Can AI Reduce Medical Errors?

Are medical errors still one of healthcare’s biggest failures? 

In this clip from our episode “One Giant Leap for Healthcare AI”, host John Driscoll speaks with Dr. Robert Wachter, Author of A Giant Leap, about how AI could help reduce diagnostic mistakes at scale

Listen to the full episode here

🎙️⚕️ABOUT ROBERT WACHTER
Robert Wachter, MD is Professor and Chair of the Department of Medicine at the University of California, San Francisco (UCSF). Author of 300 articles and 6 books, he coined the term “hospitalist,” the fastest-growing medical specialty in U.S. history. He is past-president of the Society of Hospital Medicine, past-chair of the American Board of Internal Medicine, and an elected member of the National Academy of Medicine. In 2004, he received the John M. Eisenberg Award, the nation’s top honor in patient safety. Modern Healthcare magazine has ranked him as one of the 50 most influential physician-executives in the U.S. more than a dozen times; he was #1 on the list in 2015.

His 2015 book, "The Digital Doctor," was a New York Times bestseller. His new book, "A Giant Leap: How AI is Transforming Healthcare and What That Means for Our Future," was published by Portfolio/Penguin in 2026.

🎙️⚕️ABOUT CARETALK
CareTalk is a weekly podcast that provides an incisive, no B.S. view of the US healthcare industry. Join co-hosts John Driscoll (President U.S. Healthcare and EVP, Walgreens Boots Alliance) and David Williams (President, Health Business Group) as they debate the latest in US healthcare news, business and policy. 

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Transcript

John: 0:07

Well, let's, well, I think everybody wants to see you, Bob, but that's Oh, okay. But that's the, the, the, the, the, uh, that's the nature of ev of, of, of patients. I think they want that human connection, but you really lay out some really terrifying, but. Honest statistics, 800,000 to million people harmed or killed by medical errors every year. Um, the, uh, the, the, that, that terrifying study, another one met, uh, a, a a, a very large scale study of autopsies that, you know, 20 per based on a scientific review of autopsies, 20% of diagnoses, some of which could have been life altering. Are missed, um, in, uh, in our current system. So there's clearly a big opportunity, um, to improve, um, clinical outcomes. And you, you kind of anchor, uh, the, the, the practice of medicine. Um. Back to the, the turn of the, of the 20th century when, when it, and, and sort of said that education hasn't moved forward and you kind of gently suggest that we aren't making as much progress on mand errors and improving clinical practice as we could. Okay, so if we wanna save more lives and improve patients' lives, what do we need to do in terms of leveraging technology to improve outcomes for patients?

Robert Wachter: 1:30

Well, I, I could tell you that when I'm on the wards now, I am quite frequently using AI to help me be smarter. And I don't know that I was missing that many diagnoses before I did this, but I think I'm smarter now than I, than I was. And that's not, that's not because my brain's getting better, any better at my age. Um. You know, we have this practice we call a curbside consult, meaning I don't really need a full on cardiology or infectious disease consultant where they're gonna spend an hour with the patient. But I just have a question that I'd love to have answered, and until a year or two ago, there was no good way for me to answer, get an answer to that question without calling my favorite infectious disease doctor. You might say, well, how about, um, you know, medical textbooks like up to date? Those are great when you have a very straightforward, what's the right dose of apixaban for a patient with pulmonary embolism? It has no idea what I'm talking about. If I say, this is an 82-year-old man with CLL who comes in with a fever, a white count of creatinine of 3.2 and abnormal LFTs, I can say exactly that sentence into open evidence or GPT or Gemini, and it will give me a cogent answer that is on par with what I would get from my favorite neighborhood specialist. So I think where you're going to see real. Uh, improvements in medical practice and diagnosis and in, in treatment choices is the fact that the AI now can, can essentially scale the knowledge of specialists. So it makes me as a generalist. Have access to specialty knowledge in my pocket that it makes a nurse practitioner potentially as good as a generalist in some ways, and I don't think we're quite there yet. It may make patients and their families able to do things that they previously required a, a physician to do. So now this gets much better. Right now I have to pull my phone outta the pocket and say to open evidence, this is an 82-year-old man, et cetera, et cetera, in the future. Of course, that's silly that that function should be completely embedded in the electronic health record. So that I have to tell, I don't have to tell it anything. It is, it knows everything about the patient and you then can envision a world where it not only knows that for, but for an outpatient, it's following the data that's coming from their Apple watch or from their oral ring. It's integrating that. It means that I can track how a patient's blood pressure or asthma doing without them having to come from an office visit. All of that points to a world that's much more efficient and, and much more, much less error pro than the one we had today.