CEimpact Podcast

Are We Overprescribing Statins?

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We delve into the implications of the recent study published in JAMA Internal Medicine, exposing how older risk models overestimate cardiovascular risk by about 50%. This overestimation has profound implications for primary statin use, insurer policies, and regulatory practices. Our discussion highlights the need for updated guidelines that reflect the most current evidence, ensuring better patient care and aligning clinical practice with the latest scientific findings.
 
The GameChanger
Adopting the PREVENT equations could significantly refine statin prescriptions, ensuring millions of adults receive appropriate cardiovascular risk management.
 
Guests
Geoff Wall, PharmD, BCPS, FCCP, BCGP
Professor of Pharmacy Practice, Drake University
Internal Medicine/Critical Care, UnityPoint Health

Jake Galdo, PharmD, MBA, BCPS, BCGP
CEO
Seguridad


Reference
Atherosclerotic Cardiovascular Disease Risk Estimates Using the Predicting Risk of Cardiovascular Disease Events Equations

Previous GameChangers on PREVENT score

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CPE Information
 
Learning Objectives
Upon successful completion of this knowledge-based activity, participants should be able to:
1. Discuss the impact of the PREVENT equations on statin prescription recommendations for cardiovascular disease prevention.
2. Explain clinical implications and practice changes from integrating the PREVENT equations into cardiovascular risk guidelines.



0.05 CEU/0.5 Hr
UAN: 0107-0000-24-245-H01-P
Initial release date: 08/12/2024
Expiration date: 08/12/2025
Additional CPE details can be found here.


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Speaker 1:

Hey, ce Plan members From CE Impact, this is Game Changers. I'm your host, jen Moulton. Did you know that if healthcare providers adopted the new PREVENT equations, 40% fewer adults might be recommended statins for health disease prevention? That means an estimated 17 million people who are on a statin right now might not need it. The PREVENT equations refine how we assess risk to estimate a patient's 10-year risk of a heart attack or stroke, and that model shows that many people currently on a statin don't need to be, and people who aren't on a statin maybe should be. But this risk model hasn't yet translated into new guidelines for prescribing statins. So what does that mean for your practice, into new guidelines for prescribing statins? So what does that mean for your practice?

Speaker 1:

Today I have with me Jeff Wall and Jake Galdo to talk about just that what the data shows, what it means today and what we can expect if and when the guidelines change. Welcome, gentlemen. Hello, thanks for joining me today. We have talked about the PREVENT study in the past and we'll put a link to that in our show notes, but today's topic is a little bit different, and so we're going to do a quick review of the PREVENT study but also talk about what it means for practice, in that the guidelines have not changed yet, and what we can expect when those guidelines change. So a little bit of a different spin, and there's been some new data, and so we'll dig into that as well. So a little bit of a different spin, and there's been some new data, and so we'll dig into that as well. So, jeff, let's start with you. What can you tell us about the PREVENT study and the risk model that was presented by the American Heart Association? I think it was like last November.

Speaker 2:

All right. Well, for primary prevention of coronary disease, right? So you haven't yet had a coronary event Coming up with some sort of mathematical way to say, okay, you know how intensive are we going to be in our preventative activities. Basically, you know how are we going to lower your risk and how do we achieve that balance of benefit over risk, right? So you know I'm going to put you on a new medication and they all have side effects, but the benefit of it reducing your risk of coronary disease outweighs the risk of side effects. And you know, certainly we've seen some shift in that right In the last 15 years.

Speaker 2:

You know, it seemed like and we still probably do have millions of Americans who take an aspirin a day for prevention of heart attacks, and the evidence is pretty clear that if you don't have any other major risk factors, even if you have diabetes, that using aspirin for primary prevention, the risk probably outweighs the benefit. The risk of bleeding probably outweighs the slight benefit you get from cardio protection. And so you know, because of that, over the last 20, 30 years there's been multiple, you know, models out there that allow us to give the risk of somebody having a heart attack but hasn't had one, yet a number, and then we can use that number to talk to patients to assess whether they should be on therapy. Assess, you know, other things as well. When I came out of school it was the Framian calculator, which was the original ASCVD scoring system, and it took into account age and family history and all that other stuff. And we've had several other calculators since then that have improved both sensitivity and specificity as far as assessing overall risk. But it's something you do have to be careful about because you know you can overestimate. You can say, okay, well, you know you're at a much higher level of risk than what is the reality, based on population and things like that.

Speaker 2:

And so last year I think a lot of people had recognized, including the American Heart Association, that we needed a new risk factor, because we had started to learn that you know all these metabolic issues obesity, diabetes, hyperlipidemia, you know blood pressure, family history, all this other stuff kind of gets rolled in. Chronic kidney disease kind of gets rolled into this package that gives you your overall risk, and previous calculators hadn't really ever done that. They basically said, okay, we're giving you one point if you have high cholesterol, we're giving you one point if you have diabetes. It didn't really try to take a look at the relative risks of all that and bring it into one model and that's where the PREVENT calculator came out. So PREVENT stands for Predicting Risk of Cardiovascular Disease Events, so it actually comes close to what it's supposed to do and it is a calculator that you can go to the American Heart Association website. You can use MDCalc or any of the other apps you use for medical calculations that estimates heart attack, stroke and heart failure risk, which is something new that the previous calculators didn't do. And, as the authors of the papers say, that we're not just looking at hypertension not hypertension. Diabetes, not diabetes. We're also rolling in metabolic risk factors. We're also rolling in kidney and a couple of things to help improve the sensitivity and specificity of a scheme that helps you figure out cardiovascular disease.

Speaker 2:

One of the things that people have said was you know this also may give you the go no go in patients undergoing calcium scoring. As we know, you can actually do a relatively simple CT scan that really will look at your coronary arteries and see if there's any level of atherosclerosis. Currently it's about 100 bucks to do and a lot of cardiology groups will offer you know kind of. You know sales, if you will, where people can come in and get it done, and a lot of people you know who are like well, I'm kind of scared that I might have a heart attack. You know. The problem, of course, is that they may go in and get this testing done and there's a little tiny bit of atherosclerosis, but now they know that they're kind of freaking out about it. So if you're, you know the PREVENT system actually does a better job than coronary scoring to help assess your eventual 10-year risk for having a heart attack. So if you can do this first, it may even help avoid some of the unnecessary worry that comes along with that. So it's now been in place for about a year and again you can go to the website.

Speaker 2:

And how they did this, of course, like all these calculators, is they took a pooled cohort equation that basically took a look at a wide variety of different characteristics along with patients, and then did that calculation in patients before and after they had a coronary event and said, okay, does this model predict that coronary event they had? And in this case, they developed it using from data for more than 6 million adults with a variety of racial and ethnic, socioeconomic and geographic backgrounds. So that's the other thing that a lot of people complained about with the original Framingham data was that it did not take into account different ethnicities very well or different, diverse backgrounds very well, and so this did, and so the PREVENT study really should be what we're using for our assessment of cardiovascular disease. The other nice part about the PREVENT study is that the original Framingham study was really only designed to look at people 55 and older. In fact, the PREVENT study actually you can do people as young as age 30. And in those patients, you not only get 10-year risk, but you also get 30-year risk. So you know something way way down the road. That again, I think, can help patients make appropriate decisions and, as I mentioned, it also takes into account kidney function. It also does look at heart failure risk, primarily diastolic heart failure risk, but it also does that as well. So, for a variety of reasons, the prevent calculator really should be the one that we use.

Speaker 2:

Unfortunately, this is one of those cases where guidelines have not caught up with what the current evidence shows, and so that's been a real problem, and I think Jake is going to speak to you know, if insurers and other people like the Joint Commission are basically using the guidelines as their only kind of Bible that they go against and you say, well, hold it a second. You know this patient doesn't have the risk that we thought we did. Based on the new prevent calculator, are you still going to get you know, dinged either financially or by the star system or something along those lines, because you're following the latest evidence and not just what it says in the guidelines? It's interesting because cardiovascular groups are usually pretty quick to update guidelines, probably the quickest of almost any major medical group, because things change so fast in cardiology.

Speaker 2:

Dr Justin Marchegiani, this is a case where we're over a year into this and we're still kind of waiting for the guidelines to catch up with the PREVENT scoring system. But that has not stopped investigators from saying, okay, well, even though that hasn't happened, what can we draw? What conclusions can we take a look at it, predicting the risk of cardiovascular disease compared to the older pooled cohort equations. And that's what this group. That was just published in the IJAM Internal Medicine and this did receive a lot of lay media attention. So I think those of you who are practicing primary care, who are working with patients in community pharmacies will probably get asked about this because it is probably going to be on the news, basically, but what they did, what they. I'm sorry, jake.

Speaker 1:

Oh, that's, I was just going to say. So what? What? Because they published it in JAMA just last month. So what? What did that comparison? You know what did they talk about? I feel like they did that to sort of push the guidelines along a little bit. You know, to make a big deal about, like these are the amount of people that this impacts, like we need to make a change.

Speaker 2:

Yeah, no, absolutely, you're probably right that. A gentle reminder, if you want to say it like that, to the driving bodies of guidelines and, of course, when you're at the level of the American Heart Association, they have these scientific groups who basically are in charge of writing guidelines, and it's a never-ending process. It isn't like, well, we're done, we don't have to worry about this ever again. I mean, it has to be continuously updated and things along those lines. So you know, you're exactly right. Maybe this is the little. This was an intentional or unintentional push to get to get this done. Basically, I've used myself and a wide variety of investigators use. It's a biannual questionnaire that's done by the National Centers of Health Statistics and it is, for the United States, is probably one of the most in-depth ambulatory data collectors for patients that we're ever going to get. If we never end up with single care health payer, where there's one central repository, this is probably as close as we're ever going to get, because it uses patient questionnaires, actually going and do interviews with patients, as well as laboratory physical examination and a whole bunch of other things that are collected into this information center, and they do it in kind of three-year cycles, and so the last cycle was 2017 to 2020 because, of course, pandemic kind of messed with that. But that's basically what it is and all sorts of investigators can take that information because it looks at a wide variety of health markers and try and figure out what's going with them. And so, in this case, the NHANES group is 40 to 75 who had completely completed the interviews, completely had all their information that was accessible, and, using this information, they did both the older 2013 equations as well as the 2023 prevent equations for estimating 10-year risk of atherosclerotic cardiovascular disease. And again, we won't waste everyone's time, but I mean, suffice it to say that there are numerous, numerous covariates that kind of go into both the pooled equations as well as the PREVENT score and that again, all the things you would think of.

Speaker 2:

But again, the difference, of course, with PREVENT is that it includes far more data, including things like chronic kidney disease, hemoglobin A1C, stuff like that. So basically, they just basically compared the two and then determined, based on the old equations, who was eligible for primary statin use. So these are people who, while they had not had a coronary event or a stroke, according to the current guidelines would qualify for a statin. And then they used the PREVENT study and did the exact same thing. And just a reminder that the generally accepted indications for statin for primary prevention is someone who has an LDL greater than 190, someone with an estimated 10-year ASCVD of 7.5% or greater and those with diabetes. So that's that 7.5%. That, I think, is really what they were trying to figure out, because that's, of course, based on that. You know we had data from the old guidelines on that and who was at risk with 7.5%.

Speaker 2:

Now, using the PREVENT data, what have we found? And you can certainly read the paper it's actually for free and we'll have a link to the show notes there but they found, as many had suspected, that the older pooled equations greatly overestimated the risk by about 50% actually of 10-year cardiovascular events in this NHANES group. So the population mean estimated 10-year atherosclerotic risk was 8% using the older equations and 4.3% using the PREVENT equation. So almost half. And that was true in the. And they did 87,000 subgroup analyses age, gender, racial, socioeconomic you know everything and it was pretty much a cut in half through about all of them. And so what this basically means, I think, is that a lot of the people that we thought had a relatively high risk over 7.5% risk in 10 years of having a coronary event. Don't.

Speaker 2:

And since people and we have long used that number to determine who's going to be on things like aspirins and statins and all that other stuff based in this trial data, the authors basically say well, if we apply current AHA recommendations, that means that currently 45.4 million americans, based on the older data, should be on a statin. Now, of course, I'm sure 48 million americans are not on statins for primary prevention. This is kind of a a uh, you know, taking the whole population, exactly, yeah, taking the whole population. So that's something to keep in mind. But they estimated that even if you took everybody in the us who should be on a statin for primary prevention and was, it would go from 45 million to 28 million using the prevent.

Speaker 2:

So bottom line is that there's 4.1 million patients who are currently taking statins based on the old equations, who, by the new equations, which everybody agrees are more sensitive and more specific, who, by the new equations, which everybody agrees are more sensitive and more specific, does not in fact need to take stats. So I think that's the big takeaway and, you know, the paper certainly seems reasonable. I mean, you know, again, I think they did a pretty good job of what really is, when you think about it, kind of a simple study, right you know, you take a whole bunch of people and do two sets of calculators on them and figure it out.

Speaker 1:

I think it's so interesting because I think we did a course actually back in the day. It was should statins be, in the water.

Speaker 1:

Really, it was so general, so many people were on them. Jake, let's go to you. What does this mean for practice? And when, or if, do you see this change in guideline happening? What happens next? So what you know, we're kind of in the middle ground here, I think, as practitioners, like we know the data. Should we implement the data? We don't have the guidelines, and then what does that do you know? I know you're going to talk a little bit about quality measures and payment, and you know there's a lot of things that are tied to this.

Speaker 3:

Yeah. So you know, what's fascinating is this is about primary prevention. You've not had the thingy happen, right, we want to prevent that thingy from happening, right, but I'm pretty sure we've all just had that thingy happen. We've all just had a heart attack thinking about the cluster that is what you just described. So now it doesn't matter, because we still had a heart attack. So now we're good to go.

Speaker 3:

You know, let's kind of break down the thematic elements that are really interesting in this. One is it's like there's this like Venn diagram, but it's like a trigram because there's three of us and maybe it's a Jeff of the world, it's a Jen of the world, it's a Jake of the world, and what the data really shows us or kind of talks about is because when you started this Jen, you said, hey, this kind of said that numbers go down, but other people don't have it, and I'm like how do numbers go down and go up at the same time? That's not a thing, but that's kind of a thing if there's three of us. There's a Jake, a Jeff and a Jen, right? So Jeff is on a Sten and he's calling me a Sten of Sten. Jen is on a Sten, but probably should not be on a Sten. So that's where our numbers come down. And then Jake is not on a Sten but probably actually should be on a Sten, and that's why our numbers come up. And there's more Jens in the world than there are Jakes in the world, which is why the totality of the numbers come down.

Speaker 3:

But I think it's interesting to note that it's not just people. There's kind of groupings of individuals those that are on primary prevention and continue on primary prevention, those on primary prevention that should not be on primary prevention and those not on primary prevention but should be on primary. So there's a little bit of a nuance in the numbers when we think about how to interpret it, which then gets us into. You know, what does this mean in practice? Well, I'm going to ignore Jeff. He's on it and he needs to be on it, fantastic.

Speaker 3:

But let's look at Jen. You're on it but you shouldn't be on it, all right. So clinical guidelines say let's take you off of it, right or not guidelines, the literature, the literature says not to be on it. But what's hindering that? Is my bonus payment, my, not even bonus payment, my. Do I go underwater? Do I close my shop like the 30 of walgreens right now is do you stay on it? Right? And so that's.

Speaker 3:

Our issue is, unfortunately, health care is is pragmatically a business, and the business says Jen needs to stand because that's the only way I can keep my business afloat by hitting that outdated or invalidated quality measure. Now that gets into measurement science and there should be a giant hoopla right now about changing the measures, updating them, but that sometimes takes a long time, which is unfortunate, and then sometimes they're retrospective. So the real kicker is I should fix you now, because your data now is what affects the payment in two years, which is when it's really going to go into place. Unfortunately, no one's judging my payment on two years from now. My payment's based on that. So that's why I have a heart attack and that's why it doesn't really matter anymore, because now I have secondary prevention.

Speaker 1:

Well, and that's what's hard, because you don't know what the quality measure, even though quality measures take a long time to implement because there has to be science and proven. But in two years that quality measure could be different, but it's based on today. So that is, I think. You know. You hear about pharmacists and physicians complaining about this, and I get it. It's you know, it's a legitimate complaint. And I think there's also what I where I thought you were going to go as well. I mean, I know you know tying it to payment is important, but it's also what how the patient feels as well, like this is something that they've been told to take and they want obviously to prevent a heart attack, stroke, and so now you're saying, oh yeah, you actually don't need that. It's like okay, but do I or don't I? You know I mean. So there's that whole element as well. That I think is going to be really challenging.

Speaker 3:

I'm going to say it's a double-edged sword. Right, it can go both ways. And I think the crux of the conversation is engaging the patient in the conversation. Dear Jen, new literature says you don't need this anymore. The benefit isn't as great as we thought. Are you doing okay with it? Do you want to stop it? So ignore the quality measures, ignore the payment. Focus on the patient. Right, that's how we can drive practice. That's how we should be evaluated. Right, that's the decision-making. Patient said yes or no. Dear Jake, you haven't been on it, but new literature says you might need to be on it. Do you want to take it? You know, again, I might not impact the quality measure, but it still impacts my health as a person. So we want to engage that person in the conversation.

Speaker 1:

Which is what healthcare?

Speaker 3:

should be, what it should be. What it should be what it should be. What's interesting from practice, we won't go there today. That's for the other podcast that's unpublished. So the other thing that's interesting, we're not sharing the outtakes.

Speaker 3:

If you Google the prevent online calculator and you actually walk through it and you do it. I cannot complete this in community practice. Another great point, and that's a kicker to me, right, all right. So let's look at it. I have sex, I have age, I have total cholesterol. Probably, I can probably get that. I can get HDL systolic blood pressure. All right, we're cooking BMI. I can probably get that. I can get HDL systolic blood pressure. All right, we're cooking BMI. I can calculate that EGFR estimated global nutrition rate. No, earthly idea, I don't know it. My patients don't know it, the labs don't Like. That's going to be hard. And then it says diabetes, yes, no. Smoking, yes, no. And I have a chance of yes, no With a lowering yes, no, that's easy. But then it gets to the ones Jeff also mentioned UACR.

Speaker 2:

I thought that was just a mispronounced URAC and it's not Nope. Yeah, and I agree particularly with Jake that one of the advantages of the older pooled equations and the Framingham stuff is, yeah, it really required their blood pressure. It didn't require any laboratory markers really, and anybody could kind of guess, kind of, where you were at there. Unfortunately, the prevent study to be accurate is going to require lab values that, unfortunately, I'm not really sure. You know, certainly community pharmacies are going to struggle with. But I suspect even you know some primary care you know will struggle with. You know urinary albumin excretion is not something that may routinely be showing up in a primary care screen, you know. So yeah, I totally agree with you. That is a strike of using the Prevent set. Do we use something that's easier, that may not be as accurate but can be done in every physician and pharmacist's office? Or do we say no, we want the most accurate thing but we may not be able to actually do it in patients? So that's a great point.

Speaker 3:

You know it's perfect, getting in the way of progress in some regards right and and at the same time I love that it's there there's another one, so it has the, the uacr, it has a1c and then it has zip code and it says for estimating social deprivation index. I know health equity like I live and breathe this. That is the first time I've heard social deprivation index. Usually it's social vulnerability index, svi. That's what CDC says. So then I'm like well, is this new SDI something different than SVI? Or did somebody just mumble when they said DV and they didn't understand what's going on?

Speaker 3:

And the real thing that's fascinating is you can Google this tool. I am a clinician, I am trying to fill it out. Is you can Google this tool? I am a clinician, I am trying to fill it out. I am told zip code yes or no, but it doesn't tell me how. It doesn't tell me where to enter the zip code to create that SDI that they're talking about. It doesn't tell me how to interpret it. I have a zip code, so is the answer yes, right? Or is it supposed to be specific zip codes that are high of the social vulnerability index, which is a thing that this isn't telling us?

Speaker 2:

Right, you know. Yeah, I mean, I think that you know.

Speaker 1:

I mean, it's just a heart attack.

Speaker 2:

Well, I mean it just again. It's very it. When you up the complexity of any sort of intervention, you decrease its use, and I think that's that's that's a standard rule in medicine, right? Probably in a lot of other things, the harder you make it to do something, even if it's more accurate, the less it's going to get done, and so you know that may be one of the reasons why AHA hasn't completely jumped on board with this is they realize that, sure, cardiology clinics can pull a lot of the stuff off, but a lot of primary care physicians can't and no pharmacies, very few pharmacies can.

Speaker 1:

Which is a reason to change. I mean, I don't know how easy it is to get that lab value, but maybe that gets added to a panel because of that. But then also in the community pharmacy setting, or even you know, the ambulatory care setting, for that matter, how you know, how do you access that data? And I think you know it could be a good thing. And here's my like, you know positive spin on it. This is why we need access to lab data, because we need to be able to do these things for patients to then refer them in to say you should or shouldn't be on a statin and you're having issues. So let's see if we really do need to. You know you do need to be on it or you do need to be on it.

Speaker 2:

I guess the other thing I'm kind of concerned about is, again, this is going to get a lot of lay media attention, a lot of lay media attention. And, let's be totally honest, there's a lot of people who don't want to be on their statins, whether it's side effects, or they heard from their friends, brothers, cousin that it causes XYZ, etc. Etc. You know, my physicians struggle to keep people on statins all the time and it's just going to be one more thing where people are like you know, hey see, I wasn't even supposed to be on it in the first place, you know, sort of thing.

Speaker 1:

Yeah, I wasn't even supposed to be on it in the first place you know, sort of thing, yeah, which is never a bad thing. I mean, you know, we don't want to be on something if you don't need to be on it, true.

Speaker 2:

Oh, yeah, absolutely.

Speaker 1:

Yeah, I think the complexity issue is interesting and you know, it's like when you first look at this and say, yeah, why aren't they changing the guidelines, like this is so much better. But then you dig into it and there's all these issues with it. So to your point, jeff, that it may be a reason that they haven't changed them. So, jake, when you talk about you know where this, you mentioned it, but you didn't really have a suggestion where this puts us as pharmacists and physicians. You know, value-based payment for physicians, quality measures for pharmacists and physicians I mean, where should we land in? You know, when we're in this world of this matters in two years versus today?

Speaker 3:

I think we just have to live in the world of how we're being evaluated now and what's being implemented. So there are current quality measures and that is what you're kind of reacting off of, even though they may not be optimal, and then it's our charge to highlight that, push for it, recommend exclusions and I made the joke perfect is in the way of progress, right? No quality measure should be 100% performance. No quality measure is perfect. We're held to the standard that they are, but in actuality they're not. And so you know what? If the gens of the world don't want the drug and that's going to affect our quality measures, that's okay, because our performance on that measure should never be 100%. Because if our performance is 100%, then that's a useless quality measure. Right, Because there's no room for improvement.

Speaker 2:

Right, yeah, I agree with that. Okay, there's no room for improvement, All right.

Speaker 1:

Yeah, I agree with that. Okay, well, anything, any. What are your last parting words or final final comments from either one of you?

Speaker 2:

That I think in the end, you know, in a perfect world, which we obviously don't live in, this is population level data. You know, in the end it really should be a conversation between pharmacist, provider, patient right, here are the pros, here are the cons. What would you like to do? Unfortunately, I just I kind of despair for the average health literacy of the average American that I'm just not sure that is a feasible solution, unfortunately, you know, in the end they either end up doing what their doctor tells them to do, or do what their pharmacist tells them to do, or they don't do either, and it's not really based on science or anything or what's being presented. They're just kind of like, they kind of acquiesce, you know. So I, you know that's. You know it's important to remember this is population level data important. Remember, this is population level data. We really do need to have those conversations and I'm not saying don't, I'm definitely saying do, I'm just not sure it's a practicable solution.

Speaker 3:

I think my final takeaway is anytime we talk about a screening tool here on Game Changers, Google it and take it. Even if you're making it up the numbers, just take it yourself to understand what it really looks like, so that you know how to translate it to practice. Because all the things, many of the things that I talked about you know are because I Googled the tool. We knew we were doing this. I wanted to look at it, so I went to take it and then I started to identify challenges for how I would implement this in practice.

Speaker 1:

Right, yep, yep, and you can. Rather than Google it, you can actually look at the show notes of our podcast that we did on this when it first came out.

Speaker 3:

That's what I meant by Google. That's what I thought you meant.

Speaker 1:

That's exactly what I thought you meant, of which we have a link in our show notes, so we'll be sure to include that. I think my takeaway is science takes time. I think that's the good and the bad, Um, when the media gets ahold of some of this, it's like they put it out there and then, all of a sudden, you know, there's people who are early adopters and innovators, even in their own healthcare, who want to react. Um, and then there are people, like you said, jake, that will just be like, yeah, in 10 years, when I'm supposed to change that, tell me what to do and I'll do it. So I think just being informed is the biggest thing, and you know, and knowing that the longer we have information, the more we can, you know, collect and look at things like this and say, okay, yeah, we did that because that was the best information we had at the time, but now we think maybe not everybody needs to be on it. So it's an ever evolving process and I think it's hard for us as science. People, especially like throughout COVID and people are questioning science and you know, and it's like it is, just sometimes it takes time. It takes time for everything to sort of shake out, and this is one of those times. So it'll be interesting to see where this goes Before we end.

Speaker 1:

Also, I just want to give a quick shout out to both of you for putting these topics together for Game Changers in short order, because I think often we're alerted to new research or things that get out into the media and we want to make sure we cover them for practitioners and quickly bring the true information to you and try to distill it for you and show you what is not happening in my practice I don't have a practice, but the two of you and what's actually happening in practice. What are you hearing in the trenches? So thank you to both of you for that Cause I know that behind the scenes sometimes it's a quick like oh quick, we gotta do this. So this was one of those things when we saw that research and we were like we need to address this and put it in the mix. So thank you to both of you for pulling things together quickly.

Speaker 1:

That is it for this week. So please be sure to share this podcast with a friend or a colleague if you found it helpful to your practice and if you're a CE plan member, be sure to claim your CE credit for this episode by logging in at ceimpactcom. And, as always, have a great week and keep learning. We'll talk to you next week. Thanks again.

Speaker 4:

Thanks for listening in. Claim your CE credit by clicking on the link in the show notes and check out CE Impact's other education at CEimpactcom, where we curate the most important information in pharmacy and medicine to deliver straight to you. Join today to connect your learning to practice.