#22 – Is Modern Medicine Still Evidence-Based? Reclaiming Evidence, Restoring Clinical Wisdom

Welcome to The Trip Lab 0:00

[music] Welcome to the trip lab kitchen table conversations about integrative medicine and psychedelics. [music] I'm your host and attending physician Dr. Mariela Wood. Evidence-based medicine is essential. It's the reason medicine has advanced as far as it has. Why we survive diseases that would have been fatal just a century ago. And why modern healthcare has been able to reduce suffering at a scale that was once unimaginable. And some of the most powerful medical advances weren't even high-tech. So things like handwashing or clean drinking water and sanitation that dramatically altered human survival. And alongside those foundational public health innovations, evidence-based research gave us life-saving surgeries, antibiotics, cardiovascular interventions, and medications that have unquestionably changed outcomes. So let me be very clear at the start of this episode. This is not a rejection of evidence-based medicine. This is a scrutiny of what evidence-based medicine actually is right now and how we can reclaim evidence in a way that matches the pace of our technological advancements. What I've witnessed over the past decade, and something that began long before I even graduated medical school, is a quiet but important shift. Evidence-based medicine has increasingly become reductionist medicine. I first began to think about this and seriously question this during my surgical training. I actually started out in general surgery residency before pivoting to my current career in integrative medicine. So on ICU or critical care rotations, we would scrutinize the literature in painstaking detail. Decisions like normal saline versus lactated ringers were debated intensely with statistical analyses parsed down to fractional differences. One option would be chosen because it was slightly better in the data. And to be clear again, that process is not wrong. That rigor is part of what keeps patients safe. But watching all of this play out made me step back and ask a deeper question. What do we actually

Evidence-Based Medicine vs Reductionism 1:58

mean when we say something is evidence-based? And how much clinical meaning are we assigning to very small statistical differences? So that question stayed with me and then co happened. So suddenly we were facing a novel disease with no established evidence base. There were no guidelines, no long-term outcome data, no randomized trials to learn on. So clinicians and patients alike were reaching for anything that felt potentially helpful, often highdosese vitamins, supplements, and lifestylebased interventions. We even played around with highdose vitamins given through IVs in the co ICUs, something that I never thought I would be doing in general surgery residency. So that got me curious. I started reading and what I found surprised me. Many integrative therapies had comparable levels of evidence to interventions we routinely use in conventional medicine and sometimes even more. Take blood pressure as an example.

On average, many anti-hypertensive medications lower systolic blood pressure by about 7 to 15 points. And that is meaningful, but so does a Mediterranean lifestyle. So do interventions like regular physical exercise, stress reduction, and even certain supplements like co-enzyme Q10. And these lifestyle or integrative options actually get to the root cause and change the system that's been damaged where blood pressure drugs just solely lower the blood pressure. Now, just lowering the blood pressure does have its benefits in preventing kidney disease and earlier heart attacks. But if we're not truly treating the root cause of why high blood pressure manifested, something else or worse will get you because the system was not fixed. Just a blood pressure number was. So, why don't we talk about these lifestyle or integrative therapies in modern medicine spaces? Why don't we learn about them in medical school? Why did I just have one single hour of nutrition training throughout the 20,000 hours it takes to go through medical school and residency? And it's not because it's not effective. It's money.

There was no financial incentive to rigorously study lifestyle interventions at scale. Drugs generate profit. Lifestyle does not. And so the evidence base itself becomes skewed, not because something doesn't work, but because it isn't lucrative to study. I dive deeper into the history behind this in episode 15, which is my deep dive series intro. The episode's called How Big Pharma led Used to Call Eastern Medicine Alternative, if you want a more historical lens. But in this episode, we're going to focus on now. We're going to talk about what evidence-based medicine was meant to be, how it slowly became overly reductionist, and why that matters, especially in chronic disease.

We'll examine how guidelines are created, how clinical significance gets lost in statistical language, and why patients so often feel unwell even when they're told their labs are normal. And then we're going to rebuild. We're going to talk about what a more integrated, systemaware, and clinically wise version of evidence-based medicine actually looks like. One that patients are asking for, that many physicians feel but don't always have language for, and that I believe represents the future of medicine. Before we go any further, I want to briefly acknowledge the name of this podcast, The Trip Lab. While the name obviously nods to psychedelic medicine, which is a major focus of this show, a trip also means something broader. It's an exploration, a willingness to step outside of familiar frameworks and examine what happens when we look more closely, more curiously, and more honestly. That is what I intend to do with this podcast and my career. To explore the frontiers of medicine and elsewhere, to question what we assume we already know and to better understand how systems connect rather than treating them in isolation.

Life is a trip and meaning is made through exploration, reflection, and intentional change. But back to this episode, one core idea that should lead us to examine evidence with more scrutiny is the difference between statistical significance and clinical significance.

Statistical vs Clinical Significance 5:55

We use these terms all the time in medicine, but I don't think we pause often enough to ask what they actually mean in practice. Statistical significance tells us whether an observed effect is unlikely to be due to chance. It answers a very narrow question. Is [clears throat] this result mathematically real? Clinical significance asks something very different. Does this meaningfully change a patient's life? Those two things are not the same. And yet in modern medicine, we often treat them as if they are interchangeable. A result can be statistically significant but still be clinically trivial. With a large enough sample size, even very small differences can reach statistical significance. And in isolation, those numbers can look impressive. But when you zoom out and ask whether that difference actually changes how a patient feels, functions, or survives, the answer is often much less clear. This is where I first started to feel uneasy during my training. In critical care and inpatient medicine, we would agonize over studies comparing interventions that differed by fractions of a percent. One fluid showed a slightly lower mortality rate than another, or an intervention nudged an outcome just enough to cross a p value threshold. And again, this matters. Precision matters, but it also made me ask, are we mistaking statistical cleanliness for clinical impact? And beyond that, are we even asking the right question?

Many of these studies are designed to isolate a single variable and measure a single outcome. But patients don't live in single variables. They live in systems. A modest change in one lab value or one endpoint may not translate into a meaningful shift in the overall trajectory of health. This becomes especially important when we talk about relative risk versus absolute risk. A distinction that I think is rarely explained to patients and frankly not always sufficiently interrogated by clinicians either. Relative risk makes effects look dramatic. So a therapy that reduces risk by 20 to 30% sounds powerful. But when you look at the absolute numbers, that reduction may only represent a change from let's say 5 to 4%. That may be statistically impressive, but clinically it is a very different conversation, especially when you factor in side effects, cost, and long-term burden. We see this across medicine. Medications are often framed as outcome changing based on relative risk reductions, while the absolute benefit to an individual patient may be modest. Meanwhile, we have interventions that do affect multiple systems like sleep, nutrition, stress physiology, and inflammation that are dismissed because they don't fit neatly into reductionist study designs, even when their real world impact may be equal or greater. This distinction becomes especially important when we look at how efficacy itself is defined, particularly in oncology. Many cancer drugs are approved by the FDA based on demonstrated efficacy with acceptable toxicity. But what often gets lost is that efficacy does not necessarily mean improved survival.

For years, a significant number of oncology drugs were approved not because they extended life expectancy, but because they met a surrogate endpoint known as partial tumor response rate. So this meant the drug was shown to shrink the primary tumor by more than 50% in volume. And on paper that looks like a success. Tumors are smaller, imaging improves, biomarkers move in the right direction. But when researchers later examined long-term outcomes, many of these drugs did not meaningfully improve overall survival, tumor shrinkage, while visually compelling, turned out to be a poor proxy for whether patients actually lived longer or better. Now, this is not a critique of oncology or drug development. It's just an illustration of a much larger issue. We often mistake improvement in a measurable outcome for improvement in a meaningful one. And this happens because surrogate endpoints are easier to study. They're faster to measure and more compatible with reductionist trial designs. But honestly, patients don't ultimately care whether a tumor shrinks by 50%. They care whether they live longer, suffer less, and maintain quality of life. And this brings us back to relative risk versus absolute risk and to the broader question of how evidence is framed. A therapy can look impressive when

Chronic Disease as a Systems Problem 10:07

outcomes are presented in relative terms or when surrogate markers improve. But when you zoom out and examine absolute benefit, system level impact, and lived experience, the story changes. So the questions I keep coming back to are these. Does this intervention meaningfully change a patient's life? Does it address the system or does it simply shift one measurable outcome? Because evidence-based medicine was never meant to be about chasing statistically significant numbers in isolation. It was meant to guide decisions that improve real human lives. Another foundational issue in how we generate evidence is who that evidence is based on. Randomized control trials rely on strict inclusion and exclusion criteria. And there's a reason for that.

These criteria are designed to isolate variables. They allow researchers to answer a very specific question. Does this intervention work under controlled conditions? And again, that rigor is essential. Without it, we would not know whether a drug or intervention has true effect at all. But the phrase isolate variables is the key because what it also means is that the evidence is often generated in highly selective populations. Patients who have multiple chronic conditions are excluded. People on multiple medications are excluded. Pregnant women are excluded. Older adults are excluded.

Anyone who introduces noise into the data is removed. So what we are left with is a version of the human body that is cleaner, simpler, and far more uniform than what real life looks like. So doctors do look at a study and ask whether the results are translatable to broader populations. But in my opinion, I don't think that this step is interrogated deeply enough. Guidelines are written, recommendations are made, and those recommendations are applied widely, often to patients who look nothing like the population being studied. So this is the paradox. We must study interventions this way to establish causality. But doing so severely limits real world applicability. Human beings are not controlled experiments as much as we want them to be and as much as we must study them this way right now to advance medicine. But every patient comes with a unique combination of genetics, comorbid conditions, medications, environmental exposures, stress physiology, sleep patterns, nutrition, and lived experience. Yet we often act as though evidence generated in a narrow slice of the population can be cleanly extrapolated to everyone else. I think this limitation becomes even more exaggerated when we talk about women's health. For decades, women were not included in clinical trials due to concerns about hormonal variability, pregnancy risk, and reproductive potential that led women to be left out of drug studies and biomedical research well into the late 20th century. As a result, much of what we consider foundational medical evidence was generated primarily in male bodies and then generalized to women after the fact. And even today, women's health remains significantly underfunded and underresarched relative to disease burden. Conditions that disproportionately affect women like autoimmune disease, chronic pain syndromes, functional GI disorders, and of course, hormonal disorders are often less wellstudied, less well understood, and more likely to be dismissed when objective findings are limited. And this is not because these conditions are less real. It's because our research framework have historically struggled to study complex system level and hormonally dynamic states. So when patients, especially women, are told their labs are normal, but they don't feel well, that is not a failure or imagination on their part. It is a failure of the evidence base to reflect the full complexity of their physiology.

And this is where cracks begin to show in a purely reductionist interpretation of evidence-based medicine. Again, not because the evidence is wrong, but because it's incomplete. Even when evidence is strong, the model we use to interpret it increasingly does not match the reality of modern disease. Reductionism is not inherently bad. It is the foundation of how we learned anatomy, physiology, pharmarmacology. You break down the system into parts, study one variable at a time, establish causality. That approach is why we have antibiotics, why we have surgical breakthroughs, and why we can treat acute disease with precision. But the more time I spend in medicine, the clearer it becomes that many of the conditions driving suffering today are not linear problems. They are system level problems. And this isn't just me as a sole doctor postulating. Research is emerging consistently that validates what many functional integrative clinicians have been circling around for years. Chronic disease involves networks, not isolated organs. So take mental health. We are watching the science around the gut microbiome and psychiatric symptoms evolve in real time. Human studies continue to show associations between gut microbial patterns and depressive symptoms. And we have meta analysis of microbiome target interventions like probiotics and symbiotics that suggest modest but meaningful improvements in depression and anxiety in certain populations. Is this definitive? No. The field is heterogeneous and messy. But the direction is clear. The gut, immune signaling, metabolic pathways and brain function are not separate categories.

They are interacting systems. Another example we can think of is cardioabolic disease. So the older model was almost entirely lipid centered. But the modern evidence base increasingly supports chronic low-grade inflammation as a major driver of atherosclerosis and cardiovascular risk independent of LDL. And we have major scientific statements and reviews that are now explicitly emphasizing inflammatory signaling pathways like IL1, IL6, CRP as part of the cardiovascular story. We have outcome level trials that made this hard to ignore. When anti-inflammatory pathways are targeted in carefully selected populations, event rates can shift even when cholesterol itself is not the variable being manipulated. So, modern medicine is evolving. It is beginning to name what many systemoriented clinicians have been saying for a long time, which is chronic disease is frequently multiffactorial, network-based, and interdependent. But here's the tension. Our healthcare structure and research methods have not evolved at the same pace. We are still deeply siloed. Specialization has been one of the greatest engines of clinical advancement. So cardiology, gastronurology, neurology, these fields have made extraordinary progress because experts dedicated their lives to a nearer slice of the human physiology. And even within those fields, subsp specialcialization has driven precision like electrophysiology, interventional cardiology, heart failure, etc. So that is good. We need it. But as we get more specialized, we also need the parallel evolution of a different kind of clinician. Not just primary care generalist, but what I would like to call explorative generalist. Clinicians who are trained to think in systems, to

Guidelines, Public Perception, and Curiosity 17:00

track patterns across organs, to hold complexity without collapsing it into premature certainty. People who can integrate emerging science across fields and ask what connects this rather than what silo does this belong to. This is one reason functional medicine has resonated with me and a lot of people. And at its best, it is a framework for exploring system level physiology. So, gut immune brain connections, inflammatory drivers, metabolic resilience, endocrine signaling, nutrients efficiency before disease becomes diagnosible on a narrow lab threshold. But we also have to be honest here. Functional medicine has been tainted in some places by wellness culture and its own version of reductionism.

Sometimes the underlying pathophysiology is extrapolated beyond current evidence. So claims outrun data and sometimes a complex system is reduced to a single villain or a single magic intervention. I think a perfect example of this is the longevity conversation around NAD. So we do have legitimate mechanistic reasons to care about NAD biology. NAD is involved in energy metabolism, DNA repair, cellular stress response. NAD levels appear to decline with age in multiple models. So reductionism and marketing can easily turn that into NAD declines with age, therefore supplementing NAD is anti-aging. And that is an interesting hypothesis, but it is far too simple for the complexity of aging physiology. And when you look at the human clinical literature to date, the more honest conclusion is this. We can often raise NAD related biomarkers, but meaningful downstream clinical benefits are not consistently demonstrated yet. I do have a whole podcast about NAD in this topic if you want to check it out. But my bigger point is this. Reductionism can creep in everywhere. Not just in super specialized conventional medicine when we mistake a biioarker for the whole patient, but also in integrative and functional medicine spaces when we mistake a mechanistic pathway for a guarantee of outcomes. What we really need is a medicine that can explore without concluding too early. A medicine that can hold the rigor of evidence-based practice while also respecting that chronic disease is systemic, multicausal, and personalized, especially in an era where research is rapidly proving just how interconnected the body actually is. And this brings me to medical guidelines. So in modern medicine, organizations like the AAP, American Academy of Pediatrics, the American College of Cardiology, American Heart Association. So these societies publish clinical guidelines that are widely considered the gold standard of care. These guidelines shape how we practice. They inform board exams, malpractice standards, insurance coverage, quality metrics, and clinical decision-m across the country. And again, to be clear, guidelines do matter. They help standardize care. They reduce extreme variation. They protect patients from idiosyncratic or unsafe practice. In many ways, they do raise the floor of medicine. But somewhere along the way, the word guideline began to be treated less like a guide and more like scripture. There's this unspoken culture in medicine that says, "If it's in the guideline, then it's correct. If I deviate from the guideline, I'm practicing bad medicine." And that mindset can quietly transform clinicians from thoughtful, curious scientists into algorithm followers, executing protocols rather than actively engaging with evidence. So let's talk about how guidelines are actually created. They are written by panels of physicians and subject matter experts who review the available evidence and then come together to make recommendations.

This process is rigorous, thoughtful, and often painstaking. But here is the key. Guidelines are evidenceinformed, not purely evidence dictated. Within a single guideline, recommendations can be supported by vastly different levels of evidence. Some are grounded in large high-quality randomized trials. Others are supported by smaller studies, observational data, mechanistic reasoning, or importantly, expert consensus. And expert consensus is not a flaw. We want experienced clinicians weighing in when evidence is incomplete. Medicine cannot wait decades for perfect data before acting. But we have to take a step back and remember that this is still just a group of people making a decision based on their experience and expertise. Let's not forget that they definitely are subject matter experts. But when a recommendation supported by consensus is treated the same as one supported by robust outcome level evidence, a breakdown occurs. At the end of the day, these guidelines are still the product of humans making decisions for large heterogeneous populations based on incomplete and evolving data. This doesn't make guidelines wrong, but it does mean that they're not infallible and they are not substitutes for clinical judgment. And guidelines were never meant to replace thinking. They were meant to support it. And this matters enormously in complex chronic or system level disease where rigid adherence to algorithms can obscure nuance, suppress curiosity, and prevent clinicians from asking whether recommendation truly fits the patient that's actually sitting in front of them. When guidelines become the ceiling rather than the floor of care, medicine loses something essential, not safety, but wisdom. And then of course we have on the other end of the spectrum another breakdown in how we understand what evidence-based actually means and that's in public perception. So this is what we see. A scientific paper is published. It has a carefully worded conclusion in the title. But what is not in the title are the clear limitations and very specific conditions under which those conclusions apply. But that part gets buried and a headline gets written in the news. Then it continues to be reduced and reduced and often pops up as truth in more news outlets, wellness blogs, social media accounts, and eventually gets entirely stripped of what it actually means. So what started as a narrow scientific finding turns into a broad definitive claim. And we see this all the time. I think nutrition is probably one of the most obvious examples. Let's take eggs. One year eggs are bad for cholesterol.

The next year, eggs are back. Then they're neutral. Then they're protective. And the public, understandably, wants a final answer. Are eggs good or are they bad? Should I eat them or avoid them? But that framing misunderstands how science works. The question isn't whether eggs are

Integrative Medicine and Low-Risk Exploration 23:38

universally good or bad. The question is for whom, in what context, at what dose, alongside what other dietary and lifestyle factors? Medicine and really most complex systems that show up in life, so science, philosophy, and we'll just say everything, don't operate in binaries, but culturally, we crave certainty. We want checklists. We want to conquer one problem and then move on to the next and never have to revisit it again. But if we truly did operate this way in the world, we would still think the world is flat. Science shouldn't and doesn't work that way. Evidence evolves, understanding deepens, new variables emerge. What we know today is not the vital word. It's a snapshot in an ongoing process. And this is where the public conversation around evidence often goes wrong. Not because people are uninterested in science, but because they've been taught to expect certainty where none actually exists. And this brings me to my favorite part of this conversation. The space where curiosity lives. The space between what we know and what we're still exploring. In integrative medicine, we spend a lot of time in this space. Historically, many of the therapies we explore were labeled quote unquote alternative. But what that really meant was that they existed outside the dominant research and funding structures of conventional medicine, not that they were inherently unscientific. So practicing in this field means living with a lot of emerging evidence and that naturally raises an important question. How much evidence is enough to recommend something? And that is a fair question, but I would argue that there's an even more important one, one that keeps medicine both ethical and open-minded. Could this intervention plausibly cause harm? And if the answer is yes, there is meaningful risk, unknown toxicity, or the potential to interfere with essential treatment, then we absolutely need more data before recommending it. That is non-negotiable. But if an intervention is low risk, biologically plausible, and does not meaningfully threaten patient safety, the calculus changes. The question becomes not, is this proven beyond a doubt, but might this help? Is this reasonable to explore? Is my patient interested in this? And I'll say more commonly, patients bring me these ideas. So, the interest is already there. And also, what is the financial cost? Is it reasonable to spend money on XYZ intervention, taking into account its potential to help even if it's uncertain it will or not? This is where integrative medicine often diverges from rigid interpretations of evidence-based care. not abandoning rigor but by incorporating risk context and patient values into decision-m I think all this is a little bit more philosophical so let me give you a common example let's take acupuncture for chronic pain or insomnia the data here is mixed but consistent in one important way acupuncture does appear to help some people effect sizes are modest results may vary by condition and individual and mechanisms are still being explored likely involving neuroimmune modulation, indogenous opioid release, and autonomic regulation. But the risk profile is extremely low when performed by trained practitioners. Serious adverse effects are rare. There's no systemic toxicity, and for many patients, the alternative is long-term pharmacologic management with wellocumented risks. So, in that context, the question isn't whether acupuncture is a universal solution. It isn't. The question is, is it reasonable to explore a low-risk intervention that may improve symptoms, especially when conventional options are limited, poorly tolerated, or unwanted by the patient. So, this is not reckless medicine. This is ethical curiosity. It is acknowledging uncertainty without being paralyzed by it. It is recognizing that the absence of definitive evidence is not the same as evidence of absence, especially when harm is unlikely and patient autonomy is respected. And this framework applies far beyond acupuncture. It applies to mindbody practices, light-based therapies, nutritional interventions, and lifestyle changes that affect multiple systems at once. But the key is not to overpromise. So not to collapse complexity into a single fix and not to let curiosity turn into certainty too quickly as well. So I think good medicine lives here not just integrative medicine in the balance between humility and exploration between knowing what we do know and staying open to what we have not fully mapped out yet. So this is where we are now. But to understand where medicine needs to go, we also have to look backward and forward at the same time. Little trippy here. We need to revisit clinical wisdom that predates modern medicine. Wisdom that came from physicians like Hypocrates and from ancient healing systems like Aruveda and traditional Chinese medicine. And at the same time, we also need to look towards the future toward new research methods, new frameworks, and emerging ideas like precision medicine. Before our current model of modern medicine, healing largely came from two places. what came from the earth and what came from ourselves. So food, herbs, plants, and the human capacity to think, reflect, regulate attention, and alter consciousness.

Those altering consciousness practices were often organized through rituals, ceremonies, and what we might now label as quote unquote magical thinking. But when you strip away the language and symbolism, much of this was actually early mindbody medicine. It was an intuitive understanding that the body, mind, and environment were inseparable. Then over time, medicine became increasingly siloed and eventually placebolinded randomized control trials

Reimagining the Future of Evidence 29:28

became the gold standard for evidence. And that model did give us incredible advances. But it also introduced a problem. Many of the most important drivers of health cannot be studied this way. How can you placelind meditation? How do you isolate nutrition when it affects every system simultaneously? How do you study herbs which contain hundreds of biologically active compounds as if they were single molecule pharmaceuticals? So, a single medication is one molecule designed to target one pathway. A single herb may contain hundreds of interacting compounds working synergistically across multiple systems.

Setting both of those using the same reductionist framework simply does not work. This same challenge also applies to psychedelics in mind body medicine. We cannot truly place blind a full psychedelic experience. I will just state the obvious here. You know if you've blasted off into another dimension or not. Micro doing psychedelics may be different and fit better into our current models of study and I'm doing an entire podcast episode on that soon which includes how the placebo response plays a role there. But my point here is that some interventions fundamentally resist the structures we've built to study drugs. And even beyond that, we're now realizing we can't really study drugs this way either. As we've explored throughout this episode, the body cannot be reduced into isolated organs. Chronic disease is systemwide. The heart is not just the heart. The brain is not just the brain.

We see inflammation, metabolism, immunity, and the neuroindocrine system overlapping constantly. Our study designs haven't fully caught up to this reality. So, how can we change this? And we're going to just postulate a little bit here. First, I'm thinking of patternbased evidence instead of outcomebased evidence. So, what if instead of asking does this intervention improve a predefined outcome? We instead asked what patterns shift when this intervention is introduced. Chronic disease doesn't move in straight lines. It moves in constellations. We have sleep changes, energy shifts, inflammation markers fluctuate, mood, cognition, digestion, and resilience all evolve together. So we could begin by studying interventions, especially lifestyle, mind body, and multicompound therapies by tracking systems level pattern shifts over time rather than forcing them into single endpoints.

So I think this would involve longitudinal dense data from smaller cohorts within person change over time, not just population averages and pattern recognition across systems rather than binary outcomes. Next, I'm thinking of precision curiosity trials. So personalized and of one at scale. The future may not be larger randomized trials. It may be thousands of deeply characterized individual experiments. So imagine structured, ethical, and of one trials where patients explore low-risk interventions like nutrition, supplements, mindbody practice while tracking individual biomarkers, symptoms, and functional outcomes over time. I think that this framework could treat each patient as their own control, allow interventions to be explored responsibly, generate real world data about who benefits under which conditions, embrace variability instead of trying to eliminate it, and instead of asking does this work for everyone, we ask for whom does this work for and why. That, in my opinion, is precision medicine without pretending certainty too early. But if medicine is going to evolve, we cannot abandon rigor. But I do think we need to expand our imagination. The future of evidence-based medicine is not less science. It's science that can hold complexity. Science that respects systems. Science that allows exploration without prematurely declaring victory. So not just a return to the past. This is a synthesis. And I think it's already beginning. So when I ask the question that's the title of this podcast, is modern medicine still evidence-based?

The answer of course is not a simple yes or no. Evidence-based medicine is not broken, but it has been narrowed. And in that narrowing, we have lost something essential. Evidence was never meant to replace clinical judgment. It was meant to inform it. It was never meant to silence curiosity. It was meant to guide exploration. And it was never meant to reduce human health to isolated variables. It was meant to improve real human lives. So, as disease has become more complex, more chronic, and more systemic, our approach to evidence must evolve alongside it. That means holding rigor and humility at the same time. It means honoring what we know, questioning what we assume, and staying open to what we haven't fully yet mapped. So, reclaiming evidence is not rejecting science. It's practicing science more honestly. And restoring clinical wisdom doesn't mean going backwards. It means remembering that medicine has always been both a science and an art. And the future of medicine depends on our ability to hold both. So, thank you for taking this trip with me. An exploration meant to poke holes in familiar frameworks, question what we think we know, and open our eyes to connections that weren't obvious before.

So, I'll end with this. Stay curious. Keep dripping. Thanks for listening to the Trip Lab. If you liked this episode, please subscribe and share so we can get the conversation started about integrative medicine and psychedelics to destigmatize it and fully explore what this could mean in the world. [music]