UCLA Health’s Post

Transcript

We have a very large database in our electronic health record of de identified data and we can look at that data. And so any patient going to surgery, we can look at some of their vital signs or predictive elements and run that through algorithms and say based on these and based on everything that we know in these algorithms, what is the risk of the patient having a complication from anesthesia or post surgical and be better prepared. For that, those patients then automatically get a pre anesthesia visit by one of our experienced anesthesiologists in things like imaging, right? We can have AI tools that also look at the CT scan or the PET scan and just put little highlights on it where they want the doctor to take a further and closer look. Wow. So that we don't miss anything. Other things that we're doing, we're doing some pilots now in our clinics with ambient listening. So instead of the doctor having to spend time. Writing or charting on the computer, he can be talking to the patient and family, listening to them, and the ambient listening is recording everything that he's saying so that at the end of the visit he can just look at that and really make sure that everything was transcribed accordingly. So lots of great ideas and when you think about the future and the tools that can come forward with AI, I think it's going to dramatically not only improve quality and safety, but also the patient experience.