Word-of-mouth recommendations are great for picking a restaurant or movie, but are they the best way to find a doctor?
What if there was a better way to use data to find the right doctor every time?
In this episode of CareTalk, David Williams talks with Nick Reber, Founder and CEO of Garner Health, about how they’re leveraging detailed data, including physician history and patient outcomes, to match patients with high-quality doctors.
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Episode Transcript:
David E. Williams: How do you find the best doctor? A word of mouth is the usual way, but shouldn't we be able to use data to drive such an important decision?
Hi everyone, I'm David Williams, president of Health Business Group. Today's guest, Nick Reber, is founder and CEO of Garner Health. He's leading the charge in transforming healthcare navigation. Well, before we hear from Nick, I want to take a moment to thank my surgeon, Dr. Nora Fullington, for giving me the very best experience in my recent hernia surgery.
I know that's a funny thing to talk about, but I am truly grateful for her. And this month is really all about gratitude. And along with Dr. Fullington, there's someone else we don't get to thank enough. That's ourselves. It's sometimes hard to remind ourselves that we're trying our best to make sense of everything, and in this crazy world, that really isn't easy.
So here's a reminder to send some thanks to the people in your life, including yourself and your surgeon. BetterHelp offers entirely online therapy that's designed to be convenient, flexible, and tailored to fit your schedule. Just fill out a brief questionnaire to get matched with a licensed therapist, and switch therapists at any time for no additional charge.
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Let the gratitude flow with BetterHelp. Visit BetterHelp. com slash CareTalk to get 10 percent off your first month. That's BetterHelp, H E L P dot com slash CareTalk. Nick, welcome to CareTalk. Thanks, David. Appreciate you having me. I want to talk about inspiration in particular. What inspired you to start Garner Health?
Nick Reber: Awesome. Yeah. So I my background, I worked in the investment world, was an early investment partner at Bridgewater Associates, which is a Hedge fund run by Ray Dalio and, and I actually had some back issues myself. And I was you know, it sounds like you were dealing with something somewhat similar recently.
I actually got misdiagnosed, had a surgery in my thoracic spine when I really didn't need one of my cervical spine, had a complication or revision surgery, had about five of them. And somewhere along the way, you know, I got wheeled out in a wheelchair from one of my neck surgeries, which Turns out I was actually fine.
I didn't really need I could walk. I was fine. And I started in the hospital said, no, no, no, you have this wheelchair. It's, it comes along with your surgery. It's paid for by your insurance. And I was like, but I don't, I don't need it. I don't know. It's free. You have it. And it's like a thousand-dollar wheelchair.
And I sort of just started pulling the thread on this and started to figure out who actually pays for all this stuff that I probably don't need, you know, and, and all these misdiagnoses and bad outcomes. And, and, and, And that really led me into trying to solve healthcare stuff. And ultimately I then started a health plan called Oscar health was on leadership team there, helped build that out across the country.
And got to study the data for about a million members of fully insured, high-cost quality. How do we improve outcomes? And, really, I got convinced that. The single biggest lever you can pull in improving someone's health outcomes over time and controlling cost is getting them to the right individual doctor.
And then I looked at both the data that was out there to help people with that. And just as importantly, the financial incentives and the sort of conflicts of interest that exist in the healthcare system. You know, you have all these issues with how hospitals negotiate with insurance companies and they don't really allow accountability at the individual doctor level.
And so really, that's the project we've been working on in the last few years. I think
David E. Williams: when, you know, when you start off with the back surgery, that is a good one to start with for somebody who's outside of the healthcare space, because a lot of people get back surgery because it just like the back is killing them and they go to a surgeon.
And as my dad used to say, surgeons like to cut. So they usually be recommended for a surgery of whatever type of surgery they do. And it may or may not help. And you can see about certainly back surgery. It's a very, a lot of regional variations depending on where the, you know, where the surgeons are and what you get.
So I'm, I'm glad. Hopefully you finally got the right surgery. Your hernia surgery is a little bit different, but even there, what happens is apparently about 20 percent of people that go in for hernia surgery. Surgery are actually, they just have a groin strain. They don't need surgery at all and they should go into to pt.
And there's also a lot of a lot of use of imaging which is actually not useful and sometimes counterproductive and expensive. And then people end up going to the wrong surgeon, often a general surgeon instead of somebody who's a hernia specialist. So I feel your pain, although I don't feel your pain, 'cause I feel great from my hernia.
Nick Reber: Amazing. Well, anyway, I'm glad you're you and Dr. Fullington have made some great outcomes. So let's talk about this data-driven
David E. Williams: approach, which is what I understood that you've got at Garner Health. What sort of metrics do you use? And on the one hand, it sounds like it's a really good idea. On the other hand, you're thinking, well, why hasn't this been done before?
Everybody wants to know who the best doctor is for them. Totally.
Nick Reber: Yeah. So, there've been varying attempts in certain ways over the last, let's call it 30 years, really, since the 1990s, as people started to be able to pull data and do SQL queries to figure out which doctors are high-performing.
Really, though, the methodologies really haven't evolved much since then, if you believe it. And the reason for that is a twofold one. The data has really been locked into mostly the insurance carriers for a long, long period of time. And so there were really only a few entities with anywhere approaching the sample size of data required to do the longitudinal analysis to really understand quality cost outcomes, long-term health, all of those things.
And then the second thing is that Partially because it's been locked in a few of those entities, those methodologies have really been stale in my view. And obviously I'm slightly biased here, but, but everything has been built around these sort of episode groupers. If you look at what your insurance carriers do, if you look at what most care navigators or data analytics vendors do, they all have this thing.
called an episode grouper, which is really simply just a cost per patient. And it turns out that's an incredibly blunt instrument to evaluate a doctor on because doctors see lots of different patient types with severe hernias and less severe hernias and all of these sorts of things. And so what we've done.
Is I think very, I know it's unique, and we certainly think it's a lot better than what's been out. There is number one. We've aggregated three-quarters of all the claims data in the country in a longitudinal way. So we have hundreds of millions of patients worth of data being tens of billions of encounters.
And then to importantly, Yeah. We don't use those legacy episode groupers. Instead, we've written a whole language that allows us to measure each individual decision and each individual health outcome generated by a provider. It's a library of over 500 individual metrics, and that allows us to be a lot more pardon the pun, but surgical and precise.
In terms of how we actually evaluate providers, both on the total cost of care and the quality or health outcomes generated.
David E. Williams: Yeah, I'm thinking back to what you described with your background in terms of being at a hedge fund before. And if I compare health care, with finance, yeah, it's pretty different.
So in healthcare, you can get away with having these you know, groupers that somebody came up with and wrote a paper about in the eighties and still use that and get away with that. And a hedge fund, if you use some sort of heuristic or rule of thumb or something that, you know, somebody came up with a bunch of time, you're going to lose out, you're going to lose all your money and get fired pretty quickly.
Which leads to another part, which is also related to accountability. So a lot of times the pushback actually in the healthcare field has been, aside from the idea of the methodology, is also about individual accountability. So a lot of the discussion is also about, well, you know, it's not fair to evaluate an individual physician.
You should just look at the team or, you know, something a little broader because it's a team sport, etc. Whereas a patient often want to know, like, which doctor, not like which group overall. So. Anyway, that you're it makes sense to me describing a little bit more of a financial approach to a health care public health issue.
Nick Reber: Yeah, I mean, and it's exactly I think largely a lot of the pushback from the physician community has been. The sort of black box and unfairness of the old methodologies. And that's why you've needed to get evaluated on a group or a larger sample said it's, well, there's not, there's only 50 patients or, or the methodologies, you know, are, are bad now.
There are a few. to areas where you actually where care is really delivered in a group. Like if you have breast cancer and you're getting a mastectomy, like you need both a plastic surgeon and a general surgeon and both need to be evaluated together. Great. That's a minority of cases. The vast majority of the time patients think about it to your point.
Hey, who am I going to see? I'm going to see Dr. Jones, Dr. Smith, Dr. Fullington, like, you know, for my pain. And what's fascinating is that doctors practice so differently, even in the same office right across the hall. And so you actually, if you can get the data to actually measure that, and you have the sample size, it really yields way better results for patients.
If you can do it that way.
David E. Williams: So, you know, in this, so in the hedge fund, it's, it's easy also to measure if you're doing well or not the end of the year. Someone doesn't say, is that a real dollar in the account or not? You know, it's pretty clear. Now here, we want to look at patient outcomes. And can you say, you know, if you use your methodologies, are the patient outcomes better?
And are costs lower? Is that something you can measure?
Nick Reber: Yeah, so, so the cost is actually somewhat similar to trading a hedge fund book. Yeah. You know, in other words, there's randomness just like in markets, there's randomness. But at the end of the day, we have a book of, you know, nearly a thousand clients now and We can look at the total cost of care of those people, and we put our fees 100 percent at risk if we're not delivering total cost of care trend reduction.
And we're one of the few folks to do that. And so we actually in that way actually looks a lot like a hedge fund, at least for us now. You know, and we can get fired by our clients just like we could back in the day. The quality situation is a little more oh, I don't know, up to interpretation.
And there, I think you need the way approach that we take, which we think makes sense is to create something of a basket. So the first thing is, if you're reducing utilization, it probably means people are healthier. You know, usually if there's fewer complications, if people are spending fewer days in the hospital And there's lower cost as a result.
That's pretty good. But of course you could lower costs without improving quality. And so the basket that we use is a set of things like the number of E. R. visits, the number of hospital days, the number of patients with controlled versus uncontrolled disease. So for us, you know, you're seeing a 10 percent reduction in E.
R. visits in the first year. You're seeing a 20 percent improvement in Patients with chronic disease, such as diabetes being controlled a one C levels. So we have a basket of those things that we look at from, from sort of post-procedure things, complication rates to longitudinal health outcomes like ER and hospitalization rates to even in more longitudinal sort of chronic disease stuff.
And generally you're seeing a 10 or 20 percent improvement in all of those top-line metrics when you put in Garner in the first year to 18 months.
David E. Williams: Great. So now if you, of course, one of the things that's screwy about health care is this third-party reimbursement. So the user and the customer are different and you've got strange you know, strange incentives in place.
So one of them has to do with the relationship between the patient who's not hiring. Garner directly, and they're working for their employer. And so if you're now trying to get someone, maybe to to switch doctors or to go to a different doctor than they would have done otherwise, which is great. If I know that you're motivated, you know, to help me out.
That's why the patient outcomes matter. But since you're being employed by my employer, you're there may be a concern. Oh, gee, is this just like a cost-cutting thing? So how do you, how do you build trust in encouraging patients to go in the right direction that's ultimately going to be right for them, but also good for their employer.
Nick Reber: Yeah. So a couple of things, the nice thing about it is about healthcare is that it's really very different than shopping for, I don't know, clothes or cars or houses. Lower cost goes with higher quality in healthcare. And so that's just a nice. Sort of outcome. The healthier the people are, the fewer E.R. Visits, the fewer complication rates, et cetera. The lower the cost is going to be. And because health care has been so inefficient for such a long time, there's not even any correlation between the price of a surgery. So if you take your my back surgery, your hernia the price of just that surgery and the complication rate on that surgery or the outcomes after that surgery.
So there's no relationship whatsoever. And if there is a relationship, higher quality equals lower cost. So that allows us to create a sort of a, an economic model that aligns with, I think, the moral model that we want to have, which is, hey, if you're just really high quality, you know, let's not make sure that surgery cost is not too high, but we'll make recommendations in that way.
And then the other big thing from a patient engagement trust building is so number one, we have to be transparent. We have to describe that to folks. Here's why we chose Dr Jones and we can get all the way down to the complication rates, the readmission rates like this is literally why we chose this provider.
And I think being transparent in our data methodology that is sort of bottoms up really helps that. So it's not a black box. Hey, it's here's all the complication rates. Here's how we did it. This is why we chose Dr Jones. Okay. And then the second thing is that we feel like it's important to share some of those savings back with the employee and give them choice.
So in the Garner model, you keep your network, you keep your segment United Anthem Network Garner layers on top of it. So you're not losing access to doctors, but we're saying, Hey, if you want to participate in the savings from getting higher quality, great. We're going to work with your employer and we're going to cover all or most of your out of pocket if you use the tool.
That's your choice. You don't have to. But if, but we think you're gonna get a lot higher quality care. It's also easier to book an appointment and all that stuff. And, and then you get to participate in the savings by getting your out-of-pocket covered. And so we think that's a model that that builds trust and sort of helps.
People just understand what the incentives are that if you want high quality, here's some extra money. If you don't, you want to ask your neighbor. Like, that's all good too. You're not going to lose access.
David E. Williams: How do you deal with some of the fragmentation and lack of interoperability in the system?
Because on the one hand, there's the issue about these groupers and the right methodology. And on the other hand, it's about getting access to high-quality, timely and thorough data. How do you work through that?
Nick Reber: Yeah. So interestingly, the most of what we do is based on healthcare claims data. We do have some other everything from mortality data to some EMR data, et cetera.
Most of what we do is based on the claims data. And the interesting thing is that Claims data has actually been interoperable for 40, 50 years. And the reason for that is because it's the only way everyone gets paid. And typically data systems follow the money. So EMR data and electronic medical records, you know, those things have been incredibly messy, unstructured, no, no real way of, of having standardization, obviously some AI stuff is helping on that a bit, but.
But the record of payment is incredibly precise because hospitals don't get paid unless they, they do it that way. And CMS has done a good job of reasonably organizing that stuff. And so you can actually get very good. I don't want to overstate, understate the amount of work it's necessary to clean, validate, to duplicate.
But if you have different claims data sets and you have good modern cloud infrastructure and data governance on top of it, you can actually create a really cool longitudinal record. And the claims data actually, as we've gone through, it has about 90 percent of everything you'd want. You know, 90 percent of the metrics we'd ever want to create are in there from, obviously, you can look at complication rates.
You can look at, is this doctor doing physical therapy before surgery? You can look at, is this the right drug for this patient under these times? You can look at their long-term health outcomes. And so, you know, You know, I think that is the mechanism by which we've sort of been able to sidestep some of the interoperability issues in the, in the healthcare world.
David E. Williams: You know, it's interesting what you say about the, the claims piece goes back, you know, the interoperability even earlier than the groupers, if I'm keeping track of my decades here. And you know, there's a lot of excitement when you have the electronic medical record data come in, cause that's really the clinical record.
And I think what you find is partly what you're getting at is when you look at those records, if you can get ahold of them since they're not required for payment. They may have a lot of great-looking fields, but they're not necessarily filled in, and they may not be filled in consistently. Even something like blood pressure, which you think would be standard is actually different across the different EMRs.
On the claim side, so people have to fill in everything that's needed in order to get paid, but the clinical use for it is sort of a. You know, secondary use. It's not what it was designed for. And so how do you, is there an issue about when you analyze that data? You know, you're, you're, you're picking up things about how people bill and what their financial strategies are, as opposed to what's really clinical.
Or is that not something you have to worry about?
Nick Reber: Yeah, very good question. And an important one is we like really get into the weeds on this stuff. If you look at it about 60, 70 percent of the metrics. Okay. Don't actually require much nuance like you can't fake a complication like the patient is that in the ER room after the surgery, you know, things of that nature.
There's actually a ton of that. You can't really fake doing physical therapy before surgery for the most part, et cetera. Or not doing it. But, you know, you can do. Oh, let's see. You know, we're looking at our cardiology metrics and we're looking at. Okay. Providers are who are doing in our direct to me is for, you know stenosis of the artery stenosis.
And there can be severe case or not severe case. And that's actually a provider billing question and severe cases. The literature says it's okay to do this procedure and the less severe cases. It's not really appropriate for those patients. Right? And so there, what we have to do is look at. How providers billing bill in general and okay, wait, you provider were the one doctor in the whole country that had 100 percent of your patients be severe cases.
I don't believe you. Right? And so when there's the 30 percent of the cases that do have a little bit of what you might call clinical or billing judgment, if you have enough sample size, you can look at the patients that these providers see, you can really quickly spot. Yeah. Providers are basically upcoding stuff and you're like, all right, I don't believe you anymore.
David E. Williams: Yeah,
Nick Reber: and there's a variety of statistical adjustments that you can do in those cases. So again, that's a, you know, about a third of the time we have to do that sort of thing. That's a relatively routine thing for us now. But, but it does require vigilance and management and to know which case are you in?
Are you in the hard and fast case? Are you in the provider judgment billing case and then we handle those things a little differently. Okay, but it's a significant percentage of the claims and you've got and I think
David E. Williams: one way to look at it is you could either throw up your hands and say, well, we don't look at that.
Let's go and try to delve into all the clinical records, but it's actually easier and probably more systematic and more reliable to make these adjustments that you're talking about on the billing side.
Nick Reber: We believe we've gotten some access to EMR data, et cetera. And we actually think there's, you know, if we'd spent the massive amount of work necessary to do natural language processing, to codify all that stuff, it would only give us like a 7 percent lift.
It honestly wouldn't, you know, there's a few subspecialty cancer things and a few other things like that that you're like, Oh, it should be useful. But for the vast majority of specialties it honestly doesn't provide a whole ton of lift for us.
David E. Williams: I mean, it's a proof for what you're doing and other parts of the business that are a little different, but some of these real-world evidence companies that actually spend a ton of money to try to take the EHR data.
Even if it's actually their own EHR that they own, like Flatiron and, and make it better. And they can show that they can make some improvements. They can't show that they can make money by doing that. But that's a topic for different podcasts. So let's talk about value-based care because another approach to what you're doing in terms of improved outcomes and lower costs would be value-based care.
Are you an alternative to value-based care? Do you layer in on it or are they just kind of independent?
Nick Reber: Well I'm going to be perhaps a bit off consensus on this. You know, value-based care can mean, of course, a lot of different things. I actually think if you want to change health care for the better, value-based care is a bit of a distraction.
We can work great with providers that are in value-based care or not. Groups that want to go in that direction or not. We're very flexible. But, you know, when I started my career, one of the things I did at Oscar was negotiate our hospital system contracts around the country. And I had. A couple of hospital systems, you know, let's say one of your top three academic medical centers, where we had a 50-50 full-risk deal, big deal, joint venture, et cetera.
And I went to them and I gave them some data on some of their providers around, you know, excessive use and high complication rates. And I said, Hey, we're in this risk deal. Don't you want to change your behaviors and like, you know, eliminate all these crazy extra MRIs you're doing or complications you're having on surgery?
And they went through it with their CFO and said, basically, Hey, we've thought about it and honestly, we're, we believe we're economically better off just keeping doing what we're doing. You know, that ultimately a, you're not that huge a part of our book, but even if you were, you're going to ratchet us down.
And in three years, when we renegotiate, if we, if we shrink the pie, well, you're, we're just gonna get the same share of a shrunken pie. And what's fascinating about what we're doing. And so I sort of got learned, okay, that doesn't quite work. Now, what's fascinating at Garner is because we are, I think, one of the fastest growing employee benefits, and we have a really active referral program, or our data tool is being used by primary care referral physicians for referrals.
We now control the care journeys of a couple million people, and we're now getting hospital systems around the country. knocking on our door saying, Hey, what do I have to do differently to get some of that referral volume from you? And then we can say, well, actually, we now have hospitals that are actually, if you believe it, changing their physician compensation based on our data.
And in that, I think if you really want to change health care, my view is that it's much more about controlling volume than it is about. Paying differently because the payment, honestly, it's whether I pay you this way or that way, it's still just a payment. The bigger thing is, well, how do I get more volume to you?
And if I can reward you for, with, for good behavior with more volume, the world will change. It's sort of like Uber, you know, if you want to change, get bottled water in the back of Uber's, don't pay people to get bottled water. Just give them a five-star system and say, the only way you get passengers. Is by getting a five-star.
And so that's my philosophy on it. Anyway, maybe a little alternative, but I think that'll be our path forward as an industry.
David E. Williams: So last question for you, Nick you know, you've been at this for a while. You've seen a lot of things in, in healthcare. There's a new administration coming in. We're at, you know, interesting point at the, the economy and you've got a lot of baby boomers that are retiring.
What sort of advice would you give somebody who's starting a healthcare company now, other than not to do it?
Nick Reber: Yeah, I certainly got that voice by several from many, many folks. You know, I think, I think just really making sure you understand. I had a lot of folks say, I'm going to build something on top of, or in spite of the existing managed care dynamics of health care.
And. I think that stuff rarely works. And if it works, it works at very small scale. So I think the real key is to really spend the time to understand how does, how do health, like really what drives the profitability of, of providers, of health systems, of insurance companies, what are their real incentives?
How do those negotiations work? How does the money flow? You know, like what are the incentives really at the end of the day? Why do what is the barriers to entry and why are there such tremendous network effects of those businesses today? And really understand how your business plays in that very complicated economic landscape.
And I think the successful businesses are the ones that have a real idea on that. And the ones that are okay, but maybe don't ever scale are the ones that hit a wall because they're like, Oh, the health plans no longer want me to exist, or the providers no longer want me to exist. And, and I need them to want me to exist.
And so I think that type of research is really, I think really critical, particularly in the healthcare world.
David E. Williams: Well, that's it for another episode of CareTalk. My guest today has been Nick Reber, founder and CEO of Garner Health, which is using data to find the best physician, improve outcomes, and save costs.
Nick, thanks for joining me today. Thanks, David. I'm David Williams, president of Health Business Group. If you like what you heard, or even if you didn't, please subscribe on your favorite service.
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