Hey everyone, welcome to LabReflex. How you doing, man? As always I'm here with dr. Aakash. I'm Christopher Zahner. I Hey everyone, welcome to Labber Reflex. How are you doing, man? I'm doing good, Chris. Good afternoon. As always, I'm your director Aakash, I'm Chris Mersoner. I hope you have had a wonderful last week or so. Hope you have had a wonderful last week or so, man. I know that I know that summer is ending. Summer is ending school is starting. I think today was the first day of school for you guys. We we started last week School is starting, I think today was the first day of school for you guys. You started last week. Yep, it was first day of school. Both the son and the dad, that is me, were excited. Him for going to see his new friends and me being, Yeah, yeah, exactly. I mean he was he was kind of working with you a lot actually okay, you get to go to school and I get to relax now. Yeah, I was bringing him to work quite frequently. Yeah, that is that's a little bit tough actually. So That's a little bit tough. Yep, yes sir, you got it. You know, you can be a good dad and yet still want a little bit of space And I think I think that's okay You and I have been talking a lot, very unique about making the editing. so anyway, we've you and I've been talking a lot a lot about some Specific pathology things very unique sort of I Don't know inside baseball kind of things that we've been talking about a lot lately And so today's topic Came from an idea that I had had and you've got you know, I have talked about this a number of times But we kind of wanted to make it a whole episode today and that was about how we report Yeah, and I think it's timely for two reasons. values to our patients because what has happened in the last couple years is an expansion of Reporting to patients directly and so we think it's timely for us to have a discussion about that One being that, as you said, directly reporting to the patients is one thing, and then also the availability of these reports to the patients Yeah and then directly asking Dr. Google to retrieve whatever information is on that. There's a There's a miscommunication or there's a disruption of communication Communication or the disruption of what you and I what you and I, the pathologist, actually look from these numbers Yeah and what they are inferring from those numbers and sometimes there's miscommunication, shall I say, right? Right So I think that's a timely topic that we can discuss and basically let's start with a patient experience, right? Basically, let's start with a Patient experience, right when a patient is told to go get When a patient is told to go get their labs done, and of course they come to a laboratory and then the patient opens up his charts, right, Yeah and whatever the piece of information that he or she wants to find out and then they see a value that is highlighted, let's say, has an H or an L or a plus sign or a minus sign or a red sign, something highlighting that this is outside the norms, right? Yeah What does it actually mean? Does it mean that for the patient that what is wrong with me? Why is this thing high, low, or what it actually has to do with my health right now? So let's start from there. That's a great question, I think that a lot of us we recognize that there's a lot of nuance to Yeah, that's right. Any anything complicated but there's nothing quite so It doesn't communicate the nuance quite so well as a red H on your chart, right red and bold letters are some of the most effective communication protocols that medicine has derived, right and We know that you know, if you if you're in a in a clinical setting You know that if you're in a... And you're talking to your physician It's almost impossible to hear anything after the words you might have cancer, right? As soon as you hear that Yeah, yeah. You hear that it's like your brain shuts down and they're just... It's like your brain shuts down and there's just absolutely nothing communicated whatsoever. And so I think that it's really Important that patients are given information in a way that they can actually properly process and The way that we give them information now is not the right way to communicate that Agreed. we've built systems for Communicating to people who are detached from that information There are the clinicians there the nurses there the caregivers of other side sorts They're not the people themselves They're not the people themselves. and so we really need to be careful about how we And so we really need to be careful about how we communicate Communicate in the era of communicating directly with patients as opposed to with their care in the era of communicating directly with patients. So on that note, like, of course, these pluses and highlights are like up arrows, whatever you want to call them. They come based on a reference interval range, right? So I think a lot of our listeners, pathologists or non-pathologists, or even the ones that just want to listen to it, would like to know that what actually qualifies as a reference range Yeah, right or what does a reference range really tell us? Yeah, no, no, it's great. It's great. So so Yeah, no, no, that's 20 people. The way that we evaluate our tests is to try and create 95% of a group of Healthy people of non diseased people so we we go out we get 20 people that don't have disease presumably and we measure them for a specific thing and then And we measure them for a specific thing. And then you rotate, right? We remove the top one and the bottom one and we call that the reference interval or the normal range and so just statistically speaking, you know, if you if you were to take the The value of whatever it is Let's call it, you know Aakash peptide right and Aakash peptide we measured it and we got 20 people and Mm-hmm. And let's say, not just the concopatite, Then or rather let's say not just Aakash peptide but we also were measuring a bunch of other things, but we also were measuring a bunch of other things like a Aakash ace and Aakash ion and Aakash blah blah blah and we had 20 of these things that we were measuring And you're stone cold normal. If if all of those Measurable things were completely independent which they aren't obviously they're not, you know sodium potassium like, you know, sodium, potassium, you know, calcium. You know calcium these things are somewhat dependent These things are somewhat dependent, but if they were, But if they were you know, you might think, yeah, I do a CFP and a CDC You know And you might think I do a CMP and a CBC and a couple of the things and I get 20 and a couple other things, and I get 20 tests. Tests that I'm doing the chances that you'll have at least one of them be abnormal Yeah, yeah, mm-hmm. it's like 65% so a Normal and by normal in this case, I mean Just a regular routine checkup for a person who is a little bit older A person who is a little bit older might have 20. might have 20 tests and Better than better than a 50-50 chance. They're going to have something that is considered abnormal Better than a 50-50 chance they're going to have 5%, 20 tests. because 5% of the time and 20 tests that's just how statistics works That's just how... Yeah, and so they're gonna see a red H and they're gonna think well shoot and and it's a thing Yeah. A thing they may have never even heard of. They may never even heard of they pull up my chart and then all of a sudden that becomes magically They pull up my chart and then all of a sudden, that becomes magically the most critical and important... Number. Yeah, yeah. So basically, what this is, like, you know, you can still be a normal individual and still be outside that reference range. So having said that, it's not a usual reference range for you, The most critical and important but it's an, although it's an unusual, so unusual does not mean unhealthy, right? thing in their body Which brings us to this next topic, right? So that person, as you said, might be in the best of their health, might be the healthiest person in the family, right? But he is, he or she is not in the norm. So basically, now the normal needs to be defined properly, right? So what do we actually, what mean by normal, That's right or what does normal imply in these situations? Yeah, that's great. It's a great question. So the Yeah, it's great. This is a limitation of our language partly because Because it would mean used astronomical measurements. At the very beginning of this sort of concept normal actually mapped on more closely to What we might consider to be analytical variability It was being used in the context of understanding astronomical measurements Imagine a planet is in a specific location Imagine a planet is in a specific location and I measure where it is. And I look at it and I measure where it is and then tomorrow or maybe not even tomorrow And tomorrow, from another location, I measure. Maybe in a minute. I measure it again, you know, or in a second I measure it again or from another location I measure it and what happens is even if its ground truth is in that And what happens is, even if its ground truth is my measurement, spot right there My measurement there's just variability in measuring things and so analytical variability seeps into the things that we there's just variability, analytical variability. do and There's a there's a shape of that variability and that shape is a Gaussian distribution There's a shape of that variability, and that shape is a Gaussian distribution. That's what we call it now. And so we call that a normal distribution or normal error or normal range So we call it a normal distribution, or normal range. You should, about which, that you measure height. All of that stuff is talking about Essentially the ability for us to measure a thing and the distribution about which that the truth is So that's one way to think about normal There's another way to think about normal, which is a distribution of people about a thing So let's take height for example, if you measure height, it looks pretty big I'm close to what we call a Gaussian distribution And so you can take a group of people And so you can take a group of people, measure their height, measure their height and it kind of looks like a bell curve and so therefore we can think of that normal as a and it kind of looks like a velcro. And so therefore, we can think of that normal as a population reference. population reference range we can also think about your normal like what is it that you have so imagine that I measure your height and So think about, imagine I measure your height, and, or maybe better would be, again, we'd go back to Aakash Ace, you know. or maybe Better would be your I know again, we go back to Akasha ace, you know, and we measure that and And we measure that, and maybe you run a little bit lower than the mean. Maybe you run a little bit lower than the mean But then tomorrow you're elevated against the mean but you're still within the reference interval And then tomorrow, you're elevated against the mean, but you're still within the reference number. For you that's anomalous, but it won't look anomalous if we just use the reference interval For you? Yeah. and And then there's a point, or do I not have the second way? Then there's a fourth way to think about normal and the problem is that fourth way is the way that everyone does in fact Think of it and they think of it relative to disease. Do I or do I not have a disease? Where have I have I crossed the line of disease state? and so that the problem is we're doing the second way, which is the population reference and Patients in their mind are doing fourth way, which is am I diseased or not? They see a red H Yeah, yeah. So you're at eight more? They think son of a gun. I don't like that thing Whatever that thing is that's elevated or low and now maybe I have disease and that's a problem Yeah. Yeah, basically what you're trying to say is like, again, I am 5'8", right? So for my height, if I have, it's a very good height. Which is really tall by the way 5 8 is a beautiful height it just so happens that I'm also 5 8 Yes, sir. So let's say if we go outside and meet people who we see on a routine basis, and most of them are within our height range, and we would know that we are of a normal height. Whereas if we both get put with a group of individuals who are playing basketball, right, we would be the anomaly, right? Yeah Right, that's right Because we wouldn't even be close to their elbows sometimes, Right, absolutely. Yeah, exactly. Yeah that I would feel, right, right? So we would fall out of that Gaussian curve, or we'll be very at the steep ends of the Gaussian curves. That's right, yeah So are we normal in that scenario, or are we abnormal in the second scenario, right? Yeah, that's right So I think the normal, as you said, like, serves a broader purpose when you want to compare in a certain aspect, right? Your abnormal or normal depends a lot of times against what information, That's right Against against what background that you are comparing it to. That's right, exactly So having said that, where did this 95% number came into existence? Yeah, yeah, so what happened is the the field of statistics Yeah. What happened is that other fields will be capable of measuring very accurately. Was evolving more or less at the same time maybe a little bit later than some of our Other fields where we were measuring things again, like I said like astronomy, for example Really focused on the capability of measuring very accurately and so as a result these fields began to emerge kind of together and And so as a result, these fields began to emerge kind of together. And the concept of statistics, like normal, and precise, the concept of Statistical significance, this is another word like normal Significance means something extremely precise in the world of statistics that it doesn't actually mean regular parlance, right? That it doesn't actually mean the same thing in Regular parlance right when we're speaking and we say something significant. We mean it's maybe remarkable When we're speaking and we say something significant, it means maybe remarkable. We mean a word like that and yet statistically It means a word like that. And yet statistically significant just means, oftentimes, 95% fine in the sand significant just means oftentimes 95% it really is a line in the sand that doesn't actually that doesn't actually correspond to any disease. Correspond to any disease state and so when we map on to 95% On the 95%, we know that has any physiologic relevance. We aren't actually mapping on to anything that has any physiologic relevance It was just a convention that was being used in statistics. It was just a convention that was being used in statistics and then we just kind of adopted it in pathology And then we just kind of adopted it in the valley. There's no there's no you and you can come up with a fake thing like you could say There's no – and you can come up with a fake thing. Like, you could say, oh, we divide this by that. Oh, you divide this by that and you come up with something that's called You come up with something that's called standard deviation. Standard deviation, for example They are not physiologic. Those things are mathematical concepts. They are not physiologic. So they don't actually mean anything So they don't actually mean it. They're just numbers and I mean, I'm an engineer They're just numbers. And I mean, I'm an engineer. I like numbers a lot but they don't correspond to disease state in any meaningful way I like numbers a lot, a travesty, really, that we haven't divorced ourselves And that's kind of a travesty really that we haven't divorced ourselves effectively to talk about physiology effectively. So what we just discussed. So one of the possibilities that I can think of is that if an individual is tested multiple times against a different set of ranges over the time, Against Yeah just because now we are looking at the numbers only, right, and not inferring what this actually means on the hindsight, right, there's a possibility that this person might be a diseased person Yeah Yeah appear to be that's right. Yeah in one of the tests, right? Appear to be. Appear to be, exactly, right? But how do we reconcile with that idea now? Yeah, yeah, it's a real problem so the way that we've defined this is We take a hundred percent healthy people and measure them and then Yeah. Since we just – if we're measuring one thing and there's a hundred people We call five percent of them unhealthy so I mean imagine you just go to I don't know target and you just see people and they're walking around and They're healthy. They think they're healthy. But little do they know that we have some sort of capability of measuring them and Since we just decided that five percent of people are outside the reference range Five percent of the people who if we're measuring one thing and there's a hundred people at Target it's already, we're going to claim that five of them – We're gonna claim that five of them are sick that's how it's reported right now and Yeah. If we measure enough things almost everybody at Target is gonna be considered sick because you just measure enough things You're gonna be fifth percentile and something and so it's well You're going to be fifth percent – It's not 50% out because it's two and a half percentile on one side and two and a half percentile on the other side So high or low Yeah. But you're gonna be outside the reference range because five percent of the time you are and so we measure you enough times But you're going to be outside the reference range because five percent of the time you are. And so we measure you enough times. You're gonna be outside the reference range and you're gonna think you're sick You're going to be outside the reference range. That's interesting because now – see, again, this – Right how does it then matter in the practice? Because that we are also under an assumption that the clinician or the clinicians who are looking at these numbers know that reference range does not mean a diagnosis, right? It does not mean that inside – if you are within it, it's normal, right? Of course, yeah, yeah, right. Yeah That's the inference here, right? But how consistently is this nuance expected, right? Or experienced, right? And And what happens when the patient is – again, like when they receive their results. Yeah, I think Right, of course, yeah, yeah, right. Yeah Yeah, I think So as a clinician, we are supposed to understand this nuance and still tell them, be able to confidently tell them that, Yeah your result says red, but believe me, you are okay. You're you're totally fine. Yeah Totally fine. And because on the other flip side of that, they are the – the patient is basically sweating, right? Right, of course Right, of course. Yeah, I think so. There's two parts one Exactly, right? Yeah. I think – so there's two portions. Is the clinician part so we're communicating with clinicians and a lot of the time the clinicians have Knowledge of whatever we're measuring so think like sodium potassium a Lot of the elements of the CMP they have an intuition for it and they've been thinking about it a lot And so they have a sense for Whether or not something is gonna cause disease, but that's not true for everything I mean in coagulation, for example protein C and protein s some of these clinicians made have never seen a deficiency in protein We have – S before never yeah Yeah, yeah. And so it's not likely that they will have an intuition for every single one of the 10,000 tests that we do So it seems – patients come into the doc – And so it seems silly for me or from my perspective that we don't give them some Form of prompting they aren't given any information about the criticality of this result that seems silly Okay, so that's the first thing the second thing is we also now have a group of people who are seeing their labs for the first Time that have absolutely no intuition for what we're describing. So we're talking about a statistical thing and They're thinking they're being tested for disease because that's what they are there for Patients come in to the doctor not looking for some sort of statistical anomaly. That's not why they're there They're there to see if they're healthy or not And so when you see red and the only thing you care about is whether or not you're healthy Then you're gonna freak out and I think that that's totally logical So for two reasons this matters one I don't think it's fair for clinicians to be expected to remember every last Nuance of why we do a specific test and what the values really mean. And the second thing is patients now that they see all this stuff patients now, they see a lot of information to give more useful information. They're being given too much information in a way That's a for in a in a format that's not useful for them And so I think we owe it to them both groups to give more useful information So what do you think we should do differently? well, I think The first thing that we should do is we should be thinking critically about Obviously the names that we use I'm really happy to see that we've moved to reference interval on reference range as opposed to normal range Some of our analytes don't actually Distribute in a Gaussian format, right? If you if you measure in a population, they don't look Gaussian. So So even using normal range is a dumb thing because even from a statistical standpoint, Even using normal ranges is a dumb name because even from a statistical standpoint It doesn't look like a Gaussian distribution. So normal has even in the statistical sense has no relevance it doesn't look like a Gaussian distribution. So normal has – even in the statistical sense has no relevance. So that's number one So that's number one. I think that we ought to be mapping on to what we consider to be outside a reference range and I think that we ought to be mapping onto what we consider to be outside of reference range. Yeah. And we ought to map onto a disease state. we ought to map on to a disease state, so we ought to be using guidelines more frequently and So we ought to be using guidelines more frequently. And maybe instead of using red and an H and an arrow or L, Maybe instead of using red and an H and an arrow or L we ought to be thinking about guidelines and then we ought to be thinking about guidelines. And then we might, on the back end, say they're outside the electroceiving hole. We might on the back end say they're outside the reference interval But they're not in the disease state. So I think that that's the first thing and They're not in the disease state. So I think that that's the first thing. And the second thing – and this is a hot take here, I'm telling you right now. The second thing and this is a hot take here. I'm telling you right now. It's super hot take I It's a super hot take. I, as a laboratory, think we ought to be doing more lab tests for our patients. As a laboratory and think we ought to be doing more lab tests for our patients big surprise. I know like super big surprise Super big surprise. I know. I'm like, super big surprise. um Yep. the reason I think that we should be doing more lab tests is because The reason I think that we should be doing more lab tests is because we ought to be having We ought to be having patients measure themselves against themselves patients measure themselves against themselves. Yeah. The best reference range for me is me not a random assortment of The best reference range for me is me, not a random assortment of other people You know other people who are considered healthy who are considered healthy. And so if I know my own values then I can trend those and I can understand what's normal for me Yeah. If I know my own values, then I can trend those and I can understand what's normal for me and what is likely causing this disease. And what is likely causing disease? Now, that's not true for every specific thing that we measure. Now that's not true for every specific thing that we measure some things do in fact matter that we compare against a population Some things do, in fact, matter when we compare against a population. But for the most part the things that we do care about But for the most part, the things that we do care about, I ought to be able to know for myself. I ought to be able to know for myself and right now the way that we measure people we're trying to minimize those costs And right now, the way that we measure people, we're trying to minimize those costs. But I don't think that's actually the driver of healthcare value. But I don't think that's actually the driver of health care value Removing tests and getting a good baseline for me Removing tests and getting a good baseline for me is probably the dumbest thing that we can do as a health system. is probably The dumbest thing that we could do as a whole system Yeah. Because now we are just doing a kind of a factory thingy. Right. Right? Right, that's right That's right. I mean, it would fit because he is a medium-sized individual, but compared to a bespoke T-shirt that's actually built for him, where if he wears it and if his wife or his spouse tells him, oh, by the way, I think you are getting chunkier, he gets it. He gets the idea, yes, because this shirt that I was wearing was made for me. Exactly It was a custom-made one. And it fit before and now it does it And it's not fitting before. So that means I am truly getting a weight. Exactly Exactly Getting weight. Versus like a T-shirt that was made for 500 individuals, which was generic and which everybody was wearing and fitting just fine. Generic sure That's right, yeah, that's exactly right Right? We couldn't identify whether it was an issue to start with. That's right. The majority of costs in a health care system. First of all are not lab tests They are the interventions based on those lab tests and the fewer tests that you do The higher the probability that you're gonna freak out when you have one that's elevated or low, right? Yeah. That's just the way that it's gonna work That's just intervention, whether it's a therapy, whatever it was. And so if we had a bunch of tests and we knew your shirt size, for example We knew exactly what all your measurements were gonna be then we could we could craft something perfectly for you And then we would know when you moved out of that range and then we would know most likely what we should do to affect some change whether that's a Medical intervention whether it's a therapy whatever it was and I think that's a far better way to treat our patients And I think that's give them the information they need. Give them the information that they need then they can trend them themselves And they can trend themselves, information in the hands of others. This is far more, you know hand information in the hands of the patient and allowing for more autonomy Yeah. And that can be achieved, as you said, by more testing and more testing and distributing those test results into smaller groups where they matter, rather than generalizing the idea of that result. Yeah, I totally agree well, thanks man, I really appreciate it. I think this has been a valuable Discussion as far as where these numbers kind of came from there's a big difference There's a big difference, Philosology. philosophically in the clinical pathology versus an atomic pathology world the majority of pathologists are AP focused and Yeah. Yeah, that's true. The majority characterization of that business. AP is really focused on the identification of a disease state and the characterization of that disease Whereas CP is much for focused on statistics and analysis of numbers and those don't actually always Whereas CP is much more focused on... Mean the same thing they feel like they ought to and this word normal really screws that up and so I I want us to sort of be thinking long term about how we And so I want us to sort of be thinking long-term about how we... Solve that problem because I think right now we're confusing a lot of different senses of normal and it's wrong Yeah. Well, thanks so much man, I appreciate it you have a great week buddy. All right. Thanks y'all Thank you so much, Chris. You have a great week, buddy. You too, sir. All right. Thanks, y'all.
