Fertility Forward
Fertility Forward
Ep 148: Navigating Fertility Choices: Understanding SART Rankings and Choosing the Right Clinic with Dr. Eric Flisser
Choosing the right fertility clinic can be overwhelming for prospective parents, with so many options and factors to consider. In this episode, we’re joined by Dr. Eric Flisser, a leading reproductive endocrinologist at RMA of New York, to help you demystify the process of selecting a clinic. He provides clear, actionable guidance for navigating SART (Society for Assisted Reproductive Technology) reports, understanding clinic statistics, and making informed choices that bring you closer to your family-building dreams. Tune in as Dr. Flisser shares his wisdom and expertise on what to look for when choosing a reproductive endocrinologist, why reviews might not tell you the whole story, the crucial questions you should ask your clinician, and much more. Don't miss this opportunity to empower yourself with the knowledge you need to make the best decisions for your fertility journey.
Hi everyone. We are Rena and Dara , and welcome to Fertility Ford . We are part of the wellness team at RMA of New York, a fertility clinic affiliated with Mount Sinai Hospital in New York City. Our Fertility Ford Podcast brings together advice from medical professionals, mental health specialists, wellness experts, and patients because knowledge is power and you are your own best advocate. We are so excited to welcome to Fertility for today, a recurring guest, Dr. Eric Flisr , who is a reproductive endocrinologist at RMA of New York, and also has some ties to myself and Dara . And as we were speaking before, the episode is been there since the beginning for Dara , and we're so excited to have him on to share his wisdom and insight specifically around SAR or the Society for Assisted Reproductive Technology, to talk about that with everyone and provide some guidance on kind of clinic rankings and lab rankings and how to decide where you might go or to have a better understanding of what you might be looking for when choosing a clinic or reproductive endocrinologist. So thank you so much for coming on and sharing your wisdom and insight with us.
Speaker 2:Well, thank you for having me as always, always a pleasure to see you guys. So I think just to say what, you know, let's say what SART is about, right? So the first thing to understand is that way back in, I think it was the nineties, there was something called the Wyden Act, which was a named after Senator Wyden who introduced it, which was a way of establishing a standard reporting for fertility clinics so that patients would have an understanding of what, you know, what , what to expect essentially so they could find good care and sort of standardize the, the sort of the format for reporting. The CDC was tasked, was collecting that information and publishing it every year. So all of the IVF clinics in the United States report to the CDC , their annual outcomes of infertility treatment, specifically IVF, using donor eggs or patient's own eggs . And it takes some time to collect that data, right? So you have to imagine someone has to get through treatment and then they, it reports on the total outcome . So they need to then deliver and find out what the outcome of the pregnancy was. So then it can be collected as data and then it takes time to compile all that you can imagine. So it's about two years behind the reality of the moment, right? So start data or CDC data is historical, right? It tells us what happened about two years ago, but that's the most, usually currently available data for any clinic. But the point was to present the data that's out there in a kind of standardized format for patients to look at so that they could decide where to go for care. And so CDC is the governmental organization that puts together and publishes this report, but SART is the Society for Assisted Reproductive Technology. So it's a professional members group for IVF clinics. Not all clinics necessarily are members of it, but it is the , a large organization that I think 90% or something of IVA clinics in the United States are members. And it's basically a professional organization set standards and to have a uniform reporting system. And then they report to the CDC as well what information is found. And SAR also provides professional guidelines, practice habits, recommendations, that kind of thing . So we talk about SAR because that's sort of the popular clearinghouse of information that people tend to refer to. And so the SAR report details what happens to a patient when they come to an I clinic. And it is very complicated if you ever get an opportunity to look at a SAR report, which is easily accessible because it's public information and it is on their website, which is S as in Sam, A RT as in tom.org, right? Because it's the site of <inaudible> technology. And on it they have like a thing which says like, find the clinic, right? And you can type in a zip code and it can give you the area clinics and their SAR reports. And the SAR report then details all these, these little statistical points about patients, how many patients were seen , what the pregnancy rate was, how often patients needed to be treated if they got pregnant, you know, what percentage you get pregnant the first time, which ones eventually get pregnant? How many patients who started treatment eventually got pregnant and their outcomes have had babies? How many of them were singleton babies? How many of them were twins? Stuff like that. So now the thing is, the more and more data that's been added to it over the years, the more and more complicated it's gotten to read. So it's very challenging for patients, I think . I think it's very challenging for clinicians to read, right? I think it's, you know, like what does this mean? That language is so complicated in some ways . They say stuff like pregnancy outcome per intended retrieval, right? Well, what does that mean , right? I mean there's , the wording is so complicated, but, but there are a couple things in the report that I think patients can focus on in certain metrics to look at, to get a sense of, you know, what is a good place and how to value which clinic versus another. With the one exception that SART actually says, you can't use the SART report for doing that, right? So there's the big irony, right? So SART collects all this data about all the iiv F clinics to compile it so patient can use it to make an informed decision about where to go. And then SART says very clearly, if you ever wanna look at a report, there's a little checkoff you have to click. I recognize or I understand that this data cannot be used to compare clinics to each other. Yeah, right? It's sort of curious, but , so , but what does that mean? Why , why ? Yes. So why , so get , get around the why . That's really the point , right? What they're basically saying is that the clinic's performance is dependent on which patients they see, and not all patient populations are the same, right? So make it very obvious, like , and , and this is not obvious, this is just sort of theoretical, but if I saw patients who were all, let's say 30 years old only, and all of whom were cancer survivors had chemo radiation, right? Really tough time. They're having a tough time getting pregnant, and the guy across the street only sees 30-year-old patients, but he doesn't see any that have had cancer treatment. We're not seeing the same patient population. Even if we exactly the same, you'd expect us to have different outcomes, right? For sure. And so that's basically what started saying is the started saying, only thing you get to see is the average information. You don't get to see the detailed information. So you don't know what's actually happening. And so you can't compare them because what if they are really different populations that are being seen? So they're saying that's the precaution, right?
Speaker 3:So they don't necessarily give you the specifics in terms of the age, the weight, the right. Well , yeah.
Speaker 2:They give you range values, right? So for example, iiv F data often is reported as patients younger than 35 patients, 35 to 37 patients , 38 to 40 patients , 41 and 42, and then patients 43 and above.
Speaker 1:Okay ? I mean, but the way you say it , it's true. I mean, treatment is so nuanced, right? You could have 2 35 year olds who present extremely differently. And then it's not really an equal comparison because one clinic may get a 30 5-year-old who's super fertile, and one clinic may get a 30 5-year-old who has diminished ovarian reserve and a MHA and uterus whatever, right ? Exactly . And the data and the populations and the treatment. It is so nuanced depending on the patient.
Speaker 2:Yeah. And in some ways, this is also the problem of statistics in general. I think all statisticians will tell you that statistics describe the group, not the individuals in that group, right? So meaning use something simpler like height, right? So let's say the average height of a man in the United States, I'm guessing is like five seven, let's say. Okay? So if you had a group of men on average, their height would be five seven . But you don't know if anyone in that group actually is five seven .
Speaker 3:Yeah.
Speaker 2:Okay. And so that's the problem with of statistics, okay? So the nuance, each individual is gonna change whether or not they're part of that average or not part of that average. The average just describes it as a whole. Now, one of the things I think that is super useful when evaluating a clinic is what I call throughput, right? Which basically means how many times have they done this, right? And , and the reason why I think it's again, go to sort of the , the mathy stats part of this, right? Which is when you flip a coin, everyone that knows this sort of experience, if you flip a coin, it's either gonna be heads or tails, right? And that , I mean, yeah , I get , yeah , in theory you could land on the side, but okay, we're not talking about it <laugh> tails , right ? So 50 50 chance in theory of heads or tails. So what does that mean? Well, if you flip a coin three times, the one outcome you cannot get is 50 50. You can get all heads, you can get all tails, or you can get a combination. But whatever that combination is, it's not gonna be 50% because it's an odd number of throws, right? So how do we know it's 50 50? Well, it's 'cause we've thrown the coin more than three times. We've thrown the coin a thousand times or a million times . The more and more we throw that coin, the closer and closer the average of the data we're collecting meets the true average that you can't actually know. So we all say, oh yeah, it's 50 50 because we all, it's an easy thing to think about. It's either one side or the other equal chances that's 50 50 by sort of theoretical definition. If you actually did the experiment, it wouldn't always be 50 50 unless you did a really big experiment. But the bigger the experiment, the harder it is to get away from the true average. Little numbers have large skew , meaning that you can get all heads or all tails in a throw of 3, 4, 5, 6, 7 times. But it's gonna be really odd to have all tails or all heads if you flipped a coin 20 times, right? You'd expect at least one of those would be the other , right? So my point is the more cycles an IVF clinic is doing, mm-hmm <affirmative> truer. The average is to the patient experience because there's less skew , right? Even despite all the little differences between the patients, it is more and more likely to be representative of the true average.
Speaker 3:So does that mean that it's more advantageous for a big clinic to be disseminating their information and it could reflect more of the average better as opposed to a small clinic that doesn't see as many patients or a variety of patients,
Speaker 2:Right? So I'm gonna , I'm gonna say two sort of maybe two different ways if I can remember. So one is that yes, the more patients being seen, the more throughput there is, the more confident you are that the average is real, right? Mm-Hmm <affirmative> , it's not subject to random variations. When you have a smaller throughput, it's more subject to these short, what I call short run data, right? If you have five flips of the coin, you're still very possibly gonna get all heads to all tails. So it's not enough data to be confident that they average the reporting. So if we flipped it five times and it was all heads, then we'd say it's a hundred percent. But we all know that that's only 'cause it's five times, then it's not likely to stay data a hundred percent , right? So the bigger the clinic, the more data there is, the more likely you are to get that. Now in statistics is a way of making a comment about that, right? And it's called the 95% confidence interval. And I don't wanna get too mathy in here, but the point is, as good statistician, and I think it's in the SAR report too , we'll give you the range, meaning we think the average is this based on what we've observed, but with all probability it actually falls between this and that, right? So if you flip the coin a few times, times you would say, well the average is 50%, but the true average might be 49 to 51. We're not really sure 'cause we haven't flipped the coin enough to really hone in on if it's 50. Now, if you have low numbers, that spread of true average can be quite wide still. And so the more and more you flip the coin, the closer the actual average is to the true average and the narrower that confidence interval gets, meaning it gets closer and closer to really representing there's not much variation anymore. Because you can imagine if you flipped a coin a hundred times and it was always heads and you flipped it one more time and it was tails your average almost a hundred percent heads , right? It's just barely away now. 'cause you can't move very much from one more throat. So the more and more and more you do the tighter and tighter and tighter your numbers get. And that's really good for patients because it means they can have confidence in those numbers. Mm-hmm. <affirmative>, right? They can say, well they reported two years ago that they did 300 cycles in this age group and their percent success with this. That's pretty good actually because it's pretty confidently gonna be that if they only did six, how do I know that that's actually represented the outcome? Right? If they did six and everyone got pregnant, and hopefully they did, are you really convinced that everyone always gets pregnant in that clinic? No. Right? Because even logic tells you that's not likely, right? Because not everyone gets pregnant all the time no matter what. Right? So so that's sort of what that guy , sorry to talk, go ahead . Oh
Speaker 1:No , no . Well I was just gonna sort of interject and say, well, are we then judging clinics? So you're not advising though , to make a sort of a , a large judgment on okay, this clinic has a higher volume of patients, therefore they have more data and therefore if their data is good, we can say they're a better clinic than a small , I
Speaker 2:Can't say that they're a better clinic, right ? Because I don't know that , all I know is that I can be more confident in the numbers being presented because the throughput guarantees that , right? Presuming everything in the clinic goes as it always goes, or meaning they , they aren't making radical changes to the way they're doing things, then we can be confident that those numbers are representative of what's actually happening. Because it wasn't just a lucky couple of outcomes, right? So the bigger the clinic, the more confident's not necessarily the better the clinic. That's not necessarily true. Although you would think the wisdom of crowds would help you out there, right? So the concept being more people go there because they have a good reputation 'cause they do well and that reputation is that they did well and that spread and more people go there , right? You , you sort of expect that
Speaker 3:And then , but that's not explained on the site. So is that confusing? No . No . And that's, yeah. And so, so site is basically just unfortunately
Speaker 2:Columns and data, you know, like you don't ,
Speaker 3:And you , you have to interpret it or , or analyze it the way, you know . Yeah . If someone's knowledgeable in stats, great. If not, right? And
Speaker 2:That's why I thing , I don't wanna get too mathy here because I think most people don't know these things, right? And I don't know this because it was part of my fellowship training to learn these things, but I don't expect the average rural to understand what a 95% conference interval is . And as a result, when you look at the data, it's just like lots of numbers. It's like looking at a , you know , a ledger and you're like, I don't, I don't even wanna get started this because I don't know what any of these numbers mean. Give
Speaker 3:Me the cliff notes .
Speaker 2:<laugh> . Yeah , exactly. Gimme the cliff notes . So there is sort of a way to look at the cliff notes , right? So it's just that you look at specific parts of the report and again, the report won't really direct you there, but if you kind of know what you're looking for, then you can have a good way of assessing it, right? Which is, is simply like you wanna know for each new patient seen, how often did IVF create a pregnancy? Right ? And not necessarily always just was it the first try, but eventually subsequent tries and that data is presented that way, right? So they say, you know, first embryo transfer and subsequent embryo transfer because obviously something that's not a hundred percent sometimes doesn't work. And we don't always know why. But you , what you really wanna know is am I eventually gonna be successful? Right? So cumulative data is really quite , um, helpful in , in that sense because we know it , not everyone we successful the first time we , we would like it to be and maybe one day we'll get there, but currently not there . So SAR data is very challenging because it doesn't come necessarily with a good tutorial and statistics, although it tries to explain its terminology. The terminology is difficult to read, I think.
Speaker 1:I think it's hard. I think when people choose a clinic, a lot of times they choose because a friend went somewhere and had a good experience and so they'll go off. Yeah , yeah . You know what a, what a friend said and I think that's what
Speaker 3:I did
Speaker 1:<laugh> . Yeah. You know, and I think word of mouth is great and I think a lot of times though you hear people love a clinic because they had success or they hate a clinic because they didn't. And so
Speaker 2:Yeah. Well this is the whole like reading Amazon reviews kind of thing, right? Which is mm-Hmm <affirmative> the people who it's the most polarized review, right? Like, you either loved it and felt the need to tell everybody or you hated it and felt the need to tell everybody, right? So
Speaker 3:You're right. You don't see the InBetween. Yeah.
Speaker 2:You don't see much, you don't see much on the InBetween part. Like , I mean you do but you don't like, it's like if I was like okay with it, like why would I say anything like
Speaker 1:Right, you're just existing with it .
Speaker 2:Yeah . Like
Speaker 3:I look at the five stars or the one stars , I never read the three stars ever .
Speaker 2:So there you go. So you can get, and obviously one of the most, I think, important parts of choosing a clinic is feeling comfortable with the people who are treating you , right? Yeah . So you're not gonna get that from a start report. You might get that from a friend, right? So I sometimes , oh, they were really kind and I had a good experience and they seem really knowledgeable and lovely and whatever. Okay, maybe you are experienced, maybe the doctor you meet was having a bad day that day and maybe you don't have that experience. Mm-Hmm . <affirmative> , you never really know what their opinion is going to be. Obviously everyone likes success, but sometimes they might say, okay , it was great we had , we were successful, but no , no , no , no . It's not best experience. Right? And you have to decide what kind of person are you, do you care about that experience or not? And again, that won't be in the start . It would be great if everyone had great experience all the time with us and we hope they do. But this is challenging and emotionally charged and the situation doesn't always lend itself to a positive feeling , uh, when things are going badly. 'cause sometimes they do. And you know, that's the reality. But I think interviewing a , a doctor, you know , going in for a consultation and having conversation saying, Hey, can I trust this person? Do I like them? Or do I feel like they're gonna give good care? Is a big part of it. But you also want to know Mm-Hmm ? <affirmative> , okay , is it backed up by data? Right? I wanna know that . Right . Wanna know that it's true that they actually are good.
Speaker 1:I think it's absolutely multifaceted. I think it's important. I think as you said, it's important to interview a doctor. It's important to listen to your gut, you know. And I think just out with the data, there are so many nuances. You know, your friend who went and had a bad experience, maybe they had a really difficult time with not being able to exercise and that for them ruined the experience. Maybe you don't care about exercise that wouldn't impact you in the same way. There are so many nuances to the situation. So I think it is always important to trust your gut and do your own research as well. Yeah .
Speaker 2:And so I think that's a also a good segue to , just to touch on egg freezing, which you mentioned earlier in the intro, which is to say that that, you know, egg freezing is very challenging. So the hardest thing I think that we do technologically, the embryology lab I think will would agree that freezing and thawing, it's not really the freezing, it's thaw, right ? The freezing anyway to freeze anything thawing , it's in getting to survive is the hard part. And that's a big challenge. And IVF clinics are not a great analogy, but they're sort of like restaurants, right? In the , in the sense that every kitchen is a little different and you can order the same meal everywhere you go and you'll get very different results. And the same is true for IVF . It's, some parts of it are sort of standardized, but lots of it isn't. It's just what the clinic does and the clinic habit and things like that. And that can have an impact on success. And since you can't know those parts, you need outcomes data to show what's happening . Right? And that's sort of the problem in some cases with egg freezing, which is that outcomes are really delayed, sort of by definition, people freezing eggs are not planning on using them right away. Mm-Hmm . <affirmative> , otherwise why freeze? Mm-Hmm . <affirmative> . So there's a delay in the outcome experience on that . So that makes it challenging. But a clinic has to thaw them to know what the outcome. So there was an era , and it may still exist to some degree, but where there were clinics that only freeze eggs. That's what they do . They freeze eggs and then storage is done by someone else and they don't take eggs back to make embryos. And so they don't really ever know the outcome. I don't think that's great for a patient because how does the patient know ? There's no consolidated place to know what the outcomes were . In fact, SART and the CDC require you to report the outcomes of what was done in your clinic. So by the way, it's structured. If you froze your eggs at one place and they were thawed in another place, the thaw data is what gets incorporated into the place that thawed it and their outcomes. And the place that froze it has still no outcomes. So you can't know are they doing a good job in the , because that will definitely affect the thought, right? You won't know it until you thought. And so I think that part says, okay, well now you need to know, like, again, it's a little bit of word of mouth and experience and throughput again, right? Which is you need a place that's done it and proven that they can do it and has data to share with you. But to that point, because the freezing and thawing methods are so challenging, some clinics won't take eggs in from other places because they're gonna, one is obviously it affects their appearance out there, right? If I saw someone else's eggs, some other clinic's eggs , then the outcome of that thought goes on my data sheet, not the clinic that froze it . And so I don't know what that's like, I mean , I know the standards are here and on my immediate surroundings, because we have several IVF laboratories here, right? So Long Island, we have, you know, one Brooklyn, we have one Westchester, we have one here in Madison Avenue, and I know how good those guys are, right? And I just don't know what it's like outside. So for me to bring in someone else's eggs and then post on the internet that these are my outcomes when I only did part of it, it is a little misleading, right? It's a little unfair to us and to patients.
Speaker 3:You can't strat you can't strat from like a different clinic. Like that should be another
Speaker 2:Yeah. Well email sort data points because yeah, I think you , you make a good argument, which is what's the provenance of those pets , right ? And
Speaker 1:Well , I'm so happy you touched on that because I think a lot of times, especially maybe with egg freezing where their younger patients, and maybe finances are a thing, people look to sort of like save money and they'll go to places that give these quote unquote deals and then they end up in the long run getting really screwed, for lack of a better word, because a top clinic will not accept these eggs. And then as you just astutely mentioned, right? The whole process of thawing is a huge piece of this. And if you're not in a lab that knows what they're doing, everything could be lost. And so I think this is really important to know that when freezing exit is something very much to consider, it's not to go with this sort of like discount clinic, right ? And think you can transfer those later because it doesn't work like that.
Speaker 2:Right? And also they may not be as good success 'cause you don't know. I'm not saying there aren't, I don't know that the problem is you don't know that, right? Because without the outcomes data, which you can't pin back to the place that was freezing it , you can't really know then how successful those patients are. You don't know what you're getting into. And so the eggs are only so good as you can use them , right? Meaning if you freeze them but can never thaw them . And I eventually will find someplace that will accept them . And I'm not, you know, gonna say that never , you never can find a home for them, but unless you can thaw them somewhere, they're not useful to you. So saving money on that isn't the good deal if ultimately you don't get anything for it , right? Mm-hmm . <affirmative> , uh, eventually someone of 'em will take you in, I'm sure, but it may not be the place you want it , right? Because, you know, this place has great success, but they won't take your ex . That can happen. We don't always take in embryos even from other places. And this is mostly to do with our strict standards for patient identification and labeling and all that kinda stuff. Like we really gotta be careful about that kind of thing. It's a security issue. Mix ups have happened elsewhere in the past, we know very publicly. And so I , I know I can say that and say, listen, this is be a very important thing to get right and unless we're confident in our colleagues elsewhere, we won't even take in embryos. So that's something to be thinking about as well. Like what's the integrity place that you're working with ?
Speaker 1:I think these are all so important. I'm so glad that we are talking about them. Mm-Hmm . And bringing them up because I think, you know, choosing a clinic and a physician is so important and I think, you know , there's just so much out there. And so I think it's really important to present this factual data to people. And , and you know, as we always talk about on this podcast, knowledge is power. And so SART is a great place to align yourself with knowledge and gather facts and information. And I think it's also really important to be able to bring this up to your physician as well and ask, do you have clinic data? I wanna see the statistics from your clinic and look at everything. And that should be, and Dr . Ser , you can speak to this or not, you know, if patients ask for that, that should be something that a clinic can provide, you know, no one should be hiding. Yeah .
Speaker 2:I mean, for the most part we're gonna point you to that's our report, right? Yeah . But, or the CDC , but yes. And , and that's stuff you , you know, you can have your internal data and see , because some of that stuff is not gonna be in the heartworm . You might wanna say, oh, what's the thaw survival rate of your embryos? Right? That's really important. If they're frozen for X number of years and I'm coming back to use them because let's say I was successful once and now I wanna expand my family, what's the chance that they're , I'm gonna be able to use those because time has passed and it's not as easy anymore. The whole point of freezing things is that it preserves the chance of the age at which they were frozen. So that's a huge, that's why you freeze eggs or freeze embryos. And so you wanna know what's the thought survival rate that might not be in sar Mm-Hmm . <affirmative> , Right ? They're only talking about the outcome, not, you know, what happens along the way. And so you should be able to ask your clinician, Hey, what's the chance it's gonna fall out ? What's the chance that I'm gonna get pregnant? What's the chance I'm gonna miscarry? These are things that are noble, they're measurable . Mm-Hmm <affirmative> . And sometimes the , you know, the answer isn't perfect, right? Because it's an ongoing collection all the time, right? So someone says, oh, what's the average egg number for someone in my age group? Well that can vary quite a bit actually because people are very different genetically and physically. So it can be quite variable. That's not so useful in that case I would say, listen, let's look at your own reasonable , let's look at your A MH , let's see what it looks like for you personally. 'cause that's more, you know, more useful. And we can measure that easily in a short timeframe without too much discomfort or cost. But knowing whether or not your eggs or embryos are gonna survive the thaw, well , okay, we'll since we freeze them all the same for all patients, there's not much variation there, then the group data is very useful and can give you more confidence about what you'll get back and what to expect when you get that back. And so I think, think those are things that aren't necessarily presented in those reports. And you gotta ask those kind of questions.
Speaker 3:And I think it's also like, it's good to realize that the reports and the data, it's a snapshot in time. Yeah . And things do change. So I think a lot of times we put so much weight into something when it really could be that snapshot. I wanted to ask, I was, is the start report done annually?
Speaker 2:Yes, it's an annual report. Okay . The data gets submitted, it's sort of at the end of the year, like November-ish. And then so it comes out in the early part of the year following. And like I said, it takes a long time to compile this stuff. So there's always sort of a lag to the timeframe. So as you said, there may be changes since the lab report was submitted that aren't reflected in the most current results. But again, history is a good way of sort of establishing what that clinic is. If the past couple years have all been quite good, presumably things will be the same. But again, those are presumptions. But when I say that they're the same assumptions you'd be making for everywhere, those are not one-off kind of things. Like, I accept that I can only know data from two years ago, but I can only know it for everybody. No one has any greater insight than that. That's what we have to work with. And we know that it doesn't hold true, but I have as good a guess as anyone else. So whether it did hold true, right. No reason to think they wouldn't . But it's an annual report and you can actually scroll back a few years on it in the, on the website. It , it , it allows you to look at previous years. It gives you confirmed follow-up data and ongoing data. 'cause when you report, some of the pregnancies have not been accounted for. So it will get updated, particularly when things like embryo are frozen and then they're carried forward a year or two or more. That gets reported sort of going backwards. What happened from that ? Right? Because we talk about cumulative success and stuff. So if I froze eggs a few years ago or froze embryo a few years ago , but I don't follow them until now, now I can update the information from a few years ago. So as you said, the important part is it's a snapshot of some accumulated data. It does change, but it can give you updated information periodically. And that's really the best measure. You have to get an assessment of any one clinic, again with a asterisk that you're not supposed to compare one clinic to another
Speaker 3:<laugh> . And then do you see, like, is it in graph form at all or is it just in percentages?
Speaker 2:Some of the data that they present, usually national data, they sort of do National data summary is somewhat graphically. Oh good. Most of the data reports are tables, but sometimes clinics will publish their own data. There are again, SAR rules for how you release this information to the public on your own data sheets . So meaning your website. And so those may be graphical and they could show a comparison, say between the clinic and the national average. It is not generally clinic to clinic because SART doesn't allow that. Right . You can imagine the members of SART don't want the other members to use their data against them or for them, right? Mm-Hmm . <affirmative> , that makes sense . So that's one of the stipulations. But most importantly because the populations aren't necessarily the same.
Speaker 1:Well, this has been so illuminating and I loved talking about research and numbers and statistics with you. I feel like we could geek out all day on this, but I think this is such an important part of the process. And Dr . Klier , I don't think there's anyone better to talk about this than with you though . You are so particularly data-driven and really, I know our patients really appreciate that. I get that feedback all the time. Dr. Klier sat with me, he presented data, he gave me facts and information so I could really understand. And I think that is so important. You know, I I think patients really appreciate being spoken to like that and being let in on this information and being talked to in that way so that they can make their own decisions. I mean, I think this, this process is so much about statistics and research and numbers. It's not just sort of luck of the draw if you have success science , right? Science. Science. And so to have that understanding I think is so important.
Speaker 2:Although I will say I do use a lot of metaphors also <laugh> <laugh> , which I find super helpful to , because if only for this, like, you know, go back to the coin flip. You know what a coin flip looks like, right? I mean, you've done it right. You don't know what IVF looks like. Right? You've , you've not done that, right. You don't have the expect that that's why you have an expert for that. So I often use these, I I find them, I think I, I always thought they were more illuminating. Maybe , maybe they're not, but to sort of explain, hey, this is what we're thinking. This is why we think it as a way of explaining the science. You know, the data is super important. I think communicating that data isn't just numbers . Mm-Hmm . <affirmative> . That's the thing .
Speaker 1:Well, and I love how you compared it to a restaurant as well. So , you know , sort of looking at , uh, the review , just like a restaurant review, then the days of the , uh, the gap reviews recipe .
Speaker 2:Oh yeah, <laugh>
Speaker 3:Forgot about that.
Speaker 1:The gap for fertility clinic . So thank you so much for coming on and, and sharing. I think this is so helpful for people to hear and and understand and we so appreciate your time and wisdom.
Speaker 2:Well thank you for the opportunity and like I said, it's always fun to talk to you guys. Super easy. So happy to do it whenever I can .
Speaker 3:You make it easy as well as we always like to end our podcast is with words of gratitude. So Dr. Ser , what are you grateful for today?
Speaker 2:Well, I mean, I'm certainly grateful to have these conversations, but really to work in a place that values the patient experience and good outcomes and always working even behind the scenes to make that happen. And there's a lot of ethical, emotional content that patients don't see us go over. And we have committee meetings to talk about these things. It's really focused on trying to, you know, produce the best outcome for our patients. And I'm lucky to be able to be an environment where I have colleagues who are interested and will do things like this, even to illuminate the process and make it more understandable, less scary and anxiety provoking. I think it's just a fantastic environment to work in. I can't imagine a better place really to work . It's great. I'm thankful for that .
Speaker 1:Well , we love that. Sarah , what about you?
Speaker 3:I mean, I was thinking this whole time and you sharing your information , uh, about research. I'm grateful for RMA for how much research we end up doing where A SRM is fast approaching our, our big conference. And every year we do so much research and I'm really amazed at our team at RMA that gets involved in that. But then on top of that, I'm really impressed with you, Dr. F Lister and the other doctors in terms of your communication skills. It's one thing being a great doctor and supporting your patients, but the communication aspect often can be a challenging thing. And to really be forthcoming and communicative, making it fun using these analogies is part of the experience as well. And so just like you, I'm, I'm super proud of working at RMA and the team that's there to support our patients. Pretty amazing. What about you Rena ?
Speaker 1:Oh gosh. Well I'm gonna have to piggyback all of these also . So in my gratitude for this clinic and their research that they put out, I actually had a meeting with our head of research just this week and was so impressed hearing from him even the numbers of the studies we're putting out what everyone's working on. And it really is such an amazing part of my job too, to work at an institution that is putting out so much data and information. And so I feel so honored and , and lucky to be able to be a part of that team also and hope to be able to contribute my own research this year for the next A SRM . So I'm putting that out there. Mm-Hmm . <affirmative> . Awesome. So thank you so much .
Speaker 2:You too .
Speaker 3:Thank you. Thanks so much again.
Speaker 2:My pleasure. Thank
Speaker 4:You so much for listening today. And always remember practice gratitude, give a little love to someone else and yourself. And remember you are not alone. Find us on Instagram at Fertility Forward . And if you're looking for more support, visit us@www.rmany.com and tune in next week for more fertility.