Much of emergency medicine rests on evidence that is less definitive than we might think. Ken Milne, MD, founder of The Skeptics' Guide to Emergency Medicine, joins Dr. Matthew Strehlow to challenge assumptions about clinical guidelines, research quality, and what constitutes good evidence. Drawing on three decades of clinical experience and his current doctoral research at Oxford, Milne explores the limits of evidence-based medicine, the role of patient preferences in clinical decisions, and the promise and risks of AI in scientific peer review and patient care. It's a conversation about intellectual humility, the pressures shaping modern medicine, and why even experienced physicians should keep questioning what they think they know.
Much of emergency medicine rests on evidence that is less definitive than we might think. Ken Milne, MD, founder of The Skeptics' Guide to Emergency Medicine, joins Dr. Matthew Strehlow to challenge assumptions about clinical guidelines, research quality, and what constitutes good evidence.
Drawing on three decades of clinical experience and his current doctoral research at Oxford, Milne explores the limits of evidence-based medicine, the role of patient preferences in clinical decisions, and the promise and risks of AI in scientific peer review and patient care.
It's a conversation about intellectual humility, the pressures shaping modern medicine, and why even experienced physicians should keep questioning what they think they know.
GUEST: Dr. Ken Milne is a Canadian emergency physician, medical educator, and founder and host of The Skeptics’ Guide to Emergency Medicine (SGEM), a podcast dedicated to critically appraising research and advancing evidence-based emergency care. He is widely recognized for his work in knowledge translation, promoting critical thinking, and helping clinicians apply medical evidence to everyday practice.
HOST: Dr. Matthew Strehlow is a Professor of Emergency Medicine at Stanford and serves as Vice Chair for Innovation and Clinical Improvement. His work focuses on improving patient care through system redesign, global health initiatives, and advancing emergency medicine education.
Dr. Matthew Strehlow: In medicine, we talk a lot about following the evidence, but the evidence isn't always as clear as we would like it to be. Studies conflict, guidelines change, and even the best available evidence still has to make sense for the patient sitting in front of you.
Few people have made a career of examining that gap as closely as Dr. Ken Milne. Known as a professional skeptic, Dr. Milne is an emergency physician and the founder and host of "The Skeptics' Guide to Emergency Medicine," where he has spent 14 years critically examining the evidence behind emergency medicine practice. He is also a senior associate editor for Academic Emergency Medicine with a unique perspective on how evidence is evaluated for publication and how it holds up in real-world clinical practice.
Dr. Milne has an MBA from the Ivey Business School and is now pursuing doctoral work at Oxford focused on artificial intelligence. Today, we're talking about skepticism, uncertainty, and what it takes to turn evidence into better decisions,
Dr. Milne, Ken, welcome.
Dr. Ken Milne: It's so good to be here. You know, listening to your intro, it's like I'm not often referred to as being a professional skeptic. That would imply that I'm being paid. Oh, no, I do this because I love it. I'm an amateur. I could still compete in the Skeptical Olympics.
Dr. Matthew Strehlow: I'm going to put you in the Michael Phelps, Katie Ledecky, gold medal Skeptics Olympics.
Dr. Ken Milne: Did you know that I used to swim?
Dr. Matthew Strehlow: No.
Dr. Ken Milne: Oh, yeah, no, I swam, and I made it all the way to the Canadian team and the 1988 Olympic trials for Seoul, South Korea, as a 200 meter butterflyer.
Dr. Matthew Strehlow: Wow.
Dr. Ken Milne: We're just discovering this now.
Dr. Matthew Strehlow: Incredible. Yeah. That's incredible.
Dr. Ken Milne: Yeah, so I thought, "Oh, maybe you did a background check on me or something." Yeah, no, I used to be a swimmer.
Dr. Matthew Strehlow: Ken, you've built this global reputation on being a professional skeptic. It's a role that requires challenging authority and questioning the status quo. Was there a moment or a person earlier in your life or career that made you decide that being the questioner and not just the practitioner was going to be your defining path?
Dr. Ken Milne: Wow. You know there's been so many people that have helped me along the way and molded my skepticism, but I really think that if you're looking for my superhero origin story of skepticism-
Dr. Matthew Strehlow: Absolutely...
Dr. Ken Milne: It probably came out of never maturing out of that... You have children, right?
Dr. Matthew Strehlow: Yes.
Dr. Ken Milne: So when you're about three or four, you get this one question over and over from children, and what is that question?
Dr. Matthew Strehlow: Why?
Dr. Ken Milne: Why. Yeah. Why is this? Why is the sky blue? And so I was going around going, "Why, why, why?" And I just, I never grew out of the why. And I just have so many questions, and every shift I'm on, I'm like, "So why do we use this treatment? What's the primary literature show on that? What’s the diagnostic accuracy of this test?"
It's the why that drives me, and I've been a lifelong person who keeps asking why.
Dr. Matthew Strehlow: That skeptical mindset, that why, is really powerful. But you practice in a community hospital, right? Not a large academic ivory tower. And at the community hospital, that rubber meets the road. Can you give us an example, maybe the most common example that you see or something like that, when the best evidence collides with the reality on the ground, the resources that are available, and the timeframe in which you have to make that decision?
Dr. Ken Milne: So Matt, I think it really comes down to thinking about the definition of evidence-based medicine. And evidence-based medicine just isn't about the evidence. It's not about the published literature. The literature can certainly guide our care, right? It can inform our care, but it doesn't dictate our care.
So just because there's an RCT that was done in some ivory tower academic center that said, "In this patient population, thou shalt do this," or if there is a, oh, guideline. And you know what I like to say about them. Guidelines, it's in the name. They should guide your care. They're not God lines, right?
It's not a dictum; you must do this. And so, getting back to that evidence-based medicine philosophy and thinking about it as a Venn diagram of three circles, one circle absolutely is the evidence, and we should look for the best evidence, the most relevant evidence for the patient in front of us. But then when I'm working in the community hospital, I have to use my clinical gestalt and the resources that I have there, and most importantly, ask the patient, what do they value and what do they prefer?
And perhaps in my community, which is a small, wonderful community, and I grew up on a farm just outside of this community. It's called Strathroy, but we call it Strath Vegas, baby. And you know, I grew up just outside of Strathroy. And so, the patient population, their expectations on what they're expecting and the care that they're expecting may be different than somebody who walks into, you said ivory tower, and there's not a lot of towers here in Stanford, but there's one big one that we couldn't go up today.
Dr. Matthew Strehlow: No entrance...
Dr. Ken Milne: Hoover, Hoover is it?
Dr. Matthew Strehlow: Hoover Tower.
Dr. Ken Milne: The Hoover Tower. It was closed at 4:00. Sorry we missed it. but, you know, that ivory tower, those patients may have different expectations than the patients that I see. And so, applying that is always a local context So you take the best evidence, use your clinical judgment, and then talk to the patient and ask them.
And the easiest way to figure out what patients value and prefer, just ask them, right? And so, the Canadian system where I obviously work based on my lack of accent, and you have an accent, based on where I work, their expectations might be different. I don't have a CT scanner in a lot of the places I work.
Dr. Matthew Strehlow: Wow.
Dr. Ken Milne: And so, the expectation, Matt, may be I just wanted to come in, have a kind, caring physician. And sure, there might be some clinical guideline or some clinical decision rule that suggests getting a CT. But having that conversation with that patient saying, "Well, if we get that CT, we're going to need to ship you out," which we will do.
If it's necessary, we will recommend it. But the patient might be a farmer, and they may decline it, or it might be terrible outside with the weather and snowing. And if we're going to be a Bayesian about it, what's the pretest probability that you're going to lose two highly skilled paramedics and a nurse and a patient going for a CT scan based on low level of evidence?
Dr. Matthew Strehlow: Right.
Dr. Ken Milne: And so, it really... So the thing that comes up over and over again when I work in a community hospital is how do we apply the evidence to the patient population we have in front of us? Which I think you should be doing at your center as well. What's the evidence show? Who are the patients I'm working with? And what resources do I have available to me to meet their needs?
Dr. Matthew Strehlow: So, you're talking about that uncertainty at the bedside and how the evidence may not always translate, but the evidence has more uncertainty than even just that. It travels to other parts of it. So, there's uncertainty when you're doing your research.
There's uncertainty when you're sitting on and evaluating the evidence and talking with other reviewers or decision editors about whether something should be interpreted this way or interpreted that way. It follows through to the clinical care, like you mentioned, and then it also follows through even to the courtroom, where two reasonable physicians sometimes can sit down and say, "Is the evidence really clear that one pathway or care decision should have been made versus a different decision was acceptable as well?"
So, thinking about that, how has that uncertainty with evidence played out in your work with Skeptic's Guide?
Dr. Ken Milne: So early in my career, I was much more certain that there was an answer, and the answer was right. And there was the correct answer, and we should all be doing it. And the further I got in my career, you know, after 30 years, is that there's an answer, but it may be different for each individual because we don't treat a population. And this is one of the limitations of evidence-based medicine, is that it looks at a population, a cohort, and it has an average, a mean, a median or something, and you get a point estimate of an effect size and a confidence interval around the effect size.
But it doesn't tell you if it works for you, that patient that's in front of you, and that's what the patient cares about.
Dr. Ken Milne: And so, the longer I've gone... the farther I've got into medicine, and the more I've learned about, you know, most of what we do, it's a super majority.
Most of what we do, we're standing on pillars of salt and sand. Because if you go back to the original research and say, "Hey, what is informing my care? Is it high-quality evidence?" And in fact, there's, there's a famous professor from Stanford, from where we are right now, Stanford, right? Mm-hmm. John Ioannidis. And he published a paper, and I'm not talking about the one where he says most research findings are false, okay? That has issues. But he published a meta-analysis of meta-analyses. So, in other words, an umbrella review, where he and his team searched for studies, meta-analyses, that looked at emergency medicine only.
So, they searched the world's literature, found out all these things, and then they said, "How much of the literature, what percentage of the literature supports the treatment, has high-quality evidence that it results in a patient-oriented outcome of benefit?" That it works, basically, right?
Do you know what the answer was? Do you know the number? Do you want to guess? Here we are.
Dr. Matthew Strehlow: I know it's low. Low.
Dr. Ken Milne: It's not a round number, I'll tell you that. It's not a round number. It's not a nice, round number. It's not zero. It's not 100.
Dr. Matthew Strehlow: Let's say, 17%.
Dr. Ken Milne: So, 17 is a great number because, you know, it takes 17 years for high-quality, clinically relevant information to make it to MedGuide.
Dr. Matthew Strehlow: That's what they say anyways.
Dr. Ken Milne: Eh, that's what they said in 2011. But no, it's not 17. It's not my second favorite number, which is 11 because I like... You know, this is Spinal Tap. This goes to 11. We're going to turn it all the way up...
Dr. Matthew Strehlow: Oh, we seem to be going down. So we went from 17 to 11 to five to three. Okay.
Dr. Ken Milne: 3%. Actually, it's 2.7, but so what? I'm rounding up. 3%. Now I want to be clear though, Matt. That means, how we should interpret that is, that only 3% of what is published is high-quality evidence to support what we do in emergency medicine. That should not be interpreted as 97% of what we do in emergency medicine doesn't work. It's just we don't have good evidence that it does work, and that's an important nuance to realize, because there could be a lot of stuff in that 97% that does work. We haven't done the right studies with the right methodology, with the right patient-oriented outcome to say, "Aha, we have the answer. Yeah, it does work."
Dr. Matthew Strehlow: So, if we have evidence for 3%, I want to challenge you on something else you said.
Dr. Ken Milne: Oh, challenge me.
Dr. Matthew Strehlow: You said guidelines, and I know that you said you don't always love guidelines, right? But in some ways, guidelines are saying that, "Hey, 97% of the time we don't have clear evidence. Let's get people that have spent a lot of time evaluating the evidence, have a background or expertise in clinical care, and say what do they think is the best thing in this 97% realm to do in these certain situations?" Why is that not the way to think about it?
Dr. Ken Milne: Because I think that moves from evidence-based medicine to eminence-based medicine, and I don't need a group of gray hairs and no hairs opining on something to tell me how to deal with an individual patient's needs.
If we want precision medicine and they're always talking about genetics and perfect and, you know, making it specific, how about we just talk to the patient in front of us and ask them what they value and prefer if we don't have strong evidence to say thou shalt or thou shalt not? And what you see in, a lot of guidelines, and I'll use the AHA, and I'm not picking on the American Heart Association or American Stroke Association, but they've done research on it.
And one of the research studies looked at their guidelines and their recommendations, and out of all of them, and there was something like 3,000 or 5,000 guidelines.
Dr. Matthew Strehlow: Wow. I didn't realize it was that many.
Dr. Ken Milne: Or recommendations, sorry. Recommendations in the guidelines. Out of the thousands of recommendations in the guidelines. You know how many were level A based on high quality, at least two randomized controlled trials, blah, blah, blah, blah, blah? 10%. But that means, but that means 90%...like, why publish it? It's just a lot of noise. No, it's-
Dr. Matthew Strehlow: eminence.
Dr. Ken Milne: It's eminence, and it's not signal. And we need to have the humility in medicine. We, and I'm including me in there, to know that we are biased and that we are fallible. And just because you say, "Well, in my clinical experience," isn't that great?
My clinical experience might be different than your clinical experience, and there's a whole field of literature called psychology that says we have recall bias. We remember our wins. We have selection bias. We don't have perfect recorded memories of every patient. "Oh, well, I always use this when I pack nosebleeds, and TXA always works."
Really? Let's do a structured audit of all the nosebleeds you've seen and use TXA and find out is that an accurate number, and I would suggest it's likely not.
Dr. Matthew Strehlow: So, if we're, if we are going to be skeptical of the guidelines, we are going to be skeptical of the people that are preeminent in looking at the literature and making recommendations. Are we going to then move to a situation where we're just taking AI's recommendations instead? Like we're going to substitute the guidelines of individuals for the summaries of AI?
Dr. Ken Milne: So, we don't want to go from one argument from authority to another argument from authority. Right? That's a logical fallacy and it's an informal logical fallacy. And just because an authority said something doesn't make it true, but it also doesn't make it false.
It could still be true. But I'm after the truth, the quote unquote truth, you know, the best point estimate of an observed effect size with a confidence interval around that point estimate. I want to know what's the truth lie for this intervention or this treatment and stuff like that. And so right now, we could do studies, and every study has limitations.
We can look to eminence and clinical practice guidelines and those things that can help inform our care and stuff like that. But you're asking, are we just going to outsource our intelligence to AI? I hope not. I don't recommend that. I think that AI can be a tool that can be supportive and augment what we do, and unload some cognitive tasks like dictations and things like that.
But I'm really concerned, and this is why I'm doing research in this area. I want it to elevate the human condition. I want it to be used ethically and responsibly for better care, to improve care so patients get better care. And we need to figure out and navigate how to use this new powerful tool to do that, and we're still in the middle of it.
Dr. Matthew Strehlow: I'm curious about the research you're doing at Oxford and the thinking you're doing there. Tell us a little bit more about the framework you're using to think about AI in clinical care.
Dr. Ken Milne: Well, my actual thesis, my hypothesis I guess, is looking at AI plus evidence-based medicine, right? And how we're going to use it as a tool.
And obviously evidence-based medicine is a huge topic area, and so I've narrowed it down to how AI could be used in the peer review process. So how are we using AI to support peer reviewers? Because there's lots of research out there already that says, you know, you get this paper sent to you from this journal, and they say, "Please don't..."
Well, they don't say please. They say, "Thou shalt not upload this to a ChatGPT or some large language model." And if you ask people, "Oh yeah, they're, you know-
Dr. Matthew Strehlow: They're doing it.
Dr. Ken Milne: They're doing it, right? So, we’ve got to figure out how to do this safely and ethically and responsibly, and intellectual property, and all of those types of things need to come into it.
And so I'm looking at, I guess the first thing is what do peer reviewers and editors think about using AI? That's the starting point. But then actually doing a prospective meta-analysis, which is a little different than most people. They do retrospective.
Dr. Matthew Strehlow: Right.
Dr. Ken Milne: But prospective means we don't have any information on this, so I'm going to create this prospective meta-analysis, a priori set the limitations, the inclusion, exclusion criteria on how LLMs, not just AI in general because that's a huge term, but large language models could be used for the very narrow part of helping support a peer reviewer to answer some of the questions and some of the difficulties and challenges that exist in peer review right now, and then see if that improves the quality.
Dr. Matthew Strehlow: Do we need to slow down our use of AI then? Let's try to keep it narrow for right now. In the peer review and research evaluation process, or evidence-based, or evidence evaluation process, do we need to slow down until we have these recommendations and the right people spending time thinking about it and how we should be using it?
Or is it impossible to slow that train?
Dr. Ken Milne: Seems like a gotcha question coming from Palo Alto. Let's just go forward. What is it? Break things and what is it? Break things and fail fast. Fail fast. And so what am I going to do? Push back against Palo Alto? I'm your guest here. No, you know, it's being adopted. It's happening. And like most technologies, whether it be ultrasound... Oh, let's put ultrasound probe on everything, right?
Dr. Matthew Strehlow: Right.
Dr. Ken Milne: You know, there'll be the early adopters, the enthusiasts. I learned this in my MBA, you know, there's this curve that shows about the early adopters and stuff and then it's going to settle down to a point where we're looking at how we're going to use the tool in the best way possible, and it may not be the way we thought it was going to be.
I mean, I gave rounds at Stanford this morning. It was an amazing experience, by the way. But how many of the residents had cell phones? All of them. And how many used it to make calls? Probably close to none of them. None of them. Because why are you calling me when you could text me, right?
It's very strange to call. But we call them phones, and yet they don't use them as phones. No, no. And so how we're going to use this new technology and thinking about the future, I mean, it's an exciting time to be in medicine.
Dr. Matthew Strehlow: It is a very exciting time to be in medicine. I am not convinced that we couldn't slow down with some adoption.
Dr. Ken Milne: Putting genies back in the bottle is very hard.
Dr. Matthew Strehlow: It's very difficult. You know, maybe one of the only times that we've actually slowed things is during when we were first starting to sequence the genome, and we started to make decisions about whether we wanted to put rules in, in place. Slow down for a couple of years and get international rules in place. It does feel like we are not in a situation right now where we can slow this down, and the genie or genies might be out of the bottle.
With that in mind, though, we have a lot of work to do. So where do you think we need to put our energy and effort as a specialty of emergency medicine when we think about AI adoption into our clinical arena?
Dr. Ken Milne: So, as you look at adopting artificial intelligence into the practice of emergency medicine, we should look at it as we don't just go out there and start using a new drug that hasn't been through FDA, right? Right. Like I'm in the US, so it has to go through some regulation or something like that.
And just because it's FDA-approved doesn't mean it works. It just means it's FDA-approved. And just because it's not FDA-approved doesn't mean it doesn't work. They may not have applied for FDA approval.
And there's other organizations in other countries that approve drugs and don't approve drugs. But I'm here in your house. And so would you like to take whatever AI tool instrument you're using and not just go, "Oh, let's have, " intervention bias. It's sort of like if you go back to-- Do you remember "Jurassic Park"?
Just because we could doesn't mean we should. Nobody stopped to think, "Hmm, should we really make dinosaurs?" What are the downstream problems? And so, before we start releasing AI into the medical world, I think we should have some guardrails up and be cautious. And that's one of the reasons I'm doing this PhD in AI. I've got 30 years of clinical experience, right? But I don't have the experience in AI, and it's being used. And so we need to make sure that we have some kind of, I don't want to say oversight, but just some-- a pause to reflect and say, "Should we put some kind of AI robot," and it doesn't have to be a robot, but some AI chatbot at triage?
And what's the training data? What's the inherent bias? We know most research is done on men. We know more of it's done on white men, and we know that people can present differently. And so, any of those biases that are in the training dataset, because we excluded women, we excluded socioeconomic, status, certain people and stuff like that, if you have that baked into your triage system, guess what you're going to get? Exactly what you designed.
And so I'm really concerned about that. So we should test it. We should have a hypothesis that, hey, maybe, maybe doing AI for triage can be more efficient, but what's the net impact? What's the impact on the person being triaged and the speed?
And what's the impact on the waiting room? Because it doesn't happen in isolation. This is one of the things I love about emergency medicine. I'm responsible for all the people in the emergency department, and every other specialist thinks, "Oh, well, this stroke should be seen first. This heart attack should be seen first."
We've got code sepsis. If we had code paronychia and resources put into that, we would have great metrics on code paronychia. Code paronychia. Right? And so you could, you could quantify that. So, if we're going to employ AI tools, and whether that be at triage, AI scribes, clinical decision instruments, metadata so that when that patient comes in, it searches their whole electronic record.
And you think just because, this is called automation bias, just because it's in your electronic med-medical record, is it true? Well, no. We have evidence that people cut and paste all the time, and eventually... And you saw the game of, the game of, telephone that we played today. It did not go well. So, you can get a man who in their past medical history has a hysterectomy. And I mean biological man, those errors get into it, but because it's in digital form. And they get perpetuated on and on and on. It's in digital form, so it must be true, and who am I to question it? And so, I would encourage you to be skeptical of everything, of course, and say, "Really?" And review it, and verify it, and make sure that it's accurate and true.
Dr. Matthew Strehlow: So AI has potential.
Dr. Ken Milne: It does.
Dr. Matthew Strehlow: We need to potentially take a pause or think about it and approach its integration into care very thoughtfully, systematically, with skepticism.
Dr. Ken Milne: And evidence to inform how we're going to use it, and then it's a society's question on how it... Shouldn't be my decision, shouldn't be your decision, it shouldn't be the medical community's decision.
It should be society's decision because it's about their care. Shouldn't we ask the patients, "Do you feel comfortable talking to an LLM chatbot? Do you feel comfortable having an AI scribe record your conversation with your physician? How much, how much of your data is going to be up in the cloud somewhere that's going to be, like, recorded and retrievable and stuff like that?" Privacy, all these things come into it.
Dr. Matthew Strehlow: I'm always shocked at how much people are willing to share or just say, "Yeah, yeah, record it. It's all fine. Everything's being recorded." And so maybe there are not enough skeptics out there in the general community.
I'm also concerned about the adoption of AI and what's driving that, and it feels often, at least in my early experience, that it's being driven by financial decisions, that it's being driven by the promise of being better than without the evidence to do that, and it's not necessarily being driven by the POO, or the patient-oriented outcomes.
Dr. Ken Milne: I love talking about the POO, the patient-oriented outcomes.
Dr. Matthew Strehlow: Is there a way for physicians to engage and make it about the POO and not about the dollars?
Dr. Ken Milne: Well, I think that one of the things in emergency medicine in particular is that we seem to have a real commitment to social justice.
We come into this profession that we will see anyone at any time for anything. We are the light in the house of medicine that is always on, and hopefully we see those people without judgment. We're there to care, not to judge, right? And I think that's really important, and I think that what you're bringing up is, do we have an obligation as a profession, and specifically in emergency medicine, to advocate to make sure that that happens?
And my answer is yes.
Dr. Matthew Strehlow: You have been in so many different roles over the years, but interestingly-
Dr. Ken Milne: I've worn a lot of hats.
Dr. Matthew Strehlow: You've worn a lot of hats
Dr. Ken Milne: I got this hat today from the Stanford bookstore. We walk into the Stanford bookstore, and I'm like, "Wow, I'd really like to get a hat."
I like getting hats from places I go and stuff like that. I've got a Top Gun hat. I've got, you know, all these hats, this collection and stuff. And we walk in, and what's right inside the door? Nerd. Right in the front. It's like they were expecting me. It's a Stanford nerd hat. I'm, like, in nirvana here.
Dr. Matthew Strehlow: Well, the hat looks great on you.
Dr. Ken Milne: Thank you.
Dr. Matthew Strehlow: You also took the time during your career arc, m- pretty recently, to go back and get your MBA. Talk to us a little bit about what you learned from the business training or community that could apply to the business of healthcare and help us think about how we can improve this time to adoption of best practices, this focus on the patients instead of focus on as much the dollars.
What are the lessons that you can apply or take from that business community?
Dr. Ken Milne: There were some really great lessons from the Ivey Business School that I went to, and, it was a really, really outstanding program. It was an executive MBA, and it was a straight up MBA. It was not a health MBA.
I didn't want to be surrounded by a bunch of doctors and administrators. Okay. There was one other doctor. I've been an administrator. I've been around doctors. I wanted to be with a bunch of business people because, you know, I'm outside my comfort zone, and I want to learn their language. To learn the language and the nomenclature because they have different control systems that are motivating the C-suite than motivates us, right? And we're, you know, like, "Patients, patients, patients."
And we've got to find a way to work together with administration so that we can meet the patient's goals, which are our goals, but also meet those of the healthcare system, and it's a business, and the operations, and the throughput, and the metrics, and all those things. I was chief of a department for 10 years, and then chief medical officer for the hospital for 10 years, and what I didn't know at the time was how to best speak to the chief financial officer, chief technical officer, chief operations officer.
All of these people have their own language, and I feel quite comfortable talking about medicine and diagnostic criteria for various medical conditions and how we apply it. But boy, a spreadsheet? Cash flow? Governance? It's a foreign language versus operations, right?
And I'm not one of those physicians, and, you know, there are a few, and I'm not going to name them. But there are a few physicians out there that think that because they're really smart, and they are, and really intelligent, and they are, in one area, that somehow magically transfers to every other area.
Dr. Matthew Strehlow: That's a very Palo Alto thing, by the way.
Dr. Ken Milne: That they can be experts at everything. I have a very narrow window of what I'm really good at, and the rest of it, I'll either learn it... So, I'm going to school again for my seventh university degree. Because I want to figure out AI. I could just go around the world opining on AI as an EBM expert. I don't want to do that. I want to know the why. Okay, I'm getting back to the why.
And maybe it's an over-exaggeration because I struggled through school and I had difficulties, that I keep doing this, but I really want to know that I'm standing on firm ground.
And if I don't know, I'm very comfortable saying, "I don't know. I don't have a... I don't have to have a position on that." And nobody should believe me, no matter what I'm talking about, they should be skeptical, but they shouldn't believe me just because I'm a doctor talking about the business world. But now I have an MBA and some experience. I can sit at the table, and I can have those conversations. And it's an executive MBA, but I don't have to actually do the accounting spreadsheet. But I can examine that spreadsheet, ask reasonable questions about that spreadsheet, and figure out, how are we going to take the budget we have to provide the care we need?
And if I can have that conversation with the rest of the administration team, now we're on the same page, right? Right. Now we're on team patient.
Dr. Matthew Strehlow: Team patient. It does make sense in that context. You have spent a lot of your life focusing on knowledge translation, which in some ways is about communication. And here you're again talking about your MBA as a way of improving your communication skills with other key stakeholders and leaders within the healthcare systems in which physicians operate and patients get their care. As you look at your entire career arc then at this point, from ER doc in a community hospital to a podcaster-
Dr. Ken Milne: You forgot family doctor.
Dr. Matthew Strehlow: Family doc.
Dr. Ken Milne: Family physician. Started as a family, rural family doc.
Dr. Matthew Strehlow: Rural family doc. I wanted to be a family doc at first.
Dr. Ken Milne: It's fantastic because you have to know so much about so much, you know, the whole journey, but also being rural, right? You're it. You're it. You're the ologist. You're the cardiologist, the respirologist, the endocrinologist, the pediatrologist, the orthopedist.
Dr. Matthew Strehlow: The everything-ologist.
Dr. Ken Milne: You're the ologist because that's all you're going to get in a rural area is me, right? And so, yeah, it was wonderful. But yeah, sorry, got you derailed there. I did do family medicine before I trained and got my board certification as an emergency physician.
Dr. Matthew Strehlow: Right. So, family medicine to emergency medicine to podcaster to professional skeptic to MBA and now to Oxford to study and help us figure out a path forward with artificial intelligence. What's the through line? What's the single thread that, like, weaves through all of these different experiences and roles and expertise that you've developed, that you want to pass on or make sure that the next generation of physicians and clinicians carries forward?
Dr. Ken Milne: Well, I think it gets back to being a lifelong learner. And, you know, there is a thing that, you know, that whole Dunning-Kruger thing. You know, the more you know, the more uncertain you become, and then, and then you learn more and more and more, and can be a content expert on a very narrow area.
But I think not losing that wonder of, "Why is the sky blue? Why is that? Why, why does the moon look the way it looks?" Look out into the world and be curious. And I think as long as you maintain that curiosity, you won't lose that joie de vivre of life.
Dr. Matthew Strehlow: Well, that's a great way to end.
Dr. Ken Milne: Wait a minute. That's the way we're going to end?
Dr. Matthew Strehlow: No. We have to end on a lighter note. Tell us one of your classic dad jokes.
Dr. Ken Milne: All right. Classic, just kills out there, this dad joke. So this is a Christmas dad joke. Here we go. Why is the letter E the only letter in the alphabet to get a present from Santa? Why the letter E is the only letter and none of the other letters got a present from Santa?
Why? Why? Why E?
Dr. Matthew Strehlow: Tell me, Ken, why E?
Dr. Ken Milne: Cause all the other letters were on the not E list.
Dr. Matthew Strehlow: Oh, I like it. There we go. Nailed it.
Well that's a wrap for today's episode. I want to thank Dr. Milne for his time and insight and his expertise and effort. If you liked today's episode, don't forget to subscribe, leave a review, and share it with a colleague. And as always, we want to hear from you. Send us your questions, ideas, and feedback in the link in the description.
Thanks for tuning in. We'll see you next time. Until then, keep taking care of anyone with anything at any time.
Dr. Ken Milne: How was that? Do you like the dad joke? Yes. That was a good dad joke?
Dr. Matthew Strehlow: They were not E.
Dr. Ken Milne: Oh, I have other ones. How does Santa keep track of all the chimneys he's gone down? He keeps a log.