Artificial intelligence is at the center of many emerging technologies today, and perhaps nowhere are the implications more meaningful than in healthcare.
So where is AI making an impact in healthcare today? What will the future bring, and how should healthcare providers and technologists get ready?
On the Season 4 premiere of GeekWire’s Health Tech Podcast, we address all of those questions with three guests: Linda Hand, CEO of Cardinal Analytx Solutions, a venture-backed company that uses predictive technology to identify people at high risk of declining health, and match them with interventions; Colt Courtright, who leads Corporate Data & Analytics at Premera Blue Cross; and Dr. David Rhew, Microsoft’s new chief medical officer and vice president of healthcare.
This episode was recorded on location at the dotBlue conference in Seattle, hosted by the returning sponsor of the show, Premera Blue Cross.
Listen above or subscribe to the GeekWire Health Tech Podcast in your favorite podcast app, and keep reading for edited highlights.
On the current state of AI in healthcare
Linda Hand, CEO, Cardinal Analytx: When I look at AI in healthcare, I see most examples in either the science of healthcare or in the practice of healthcare. I feel like it’s an emerging business for us to expand that to the insurer side of the house. Machine learning can find patterns that a human cannot, when it’s not prescribed in terms of the outcome that you’re looking for, and that’s a very powerful thing. And that’s where it can be better than a doctor.
The ability to take data and leverage that to move from a reactive care model, reactive intervention, to a proactive intervention is the promise of that because the predictions are up to 12 months in advance. And so being able to understand that someone will rise in cost eight months out is a very different opportunity for a conversation than, “Hey, I see you’re in the hospital.”
Colt Courtright, Premera Blue Cross: The healthcare industry represents $3.5 trillion a year, and annual spend is 18 percent of GDP. It’s expected to support 300 million-plus Americans. And so while some of these technological achievements are possible, you can prove out that diagnostics are in fact more accurate in some cases using machine learning versus a human being.
AI today, and over the next couple of years, is going to be more like the technology of yesterday. Think of it like a stethoscope. A stethoscope magnifies the hearing of the human doctor. It enables them to diagnose more effectively. The AI applications that I see being adopted near-term really have to do with being able to discern patterns in data, patterns in past histories that a human doctor could, if given enough time, discern on their own.
David Rhew, Microsoft: Where we’re seeing the trends today are around the ability for us to start pulling in data that are cleaner, and more interoperable, that allow us to be able to then combine data sets that we couldn’t look at before. We’ve been limited in the fact that we had very dirty data sets that didn’t allow us to be able to really understand beyond what was the scope of what was currently available.
Now we have an ability to have much cleaner data sets combined with others real time. And that’s a really exciting opportunity because now we can think about how can we combine claims data with electronic health record data, with lifestyle data, with social determinants of health, and try to understand how it matches to an individual from their genomics and other types of personalizations. And that’s where the real opportunity lies.
AI’s impact on healthcare costs
Courtright: Costs are impacted by a great number of things, new drug discoveries, new medical treatments, there’s very legitimate reasons for costs to go up. However, the pricing of risks, the setting of premiums is set with the level of information we know today. And we know that machine learning creates a greater predictive accuracy in understanding future financial risk.
Rhew: There’s great opportunity for us to be able to figure out how AI will translate to lower costs. We just have to validate this on a larger scale and once we’re able to do that, then that will hopefully translate to lower costs across the board.
What AI means for doctors and patients
Hand: I think the opportunity is really putting the human back in healthcare. Providing insights that one can’t see even if they had enough time, putting it in front of them so that they can be very efficient in that interchange with a patient, with a member. Wherever that engagement is, I think, is a huge opportunity. You enable the human in the doctor, allow them to leverage all the insights to be the trusted adviser. People go to their primary care physician or a specialist for advice on a particular thing. Right now you feel you have to bring all the information and educate them. AI should be able to give all of that to that person so that they can actually advise and have a conversation about what is the best course of action.
Courtright: When you go to an exam room, what’s your typical view? It’s the back of your physician’s head. It’s because they are looking at their keyboard as much as they’re looking at you. And they’re doing that because of the administrative burden and the documentation requirements of medical care today. And the aggregation of that is such that doctors, clinically trained professionals, are only able to spend half of their time delivering medical care. And so when I think about the possibilities of AI over the next three to five years, I think about the opportunity to automate the basic tasks that are taking away the physicians’ attention when they deliver medical care.
Rhew: We’re talking a lot about what happens in a hospital and in a clinic. But much of healthcare is actually moving outside. It’s moving to the home, it’s moving to retail clinics. And so the user experience will be very different in those scenarios. In many cases, they will not have a doctor, a nurse, a clinical person to be able to help oversee the care, which means that the technology, the AI is going to be even more important because it’s going to allow individuals to feel confident that they can actually manage their care outside of the care of what we traditionally view as a hospital, a clinic.
Implications for data and privacy
Hand: I think we have a really inconvenient relationship with privacy. Everybody wants to keep their stuff private, but everybody wants the benefit of having the insights from using everybody else’s data. There’s just a huge disconnect there.
Rhew: It’s very important to be proactive on this because once the information moves outside of the medical record into the individual’s phone, it’s no longer under the context or umbrella of HIPAA. They can do what they want with that. Now we’re talking about the Wild West in terms of how data can be used and moved around. We have to really start thinking proactively about how do we put those safeguards in without being too restrictive at the same point.
Courtright: I think we are in an inflection point where we are being forced to grapple with these kinds of considerations. The Privacy and Security Standards that have governed what I would call the traditional actors in healthcare — the health plans and the providers — will remain the same. The shift is really to say the member owns their medical record. The member should be able to control that, and use it, place it where they would like it.
Future of AI in healthcare
Rhew: We will see changes in the way that people use these tools. It won’t be the same way that we practice medicine. There’ll probably be new specialties focused just on digital tools with AI. Individuals focusing more on populations rather than just on individuals themselves, or patients themselves. We will see changes. It may require that some individuals have to rethink what they used to do, but that comes along with the great benefits to the patients and the populations, the reduce costs, and improved quality.
Hand: I’m extremely optimistic. That’s why I took this job. But I will say that if we only focus on the business practice of this AI enablement and operational efficiencies, we have the ability to misuse AI to do bad things faster and at scale. AI can be used to counter that, so I hope we’re smart enough to do that, but there is a danger of that, of only focusing on one. I’d like to see us in the industry balance the science, and the practice, and the business operations to make sure that we’re looking at the right incentives across that continuum.
Courtright: I’m definitely an optimist, from the perspective of the patient, the physician, and the holders of financial risk. I think there’s a tremendous amount of opportunity in AI for those three actors, which are the dominant actors in our healthcare system. This is a target-rich environment. However you examine healthcare performance today, whether it’s preventive care, a third of it is not provided; it’s recommended chronic care, a third of it is not provided; whether it’s medical errors, and where that ranks in preventable deaths in the United States, and the cost; there’s a lot of opportunity for AI.
