Keeping Pace: The Need for Digital Health Education in Medical Schools
Abstract
To the Editor: The potential of digital technologies in clinical settings is enormous. However, to take full advantage of these technologies, medical students need to have a basic understanding of how and why they work, as well as their potential pitfalls. Unfortunately, the rate of digital implementation is far exceeding the rate of increasing digital health literacy. Although some basic statistics, epidemiology, and informatics courses are offered at medical schools, as students, we do not receive basic training in fields, such as artificial intelligence (AI), biohacking, or big data. These technologies are not yet routinely used in clinical settings, but their presence is growing. Three main ideas should guide digital health literacy curriculum implementation: (1) Encompassing relevant technology: We should prioritize AI and telemedicine in curricula since they are likely to be used routinely. (2) Identifying the necessary level of competency required: We need a basic understanding of the concepts within each type of technology, but by no means do we need to become experts. (3) Addressing the ethics and potential pitfalls of each technology: We should avoid certain patient groups from being disadvantaged as a direct result of digital initiatives (e.g., AI bias, inequity with regard to access, etc.). Integrating more digital health into curricula would undoubtedly lead to more physicians feeling comfortable navigating this landscape.1 The onus is on both medical students to demand additions to the curricula and on curriculum directors to recognize this demand and act proactively. For example, in the field of genomic medicine, there have been efforts in the United Kingdom and in the United States to revise the curriculum by reaching consensus on the most important topics to include and subsequently implementing these changes.2–4 As digital health espouses the up-and-coming mantle previously championed by genomic medicine, medical education needs to keep pace.
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Contributions elaborated mainly or solely by medical students strongly call for the inclusion of AI education in medical curricula; students were enthusiastic about learning AI and recognized its crucial role in the future of medicine, but reported a lack of formal AI training and insufficient AI-related learning opportunities; researchers and educators also demanded inclusion of AI in medical Cur
“Finally, contributions elaborated mainly or solely by medical students strongly call for the inclusion of AI education in medical curricula [50–54]. Students were enthusiastic about learning AI and recognized its crucial role in the future of medicine [45, 55]. However, they reported a lack of formal AI training and insufficient AI-related learning opportunities in their medical education [46, 56,”
From Artificial intelligence in undergraduate medical education: an updated scoping review (2025) · cites this paper as [53]
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Grunhut, J., Wyatt, A. T., & Marques, O. (2021) · Journal of Medical Education and Curricular Development · doi:10.1177/23821205211036836 · Cited by 161 · see citing works
“Medical students need to be sufficiently proficient in understanding the fundamental concepts of how AI functions, its advantages to improve expenses, increase quality, and ease access to healthcare.(24,25) Similarly, students must be educated about the shortfalls of AI such as transparency and liability.”
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Prophecy and promise: Sociotechnical imaginaries in academic medicine strategic planningPreprint
Rowland, P., Brydges, M., & Kulasegaram, K. M. (2023) · Research Square · doi:10.21203/rs.3.rs-3697943/v1
Khurana, M. P., Raaschou-Pedersen, D. E. T., Kurtzhals, J., Bardram, J. E., Ostrowski, S. R., & Bundgaard, J. S. (2022) · Figshare · doi:10.6084/m9.figshare.19242487
Self-citationKhurana, M. P., Raaschou-Pedersen, D. E. T., Kurtzhals, J., Bardram, J. E., Ostrowski, S. R., & Bundgaard, J. S. (2022) · Figshare · doi:10.6084/m9.figshare.19242481
Self-citationKhurana, M. P., Raaschou-Pedersen, D. E. T., Kurtzhals, J., Bardram, J. E., Ostrowski, S. R., & Bundgaard, J. S. (2022) · Figshare · doi:10.6084/m9.figshare.19242484
Self-citation
- Authors
- Khurana, M.
- Affiliations
- University of Copenhagen (DK)
- Corresponding author
- Khurana, Mark
- ORCID
- Khurana, Mark
- Venue
- Academic Medicine
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-10-27
- Volume
- 95
- Issue
- 11
- Pages
- 1629-1630
- ISSN
- 1040-2446 (ISSN-L)
- OpenAlex
- W3097296491
- Cited by
- 21
- References
- 3
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 4 · 2022: 7 · 2021: 3
- FWCI
- 1.04
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Academic Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Health Sciences › Health Professions › General Health Professions › Health and Medical Education
- Keywords
- digital health literacy, medical curriculum, artificial intelligence in healthcare, telemedicine, biohacking, big data, algorithmic bias, health disparities, medical students, competency requirements
- MeSH terms
- Digital Technology, Artificial Intelligence, Curriculum, Education, Medical, Undergraduate, Humans, Professional Competence, Telemedicine
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