The Exchanges

Q because of weather more times than I can count. I think you'll see how persistence was rewarded when you listen to this wide-ranging conversation. Let's get started. I'm gonna ask you a question. I was debating on the flight over here today, how I wanted to start this interview, and I think we're gonna go back to, like, med school, which is, why did you want to become a doctor?

A Well, um, I didn't want to become a doctor. So, you know, I grew up in, uh, southeastern Ohio, uh, the kid of two Indian immigrant doctors, and of course, what do they expect that, but, you know, it's, when will you go to medical school? And so I spent college, um, I majored in biology, but I also majored in political science, kind of looking for, there must be more to the world than just medicine, and I found it. I found it in lots and lots of different places, um, Some in science. I worked in a lab. Some, you know, I, I tried everything in college. I, I, uh, was in a band. I learned to play guitar. I, I wrote music reviews for the, um, the, the student newspaper. I joined Amnesty International. I worked on Gary Hart's very short-lived campaign for president as a volunteer. And then, um, uh, and then when I got out of, Stanford. I went on to do a master's degree in politics and philosophy economics at Oxford out of hope that I could maybe do a graduate degree in political theory or something like that, and I just found I wasn't very good at those questions, and a lot of the things that I tried I just wasn't really made for or cut out for, and I kept coming back to medicine as a place where I was familiar, I was comfortable, It wasn't for the best reasons, right? It was a place that I knew and I could, I could thrive. What I also liked about it was you didn't actually have to d…

AI assessment note: “I kept coming back to medicine as a place where I was familiar”

Q And then what are they doing better that could be possibly copied or?

A Yeah. And so we, we've started to unravel that. Um, we started to pull those things apart and, uh, and it, and it often is really mundane things. One example, uh, we published, uh, some data on, um, uh, hospitals and, and the variation between hospitals with a colleague that we partnered with named Rafaela Sadun- Who's at Harvard Business School. And we measured across hospitals in the country implementing safe surgery programs and so on. And, you know, for many of your listeners, it's like, oh, this is totally just like business one-on-one. Do you hire for talent and their ability to achieve the, your, your main goals and objectives? Do you, number two, do you, um, have measures of Whether you are achieving those goals and objectives. Number three, do you have goals and objectives? Do you have targets for what you aim to do that you're measuring against and hiring for? And then fourth, do you standardize operations around, do you, do you make a kind of a checklist for the key things that you are, your key targets and what you're trying to accomplish? And We now see that there is direct correlation between the more of that you do, the better off patients are, substantially better off patients are, and better off in terms of quality. And we also see There isn't a single hospital we have measured yet that is doing it at the highest levels, um, that would get a, you know, five on …

AI assessment note: “Do you hire for talent... have measures of Whether you are achieving those goals”

Q but as you pointed out, I mean, it's a lot more difficult when we do know that there's an established method for solving this particular problem. How do you end up with open and honest reporting in the medical system for doctors? I think you mentioned an M&M And morbid, morbidity and mortality conference. Morbidity and mortality conference. I was wondering if you can give us some insight into that.

A Yeah, um, we just had ours, uh, um, uh, today. Um, is it today? No, it was yesterday. Um, so this is a conference we have every week, seven o'clock for an hour, and it's a, um, and in that meeting we bring the Complications, which is to say, the cases that had things go wrong, where, um, ah, where, ah, the patient had a bad outcome, and we're specifically bringing up the cases where, um, we're addressing errors, and, you know, what could we have done differently, and how can we learn from it and make things better? And then every death is also reviewed there. And, ah, and some of them can be prevented and some can't. Um, And part of what's interesting to me is the culture of that. There is a space, it's actually a legally protected space, for us to be open every week about what went wrong and what happened to people, including, you know, terrible things. Um, people left permanently disabled because of something that we've done. And it's a kind of ritual where the person presenting Stands at the front of the room and says, I was responsible for this. And my responsibility is not perfection. My responsibility is, however, that we always have to be aiming for it, even when, even when we know we're going to fall short. And then the second part is not only owning it, but also the fact that next week we're going to have another meeting. And there's going to be More cases that we will…

AI assessment note: “There is a space, it's actually a legally protected space, for us to be open”

Q You, you mentioned sort of rising medical costs. I want to grab onto that and kind of run with it a bit in Uh, maybe from the outside looking in and from doctors that I've talked to from the inside looking out, there's something wrong with medicine, but what's wrong with medicine?

A Well, I, there's, there's a couple things to separate here. The fact of rising healthcare costs is not the problem. What is, uh, the problem is, uh, how much of the costs are rising that have not, that are not actually, um, connected in any way to value. So, um, an example would be that, um, we have a substantial amount, uh, of, um, Healthcare that we provide that provides no benefit or makes you worse. Estimates are that about 30% of healthcare is waste. It's going to things that are either, um, much higher administrative costs that add no value, or are actual treatments and tests and procedures and drugs that are of no benefit or actively harmful. Um, you know, I've written about, for example, there was, ah, a study of 26 different, um, tests and procedures ranging from, ah, EEG for headaches. EEGs are good for detecting seizures, they're of no benefit for evaluating people with headaches, to cardiac catheterization for people with stable heart disease.

AI assessment note: “Estimates are that about 30% of healthcare is waste.”

Q Two questions left. One easy, and one more philosophical, uh, and self-reflective. We'll start with the easy one, which is, uh, what do you wish all patients knew?

A What I wish all patients knew is what the role of the clinician ought to be, and what their role is, and that you can demand it. And the role of the clinician is not just to tell you the facts of what your situation is. Here's your disease. Here are the options, A, B, and C. Here are the pros, the cons, the risks, the benefits. But the role of a clinician is also be a counselor, and that means that the clinician should be someone who helps you understand and identify your goals, given the cards in your hand right now, which may not be a great hand, but what matters to you now, and, um, they should then be able to help you understand, here are the options, here's The, you know, what, what they understand about them, but then help me match what my goal is with which one might give me my best shot at achieving that without sacrificing things that are important to me. And your role is that you need to help the clinician understand your goals and, um, and to be as clear as you can about that. You know, my father, when he had his brain tumor, uh, Um, his first goal was, he was a surgeon, do not give me a treatment that's going to cost me my ability to keep doing surgery. We already knew it was an incurable cancer, so everything we were doing was to prolong life, and to him, life, one of its key values was getting to continue to take care of patients. And so, you know, having, even wi…

AI assessment note: “What I wish all patients knew is what the role of the clinician ought to be”

Q In your book Complications, one of the things that you explore is the, what makes a good doctor. Can you expand on that for us?

A Well, in some ways, I think I've been interested in that from the very beginning. So Complications was written out of my early New Yorker articles where I was a, a trainee in surgery, and I was very interested in, um, what does it mean to be good at what we do as a doctor? When I'm I'm still learning. I'm practicing on human beings. One of my, one of my very first article was about a, um, a computer that could diagnose heart attacks better than, uh, better than, uh, the most experienced doctor could, and a hernia factory in Toronto where, um, the surgeons were, none of them were actually trained as surgeons. One was like a family physician, but they did more hernia operations At lower cost with far better results than any I would ever achieve.

AI assessment note: “they did more hernia operations At lower cost with far better results”

Q Was it conscious to apply ideas from other domains, or was there an, like, was there an aha moment that this makes sense, or, like, how did that come about?

A I think it's more personality. I mean, I think I, um, grew up kind of interested in how the world worked, and I had a very Limited vantage point in a, in my town in Ohio growing up, and every opportunity to see more, you know, my handle hold was through science. My parents were doctors, and that gave me a, a way of seeing and thinking about the world. Um, but then my parents were also people who were deeply involved in the community, um, in trying to deal with the challenges in, um, a community that had A college, but was also the poorest county in Ohio. And so, you know, my brain worked in such a way that, um, I loved the, uh, understanding the ideas at a ideas level, and then trying to figure out how you ground it. So I was always looking for ways to understand the world, and that meant needing to bridge and look more widely. And so each move College, and then going beyond, kept widening that, and I, and I've, and I've just loved that. I've loved adding another, um, space that I could explore, and it was only by happenstance, it was very late, that I found I had anything to contribute, um, and that really wasn't until my thirties, uh, when I finally, uh, found I could connect the dots between different things I've been learning about.

AI assessment note: “I think it's more personality. I mean, I think I, um, grew up”

Q interesting to hear you say that you, you felt like you weren't good at something, because from the outside looking in, you're a surgeon, a prolific writer on multiple subjects, uh, at the New Yorker, multiple books, and so it looks like, and a researcher on top of all of that, right? Not to mention a husband and a father, so it looks like failure's not really in your vocabulary.

A Well, but, um, A, it doesn't mean I do all of those things well. Um, and, uh, B, um, you know, I, I, I like having a lot of irons in the fire. I like being, uh, a jack of all trades, and, um, finding the edges between things is often where I have something to add. You know, I'm, I'm not, uh, in, in, If you look at what I contribute in these spaces, it's, it's not genius ideas. A checklist for surgery. It's just taking an idea from one domain and saying, let's bring it over to the other and see if it can work. Um, or, um, you know, understanding what people's goals are when they face mortality at the end of life. A lot of them just come from digging in deep enough to understand the gap between what we're aspiring for And the reality of what we're doing, and then trying to figure out where the bridge is to narrow that wide gap. And so most of my value just comes from Saying and pointing out, wow, we don't live up to what we say we're going to do. It's, it's not for, usually not for evil reasons. It's usually for really complicated reasons, and then unknotting the complexity, um, and just taking time, uh, to do that. I find in each line of work, whether it's surgery, um, our public health, uh, research center, where we're sitting today, Ariadne Labs, Um, or my writing. I'm just doing the same thing over and over again, actually.

AI assessment note: “Well, but, um, A, it doesn't mean I do all of those things well.”

Q What's changed in your mind about what it meant to be a good doctor since you were a resident writing that and today?

A Um, I think it's evolved, you know, in, in the beginning it was a lot around, um, how do you cope with the reality of error? Uh, complications was, Partly about the nature of, you know, how errors occur. Some of it's because of ignorance and we just don't have the science. Some of it's because of errors and actually failure to do what we ought to know how to do and learning curves and, and, and systems and things like that. And some of it, what is the reality of complexity, meaning that you're always fallible and that you will never be error free. Um, as I Then finished my training and went into practice, I became comfortable with the fact that I was doing what I could to keep on climbing the learning curve, but, um, now mystified and, uh, struggling with the reality of the system around me being as important in the outcomes of my patients as me, in fact, in some ways more important, um, The, ah, the, how well the place I work in delivers, ah, makes a huge difference in whether people do well or not. And so that became the next area of obsession. How do I understand the bell curve? Why there's a wide gap between, ah, the performance of, ah, different people and different places depending on where you go to as a patient. And then by the, by, you know, the next stage I'd found That I could try solutions and borrow them from different places, and checklist manifesto was, um, you k…

AI assessment note: “in the beginning it was a lot around... how do you cope with the reality of error”

Q Aside from the M&M, what specific sort of performance techniques do you use, um, to get better at surgery? I know you wrote a New York article about hiring a coach. Yeah. Can you expand on that?

A Yeah. So, you know, what, what's, what's interesting about, um, the work as it's gone along is the first step is trying to make sure you don't do this, do, do, The stupid things that, um, people already know about that demonstrably get to better results. That's, that, you know, do your checklist. Don't, don't make the dumb mistakes. Um, but then if you're trying to get to excellence at the other end of the scale, it's interesting to me that we have such different theories across different professions about how you make that happen. Um, the pedagogical theory is you go To Juilliard. You get your 10,000 hours of practice with the violin, and you then head out into the world, and you're responsible for the rest of your self-improvement along the way. That model is the primary one in professional life. Most musicians, in medicine, in teaching, in business. Um, The other model is mostly out of sports, and that's the coaching model. And that says, I don't care if you're Roger Federer, you, um, you will have blind spots when it comes to your own improvement, and you need a coach.

AI assessment note: “The other model is mostly out of sports, and that's the coaching model.”

Q Is it, uh, I come from Canada, so we have more socialized sort of healthcare system where, uh, the costs are rising, obviously, and these questions come up occasionally, which is like, what is that sort of duty of care to the patient if we're going to spend a 100,000 dollars to extend somebody's life? For a week. Um, how do you think about that? Can you expand on that?

A Yeah, there's a couple things. One is, we think the U.S. is a big outlier in this way, but in fact it's not. Um, when you look at, um, studies outside the U.S., it's also fairly typical that it'd be around 23 to 25% of spending after age 65 in the last year of life. And when you understand that, um, that what happens is that we are in a situation where when you come To the end of life, you don't know when that last year of life is. There's tremendous uncertainty. And how we manage that uncertainty is the, is the great difficulty. And we manage it really badly. Um, and so this is the second part of it, is that we assume that, hey, if I'm going to spend a 100,000 dollars, um, that the problem is that we're, um, uh, we're just not, you know, we have to make a, uh, brutal decision and say, look, It gives people an extra month of life, and sorry, you just don't get it. It's not worth it. Um, there's a, there's...

AI assessment note: “when you come To the end of life, you don't know when that last year”

Q remarkable to me how these people have so much intelligence and so many different domains, but, uh, these simple words can kind of bring us back. Have you studied other industries that have sort of catastrophic consequences and what their disclosure policies are to get at some sort of learning? I think you mentioned pilots in your book about reporting to NASA. Is there anything else that comes to mind?

A Yeah, I mean, the, the, the pilot's example is one where NASA also has a protected space where if you submit a, um, report on an error or on a, what they call a near miss, it didn't crash the plane, but it could have, you get a jet, get out of jail free card. So by reporting on it, you, you are not, um, subject to investigation. Now, I, I think that there's, we're coming to understand what people call a just culture, which is that there are clear norms and values, which are, there is no get out of jail free card. You lie about, uh, what's the, what's happened or, um, falsify information. Um, you hide information. You, um, uh, or you are, uh, Actively, um, subverting the system or malicious in certain ways. And those are, those kind of behavioral norms are ones that should get you fired and are appropriately removed. But then when you're talking about, um, fallibility, uh, human weakness, the, um, you know, problems that occur because people are in conflict or they're tired or, or all of those things, or you just, you don't, you weren't thinking, um, Those are part of, uh, human beings trying to work together on really hard things. And so, um, in other industries that I've seen that have been able to create that space, you know, engineers on successful teams are able to create, and you can see on teams, um, within the same organization, in the same research lab, for example, you…

AI assessment note: “the pilot's example is one where NASA also has a protected space”