Data-Enabling Health Care | Clarify Health CEO & Founder, Jean Drouin

In this episode of TD Cowen’s FutureHealth Podcast Series, Charles Rhyee, Health Care Technology Analyst speaks with Jean Drouin, CEO and Founder of Clarify Health. Clarify Health is a healthcare analytics platform that uses comprehensive, longitudinal and linked data from clinical, claims, prescription, lab, and consumer data sources to inform thousands of predictive models and streamline decision-making for payors, health plans, and pharma.

They discuss the digitization of healthcare data in the past decade, early efforts into data analytics and population health, as well as challenges that still remain. They also explore how Clarify Health combines unique and detailed datasets with a technology stack that drives value for payors, providers and pharma. Clarify enables payors and providers to adopt risk-based contracts by offering data-driven insights into patient populations. Lastly, they discuss the future of our healthcare system and the role that data can play in addressing problems exposed by the COVID-19 pandemic.

Press play to listen to the podcast.

Transcript

Speaker 1:

Welcome to Cowen Insights, a space that brings leading thinkers together to share insights and ideas shaping the world around us. Join us as we converse with the top minds who are influencing our global sectors.

Charles Rhyee:

Hello, my name is Charles Rhyee, Cowen’s healthcare technology analyst, and welcome to the Cowen FutureHealth podcast. Today’s podcast is part of a monthly series that continues Cowen’s efforts to bring together thought leaders, innovators and investors, to discuss how the convergence of healthcare, technology and consumerism is changing the way we look at health, healthcare, and the healthcare system.

Charles Rhyee:

And in this episode, we’ll talk about data and its ability to align incentives and improve health outcomes. And to discuss the topic with me is Jean Drouin, CEO and founder of Clarify Health, a healthcare analytics platform that uses comprehensive longitudinal and linked data from clinical claims, prescription lab and consumer data sources to inform thousands of predictive models and streamline decision-making for providers, health plans and pharma.

Charles Rhyee:

Thanks for joining us today, Jean.

Jean Drouin:

Thank you, Charles. It’s a pleasure to be with you and I really appreciate the invitation.

Charles Rhyee:

Yeah, thanks. So when we talk about data in healthcare, it really wasn’t that long ago when health records were largely kept in paper records and analysis were done painstakingly with Excel, but fast forward probably just a little more than a decade and we’ve seen this incredible transformation in the healthcare industry where now most, if not all health information has been digitized. And when I think about it, isn’t that just the first step? Isn’t the next step really trying to make sense of all the data that we have now?

Jean Drouin:

Yeah, very much so. And I think for a long while, we’ve been focused, to your point, on bringing in EMR platforms to allow clinicians to capture important information, as one example. Now, interestingly though, in the background, the US health system has been collecting a very large amount of additional information, claims information, lab information, social determinants of health, which, intriguingly, banks and consumer firms have been collecting for their own purposes for years and years.

Jean Drouin:

And the real challenge now that you hear CEOs talk about a lot, whether it’s providers, payers, or in life sciences, is how do they transform what are now significant datasets into insights in a more timely, precise, and ultimately actionable way, because actionable means that, presumably, some amount of ROI is generated on the other side.

Jean Drouin:

And some of the questions that people are asking are starting to change as well, because instead of just saying, “Hey, can I get historical information on someone and can you send it to me?” which is what providers would do, right? People are now starting to ask, “Well, can I follow referrals around? And not just follow them because I want to understand where they lead, but how can I match a patient to the right care?” So smart referrals. They’re starting to say, “Well, can I look at prior patterns of practice to inform how to improve?” and doing that by applying, for example, baseball style analytics, just as sports teams use to help their players improve. So the nature of the questions is starting to get more sophisticated as well.

Charles Rhyee:

And it’s interesting you talk about that. Banks and consumer firms have been collecting a lot of information probably for decades, right? When we think back in healthcare though, people used to talk about population health. And I guess maybe in that sense, was it just that the healthcare system just had such a narrow view of what information they should be looking at? What did the early iterations of population health maybe set the stage for them today?

Jean Drouin:

Population health accepted more widely is still a relatively recent phenomenon. And the reason I say this is I had a stint in the mid-2000s where I was in the strategy team for NHS London, so all of London’s healthcare in the UK. And it was just around I remember 2005, 2006 that people really started talking about population health and value-based care. And at the time, really what they meant is starting to consider very basic factors such as demographics, income, and a few other things in better matching or delivering the care to certain populations. So they would say, “Hey, culturally, this population doesn’t like to go into the emergency room, but they’d accept an elder having a point of view.” And that was just starting to come into the lingo.

Jean Drouin:

Meanwhile, over in banking and consumer, they were really starting to start predicting, for example, what we might like to purchase, or they were on their way to developing the means to automatically approve a credit card online, where they were developing much richer psychographic profiles, if you will, of how you and I behave as individuals. And the old adage in healthcare, that it takes 17 years for a good proven innovation to wind its way through, it’s almost as if it’s taken us about 15 years in healthcare to say, “Huh, okay, those abilities that they have in the consumer and financial services industry to understand how we might behave, wow, that might be pretty helpful in healthcare as well.”

Jean Drouin:

And it’s really only in the last couple of years that we’ve seen that starting to scale. And the big reason in healthcare is before the last couple of years, the various data sets that you need to stitch together at the individual patient level were still quite siloed.

Charles Rhyee:

Yeah. And speaking of that, so I mean, how much then… You were saying the last few years. Obviously I think, if I’m not mistaken, right, the final rule for interoperability went into effect at the beginning of this year and enforcement just started, but even before that, right, finally coalescing around sort of a set of standards for interoperability. Would you say that that’s been a big driver to kind of accelerate now people’s efforts?

Jean Drouin:

Yeah, I would say there have been a couple of drivers. One of them that might seem counterintuitive is HIPAA. Actually, HIPAA, in my mind, provides a fairly coherent and intelligent way to think about what you can and can’t do. Essentially it says, you know what, for the purposes of improving care, ensuring the bills are correct and doing research, we’ll allow you to pull various largely de-identified data sets together, but if you start using it for more commercial uses like marketing of therapies in pharma, that’s a different thing.

Jean Drouin:

The other is around 2013, 2014, a couple of important changes came about. One is CMS made it possible to become what’s known as a qualified entity, which means that after going through several fairly onerous hoops, you can get access to all of Medicare or the data on the fee for service Medicare population fully identified. The other thing that happened is there was a more of a push, as you know, around value-based payment models. Now, that did slow down during the Trump administration, but it appears to be coming back. And then, to your point, there continued to be a push around driving interoperability.

Jean Drouin:

That’s what happened on the policy side. The big thing that happened on the technology side at the data level was the rise of players like Datavant and HealthVerity and the ability to tokenize and link previously siloed data sets in a de-identified way at individual patient level.

Jean Drouin:

You take all of those things, five years ago, pretty much the largest data set you could pull together was this Medicare dataset. Now, you can pull together a data set on 300 million Americans.

Charles Rhyee:

Yeah, that’s pretty interesting. And it’s amazing how far we’ve come in such a short time. You mentioned just now, right, obviously policy with value-based care programs I guess in effect and what’s been changing. Certainly it seems like a lot of investment decisions in healthcare tend to be guided by the policy at the federal level. You just mentioned, right, there was some changes with the Trump administration around value-based care. It does look like it’s kind of shifting back. Maybe talk a little bit more how is that kind of shifting regulatory background having an impact on not only industry, but maybe even for Clarify here?

Jean Drouin:

Sure. The unpredictability is definitely tough when you’re trying to get going and you have to pick an initial niche in which to play. And so it so happened with us that we got access as a qualified entity to the Medicare data set and we said, “Oh, this is terrific. Hillary Clinton is going to get elected. The bundles will become mandatory. So we will provide the most precise and helpful analytics on how to improve performance in essentially journeys of care.” And there were a couple of other companies at the time, CareJourney and others that came along as well.

Jean Drouin:

And roll forward 2015 to 2018, Tom Price comes in and a different way of looking at the world, and all of a sudden, your market completely evaporates.

Jean Drouin:

Now, we happened to be lucky and have raised our Series B just before that, so we were able to pivot and use the capital we had raised to move into more fee for service use cases. And ultimately I would say we were fortunate on timing and it led us to a place where instead of just focusing on a subset of patients that are in value-based arrangements, we’re now able to focus on all commerce, whether you’re in fee for service or fee for value. But that said, lots of companies weren’t nearly as fortunate on timing. And in this case, there was really quite a bit of luck.

Jean Drouin:

So government seems to take it as sport that every few years, you need to change the rules. It makes it really tough on young innovators.

Charles Rhyee:

And then maybe just to follow

[inaudible 00:11:40]

, how do you see the current regulatory landscape then for value-based care?

Jean Drouin:

Sure. What’s really interesting to me is it looks like the commercial payers and enough providers want to go there now that, to your point, the government seeded the thought, but now the horse is out of the barn and the commercial entities are going to push it forward.

Jean Drouin:

The thing that’s been holding it back, both on the government side interestingly and on the commercial side, is, if you think about it, a value-based arrangement requires a trusted baselining of here was clinical performance before, here’s clinical performance after, and the docs will always say, “Hey, my patients are different,” so it has to be case mix adjusted. You load in the contract and then a trusted party theoretically reconciles performance, pre-performance, post, here’s the bonuses, penalties, et cetera, that get paid out.

Jean Drouin:

Up until now it may sound odd, but even on the CMS side, it’s usually contractors on spreadsheets who are reconciling these value-based contractual arrangements, and that has dramatically slowed things down. There’s now a set of companies, innovators, Clarify included, that are saying, hey, we can automate all of this, both the baselining, the loading of the contracts and the reconciliations so that not only is it easier to figure out who should get paid what, but upfront, the docs naturally say, “Hey, okay, if you want me to sign up for this arrangement, can you at least show me, based on how I did last year, how I do?” And so far, with the spreadsheet method, it was, “Well, you’ll have to trust me.” And you know how well that goes down with clinicians when it comes to payment.

Jean Drouin:

So I am actually somewhat optimistic that we will see an uptick in the velocity at which these payments are adopted more broadly in the next five years. And it’s going to come from the commercial side. It doesn’t have to come from the government. What you’re going to see from the government I think is more around direct contracting, so the next generation ACO type models.

Charles Rhyee:

Right. And I think that’s a great segue. Maybe let’s dive into Clarify Health a little bit. Why don’t you talk to us about your current offering, how do you drive value for payers and providers, and now even pharma?

Jean Drouin:

So think of the broad problem that we see in healthcare as the following, which is the way to get to actionable business insight today, the model is typically, “Oh, hey, Clarify, you’re the new kid on the block. What data set do you have? I’ll overlap your data with mine, and the sliver that’s different, maybe I’ll buy that. And then I’ll put that in my data lake,” which is just a fancy term for a dirty data cesspool, “and then I’m going to, when I have a business question, get a bunch of analysts to go in there and SQL query their way around it for four to six weeks. And then come back with a one-off analysis that’s dripping wet in dirty data, still looks like a spreadsheet and might be dressed up in Tableau.” And that has been the primary model over the last decade for how to generate insight from big data. So it’s very manual and there’s actually quite a time lag.

Jean Drouin:

Meanwhile, if you look at an industry like banking, they have a Bloomberg Terminal, which if you think of it anthropologically, enables an analyst to practice at the top of his or her license and self-service on demand, get a set of insights on a daily basis, many of which are automated. And if you want to trend things, it’s there, et cetera.

Jean Drouin:

So think of Clarify essentially as having built the equivalent of a Bloomberg Terminal, and interestingly, our technology team came out of financial services. And we have put that capability on top of one of the cleanest, if not the cleanest of the massive healthcare data sets. So we now have a data set on over 300 million Americans which encompasses claims, lab, prescription, EMR, and social determinants data. And the social determinants, we do, like a bank or Amazon, at individual level. And what that allows us to do is to effectively productize and automate a set of business applications that answer the fundamental questions that either a provider, a payer or life science company has.

Jean Drouin:

So a payer, for example, three main levers to make money. One is pick the right docs, second is manage the medical risk, and third is understand the incoming risk of new members to match them to the right care. So not surprisingly, we have what we call Clarify Networks, Clarify Care, Clarify Utilization, and those all help the payers to much more precisely understand individual patient journeys to be able to do a better job of pulling those levers that ultimately allow them to be more successful.

Charles Rhyee:

And obviously at the surface, right, having access to the data on 300 million Americans, quite powerful, but to a certain extent, isn’t access to that data becoming more ubiquitous over time?

Jean Drouin:

Yes.

Charles Rhyee:

How do you differentiate then further in this field?

Jean Drouin:

Great question. So the way we think about that question is to think about a layer cake of a technology stack. And so the bottom layer of the cake is your data layer. The middle layer is the intelligence layer. The third layer is the workflow layer, and then on top of it, there are candles, which are the business applications that are offered to the market.

Jean Drouin:

On the data layer, one way to differentiate is how automated is the linking ingestion cleaning of the data itself so that the fuel you are then putting into the second intelligence layer, how refined a fuel is that? And we have invested quite a bit and have several patents around the automation of the linking and cleaning of healthcare data. So that’s one.

Jean Drouin:

The second is that intelligence layer is where we feel the real differentiator is going to be moving forward. So at a business level, it’s how quickly can you turn raw data into a specific insight? So for example, if a pharma company says, “I want to understand a cohort of congestive heart failure patients with these characteristics, including social characteristics and how they do on my drug,” you have to have the ability to, in seconds, go into the very complex coded healthcare data and return exactly that cohort. To do that, you need what’s called a grouper, which is almost like a ledger in the banking or the blockchain world, and you need the speed and power to interrogate a massive data set that quickly. Clarify is probably the only one that has the combination of the grouper and the speed to do it in real-time.

Jean Drouin:

And then the third thing to me is don’t fight the workflow in healthcare. If somebody wants the insight in an EMR, if they want a text, if they want to go into your own platform, let them have it the way they want. So those would be the three.

Charles Rhyee:

When you talk about the grouper, you had the example before about a lot of healthcare, they call it the data lake. And so they have all these sources of data put in there, and to your point, then they’re querying it. But my understanding has always been that data still needs to be tagged to be then retrieved.

Jean Drouin:

Yeah.

Charles Rhyee:

So wouldn’t that be the same for you as well? You talk about this group, but at the layer below that, doesn’t that data have to be tagged in a way to be found?

Jean Drouin:

Sure. So essentially there are different ways to tag data, but one of the… And this is one of the advantages in the US system relative to say the UK or Australia, is ICD-10 with its explosion of codes and the additional data that was included in the claims file actually gives you a pretty good start on a tagging mechanism. And interestingly, what I often say when I speak to clinicians is, hey, the myth that EMR data is the gold standard for everything we need to look at again because the claims data also comes out of the EMR.

Jean Drouin:

Now, look, there are certain use cases where you absolutely want some of the data that comes out of the EMR, but there are many where the tagging from the claims and linked to an individual gives you more than enough that in the grouper, what you’re doing is essentially sorting through claims codes as the tags. And then you can add additional tags on top of that, but it’s possible to build a very, very powerful longitudinal patient journey grouper with ICD-10 claims being the

[inaudible 00:21:41]

.

Charles Rhyee:

And that makes a lot of sense, but we also hear often, right, people talk about how important unstructured data is-

Jean Drouin:

Sure.

Charles Rhyee:

The physician notes,

[inaudible 00:21:54]

dictation. How do you incorporate that into the data set?

Jean Drouin:

Sure. So it’s a great question on where natural language processing will fit moving forward. The way I think about NLP and it being most useful is that NLP helps to translate unstructured information into a structure, and then ultimately, you’re adding some elements that weren’t in your original structured data. So a good example, we [inaudible 00:22:25] include something about a patient’s family context, and that wasn’t in your social determinants and you’re able to structure it and add it.

Jean Drouin:

But interestingly, there’s also the potential for NLP to introduce a lot of false negatives. And that’s been I think partly its downfall so far, which is if somebody has redness of the knee post-op from a knee replacement, 90 plus percent of the time, it’s fine. A few percent of the time, there’s something that needs to be done, but NLP alerts you all the time because it’s hard to get the context.

Jean Drouin:

So I would say that we are still in a world where there is so much low-hanging fruit from just using the structured data that it’s been okay not to have to use too much of the unstructured data, but we will come to a place where the structured data will be figured out and the next iteration will be layering in the unstructured, if that makes sense.

Charles Rhyee:

Yeah, it does. You touched on it a little bit before, but now having this access to this type of data, what kind of questions can we now answer that we couldn’t before?

Jean Drouin:

Sure. So a big part of it is kind of questions can we answer in a way that is of high enough quality and precision that it’s now trusted by clinicians and patients? I think that’s an important way to frame the question.

Jean Drouin:

So we had benchmarking in the past that was quite crude on is this a good primary care or not a great primary care physician? It’s now possible to be much, much more specific and to say, okay, adjusting for the difficulty of the patients that you see, we can comment on your quality, your [inaudible 00:24:18], et cetera. So there’s a precision and a trust to it that’s completely different.

Jean Drouin:

In life sciences, it’s now possible to have synthetic clinical trials, and actually, with real world evidence, have cohorts that are completely out of the phenotypic and/or EMR data. And that’s beginning to be accepted.

Jean Drouin:

And then the other piece, I think we talked about it a little bit, but we’re able to automate pretty much in real-time where patients who are under value-based arrangements are in their journey, and therefore [inaudible 00:25:01] what that means to the organization that is taking on that risk.

Charles Rhyee:

To your point, right, you mentioned earlier that this value-based care journey will be more driven by the commercial market. And you listen to a lot of payers speak about their commitment to value-based care. And often you listen to some of these companies and they turn out these great examples of, “Hey, in this market, we were able to lower readmissions by some large amount or unnecessary ER visits,” or demonstrate really pretty compelling outcomes, but at the same time, they tend to be in specific markets often where they have a lot of coverage and density or they own the provider groups. What is limiting then really to scale value-based care more nationally?

Jean Drouin:

One we’ve already talked about, which is just the ability of the payer to administrate the contracts and to also scenario plan what it would look like for a doctor or a practice they’re trying to sign up to go in. So that’s number one.

Jean Drouin:

Number two is the doctors themselves, the clinicians themselves have to have a sense that they have an ability to be the same or better off and having some ability to improve. So providing them with granular and specific enough information about either their own patient panel or their practice pattern is essential. And the granularity of the reporting that they’ve been getting in the past just wasn’t there, nor was the timeliness.

Jean Drouin:

And I’ll never forget this. I still remember where I was. It was five or six years ago near Stanford and I’m talking to one of the surgeons and describing the concept for Clarify. And he says, “Wow, if you can pull this off, it would be amazing, because the last report I got from the hospital, it was nine month old data and it went straight into the garbage.” So that is a huge piece of it as well.

Jean Drouin:

And then the other, the third is I think there just has to be a sense that a large enough proportion of health systems or practices or an individual’s payments are going to be in that kind of an arrangement that you now have to start paying attention.

Charles Rhyee:

Yeah. Maybe two questions from that. First, provider sentiment towards value-based care. You often hear that, to your point, right, it’s maybe because there’s a lack of trust or this current generation of physicians don’t want to change, but I think more and more physicians are employed by a health system, and so maybe that changes it. What flips the switch really for physicians to really more embrace value-based reimbursement?

Jean Drouin:

So we hear that COVID had some amount of impact in changing minds, because if you were in a value based arrangement at the beginning, then you still got your payment because you were more like a payer in that sense. We all know that payers generally did quite well during COVID.

Jean Drouin:

The second piece I think you’re absolutely right, which is the more you are employed, and larger practices and health systems tend to have the means to bring in the IT and information systems to be able to manage these programs, the more it starts to make sense, whereas the solo practice model really went hand-in-hand with fee for service.

Jean Drouin:

Look, I think the combination of more employed and also a much easier ability to see how successful one might be in the arrangements will make the difference. Now, clearly the contracts have to be structured so that enough of the clinicians are winners, because by definition, if you’re not increasing the… And interestingly, when we tried to bring in value-based payments in the UK, we talked a lot about should we slightly increase the total amount we had to pay to encourage people on the margin to go into these arrangements. And you can almost say that a similar thing happened with Medicare Advantage in the US and its popularity is partly because it’s been quite economically advantageous for plans and providers to go into it.

Jean Drouin:

So there is a question in my mind on the government and the commercial side, is if you really want people to adopt these ways of getting paid, then do you have to prime the pump in some way?

Charles Rhyee:

Yeah. And one of the other arguments that you sometimes hear from provider groups is how do you structure where maybe 30% of your contracts are in value-based care? So in effect, you want to keep that person out of the hospital, but the other 70% is fee for service, so you want to get people into your hospital. And you listen to some CFOs of hospitals say, “Well, I got to keep the lights on,” but I do want to shift to there. And it’s almost like they’re using it as an excuse a little bit, but then you hear another group saying, “Well, you know what, I’m not going to treat my patients any differently. I should have sort of the best way.” What’s sort of the response to that?

Jean Drouin:

I have a lot of empathy for those CFOs because it’s really hard to keep almost a hard wall in your own head and say, “Hey, I’m going to operate in two ways.” And it’s the same for the clinicians, because it’s almost like they need an alerting mechanism when the patient comes in and says, “Oh, well, it’s one way for this, one way for that.”

Jean Drouin:

And then from a purpose point of view, that’s just toxic. This is why some people say, and they may be right, that it’s going to be slow, slow, slow, and then all of a sudden, the switch will flick and you’ll go from one world to another. If that’s going to happen though, I would think the switch will have to flip completely on the government side, because otherwise, you’ll live in a bit of an in-between.

Jean Drouin:

Interestingly, if you look at the commercial market, there are quite a few examples of practices dabbling in it and then switching quite a bit, right? So maybe that has to be the way. Now that’s tougher for hospitals to do.

Charles Rhyee:

Yeah. Does then maybe like direct contracting, is this direct contracting program then quite important for CMS? Because that seems like that next step where you turn all of Medicare more or less into a type of Medicare Advantage type structure.

Jean Drouin:

Yeah, agreed. What would help a ton is if it’s made clear that there’s at least five years worth of the same rules. And really, there’s a massive difference in my view between three years and five years because it takes most practices and hospitals a year and a half to get through all of the planning for how you’re going to change things, and then you’ve only got a year and a half left, and then it’s really hard, to your point, for a CFO to say, “Well, why am I going to invest in this? Because I don’t even know what’s on the other side.” Whereas if it’s three and a half years on the other side and there’s been a little bit of priming the pump that starts getting way more attractive.

Charles Rhyee:

Yeah, but right now, this direct contract, it’s a three-year program, right?

Jean Drouin:

Sure. So that’s a suggestion.

Charles Rhyee:

Hopefully someone from CMS is listening. Well, okay, so maybe the close out a little bit, I mean, unfortunately, right, we’ve been exposed to COVID and the impact it’s obviously had on our economy and society. You just talked about a lot of the here and there. We obviously know the problems, or we can see a lot of the problems that are with our healthcare system, access to care, better outcomes from the care that we provide.

Charles Rhyee:

I know we’ve talked before, but you seem quite optimistic in some ways. So as you look out into the future, what do you think our healthcare system will look like in five to 10 years? How do you think how it can be? And it sounds like kind of a little bit more brighter view on things.

Jean Drouin:

Five years is very short, so I’ll take 10. And so I think in 10, the trends around employment of physicians into larger groups, continue to see that, consolidation, continue to see that on the provider side. Interestingly, I think you’re going to see much more of a willingness on the part of payers to invest in their provider partners to be able to better take care of populations. And you’ll see payers increasing the amount of providers they have in value-based arrangements, and those things go hand-in-hand.

Jean Drouin:

You’ll see a lot more transparency for patients on the quality and availability of the facilities and the providers that they have that they can go to. I think that’ll mean patients will affect a little bit more choice.

Jean Drouin:

I think one thing that doesn’t change though is there’s still something quite sacred about the provider-patient relationship, and those providers that nurture that will continue to do really well.

Jean Drouin:

I do think though that the successful payviders you’ll see making significant growth moves. So an example could be Intermountain looking to grow in the immediate states that it plays in.

Jean Drouin:

And then different parts of the country are going to move in different ways because healthcare structure in New York City is obviously very different than it is in other parts of the country, but even in New York City and in places like the Cleveland Clinic, they’re starting to think about their total cost of care and being able to go to their payers to argue higher facility rates based on the fact that they, on a total cost of care basis, do a better job of treating the members.

Jean Drouin:

So funnily enough, even in a fee for service rationale, people are starting to use a value argument to justify their fee. And I think you’ll see more of that because the analytics exists for that now.

Charles Rhyee:

What’s interesting in all of this though, we really haven’t touched on the consumer, the patient as a consumer, and there’s a lot often talk about consumerism and incenting the patient to make the right choice, but it really seems, in many ways, if you arm the provider with the right tools, because of that relationship with the patient, they’re able to get that person into the right setting. Is that maybe in a sense that as much as we talk about consumerism, that isn’t really the right way to necessarily tackle some of these issues?

Jean Drouin:

So my question is more around over what elements of the patient journey does the patient want to be a consumer and over what elements with the patient prefer a guide. So I think in terms of the experience that one receives, the patient or the family member helping out probably does want to be a consumer. And so when I call the hospital, is it a real person that answers? How quickly does it take? Is the parking free? Do they make me feel dignified, et cetera? I think those things, people want to be a consumer around.

Jean Drouin:

I’m not sure to what extent the patient wants to be a consumer around should I choose this or that doc? And so I think for me, that’s what’s going to be interesting, is where is the patient willing to be a consumer? And there’ve been lots of attempts over the last 10 or 15 years, to your point, to introduce incentives like $15 a month for a gym membership or lower copays or whatnot, and relative to what’s on offer, it just feels that either the needle hasn’t moved as much or it hasn’t scaled as much as people might’ve hoped.

Jean Drouin:

So I would find it really interesting for someone to do a psychographic study of where along the journey, as I say, does someone really want to be consumer and how. I think it’s a giant open question. Now, whoever cracks it, kudos to them because that’ll be a very, very big deal.

Charles Rhyee:

Well, I’d imagine giving access to Clarify’s 300 million patient database might be a good start.

Jean Drouin:

It might well be. You’re giving me an idea actually.

Charles Rhyee:

Well Jean, I think that’s all the time we have. Really appreciate you taking the time to be with us today, and good luck with everything. And thank you everyone for joining us for this episode.

Jean Drouin:

Charles, thank you. It was a real pleasure and really appreciate it.

Speaker 1:

Thanks for joining us. Stay tuned for the next episode of Cowen Insights.

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