182 (15%) medical students, 84 (7%) advanced practice providers (APPs), 120 (10%) nurses, and 249 (21%) allied health professionals (AHPs). Overall, participants achieved an average overall accuracy of 56.4 ± 17.2%, interpretation time of 142 ± 67 seconds, and confidence of 0.83 ± 0.53. Cardiology FITs demonstrated superior performance across all metrics. PCPs had a higher accuracy compared to nurses and APPs (58.1% vs. 46.8% and 50.6%; P<0.01), but a lower accuracy than resident physicians (58.1% vs. 59.7%; P<0.01). AHPs outperformed nurses and APPs in every metric and showed comparable performance to resident physicians and PCPs.

Conclusions: Our findings highlight significant gaps in the ECG interpretation proficiency among healthcare professionals.

Reference: Kashou AH, Noseworthy PA, Beckman TJ, Anavekar NS, Cullen MW, Angstman KB, Sandefur BJ, Shapiro BP, Wiley BW, Kates AM, Huneycutt D, Braisted A, Smith SW, Baranchuk A, Grauer K, O'Brien K, Kaul V, Gambhir HS, Knohl SJ, Albert D, Kligfield PD, Macfarlane PW, Drew BJ, May AM. ECG Interpretation Proficiency of Healthcare Professionals. Curr Probl Cardiol. 2023 Jun 30:101924. doi: 10.1016/j.cpcardiol.2023.101924. Epub ahead of print. PMID: 37394202.

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