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Artificial Intelligence: The Hope Beyond the Hype

By John Commins  
   August 29, 2017

Dip your toe or dive in?

While there is potential for what AI will do for healthcare delivery, and how soon, most experts warn against a two-footed leap into the new technology.

"Anyone who tells you that's the way to go is trying to sell you something you don't need to buy," Harvard's Kohane says. "You want to test, experiment, but you don't say, ‘It's going to work on the first time around so I want to implement a whole system.' That is super high risk and often a failure. Starting small is definitely the best advice."

Anil Jain, MD, a part-time internist with Cleveland Clinic, and vice president/CMO of IBM Watson Health, says a Big Bang implementation of AI likely will not work for most healthcare providers. "With things like AI, you want to do it in phases, and with pilots where those who would benefit the most and those who are going to be able to give you an honest assessment of what is good and what is bad and what is working and what is not are able to do that," Jain says. 

"I would start by looking at some of those products that are on the market today, where I can help my oncologist or my primary care doctors do a better job immediately by looking at the analytics and cognitive insights that can be brought in," he says. "Either you wait for the broader EHR market to deliver something meaningful, or you get into these pilots and procure these solutions that do these things, knowing that as the solution evolves, you will too. The nice thing about cloud-based solutions is that as these solutions get enhanced, you are not having to reinstall things and the training cycle is not going to be significant."

Kohane says a good place to begin the clinical AI journey would be around image interpretation, analysis, and diagnoses in oncology, pathology, and ophthalmology, which have undergone rapid improvement over the past five years, and which he believes will create disruptive change within the next two or three years. 

"This really unexpectedly strong performance in image recognition is only going to improve the productivity of doctors," Kohane says. "I don't think ophthalmologists would mind if they had to spend less time screening retinas and spend more time productively engaged in the operating room or with a patient. If I am a surgeon and I want to have a fast, high-quality read on an x-ray of a patient who I am seeing in the operating room right now, maybe I don't need to have a radiologist read that anymore, or wait for the pathologist to read it. They can run it through a program."

John Commins is a content specialist and online news editor for HealthLeaders, a Simplify Compliance brand.

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