The way we practice medicine today is broken. We prioritize the business and treat the patient as nothing more than a cog in our great machine. According to today’s guest, ” we have an emotional breakdown, with disenchanted patients largely disconnected from burned-out, depressed doctors.” Dr. Eric Topol calls this epidemic “shallow medicine”. It’s driven by runaway healthcare costs and an insatiable drive for increased efficiency and profits, and unfortunately, is largely the way we deliver healthcare today. Because of this, Topol says, “patients exist in a world of insufficient data, insufficient time, insufficient context, and insufficient presence.”

But, Dr. Topol is optimistic. He believes that Artificial Intelligence (AI), while still finding its place in medicine, and still mostly unproven in real-world clinical situations, can create the space we need to change course.

In his new book, Deep Medicine, Dr. Topol makes an optimistic, but realistic argument for how artificial intelligence can make healthcare human again. He tells us that it’s early, and this is definitely a race with no finish line, but we’ve seen great progress so far and there’s plenty of evidence that the tools will have a profound impact on every part of healthcare. Dr. Topol believes that we will get there, and that AI will create new efficiencies and workflows that can be used to either make things really good, or really bad. He tells us that “the increased efficiency and workflow could either be used to squeeze clinicians more, or the gift of time could be turned back to patients – to use the future to bring back the past.”

On this episode, Dr. Topol explains his thesis and we explore the potential paths from where we are now, to where we might go. Dr. Topol makes a compelling case for breaking that inertia and putting the priority back on the patient.

The Path to Deep Medicine

The path to Deep Medicine is by no means a slam dunk, but there is a path if choose to take it. There are obvious business cases for applying AI to what Dr. Topol calls “Doctors with Patterns”. Algorithms can be trained via machine learning to see things that humans cannot and will never see. This isn’t an indictment of our clinicians and their immense hard-earned skills, but rather an admission of our human limitations and a willingness to seek out tools to move past them. Topol believes the trend will start in radiology, ophthalmology, and pathology, where machines can read images far faster, and in many cases more accurately than humans can.

The application of AI will ultimately expand to aid all clinicians. A simple, but profound example will be “liberation from the keyboard”. Voice recognition and natural language processing will allow doctors to maintain eye contact and physical touch with their patients as their conversation is captured in real-time and converted into medical charts automatically. Additionally, according to Topol, AI will level the medical knowledge landscape and put a new premium on doctors with emotional intelligence. Topol says this is the opportunity to “restore the precious and time-honored connection and trust – the human touch – between patients and doctors.

Breaking the status quo

Today we blindly apply diagnostics and technology to the “average patient”, who Topol says “does not exist”. We use surrogate measures with flimsy evidence because that’s the best we can do with our current knowledge, data, and limitations. This leads to over-testing, false positives, and a missed opportunity to treat the individual patient based on their very specific situation. The rise of AI will give clinicians a “new partner” to help them do just that.

Data Challenges

One of our biggest challenges will be to gather the data necessary to enable the new algorithms. Topol notes, and I emphatically agree, that the difficulty in assembly and aggregation of the data has been underestimated by all tech companies getting involved in healthcare. I’d expand that to say that very few people in general, whether inside or outside of healthcare, fully appreciate the challenges we face on this front. This lack of appreciation is the primary reason why we’re still having a national conversation on lack of interoperability and will be one of the most important obstacles to overcome if we’re ever going to realize the true potential of AI in medicine (more on my position here).

Man Plus Machine

Topol does not believe that clinicians will be replaced by AI. On the contrary, he sees the future of healthcare as one where clinicians welcome the new algorithms as valuable partners in delivering care. And it’s not just about doing what we do now more quickly and efficiently, but it will enable us to do new things that just aren’t possible today. It will enable PCPs to more adequately address issues that require a specialist today (i.e. Dermatology) and it will enable non-clinicians to take on more of the grunt work of medicine. This, rather than replacing clinicians, will free them up to deal with the more important issues. It will enable them to spend more time on addressing the critical issues of their patients, and in pondering the “why” behind what they do, rather than the “how”.

Deep Liabilities and Fear

There are well-founded concerns that AI can also lead to bad things. Insurance companies using it to deny coverage or raise premiums ranks high on that list. And with the deep phenotyping that these algorithms will require, there will be a very rich set of data on every patient and that leads to obvious concerns around privacy and security. Further, a “bad” algorithm can quickly scale physical harm to patients or make inequities worse.

Additionally, there is the issue that we can’t yet explain how many of the algorithms work. How will regulators deal with that uncertainty? And how will patients and doctors feel about applying algorithms that they can’t explain to make critical medical decisions?

What we have here is a bit of a marketing problem (as is often the case). First, we have this expectation that what doctors do today is not “black box”. That is just flat out wrong, but we are more willing to accept a human black box than an artificial one. Interestingly, Topol makes the point that we may someday be able to explain the algorithms better than we’ll ever be able to explain why humans do what they do.

In making this assessment, we ignore the fact that every doctor is prone to human biases and the limitations of their own experience. Topol breaks this down and skillfully applies many of the ideas from Daniel Kahneman’s Thinking Fast and Slow to explain where this occurs. Topol points out that we’ve been doing similar things for a long time, but in the old days we simply labeled it “computer-aided”, rather than AI. Sure, AI sounds sexier for marketers of AI tools, but maybe going back to that “computer-aided” label would prevent some of the fear. Or we could try Topol’s term: “A more human medicine enabled by machine support”.

Finding Deep Empathy

Topol makes a compelling case for how we can use AI to return humanity to medicine, and I hope it plays out that way. To me, the big question is this: How will we override current inertia so that we don’t use the new efficiencies to increase patient throughput and drive revenue even higher? How can we make the case that deep empathy and patient-centeredness are not only good for doctors, and patients, but the business too? If we can find that alignment, then, with time, I think Dr. Topol’s vision will become a reality.

This is a well-researched, well-written book, and I got tremendous value from reading it. I strongly recommend it to anyone working in healthcare innovation, AI, or who is simply interested in finding new ways for our healthcare system to move forward. ~ Don Lee



About Dr. Eric Topol

Eric Topol, MD, is Executive Vice President and Professor of Molecular Medicine at Scripps Research, and the Director and Founder of the Scripps Translational Institute Department of Molecular Medicine.

Voted as the #1 Most Influential Physician Leader in the United States in 2012 in a national poll conducted by Modern Healthcare, Dr. Topol studies technologies that are changing the future of medicine.

A longtime practicing cardiologist, he was widely credited for leading the Cleveland Clinic to become the #1 center for heart care. While there, he also started a new medical school, led many worldwide clinical trials to advance care for patients with heart disease, and spearheaded the discovery of multiple genes that increase susceptibility for heart attacks.

Since 2006, he has led the flagship NIH grant-supported Scripps Translational Science Institute in La Jolla, California. He has published more than 1,100 peer-reviewed articles, has over 230,000 citations, was elected to the National Academy of Medicine, and was named in GQ Magazine as one of the Rock Stars of Science. From 2017-19, he was commissioned by the UK government to lead a team assessing technology and planning the future of the National Health Service. He is also the Editor-in-Chief of Medscape. His previous books The Creative Destruction of Medicine and The Patient Will See You Now were both published by Basic Books.

He lives in La Jolla with his family.

(Photo © John Arispizabal)

Books by Dr. Eric Topol:


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