Expert: AI benefits for patients will also help reduce pressure on providers

Currently, physicians are burned out and patient experience is suboptimal, says one longtime stakeholder, but artificial intelligence holds the potential to help fix all of that.
Jeff Rowe

"If we exploit machines' unique strengths to foster an improved bond between humans, we’ll have found a vital remedy for what profoundly ails our medicine today.”

So said Dr. Eric Topol – cardiologist, geneticist and digital health pioneer – in a recent interview with Healthcare IT News.

The author of a new book, Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again, Topol argues that if properly and humanely deployed, AI and and machine learning have to potential to restore efficiency to a wide array of burdensome healthcare processes, freeing up physicians to treat their patients in the way they deserve. 

"The path won't be easy,” he observed, “and the end is a long way off. But with the right guard rails, medicine can get there."

Much of what Topol argues can be summed up by the distinction between what he calls “shallow medicine” and “deep medicine.”

The former “is rife with problems such as lack of time. So there's very little human contact. And in the minutes when it occurs, it's compromised by keyboard and screen and minimal, if any, eye contact. So it's totally depersonalized and that's a big problem.”

Moreover, Topol says shallow medicine is leading to burnout, clinical depression and even a high number of suicides among physicians. “And then even further disillusionment: You have patients who feel that they're not being cared for because there's so very little time – less of a bond, and the sense of presence and trust and that whole precious relationship that has deteriorated.”

With that physician pressure in mind, Topol points out that AI has great potential for use by patients themselves, which would help providers manager their workload.  

“We’ve already had smartwatches with heart rhythm detection out there with a deep learning algorithm, FDA-approved for consumers,” he noted. “And there's going to be a lot more of that. If we have people diagnosing their skin lesions or their child's ear infections and all these other reasons for going to a doctor, that's going to be huge. That's a big part of healthcare: the routine, not-serious but important things that need accurate, rapid, inexpensive diagnosis.”

Over the long run, Topol said, “the biggest thing of all is remote monitoring and getting rid of hospital rooms. And there, the opportunity is extraordinary. Because obviously the main cost in healthcare is personnel. And if you don't have hospital rooms, you have a whole lot less personnel. So setting up surveillance centers with remote monitoring – which can be exquisite and very inexpensive with the right algorithms, when it's validated – would be the biggest single way to improve things for patients, because they're in the comfort of their own home. They're not subject to the risk of nosocomial infections. That would be very well appreciated by patients if it was proven to be safe and effective.”