Farzad Mostashari, MD, the former national coordinator for health information technology at the Department of Health and Human Services, warns that the prodigious amounts of data churned from machine learning algorithms are only as good as the data that goes in. For AI to work, Mostashari says the algorithms must be given specific tasks that rely upon accurate data. "You have to be able to set up the problem really well and clean the data in such a way that it most neatly answers the question that you are trying to answer," he says.
"The more you turn over the wheel, as it were, to an autonomous driver, the more important it is to tell the driver clearly where you're going, and what the question is you want answered, and for that machine to have really clear maps and data about the world," says Mostashari, who is the founding CEO of Aledade, Inc., which operates ACOs in 16 states.
"One of the challenges for healthcare is to be careful not to just blindly throw these methods at problems without having done that prework," he says. "It's tempting—and I have seen this for less-trained people who don't really understand the healthcare context—to find a bunch of data somewhere and throw the machine at it. And then what? Then you get some answers, but you have no idea if there was some aberration in the data or how you defined your outcomes that led you to that false conclusion, and no way of really interrogating the black box to say ‘Why did you come up with this answer?' "
Clinicians don't want to be given a specific list of recommendations or a care regimen with no context, Mostashari says; they want to know why.
"Don't just tell me that this patient probably has this diagnosis. I also have a processor. It is called a brain, and I also want to process and learn why you think this patient is high risk," he says. "So there is a need, I believe, in healthcare where you are not asking the AI to just do it—just be an autonomous car and take me there. We want humans and machines to be greater than either machine or human alone. In those situations, the human and the machine have to be able to understand and trust one another. It requires more transparency than some of the traditional AI methods."
John Commins is a content specialist and online news editor for HealthLeaders, a Simplify Compliance brand.