Your surgeon may have finished training with less time in the operating room than surgeons once had. Danny Goel, an orthopedic surgeon in Vancouver, says the apprenticeship model never changed while duty hours, efficiency pressure, and outpatient surgery reshaped everything around it. He explains why case counts and exams can't tell us who is ready to operate alone, what patients should ask, and how immersive simulation could close the gap.
⏱️ Chapters:
0:00 Introduction
0:43 Why the old apprenticeship model is breaking
2:36 The surgical shortage no one counts
3:57 Where duty hours quietly take OR time
5:07 Why cadaver labs and simulators fall short
6:51 Do less-ready surgeons mean worse outcomes?
9:07 Two questions to ask your surgeon
10:19 Why "you're ready" has been a gut call
11:52 Practicing a shoulder replacement at home
13:36 VR so real surgeons dropped the controller
15:17 Why residents log thousands of short sessions
17:11 A personal tutor for every procedure
19:02 Take home messages
About this episode:
Danny Goel is an orthopedic surgeon in Vancouver who specializes in the shoulder and has spent his career thinking about how surgeons are trained. He argues that the apprenticeship model is unchanged, but the system around residents is not: fewer duty hours, efficient operating rooms, and a shift to ambulatory surgical centers. Because rounding, call, notes, and emergency consults still fill a resident's hours, time in the operating room is what shrinks. Cadaver labs are scarce and costly, single-purpose simulators sit in sim labs, and industry courses do not scale. New surgeons now add fellowship years, and his article cites a 2026 American College of Surgeons bulletin where senior surgeons judged over half of younger colleagues unprepared. For patients, his advice is to ask a surgeon how many times they have done the procedure and what bad outcomes they have personally had. As CEO and co-founder of PrecisionOS, he describes a phone-based AI mentor paired with a VR operating room where residents can safely make mistakes. He closes with three lessons: exposure is not competence, education does not end with training, and AI should show us what we don't know.
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