Ayden Jacob

Creating the AI Physician: Administrative Support

This is the third part of a four-part series, examining the ways in which we can architect “The AI Physician” by exploring the pieces involved in bringing this idea to fruition. As the pairing of man and machine has proven to result in noteworthy positive clinical impacts, what steps ought to be taken to educate physicians about AI for the purpose of improving patient outcomes? Here, we dive into the necessity for administrative support:

In an article discussing machine learning in the world of medicine, Dr. Brian Hodges and colleagues state, “to train physicians who are resilient in the face of potential labor market disruptions caused by emerging technologies, medical education must teach and nurture unique human abilities that give physicians a comparative advantage over computers.” 

We are at the dawn of understanding how to implement medical education in this field and can learn quite a bit from pilot studies conducted hitherto. As reported by Debenedectis et al., upper level radiology residents at the University of Massachusetts (UMass) were exposed to training alongside our AI algorithms in an effort to understand the impact of AI on radiology resident training. As one of the first in the country, the UMass offers its residents exposure to AI modules, learning sessions, and guest lecturers, headed by their inhouse AI Steering Committee. Over 90% of residents agreed that AI decision support systems should be part of the curriculum. A quarter of residents felt that AI was very helpful, while 66.7% of residents reported it was helpful towards radiology learning and workflow improvements. Interestingly, the study reported that the majority of residents found the AI tool most helpful in emergency radiology and neuroradiology, both settings which require rapid turnaround times and more independence.

The residency program at the UMass clearly demonstrated a novel methodology by which residency physicians can become adept at utilizing and understanding AI technologies during their training, thereby empowering them to be leaders in their respective fields as they embark on the next phase of their careers in healthcare. This is important in that it creates a precedent of positively implementing an educational framework for integrating AI training into the pedagogy of radiology residency.

Ayden Jacob