EP. 66: VISION FOR THE FUTURE OF MEDICINE

Jun 14

WITH MICHAEL F. CHIANG MD

The Director of the National Eye Institute explores the elegant intricacies of the human eye and shares what excites and concerns him most about the confluence of digital technologies and health.

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Episode Summary

For over 50 years, the National Eye Institute (NEI) has been a driving force for cutting-edge vision research, education, and public health guidance. In this episode, we speak with Dr. Michael F. Chiang, Director of the National Eye Institute. A pediatric ophthalmologist by training, Dr. Chiang's work focuses on the application of biomedical informatics to ophthalmology, in areas ranging from telehealth to artificial intelligence to health data management. Over the course of our conversation, Dr. Chiang describes the elegant intricacies of the human eye, shares what excites him most about digital health, discusses the urgent need for reformation in medical education, and shares his mission as the leader of the nation's foremost agency for promoting eye health.

Michael F. Chiang, MD is Director of the National Eye Institute. By background, he is a pediatric ophthalmologist and is also board-certified in clinical informatics. His research focuses on the interface of biomedical informatics and clinical ophthalmology in areas such as retinopathy of prematurity (ROP), telehealth, artificial intelligence, electronic health records, data science, and genotype-phenotype correlation. He is an Adjunct Investigator at the National Library of Medicine, and his group has published over 250 peer-reviewed papers and developed an assistive artificial intelligence system for ROP that received Breakthrough Status from the U.S. Food and Drug Administration.
He received a BS in Electrical Engineering and Biology from Stanford University, an MD from Harvard Medical School and the Harvard-MIT Division of Health Sciences and Technology, and an MA in Biomedical Informatics from Columbia University. He completed residency and pediatric ophthalmology fellowship training at the Johns Hopkins Wilmer Eye Institute. Between 2001-2010, he worked at Columbia University, where he was Anne S. Cohen Associate Professor of Ophthalmology & Biomedical Informatics, director of medical student education in ophthalmology, and director of the introductory graduate student course in biomedical informatics. From 2010-2020, he worked at Oregon Health & Science University (OHSU), where he was Knowles Professor of Ophthalmology & Medical Informatics and Clinical Epidemiology, and Associate Director of the Casey Eye Institute.
In this episode, you will hear about:
• Dr. Chiang’s upbringing in a family of engineers and eventual path found to ophthalmology - 2:22
• How the practice of ophthalmology is changing and the role of informatics in this change - 6:43
• What pediatric ophthalmology entails, and why this work inspires Dr. Chiang to this day - 10:39
• The mechanical intricacies of the human eye - 14:20
• Dr. Chiang’s reflections on how his education in engineering shapes the way he practices medicine - 18:03
• The importance of patient stories and how modern clinical practice leaves little time for them - 22:55
• How artificial intelligence is changing medicine and what that means for the future role of doctors - 25:55
• What excites Dr. Chiang most about the future of medicine, and what concerns him the most - 33:40
• Dr. Chiang’s vision for the National Eye Institute - 44:10
• Advice to young clinicians on lifelong curiosity and adaptiveness - 46:04
Henry Bair: [00:00:01] Hi, I'm Henry Bair.
Tyler Johnson: [00:00:02] And I'm Tyler Johnson.
Henry Bair: [00:00:04] And you're listening to the Doctor's Art, a podcast that explores meaning in medicine. Throughout our medical training and career, we have pondered what makes medicine meaningful. Can a stronger understanding of this meaning create better doctors? How can we build healthcare institutions that nurture the doctor patient connection? What can we learn about the human condition from accompanying our patients in times of suffering?
Tyler Johnson: [00:00:27] In seeking answers to these questions, we meet with deep thinkers working across healthcare, from doctors and nurses to patients and health care executives, those who have collected a career's worth of hard earned wisdom probing the moral heart that beats at the core of medicine. We will hear stories that are by turns heartbreaking, amusing, inspiring, challenging and enlightening. We welcome anyone curious about why doctors do what they do. Join us as we think out loud about what illness and healing can teach us about some of life's biggest questions.
Henry Bair: [00:01:03] In this episode, we speak with Dr. Michael Chiang, the director of the NEI. For over fifty years, the National Eye Institute, or NEI, has been a driving force for cutting edge vision research, education, and public health guidance. A pediatric ophthalmologist by training, Dr. Chiang's work focuses on the application of biomedical informatics to ophthalmology in areas ranging from telehealth to artificial intelligence to health data management. Over the course of our conversation, Dr. Chiang describes the elegant intricacies of the human eye, shares what excites him most about digital health, discusses the urgent need for reformation in medical education, and shares his mission as the leader of the nation's foremost agency for promoting eye health. Mike, thank you so much for taking the time to join us and welcome to the show.
Michael Chiang: [00:01:44] Thank you. Glad to be here.
Henry Bair: [00:01:47] As some of our listeners may have picked up from recent episodes, I've matched into ophthalmology. In fact, this episode's release should coincide with the time I begin residency. So for me, it's a particularly special privilege to speak with you today.
Tyler Johnson: [00:02:01] Yeah, Mike, just on behalf of all of us at Stanford, we're really glad that you and your colleagues would let Henry into the field. So thank you for allowing him to match.
Michael Chiang: [00:02:10] Well, you know, Henry, we've just met, and so I can't speak to whether that was a good idea or a bad idea, but it's a great field.
Henry Bair: [00:02:20] All right. Well, we will see. All right. So to kick us off proper, can you share with us what first drew you to a career in medicine and then specifically to ophthalmology?
Michael Chiang: [00:02:32] Yeah, absolutely. Henry I grew up in a family where almost everybody was an engineer, and I just assumed that when people grew up, they became engineers. It was all the toys that we played with. And it was that was basically my childhood. And so I went to college, assuming that I would be an engineer. And in fact, that was my major in college, electrical engineering. You know, it happened that I spent a summer working in a startup company in Mountain View, California. I went to Stanford for college and they built cardiac ultrasound machines. And so what I did was circuit design. And then another summer I actually spent working in a lab in the medical school where we wrote little computer programs to analyze images. And the images actually came from cardiac ultrasound machines. And it was meant to diagnose patients who were having heart disease, you know, rejection after heart transplant surgery. And that actually fascinated me that you could build a machine and then use it to treat somebody and, you know, help somebody. And that's actually what made me want to become a physician. And so I went off to medical school. Now, this was now the early to mid 1990s. At the time, a field that was very hot was computational neuroscience and artificial neural networks. And they were very hot then. And then they became un-hot and then became hot again now.
Michael Chiang: [00:03:56] And so when I started medical school, I thought I wanted to be a neurosurgeon. And I thought that I could understand the brain and model it using computers and then operate on the brain. I basically, you know, found a lab that was in the neurosurgery research division at one of the local teaching hospitals. And I studied information processing in neurons there. And it happened to be that the lab, my mentor there was Dick Maslin, and he worked at Massachusetts General Hospital in Boston, and he happened to study the rabbit retina as a model tissue. And that's how I learned about vision and visual information processing. And after being in that lab for a few years, I loved it. And I decided that I actually wanted to be an ophthalmologist. You know, as a medical student, I also met the person who became my wife, who wanted to become a pediatrician. That's basically how I ended up going into ophthalmology. You know, what I learned from this, I guess, is that what I thought I would be doing in five years was often not what I was actually doing in five years. And I learned that that that's okay, that, you know, you don't have to worry about it, but that it is good to remain thoughtful about how your life and career may end up evolving.
Henry Bair: [00:05:10] So can you share with us some of the the expectations and what actually happened that you went through? You mentioned every five years you things would kind of change up a little bit. So, for example, when you were starting residency, what were you hoping for? And then after residency, what were you hoping for? And then where did you end up in actuality?
Michael Chiang: [00:05:28] When I started off as a resident, I knew that the reason I went into medicine was to apply technology to the practice of medicine and ophthalmology and, you know, thought I wanted to build devices. When I was a resident -this is now the late 90s, early 2000s- everything was about paper charts and handwritten notes and X-ray films. And I thought, there just must be a better way to do this. And so at the same time, you know, technologies like the Web were starting to become mainstream. And so I thought, well, maybe the world doesn't need more people to build devices. Maybe we need more people to manage data. And that's how I learned about informatics. At the time there wasn't a clear career path, you know, for people who wanted to do that field. And so it was a very confusing time. But, you know, decided that what I want to do is, you know, first of all, I became a pediatric ophthalmologist. That's a subspecialty within ophthalmology and then decided what I want to do is another, you know, fellowship training in informatics. And that would somehow blend those within my career. And that's how I got started. And it was another evolution that I wouldn't have imagined, you know, when I first started.
Tyler Johnson: [00:06:43] As a non ophthalmologist- So we had I know this is probably offensive to you guys, but when I went to medical school, we had one week of ophthalmology, right? And that was at Penn. We had this all of the core rotations were packed into this one year. So anything that you got that was not general surgery or internal medicine, you were deeply grateful for not having to be at the hospital at 3:00 in the morning. Right.
Henry Bair: [00:07:07] We had we had two afternoons at Stanford over two years.
Tyler Johnson: [00:07:11] Oh, see, we were way ahead of you then. We had like five times that much. So but the thing that I just remember from that week about ophthalmology, I unfortunately remember almost nothing of the medicine that I learned. But what I do remember was just this awestruck feeling that even as a, you know, budding doctor who at that time, it came relatively late in my year. So I had a, you know, a good number of rotations under my belt and had seen a lot of, you know, surgeries and whatever. But I just remember that when I would go in for the detailed, scope-driven ophthalmologic exams, thinking, oh my gosh, this is like this entire secret world that I didn't even know existed. Like, I remember the first time that I saw a person's iris under magnification. It was like, Oh my gosh, this is like the cratered surface of the moon, right? There's all these little, like, lacunae and all of these sort of like trabeculation and all these things that, you know, I mean, obviously I've been looking at people's eyes for my entire life just like anybody else, but I just had no idea that it was like that. Right? And so I guess that all of that is just to say, can you talk a little bit about what it's like as an ophthalmologist to have access to this entire world that, of course everybody has, but that almost nobody has ever seen? Right. And that almost nobody, even doctors. I often joke with my patients when they ask questions about their eyes. I often say that as an internist, I know a lot about almost every part of the body except for the feet and the eyes. I know absolutely nothing. So if they have questions about those two things, they might as well just take them somewhere else because I'm not going to say anything helpful. So can you talk a little bit about what it's like to have that sort of access to that kind of private but really beautiful part of the body?
Michael Chiang: [00:09:02] Tyler. Those are a lot of interesting observations from your one week of ophthalmology at Penn. I think there's a lot that can come out of that. And let me just try to hone in on 1 or 2 aspects of it. I think ophthalmology is largely a specialty that's based on structures of the eye. It's a small organ, but it's a really amazing organ. And a lot of the way that ophthalmologists diagnose problems is based on morphological changes that occur in the eye. Historically, the way that this has been done is that we look into the eye with magnifiers, slit lamps, ophthalmoscopes, and we look at those structures and we describe what we see classically. Now, this is going back, you know, 50 or 100 years. You look at the structures and you use words and pictures to describe what you saw. That's subjective and it's qualitative. What's fascinated me about the field is that when I started, that's the way that I learned to practice ophthalmology. And now because of imaging technologies and artificial intelligence, it's becoming more and more quantitative. And I think that all of medicine this is happening, that we're going from qualitative to quantitative. And so I think that one of the things that I love about ophthalmology historically is that it's descriptive and you get to see all these amazing structures that you talked about. Tyler And one of the things that I really enjoy now is that we're all helping to transition this field from what it used to be like to what it's going to become in the future.
Henry Bair: [00:10:39] You mentioned earlier that you are trained as a pediatric ophthalmologist. I think most people probably don't have a clear idea of what kinds of conditions you treat. Can you tell us more about that? Like, what are the most common disorders? The most common procedures that you perform in the work of a of a pediatric ophthalmologist?
Michael Chiang: [00:10:59] Henry, one of the reasons I became interested in pediatric ophthalmology was that every field has its so-called bread and butter problems and one of the common issues in pediatric ophthalmology is strabismus. When the eyes become misaligned, they can become misaligned left, right, up, down or rotationally torsionally. And that just fascinated me because it was basically like solving math puzzles and doing surgery to make people's eyes straight again. And so that's actually what drew me to become a pediatric ophthalmologist. It was analytical and intellectually, intellectually challenging, you know, kind of like problem solving. You know, I think another of the common bread and butter problems in pediatric ophthalmology is amblyopia. It's when the eyes don't receive visual stimulation because they can be misaligned or because the child need glasses and doesn't get them, and then the brain doesn't get appropriately stimulated during a critical period of development. And so it never really learns how to see. So this becomes irreversible at a certain stage. And then obviously in pediatric ophthalmology, there are all sorts of developmental genetic problems that kids can have that have really critical implications for vision. But I guess I would say that one common thing that ties these things together in pediatric ophthalmology is that there's a lot of science and math involved. It's stuff like genetics, developmental neuroscience and strabismus to realign the X, Y, and Z coordinates of a patient's eyes. And so I think it's it's been enormously fulfilling to take care of kids and just help them grow up with normal eyesight and just, you know, be in a field where you can impact someone for the rest of their life. And so I guess I guess if I could summarize, I'd say that, you know, what I learned about becoming a pediatric ophthalmologist is it's really important to pick something that you love doing for your, you know, for your life's work.
Henry Bair: [00:13:06] Yeah. One of the one of the things that drew me personally to ophthalmology, I felt, was the balance of the procedural stuff, the intellectual stuff, The, you know, increasingly, as you mentioned, it's becoming more and more data driven. And yet I think ophthalmology offers an opportunity for that longitudinal relationship to be formed, especially if you're doing something like retina, where you are seeing a patient every six months to monitor progression of like a, I don't know, like diabetes or something, or glaucoma, which is a chronic condition, right? Has that relational aspect of medicine in of that patient interaction been something that you have found prominent as a pediatric ophthalmologist? Is that something that also played a part in in drawing you to the field?
Michael Chiang: [00:13:52] Oh, absolutely. I mean, number one, I Happen to be married to a pediatrician and just enjoy being around kids. That has been very gratifying to take care of kids and just watch them grow up. It happened that I spent nine years in my first job and then ten years in my second job. And so I never got to see anybody truly go from childhood to adulthood. But I have loved that aspect of my job.
Tyler Johnson: [00:14:20] I want to back up. Back to this idea of a hidden world. I remember that. You know, one of the things that's so interesting about medical school is that there are all sorts of things that I had just forever taken for granted as a like I hadn't even realized that there was a process involved. I just thought it was a thing that existed as a complete, you know, as one entity. And then in medical school, you learn that it is so much more complicated and nuanced and elegant and beautiful. And I think that one of the places that again, that that was true the most for me was just the the concept of vision. Right. I mean, I think that because I think most of us would probably agree that vision is our most integral sense in in the and what I mean by that is that it's difficult for sighted people to imagine perceiving the world without sight because it's so hardwired into the way that we negotiate every part of our lives that trying to think about what life would be like if we couldn't see is just definitionally impossible, Right? And so because it's so hardwired into us, I think that we most of us certainly I had no idea how complicated the process is. And so I'm wondering if I don't mean this to be, you know, like a pop physiology quiz, but just as this is your area of expertise, I think it's so interesting. Can you just walk us through a sort of a medium, high level version of what exactly has to happen for light waves that are coming from outside of your body to get translated into a navigable image by your brain? Like, can you just walk us through some of the steps of what actually happens in the eye?
Michael Chiang: [00:16:08] Tyler, I think that that's a really interesting question. And again, that takes us into what made me interested in this field in the first place. Basically, I would say in a lot of ways, the way that visual information gets created and processed is not really different from how any other neurological signals and sensory signals come to be. We basically get light waves that get translated to electrical signals that go from the retina, you know, through a series of multiple steps into the brain. And then we have all these other sorts of higher level processes that occur. How do you detect motion stereopsis, you know, all those elements of higher order visual processing? And then of course, there's an even higher level of processing, which is how do those sites get translated into emotions? Those were really some of the things that drew me into the field, like some of exactly what you said, which is that, number one, the process of vision is really important and how it works and how it goes wrong when people get disease. But I think another element is that people really value being able to see. Think you're right that there have been surveys saying that people are really more afraid of losing vision than almost any other ailment that they can get and that, you know, for example, you know, it's sort of our gateway to relationships and emotions. And, you know, I'm always going to remember the memory of my two daughters taking their first steps because it's that visual memory that gets ingrained in you. And so I think that, you know, those are some of the reasons that I really that really ultimately drew me to this field and why I love doing it.
Tyler Johnson: [00:18:03] Can you along the same lines, It's kind of funny. After you spend many years in medicine, you can start to identify some common pathways that lead into medicine, and along with that are some common kind of ways that people's brains work, right? Ways that people sort of how how it is that they latch onto it or engage with it. And one of the types that I have been so interested to see is engineers who go into medicine. And, you know, it might that might seem a little bit counterintuitive to some people because we usually think of people who go into medicine as having been in the life sciences or on this podcast, we talk to a lot of people who have been in the humanities, but we may not think about engineering per se as much, but some of the best doctors that I have known come from an engineering background, precisely as you say, because my experience has been that they often have this very regimented, logical way of approaching medical problems and thinking through medical solutions that has a sort of intellectual rigor to it. That's just different than almost anybody with any other kind of background. But can you talk through for us a little bit what it's like to approach this, you know, teeny little, incredibly complex machine of the eye as an engineer? Like how does your brain sort of think through problems that way?
Michael Chiang: [00:19:34] Tyler, again, I think you've raised a lot of really interesting points here. I was originally trained as an engineer and I was probably raised to be an engineer, you know, just because of the family that I grew up in. And I do view the world very systematically, like like like many engineers, I love solving problems. You know, just to give an example from my own life, the way that I started my career is that we built telehealth systems to try to diagnose a disease that premature babies get- retinopathy of prematurity. It happened that I met a few mentors, you know, who were interested in various aspects of that problem. And so that that's how I got my start at Columbia University. And in doing that, exactly as you said, we approached it very systematically. Like the way you diagnose this disease is by characterizing the different aspects of retinal morphology. We train nurses to take photographs of the retinas of babies. And then we built computer systems to collect those images and you know, basically organize them. And then we trained readers to log in to those systems and make very systematic diagnoses. And and we looked at effectiveness, cost effectiveness, all these things. And I felt like that was a very, you know, organized, systematic way to solve that problem. You know, one of the things that was really gratifying for me is that I spent the first, you know, 7 or 8 years of my career doing that. And then a number of years after that, we wrote a policy paper with the American Academy of Pediatrics and American Academy of Ophthalmology and the Pediatric Ophthalmology Society, APOS.
Michael Chiang: [00:21:28] And that became part of the standard of care. Now there are babies who are actually diagnosed for this disease using telehealth and say, Wow, I contributed because of this process to something that changed, you know, the way that ophthalmology is practiced for this niche disease. But I think that one thing that I've really gathered more is my career has evolved is that I started out approaching the practice of medicine and the practice of ophthalmology from a scientists and engineers perspective. You've got to be systematic, we can categorize things, and what I've had more and more an appreciation for as I've done this longer is that medicine is also very much an art, and that you've got science, technology and art. And, like, more and more, I think that you have to have all three of those to be a good physician. And in fact, I would argue that two of them isn't enough. And that we talked about the examination of the eye being systematic and structural and morphological in ways that we can quantify it. Yet ultimately, in terms of talking to a patient and understanding the nuance of really what concerns them. I think that that's largely an art, and I don't want to see that lost in terms of all the focus that we have on the technology and the amazing science that we're doing.
Henry Bair: [00:22:59] So to your point about the art of interacting with a patient, when I work in the retina clinic, it's not unusual on some days for well over half of the patients to be coming in for the same condition: diabetic retinopathy. This is a complication of diabetes in which blood vessels in the eye are damaged. The thing about this is the screening and management can be quite algorithmic, right? In many instances, treatment involves giving an eye injection and you might do this again and again for 15, 20 or even more patients in a day. But the best retina specialists I've seen take a few extra moments to ask each patient about what they most enjoy doing. The answers might be painting or traveling or watching TV or seeing family and friends. And when you know this, the relatively routine act of giving an injection becomes a process of preserving someone's source of joy, a way of life or relationships with loved ones. To your point, it's so crucial that we hold on to this perspective really in all of medicine.
Michael Chiang: [00:24:19] Well, Henry, I think it's a little bit interesting that at the beginning of my career, one of the reasons I became interested in informatics is that as a medical student, I would learn, like every other medical student, to admit patients to the hospital and listen to their stories. Right. You know, Mrs. Jones went up five flights of stairs and on the fifth flight, she began to feel tightness in the chest. And then Mr. Jones called 9-1-1 and they ended up in the hospital. And I began to wonder. Do I need to know all those details? Because if the end result is going to be that, I'm going to admit them to go through the rule out protocol. Why? You know, I could have just checked a box. And now the irony is that we sort of live in a world of checked boxes. You know, it's electronic health records and the patient had pain- check. You know, they had stabbing or, you know, you have options stabbing, dull, throbbing, and you just sort of check the ones that apply. And after having practiced in both of those worlds, I increasingly recognize that I think I've lost something from the practice of medicine, from not knowing those people's stories. And so I really appreciate that, you know, you who's closer to the beginning of your career is recognizing the impact of those stories on, you know, what I'd call the art and the practice of medicine. I think it's going to be increasingly important to remember that. And, you know, I, of course, appreciate that the title of this podcast is The Doctor's Art.
Tyler Johnson: [00:25:55] Yeah. You know, we have talked with a number of guests about the fact that I think there is a sort of divergence that's happening in medicine that is that we need to recognize in order to be mindful that it doesn't cause unintended consequences. What I mean by that is that even when I was in medical school 15 or 20 years ago, really the point of the doctor was to figure out what was wrong and how to fix it. Right. And I think at that point, the only way that anybody could really think about doing that in any realistic fashion was by a probing interview and a thorough physical exam, because what other option was there? Right? I mean, that that was the only you know, that was what we used to always say was 90% of what you're going to do is taking a good history and physical. Right. And it reminds me of I have very mixed feelings about the movie Patch Adams. But Patch Adams is a movie about Robin Williams playing this kind of unorthodox gadfly, medical student who goes through medical school and causes all these problems. But he has this very kind of doctrinaire, hyper orthodox medical student roommate, and they have this fight in one scene where the roommate is on Patch's case because he thinks he's not studying enough. And the roommate is saying, you know, has some big textbook in his hand. And he says, you know, "I'm studying this because someday I could be in a situation where if I don't know, the key fact that's in some obscure page of this textbook, a patient could die because of my ignorance.
Tyler Johnson: [00:27:31] And you're mocking my studying by, you know, doing all your other stuff that you're doing during medical school." And 25 years ago, that idea totally made sense, right? That if you didn't cram enough facts into your brain that somebody's life could be on the line because of what you didn't know. Right. But of course, now that's almost like even just in the era of Google, that idea became almost silly. And in the era of Chat-GP4 and whatever else is going to come after that, then it's going to become almost entirely obsolete. And as that has less and less purchase that function of the physician of like figuring out the problem and figuring out what to do about it is probably in some ways going to become increasingly ancillary because there may be bots that can quantify the damage to the retina or what used to be an art and an estimate can now be done much more accurately by some AI bot. But the thing, unless we end up in a, you know, true sci fi, strange landscape, the thing that's actually going to emphasize even more is the importance of the art. So that even if we are not as necessary for quantifying or identifying the problem or discovering the solution, that's going to make it all the more important that the sort of ritualistic the healing part of the doctor patient encounter is going to become even more vital as that other may start to fade away.
Michael Chiang: [00:29:06] I think that's really fascinating that if I can just follow that with an anecdote from my own life. That when I was training 25 years ago, I would say the equivalent of some of these things would be that, you know, we needed to learn to examine the retina, you know, with contact lenses that we would put up onto the retina and learn every nuance of the macular structure, the optic nerve head. And then again, like we were talking about in the beginning, use words and pictures to just qualitatively describe and we draw, you know, what we saw. And I always viewed that as that was my added value that, you know, after doing that from hundreds or thousands of patients, that I became good at it. And that was something that other people couldn't see. You talked about looking inside the eye and looking at that world that's there. And the problem is that in 2003, nobody does that anymore. You know, in fact, in fact, today's trainees don't even learn how to do that. There are machines that get. Quantitative data from the eyes of patients. Tyler mentioned a chat bots, but it really turns out that and Oct angiography devices now you know you know look at retinas and they can give you numbers about all these different aspects of the eye and that's what people look at now instead of that. Nuanced drawing.
Henry Bair: [00:30:30] Sorry, could you just explain for many of our guests what an oak tree is and what it does?
Michael Chiang: [00:30:35] Yeah. Oak Optical Coherence Tomography. About 20, 25 years ago, this became really, really popular as a method of imaging the retina where you'll capture, for example, cross-sectional images of the retina and quantify how thick, how thick is the retina, You know, are there spots or abnormalities or fluid that's there to a level that we really cannot see often, you know, from the traditional ophthalmoscopic exams where you look inside the eye. You could make this analogy In any field of medicine, there's more and more machines that are doing this, and I think that that is transforming the field of ophthalmology and what it means to become an ophthalmologist. And sometimes these changes have occurred. So, you know, I would say so gradually that people often don't realize that the field is changing. And one thing that I've often wondered about is that these amazing machines and artificial intelligence devices generating numbers and, you know, everybody sees the same numbers. And so, you know, if you're a super subspecialized retina specialist versus a general ophthalmologist versus an optometrist versus a patient primary care doctor patient using Google search, you know, we all see the same numbers and the same data dictionaries about what the numbers mean.
Michael Chiang: [00:31:59] And so I think that we're going to really have to figure out what the added value is of physicians in the 21st century. Tyler, one thing you suggested is that the added value may be the ability to talk to patients and now you have cancer. Are we going to do chemotherapy and you're going to have a miserable, you know, next few months, but a longer life expectancy on the average versus B, go into hospice and spend quality time with your friends and family. Different people may react differently. I don't know that there's a right or wrong answer in those cases. You know, do we do surgery, medical management, observation? Those are human choices. And I think it would be ironic if doctors in 2023 are losing their communication skills because they're too busy copy-pasting in EHRs. And so I think that there's a lot that the field is going to have to think through in anticipating and evolving toward the future.
Henry Bair: [00:33:00] Yeah, it's definitely something to think about because as I approach my internship the first year after graduating medical school, I can't help but think back to when I was a medical student working for those interns, how much time they spent on the computers and not what the patients. In fact, that's one of my favorite things -unfortunately, actually- as a medical student, I got to spend like twice or three times as much time with the patients as my, you know, as the interns, because they just had to tend to the chart and copy paste on the electronic health record. Speaking of which, we know that you have, as you've talked about already, you're deeply interested in digital health tools, not just in ophthalmology, but in medicine in general. Like, this is an area that you you do research in. Can you tell us some of the the things in digital health that you are most excited about? And then maybe what are some things that you're most worried about in this field?
Michael Chiang: [00:33:54] I think that there's a lot to be excited about. You know, when I started my career, we talked about doing telehealth, and that was for one, disease, retinopathy of prematurity. For me, that evolved to, you know, we captured so much image data and we started doing artificial intelligence, you know, for this disease built systems that could, you know, we showed could diagnose disease better even than world experts, you know, became interested in electronic health records registries and big data analytics. You know, just enormous fun building that part of my academic career. You know, before moving to this job at NIH two years ago, I think that one of the things that I'm really excited about, as we've talked about, is that these have potential to transform the way that we take care of patients. They are transforming the way that we take care of patients to the point where we can make more accurate diagnoses that are more reproducible and, you know, create potential to make health care accessible to people who are in medically underserved areas, regardless of whether that's in the US or around the world. I think that some of the things that make me nervous are things that we've touched on already. But just just to hone in on one of them. Henry, I know that you're you're starting a residency in ophthalmology, and I think that we've got a lot of when I honestly look at the field and how it's evolved over the 20 plus years that I've been a physician, it's evolved dramatically. But I don't think our educational system has evolved nearly as much as the field has evolved. And I think that is a big problem. If you were to ask what is the one tool that every single doctor in this country uses? You know, some people might say it's a stethoscope or if you're an ophthalmologist, you might say it's an ophthalmoscope.
Michael Chiang: [00:35:53] But, you know, not every ophthalmologist uses an ophthalmoscope. I would argue that the one tool is the computer. Yet I would also argue that most medical schools and residency programs don't really have dedicated time toward teaching about those technologies and what the implications are for the future. You know, I would contrast that to, you know, how do you take a history? You know, Tyler, you would alluded to, you know, how do you do a physical exam? How do you auscultate the heart? I mean, you know, trainees will spend months to years of dedicated time focused on learning those skills. But, you know, for the one thing that every single doctor does, you know, often it's zero dedicated time and people learn it by trial and error. And there's also this paradigm in medicine where the more junior person learns by emulating, the more senior person. And in this case, it is often the junior person who knows more than the senior person. And so we really need to rethink this. You know, what I'd call educational paradigm, you know, and the last thing I'd say is that. It's often in the area of technology and evolution of practice, the younger people who have more creative ideas. You know, they've grown up using these technologies and can think outside the box. Yet it's the senior people who have decision making authority. And so I think that we'd benefit from getting junior and senior people to work more closely in terms of shared decision making. And I think that those are some of the concerns that I have and some of the ways that we might try to address them moving forward.
Tyler Johnson: [00:37:32] One thing that I'll add to that, as someone who spends a lot of time teaching medical students and residents, is that I think that the you know, there's this famous book by Neil Postman from like the 1970s where he talks about the idea that the medium is the message, meaning that the the way that you deliver information actually ends up shaping the information that you deliver. And I feel like we see some of that in medicine as well, in the sense that there are definitely times when we're teaching medical students or early residents how to think through a complex patient and all of their interrelated problems, where what you figure out over time is that they have grasped a lot of information and they may have even grasped a lot of individual problems. And they can tell you about this problem and this problem and this problem and how to analyze them. But then if you ask them to sort of bring it all together and to say, okay, but what happened? What's wrong? And what are we going to do to fix it? Those questions, which are the fundamental questions when you're taking care of any patient, are often very difficult for them. And I think that part of the reason for that is that they have grown up cutting their teeth on an electronic medical record that is chock full of a glut of information, but that has incredible difficulty boiling all of that down and distilling it into the heart of no pun intended, of like what's really happening.
Tyler Johnson: [00:39:08] Right. Like it it's like it teaches us to think in this very divided way, this very sort of expansive, you know, because like, if you look at a lot of notes for patients in the hospital, the note for a single day for a single patient goes on for six, eight, ten, 12 pages, the vast majority of which is cut and pasted from the day before. The vast majority of which is sort of background information that doesn't actually tell you anything about what has happened over the last 24 hours. And you could really boil the last 24 hours in the like pertinent changes down to maybe a page, but you can't even find that information because it's buried in all of this other stuff, most of which is kind of incoherent and really not that important. And I, I worry that in that way, the way that we have approached traditionally the electronic medical record, which is often done with an eye towards billing, frankly, more than anything else, it's just list everything so that you can bill for everything actually impoverishes the way that medical trainees learn to think about medical problems.
Michael Chiang: [00:40:12] There is so much depth in Tyler into what you said. I definitely agree that we're challenged that the medical record system that we have is based largely on billing and compliance rather than on patient care, and that it's very tough to separate the signal from the noise and that in some ways it's tough to completely blame trainees or doctors for copy pasting because when you have to see. 40 patients in a day and there are 100 prior notes and there's just so much information to go through. This is the world that we live in. And I've heard many times doctors will say, well, gosh, if the engineers just knew, this wouldn't be the but but I think to me, that's reason that doctors have to get involved with this, because from the engineers perspective, it's going to be, well, ask the doctor. They were too busy for me. So it's I think this is it's difficult to characterize that as a one sided problem. It affects everybody. I think another challenge that I see is in medicine, there are a lot of traditional ways that we represent information graphically, serum chemistries. You know, for example, there used to be the checker box, you know, way of putting sodium, potassium, etcetera. And, you know, it's been 25 years since I worked up in internal medicine patient as an intern, but I can still look at that and have a sense of what is happening with a patient's chemistry, because the way that I view it is that there's a mental model that we've built for, you know, for doing that.
Michael Chiang: [00:41:49] And in ophthalmology, there are other analogies to that. There's a H that we use to represent eye movements. You know, there's a tic tac toe box for strabismus, to use those examples, you know, from pediatric ophthalmology. Often in the world of 2023, electronic health records don't have those systems. And so sometimes I've wondered, you know, are today's younger people not building those mental models? You know, for example, in different electronic health record systems, I've seen some of them represent serum chemistries alphabetically and I've seen others represent them the way that, you know, that I was used to thinking about them, you know, HCL and I wonder, are we not building the same mental models that we used to or are we just doing it differently? And I think that there are a lot of implications for learning and processing. And when you mentioned, you know, the medium and the message that we're really going to have to think through as a as a community, I think that when this transition started, you know, we were very busy in terms of just making that transition. And, you know, now that we've. You know, for all practical purposes, completely made the transition. I think that we're going to need to think about some of these issues that we've been talking about here. How can we really use these technologies and develop these technologies to let us do the best doctoring in the future?
Henry Bair: [00:43:12] Yeah. What's what's been striking over the course of this conversation is that we we've talked a lot about the rapid evolution of technology in medicine. And yet it seems like despite this evolution, we're not doing well, technologically speaking, as physicians and training future physicians. And we're also not doing so well in training the humanistic side of medicine. Both sides, the technical side, the artistic side. They don't seem to be you know, there's a lot of work here. Basically, despite the technological advances we've been seeing over the past decade.
Michael Chiang: [00:43:48] Henry I would agree with those things. And what I do think on the flip side is that we have good people in the field. You know, they're smart people who want to solve problems and who care ultimately about taking care of patients. And so I think one of the challenges is going to be to create structures for people to be able to channel that creativity and sort of knowhow into some of these solutions that we're talking about.
Henry Bair: [00:44:13] There are two things I'd love to just briefly explore with you. One is your work at the National Eye Institute. I'd love to know what your approach to leadership is. What is your mission as its leader?
Michael Chiang: [00:44:25] So first of all, what is the National Institute? You know, we're one of the institutes at the National Institutes of Health, and we were founded in 1968 to basically be the branch of the NIH that manages national efforts in vision science. And so, Henry, you asked about what I view as my mission. And I guess that's one of the first things that I did when I started here about two years ago, is to redo our mission statement. You know, it hadn't been changed since 1968 when we were founded. And so I'm a real believer in going through that process because it defines that North Star. You know, it's like it's like Alice in Wonderland. If you don't know where you're going, you know, any any road will take you there. And so, you know, we spent six months doing that and we came up with this mission statement that our mission is to eliminate vision loss and improve quality of life through vision and research. And, you know, how do we do that through leadership in four different ways. Number one, we drive innovative research. Number two, we foster collaborations. Number three, we recruit, inspire and train talented people to strengthen the vision workforce. And lastly, we educate people about what we do and why it's important. And so basically, you know, at the We are the lead federal agency for research in vision disorders and we build programs that have the goal of preventing and curing eye disease. And, you know, and also for people who have eye disease that's currently not curable, you know, we build programs to help with accessibility. And so that's that's my job that every day I try to focus on that mission.
Henry Bair: [00:46:04] The last thing which we always close our episodes with is asking about some of your advice for younger clinicians, for trainees, future doctors. Like what advice do you have for them about healthcare leadership, about doing work that is truly meaningful for you, for finding work that is best aligned with your interests, or really advice on anything else that you've learned from your life.
Michael Chiang: [00:46:32] There are several things I could say, but is that like everyone else, I've fumbled through life. Guess I'll say one thing. I was once in a room when I was about 16 or 17 when we were told that we were, you know, the best and the brightest and that that felt great to hear. And so I was 16 at the time, and I used to teach a lot of medical students and residents who I assume most of them are in their 20s and 30s. Right. And, you know, we often told them that they were the best in the brightest. And, you know, you are at Stanford. I'm guessing you've heard that phrase as well. And you know, now, yeah, I'm 52 right now. I'm occasionally in rooms that are filled with more senior people. And I hear that term, you know, with rooms that have more gray hair, like, oh, you're the best in the brightest. You're, you know, working with solving the problems of this country. But, you know, I used to assume that the people who were in that room were the same people who were in the room when they were aged 30 and the same who were in the room when they were age 50 like that. That was the implication when I heard that when I was 16 and and a few years ago, I had an epiphany that they're not the same people, you know, think some of them are the same people, you know, but but a lot of them are not.
Michael Chiang: [00:47:51] And what I would sort of say to younger people, to answer your question, is that you don't want to be in that room when you're 30 but not in that room when you're in the sweet spot of your career, when it really matters, like when you're 40 or 50 or whatever. I feel like my observation is that I've met quite a few people who are in that room when they're senior, yet we're nowhere near that room when they were 16, and that's always fascinated me. And I've thought and of course we've all met people who were in that room when they're younger. You don't want to peak too early, you know, end up there and then not, you know, not there later. And so I've thought a lot about, you know, what makes people move in and out. And nobody knows the answers, obviously. And but my best guess so far is that what sustains people as being the so-called best and the brightest is the ability to take in new knowledge and adapt to change.
Michael Chiang: [00:48:52] And, you know, you know, Henry, as you go through your career, I will be interested in your thoughts about this. You know, maybe we'll have this conversation in 20 years and you can tell me or you'll tell some other podcaster, you know, in 20 years what the answer is. But, you know, so I guess for now, my advice would be that I think the educational system is very focused on milestones and what you need to be the best doctor in 2023. But, you know, you really need to be developing the best the skills that are going to let you be the best doctor in 2030 and 2040 when you're in that sweet spot of your career. And I think it's cultivating that ability to adapt to change and learning new skills. And I guess the last thing that I would say to people who are interested in academics who are young is that it's awesome. You know, I think that it's an amazing career to solve problems. And Tyler, you began with like, you know, systematically solving problems. And I think that's been a ton of fun. So I would say just enjoy it. And you got a lot to look forward to.
Henry Bair: [00:49:56] Well, with that, we want to thank you for your time, for joining us and sharing your insights, your stories. It's been a true privilege for us.
Tyler Johnson: [00:50:04] Thanks so much. We really appreciate having you on the program.
Michael Chiang: [00:50:07] Henry, Tyler, thank you very much. A privilege for me as well.
Henry Bair: [00:50:12] Thank you for joining our conversation on this week's episode of The Doctor's Art. You can find program notes and transcripts of all episodes at www.thedoctorsart.com. If you enjoyed the episode, please subscribe rate and review our show available for free on Spotify, Apple Podcasts or wherever you get your podcasts.
Tyler Johnson: [00:50:30] We also encourage you to share the podcast with any friends or colleagues who you think might enjoy the program. And if you know of a doctor, patient or anyone working in health care who would love to explore meaning in medicine with us on the show, feel free to leave a suggestion in the comments.
Henry Bair: [00:50:44] I'm Henry Bair.
Tyler Johnson: [00:50:45] And I'm Tyler Johnson. We hope you can join us next time. Until then, be well.