Jordan Rosenfeld

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Artificial intelligence (AI) is no longer just the future of medicine—it is already here, and over time it will transform nearly every area of medical practice, according to experts.

AI involves machine learning, where computers get smarter at seeking patterns or connections the more data is input; natural language processing, where computers learn to read and analyze unstructured clinical notes or patient reports; robotic process automation, such as chat bots; diagnostic capabilities such as IBM’s Watson; and even more processes that help with patient adherence and administrative tasks.

“AI is impacting health care at every level, from the provider to the payer to pharma,” according to Dan Riskin, MD, CEO and founder of Verantos, a health care data company in Palo Alto, California, that uses AI to sort through real world evidence.

“AI is utilized in a multitude of ways depending on the health care ecosystem,” added Athena Robinson, PhD, chief clinical officer at Woebot Labs, a digital therapeutics company in San Francisco. “Some folks think of augmented systems, such as transactional bots that you call to schedule an appointment.”

For providers, AI can help with tasks ranging from clinical decision support to disease management, Riskin says. However, it might be especially useful to physicians for understanding population health.

“If you want to identify a group where you are not meeting the standard of care or need to do better, and you find you are having trouble identifying [these patients] with common software, you might do better with more innovative, AI-based software,” Riskin said.

Or from a patient-facing approach, AI can assist in disease management for patients with adherence problems.

Robinson agreed that AI will be especially helpful in extending the clinical relationship outside the office.

Artificial intelligence will never replace physicians or other providers, but it does have undeniable strengths with which the human brain simply can’t compete.

“The main strength of AI in general, not only pertaining to medicine, is its ability to digest large amounts of data to detect patterns and connections between the data points that a human wouldn’t necessarily be very good at doing,” said Theodore Zanos, PhD, head of the Neural and Data Science Lab and an assistant professor at the Feinstein Institutes for Medical Research at Northwell Health in Manhasset, New York.

AI can also make connections much more quickly than a human doctor, reading and interpreting hundreds of thousands of pages of medical records—and it’s only going to get better at it. This function has been a boon during the COVID-19 pandemic.

For those who are concerned that patients might not trust AI, Riskin says it’s not an either/or situation.

AI supports precision/personalized medicine

At the moment there is no unifying model that can predict all diseases and conditions. But “there are a lot of specific (AI-based) models for specific diseases and conditions and time horizons and use cases,” Zanos says.

However, because of AI’s computing power, it lends a significant hand to personalized medicine now and into the future. Unfortunately, there are no ratings for these models yet, so doctors have to apply trial and error to see which ones work best, and they will need to practice using them.

Another factor to consider when adopting AI-based interfaces, programs and apps, Riskin said, is that younger patients have come to expect more contactless health care experiences.

Of course, no practice is going to simply shift everything to AI-based programs overnight, Zanos explained.

“The stakes are just a lot higher in health care. In other industries, it is fine if you suggest the wrong product to a user or the wrong movie on Netflix — it’s not going to break your company,” Zanos added. “But you can’t just release a tool in the wild in health care. It needs to go through careful validation, approval and regulatory approval from the FDA, so the cycle is longer and it slows down the progress a bit in the field.”

Once physicians have an idea of how they’d like to use AI in their practice, there will be some tough decisions to make, Riskin noted. He suggests sticking with legacy vendors for things such as EHRs and considering more innovative AI-based startups for things such as revenue cycle management or less patient-centric tasks.

Zanos reminds physicians that AI is an emerging field, but it is one that’s here to stay.

“There will be growing pains,” he concluded. “There is value in understanding how these technologies are created. Physicians need all the exposure and practice they can get.”

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