Kaiser Permanente, Mayo Clinic Execs Detail AI Approaches

Lee said he likes to refer to AI as augmented intelligence rather than artificial intelligence, because he thinks of this technology as being a set of tools that assist and augments a physician's ability to care for patients. “It's a lot like other ways that we support physicians with clinical decision support tools; AI just happens to be more advanced and more complex than other types of decision support,” he said. Lee described a number of ways they are using AI at Kaiser Permanente, including use cases related to natural language processing, computer vision, and predictive analytics. And of course, this helps our patients get timely responses to their health concerns,” he said. We know that diabetes is a leading cause of blindness, and considering the number of diabetic patients we have, using a tool that helps us determine whether a patient does or doesn't have diabetic retinopathy can allow us identify retinopathy sooner, which gives us the best chance to prevent someone from going blind.”

Finally, in analytics, Kaiser Permanente has been developing a number of algorithms to help it stratify COVID-positive patients so that they can better anticipate which patients are at highest risk for developing more severe symptoms. “We also have our advanced alert monitoring program, which helps us keep an eye on our hospitalized patients in real time, and predicts which patients are at risk for deteriorating and may require being transferred to the ICU,” Lee explained. With all of these examples, AI is augmenting the care of our physicians and our teams and when combined with clinical judgment, we create the potential for significant improvement in outcomes for our patients as well as efficiencies for our clinicians and our health system as a whole.” That involves EHR data, imaging, telemetry, and patient-reported outcomes data, organized longitudinally and then made available to investigators using what he calls an AI factory. We actually took a couple of years to cleanse the data,” he said. And we de-identified it so there would not be a lot of tricky IRB human subjects or privacy issues around the use of the data, but it is still stored in a secure cloud container with tools on top of it for all of our clinicians and all of our investigators at Mayo Clinic to create models.” “We've also established a variety of collaborations nationally and internationally to test the models to make sure they're fair, unbiased and useful for purpose.”