Determining electrocardiography training priorities for medical students using a modified Delphi method

DOI: https://doi.org/10.21203/rs.3.rs-68479/v2

Abstract

Background

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 expert consensus amongst content and context experts on an ECG curriculum for medical students.

Methods

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. 

Results

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.

Conclusion

A multidisciplinary expert panel reached consensus on the ECG training priorities for medical students.

Background

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 students.5  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.


Establishing consensus using the Delphi method

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.

Methods

This study used a modified Delphi technique to establish consensus on a curriculum for undergraduate ECG training.


Delphi expert panel

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 expert panel if they fulfilled all of the following criteria:

In South Africa, medical students undergo six years of undergraduate training before graduating as medical doctors, with the exception of one medical school offering a five-year course.   South African undergraduate medical programmes include both pre-clinical and clinical training.  Although there is no national or international guideline on which undergraduate ECG training or assessment is based, the eight medical schools in South Africa offer comprehensive undergraduate ECG teaching, as demonstrated in Table 1.  Medical students receive formal ECG tuition during pre-clinical (typically second and third year) and clinical training (typically fourth to sixth year) and are exposed to real-life ECG analysis and interpretation during various clinical clerkships.  However, each academic institution choses their own curriculum and appoint lecturers (from various departments) who are available and show an interest in the subject.   For the most part, ECG competence is assessed by multiple choice questions (MCQ), objective structured clinical examination (OSCE) and as part of clinical examinations.  

After graduation, South African medical graduates do a two-year internship at an accredited hospital where they practice under supervision.  All medical interns rotate through Family Medicine (with dedicated time in Emergency Medicine and Psychiatry), Internal Medicine, Paediatrics, Obstetrics, Orthopaedics, Surgery and Anaesthetics. Although there is little formal ECG training during their internship, they are required to perform and interpret ECGs in most of these rotations.  In the third year after graduation, they are compelled to 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.

 

Delphi survey development

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

 

Delphi survey administration 

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.

The first round of the modified Delphi study

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.

 

Analysis of the first round’s results and preparation for the second round

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, as well as the additional items suggested by the expert panel (Supplementary Table 3).

 

The second round of the modified Delphi study

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.

 

Analysis of the second round’s results and preparation for the third round

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.

 

The third round of the modified Delphi study

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.  

 

Statistical analysis after the third round

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

Results

The modified Delphi expert panel

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 (Figure 2). Of the 249 specialists who were 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 2, 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.).

 

Items that achieved consensus

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 3, 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.

There was consensus that medical graduates should be able to perform basic analysis of the ECG (Table 4) and recognise the normal ECG (Table 5).  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 6, 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.

 

Feedback from participants

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 7).

 

Issues with curriculum development

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.

 

Knowing when to seek advice

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.

 

Contextualised learning

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. 

Recognition of the importance of this Delphi study

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.

 

Final list of “must know” ECG diagnoses

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 8).

Discussion

This modified Delphi study was a first attempt to obtain consensus on an ECG curriculum for medical students.  The variable training opportunities offered by medical schools and the lack of national and international guidance for an undergraduate ECG curriculum was the rationale for performing this study.  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 “should know” topics, it was possible to identify 23 “must know” conditions, which are considered as imperative ECG knowledge.  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.   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.  

A theme that emerged strongly from the feedback by the expert panel was the need for prioritisation within a curriculum (Figure 3).  Despite the concerns of curricular overload, 80 topics of ECG instruction achieved expert consensus.  These “should know” topics are proposed to guide undergraduate ECG instruction.  ECG lecturers and tutors are discouraged to include “nice to know” topics in undergraduate curricula.  However, reducing the list of 80 “should know” topics to a list of 23 “must know” conditions, allows for a core ECG curriculum that does not overwhelm the student.  This condensed list 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.59  Training that ensures that medical graduates are competent at diagnosing the conditions included in the core ECG curriculum, would therefore allow for safe practice.  However, in the event of diagnostic uncertainty, graduates should be encouraged to seek assistance from more senior colleagues.  Current medical education opinion is also increasingly recognising the supportive role of information technology in the process of clinical reasoning and diagnosis.60  The expert panel’s suggestion that smartphone applications be used to support cognitive diagnostic processes in ECG training is well aligned with this opinion.

It has been suggested that tuition should be geared towards the understanding of vectors,61 and the basics of electrocardiography.62-64.  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.65-67

The need for clinically contextualised ECG training was reaffirmed by this study.  This observation is consistent with previous reports that students and clinicians make more accurate ECG diagnoses when the clinical context is known.38, 68  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.69, 70 

 

Lessons learnt from this modified Delphi study

Although expert consensus on an undergraduate ECG curriculum could be derived from the quantitative data collection, the modified Delphi process also allowed for the collection of qualitative data, which helped to put the results of this study in perspective.  The quantitative results should therefore not be appraised in isolation or seen as the final arbiter, but rather be considered along with the important remarks by the expert panellists as highlighted by the qualitative content analysis.  The suggestions from the quantitative and qualitative analyses should also be implemented according to local context.

The large expert panel’s enthusiasm to participate in this study highlighted their acceptance of the Delphi technique as an appropriate means of establishing consensus.  The low attrition rate (despite the iterative rounds of the Delphi study) testifies to the inclination towards an expert consensus document for undergraduate ECG training.

 

 

Study limitations

Although this modified Delphi study was conducted in only one country, it does represent a broad spectrum of opinion amongst a large group of specialists 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, including those where specialist training commences straight after undergraduate studies.  The list encompasses conditions that are commonly encountered by clinicians, not limited to those who only work in Cardiology or Internal Medicine.  For example, a septic and dehydrated patient awaiting bowel surgery is at high risk of developing atrial fibrillation; or a femoral neck fracture might be the result of a syncopal event associated with third degree AV block.

A limitation to this Delphi study is the absence of Anaesthetists and Paediatricians on the expert panel for devising this undergraduate ECG curriculum.  These groups of clinicians, and potentially others, should be involved in future Delphi studies for the development of ECG curricula tailored to their practice.

This modified Delphi study established consensus for a list of conditions that we propose for the tuition of medical students.  These topics are apt for pre-clinical and clinical phases of training of medical students.  However, this study did not aim to achieve consensus on the teaching modalities that should be used for ECG instruction or assessment of ECG competence.

Conclusion

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.

Glossary Terms

Abbreviations

AF, atrial fibrillation; AV, atrioventricular; ECG, electrocardiogram; EPA, Entrustable Professional Activity; HREC, Human Research Ethics Committee; LAFB, left anterior fascicular block; LBBB, left bundle branch block; MCQ, multiple-choice question; OSCE, objective structured clinical examination; RBBB, right bundle branch block; SD, standard deviation; STEMI, ST elevation myocardial infarction; UCT, University of Cape Town; WPW, Wolff-Parkinson-White.

Declarations

Ethical approval and consent to participate

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.

Consent for publication

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.

Availability of data and materials

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.

Competing interests

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the article.

Funding

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.  

Authors’ contributions

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.  All authors have read and approved the manuscript.

Acknowledgements

The authors wish to thank Dr Heleen Emmer at Groote Schuur Hospital, Ms Sylvia Dennis and Dr Julian Hövelmann from the Hatter Institute for Cardiovascular Research in Africa (HICRA) for their very valuable 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 Ms Elani Muller and Dr Heike Geduld for their advice on conducting the modified Delphi technique and the medical interns at Groote Schuur Hospital for their willingness to provide insight to their undergraduate ECG training.  We would like to extend a special thanks to the expert panellists for their time to complete the iterative online surveys and their valuable input throughout study.

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Tables

Table 1: Overview of undergraduate ECG training at the eight South African medical schools.

 


n (%)

Formal lectures

Departments responsible for formal ECG lectures

Physiology

5 (62,5)

Clinical Skills

3 (37,5)

Cardiology

5 (62,5)

Internal Medicine

4 (50)

Family Medicine

4 (50)

Paediatrics

2 (25)

Anaesthesiology

2 (25)

Year of study during which medical students receive formal ECG teaching

2nd year

5 (62,5)

3rd year

6 (75)

4th year

6 (75)

5th year

5 (62,5)

6th year

7 (87,5)

Clinical exposure

Clerkships during which medical students are exposed to ECGs in the clinical setting

Cardiology

3 (37,5)

Internal Medicine

8 (100)

Family Medicine

5 (62,5)

Emergency Medicine

2 (25)

Paediatrics

2 (25)

Anaesthesiology

3 (37,5)

Year of study during which medical students are exposed to ECGs in the clinical setting

2nd year

0 (0)

3rd year

2 (25)

4th year

6 (75)

5th year

6 (75)

6th year

7 (87,5)

Assessment

Method by which ECG competence is assessed

MCQ

7 (87,5)

Written exam

1 (12,5)

OSCE

7 (87,5)

Case studies

2 (25)

Part of clinical examination

7 (87,5)

Year of study during which ECG competence is assessed

2nd year

2 (25)

3rd year

3 (37,5)

4th year

2 (25)

5th year

3 (37,5)

6th year

7 (87,5)

 

The above information is based on an anonymous survey conducted on first and second year medical interns at Groote Schuur Hospital, who trained at the eight medical schools in South Africa, namely Sefako Makgatho Health Science, University of Cape Town, University of the Free State, University of KwaZulu-Natal, University of Pretoria, University of Stellenbosch, University of the Witwatersrand and Walter Sisulu University. MCQ, multiple-choice question; OSCE, objective structured clinical examination.

 

Table 2: Composition of the modified Delphi study expert panel.

 

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 

 

 

Table 3: Know the indications for performing an ECG, as well as its technical requirements and reporting

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.

Table 4: Basic ECG analysis

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.

Table 5: Recognition of the normal ECG and abnormal rhythms and waveforms

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.

 

Table 6: Using the ECG to make or support a diagnosis

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.

 

 

Table 7: 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”

 

 

Table 8: The majority of expert panellists strongly agreed that a junior doctor should be able to make the following ECG diagnoses

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)