Despite the critical role diagnostic ECG plays in patient management across specialties, there are persistent shortcomings in ECG training that have been described and discussed at length in the medical literature for decades.
The inconsistency in training starts in medical school, which may leave graduates ill-prepared for ECG interpretation as they progress through their training, ultimately resulting in suboptimal accuracy—even when experienced physicians are reading ECGs.
The pervasive issue of missed diagnoses
One study highlights the issue, showing generally low competency around ECG interpretation among both healthcare staff and students at a medical sciences university.1 The average score on an assessment of competency was approximately 5 out of 10, with physicians performing somewhat better. Most participants, however, were unable to identify common findings like normal sinus rhythm (77.3%), acute MI (63.8%), and pathological Q-waves (62.2%).
Another study explored internal medicine residents' comfort with ECG interpretation.2 Nearly three-quarters of those surveyed said they lacked confidence when interpreting ECGs, and 30% reported they often leaned on automated ECG interpretation when making a diagnosis. Comfort level appeared to be greater after a few years of residency.
Indeed, experience seems to mitigate the problem, although not completely. A recent meta-analysis showed that the median accuracy for ECG interpretation across training levels was just 54% on pretraining assessments and 67% on post-training assessments.3 Performance on pretraining assessments was lowest among medical students (42.0%) but increased to 55.8% for residents, 68.5% for practicing physicians as a whole, and 74.9% for cardiologists.
"Improvement in both training in and assessment of ECG interpretation appears warranted, across the practice continuum," the investigators of the meta-analysis concluded. "Standardized competencies, educational resources, and mastery benchmarks could address all these concerns."3
Causes and consequences of inadequate ECG training
Researchers proposed several explanations for the deficit, noting first the difficulty inherent in teaching and learning how to interpret ECGs.4 In addition, although exposure during clinical encounters is a key way of acquiring the skill of ECG interpretation, the authors observe that "experiential learning alone does not guarantee ECG competence unless it is supplemented by structured teaching." Finally, they acknowledge that "medical knowledge is ever-expanding, and there is limited time allocated to the teaching of electrocardiography in medical curricula."
Indeed, in the Journal of Electrocardiology, experts note that programs have to bring trainees up to speed on a variety of diagnostic technologies, including CT, MRI, and ultrasound, which limits the amount of time that can be dedicated to ECG interpretation.5
Giving short shrift to ECG during training will invariably affect interpretation skills further down the line, indicates Anthony Kashou, MD, a global expert known as "The EKG Guy." He notes that "ECG interpretation is a challenging cognitive skill set that demands a considerable amount of time and effort to develop."
Insufficient training, then, can have real and potentially life-threatening consequences. Even before getting to the point of interpretation, lead misplacement—which clearly affects the quality of the results and, in turn, clinical decision-making—has proven to be a common issue. Moreover, researchers writing in the GMS Journal for Medical Education point out that mistakes in ECG interpretation can spur inappropriate downstream testing and delay diagnosis and treatment.6
Possible training methods
As with any skill, attaining proficiency in ECG interpretation requires deliberate practice. However, according to researchers, "structured repeated practice and feedback for ECGs is likely not provided to most medical students."6
They explored the learning curve for ECG rhythm strip interpretation among medical students who underwent a more structured program of deliberate practice involving online instruction. Feedback was provided for each case. The investigators determined that students must complete an average of 112 minutes of training and 34 practice cases to achieve a 75% grade on an ECG rhythm strip exam. The approach was associated with high student satisfaction.
The authors acknowledge, however, that interpretation of 12-lead ECG is more complex and might require more practice time. That thought is reflected in guidance from various professional groups. In a 2001 clinical competency statement published in Circulation, for instance, the American College of Cardiology and the American Heart Association (ACC/AHA) recommended a minimum of 500 supervised interpretations to learn how to interpret 12-lead ECGs, as well as 100 interpretations each year to maintain proficiency.7
In 2015, a Core Cardiovascular Training Statement (COCATS) task force published a different recommendation, saying that interpreting roughly 3,000 to 3,500 ECGs over a three-year period "should provide ample experience to acquire such competencies" for trainees.8
That volume of ECGs would require considerable feedback, presenting a logistical challenge to getting medical students and trainees up to speed on ECG interpretation. Computer assistance may help. In the GMS Journal for Medical Education study, feedback was automated and provided by computer algorithms, which took much of the burden off the instructors. That approach also enhanced the consistency and quality of feedback over time as the program uncovered trainees' common errors.
The research shows that computer-assisted training in ECG interpretation was no better for attaining ECG competence than face-to-face instruction.4 However, when computer-assisted approaches were used in a "blended learning context," they came out on top, "especially if trainees had unlimited access to teaching materials and/or deliberate practice with feedback."
Kashou has studied the impact of computerized ECG interpretation in a series of recent studies, concluding that this approach can certainly aid clinicians in making sense of an ECG reading. "Computerized ECG tools present an opportunity to bolster traditional training methods," Kashou said. "They provide immediate feedback, enabling trainees to cross-check their interpretations, hone their skills, and gain confidence in real time."
More recently, the emergence of artificial intelligence (AI) algorithms has opened even more opportunities for training in ECG interpretation.
Establishing competency standards
Various groups have proposed that competency standards for ECG training should be applied in medical school and in subsequent years of instruction. However, there is no single accepted set of such standards available, and Kashou and his colleagues make a plea for universal ECG competency standards.9 They write, "ECG competency standards should apply to all healthcare providers and correspond to each medical professional's level of training and the importance of ECG literacy to their clinical practice."
Kashou et al. provide an example of how competency standards might look for clinicians interpreting ECGs, across all levels of experience. Beginners (all medical professionals), they propose, should be required to master the basics of ECG equipment and lead placement and be able to identify common patterns like heart block, sinus rhythm, atrial fibrillation, and STEMI, among other competencies.
Intermediate interpreters include clinicians working where ECG interpretation may influence how patients are managed, such as physicians, nurses, and advanced practice practitioners. In addition to mastering beginner competencies, these individuals should become adept at these tasks:
- Distinguishing and describing bundle branch and fascicular blocks
- Identifying less common rhythms
- Identifying common clinical disorders like pericarditis and left ventricular hypertrophy
- Performing 12-lead ECG interpretation independently
The most advanced interpreters will be clinicians who provide specialized cardiac or intensive care. They should be able to perform tasks such as identifying ECG patterns consistent with various myocardial diseases and with inherited disorders that carry a risk of sudden death.
The creation and acceptance of universal ECG interpretation competencies will help close training gaps and eventually improve quality of care. "Once competency expectations are in place, effective, efficient, and widely accessible educational resources could be used to help achieve these benchmarks," Kashou et al. say. "By aligning ECG education initiatives with consensus-based competency standards, we would be able to promote an enriched educational culture capable of delivering better patient care."
Resources:
1. Amini K, Mirzaei A, Hosseini M, et al. Assessment of electrocardiogram interpretation competency among healthcare professionals and students of Ardabil University of Medical Sciences: a multidisciplinary study. BMC Medical Education. June 2022;22(1):448. https://bmcmededuc.biomedcentral.com/articles/10.1186/s12909-022-03518-0
2. Al-Akchar M, Ibrahim AM, Salih M, et al. Learning electrocardiogram interpretation – insights from residents and a proposed solution in an observational study. Journal of Community Medicine and Public Health Reports. October 2021;2(11). https://www.acquaintpublications.com/article/learning_electrocardiogram_interpretation_insights_from_residents_and_a_proposed_solution_in_an_observational_study
3. Cook DA, Oh SY, Pusic MV. Accuracy of physicians' electrocardiogram interpretations: a systematic review and meta-analysis. JAMA Internal Medicine. September 2020;180(11):1461-1471. https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2771093
4. Viljoen CA, Millar RS, Engel ME, et al. Is computer-assisted instruction more effective than other educational methods in achieving ECG competence amongst medical students and residents? A systematic review and meta-analysis. BMJ Open. November 2019;9(11):e028800. https://bmjopen.bmj.com/content/9/11/e028800
5. Breen CJ, Kelly GP, Kernohan WG. ECG interpretation skill acquisition: A review of learning, teaching and assessment. Journal of Electrocardiology. July-August 2022;73:125-128. https://www.sciencedirect.com/science/article/pii/S0022073618306411
6. Waechter J, Reading D, Lee CH, Walker M. Quantifying the medical student learning curve for ECG rhythm strip interpretation using deliberate practice. GMS Journal for Medical Education. August 2019;36(4):Doc40. https://www.egms.de/static/en/journals/zma/2019-36/zma001248.shtml
7. Kadish AH, Buxton AE, Kennedy HL, et al. ACC/AHA clinical competence statement on electrocardiography and ambulatory electrocardiography. A report of the ACC/AHA/ACP-ASIM Task Force on Clinical Competence (ACC/AHA Committee to Develop a Clinical Competence Statement on Electrocardiography and Ambulatory Electrocardiography). Circulation. December 2001;104(25):3169-3178. https://www.ahajournals.org/doi/10.1161/circ.104.25.3169
8. Balady GJ, Bufalino VJ, Gulati M, et al. COCATS 4 Task Force 3: training in electrocardiography, ambulatory electrocardiography, and exercise testing. Journal of the American College of Cardiology. May 2015;65(17):1763-1777. https://www.jacc.org/doi/full/10.1016/j.jacc.2015.03.021
9. Kashou A, May A, DeSimone C, Noseworthy P. The essential skill of ECG interpretation: How do we define and improve competency? Postgraduate Medical Journal. March 2020;96(1133):125-127. https://academic.oup.com/pmj/article/96/1133/125/6842813
