Dr. Brent James - Covid Conversations

Speaker 0 00:00:05 No, no, no shame. Which moment next man. Good. Speaker 1 00:00:19 I'm Dr. Robert groves, your host for the groves connection podcasts, the groves connection brings you intimate conversations with pundits providers, patients, leaders in late people all to help us understand a contradiction. How can our healthcare system be both magnificent and yet so deeply flawed. We're going inside healthcare to talk candidly with those who know what they have to say, may delight, surprise frustrate, or at times even anger. But I invite you to get curious and listen to the truth about healthcare and those who want to fix it. Maybe the answers have been there all along. We just need to make the connection. Speaker 0 00:01:06 <inaudible>. Speaker 1 00:01:16 I am so excited to introduce my guest for this episode, Dr. Brent James is a healthcare legend in the fields of healthcare, quality improvement, patient safety, outcomes, research, and true cultural transformation. And if I listed all of his academic appointments, awards, and achievements, and we'd never get to the podcast, he's a clinical professor at Stanford and invited lecturer at Harvard, a member of the national Academy of medicine and a consultant to healthcare systems, both across this country and internationally, he's trained thousands of leaders through his advanced training program at Intermountain health and spawned several dozen light training programs based on his methods. He is a rigorous analytical thinker, but also a great storyteller. Dr. James knows how to take a complex idea and make it interesting and relatable. And he's full of surprises. I opened the conversation by asking about his perspective on COVID-19 and you don't want to miss his response. Please enjoy my conversation with Dr. Brent James. Speaker 0 00:02:22 Ready, Speaker 1 00:02:49 Welcome everyone to my conversation with Dr. Brent, James, I, I am really excited to be here. You and I were speaking earlier, before we started recording about the first time that I saw you speak and that had to be back in the early nineties, I was a brand new intensivist newly-minted, uh, and I was chosen to go and attend a workshop that was at Intermountain health. Um, and, uh, although I'd learned about, uh, quality management and continuous quality improvement and, uh, the work of Dr. Deming and others, when I was at the veterans administration hospital in training, I was interested, but it wasn't until I heard you speak about it, that I got truly excited. And, and frankly, I spent much of my career at banner health, working on driving out, uh, unnecessary variation in care, establishing a shared baseline, et cetera, but where I'd like to start today, we're in the middle of a pandemic. So where I'd like to start today is how do you think about that risk love to have your perspective on COVID now, Speaker 2 00:04:00 You know, it's all about risk, um, a lifetime of training in statistics and probability. I find it to be quite helpful. The truth is, is we all face a series of risks every day, risks to how long and how well we live. I regard to SARS cov two is just one more risk in the stack. Uh, I have the benefit. I tend to track the numbers a bit and try to come up with the best estimates of how much risk it really represents as a trade-off sometimes aggressively pursuing protections against SARS Colby to actually increases or exposes me to other risks. So it's a balance, isn't it? Right. And you already think about it correctly. Speaker 1 00:04:40 We're not good at that. As, as human beings, we, we don't tend to think stuff Speaker 2 00:04:44 Typically. Oh, we're no good at it at all. That's been very well-documented many times we tend to be driven more by emotion by fear. So I like to approach it by taking the fear out, uh, frankly, to be honest, I'm not very afraid of, of SARS Colby to COVID-19 it's a risk. Yes. Um, frankly in Utah track the numbers, I figured that my risk of dying should I contract it is Oh, somewhere less than one in a thousand. Uh, and compared to other risks, I routinely face it's a little bit larger, but it's not completely out of range. Now that doesn't mean I'm going to be foolish, right. Masks work. All right. I really like can, 95 is more comfortable to wear than N 90 fives. And they're within a hair's breadth of being as effective. You'd be an idiot not to use them. Social distancing works. Washing your hands is a good idea in any circumstance. Let's not get silly here. All right. Uh, but on the other hand, um, I think it's a matter of balancing risks and I don't believe in driving my life on fear. Speaker 1 00:05:48 Let me just ask you a quick question, because I'm fascinated by the one in a thousand. How did you arrive at that Speaker 2 00:05:55 Number? I twos things. I try to capture on my computer, uh, every major article on the topic and I try to stay fairly, fully up on the science and the other thing I live here in Utah. So I tracked the numbers in Utah every day. So I've got a graph on my computer that shows across all age ranges. It shows the case fatality rate, right? CFR want to define what you mean by that? So it's among identified cases. How many people die currently in Utah and others about a three week lag in deaths. So you got to lag the data properly auto correlation, right? Statistically, uh, is 0.0, zero five is where it's running in Utah right now is kind of the, the center line. That's the case, fatality wrestle case fatality rate. Now we know something else, depending upon which literature we believe. There's not a really solid study yet. Speaker 2 00:06:51 They're in progress and I'm tracking at least some of them that are in progress. So it's the infected mortality rate or the IFR, as opposed to the CFR. What we know is that for every case detected, there are between three and 10 people in the community who actually were infected with SARS Colby to developed a full immune response. But their symptoms were so minor that they chose not to test chose, not to test. They never went. And for it, test three to 10, that means a true affected fatality rate, the IFR, which is what you're really after this thing, take that 0.005 and divide it by a number somewhere between three and 10. Now the part of my model that I'm leaving out, because I haven't been able to get solid data on it, is it turns out that the COVID-19 is very strongly related to age. Speaker 2 00:07:44 If you get done in healthier younger populations without major comorbid diseases, the fatality rates, even more, of course, most of this disease concentrates in the elderly, I'm 70. I have one major comorbid disease. I'm making guesses about those. You see how I can get into my number though. I did this thing. And then I look at that and I look at the other dumb things routinely do. How does convenience that I know convey risk? Yeah. Um, usually humans, we're more Sheryl beans and we ignore those risks. But you know, in the back of my head, I know that they're there. And every time I get in my car and go for a drive, I realize that I'm taking a small but real risk. I have friends who refuse to get on airplanes because they feel that they're so dangerous, heavy emphasis on the word feel they're certainly safer than driving in a car, right? Speaker 2 00:08:32 Roughly as safe as the trains that they tend to use to get across the country and, and much faster and much faster, much more convenient course, you're in crowds and you probably have a higher infectious disease risk, yada, yada, yada. There are all those risks you have to balance. You see what I mean? So that's, I think about the thing. Um, I am, as a, I mentioned earlier, a little disappointed in our news media think they over sensationalize and what they're doing is playing off people's emotions off their fears. It's manipulation really? Isn't it? Yeah. You don't see it that way, of course. But, but it is technically, it really is. Your hair catches on fire and they run around. And as a crusty old surgeon, who's come to the curmudgeon part of my life. I'm just so much into that, Speaker 1 00:09:18 Uh, uh, interested in how you think about the steps that we've taken. Okay. Masks hand-washing social distancing, all make sense in, in, uh, a novel virus that is sweeping through the population. What else should we be doing? Is, is it okay to shut down the economy? Or, you know, what's, what's the, Speaker 2 00:09:41 Yeah. Well, you said it right. You said it exactly right. Robert, it's a balance. We know the evidence is overwhelming that when you have a major economic downturn, it costs human lives to a number of different factors, particularly depression. Yeah. We pay for that in lives. And so it's striking an appropriate balance between the two very early in something like this. If we'd been able to close our borders and number of countries have used that fairly effectively. I think that that, that particular horse is out of the barn. Yeah. Um, once you get a few cases across the line, uh, you're going to have a real hard time limiting them. The idea of more effective testing regimens is certainly very appropriate finding people who actually have the disease and then getting them into isolation or controversies though, for example, some would have us basically locked them in a hotel, incarcerating them in a hotel rather than allow them to, to, uh, be in their homes, live within their homes. Speaker 2 00:10:37 So there are issues around comes down to civil rights balances against civil rights to in basic human rights, along the way. It depends on how afraid you are, uh, how far you're willing to go with those things in terms of how you're balancing them. Um, of course your real hope is to prevent two things. Uh, when you have a Virgin population and a new virus is introduced, you're going to get very, very high infection rates. And even if you have a quite low mortality rate, it's still going to show up as a lot of deaths, right? When you in those numbers, Speaker 1 00:11:11 And that's kind of the situation we're in, that's the situation Speaker 2 00:11:13 We're in. You don't want to overwhelm the care delivery system. So one legitimate argument is, is that we're really stressing our capacity to care for people who have advanced disease. And what you're doing is you're flattening the curve. You're pushing those cases out across time. The things we do probably won't stop people from eventually getting COVID-19, it'll just delay when they get it. Speaker 1 00:11:38 And, and another way of saying that is the area under the curve is going to be issue Speaker 2 00:11:41 It's about the same. Yeah. Yeah. It's just that you spread it out over time. So the capacity of our system and the other big one, of course, a truly impressive scientific achievement in terms of rapidly producing vaccines. Wow. Speaker 1 00:11:55 Yeah. That's an amazing feat. Yeah. Speaker 2 00:11:58 Amazing feat. And if we can get to that vaccine availability and of course, we're right in the midst of that right now, a lot of angst around that too guys. It's just a matter of time. We'll get there. Yeah, of course. We'd all like it to happen faster rather than slower. And you shouldn't let down your guard in the meantime, the obvious things from something like this, uh, but we'll get there. And I predict when Dr. Fowchee said that sometime later this summer, any American who wants access to an effective vaccine will have it in my tracking the data. He's right. There are a few other vaccines that are hanging in the wings. My personal favorite is Novavax by the way, protein, but it's protein based is what almost all of our vaccine technology is built around. You know, if you get a T DAP protein based Shingrix, protein based, most influenza vaccines, protein based. Speaker 2 00:12:45 So we have some novel vaccines to DNA RNA. So Pfizer, Moderner both messenger, RNA vaccines, uh, Johnson and Johnson. AstraZeneca are both viral vectors. Those are new technologies. It's not just that you have more trouble handling them. It's not just that. It's our first time to expose large groups of people to them, by the way, there is a risk in there. Oh yeah. Just annoying that you're balancing risks again, is that we have limited production capacity Novavax will be the first protein based vaccine to cross the line. We know how it behaves, but more important. Our production capacity is massive. Novak says that there'll be able to produce 2.1 billion doses in 2020. Speaker 1 00:13:26 Wow. And is it easier to transport? Speaker 2 00:13:29 Well, yeah, it doesn't require a special refrigeration and Stuart and just a regular fridge. That's a glass for months, you know? Uh, it's more like a regular vaccines. Yeah. Gotcha. So I've been kind of watching for truth in advertising. Um, they ran a major phase three trial in the UK with just 15,000 patients. They were delayed in starting their trial here in the us. Um, they had trouble with production, um, but it came alive. But at the end of December and I signed up, I figured I ought to put my body where my mouth is. And so I signed up and volunteered for their trial. I it's funny as an old guy who started doing trials, I started with the Eastern cooperative oncology group working out at Dana Farber cancer Institute for cancer, clinical trials, GI tumors as an old trial guy, they're randomizing in a really squirty way. Two thirds of patients get the vaccine one third, get a placebo and they're buying to trial. It should go the other way, frankly, if you really wanted to get the science out fast. So it's very clearly being affected politically. Gotcha. Okay. Um, now explain that because you know, the strategy Speaker 1 00:14:39 That I'm familiar with is roughly half and half Speaker 2 00:14:41 Well that's, uh, that's the traditional one is half and half, but here's the trick. The driving statistic in a trial of a vaccine against COVID-19 is the number of people who get COVID-19. So, given what we know about these vaccines, the early phase one phase two trials, sometimes combined, uh, we know that they do have some level of efficacy and I'm the thing that determines when I can actually cross the Mark is I have to have a certain number of COVID-19 infections. Presumably the vaccine arm of the trial is going to have very, very few, but you're not trying to accumulate COVID-19 infections in the control arm of the trial, the placebo arm of the trial. Speaker 1 00:15:23 You put two thirds in the control arm. You're likely to hit that number five sister got you. You'll hit it fast. Okay. Interesting. Speaker 2 00:15:29 But they've chosen to randomize the opposite direction. I think it takes longer than to get. Now I'm making an assumption. Um, I'm not truly maintaining equal poise. I'm going into this. I personally believe on the early data that almost certainly these vaccines are efficacious. And so I'm going to design a trial in the heat of the moment, given that we're in the middle of an emergency, I'm going to design a trial for that case. Now I'm sure I bet somebody is going to say, well, here are the other reasons I did it the other way. And I'm just up in the night on this probably, but maybe there's another reason if there is, I'm just not familiar with it. Speaker 1 00:16:07 Yeah. Yeah. So let's, let's talk about, uh, the messenger RNA vaccines. Cause that's what everybody's getting right now. I don't know how many millions of doses are out there at seven or Speaker 2 00:16:19 Yeah. They're getting them out there. It's it's, you know, it's in that range more than we'd like, but it's a really good. Speaker 1 00:16:24 Yeah. Yeah. So, so what do you think the risk is now for those two vaccines? The UN I guess there's an unknown unknown, because we've never done this before. Speaker 2 00:16:33 We, we have the randomized controlled trial suit brought the vaccines, not to full approval, but to a, an emergency use approval, right. In the way they range about 30,000 patients. So we've exposed half of that, two thirds of that 20,000 patients, 30,000 patients to each of those vaccines, which gives you a pretty good luck, at least for short-term consequences. When we did the scientific reviews of this, uh, I sat on some national policy groups and they took us through good scientific reviews down in the past. We've had some whole minor debacles with other vaccines when we finally exposed large numbers of people to him, that's when you really find out how they behave, the risk of that is very low. So we're back to balancing risks, right? What's the risk of an untoured consequence from an MRR and a vaccine that we don't understand yet versus the risk of contracting and dying from. Speaker 2 00:17:26 COVID-19 see the idea. And frankly, if that were my choice, I'd go with NMR and RNA, because I think that that's a lower risk than being exposed to COVID-19 if you see what I mean. Yes. If I had a good protein based vaccine, I perceive that the risk is slightly lower still, so I'm going to go and have the proteins here. So that was why I did it. And I figured if I'm sitting around talking about this all the time that I oughta be willing to ante up. Yes, indeed. So I went in and got a shot and I'm collecting the daily data and, uh, blood draws where they tracked your immune response in some detail. And so there you go, give your body to science. I think they, as part of being a physician at some level. Speaker 1 00:18:08 Yeah, yeah. You know, I, it helps to talk to somebody who has a, uh, more statistically based mind than I do. I will admit that I get emotional about this sometimes, and I've let my fear run away with me. And it certainly seems to be, uh, enhanced by, uh, the media and, um, you know, politicized for lack of a better term. And, and, uh, the answers are either black or white. In other words, uh, either you shut down and don't leave your house or you ignore and pretend like it doesn't exist at all. Those are the two options that we're sort of given Speaker 2 00:18:50 And they're false choices. Aren't they, they really are false choices. Yes. It's gray, it's nuanced. And we will have time for nuance a lot in today's political environment, nuance in a sound bite emotion. Yeah. You can't. And frankly, um, I have the advantage of 40 years of scientific research as a physician, a statistician, most people don't. Yeah. Yeah. And you know, it's hard to know what to rely upon in today's noisy environment. Speaker 1 00:19:20 If you were going to give advice to lay person out there today, what would you tell them about how to think about all the information that's out there? How do you find the information that's truly valuable in that mass and, and how do I I'm thinking about thinking, I guess, what, what would your advice? Speaker 2 00:19:39 Well, one of the challenges we already have had is we haven't had an authoritative voice that tells the truth, I should say. And as a side, Robert I'm disappointed people get into spin mode where they're trying to spin the public response. So early on, uh, we were having shortages of protective equipment PPE. And so we got a message, national message that we shouldn't seek masks, that masks were not effective. Uh, now I'm going to say this in a particular way. Hopefully it's not as harsh as it sounds. That was a lie. Um, masks are effective. Now let's be precise at protecting others around you, is their primary role, a much lower ability to protect you from getting it. But remember, this is a disease where somewhere between, um, two out of three and nine out of 10 people who get it are shedding the virus and have no symptoms. Yeah. It gets worse. There's a prodromal period of four to six days. So even those who are going to eventually develop symptoms, go four to six days of shedding virus without any symptoms. The reason you mask up is to protect your loved ones and those around you. Um, it's a matter of social responsibility. Now, if you want to go, as far as the key in 95 mask, which is what I wear my saw you were in, when you came in, that will actually protect you to some degree because of how they work, Speaker 1 00:21:06 Reduce the viral load at a minimum. Well, Speaker 2 00:21:08 It will certainly, it does the best job of protecting those around you. And it will also reduce, it will protect you to some degree. Speaker 1 00:21:14 You know, my, my, uh, my test of that, my measure of the protectiveness of, of a mask really is, is does it collapse when I breathe in? Speaker 2 00:21:24 Well, I liked Ken 90 fives because I find them there within a hair's breadth of an N 95, which is the standard at, and there's so much more comfortable to wear. I like to wear them better than I could surgical mask. I spent half my life wearing surgical masks, and I find a can 95, more comfortable because it stands out from your face and it kind of seals against your skin and you can't wear it without covering your gnomes. I think the first thing is, is that we need those in authority to tell the truth, to tell the truth. That means you have to trust the people. It means you can't be trying to manipulate them to some sort of a policy agenda or policy goal. Guys, just tell the truth. I realize it's complex, but most people with a little time can understand even complex truths. Yes, we do it routinely. So tell the truth is the first thing, part of the truth is what we talked about earlier. When I look at it and say the truth is much closer to, I'm not going to hunker in fear. I think with the new administration, that we're much more likely to have authoritative national voices speaking to the extent that they tell the truth. I think it will serve us quite well. Speaker 1 00:22:34 The most troubling thing to me about the early part of this pandemic was the fact that we weren't getting the truth from trusted sources. And that that really sort of poisoned the well a little bit for future pronouncements about what to do Speaker 2 00:22:52 Once you're caught in a lie, you're a damn liar forever. You know, I've seen statistics that suggest that within the United States, number of people who, who trust the mass media is, is so well under 50%, both sides of the spectrum. It got worse than that though. Robert, I have a colleague at Stanford, John, and who was deeply respected across the profession for his work in evidence-based medicine, as he deserved, by the way, very thoughtful boys. He's a good, good statistician. He says, follow the data guy, by the way, in my department at Stanford, during our faculty meetings, the same thing emerges fairly quickly, their view. Well, my view is they're a B be the way to say it. It's kind of conversations we have with John early on and said, you know, guys, that early data isn't matching up to the modeling. We're hearing the modeling that makes us look like a it's going to kill us pandemic. Was that modeling early? Oh, it was. And he, he quiet boys saying guys, I'm not sure the data matches. He was savagely attacked. In my opinion, on social media, it was politically incorrect. So it's not just telling the truth. In our current media environment, you can be fairly viciously, attacked from both sides from telling the truth. Now the trouble with science, as you will understand the story of medicine is a constant constant conversation to find better versions of the truth. We basically failed toward better and better, more accurate versions of the truth. Speaker 1 00:24:23 I liked that. I liked that expression of the process because there is a failure because it's not the best yet, is it for the best? Yeah. Yeah. Speaker 2 00:24:31 And as part of the fog, by the way, you can make it consistently better. And looking back, look at the progress of medicine, that's a story of medicine you see, but to do that, it takes the conversation. And we got in circumstances where you couldn't have the conversation and that's deadly, uh, when you shut things down, largely ideologically. Um, and it has to do with our current political environment as much as anything and the way that social media works. So truth in advertising. I don't, I'm not on Twitter. Uh, I track some of my friends on Facebook. I got on Facebook mostly to make sure that nobody stole my name on Facebook. Um, that's great. Uh, I don't believe in those media as a means of effective truth-based communication. I realized I'm a little extreme on that. I'm like I'm being a curmudgeon again. Uh, but you know, I, I find my sources of truth from other sources and I appreciate thoughtful kind of humbled voices who give me the full continuum, not black and white. Speaker 1 00:25:41 Yeah. Yeah. Do you think that the position that we find ourselves in now is salvageable? How do we get back to a better conversation? Um, nationally, locally, you know, with our neighbors, how do we get back? Speaker 2 00:25:57 Yeah, it's a harder question. I don't think there's a clear answer yet. I, I tend to be an optimist. I think the pendulum will swing. The question is, is how bad does it have to get before the pendulum swings? Now you want to really have a fun conversation. Um, we hear a lot about tribalism right in the media today in our own conversations today. Here's a idea that even lies below tribalism kind of foundation upon which tribalism rest it's called ingroup outgroup. In-group out-group okay. Yeah. You've heard that. Sure. Yeah. So it turns out humans tend to form groups. Burberry's book us versus them claims that this is a evolutionarily hardwired into our brains. Yeah. We're individuals, but at the same time, we need a group of society to survive. If you were somehow excluded from the group, for some reason, uh, in evolutionary history, in theory, it meant that your chances of dying went way up. You'll see. It was really hard to survive as an individual compared to surviving as a group. Speaker 1 00:26:55 So we're, we're expanding essentially the idea of cliques in high school. Speaker 2 00:26:59 Yeah. Right. I mean sort of one example, there are many more. Now you can belong to many groups at one time, but in group out group, here's the key thing for our group, especially if it's around contention and competition, an enemy, we dehumanize the outgroup. The thing that people miss on tribalism is this idea of dehumanization. Hmm. Another book it's called on killing about how we inculturate soldiers to be able to kill an orange. It turns out it's really hard for human being to kill another human being. And it takes a very careful training to get most people. Uh, we have a few people, we call them sociopaths who are troubled by this. But for most people, it seems to be a deeply ingrained part of human nature. Um, when you dehumanize what you mean, you're saying they're not humans, Burberry sites, uh, lynchings in the Celsius in the United States during the civil rights era. Speaker 2 00:27:51 And when you read those accounts, it's very clear that the people that were killing black Americans were dehumanizing them. They didn't see them as human beings. That's the thing that I watch underneath it all is the dehumanizing language. And it goes both ways. It does, um, I a hater, a bigot, these terms sometimes apply, but they're used much more generally, you know, benighted. They just don't understand, uh, what was it deplorables that same group out group language and it's dangerous. Um, and the question is, is how bad does it have to get before we finally get over it? Speaker 1 00:28:27 Absolutely. Aye. Aye. Aye. Aye. What I'm thinking is underneath that, is that where anti-science movement comes from, is that, how do we, how do we explain people who believe conspiracy theories or vaccination, conspiracy theories? Anti-vaxxers how, how, how does that come to be? What is that about? Speaker 2 00:28:49 Yeah. So, um, here's my belief. This is a belief and you can judge it for yourself by the way. I'll try to be really careful. I'll say when I have evidence, I'll say here's the evidence guy who wrote about that was a Jonathan Haidt, H a I D T a. And he wrote a few really good books in my opinion. Uh, but this particular one, he talks about the rider and the elephant. Do you remember that motif? Remember this? So the elephant is your emotions and the writer who in theory is controlling and directing the elephant is rational thought, but he points out that it's a 6,000 pound elephant and 150 pounds. Right. And it feels like that so many times. And in fact, if you extend the argument all the way out, without going through the fine detail with apologies for not going through some of the argument, it turns out that what the writer appears to spend most of its time doing is justifying the decisions the elephant made. Oh, I didn't mean to go that way, right? Yeah. Um, well there's a famous saying in statistics, uh, came from, uh, turn of the 19th century statistician. He uses statistics like a drunken man uses lampposts for support rather than illumination. Speaker 1 00:30:06 So it's possible to do that for somebody who saw it. Speaker 2 00:30:09 Yeah. It's extremely common. You establish a position, then you filter the data to back it up. Now we all do that. We all do that. We all do that unless you're pretty careful in your thinking. We do it all the time. Speaker 1 00:30:21 I have a confirmation bias. We want to look at that, which reinforces what we already believe. Speaker 2 00:30:29 So if you've ever studied misdiagnosis as a physician, as you're looking at a patient, you fairly quickly come up with an idea about what's causing their problem. You arrive at a diagnosis and then you tend to filter all the data you receive from that point. And it's what leads to misdiagnosis. Really good diagnosticians. They wait longer before they actually commit. Huh? Is what happens in that, in that little body of science, that's what makes you a really good diagnostician? You don't commit too soon. John Williamson at Hopkins. And later he was at the VA in salt Lake. He came up with a decision support tool that gave you a differential diagnosis of Bayesean differential. As you work through a patient problem. Um, it had some real advantages, but by having the differential in front of you, it meant that you didn't commit too soon. Interesting. Okay. Kept other alternatives on the list. Yes. And it was associated with a real reduction in misdiagnosis rates. Speaker 1 00:31:30 Well, Dr. James, now that we've gone down that road, I want to ask a question. Where does AI come in with a diagnostic support? Have you, have you given that thought in and is it always going to be an aid or does it replace it sometime? Speaker 2 00:31:46 So this is a personal opinion. I believe that, uh, well it'll be nuanced. It will always be an a and the way to think about it. It's again, that's part of the history of medicine. It's the core idea behind quality improvement. Two is currently practiced in quality improvement in the lean version of quality improvement. We would call it mass customization and the idea of mass customization. It's a way of dealing with complexity. Humans have only ever come up with two ways of dealing with complexity. To my knowledge. Number one is subspecialization also known as the analytic method. You have a problem that's too big to solve, divided into a series of small problems, salvage the small problems you've solved the big problem. Um, so you sub-specialize, uh, you know, you're an internist, internal medicine is pretty broad, well, too broad to really master within that. You focus just on endocrinology, still pretty broad within that you focus just diabetes, narrowing your focus to deal with the complexity. I've of course got some colleagues here in town that I know who just do cystic fibrosis diabetes. Now you're getting really narrow. Speaker 1 00:32:49 The danger in that is fragmentation. Exactly. Speaker 2 00:32:51 That's the trade-off well, the other way, it's a complimentary way that people have come up to deal with complexity is called mass customization, the CME and oxymoron, the key to effective variation is standardization. So you establish what's called standard work, a standard protocol, a guideline, all right. But you establish it with the purpose that I'm going to vary around it based on individual patient need. Yeah. Now that idea has been around for a long, long time. The lean guys claim to have invented it, but that's not true. Um, for example, back when I was a youngster flying medivac as a resident, uh, w we in the air use something called a bird van later, some of us are old enough to remember bird ventilators. Yes. I remember bird ventilators probably right at the fringe of your career, but they were mainstays. Speaker 1 00:33:38 I have, I have poured peep in an Emerson before, so, Speaker 2 00:33:42 Okay. Yeah, there we go guys rule, but yeah. Um, I had to be able to field strip one that sometimes stop working. So you'd have somebody who has Sardo's history, usually a nurse and blue bag, the patient, and then you'd strip down that ventilator, clean it up, slap it back together. And usually it worked. Can you imagine doing that with the modern ventilator? No, no, of course not. It's the history of medicine, John Eisenberg, a lead physician, George Washington university hospital, and also the head of HR Q John and work. We used to call him, he points out that this is true across at least the last 300 years of medicine's history. What we do is we study something and when we start to understand it, we standardize it. And what it does is it frees the most important resource. You have the trained human mind, the expert to focus on the things that the cutting edge see the idea. Yes. Yeah. And if you track the history of medicine, I mean, I got lots of examples beyond just a leader. What we did was understood ventilation well enough that we build it into the machine. So Dr. Rose an intensivist, you don't have to think about that level of detail. Yes. And what it means is, is you get to focus on other critical things. Don't you that matter more in this circumstance, see the idea as AI, that's AI, Speaker 1 00:34:57 I've used your, uh, descriptions and approaches and sold it to my colleagues, uh, based on that for my entire career. Yeah. Speaker 2 00:35:07 Yeah. I mean, it's all of us share that common experience. And if you look back as we just didn't put a fancy name on it and try to sell it as a consulting service, but it's a history of medicine. That is what it means to be a doctor. I think of it as wings, you know, an aircraft wing. So in world war two, a major breakthrough was the P 51 Mustang. It was the first wing that had laminar airflow and it massively increased lift on a wing. So you can have shorter wings and get more lift by modern jazz fly. All right, what happens is, is they're designed in such a way as, as the air, which is, uh, kind of chaotic as it hits the wing. It actually organizes into like, they were little channels of molecules coming across the wing as a little chain, right. Speaker 2 00:35:55 Is standardized. In other words, interested that's medicine at the leading edge of the wing. It's always chaotic. That's a beautiful analogy. And then as we work on it and we understand the structure of it comes back across the wing, we standardize it. And as a physician, I live at the zone of chaos when I was in training a long time ago, back in the seventies, some of my mentors had been around as young physicians when IVs were first introduced and it was a mainstay of their practice. They carry their own tubing in their pocket, their own set of needles. They sterilize their own bottles. Can you imagine doing that today? Well, now we standardized it and pushed it down the line. Didn't we, it was a breakthrough at the time, but then a breakthrough becomes routine care. Isn't that the history of medicine isn't that the nature of progress that we as physicians, we should exist at that turbulent cutting edge. And as we standardize things appropriately, it takes it off our plate. There's a limited capacity of the human mind. And we take our most important resource of trained expert mind and focus it on the stuff that really makes a difference. Speaker 1 00:37:10 I'm going to ask you about some statements that you've made in the past, in fact, fairly frequently related to that. And one of those is much of what we spend on healthcare, and we can have a separate conversation about how much, what we call health care actually impacts longevity. Yeah. But, but let's focus first on, on healthcare. And you've, you've said that I think it was an Institute of medicine report that, that quoted 30 to 50%. Okay. Speaker 2 00:37:43 2010 called together the experts at Institute of medicine. Now, national Academy of medicine, um, we were measuring something called quality associated waste. Deming established Damien's approach is basically a mathematical proof. Doesn't get much better than that. He was comparing what he called physical outcomes to cost outcomes in process theory. And he showed three hard causal links for two of the three. As you improved your physical outcomes, that's what we call quality, the attributes of your physical outcomes. In our case clinical outcomes, he demonstrated mathematically that it caused your cost of operations to drop. All right. And that became the core definition for something called quality associated waste. Okay. That's great. We know it exists. How big is it? And so we called together the experts and said quality associated ways to how big is it? And the soundbite single line result of that big report was a minimum of 30%. Speaker 2 00:38:39 I'm probably over 50% of all spending in healthcare is quality associated waste. Now a couple of caveats is to across the world. I worked fairly heavily internationally. My favorite health system, one of my very favorites is Sweden. Their waste rates appear to be about the same as ours. Another one is Singapore working with them at the moment as they try to reform their health system, there all the way up to 3% of their GDP. But the rate of increase is too high. So they invited some of us into advise them as a reform, their health system because of expense. They have relatively high quality associated waste rates. Interestingly enough, same in every country I've ever visited. If you take a closer look. Speaker 1 00:39:19 So that's an important point. I mean, there's a perception sometimes among physicians that are, uh, interested in this aspect of health care. And even I think among some policymakers that the us is problems with cost. Escalation are unique. They're not are there. Speaker 2 00:39:39 Yeah. Quality waste levels are very similar, uh, best I can tell. All right, there'll be some differences. Speaker 1 00:39:45 I got a headstart on them in terms of total dollars, Speaker 2 00:39:49 Optimizing a different function. So the way to ask question, I had an old colleague, a friend truth in advertising, clay Christianson, and I were missionaries together in Korea as young men. Speaker 1 00:40:00 Yes. Sure. Wow. And clay, that's an interesting connection. Speaker 2 00:40:04 Yeah, he did pretty well. I mean, it was the guy who kind of alerted the world to disruptive innovation as a professor at Harvard business school, as you guys are doing okay. It worked out that way. Well, clay, uh, approached me and said the key thing in any enterprise, he labeled it the job to be done. And he said, what's the job to be done in healthcare delivery. Now, as you alluded to, it's not life expectancy. It turns out life expectancy is an extremely poor metric. Compare health systems shows a level of stunning naivete, lack of understanding. Um, the three that emerged the way I like to say them. There are other ways of saying them, uh, look at the work of Tom Lee, for example, now that he's at press Ganey on this topic, number one is caring. There's a reason we're called the caring professions. Speaker 2 00:40:54 That's reducing mental, emotional suffering. If you will. We forget that sometimes. Do we ever, it's easiest to see when lives are on my mind, but I believe it's our most important role is to clinician patient relationship. It's one of the most rewarding. Oh yes. By far to, you know, look back before 1900. What we know today, if you went to see a typical healer, chances of survival went down, our treatments killed people pretty effectively. Um, uh, by any standard that we use today, it's crazy to look at it. How is it that we were central to human society is all about caring and that hasn't gone away. Now you have to have the eyes to see it. You have to look to see it, but it's there as strongly as easiest to see when lives are on the line, when someone's dying. You know, Robert, what I'll say is as an old cancer guy, I think I did some of my very best work when my patients died. I really did. I could change the nature of death. Yes. Isn't that what it means to be? Speaker 1 00:41:55 It is what it means. Ultimately, because we were having a conversation before we started recording and you made a point that my dad made in a different way, because when I got into medical school, he said, what's the number one cause of death. And I said, heart heartsease. He said, no. And I said, lung disease. And he said, no, he says being born. Speaker 2 00:42:18 Yeah. The mortality rate is still the uniformly, a hundred percent somebody getting out of here alive. Speaker 1 00:42:21 And he was making that same point that ultimately the most important thing that we can do for anyone is care. Speaker 2 00:42:29 Well, interestingly, when you ask patients, well, that's why I really like Tom Lee's were that's her number one thing. Number two is curing healing, the body healing, the mind where possible. So limited ability on the other hand, yeah. It's five to 10% of life expectancy tracks back up, by the way, uh, Arnie Milstein and Bob Kaplan at Stanford in my department just published a really nice summary paper on this topic, Carol, that reads only about five to 10, maybe 15, if I'm really liberal percent of life expectancy, Speaker 1 00:42:59 3.6 trillion on that. Yeah. Five to 10% and half of that's quality waste. Yeah. Speaker 2 00:43:05 Uh, by the way, about 40% of your own personal health behaviors, which ties very tightly to your education level. So the health behaviors are endemic within underserved populations. 30% roughly is genetics. You'll joke how wise you are in selecting your parents. Haha. Not much to offer there 20 to 25% is a physical environment. Social networks control of epidemic, infectious disease or public health of care delivery is five to 10%. If you're really rigorous of maybe 15, if you're quite generous along the way now let's not under undermine that it's three and a half to seven years of life expectancy on average for every, every member of our society. This is solo at my age. Let's not get too cavalier here looks pretty good. That's seven years starts to sound pretty, pretty good. I mean, let's not get too over the top here guys. Uh, um, on the other hand, compared to the other sources of health, that's relatively minor. There's a literature that shows that you'll get much bigger health impact by investing in general education. You put that money in general education, more high school graduates, more college graduates has a bigger impact on health. They're putting the same money into care delivery. So Speaker 1 00:44:17 Are we misguided when we talk about social determinants and, and uh, gosh, I'm forgetting the name of the system in New York is, is buying hotel rooms for homeless folks because it's cheaper to keep them in a hotel room than it is in the hospital. Are we barking Speaker 2 00:44:32 Up the wrong tree there? Uh, not entirely. I mean, it's part of the waste modeling. I like to approach it as a waste of modeling. Um, because hospitals are so very, very expensive. Um, by the way we encountered this, I, I was of course the senior officer in a major healthcare delivery system and we were being quite successful with our improvement waste elimination efforts, quite successful. And the question is, is how do we use the money? And the question came up, should we go address some of the social determinants? Um, now this is a really good conversation. I recommend it to others. You may come to a different conclusion than us, right? It's it's not black and white. Our conclusion was is that our primary mission was healthcare delivery. And we should not try to supplant the forces of local and state government with housing and with food supply and with education that our biggest contribution, we should be part of that conversation. We should be driving it convenient, right? We don't want the conversation to go away, but we should reduce the cost of healthcare. Ah, so that it wasn't competing with these other social goods. That was our primary mission. Otherwise what you become as you become a independent taxing agency where the population with your high healthcare prices and then I use it for social good. Does that belong to a private organization? No. Or should that Speaker 1 00:45:51 That's a redistribution through a private organization is unnecessary and probably wasteful in all the bureaucracy that's tied up in making that happen. Speaker 2 00:45:59 We decided that we were going way, way beyond our remit way beyond our mission. And we decided that we wanted to be part of that conversation, but that we should not try to supplant local and state government, um, that our problem was is healthcare costs too dang much. Yeah. What would happen if you drop the cost of health insurance by 50%? What would it mean to other programs that we could run? What would it mean to middle-class productivity for one, I mean, across the board and the question is is where are we going to pull this power on to ourselves? Or are we going to play an appropriate role in our larger society? That's how we saw. Speaker 1 00:46:37 That's a very interesting perspective and what I've not heard a lot. Speaker 2 00:46:41 Yeah, well we, we were being really successful with taking out waste across four years. We took out 13% of our costs of operations. It was what $688 million out of a $5 billion system. And this is Speaker 1 00:46:55 Through essentially mass customization. We described earlier quality improvement, having a shared baseline. Everybody agrees. Here's what we ought to be doing, but yeah, we're standardizing a lot of stuff. And what you used to have to do was remember everything you needed to do for every patient. Now, what I need you for is to identify when that patient, and this is I got from you doesn't fit that protocol. So you still need to be alert. You still need to be a highly trained, responsible physician. Oh yeah. Because otherwise you miss stuff and you miss it's a different error, but it's still an Speaker 2 00:47:30 Error and all that we've done there, Robert is we've taken a concept. That's been underlying medical practice, good medical practice, the advancement of our profession for hundreds of years. And we're formalizing it a bit and start measuring the results and start measuring the results. And let's just, let's do better what we came to do. Well, we had this conversation and we decided that our mission was to reduce the costs of healthcare. So should I be buying housing? You know, it all started in Denver and it was a state while the city government who is buying the housing to keep people out of the ed. It's a grand example of this. It's a population health move, upstream quality improvement strategy, beautiful example. But do we have to do it alone? Should we pull that power onto ourselves? Should we try to replace our elected representatives say anti-democratic and, and we, we considered it carefully and decided, no, that's, Speaker 1 00:48:24 That's a new perspective for me that I hadn't really explored to that depth. So, uh, thank you for that. I, I guess my next question is why aren't we seeing results faster nationally? We, the price of healthcare continues to escalate pharmaceuticals now, or are starting to be an increasingly large percentage. What are we missing? Because we know we can do this Speaker 2 00:48:50 What's missing. So there are two main causes that I think are in play. By the way, this is a whole reason that Arnie Milstein started the center for excellence. The clinical excellence research center at Stanford, a member of that department is to try to understand that. And we're still at the level of how to say it, Oh, fairly based opinions. But we argue like crazy. Um, I believe it's two things. Uh, one is tradition, habit, existing systems that sometimes it's really hard to turn the carrier. A bigger one for me is misaligned incentives of a particular time. You are Speaker 1 00:49:24 My song because that's the way I think about it is I used to think, I knew how to fix healthcare and I no longer believe that the complexity is overwhelming. As I got into the insurance side, there's another whole layer of complexity. And what I've decided is what we need to do is ask the right questions and get the incentives, right? And there are a whole lot of smart people who following those incentives will figure it out. Speaker 2 00:49:48 Well, here's how it works with waste. I have a particular model of waste that I like to use. Um, it has some very attractive features to my mind. I need to write it up. I haven't yet, um, in a formal way, I've taught it. Um, but it layers out waste and different layers. It's really nice because so far as I can tell, it gets every source of waste that everybody at most people use kind of a heap style and giving samples. It also picks up social determinants and picks up population health quite nicely. It fits them all really nicely, but it layers it out. The big one, it ties to payment mechanisms. So the way to think about it, any time you're going to do improvement, it always requires an investment. Yes, you have to change systems. Data systems should bring in new technologies. You have to train people, you know, all sorts, sometimes change your physical plan and sacrifice productivity in some cases, learning new systems. Speaker 2 00:50:38 Correct. So there's always a price best. I can tell that price is pretty much always paid by the care delivery group. So I make these changes to care and quite predictably. Uh, I mean, it's like the summarizing you'll eliminate waste in your costs fall. The question is who makes the investment and who gets the savings? And it depends on how you're paid. Now. We published this in Harvard business review a few years ago. It's a crazy story, how it ended up there, but it's in Harvard business review, but laid out the basic layout of the thing. Uh, if I am paid fee for service, the only time that the financial incentives of mine are for areas where I reduce my purchase costs for the supplies I use, uh, it's actually a pretty darn narrow and that doesn't happen a lot. Yeah. It's, it's, it's, it's spelled 15% of the total waste opportunity when I model it, we could debate that by the way, it's about 15%. Speaker 2 00:51:34 So it's not trivial. I mean, it's still want to go for it, but of the total waste opportunity. It's about 15% of those supply chain efforts too. You got it. Supply chain is a classic example. And there, even if you're paid fee for service, it's going to benefit. You make the investment, you get the return. So you can recoup your investment. And hopefully with a little bit of overhead leftover to do the next round of good things, um, if you're paid per case, you can pick up a subset of clinical variation. It turns out that payment level is about Oh, 25, 30%. This is DRG DRGs. Yeah. You go to a per case payment system from a fee for service and you'll get the financial alignment for a bigger chunk, but about 45% of waste savings opportunities require that you bumped to the level of some form of shared savings. Speaker 2 00:52:28 Now my favorites capitation. Yeah. That's where you get full alignment. So the lion's share of the waste savings requires some sort of a capitated there seven or eight versions of capitation by the way. But some sort of a shared say saved means capitated environment. And by the way, some groups in the country are doing really, really well with that. The groups that go all in on care management, but you can't nibble at the edges, particularly you're either in or you're out or these groups demand capitation. And the reason is it works out so well. So I was working here, you know, for so many years at inner mountain, we had our own health plan. So we were effectively capitated for about 35% of our business. Oh, the tipping point when I modeled it mathematically, I done a mathematical model. I got 23% was a tipping point. Speaker 2 00:53:17 That's interestingly low. It is. Why is that? Well, it turns out that when I'm being paid fee for I'll make a margin, but the margins typically small three to 5%. Right, right. Um, what happens if you're capitated, what you're doing is eliminating whole cases, you're moving upstream. And one of your primary roles is to reduce hospitalization rates, you know, get better primary care. We publish this in jamming and, and, Oh, it was three years ago. Um, and we showed that by care management for chronic diseases, we could drop our hospitalization rate by 22%. This is what we published in JAMA. You'll see. Well, think about that. How did the hospital administrator thing think about that? Well, if they're on fee for service, they don't like it. Or if they're on per case, it don't make it either. I just nailed their budget. Speaker 1 00:54:08 Sorry. I remember your comment about icing the Hill. What do you want me to? Speaker 2 00:54:13 Yeah. I mean, if I go out on and salt Lake weather and I, the hospital was on a Hill and I put the hose out, nice the Hill, I'm going to get lost more volume into my ed. Speaker 1 00:54:22 It is though that the biggest opportunity, the biggest margin is in Speaker 2 00:54:27 And improving quality from a shared baseline. Yeah. And continuing to do that. So think of it. If I, if I do the case, I have all the expenses of doing the case. And if I'm doing really well, let's say I get a 20% margin. That's quite a high margin for a hospital to get 20% of the total spend comes to my bottom line. If I'm capitated, though, when I move upstream and I completely eliminate the case, how much of that do I get? I get a hundred percent. Right? So frankly, for a lot of those cases, by the way, I'm underwater, I actually lose money. Every time I do a case, that'd be for self pay or Speaker 1 00:55:04 Communicate a cost center rather than a profit. Speaker 2 00:55:08 So that 20% is being extremely generous. That's why it's. So when I modeled it, it came out at 23, we had big internal debates. The guys in finance were doing this kind of empiric model as opposed to my mathematical modeling. And they were getting around 30, 30, 2%. And we had a huge debate between 23 and 32, by the way. And it was great. Speaker 1 00:55:25 Fun were pretty darn low. So we were already, Speaker 2 00:55:28 We finally, after having days of debate, we looked at it all and said, well, it's somewhere in that range or shore. And we said, we're already at 35% at risk. So this is Speaker 1 00:55:38 The point I want you to clarify it for us is, is when you say capitation, right. People Speaker 2 00:55:46 My age, we'll think back to, Speaker 1 00:55:48 To the eighties and they'll think, gosh, what a disaster, because the cheapest way to take care of somebody with pneumonia is just let them Speaker 2 00:55:54 Die at home. So Speaker 1 00:55:56 You're talking about a strategy that's very, very different. What is that difference? And so here's the link. Speaker 2 00:56:04 So I lived through that same thing as you did. Um, and it came during the HMO movement as where we really studied a third two things you need to know. The first is, is today. We have much better measures of quality. So the idea is you actually measure clarity and make sure that the care delivered is as, as described, right? There are real issues around it. That'd be another lengthy conversation, but you can get there. The second big thing though, um, we did a series of trials back in those days. The most classic was the Rand study. And what it showed is under capitation care actually improves slightly. Now there were subgroups where it may have gotten worse, but overall there was a slight improvement in quality of care associated with that. Even back in the eighties, if you actually wanted to look at the evidence as opposed to the, the ideologic argument, right? Speaker 2 00:56:53 What lies underneath it, in my opinion, uh, this is when I'd be willing to fight for hard though. I think you have to understand the hearts of doctors. I have a joke. I say, say what you will about the human professions. We're really good at weeding out the social paths to knowingly withhold care from a patient to make money. You would have to be a sociopath and frankly, we're not, we select against it. We train the opposite way. It's heavily, heavily reinforced across your career. Do they occur? Yes. In my role, when I was at inner mountain or there were seven or eight times when I had to deal with people who really shouldn't be in practice, it was, it was quite rare. And when you find them guys, we have a moral obligation to take them out of practice. They shouldn't be represented in our profession. Speaker 2 00:57:37 They shouldn't be doing this to patients, to be honest with you in almost every circumstance. Well, in my experience, every one of them, they had, they were impaired. One fellow had had a traumatic injury and actually had some, uh, hard to detect traumatic brain injury left behind. And his judgment was shot. Start out as a good physician, then had an accident. Most of them were drug or alcohol impaired. Yeah, occasionally it got one that was judgment impaired. Those are the hardwoods, but we have an obligation to take them out. But the vast majority of our opportunity is with good, dedicated hearts in the right place, committed to patients. And we don't kill patients to make money. And so the underlying logic, I get the logic, it just empirically doesn't play through. Now, part of my job was to lay out the ethical choice clearly. So people could see it at a functional level, make it explicit, make it explicit, and then let their good hearts carry the day. And I've come to believe in physicians. And I believe in their hearts. I really do. I truly believe in them as a profession. I think it's the best profession in the world has ever seen. Speaker 1 00:58:44 We have been going, uh, Dr. James for about an hour now. And so I think this is a good place to stop or pause. And if in fact, uh, uh, we move on today, I hope you will come back. This has just been fascinating. And I, I can't remember a conversation that I've enjoyed more. So thank you. Speaker 2 00:59:03 Thank you. You know, I, I'm perfectly willing, I believe in this stuff. I mean, I drink my own Kool-Aid I really believe in it on the evidence. Our opportunities are massive. When you look at the data, we could be so much better than we are. No kidding. I mean so much better and Oh, by the way, I'll be cheaper. So our services will be easier for people to use along the way. Can you think of a better way to spend a career? No, I can't honestly create that kind of a world. We're creating a new future for humankind. Speaker 1 00:59:38 Sign me up. Well, Speaker 2 00:59:41 I can't, I, my trouble is I really believe this stuff. Speaker 1 00:59:44 No, I, I, I understand that and I feel it, and that is a fantastic place for us to end this discussion with that upbeat optimism about the future of healthcare and our future. And I could not agree more. I think we can get there. And when we come back again, we're going to explore lots of other topics because I know you have a fascinating mind and I, I love, uh, peeling back the layers of the onion to find out what's underneath. Well, thank you. Thanks. You're very kind. Speaker 2 01:00:19 Thank you. Thanks for the conversation as I love these conversations, especially with the knowledgeable, Speaker 1 01:00:25 Thank you very much. Welcome back. We're going to have a couple of, uh, Oh, I'm going to call them rapid fire though. That's unlikely to be how this plays out, but we're talking about evidence and, and, uh, you've said before that small portion of what we do in healthcare is really evidence-based. Can you unpack that? Speaker 2 01:01:01 Yeah, of course, I worked for 30 years at a system where we were building evidence-based best practice guidelines have personally participated in more than a hundred guidelines. I've also talked to colleagues and other settings who generate guidelines. Uh, roughly I think that we have evidence for best practice, about 15 to 20% of the time, 75, 80% of the time physicians and nurses can hold legitimate differences of opinion about what's best because there's literally no evidence, no evidence level one evidence is randomized controlled trials. Love it. When I can get that, I'm actually quite happy if I can get level two, um, those are observational designs of the best or quasi experiments, uh, prospective non randomized controlled trials, cohort studies, Oh, level two dash C or Q series level three. Evidence is expert consensus opinion. And when I say 15 to 20 I'm including level three evidence that makes me a little bit worried. Speaker 2 01:01:58 Uh, David Eddy, when he was at Stanford to my mind, fairly clearly demonstrated that level three evidence is not reliable. That expert consensus opinion is not a reliable basis for making best clinical decisions. Well, yeah, what you really want to do is set up an environment where you get good enough data coming out of your mass, customized that you get measurement about the outcomes of treatment. That's two dash C evidence. And that was one of our major goals. So that every case gave me evidence about best practice. So I could learn from every case. That's what eventually came to be called the learning healthcare system. Yeah. You build it right into your practice. Speaker 1 01:02:40 Yeah. Um, I'm going to ask you a question about another, uh, and maybe I'm misquoting you on this, but, uh, but I, I think I remember you saying this in one of your courses that you got a choice between doing things the right way and doing it the same way as a group, do it. Speaker 2 01:02:54 I that's something I have said. And the reason is this. If you do it the same way, you can apply the scientific method. Now, now when I say do it the same way, do it wisely the same way, of course, but you can apply the scientific method. You can measure outcomes and you can learn from your own data. If you don't do it in a consistent way, it makes it impossible summer. Yeah. Speaker 1 01:03:16 You have to compare against a shared baseline, not chaos. That's correct. Speaker 2 01:03:19 Yeah, that's correct. It's built into the design of trials. Uh, why is it? We use portal calls in the arms of trials. The reason is if you don't deliver the care in a consistent way, you cannot causally link treatment to outcome. Got it. You see the idea. Yeah. So it's a fundamental element of the philosophy of science that underlines, underlies our shared learning. And so, yeah, it's important that you do it the same as a group so that you can measure accurately. So if, I don't know today, I have some hope of knowing tomorrow. And when you look at the giant gaping black hole of lack of evidence that confronts real practice. Yeah. It's the only way that I can imagine that will ever fill that hole. Speaker 1 01:03:59 Yeah. Is there anything you'd do differently in your career or today to try and accelerate the process of adoption of these concepts? Speaker 2 01:04:09 In my opinion, the biggest barrier we face is a lack of adequate it systems underlying good practice. It turns out that eventually you're forced back to that electronic data system in order to record what you've done, and then be able to analyze Merton from what you've done. Today's current electronic medical records are designed with a different aim or different purpose. Their primary purpose is determined by administration who actually makes the buy they're designed for financial performance. And I would much rather see systems that were designed for clinical performance and let the finance drywall off of that. Is anybody working on that? Yeah. Some people are, uh, we personally were heavily engaged in one. What would it look like if you start with first principles and design an EMR for clinical practice, as opposed to for finance, if we didn't follow the old Cal path paved the cow path of how we handled written records originally. Speaker 2 01:05:08 Um, and so I've been engaged in some of those activities are kind of on the fringe. They're kind of nascent, but wow. They hold potential. I mean, imagine being in a practice where you're not spending two hours on the computer for every hour, you spend with the patient, the primary source of physician burnout, where your it systems actually supported your decision-making as you worked, or they could believe it or not. You can get them to the point where they can understand what you say and what you mean, but it requires a complete new design. And that, that will be a game changer, true transparency in clinical practice. Speaker 1 01:05:43 You think it's going to look like current systems. You think we're getting close to being able to capture voice and move voice to data. Speaker 2 01:05:54 We've actually been able to demonstrate that you can do exactly what you just said, that you can capture voice as data. Now there's a trick. Um, and informatics for the last 40 50 years, we've been studying something called natural language processing. Most commonly, we do it as you have a typed record, right? Microsoft word document. Uh, these days you can get to the Microsoft word document from spoken voice pretty effectively. What you're trying to do is extract what's called semantic, meaning out of a text document and that's natural language processing so far in 40 years of research, it hasn't been wildly successful. Oh, we've got some real successes. I don't want to take away from the good that did result, but the ability to actually step up and be accurate enough to use in clinical practice, it just hasn't hit that line. Well, as you know, we started in, in quality improvement. And one of the main tools we used for mass customization is something called a care process model. So you build an evidence-based best practice guideline. It's going to be a shared baseline. You build it into clinical workflow. So it doesn't rely on memory. Then you capture data around it, particularly variance data. You lay it out there and say, guys, please follow the guideline. But I have strong evidence that you can't write a guideline that perfectly fits any patient. And I do, by the way, therefore, doctor, you need to decide what Barry's right. Speaker 1 01:07:17 And by the way, that's not opinion. That's evidence. You have evidence Speaker 2 01:07:20 Evidence of that. We breed about five to 15% across more than a hundred protocols, but it was extremely rare to find a case where you followed a hundred percent of the time. You know, this as well as I do the patients who come to us for care different from each other. But I had those evidence-based best practice guidelines and there was a way to structure them in an it system. So I'm not talking about all of medicine. I'm just talking about workup of ruled out pneumonia. What happens when you do that? It reduces a clinical vocabulary. You have to manage, uh, from hundreds of thousands of terms, millions of terms down to a relatively narrow subset on average for a care process model that was maybe 5,000. And we ran some experiments with that. And what we discovered is when I got in that narrowed context, exactly the way a physician thinks about care or nurse thinks about care. Speaker 2 01:08:13 When I got into that narrowed and LPs started to work interesting, we actually published a paper on this. Um, the example we used was a evaluation of chest radiographs for ruled out pneumonia. Uh, we were capturing over 98, 99% of all data captured was computable data. Uh, and the computer in that narrowed context, slightly a star Trek computer. You could understand what you meant. Of course, we were thinking of it as a tool to deploy clinical decision support, where the computer becomes, not just a scribe. This is not some medical student, but a good resident level scribe feedback loop could give you a good feedback, right. And anticipate it slaps the right instrument in your hand when you reached out, because it's anticipating what you need, the right data, the right next step that slaps it in your hand. And wow. It was cool. Easy to fall in love with this one. Speaker 2 01:09:09 Oh, it had another major secondary advantage. Um, technically we wrote it as what's called a compiler. It was to give a computer language to physicians and nurses, easy to use. So you could write your own workflows, but you do, we should take it out of the middle, that giant bottleneck of it. You democratize it and put the control in the hands of the physicians and nurses of the clinicians at the front line. So you get to design your own work environment. We showed that our data capture rates went up close to a hundred percent currently they're at about 30 or 40%, by the way, this is being used anywhere. Uh, yeah, a little bit, uh, still experimental, but it is being used a little bit while you see things like that, I'm not sure what form it will take. Uh, but you know, it's going to change. It has to almost, Speaker 1 01:09:56 But let me, let me reiterate the concept and make sure that I understand it. The prerequisite is that you have to have a shared baseline. Oh yeah. That takes chaos down to a manageable number terms. That's correct. Uh, and if you focus on those in the AI Speaker 2 01:10:13 Works, got it. It massively simplifies it. Yeah. And so tools that are already fairly well-established, they suddenly started to work pretty well and the computer can anticipate what you mean. And it means you can extract semantic, meaning out of text and structure it. What it means is imagine a circumstance where most of what we do just in routine practice was computable data. Now AI moves to a whole new universe and its ability to support us. Now it's unthinking. I still need that expert mind. Yes. Remember that variance problem. Yeah. I can't write a guideline that perfectly fits any patient. I still need a thinking mind. That's my most important resource is that trained expert mind at the interface. And that's what you, Speaker 1 01:11:00 What I'm doing is focused just on that area where you can't standardize it. Speaker 2 01:11:07 It accelerates us as a profession. Our rate of learning goes way up. It enhances us. It makes us super humans almost. If you see what I mean, Holy cow, it's fun. Well, Speaker 1 01:11:19 We are super human in that aided Speaker 2 01:11:21 By protocols, Speaker 1 01:11:23 Shared baseline computer systems. We're able to focus on those things that are the most important in terms of caring for that patient. And one of those, by the way, as we will recall, is caring. Yeah. Having time to care is critical. Speaker 2 01:11:39 That's right. The human interaction, the clinician, patient relationship, number one thing, patients seek when they come in to see us. And that means we get to be human beings. So we sometimes call those hybrid systems. But what I have is that thinking expert then supported by AI, uh, supported by an it system, pulling the right evidence forward to make me more effective at helping me with the obvious stuff. The scutwork. So I don't have to do every little teeny thing, you know, allowing me to focus where I'm most effective. Again, we have not yet begun to understand how good we could be. Speaker 1 01:12:18 That's a wonderful thought. And that really is. That truly is. And I, I believe that I believe that we're capable of so much more. And the other thing that I, uh, I think is important to conclusion that I came to after being on multiple sides of the equation from, you know, private practice to large integrated system to the payer side. Yeah. Is it really is no enemy out there. It's mostly Speaker 2 01:12:45 Really good people that are trying to do the right thing that are Speaker 1 01:12:50 At times chasing misaligned incentives. Speaker 2 01:12:53 Yeah. Yeah. That's exactly right. You know, a funny thing though, Robert, I wish I was 23 again and just entering medical school. I mean, there are obvious reasons you'd like to be 23, again, I think this next generation we're going to see progress within the medical profession that John tar understanding will be unimaginable. We'll just be stunning as these tools come together all to be able to go on that ride. Speaker 1 01:13:19 Yes, indeed. I, you know, I absolutely agree that the, the progress that's being made in genetics and epigenetics and computer science in conceptualizing models that continuously learn yeah. Speaker 2 01:13:32 Care delivery science, um, yeah. It's going to be amazing. Um, and the level of care we provide is going to be night and day difference. I mean, we're good. Yeah. Yeah. We're the best the world has ever seen, but that's not Sam much compared to where we could be. And we're going to get there as a profession, all to be young again, and be able to live through that transition. Oh, I envy the, um, wish I could be there. Speaker 1 01:14:05 We can say is that you've been a big part of kicking off that, uh, journey. And, uh, I appreciate, uh, uh, life's work, you know, the advice that you've given to, uh, and you're not done yet, you know, you're up was even right. I mean, you're still out there advising and, and, and pushing. And that's the whole point I guess is yeah. While we're here. No, thank you. Thank you very much. And I appreciate the bonus minutes. You've been listening to the groves connection, your connection to the inside story on healthcare, featuring in-depth interviews with those who know you can find us on Apple podcast, Spotify, and anywhere else, you get your podcasts. If you like, what you hear, give us a five star review to keep the connection going and hit the subscribe button to be sure you never miss a beat. The groves connection is produced by Dr. Robert groves, original music editing and creative direction provided by Alton groves, production support, content guidance, courtesy of Janae sharp and Elizabeth Barrett. Thank you for listening.