“If you want to build a ship, don’t drum up the men to gather wood, divide the work, and give orders. Instead, teach them to yearn for the vast and endless sea.”
Antoine de St. Exupery, French author and aviator
Introduction
It has been over 100 years since the initial Flexner report that was the beginning of the current medical education. This report, written in 1910, promulgated a more structured approach to a biomedical model of science-based medical education and training. Abraham Flexner, aneducator, collaborated with the members of the Hopkins Circle (William Welch, the dean of Johns Hopkins and William Osler, the chief of medicine are among members) in his report on medical education in the United States and Canada that led to its reform.
The current world has seen a Cambrian explosion of innovative technologies such as artificial intelligence, extended reality, digital twins, etc as well as disruptive paradigms such as transdisciplinary collaboration, biomedical entrepreneurship, and diversity principles, but the medical school curriculum has not kept pace with these exponential changes. There is a paucity of references on how the medical education should be adjusted to reflect the current portfolio of advanced technologies, and even less written on a coherent strategy or plan to reshape the present day curriculum, but most authors agree that a major change is necessary to enable future clinicians much better prepared for the imbroglio of healthcare ([1])([2]).
[1] Han ER, Yeo S, Kim MJ et al. Medical Education Trends for Future Physicians in the Era of Advanced Technology and Artificial Intelligence: An Integrative Review. BMC Med Educ 2019; 19:460-475.
[2] Wartman SA and Combs CD. Reimagining Medical Education in the Age of AI. AMA J Ethics 2019; 21(2): E146-152.
Current State of Medical Education: Widening Learning Gap
The Medical Education. A common hierarchical infrastructure has the office of medical education reporting to the vice dean of education and consulting with the curriculum committee as well as the department chairs. The vice dean of education reports directly to the dean.
The Typical Curriculum. Current curricula consist of a decades-old structure: two years of pre-clinical work followed by two more years of clinical education and training. The first two years encompasses courses like anatomy, physiology, histology, and pathology that focus on a myriad of organ systems while the latter two years have clinical clerkships and sub-internships in pediatrics, internal medicine, surgery, obstetrics/gynecology, etc. Part of the fourth year is usually reserved for electives, interviews, and time for preparing for the examinations.
Shortcomings of the Current Curriculum. First, the junior students spend much of their time in pre-clinical science courses while the senior students are occupied with clinical rotations. This arrangement precludes the possibility of students learning from real patients but instead promotes learning and memorizing from textbooks. In addition, there is usually very little interaction between students from different years for there is minimal if any mentoring between junior and senior students. Lastly, there is a myriad of “new motifs” (relevant topics and current themes) that are not adequately covered (or at all taught) in the current curriculum that places the present day medical school student in a very vulnerable position in the near future. Perhaps the most notable topics that are not routinely taught but should be are: biomedical entrepreneurship, diversity principles, social media, and artificial intelligence. For artificial intelligence, the two main challenges of artificial intelligence being taught in medical schools include: 1) limitations in the perceived usefulness of AI and 2) technical difficulties with the development of AI applications ([3]).
In short, the trajectory of learning in medical schools is relatively linear while the learning really needs to be more exponential like the aforementioned new motifs or emerging areas (see figure). This differential between the linear trajectory of our current medical education and the exponential trajectory of our clinicians educational needs creates a rapidly growing “learning gap”. There is an increased consensus that this learning gap should be decreased with a new educational strategy and a sense of urgency.
Future State of Medical Education: Innovative Transformation
It is perhaps ironic that the medical profession and its occupation with science after the Flexner report was not balanced with excellence in human aspects of clinical training. It is necessary to train the future clinician today with a much more robust portfolio of tools and knowledge while maintaining the human aspects of practice.
The following are ten innovations for the future of medical education to lead to an overall transformation (named MEd2030”):
Innovative Structure. The traditional structure generates utter boredom for the junior students while they are in the classroom and chronic fatigue for the senior students as they are in clinical rotations one after another. Perhaps one alternative arrangement is to have students from all four years divided to have alternating months of clinical rotations and learning sessions.
New Motifs. A myriad of relevant topics need to be included in future medical education as knowledge of these areas are essential for the present day clinician. These include: biomedical informatics, artificial intelligence, health entrepreneurship, virtual health, health systems, medical business, and professional leadership. These motifs are “blended” with the traditional classes.
Technology with Empathy. The future of medical education should possess a balance of the new technologies and human elements of empathy, justice, equity, and compassion. While the emerging technologies are important aspects of future medical education, a return to more human aspects of clinical medicine is more important than ever before.
Minimal Didactic Teaching. The content of the traditional courses as well as the new motifs are taught in the now common flipped classroom format where papers and videos are available for asynchronous learning prior to the class. The teaching and learning are all based on the premise that the students already know the material.
Case-Based Lessons. An emphasis can be placed on case-based lessons on an individual basis sothat the student can learn based on cases and observations from the clinical rotations. For example, the student can learn the histology as well as the pathophysiology of diabetes following a clinical rotation during which he/she followed a diabetic patient.
Project-Based Learning. Project-based group learning is set up so that learning is based on clinical experiences and observations of a student group. By having students from all four years working together on a clinical or health project, the projects can be very productive and insightful team experience.
Real-time Learning. By embedding more flexibility into the curriculum in the form of these newer dimensions, relevant and timely topics can be immediately included in the aforementioned case-based lessons and project-based learning. The current COVID-19 and its diagnosis and treatments can yield numerous lessons and projects.
Multi-Disciplinary Faculty. Rather than a single faculty member, virtually every topic rendered more interesting when multiple faculty members are involved in the teaching of a topic or have an office hour together. For example, a discussion session on diabetes from an endocrinologist, a physiologist, a pediatrician, and an emergency room physician would be multi-faceted.
Transprofessional Colloboration. In addition to a multi-disciplinary clinical faculty, it would be ideal to have several professions outside of the clinical domain to contribute to the learning experience.
For instance, a learning session could be focused on redesign of the clinic room with participation from architects, innovators, family members, etc.
Gaming for Progress. The curriculum is designed for continuous learning so a gaming approach can be set up to encourage continual assessment and self-motivation. The students can score points by being able to answer the self-assessment questions, and machine learning can direct questions for relatively weak areas for the student.
[1] Han ER, Yeo S, Kim MJ et al. Medical Education Trends for Future Physicians in the Era of Advanced Technology and Artificial Intelligence: An Integrative Review. BMC Med Educ 2019; 19:460-475.
[2] Wartman SA and Combs CD. Reimagining Medical Education in the Age of AI. AMA J Ethics 2019; 21(2): E146-152.
[3] Chan KS and Zary N. Applications and Challenges of Implementing Artificial Intelligence in Medical Education: Integrative Review. JIMR Med Ed 2019; 5(1): e13930.
