Introduction
Electrocardiography skills are an important part of clinical knowledge for physicians of different specialties. There is no single solution to teaching and learning ECG. Several options have been used, but the final results have never been fully satisfactory [1–4].
In a publication dedicated to the improvement of clinical skills in radiology, Koontz and Heitkamp [5] point out that the basic rules of bird identification have a striking resemblance to the practice of radiology. These authors explain that while making bird observations, radiologists can both relax in contact with nature and practise a radiological skill, as well as master their experience in clinical practice. In our opinion, this can also be extended to the analysis of ECG records.
They described similarities between these two seemingly distinct activities. Like radiologists, birders rely on visual pattern recognition to identify and correctly differentiate bird species. Similarly, a radiologist should assess a lesion’s size, shape, margins, signal intensity, and enhancement pattern to differentiate certain pathologies. Birders use a similar multivariate analysis of a bird’s size, shape, colour, behaviour and so-called ‘field marks’ – characteristic stripes, spots or patterns – to distinguish bird species. They emphasise that success in birding, as in radiology, requires more than superficial recognition of units based on appearance, but a deeper understanding of the bird’s habitat, behaviour, vocalisations and other information. The authors add that birding is primarily a visual interpretive activity; therefore, birders make diagnostic errors similar to those made by radiologists. They conclude that to err is human, but experiencing the process of making, identifying and correcting such diagnostic errors in a pressure-free, penalty-free activity such as birding can provide an invaluable learning opportunity for radiologists.
In our view, all these observations can also be extended to ECG diagnostics. This is also an activity based on visual analysis of data, analogous to that in radiology. Therefore, improvement in the ability to analyse shapes, details, and the context of the ECG recording can, in our opinion, be improved by learning to identify bird species. It can also lead to the achievement of a high capacity for procedural data analysis, called clinical intuition in medicine and ‘jizz’ in ornithology [6].
We would like to verify whether a method of improving visual analysis skills analogical to that described above may help in ECG learning, in general, in improving the recognition of important, albeit sometimes small, seemingly ‘hidden’ changes in the ECG tracings.
Material and methods
We offered to the participants of a cardiological conference volunteer attendance of a short experimental ECG course. Due to the innovative nature of the course, this was a single-group study without a control or comparison group. The main purpose that we announced was improvement in ECG recognition.
The course consisted of 4 parts. In the first part, the participants were presented with 10 ECGs in succession on the screen (2 min each) and a question with one correct answer.
Questions were based on the recognition of P waves, QRS width, QRS morphology and QRS origin. One point was awarded for each correct answer. Participants responded anonymously on the printed form. They were also asked to indicate their level of ECG knowledge – beginners, advanced or experienced.
In the second part they had a 20 min lecture on ‘how to recognize birds’ with a detailed explanation of how to recognise important differences in bird morphology. The presentation of bird species was based on the pages of the atlas Birds of Europe [7], using the most common species in Polish conditions: sparrow, tree sparrow, Eurasian siskin, greenfinch, blue tit, great tit, Corvidae, hawk, and buzzard. Participants were asked to analyse the appearance of birds in the atlas and then identify the bird species in photographs without species descriptions.
The third part involved repetition of 10 previously analysed electrocardiograms with the same questions. After this part, the forms were returned.
After the break, in the fourth part, all the electrocardiograms were explained. The participants were asked to answer the second form. The questions were generally about their opinion on the usefulness of such ECG teaching.
Statistical analysis
Continuous variables are presented as mean (SD). Student’s t-test for paired and nonpaired data was used.
Results
Finally, 57 persons started and completed the course – 39 women and 18 men. Fourteen of them self-identified as ‘beginners’ in ECG, 27 as ‘advanced’ and 16 as ‘experienced’.
The mean result was 4.26 (1.9) in the first part and 5.04 (2.1) in the repetition (p = 0.002). Seventeen participants (30%) achieved an improvement in the result of more than 1 point, while four (7%) had a worse second result than the first (more than 1 point). Two participants had the best results – 10 and 9 – in both parts. Additionally, 5 achieved a result of 8 in the second part. In Table I we present the results in the 3 subgroups in the final form.
Table I
Accuracy of ECG analysis before and after a workshop on bird species recognition in groups of physicians: beginners, advanced and experienced
Discussion
In addition to the work on radiology by Koontz and Heitkamp cited above [5], which highlights the potential for applying methods similar to those used by birdwatchers to medicine, there are other reports and a consensus that doctors can improve their diagnostic skills through birdwatching [6, 8]. One notable example comes from Harvard Medical School (HMS), where Professor Rose Goldman, an advocate of integrating birding techniques into medical education, has used this approach [8]. She argues that finding distinguishing features to arrive at a medical diagnosis is similar to looking at the characteristics and behaviour of a bird to arrive at an identification. Goldman incorporated a short bird identification lesson into the HMS Practice of Medicine (POM) course. She uses bird identification methods in the early years of medical training, particularly for students who do not yet have an established base of scientific or medical knowledge and are not well versed in the multitude of diseases that can cause a patient’s symptoms. Based on this experience and a review of the neurobiological literature, it has been suggested [9] that a person with a talent for bird-watching might also excel in visual diagnostic fields such as dermatology or radiology – and we would add cardiology to this list. Conversely, someone who is naturally inclined towards the visual aspects of medicine might also be an adept birder. In general, developing frameworks and tools for birding helps to sharpen focus in other areas, including medical diagnostics.
One of the factors influencing this study is the fact that the course participants were cardiologists, particularly those interested in electrocardiography. These individuals already had some ECG interpretation skills and wanted to develop them, and had extensive prior experience in cardiology training. Therefore, their subjective evaluation of the course may have been influenced by a number of factors. First, they were exposed to a course that they had never experienced before. As a result, the novelty effect and the tendency to give positive responses to please their instructors may have played a role. On the other hand, a course with a format different from all previous ones may have elicited negative evaluations, especially from those who favour a strictly scientific approach and are used to traditional and therefore ‘correct’ teaching methods. According to the authors’ opinion, this is perfectly reflected in the distribution of ratings – some participants found the course a novel and interesting experience (32 out of 50), while others found it unhelpful (16 out of 50) or even disruptive (2 out of 50).
Conclusions
To the best of the authors’ knowledge, this is the first study on the use of bird species recognition training to improve the accuracy of ECG analysis. The results of our experiment confirmed a well-known opinion – there is no universal way to teach ECG, and new teaching methods should be explored. Our experimental course showed that training in bird species recognition can help to improve recognition of different parts of the ECG curve. Learning to recognise bird species can activate visual analysis fields, and this process may extend its effect beyond just recognising birds [10]. Our results suggest that it can promote an improved ability to analyse ECG recordings. We have to admit that we did not have a control group (repetition without the ‘bird recognition lecture’), but the final results and the opinion of the participants suggest that this type of teaching can be considered as a method for better ECG recognition by clinicians. Our study should be repeated with a control group to obtain fully reliable results.
