Medical education aims to keep pace with modern technology. Now, clinicians and scholars in Yale’s Department of Anesthesiology are asking where AI systems might fit. With careful and safe integration, the team is exploring how AI could contribute to personalized anesthesiology training.
Supporting learning and simulation
The operating room can feel like a mystery for many medical students and trainees. This is especially true for those just starting their journey to become clinicians. Harnessing AI, Yale medical student Chanseo Lee worked with anesthesiology faculty to develop Anesthesia Playground, an interactive site with AI-enabled anesthesia simulation features.
“We came up with the idea of building an interactive anesthesia website. It includes common scenarios for learners. This helps them avoid seeing something for the first time in the operating room. They won’t have to wonder, ‘What’s going on?’” says Christopher Szabo, MD, associate professor of anesthesiology and collaborator on the site. “It can give trainees a bit of a leg up, so some scenarios won’t feel completely new to them. This is because most medical schools don’t require anesthesia training for medical students.”
Demystifying the operating room
Lee, who is in his fourth year of medical school, saw a need for more personalized training for healthcare professionals who want to work in an operating room long-term.
He says, “the operating room can be a black box for a lot of medical students. Even though anesthesiologists are open and willing to teach, curtains often hide them. This can make it feel like they are in a world students aren’t able to access.”
His passion for technology and web design inspired the site. This AI-powered intersection between medical care and computer science includes tutorials, clinical scenarios, and a dashboard for instructors.
“I first made Anesthesia Playground for medical students doing clerkships and sub-internships,” Lee says. “But it’s for anyone who is interested in anesthesia or surgical procedures. I do think it should be accessible for any medical student and above to learn and hopefully get something out of it.”
Much of the early anesthesiology experience for trainees depends on the cases occurring when they enter the operating room, intensive care unit, or other clinical setting. The cases in progress at that moment shape their early exposure, which is why training can vary from person to person.
Anesthesiology has many subspecialties, such as obstetric anesthesia, critical care medicine, head and neck anesthesia, and more. The platform can tailor simulations to each user’s unique learning journey. It can also offer quick access to scenarios for complex cases across a variety of subspecialties. This could help students choose which path to pursue.
“We could create scenarios that show five key things you need to know about cardiac anesthesia,” says Szabo. “Or we could create something that makes people interested in palliative care. That is the spark I hope will happen. I hope taking part will inspire more education, teaching, and learning.”
The importance of mentorship
While AI can strengthen educational practices, the team stresses that it complements, rather than replaces, face-to-face teaching. They emphasize that AI works best as an additional tool that can support educators and learners, while mentorship and judgment remain grounded in human supervision.
“AI can’t replace the mentoring relationship,” says Lee. “Mentors and mentees share a bond. It goes beyond just sharing information. Relying too much on technology carries risks. Medicine, fortunately, is not a practice you can do just by looking at screens–it’s something you learn and do with people.”
Mentorship is a key part of anesthesia training and is a cornerstone of medical education and continuous improvement. As the operating room is complex and fast-paced, trainees take different paths to become skilled clinicians.
Many of the field’s key skills develop through supervised, hands-on work. These skills include quick problem-solving, teamwork, and awareness, which do not develop on a screen.
“You need attendings, senior residents, and people with experience for mentorship and that nuanced art that we employ,” says Szabo. “But, the technology may provide a solid ground level so that those disparities you might see between different learners are smaller, and so all can get to a higher level of understanding in anesthesia.”
In addition to Lee and Szabo, the other Yale contributors to Anesthesia Playground are John Guzzi, MD; Viji Kurup, MD; Kevin Rooney, MD; Landon Crippes, MD; Manuel Cintron, MD; and Thomas Stovall, MD.