To the Editor: The timely article by Coiera and colleagues1 makes several astute points, including the need for a fleetness of response in the development of a workforce that is able to contribute meaningfully in the realm of artificial intelligence (AI). The role of several clinical colleges is highlighted in the article. At present, clinical trainees in multiple programs who wish to pursue further education in fields relating to AI and digital health must do so concurrently with their clinical training. We contend that digital health training should be recognised as an accredited term in specialty training pathways to facilitate this future workforce development.
Medical student education clearly has an important role in the development of practitioners with the requisite abilities to engage with modern digital health trends. Evidence suggests that medical students from diverse backgrounds currently have deficits in areas including understanding the stages of model development and algorithmic performance evaluation.2 Although such early education is important, there are likely to be certain skills that can only be learned and honed once in the workforce. Skills that are required include aspects of data management, analysis, security, and ethical use, to name a few domains. Recent review articles in college journals have described such digital competencies and means by which their teaching could be promoted.3,4 However, as with clinical medicine, only so much can be learned through didactic teaching.
Undertaking roles working in the digital health space is likely to be required to develop a replete set of abilities for practitioners with a focus on digital health. It is not envisaged that accredited digital health terms would be undertaken by all trainees. However, to facilitate the development of a diverse and skilled workforce, the accreditation of rotations undertaken in such fields for interested trainees may be necessary. With respect to digital health, the canonical statement commonly attributed to Benjamin Franklin is as relevant now as ever before: “Tell me and I forget. Teach me and I remember. Involve me and I learn”.5
- 1. Coiera EW, Verspoor K, Hansen DP. We need to chat about artificial intelligence. Med J Aust 2023; 219: 98‐100. https://www.mja.com.au/journal/2023/219/3/we‐need‐chat‐about‐artificial‐intelligence
- 2. Blacketer C, Parnis R, Franke KB, et al. Medical student knowledge and critical appraisal of machine learning: a multicentre international cross‐sectional study. Intern Med J 2021; 51: 1539‐1542.
- 3. Scott IA, Shaw T, Slade C, et al. Digital health competencies for the next generation of physicians. Intern Med J 2023; 53: 1042‐1049.
- 4. Kovoor JG, Bacchi S, Gupta AK, et al. Artificial intelligence clinical trials and critical appraisal: a necessity. ANZ J Surg 2023; 93: 1141‐1142.
- 5. Richards JC, Rodgers TS. Approaches and methods in language teaching: a description and analysis. Cambridge, England: Cambridge University Press, 1986.
Open access:
Open access publishing facilitated by Flinders University, as part of the Wiley – Flinders University agreement via the Council of Australian University Librarians.
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