Medical education trends for future physicians in the era of advanced technology and artificial intelligence: an integrative review
Open accessAbstract
Background: Medical education must adapt to different health care contexts, including digitalized health care systems and a digital generation of students in a hyper-connected world. The aims of this study are to identify and synthesize the values that medical educators need to implement in the curricula and to introduce representative educational programs. Methods: An integrative review was conducted to combine data from various research designs. We searched for articles on PubMed, Scopus, Web of Science, and EBSCO ERIC between 2011 and 2017. Key search terms were “undergraduate medical education,” “future,” “twenty-first century,” “millennium,” “curriculum,” “teaching,” “learning,” and “assessment.” We screened and extracted them according to inclusion and exclusion criteria from titles and abstracts. All authors read the full texts and discussed them to reach a consensus about the themes and subthemes. Data appraisal was performed using a modified Hawker ‘s evaluation form. Results: Among the 7616 abstracts initially identified, 28 full-text articles were selected to reflect medical education trends and suggest suitable educational programs. The integrative themes and subthemes of future medical education are as follows: 1) a humanistic approach to patient safety that involves encouraging humanistic doctors and facilitating collaboration; 2) early experience and longitudinal integration by early exposure to patient-oriented integration and longitudinal integrated clerkships; 3) going beyond hospitals toward society by responding to changing community needs and showing respect for diversity; and 4) student-driven learning with advanced technology through active learning with individualization, social interaction, and resource accessibility. Conclusions: This review integrated the trends in undergraduate medical education in readiness for the anticipated changes in medical environments. The detailed programs introduced in this study could be useful for medical educators in the development of curricula. Further research is required to integrate the educational trends into graduate and continuing medical education, and to investigate the status or effects of innovative educational programs in each medical school or environment.
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There have been few developments in formal educational opportunities about AI or ML for medical trainees at all levels.
“Despite the paradigm shift that AI may bring, there have been few developments in formal educational opportunities about AI or machine learning (ML) for medical trainees at all levels [3, 4].”
From Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study (2022) · cites this paper as [4]
Traditional roles of physicians, particularly those performing imaging-based diagnostics, are expected to change in some capacity as AI tools progress towards clinical implementation.
“While many of these technologies remain investigational, the traditional roles of physicians, particularly those who perform imaging-based diagnostics, are expected to change in some capacity as AI tools progress towards clinical implementation [3, 4].”
From Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study (2022) · cites this paper as [4]
Other key skills in medicine such as ethical aspects of decision making or humanization and empathy through doctor-patient interaction may become more important.
“Additionally, other key skills in medicine such as the ethical aspects of decision making or humanization and empathy through the doctor–patient interaction may become more important [3–5].”
From Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study (2022) · cites this paper as [4]
A lack of knowledge about AI and its uses in a clinical context will plausibly pose a barrier to future uptake and effective use among physicians.
“A lack of knowledge about AI and it’s uses in a clinical context will plausibly pose a barrier to future uptake and effective use among physicians [3, 4].”
From Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study (2022) · cites this paper as [4]
Lack of knowledge in AI among medical school faculty is the single most important hindrance to incorporating AI into the curriculum.
“Based on our results of the previous literature, we found that the lack of knowledge in AI among medical school faculty is the single most important hindrance in incorporating it among the curriculum.34,47,49,55”
From Educating Future Physicians in Artificial Intelligence (AI): An Integrative Review and Proposed Changes (2021) · cites this paper as [34]
Medical education has not kept pace with the remarkable breakthroughs made in AI.
“Despite increasing interest in this technology, medical education has not kept pace with the remarkable breakthroughs made in AI [12].”
From AI in medical education: medical student perception, curriculum recommendations and design suggestions (2023) · cites this paper as [12]
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- Authors
- Han, E.-R., Yeo, S., Kim, M.-J., Lee, Y.-H., Park, K.-H., & Roh, H.
- Affiliations
- Chonnam National University (KR)
- Kyungpook National University (KR)
- Kosin University (KR)
- Korea University (KR)
- Gachon University (KR)
- Inje University (KR)
- Corresponding author
- Roh, Hyerin
- Venue
- BMC Medical Education
- Published
- 2019-12
- Volume
- 19
- Issue
- 1
- Pages
- 460-460
- ISSN
- 1472-6920 (ISSN-L)
- PMC
- PMC6907217
- OpenAlex
- W2995872180
- Cited by
- 393
- References
- 62
- Citations by year
- 2026: 49 · 2025: 75 · 2024: 100 · 2023: 85 · 2022: 43 · 2021: 29 · 2020: 12
- FWCI
- 19.34
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Education (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Health Sciences › Health Professions › General Health Professions › Health and Medical Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- undergraduate medical education, medical curriculum development, artificial intelligence in healthcare, digital healthcare, longitudinal integrated clerkship, humanistic medicine, patient safety, student-led learning, active learning, community participation, diversity in medical education, future of medical education
- MeSH terms
- Self-Directed Learning as Topic, Artificial Intelligence, Curriculum, Education, Medical, Undergraduate, Humans, Technology
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Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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