Univfy increases IVF conversion by 2-5 times, translating to more than $1-3 million in increased profit. Click to download this free tool to set and achieve your own revenue goals from IVF conversion: www.univfy.com/ivfpatientretention
DISCLAIMER: This is a featured sponsor episode with paid sponsor content. Advertisements are not an endorsement from Inside Reproductive Health, nor their personnel.
Univfy supports fertility centers in increasing IVF conversion, outcomes, and revenue. Providers who counsel patients with the support of the Univfy PreIVF Report see a 2-5x increase in IVF conversion. That means if you make $10 million in IVF revenue today, you can make $3 million more with Univfy. This week, Griffin hosts co-founder and CEO, Dr. Mylene Yao, to discuss how Univfy is working to make family-building more accessible, predictable, and successful, and how their technology has proven to benefit both fertility centers and their patients.
Listen to hear:
● How Univfy uses AI/ML to increase IVF access by helping patients to move past key decision points in the provider-patient flow.
● How Univfy services are easy to use.
● How AI and predictive outcomes have transitioned from a “nice to have” to a “need to have” as Gen Z and Millennials overtake the fertility space.
Click to download this free tool to set and achieve your own revenue goals from IVF conversion:
www.univfy.com/ivfpatientretention
Mylene Yao’s Info:
Company: Univfy
LinkedIn Handle: https://www.linkedin.com/in/mylene-yao-m-d-049a2915/
Website URL: www.univfy.com/providers
Transcript
Griffin Jones 00:46
80% of patients are not helped in the IVF patient journey, because they don't make it all the way through could be the case I explore this today with Dr. Mylene Yao, the CEO of Univfy, and we go through the patient journey at different points talking about IVF conversion, talking about patient dropout, we talk about how AI is using individualized predict predictive outcomes, and specifically how Univfy is using that AI for individualized predictive outcomes to solve for challenges on the provider and, and on the patient. And you can actually see this visual too for free. If you go to univfy.com/ivfpatientretention, this is something for you to look into AI is here, Univfy has been using it for years, it's impacting every point of the patient journey, every point of your workflow, and IT needs to work in your favor. So this is a solution for you to investigate. And the more the demographics of our patient generations advanced, the more this becomes a must have for previous generations, artificial intelligence and develop individualized predictive outcomes may have been a nice to have now they're a must to have. You have Millennials, you have Generation Z entering your practice, and they're not satisfied with generalized outcomes. They want individualized prediction models they want coming from artificial intelligence. They want it coming from your data. They need it in order to make decisions in many cases, Dr. Mylene Yao. Welcome to Inside Reproductive Health.
Dr. Mylene Yao 02:23
Hi, Griffin. It's great to be here. Thanks for having me.
Griffin Jones 02:26
It's my pleasure. I knew you first. As an entrepreneur, I think the first time I knew of you was actually at an arm event, some years back, it must have been several years back now because it's been a long time since arm has been in Chicago. And so I knew you first as CEO, and then come to find out, you are a physician by training and then come to find out some more, not just a physician, but you actually were an OBGYN. You practice in women's health. Is that right?
Dr. Mylene Yao 02:57
Yeah, that's correct. I started my career as an OBGYN. First really focused on the clinical side, I grew up in Toronto, did my medical training in Montreal, did my residency there at McGill University and graduated from University of Toronto, and then really felt passionate about reproductive health and went to Brigham and Women's Hospital in Boston. To do my clinical REI fellowship there, I learned a great deal from really amazing people. And then cut the research bug and went into academic research, which I really, you know, was passionate about as well.
Griffin Jones 03:37
You go on to start a company and I want to talk about how that journey came to be. I'm also interested in the problems. It's all because when I think of Univfy think of IVF conversion. So was that the first problem that you sought out to solve? Was there another problem that you came across your research that made you start unified, which came first?
Dr. Mylene Yao 04:01
I was really an academic researcher. I was faculty at Stanford University, in the department of OB GYN where I lead NIH funded research projects that focused on embryo development, early embryo development, on site development, and so on. And one question, and I think that's the benefit of, you know, being a clinician scientists at the time, is, you know, when I saw patients in the fertility center, patients just really want to know, what are the chances of having a baby? So I think that was my, you know, initial motivation and still is, we want to be able to give very accurate and personalized information to patients so that they can make the best decisions about how to proceed to have a family
Griffin Jones 04:48
meal and how does how are you using artificial intelligence to solve this because one of the artificial intelligence for I would say three years ago, it was good enough to kind It just talks about generally in the field, oh, here's how it's going to come in. And then I've heard it SRM and PCRS. When someone's talking about AI, they'll say, Oh, this is the same talk, it's going to change the world. And people are interested in the specific use cases of AI now, and so that this is a good opportunity to see how AI is not down the road. It's here. And what, in what cases? Are you using artificial intelligence? Now to solve this problem?
Dr. Mylene Yao 05:30
I think recently, just with a lot of interesting stories in the media, we're all made more aware of the power of AI. And but maybe let's start with, I mean, there are many different types of AI. So there's no, right now, there's not a robot a chat, GPT doing your IVR prediction model. So like, so in, kind of, in the field of AI, there are different types, like, there's the original vision that, you know, AI experts had from long ago that AI is going to be this super intelligent, kind of machine that can do everything, like a human and better than a human, you know, can talk can have motions can do all these things can calculate numbers that we can't, can run faster, whatever. We're not talking about that kind of AI that's more like general AI. And that vision, I would say, the world is getting closer, but there's still a huge gap. And we're not focusing on that. Right now. There's another kind of AI, which is really what is behind a lot of processes now, which is narrow AI, and narrow AI. Sounds narrow. And it is, for good reason. narrow AI means using AI to do a very specific task very well, better than humans faster than humans more accurately than humans. Mostly not because humans are not smart. Because it is really leveraging, you know, cloud computing, and can do a lot of calculations in a very short time, at very little cost, right. So narrow AI is what we do. And that's what most you know, businesses do to support their customers. And within that, there's also there's, you know, machine learning is a big part of this narrow AI, and kind of bring it to the healthcare. In general, you have a lot of healthcare now use AI to do to support radiologists to support pathologists. And that's where you're using really imaging and deep learning to use imaging to support kind of call out some, maybe an MRI that is more questionable, more likely to have cancer or something like that. There are tons of studies and tons of applications there already. And you know, but there's also a different kind of AI in the general healthcare, like, oh, which patients are most likely to come back to the ER after we discharge them from hospital. Because if we can identify those patients, we can implement better prevention programs, or which patients in the ICU right now have a high risk of crashing, and less put more kind of monitoring on that patient. These are things that already are being used. And then in our fertility space, what we do see right now that are really emerging, is you hear a lot about what embryologist talked about which is using imaging AI to try to detect the embryos that are most likely to be viable, and so on. So but what we're talking about here, what Univfy does, is not that at all, is a different kind of AI. We're using AI and machine learning to analyze structured data. And structured data means the datasets, the data that is in your EMR, the data that is in your start export, you know, or in your billing data in your billing records, is really making use of that data so that we can get the smartest information out of it to inform all the things that you need to do in the clinical setting. So that's the AI that we're focusing on. And in particular, our platform is designed and we got very good at building IVF prediction models for you know, each specific clinic using a clinics own data validated by their own outcomes. And we have, you know, we're I think the only company with this high scalability of being able to do that we're We're really having a lot of quality assurance in order to provide this level of service at the point of care where you can use it with your patients. So I think that maybe helps to frame you know, what is the AI that we're using? And, you know, going from there, you know, now with that kind of prediction model that is specific to your patients, you know, what can you use it for? What are all the things that you can do? faster, smarter, better, as a result of being informed by that model?
Griffin Jones 10:34
Yeah, one of those things that I want to zoom in on his financial risks, how does that AI that use of AI that you're all doing go far beyond the reconciling of financial risks, to remove financial risk, and what's the difference between those two things are.
Dr. Mylene Yao 10:51
An important part of our platform is that we're very adaptable. We already start off with many questions and analysis that most centers want, and need. But we're also very adaptable. Like if there are specific unique situations that you want to analyze, we can do that too. But we also in addition to the IVF outcomes model, we also analyze utilization of care. So, for example, we've now analyzed utilization of care for over 100,000 unique patients. And so what that means is we can chart for every UD patient, what are all the services that they kind of received from your center, and over what period of time because time matters to the patient, because, you know, their biological clock is ticking. But time matters to the clinics too, because you are investing in the patients that you see. Because you're investing a lot of manpower and a lot of support, to help them get to having a family. And so we take all of that into account. So the analysis could be, you know, really accounting for the operational cost, the utilization. And the reason this IVF outcomes prediction model is important is not surprisingly, patient, let's say you have four prognostic groups, right, just making it up, it could be three, it could be four, it could be five, whatever, the people with the best prognosis in that group, they actually will have a lot more utilization of FGTS, because they have more crowd preserved classes, and so on, and so forth. And maybe patients within the lowest prognostic prognostic group may have the least number of FGTS. And so the kind of average weighted revenue that you would get, as a business from these different groups, this can be very different. And so again, if there's not a stratification, you're really looking at all operational costs, all revenue, as kind of a lump sum. And that's really can, you know, really doesn't help you to optimize, you know, strategy and growth and planning or, you know, making your operation more efficient. So those are the ways in which what started out as an IVF prediction model that is so important to support the patient counseling gives patients what they want, is also the fundamental model that can support a lot of business decisions as well.
Griffin Jones 13:41
There's a lot of uncertainty in the patient journey. And we just had an event about it through arm yesterday going through the whole patient journey. And there's countless points where there's uncertainty and there can be points for drop off every time the patient feels like they have to make a decision, and they don't have the information or they don't know how to weigh the pros and cons of the decision. Indecision is always a motivator for inaction. And so for you all, what were the biggest points that you were seeing where patients were dropping out? How did you look at that?
Dr. Mylene Yao 14:21
Patients want to have a family, they're already seeing a doctor, which means they're motivated, they want to do something about it. And not knowing your personalized, you know, probability of success is a big barrier, especially since many patients know, maybe friends or have heard in the media by now. I mean, everybody has heard good and bad experiences from IVF. But the problem is that all of those stories aren't personalized to them, you know, what happens to another person may not be their situation. And so, you know, the most important thing is you really to figure out based on the patient's profile, what is really hurt, probably of having a baby from not just IVF, but compared to other treatments such as IUI, or other options, or even not doing any treatment, so that people can have some visible, you know, good visibility as to, you know, the pros and cons of different treatments, but also the cost, of course. So, and it's not just that it's expensive. I think this is complex, because, in addition to the expense, you know, if someone will talk about people they're paying out of pocket, and then we can talk about people with coverage, people paying completely out of pocket, in addition to the expense, there is a chance that it might not work, which means the money to them, the way the patient's right fully would perceive is the money went down the drain, there is no purchase. And in the US, let's say the cost of IVF, justifiably is high because of all the expectations we as patients have from this treatment. So it can depending on where you are in the US, it could be somewhere between 10 to 20, or even 30,000. All in, by the time you include everything, you know, FET IXI, and if you choose to do PGT, so for the patient there, I mean, for us consumers, there's really no consumer purchase like that, where you pay that amount of money, and you may not get the product, which is the baby. Now from the provider side, we care a lot about provider empathy providers are working so hard, their teams are really going all out for these patients. So they're providing top quality care. So the question is, well, how do you reconcile, you know, the two things, you have centers providing excellent care, you have patients feeling like they paid and didn't get what they want? So that's kind of the question we more and more we look, I didn't realize this, I started out as an academic researcher and a clinician, too, you know, so my journey with Univfy and leading Univfy it was like peeling an onion, one layer at a time, like, oh, patients need individualized care patient needs, patients need personalized prognosis. Oh, patients need a way to cap their financial risks, not necessarily even cost, but the risks that they perceive, oh, patients need to be educated because, you know, many people may not succeed on the first try, even though IVF is a very effective treatment, and is the most effective and safest treatment. But they may need more than one treatment to have a family. And some people may not succeed, even if they try three times. But how do you put that together to educate the patients, so they see it as a course of treatment, but also so that the pricing can reflect that what
Griffin Jones 18:06
you're talking about what you're tugging at is that there is something beyond clinical outcomes relative to the standard of care, clinical outcomes are requisite. They're they're absolutely necessary. They're insufficient in terms of just categorizing all of the standard of care if we when when you're talking about you have the quality of treatment, that's kind of like the product when you're talking about the market problem is really talking about the delivery. And if we were to use a simple example, let's say we have the best pizza in town, it's the very best pizza. That's the best product or clinical outcomes. But then you also have, if we don't have parking for the pizza parlor, if there's no way to order, they don't answer the phone, they there's no way to order via app, if they can't take electronic payment. If it takes an hour and 45 minutes to get your pizza, it doesn't matter how good the product is. Because the delivery, what you're talking about the market problem is irreconcilable to how good the product is. And that when we think of the standard of care as just clinical outcomes, that's what we're doing. We're thinking of just the pizza and what you're talking about is talking about the rest of what the the standard of care is.
Dr. Mylene Yao 19:26
Well, Griffin, that's that's a great analogy. And I would maybe expanded a little bit. clinical outcomes are the most important things, but it needs to be stratified and personalized. When you lump everybody together and call it clinical outcomes. There's really no visibility to what are you improving? So for example, I think you don't need to be a doctor to know by now we all have friends and family that have you know, been touched by care Sir, right? So if you were to go through a pit, every patient knows, even if you don't have cancer, well, you, for people who need chemotherapy, there's a course of chemo, you don't just go in once and say, Oh, what's the remission rate from doing one session, your oncologist is going to tell you, Well, this course of chemo is going to consist of, you know, three visits, or six visits, or whatever, or this is the junk therapy. And this is the remission rate that you could expect. And so, you know, there's kind of a framework for that. And that's also going to be stratified by, oh, this, this patient has stage one, this is the right protocol for her, or this patient has stage two of this particular kind of cancer. Now, fertility, fertility, you know, conditions, not cancer. But if you, I think there are many studies that have shown, when you ask patients, they do, you know, kind of explain the stress, and, you know, the mental burden is really similar to what, you know, patients with other conditions are, you know, can experience and but we, I think as a field, we don't do a good enough job, to really kind of figure out this course of treatment, so that we can give patients a view of what their maximum potential of having a family could be like, and also package it in a way so that they could actually, you know, afford it and achieve it. And I think the what a lot of people don't know, is this does not have to come at, like a huge cost to the Fertility Centers. And this is what is not like, you have to give anything away for free, you can still be growing profitable, F very healthy, you know, really successful business, but there's a way to package it. So that is a win win.
Griffin Jones 22:05
I also want to touch on this stratification piece a bit that you brought up because it there's a cost for not stratifying it so you were correct in saying it, the clinical outcomes need to be stratified. And they do because when we just say things like IVF has an 80% success rate, there is a big Asterix and what Dr. Yao is talking about is you have to stratify that Asterix and I can tell people on a marketing side or patient satisfaction side, if you don't, if you don't stratify that from the beginning, you are you begging to have consequences to your online reputation. That's very often where the negative reviews come in, is where people feel that they're misled. I know none of our listeners feel like they, they mislead people. And I know they don't intentionally do but I hear clinicians all the time really and say IVF has an 80% success rate. It's like yeah, if A, B and C or if you're under 35, if you're doing three cycles, if we just say IVF has an 80% success rate, then inevitably we're going to disappoint some people. And so Griffin,
Dr. Mylene Yao 23:15
that's really interesting, because you're seeing I'm actually seeing the a bit of the opposite. So there are two flip sides to this. A lot of patients when they Google online, they're gonna see the average IVF success rate from the CDC. And what they're seeing is a number in the 30s. Okay. So there's that site like so you and they come in, they can come in feeling like, oh, IVF has such a low success rate. And in fact, you know, a lot of people I've heard would say, why is IVF? Why does IVF has such a high failure rate? And at first, I was like, What are you talking about? IVF is a very effective treatment. And we're all talking apples and oranges. And your examples. Great, too. There's the other flip side. And so I feel like, you know, everyone's saying this, everyone is factual. But everyone's talking about different things. And then we want to bring kind of some, some ways for this communication, to really be very clear. And in fact, what we find is that when we you know, we're in the business of building IVF, success prediction models. We have, you know, built models and analyze IVF cycles and outcomes for many clinics now, very diverse kinds of datasets that we've seen, all the way, you know, from smaller, you know, private individual centers, all the way to large academic centers, or, you know, centers with multiple locations and so on. So we've seen really a wide range of patients clinical profiles, and different socio economic demographics. And so we're seeing that, in general, doctors are underselling IVF, when the prognosis is not personalized, because actually, what we do see is, most clinicians are really kind of shy to talk about IVF. And how successful it can be. Just because they feel like, well, I don't want the patients to feel I'm pushing them down this path, because it's more expensive. I don't want them to feel like I have any business agenda. I better not, you know, sick, you know, give them some high numbers. And that actually, is not doing patients a service as well, because and we see that a lot, actually, when we talk to senators and, and they would say, Well, maybe some doctors feel more confident, some really are more shy about it. But at the end of the day, is because there's not a model and the data driving their conversation that is tailored to their center. So the doctors don't really know. Well, I really think if you asked me, honestly, I think this patient has a 70 to 80% success in one cycle, because I think she has all the best, she's has the best profile. But I feel worried to tell her that, because I don't want her to think that I'm being pushy, or, you know, get a bad review, like you said, because there's still a one in five chance that it may not work for her in the first cycle. So in that situation, what we're seeing is actually being too conservative, is also not doing a service to the patients, because they come in, they want a family, they want to know, you know, whether they should do this treatment or what they should expect. So there's really one very, I would say easy, because it's available now, which is well just use the data driven approach, we can build an IVF prediction model, that is using that clinic specific data, their own data, validated with their own outcomes, and really kind of customize in a way to in the patient report, which is the report used to counsel the patients, and the doctors would use this. So Univfy is not part of, you know, providing the medical counseling at all, we're just supporting the providers. And in that conversation, the doctors can feel confident this is based on data from our own center, this has been validated, it just makes them you know, really be able to communicate the actual, you know, facts without worrying about, you know, patients, not trusting them or anything. So in fact, we find that, you know, patients, it really helps patients and doctors to build confidence in that relationship, as well.
Griffin Jones 28:12
I recommend that people go to the Univfy website, we'll link it in the show notes, we'll link a couple of different things that are useful visuals for our listeners, for the concepts that we're talking about, you can actually see some of these things. And there's a sample three IVF report that you can see on the Univfy website. So I recommend that people go and take advantage of that. And I get as as you're talking, we learn I'm thinking, oh yeah, this is why you need individualized predictive outcomes, because you can err on either side of the spectrum, you can either be too bullish. And then ultimately, even if you're not saying, and I don't think most people are saying, oh, there's 80% success rates, but they feel like, Oh, we're gonna get you a baby and it doesn't always happy. It's it doesn't always happen. It's to anecdotal, it might be to based on temperament or to based on optimism. And on the flip side, very often we see we wasted so much time with this clinic because we needed IVF. And and they didn't tell us that and we went some other plate, right? So you're right. It's a spectrum, you can err on other side. This is why you need to have individualized predictive outcomes. And you're seeing this on all of the patient side. So on the provider side on the clinic side, what does it look like for dropout and conversion from start of have someone coming into the office and having a consult and then leaving with a healthy baby? What are the dropout points that you're seeing? Typically,
Dr. Mylene Yao 29:45
right. So I'm kind of speaking this generically, but what we do just so that you have the context for you know what, we're all about data and we're all data driven, but everything that I say is really fun. AR platforms firsthand experience and analyzing data. So when we work with providers, what we do is we actually analyze the utilization of care. And that's how we would know at every step, you know, let's say 100 100 people, 100 patients come in and make appointment for new patient visit. And they are candidates for IVF. We're not talking about people coming in for surgery or other things, right? And what happens to them? They also, a lot of times patients are thinking about what's less expensive? Should I do IUI? Should I wait? Should I try on my own a little bit further? You know, should I, you know, go to another clinic and see what's available there. These are all very, you know, typical kind of mindset and questions that people have. So they come in, and, and every place is going to be a little bit different. I'm just kind of making it more general right now. So we look at, you know, patients coming in for the initial consultation, and what percentage of patients actually complete their diagnostic workup. Let's say they're new patients. And that's very important indicator, because if you can't complete the diagnostic workup, I mean, it's difficult for the provider to make a diagnosis and offer you to treatment options. And then but at that point, when the patients come back, after they've completed their diagnostic workup, and the doctors telling them oh, you know, based on the testing, and your history, and you know, examine you this is your clinical diagnosis, you know, you have tubal factor or you have PCOS, you have malefactor what have you, or maybe you have more than one diagnosis. And here's my recommendation, you have an option to do IVF, blah, blah, and this is your success rate that you can expect, or you have an option of doing IUI. And doctors are really excellent in explaining the pros and cons of different treatments. But patients really need more than that, to really help them make this decision. They really want to know, especially if they don't have full coverage, they really want to know, okay, how much am I spending? And what does that mean? And now, if they are sophisticated, and having done a lot of research, they might say, Oh, what if it doesn't work, you know, and, and if they're not, the counseling should also support that. Because otherwise, if a patient has not been kind of educated in the risk of failure, and what might happen next, then where, you know, the dropout rate could be very high. So for example, all comers and, you know, so that we're just keeping things general. But when we do that, when we do this analysis is specific to each center, to help inform how they can improve their patient awareness programs, and things like that. So but generically, for patients who are paying out of pocket, the dropout rate can be as high as 80%. And that's really, really unfortunate, because that means these patients are not benefiting really maximally from IVF treatment. And a lot of times, it's not just that they can't afford another treatment. I think it's just seems really intimidating to be paying another amount, not knowing whether you can have a baby or not. And so that's why by educating patients and putting together not, you know, in addition to a personalized medical prognosis to put together a financial plan that can help them achieve that, even though Okay, nobody has 100% success rate, but how can we put together plan to help you achieve 80% success rate, or 70%. And for some patients, maybe they have very poor prognosis, maybe three cycles could give them 50% success rate, or patients who want to who may really be a good idea for them to start thinking about donor egg to really think about that as like an overall plan or an option. So those are the things that, you know, the Univfy report, can support. And we can also support, you know, the clinics in designing these pricing programs in a way that's, you know, really a win win. And, you know, patients feel really comfortable knowing that, you know, they have, there's a way to you know, achieve a certain amount of success.
Griffin Jones 34:58
I want to talk to you about How you help clinics implement this because you all have been around for a little while. And one of the differences between the companies that have been around for many years versus those that run through their VC money and then they're gone in a year or two is that they can't figure out how to get the clinic to adopt the solution with the clinics, workflow. clinic workflow, as we say every other episode on this show is one of the biggest barriers to scalability in this field, because there's so much variance between clinics workflow, and it makes it hard for people that even when they do have a really good solution, again, this kind of goes back to product quality of product, but you also have to have quality of delivery or else even though the quality of product comes first, it's a moot point if you don't have the delivery to be able to do it. So I bet you've learned some hard lessons
Dr. Mylene Yao 35:55
analogy. Yeah, definitely. We at one point, when we first started, we were that best pizza parlor. That Oh, but how do we do this? How do we get the pizza? Right? So we definitely had some tough lessons that we learned. And, you know, I think all of digital healthcare, had to learn some tough lessons early on. And oh, and we're really excited. There's one thing maybe I you know, just to mention. So recently, we've been named Top 150, global, digital healthcare companies, by CB insights. So that's a really great honor. And I think a lot of what went into that, to being named there is the delivery. And so I think we start with the philosophy in our company. And this is a philosophy that across the company is top of mind all the time. Of course, we're all doing this to support the patients so that they can have a family. But that is not possible. If we don't have provider empathy, provider empathy. We always talk about patient empathy. You know, that goes without saying, but provider empathy is not something you hear people talk about a lot. And we really focus on that, oh, what does the provider team have to do? Picture what they're dealing with all the things that they have to do to support their patients? So how can we, as a technology company, make it as easy as possible? So now, what we have, I won't, you know, I won't walk you guys through all the phases of how we got here. But what we have now, and I'm really also grateful to the providers that have worked with us, and have given us so much feedback, and put their trust in us to let us improve on our delivery. And so what we have today, is really that white glove ai plus human expert platform, the human component is so important. It's always been there. But we realize we shouldn't call this an AI platform as human plus AI, because we have you really amazing humans kind of, you know, shepherding, you know, the process. So what we can, what a provider can expect is, you know, there's not a duplicate data entry. You know, if you put things if you put data into the EMR, there's EMR integration. And a big effort was actually, that we're really excited about is that recently, we completed integration on the back end with E IBF. And so there is this very seamless and customized integration for each clinic, we understand that clinics use the EMR modules in different ways. And so they don't need to worry there that all that is taken into account. And so it's been amazing to work with the IVF team to be able to bring this integrated service. So now with a click of a button. Patients can I mean, provider teams can generate a report and give it to their patients. However, we also have some clinics that say, Oh, well, we really want to be supported by you know, your your team. And there we also have unified fertility concierge, which is a team of just amazing people, you know, that are registered nurses and they have decades of experience working with providers and patients, knowing the language knowing that what it's like to be in a busy clinic. So we have a lot of empathy there. And unfortunately, concierge can support our clients by really helping them run the reports as well, and even keeping track of so many things. So you could be using Univfy report And hardly lifting a finger and not needing to track a lot of things. And we can do a lot of tracking. Oh, we see these patients are going to be coming in for their recons out, hey, here are all the unified reports ready for your doctors to use. That's the kind of white glove service that we have. And of course, there's some hybrid. So, you know, whatever clinic needs like, oh, we want some IT support and some human support, whatever that is, is already can be configured as well.
Griffin Jones 40:32
I think if you can't figure out how to help clinics implemented it, it's just a moot point. And frankly, it does take a lot of hand holding it does take it isn't just here's your automated solution.
Dr. Mylene Yao 40:46
And a very big part of what we do is, is always customer first. So while you have a e IVF. Integration is the first that we accomplished. Many customers are requesting EMR integrations now, and they're using other EMRs. And we are doing that as well. So we do whatever is needed, whether it's E IVF, or another EMR, we do whatever is needed, so that the customers can have the best experience. And I think that in turn, when the provider team is less burdened, they in turn can give better service to their patients as well. So we really believe in, you know, supporting the provider team so that ultimately the patients will get you know, the right kind of attention,
Griffin Jones 41:35
you must have somehow also figured out the other sticky issue, which is pricing, because sometimes it just it doesn't work, it ends up being too much of an intermediary. And you can either take a piece of the pie, or you can make the pie bigger and the way that people use pricing matters for for which of those that ends up being so how did you decide on the model that you use?
Dr. Mylene Yao 42:02
Right? So there are really two sides. So to be just very, the easiest way to explain our pricing is is a SaaS fee. So that's software as a service or AI as a service, which means we make it very feasible as a monthly flat fee. And it's also customized. So now we have an algorithm for you know, providing an algorithm. So to be very objective, very fair, we take into account, your, you know, your central specifics like your pricing, because the pricing can vary so much across the country and around the world, pricing, your IVR volume. And you know, even the percentage of patients that come from coverage or reimbursement, knowing that reimbursement is usually less, so we account for all of this to make it feasible. And so, you know, most centers don't find that pricing is really a barrier at all. And, and the other hand, on the other hand, getting the ROI is very important. The AI platform is yes, as utilization is really inexpensive, but also at the same time, we recognize that knowing the ROI is very important for business. So we really look at it as you know, if you, you are going to get a certain amount of increase in IVF conversion. And you know, if you get even one, not even one additional conversion a month, it will be more it will pay for the unifies fees, you know, and half excess. And so that's kind of like our principal. And the conversion going back to you know, what you started out discussing, it is important, because it's really another word for, you know, helping more patients be able to access care. And there, we find and we've done a lot of business analytics now with individual clinics to know that for each clinic, when patients are counseled with a unified report, they are more likely to proceed and go on to IVF. And for some clinics, that might be a two fold increase for some clinics that might be up to a five fold increase. So we're really excited. And it's also seems that we've been doing these business analytics for, you know, four to five years now consecutively. So what we're seeing is also that this kind of increase in IVF conversion is continues to increase over time. And, you know, the more reports that you are the more patients you give reports to the more you know, expanded access As you can get. So these are some trends that we've observed from working with individual clinics. But now what we've done is an also really grateful to clinics that are that want to give this information back to other providers and patients and everybody in the space is we're forming research collaboration, we now have eight centers that have joined the research, collaboration and more than a joining. And they're giving us permission. And it's all IRB approved and everything to to aggregate all of these analytics. So it is not like when we provide a service to each clinic, that's business analytics. But when is aggregated, and we report utilization of service back to the public, that's research. And so we're doing that right now. And we're really excited, we have a manuscript that we're preparing right now, in its final stages of drafting. And it's definitely, you know, we can't wait, you know, until we share the science behind it, and the analytics, you know, with, with everybody, so that we we can help, you know, more patients be able to access care.
Griffin Jones 46:25
And you have a third constituent, which is employer. So if we were having this conversation 20 years ago that, that third constituent probably wouldn't enter the conversation, wouldn't want your employer to know anything about your fertility treatment at that time. And now they are among the people that are the most interested constituent in clinical outcomes in individualized care, because this is the benefit that they're offering to their employees. And if they're not happy, if the employees aren't happy, then the employers aren't happy, it doesn't work as a benefit for the employer, if it doesn't work for the employees. So how does Univfy work with employers?
Dr. Mylene Yao 47:10
Right, so we're getting a lot of interest from employers, because what they want, and maybe just, not all employers have the same type of benefits, right? We have really amazing benefits companies now. Like, you know, progeny, carrot, Maven kind body is amazing. Because in order to expand access to care, we have to have many different formats, because they're really, you know, have there's diverse types of employers with different ways that they want to support their employees. So I think is really amazing that we're seeing that in the marketplace. And employers really want to know, what is the value we're bringing to our employees. So especially for employers, who are not supporting unlimited fertility care, if there's some kind of financial limit, which is still sadly the case for most employers at but we need to work with that. I mean, they're constantly expanding their, you know, budget, but still, we need to support, what is the best that they can get. But how about the traditional way of doing it is, hey, let's just reimburse the doctors less. That's not value. So I think there's more and more realization, that that is not the best model that does not give back the best support to the employees. So what employers want, and it doesn't have to be that there is a way to help support costs, and cut costs without kind of penalizing the providers. And so what employers really want to see is, how are our employees supported in that navigation? Do they understand, you know, the pros and cons of different treatments? And do they understand that there may be an out of pocket cost later, because when employers are not providing unlimited coverage, that means what we see so unifies the firsthand experience from that is usually when some patients, they initially have coverage. So let's say the employers gave them 20,000 or even 30,000, which, you know, is not ideal, but it's it's really good as a start. So employees go in with coverage, so they feel relaxed. Maybe they didn't ask a lot of questions. Maybe they didn't fully understand what that there might be multiple cycles. I'm sure the doctors explained it, but maybe they just didn't hear a certain way, it's because there's lot of overwhelming amount of information in that counseling session. And then they go through the first cycle, and it's covered, great. But if it doesn't work, and now they realize, Oh, I'm on my own. So what we're seeing a lot is that some employees that have initially have coverage, they become patients with no coverage after the first cycle. And because they hadn't planned on that, and they might say, to, you know, they might say, Oh, how did I know? I would have planned this way? Had I known I would, I wish, our employer could have supported a multi cycle program. Because now, we're suddenly like, the employees is out of pocket, and really cannot afford a second cycle. And then the employers might also feel like, oh, we funded our employees, how come they're still people coming back? Saying they didn't get their have a baby? Right. So So I think we're, you know, seeing more and more of those questions coming from employers. And I think there's a really good way to set expectations, and really, ultimately, you know, being able to expand access to care, by kind of like making that whole navigation seamless and support it by personalized prognosis, and tying that to a really good, you know, financial plan. So maybe initially is the employee and employer or maybe they chip in, you know, to support a program, or at least give the employee that option to chip in. So those are some of the concepts that are coming through right now
Griffin Jones 51:56
covered a lot of ground today, we talked about narrow AI and machine learning how it is used by Univfy to remove financial risks, how individualize predictive outcomes are necessary, because otherwise, you can err on one side of the spectrum of over selling or under selling or being unclear. And you don't have to rely on human temperament or opinion, you have hard data to use, we talked about how you actually implement that with integrating into EMRs, making sure that there isn't data duplication, that you're accounting for the different uses, that people use their EMRs for using provider reports that even that that can be repurposed for the provider and you know, five fertility concierge can help run those reports and insert them into different points of the workflow, we talked about how you come up with a pricing model for all of this in a way that works for the clinics. And we also talked about even how business analytics comes to be researched for the field once it becomes aggregated. And I wish that you were in an event that happened just yesterday, and people were asking about the tools for IVF conversion, because people really want these tools. And so I recommend to those of you even if you're still checking out unifier even to use it for yourself, this is free if you go to Univfy.com/ivf patient retention, but most of you aren't going to remember it, you're going to go to your phones and click on the link. And so it's going to work and bring you there anyway. And you can download this, it's free to be able to see what it looks like when you have a win. If you have 100 patients on general the different points of drop out. And so go ahead and take it go ahead download it and plug in your you can point to your own workflow. And numbers. I encourage everybody to do that for Dr. Yeah, I was part we you given the audience so much today, how would you like to conclude either about the challenges of IVF conversion and patient drop out in the field or what Univfy is doing to solve them or what unifies doing with artificial intelligence? How would you like to conclude,
Dr. Mylene Yao 54:17
I really appreciate this chance to, you know, chat about the different ways to use the Univfy AI platform. And I would say, you know, there's a lot that all of us meeting providers, companies, you know, all the stakeholders in the fraternity space, there's a lot that all of us need to do and can do, so that we can help more patients to have a family. And in fact, you know, I think we have a shared vision in this space, which is great. We all just want you know, everybody who wants to have a family should be able to have one and we should be able to provide very equitable, high quality care can do it in so many ways. Whether you are advancing therapeutics, advancing diagnostics, advancing other types of personalized care, or advancing, you know, a better way to, you know, make IVF care or fertility care in general more feasible, more affordable to patients and employers that want to support them. I think, you know, there is a way to use the technology that we can provide, it's going to take so many people in so many companies to come together to really accelerate this, you know, access to care, vision. So we would love to be able to support whatever it is that you're doing, whether you're on the business side on, you know, care, or research, Univfy has the technology to help you accelerate. You know, your vision.
Griffin Jones 56:04
Dr. Millennial, thank you so much for coming on the inside reproductive health podcast.
Dr. Mylene Yao 56:08
Thank you, Griffin.
56:11
You've been listening to the inside reproductive health podcast with Griffin Jones. If you're ready to take action to make sure that your practice thrives beyond the revolutionary changes that are happening in our field and in society. Visit fertility bridge.com To begin the first piece of the fertility marketing system, the goal and competitive diagnostic. Thank you for listening to inside reproductive health