DOI: https://doi.org/10.21203/rs.3.rs-68479/v1
Although electrocardiography is considered a core learning outcome for medical students, there is currently little curricular guidance for undergraduate ECG training. Owing to the absence of expert consensus on undergraduate ECG teaching, curricular content is subject to individual opinion. The aim of this modified Delphi study was to establish consensus amongst content and context experts on an ECG curriculum for medical students.
The Delphi technique, an established method of obtaining consensus, was used to develop an undergraduate ECG curriculum. Specialists involved in ECG teaching were invited to complete three rounds of online surveys. An undergraduate ECG curriculum was formulated from the topics of ECG instruction for which consensus (i.e. ≥75% agreement) was achieved amongst the expert panel.
The panellists (n = 131) had a wide range of expertise (42.8% Internal Medicine, 22.9% Cardiology, 16% Family Medicine, 13.7% Emergency Medicine and 4.6% Health Professions Education). Topics that reached consensus to be included in the undergraduate ECG curriculum were classified under technical aspects of performing ECGs, basic ECG analysis, recognition of the normal ECG and abnormal rhythms and waveforms and using electrocardiography as part of a clinical diagnosis. This study emphasises that ECG teaching should be framed within the clinical context. Course conveners should not overload students with complex and voluminous content, but rather focus on commonly encountered and life-threatening conditions, where accurate diagnosis impacts on patient outcome. A list of 23 “must know” ECG diagnoses is therefore proposed.
A multidisciplinary expert panel reached consensus on the ECG training priorities for medical students.
The first step in the development of an outcomes-based undergraduate medical curriculum is the performance of a needs assessment to ascertain what junior doctors are expected to know.1, 2 The results of such a needs assessment serve to inform those involved with curricular design of the core knowledge and skills medical students need to acquire during their undergraduate training.1 In the absence of expert consensus, however, curricular content is subject to the opinion of individual lecturers and, therefore, variable between academic institutions.3
Worldwide, graduating medical trainees lack adequate ECG competence,4–7 i.e. the ability to accurately analyse and interpret an electrocardiogram (ECG).8 Yet, ECG competency is considered an Entrustable Professional Activity (EPA) that medical students need to master prior to graduation.9 It is important to consolidate ECG knowledge and skills before qualifying, as there is usually little formal training in electrocardiography once medical students graduate.10
Even though electrocardiography forms part of core undergraduate medical training,11 there is a lack of guidance as to which ECG diagnoses should be taught to medical students5 In a recent systematic review, it was found that there was significant variation in topics of undergraduate ECG instruction.12 This could be explained by the inconsistency in undergraduate ECG curricular recommendations in the literature.9, 13 Central to the process of addressing the lack of ECG competence is the establishment of a mutually agreed curriculum.
Delphi studies are a recognised method for establishing expert consensus in curricular development.14 The Delphi technique is an iterative process through which expert opinion is transformed into consensus amongst experts.15 Experts in the field are invited to complete multiple rounds of questionnaires. These questionnaires are completed anonymously, and the collective results are shared with participants in subsequent rounds.16, 17
The classical Delphi method starts with a set of open-ended questions (to collect qualitative data) in the first round. Participants’ responses are then summarised and used to create closed-ended questions (to collect quantitative data) for the subsequent rounds.18, 19 However, multiple studies in health professions education have adopted a modified Delphi technique wherein the first round already starts with closed-ended questions that are carefully selected by the convener through literature reviews and expert consultation.20–22 As the methodology is flexible, a modified Delphi study can still collect input through open-ended questions, by asking participants if they have any additions to the list prepared by the convener.14, 23
In a Delphi study, quantitative data is collected by means of directed questions, in the form of Likert-type questions, through which participants indicate how strongly they agree or disagree with each statement on the list in the survey of each round.16, 24 Likert-type questions typically ask, “please select how strongly you agree with the following statement…”. Most studies use five response categories (i.e. “strongly disagree”, “disagree”, “uncertain”, “agree”, “strongly agree”), with a central point (i.e. uncertain) to allow for participants to opt out if they are not sure about the statement.3, 15, 22, 25, 26 Frequencies and mode are appropriate descriptive statistics for the categorical data collected by Likert-type questions.22, 24, 27 Frequencies indicate variability of the data, i.e. the level of agreement for each statement in the survey,28 whereas the mode indicates the central tendency of the data (i.e. the response most commonly selected).
The level of agreement amongst participants that is considered as consensus varies between 51 and 80% in the literature on Delphi studies.14 Investigators decide a priori on the level of agreement that would be considered as having reached consensus.29 Although there is no universal value that is used for this purpose, many studies use 75% agreement between experts as the cut off value to establish consensus in Delphi studie.29 Surveys are administered through multiple rounds until the predetermined level of consensus for each statement is reached. This usually occurs after the third round of the study.14, 16
There are no rigid criteria for the selection of participants in a Delphi study, neither how many participants should be recruited.30 The investigator needs to take great care in the selection of potential participants.31 Participants that are invited to take part in a Delphi study should be content and context experts, so that the results can be accurate and reliable.32, 33 The panel of experts invited to take part should have a keen interest in the subject matter.26 Also, because of the risk of losing participants between successive rounds, those invited to take part in the study should be willing to take part in a multi-stage surveying process.15
The aim of this study was to establish consensus (amongst specialists who regularly analyse and interpret ECGs in clinical practice [i.e. content experts], and who are involved in ECG training [i.e. context experts]), on an outcomes-based undergraduate electrocardiography curriculum for medical students.
This study used a modified Delphi technique to establish consensus on a curriculum for undergraduate ECG training.
Cardiologists, Specialist Physicians, Emergency Physicians, Family Physicians and Medical Education Specialists at the eight medical schools of South Africa were invited to take part in this modified Delphi study. The purpose of the study was explained in the letter of invitation. On acceptance to take part, an email with a link to the online survey was sent to the participant. Consent for participation in the study was obtained electronically prior to accessing the online survey in the first round. Invitees were also asked to nominate other colleagues who were responsible for ECG teaching of undergraduate medical students and/or work closely with junior doctors at the academic institutions or hospitals that are considered intern training sites.
Participants were only included as part of the modified Delphi expert panel if they fulfilled all of the following criteria:
In South Africa, medical graduates do a two-year internship at an accredited hospital where they practice under supervision. In the third year after graduation, they work independently as community service medical officers in the public sector, often at sites where there is limited supervision. Once they have completed this year of community service, they are registered as independent practitioners and are eligible to work in the public or private sector and may then enrol for specialist training.
The investigators carefully selected the ECG diagnoses included on the pre-selected list in the first round, by considering the content of undergraduate ECG lectures, suggested and prescribed textbooks for ECG learning,34, 35 as well as a thorough literature search of topics of undergraduate ECG teaching,4, 6, 7, 9, 13, 36-46 as well as postgraduate ECG training.47-51
The study comprised three rounds of online surveys that were completed by the participants in the study (Figure 1). The surveys were administered through REDCap (Research Electronic Data Capture), which is a secure (password protected) online database manager hosted at the University of Cape Town (UCT).52 Participants had access to the online surveys through an emailed link specific to the survey of each round and unique to the participant. If, after three weeks, no responses were received, reminder emails were sent to all participants who had not yet completed the online survey by that time.
In June 2017, a link to the online survey of the first round was sent to all consenting participants. The survey consisted of directed questions and open-ended questions:
The expert panel continued to nominate other colleagues to also participate in this modified Delphi study throughout the course of the first round. The last of these invitations were sent in May 2018 and the last response to the survey of the first round was received in June 2018.
In June 2018, after three weeks of not receiving any new responses from participants, the first round was closed. The investigators subsequently analysed the data collected. The following criteria was used to determine consensus for each ECG diagnosis in the survey:
The survey in the second round was prepared and consisted of all the items that had not reached consensus (either included or excluded from the curriculum), as well as the additional items suggested by the expert panel (Supplementary Table 3).
In July 2018, a link to the second round’s online survey was sent to all those who participated in the first round of the modified Delphi study. Participants were given collective feedback from the first round. Frequencies of participant responses to each Likert-type question were presented to the participants (Supplementary Table 4), before they completed the Likert-type questions of the second round. After completing all the directed questions (Supplementary Table 1), the expert panel was given the opportunity to comment on the feedback they had seen. The last response for the survey of the second round was received in December 2018.
Subsequently, the investigators analysed the data collected from the second round. The same inclusion and exclusion criteria that were used in the first round were applied to the responses to the closed-ended questions. The survey in the third round was prepared and consisted of all the items that did not reach consensus in the second round.
In May 2019, a link to the online survey of the third round of the modified Delphi study was sent to all those who participated in the first round. Participants were given collective feedback from the second round. Frequencies of participant responses for each Likert-type question were presented to the participants (Supplementary Table 4) before they completed the Likert-type questions of the third round (Supplementary Table 1). The last response to the survey of the third round was received in October 2019.
The investigators subsequently analysed the data collected during the third round. From these results, and those of the prior rounds, an undergraduate curriculum could be formulated from the topics of ECG instruction for which consensus was established (i.e. ≥ 75% agreement) amongst the expert panel. Thereafter, a mode was calculated for each item in all the rounds, to indicate the majority of responses amongst the expert panel. A final list of ECG diagnoses was compiled, only including those ECG diagnoses that had a mode of 5 (i.e. most participants voted “strongly agree”) and diagnoses that can only be made by means of an ECG recording.
Qualitative content analysis
Qualitative content analysis was performed by two investigators (CAV, VCB). An inductive approach was used to identify themes and subthemes from the free-text comments made by expert panellists at the end of the second and third rounds of the modified Delphi study.53, 54 Themes and subthemes were refined through an iterative process of reviewing the panellists’ responses.55 Disagreement was resolved through discussions with a third investigator (RSM). A deductive approach was used to quantify the frequency in which the themes and subthemes emerged from the feedback by the expert panel.56
This modified Delphi consisted of a large expert panel (n = 131), with good retention in the second (80.9%) and third rounds (77.1%) respectively (Fig. 2). Of the 249 specialists invited to take part, five declined the invitation and 111 did not respond. Two participants consented to take part, but never completed the surveys.
As shown in Table 1, the composition of the expert panel remained stable between the rounds with regards to speciality, years of experience, settings in which the panellists encountered ECGs in their own practice and where they taught ECGs. The panellists had a wide range of expertise (42.8% Internal Medicine, 22.9% Cardiology, 16% Family Medicine, 13.7% Emergency Medicine and 4.6% Health Professions Education). A third of the expert panel had more than 15 years’ experience as academic physicians. Most of the panellists consulted in the emergency department (70.2%) and in-patient wards (66.4%), and more than half (55.7%) interpreted an ECG at least once a day. About two thirds were affiliated to a University as a lecturer or senior lecturer. Whereas only 15.3% of the panel were responsible for large group teaching of ECGs (i.e. lectures), 91.6% were involved in workplace-based teaching (i.e. teaching ECGs on ward rounds, etc.).
First round | Second round | Third round | |
---|---|---|---|
n = 131 n (%) | n = 106 n (%) | n = 101 n (%) | |
Specialty | |||
Cardiology | 30 (22.9) | 20 (18.9) | 23 (22.8) |
Internal Medicine | 56 (42.8) | 47 (44.3) | 41 (40.6) |
Emergency Medicine | 18 (13.7) | 15 (14.2) | 16 (15.8) |
Family Medicine | 21 (16.0) | 18 (17.0) | 15 (14.9) |
Health Professions Education | 6 (4.6) | 6 (5.7) | 6 (5.9) |
Years of practice as an academic physician or years at an academic medical institution | |||
< 5 years | 47 (35.9) | 36 (34.0) | 35 (34.7) |
5–15 years | 45 (34.4) | 38 (35.9) | 34 (33.7) |
> 15 years | 39 (29.8) | 32 (30.2) | 32 (31.7) |
Settings in which expert panellists practice | |||
Cardiac intensive care unit | 35 (26.7) | 23 (21.7) | 26 (25.7) |
Cardiac Clinic | 38 (29.0) | 26 (24.5) | 30 (29.7) |
Out Patient Department other than Cardiac Clinic | 67 (51.2) | 52 (49.1) | 48 (47.5) |
Hospital wards | 87 (66.4) | 67 (63.2) | 64 (63.4) |
Emergency Unit | 92 (70.2) | 73 (68.9) | 70 (69.3) |
Frequency of ECG interpretation | |||
At least once a day | 73 (55.7) | 57 (53.8) | 57 (56.4) |
At least once a week | 43 (32.8) | 37 (34.9) | 33 (32.7) |
Less than once a week | 15 (11.5) | 12 (11.3) | 11 (10.9) |
Academic rank | |||
Professor | 10 (7.6) | 8 (7.6) | 8 (7.9) |
Associate professor | 14 (10.7) | 12 (11.3) | 11 (10.9) |
Lecturer / senior lecturer | 82 (62.6) | 67 (63.2) | 60 (59.4) |
Setting in which panellists teach ECGs | |||
Large group teaching (lectures) | 20 (15.3) | 15 (14.2) | 15 (14.9) |
Small group teaching (tutorials) | 60 (45.8) | 45 (42.5) | 44 (43.6) |
Workplace-based teaching (wards) | 120 (91.6) | 96 (90.6) | 91 (90.1) |
Working with | |||
Recent graduates * | 105 (80.2) | 85 (80.2) | 82 (81.2) |
Independent practitioners † | 114 (87.0) | 91 (85.9) | 91 (90.1) |
* recent graduates are junior doctors who graduated less than 3 years ago, who practice under supervision | |||
† independent practitioners with more than 3 years of experience, but who are not specialists |
Of the 53 items on the pre-selected list that was used in in the first round, 46 items (87.0%) reached consensus to be included in an undergraduate curriculum amongst the panellists, during three rounds of the modified Delphi study (Supplementary Table 2). At the end of the first round, the expert panel suggested an additional 76 items to be included in subsequent rounds of the modified Delphi study, of which 34 (44.7%) reached consensus to be included in the curriculum by the end of the final round (Supplementary Table 3). None of the topics reached consensus to be excluded. The outcomes of the first, second and third rounds are presented in Supplementary Tables 5, 6 and 7 respectively, indicating overall agreement amongst the expert panellists, as well as amongst the different specialties separately.
As shown in Table 2, there was consensus amongst the panellists that a new graduate should know the indications for performing an ECG (i.e. chest pain, dyspnoea, palpitations, syncope, depressed level of consciousness), and that they should be au fait with the technical aspects of performing and reporting a 12-lead ECG.
Topics for which consensus was reached | Round in which consensus was reached | Agreement amongst panellists (%) | Mode | Topics for which consensus was not reached | Agreement amongst panellists (%) | Mode |
---|---|---|---|---|---|---|
Clinical indications for performing an ECG | ||||||
Know when the ECG is indicated | Second | 97.1 | 5 | |||
ECG for chest pain | Second | 99.0 | 5 | |||
ECG for dyspnoea | Second | 97.1 | 5 | |||
ECG for palpitations | Second | 99.0 | 5 | |||
ECG for syncope | Second | 100 | 5 | |||
ECG for depressed level of consciousness | Second | 80.8 | 5* | |||
Know the diagnostic limitations of electrocardiography | Second | 93.3 | 4 | |||
Technical aspects of performing and reporting an ECG | ||||||
Acquire a standard 12-lead ECG and know where all the leads should be placed | Second | 94.3 | 5 | Acquire and interpret lead V4R | 69.3 | 4 |
Interpret the paper speed and voltage / know the correct calibration | Second | 94.3 | 5 | Acquire and interpret leads V7, V8, V9 | 37.6 | 2 |
Be able to recognize left right arm reversal | First | 76.2 | 5 | Perform and interpret a stress ECG | 35.0 | 2 |
Acceptable ECG documentation (including medico-legal aspects) | Second | 93.3 | 5 | Interpret the basics of a paced rhythm | 72.0 | 4 |
The patient-related and ethical aspects regarding ECG registration (including patient privacy, provision of information to patients regarding the registration of their ECG, etc.) | Second | 80.8 | 4 | |||
How to avoid ECG artefacts | Second | 90.4 | 4 | |||
Recognising computer misinterpretation from correct interpretation | Second | 90.4 | 5* | |||
For the mode, 5 represents strongly agree, 4 agree, 3 neutral, 2 disagree and 1 strongly disagree. | ||||||
* Wherever two modes were found, the higher mode was used. |
There was overwhelming consensus that medical graduates should be able to perform basic analysis of the ECG (Table 3) and recognise the normal ECG (Table 4). Most panellists strongly agreed that young doctors should be able to diagnose sinus rhythm, sinus arrhythmia, sinus tachycardia and sinus bradycardia. Regarding atrial rhythms, atrial fibrillation and atrial flutter were considered important by most. None of the junctional rhythms reached consensus. The life-threatening ventricular rhythms, i.e. ventricular tachycardia, torsades de pointes and ventricular fibrillation all reached consensus. Conduction abnormalities such as left and right bundle branch block, as well as all the atrioventricular (AV) blocks were considered important. Left and right ventricular hypertrophy reached consensus, as well as transmural (STEMI) and subendocardial ischaemia (NSTEMI). As shown in Table 5, most panellists strongly agreed that medical graduates should be able to recognise ECG features such as AV dissociation and pathological Q waves. Consensus was also reached for the recognition of clinical diagnoses such as pericarditis and electrolyte abnormalities (such as hyperkalaemia) on the ECG. Most panellists strongly agreed that medical graduates should have an approach to regular and irregular, narrow and wide complex tachycardias.
Topics for which consensus was reached | Round in which consensus was reached | Agreement amongst panellists (%) | Mode | Topics for which consensus was not reached | Agreement amongst panellists (%) | Mode |
---|---|---|---|---|---|---|
Calculate the ventricular rate | First | 96.2 | 5 | Calculate the corrected QT interval | 64.4 | 4 |
Calculate the atrial rate | First | 90.8 | 5 | |||
Recognise sinus P wave | First | 99.2 | 5 | |||
Measure PR interval | First | 94.7 | 5 | |||
Measure QRS width | First | 96.2 | 5 | |||
Determine the QRS axis | First | 90.1 | 5 | |||
Measure QT interval | First | 82.4 | 5 | |||
For the mode, 5 represents strongly agree, 4 agree, 3 neutral, 2 disagree and 1 strongly disagree that a junior doctor should be able to perform these ECG analyses. |
Topics for which consensus was reached | Round in which consensus was reached | Agreement amongst panellists (%) | Mode | Topics for which consensus was not reached | Agreement amongst panellists (%) | Mode |
---|---|---|---|---|---|---|
The normal ECG | ||||||
Normal ECG | Second | 100 | 5 | |||
Sino-atrial rhythms | ||||||
Sinus rhythm | First | 98.5 | 5 | Sinus pauses | 54.5 | 4 |
Sinus arrhythmia | First | 87.0 | 5 | Sino-atrial (SA) exit block | 23.8 | 2 |
Sinus tachycardia | First | 99.2 | 5 | |||
Sinus bradycardia | First | 97.0 | 5 | |||
Sinus arrest | Third | 78.2 | 4 | |||
Atrial rhythms | ||||||
Premature atrial complex (PAC) | First | 77.1 | 4 | Ectopic atrial tachycardia | 32.7 | 2 |
Atrial fibrillation | First | 99.2 | 5 | Multifocal atrial tachycardia | 48.5 | 2 |
Atrial flutter | First | 94.0 | 5 | Atrial flutter with fixed block | 73.3 | 4 |
Atrial flutter with variable block | 52.5 | 4 | ||||
Junctional rhythms | ||||||
Premature junctional complex (PJC) | 40.6 | 2 | ||||
Junctional escape rhythm | 49.5 | 4 | ||||
AVJRT | 27.7 | 2 | ||||
AVNRT | 32.7 | 2 | ||||
AVRT | 28.7 | 2 | ||||
Ventricular rhythms | ||||||
Premature ventricular complex (PVC) | First | 91.6 | 4 | Capture beat | 32.7 | 2 |
Ventricular escape rhythm | First | 77.9 | 4 | Fusion beat | 26.7 | 2 |
Monomorphic ventricular tachycardia (MMVT) | First | 92.4 | 5 | |||
Polymorphic ventricular tachycardia (PMVT) | First | 90.1 | 5 | |||
Torsades de pointes | First | 87.8 | 5 | |||
Ventricular fibrillation | First | 99.2 | 5 | |||
Ventricularly paced rhythm | Second | 77.4 | 4 | |||
Abnormal conduction | ||||||
Complete left bundle branch block (LBBB) | First | 98.5 | 5 | Left anterior fascicular block (LAFB) | 37.6 | 2 |
Complete right bundle branch block (RBBB) | First | 97.0 | 5 | Left posterior fascicular block (LPFB) | 24.8 | 2 |
First degree AV block | First | 93.9 | 5 | Bifascicular block | 36.6 | 2 |
Mobitz type I second degree AV block | First | 91.6 | 5 | Non-specific intraventricular conduction delay | 34.7 | 2 |
Mobitz type II second degree AV block | First | 93.1 | 5 | SVT with bundle branch block | 59.4 | 4 |
2:1 AV block | First | 86.3 | 5 | AF with bundle branch block | 67.3 | 4 |
Complete heart block | First | 98.5 | 5 | AF with pre-excitation (WPW) | 40.6 | 2 |
Pre-excitation / Wolff-Parkinson-White (WPW) pattern | Third | 81.2 | 4 | |||
Chamber enlargement | ||||||
Left atrial enlargement | First | 75.6 | 4 | |||
Right atrial enlargement | Second | 84.9 | 4 | |||
Left ventricular hypertrophy (LVH) | First | 93.9 | 5 | |||
Right ventricular hypertrophy (RVH) | First | 86.3 | 5 | |||
Ischaemia | ||||||
Transmural ischaemia (STEMI) | First | 99.2 | 5 | Wellens' syndrome | 44.6 | 2 |
Subendocardial ischaemia (NSTEMI) | First | 98.5 | 5 | De Winter's syndrome | 24.8 | 2 |
Right ventricular (RV) infarct | Second | 88.5 | 4 | Left main coronary artery insufficiency | 56.4 | 4 |
Posterior infarct | Second | 88.5 | 4 | Pseudo-infarction patterns | 64.4 | 4 |
Different phases of a myocardial infarction | Second | 76.9 | 4 | STEMI in the presence of a LBBB | 61.4 | 4 |
Able to localise myocardial infarcts | First | 85.4 | 4 | STEMI in the presence of a paced rhythm | 32.7 | 2 |
Differentiate early repolarisation from ischemic changes | 66.3 | 4 | ||||
Abnormal repolarisation | ||||||
Long QT syndrome | First | 89.3 | 4 | Short QT syndrome | 16.8 | 2 |
Repolarisation changes (strain) secondary to LVH | Second | 86.5 | 4 | |||
Repolarisation changes (strain) secondary to RVH | Third | 79.2 | 4 | |||
For the mode, 5 represents strongly agree, 4 agree, 3 neutral, 2 disagree and 1 strongly disagree that a junior doctor should be able to make these ECG diagnoses. | ||||||
* Wherever two modes were found, the higher mode was used. |
Topics for which consensus was reached | Round in which consensus was reached | Agreement amongst panellists (%) | Mode | Topics for which consensus was not reached | Agreement amongst panellists (%) | Mode |
---|---|---|---|---|---|---|
Abnormal features on the ECG | ||||||
AV dissociation | Second | 82.1 | 5 | Early repolarisation | 60.4 | 4 |
Poor R wave progression | Second | 87.7 | 4 | Brugada pattern | 27.7 | 2 |
Small QRS complexes | Second | 87.7 | 4 | New tall T wave in V1 | 51.5 | 4* |
Electrical alternans | Third | 80.2 | 4 | T wave inversion in aVL | 47.5 | 4 |
Pathological Q waves | First | 97.0 | 5 | U waves | 71.3 | 4 |
Non-specific T wave inversion | First | 83.2 | 4 | Inverted U waves | 15.8 | 2 |
Clinical / biochemical diagnosis | ||||||
Pericarditis | First | 87.8 | 5 | Tricyclic antidepressant (TCA) toxicity | 59.4 | 4 |
Pericardial effusion | Second | 88.5 | 4 | Na channel blocker toxicity | 28.7 | 2 |
Acute pulmonary embolism | Second | 87.5 | 4 | Calcium channel blocker toxicity | 39.6 | 2 |
Features of pulmonary hypertension | Second | 86.5 | 4 | Beta-blocker toxicity | 60.4 | 4 |
Hyperkalaemia | First | 94.6 | 5 | Hypertrophic cardiomyopathy | 59.4 | 4 |
Hypokalaemia | First | 76.9 | 5 | Dextrocardia | 57.4 | 4 |
Digoxin toxicity | Second | 75.0 | 4 | Hypothermia | 72.3 | 4 |
Shivering artefact | Second | 86.5 | 4 | Hypothyroidism | 37.6 | 2 |
Pleural effusion | 17.8 | 2 | ||||
Pneumothorax | 17.8 | 2 | ||||
Raised intracranial pressure | 41.6 | 2 | ||||
Diagnostic approach to the abnormal ECG | ||||||
Differential diagnosis for right axis deviation | First | 80.0 | 4 | |||
Differential diagnosis for left axis deviation | First | 80.8 | 4 | |||
Differential diagnosis for dominant R wave in V1 | First | 77.7 | 4 | |||
Regular narrow complex tachycardia | Second | 95.2 | 5 | |||
Irregular narrow complex tachycardia | Second | 87.5 | 5 | |||
Regular wide complex tachycardia | Second | 95.2 | 5 | |||
Irregular wide complex tachycardia | Second | 88.5 | 5 | |||
For the mode, 5 represents strongly agree, 4 agree, 3 neutral, 2 disagree and 1 strongly disagree. | ||||||
* Wherever two modes were found, the higher mode was used. |
Feedback was received in free-text form from 25 and 28 participants at the end of the second and third rounds’ surveys respectively (Supplementary Table 8). Themes that emerged from the inductive analysis were issues with curriculum development, knowing when to seek advice, contextualised learning and a recognition of the importance of the work studied in this modified Delphi study (Table 6).
Table 6: The leading themes and subthemes that emerged from the qualitative analysis
Theme |
Subtheme |
Number of mentions |
Examples |
Curricular development
|
Need for prioritisation |
16 |
“I feel we should focus on firm basics and the emergencies” “There are certain things they need to be able to recognise on their first night on call - can these issues be weighted more heavily?” “Focus should be on identifying life threatening conditions and conditions that cannot be diagnosed without an ECG.”
|
Too difficult |
9 |
“The more complex the curriculum, the more insecure the junior doctor.” “When making things too complicated one can overwhelm the students.” “If too much detail is taught to the undergraduate, mistakes are even more likely!” “Complex diagnoses … may be overwhelming for a large proportion and result in less learning paradoxically.”
|
|
Too much work |
5 |
“Although it is important for junior doctors to have a good knowledge of ECG interpretation, it will be difficult for them to retain all included aspects.” “The undergraduate curriculum is extensive and needs to be reduced” “Our purpose is to empower the junior doctor, not provide a comprehensive overhaul from the outset. Knowledge is incremental over the doctor's work lifespan. For the junior doctor, keep it simple with must know and nice to know”
|
|
Know when to seek advice
|
From an experienced colleague
|
4 |
“Not knowing everything is OK but their teaching must include that when they don't know it is imperative to ask somebody who does know”
|
By means of electronic support |
5 |
“Expose them to the many medical apps that are available that can assist with diagnosis” “Consider the usage of phone apps to assist at the bedside. Most students use tthese and it might be worth including teaching the skill of looking up ECGs at the bedside”
|
|
Contextual learning |
Clinical context |
3
|
“It is vital to teach the ECG in a clinical context and to integrate it into the clinical diagnosis”
|
Workplace experience |
3 |
“Other … factors may have to be taken into account, such as the amount of patient exposure an undergraduate student … would have had, the … curriculum contact time that can be afforded to ECG training and the most common diagnoses that students will encounter in a particular environmental context”
|
|
Other strategies for making diagnosis
|
2 |
“… junior doctors have … access to a lab in South Africa: [diagnosing] hypokalaemia / hyperkalaemia etc … by ECG loses importance”
|
|
Recognition of importance study |
Positive stakeholder engagement
|
11 |
“Thank you for the opportunity to participate in this study.”
|
Criticism of Delphi process |
4 |
“The time between rounds may have influenced my responses” “The panel should not consist of too many cardiologists.”
|
|
Dissemination of results
|
4 |
“Please circulate findings as soon as available.” “The results will really polish our way to tutoring and mentoring”
|
An important sub-theme that emerged under curricular development, was the need for prioritisation of the different topics that are taught in electrocardiography. Students should be taught “the firm basics and emergencies” to ensure that they are able to diagnose conditions that are life-threatening, or often encountered in clinical practice, once they graduate. Expert panellists cautioned against an undergraduate ECG curriculum that is too difficult (i.e. including ECGs that are too complex for the level of training of young graduates) and also voiced their concern of an undergraduate ECG curriculum that is too extensive and covers too much work.
Participants advised that students should be encouraged to seek advice from more experienced colleagues when they have diagnostic uncertainty and to be taught how to make use of electronic support, such as smartphone applications (“apps”) as points of reference, in the workplace.
It was recommended that ECGs should be taught within a given clinical context. However, with regard to ECG diagnoses, panellists suggested that the focus of an ECG curriculum should be on conditions that can only be diagnosed by an ECG. With regards to workplace teaching, there was a concern that not all the ECG diagnoses recommended by the Delphi study would be encountered in the workplace during student training.
There was predominantly positive stakeholder engagement. Participants were often appreciative of being invited to be part of the expert panel. On occasion, narratives concerned criticism of the Delphi process with regard to the composition of the panel and the interval between the rounds in the study. However, it was felt that the results of this study should be disseminated, as it would have a positive impact on undergraduate ECG training.
Based on the concerns of curriculum overload, we compiled a consolidated list of “must know” diagnoses that can only be made by means of an ECG recording (Table 7).
The normal ECG |
---|
Normal ECG |
Sino-atrial rhythms |
Sinus rhythm |
Sinus arrhythmia |
Sinus tachycardia |
Sinus bradycardia |
Atrial rhythms |
Atrial fibrillation |
Atrial flutter |
Ventricular rhythms |
Monomorphic ventricular tachycardia (MMVT) |
Polymorphic ventricular tachycardia (PMVT) |
Torsades de pointes |
Ventricular fibrillation |
Abnormal conduction |
Complete left bundle branch block (LBBB) |
Complete right bundle branch block (RBBB) |
First degree AV block |
Mobitz type 1 second degree AV block |
Mobitz type 2 second degree AV block |
2:1 AV block |
Complete heart block |
Chamber enlargement |
Left ventricular hypertrophy (LVH) |
Right ventricular hypertrophy (RVH) |
Ischaemia |
Transmural ischaemia (STEMI) |
Subendocardial ischaemia (NSTEMI) |
Clinical diagnosis |
Pericarditis |
* this list excludes conditions which can be diagnosed with alternative diagnostic modalities (e.g. hyperkalaemia, hypokalaemia that are diagnosed in the laboratory) |
This modified Delphi study was a first attempt to obtain consensus on an ECG curriculum for medical students. Through an iterative process of systematically measuring agreement amongst ECG experts, 80 topics reached consensus to be included in undergraduate ECG teaching. These topics included the clinical indications and technical aspects of performing and reporting an ECG, basic ECG analysis (rate, rhythm, interval measurements, QRS axis), recognition of the normal ECG, abnormal ECG rhythms and waveforms, and use of the ECG to make or support a clinical diagnosis. From this list of topics, it was possible to identify 23 “must know” conditions, which medical graduates should be able to diagnose. These 23 conditions should serve as the core of an undergraduate ECG curriculum, because they encompass important life-threatening conditions (such as ischaemia, ventricular arrhythmias, atrial fibrillation and high degree AV blocks) that can only be diagnosed by means of an ECG, and for which urgent intervention is likely to make a significant difference to outcome.
The validity of the results of any Delphi study depends on the expertise of the panel.16, 26 Our study consisted of a large expert panel working in a broad range of clinical practice settings. The Delphi study literature has cautioned that large expert panels are difficult to manage, with little benefit of better results.16, 57 Indeed, we did encounter delays in obtaining responses from the expert panel. However, there was a high response rate and little attrition between rounds. Moreover, the positive stakeholder engagement by participants endorsed the importance of the study. As the surveys were done online, the study was a cost-effective way of gathering the opinion of experts,15 and it saved the participants the time and expense of face-to-face meetings.25 Furthermore, anonymous participation and feedback limited the influence of panel members on each other.15
Over and above the list of topics that should be taught, the responses by participants in this study highlight several important issues regarding ECG curriculum development. The long list of topics that was suggested, over and above the original pre-selected list, illustrates the tendency for curricular overload and the demand for diagnostic expertise beyond the reach of new medical graduates. Overwhelming novices with ECG content that is “too much” and/or “too difficult” paradoxically results in less learning.58 It is therefore important that course conveners refrain from overloading students.
It has been suggested that tuition should be geared towards the understanding of vectors,59 and the basics of electrocardiography.60–62. If students are familiar with the features of a normal ECG, they may be more able to identify abnormal rhythms and waveforms by means of analysis and pattern recognition.63–65
A theme that emerged strongly from the feedback by the expert panel was the need for prioritisation within a curriculum. The list of 23 “must know” diagnoses, is well aligned with the current recommendation in the literature that ECG teaching should focus on enabling medical graduates to safely diagnose life-threatening conditions, so that the emergency management could be promptly implemented.66 However, in the event of diagnostic uncertainty, graduates should be encouraged to seek assistance from more senior colleagues. Current medical education opinion is increasingly recognising the supportive role of information technology in the process of clinical reasoning and diagnosis.67 The expert panel’s suggestion that smartphone applications be used to support cognitive diagnostic processes in ECG training is well aligned with this opinion.
The need for clinically contextualised ECG training was reaffirmed by this study. This observation is consistent with our knowledge that clinicians make more accurate ECG diagnoses when the clinical context is known.38 While this underscores the importance of learning in the workplace, our modified Delphi study identified ECGs that may not be routinely observed in clinical training settings. The participants therefore expressed concern that undergraduate ECG training must be comprehensive and not driven by opportunistic learning encounters only.68, 69
Although this modified Delphi study was conducted in only one country, it does represent a broad spectrum of opinion amongst a large group of clinicians engaged in undergraduate ECG education and is, therefore, worthy of consideration in the international community. The proposed list of 23 “must know” conditions, consisting of life-threatening and commonly encountered conditions, is applicable to medical school training in any part of the world.
This modified Delphi study established consensus for a list of conditions that should be taught. However, it does not recommend the teaching modalities that should be used for ECG instruction.
We have identified undergraduate ECG teaching priorities by means of a modified Delphi study with an expert panel that consisted of specialists with a wide range of expertise. Instead of teaching long lists and complex conditions, we propose focusing on the basics of electrocardiography, life-threatening arrhythmias and waveforms, as well as conditions commonly encountered in daily practice.
AF, atrial fibrillation; AV, atrioventricular; ECG, electrocardiogram; LAFB, left anterior fascicular block; LBBB, left bundle branch block; RBBB, right bundle branch block; SD, standard deviation; STEMI, ST elevation myocardial infarction; UCT, University of Cape Town; WPW, Wolff-Parkinson-White.
Approval was obtained from the Human Research Ethics Committee (HREC) at the Faculty of Health Sciences (HREC reference number 680/2016), as well as institutional permission from the Human Resources Department at the University of Cape Town. All participants provided consent prior to participation in the study.
All study participants provided informed consent for the anonymised analysis of their responses in the three rounds of the modified Delphi study and a possible scientific publication of the results.
The datasets used and/or analysed during the current study, are available in the “Determining electrocardiography training priorities for medical students using a modified Delphi method” repository, which could be accessed at the DOI 10.25375/uct.12412724.
The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the article.
RSM is a lecturer and host of the AO Memorial Advanced ECG and Arrhythmia Course and receives an honorarium from Medtronic Africa. The authors did not receive a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
CAV conceived the study protocol, with advice from RSM and VCB regarding study design. CAV collected the data. CAV performed the statistical analysis under the guidance of KM. CAV, RSM and VCB interpreted the results. CV drafted the manuscript, which was critically revised by RSM, KM and VCB.
The authors wish to thank Ms Sylvia Dennis from the Hatter Institute for her input and assistance, as well as Ms Annemie Stewart and Ms Chedwin Grey at the Clinical Research Centre (CRC), Faculty of Health Sciences, University of Cape Town for their support with REDCap. We are grateful for Dr Heike Geduld for her advice on the modified Delphi technique. We would also like to thank the expert panellists for their time to complete the online surveys and their valuable input.