Conversations With Kohli | Medical Education in 2018: Is This Progress?

Over coffee with my 24-year-old cousin in a boutique coffee shop, I was introduced to today’s style of medical education. She’s a second-year medical student who’s just finishing her preclinical education and starting her clinical rotations. “How are the hours… brutal?” I nearly aspirated my coffee when she responded with “No, it’s actually not too bad – easier than college!” I learned that in her first two years of preclinical coursework, she attended only a handful of classes in person — under 10! Instead, she stayed home most mornings, drinking coffee and watching lectures online at double speed (in other words, in half the time!). All lectures must be recorded and posted online and most students watch remotely. Only a limited few attend class in person.

My shock grew as she told me about her open-book exams, where students are now tested on their ability to access the information in a timely manner, rather than reciting it from memory. But what left me reeling the most was this: she had only two overnight calls during her first clinical rotation, which was surgery! Gone are the good old “Massachusetts General-style” surgical rotation schedule of 24 on and 24 off and the eight to 10 hours of daily didactic lectures I recall from my days at Harvard Medical School.

I was perplexed and confused after our conversation. How had the model of medical education evolved so dramatically away from classroom learning in just the few years since I was in training? Has technology allowed us to make so much progress that the traditional memorization model of medical education is no longer necessary? Is peer-to-peer interaction now mostly conducted through chat rooms and online groups rather than face-to-face? And does this evolution reflect serious progress or will these future doctors be ill-prepared to care for complex and critically ill patients in high-stress situations with conflicting data because their skill set is limited to “looking stuff up”?

I dissected our conversation piece-by-piece. First, watching lectures at home at double speed. Her justification is that in the same amount of time required for the in-person lecture, she can watch once “for an overview” and a second time “for consolidation of knowledge.” This makes sense and I wonder why don’t we all do this. Yet, several key things seem lost in this approach: bouncing ideas and complex cases off fellow students, asking the professor questions in person and even the simple things like hanging out after anatomy class to review together the muscles of the leg. Importantly, these interactions also create our lifetime connections with colleagues and mentors. For today’s students interacting with their laptops rather than each other, will they have these lifelong connections that we rely on for professional support and that also enrich and enliven our work life? Did we have it right or is this a more efficient way to learn?

With the advent of the internet, education and the way we learn has dramatically evolved. Education platforms such as the Khan Academy (founded by my friend and MIT college classmate Salman Khan) has revolutionized the way we begin learning and processing information from a very young age. A definite shift has occurred to learning outside the classroom in all disciplines. MIT and other higher learning institutions now participate in Open CourseWare, with education materials accessible on a public platform. The walls of the hallowed ivory towers have been removed and the education playing field has been leveled. Everyone with internet access now has access to an ivory tower education. Clearly, this is progress.

But, does this also apply to medical education? Can we rely on an app to run a code blue if a doctor doesn’t have the algorithm memorized? Is this a step forward or back? I wonder if a doctor is still a doctor when their training is teaching them how to access information real-time to treat the patient, rather than knowing it and instinctively using that knowledge real-time. In my opinion, no matter how easily technology can warn us about the interaction between amiodarone and warfarin, there are still some fundamental topics around physiology, pathology and pharmacology that every doctor must commit to memory. And, in complex clinical situations with conflicting clinical data, a fundamental understanding of disease processes is crucial to making decisions that are not always clear cut.

I recognize the general trend in our society has shifted away from the individual and towards devices. How many phone numbers, addresses or directions can we recite from memory nowadays? So, it should come as no surprise there is a startup company working on a “smart” personal assistant for doctors, which can help with everything from drug-drug interactions to a differential diagnosis for cough and fever.

There is no doubt that the way we learn and interact with new information has changed. Yet, I’m still struggling with whether it will make the next generation of physicians more efficient, better doctors or whether it has fundamentally weakened our ability to interact with our peers and mentors and to synthesize and apply critical thinking to situations that aren’t always available on Google or Alexa.

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What are the trade-offs associated with evolving models of medical education? Is there a happy medium? Can professional societies like the ACC help?

Share your thoughts on Twitter using #CardiologyMag and #ConvosWithKohli. Tag @ACCinTouch.


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Payal Kohli, MD, FACC, practices at the Heart Institute of Colorado in Denver, where she treats a variety of cardiovascular diseases. She is also the lead physician of the Women’s Heart Center.

Clinical Topics: Anticoagulation Management, Arrhythmias and Clinical EP, SCD/Ventricular Arrhythmias, Sleep Apnea

Keywords: ACC Publications, Cardiology Magazine, Schools, Medical, Students, Medical, Amiodarone, Warfarin, Mentors, Friends, Critical Illness, Diagnosis, Differential, Learning, Education, Medical, Memory, Attitude, Cardiopulmonary Resuscitation, Drug Interactions, Algorithms


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