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Datavant is Building the Data Layer AI Needs in Healthcare · Vanguards of Healthcare by Bloomberg Intelligence

0:20
Speaker 1: Welcome to another episode of Bloomberg Intelligence's Vanguards of Healthcare podcast,
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Speaker 1: where we speak with the leaders at the forefront of
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Speaker 1: change in the healthcare industry. My name is Jonathan Palmer,
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Speaker 1: and I'm a healthcare analyst at Bloomberg Intelligence, the in-house
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Speaker 1: research arm of Bloomberg. My guest today is Kyle Armbruster,
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Speaker 1: the CEO of DataVant, a company focused on one of
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Speaker 1: healthcare's most persistent problems, getting data where it needs to go, securely,
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Speaker 1: and in a form that can actually be used. Kyle
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Speaker 1: has a unique vantage point on that challenge. He spent
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Speaker 1: a number of years at Athena Health before moving to Signify,
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Speaker 1: where he served as CEO, took the company public, and
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Speaker 1: ultimately sold it to CVS Health. After spending time inside
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Speaker 1: CVS working on healthcare delivery, he joined DataVant as CEO
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Speaker 1: in 2024. In this episode, we'll talk about what he
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Speaker 1: learned in each of those stops, why healthcare data remains
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Speaker 1: so fragmented, and how DataVant is trying to connect the
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Speaker 1: system and what AI can mean for the way that
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Speaker 1: information is accessed and used. Kyle, thanks for joining me.
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Speaker 2: Yeah, glad to be here. Thank you for having me.
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Speaker 1: So I've really been looking forward to hearing about your
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Speaker 1: career journey, but before we maybe rewind a little bit,
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Speaker 1: why don't we start with the present day and DataVant?
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Speaker 1: You know, where does the company sit in the healthcare
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Speaker 1: ecosystem and what problem are you guys trying to solve?
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Speaker 2: Yeah, DataVant sits in a really unique spot. And it's
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Speaker 2: a spot, frankly, that I've been chasing most of my
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Speaker 2: career to try to tackle, improve, and move the ball
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Speaker 2: forward across the entire healthcare industry. Data has existed in
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Speaker 2: silos forever. The systems are fragmented. They're not connected to
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Speaker 2: themselves or to other systems. And the ability and the
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Speaker 2: capability to move that data around is something that drives
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Speaker 2: better outcomes for patients, reduces costs. It kind of rises
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Speaker 2: all boats. And so DataVant uniquely sits in between supply
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Speaker 2: and demand of data. And we've built out tremendous scale
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Speaker 2: nationwide and moving international as well to take the demand
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Speaker 2: for healthcare data and the supply of healthcare data and
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Speaker 2: marry them together. And we've done that with extremely robust
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Speaker 2: integration capabilities, a ton of technology, a lot of AI
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Speaker 2: built into our core that we've had for quite some time.
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Speaker 2: But it's a large manual problem historically And what we've
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Speaker 2: been able to do is to automate and really make
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Speaker 2: it a lot more efficient and effective for both sides
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Speaker 2: of the equation, supply and demand.
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Speaker 1: That's a great synopsis. And I want to come back
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Speaker 1: to DataVant in a second. But, you know, you mentioned
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Speaker 1: that intersection of technology and healthcare, and that's really what
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Speaker 1: you've been doing your entire career. So what first kind
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Speaker 1: of pulled you into the industry to start with?
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Speaker 2: Yeah, it was early on in my career as a technologist,
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Speaker 2: my entire early life started and sold to pure technology companies.
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Speaker 2: I then pivoted into healthcare when my father and grandmother
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Speaker 2: passed away one summer and I was forced to get
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Speaker 2: into their med records, try to get them into hospice,
3:00
Speaker 2: digging into like legacy Meditech green screens. And I was
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Speaker 2: just shocked, frankly, at the state of where we're spending 25%
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Speaker 2: of GDP almost. And Charlie Baker was running for governor
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Speaker 2: in Massachusetts and I was spending time with him, helping
3:13
Speaker 2: him work on his campaign. And he said to me, hey,
3:16
Speaker 2: there's a guy I'd really like you to meet. His
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Speaker 2: name is Jonathan Bush and he's building what he believes
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Speaker 2: to be the healthcare internet. And I think you could
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Speaker 2: really use someone with your technology skills and your, you know,
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Speaker 2: kind of background. And so I met Jonathan and, you know,
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Speaker 2: I had wanted to pivot in after all that family
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Speaker 2: stuff that I just mentioned. And it was a great fit.
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Speaker 2: I was at business school at the time and Athena
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Speaker 2: was a mile down the road. And so I was
3:40
Speaker 2: able to easily go down there and work. And yeah,
3:43
Speaker 2: what an experience it was. It was amazing eight years.
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Speaker 2: And It was right when meaningful use was exploding. So
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Speaker 2: we were subsidizing medical records via the Affordable Care Act.
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Speaker 2: And so we were the bell of the ball in
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Speaker 2: many ways. And we were connecting and selling and scaling
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Speaker 2: in a way that I'd never experienced before in my career.
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Speaker 2: And so I caught the bug early on and I
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Speaker 2: decided then and there I want to dedicate the rest
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Speaker 2: of my life to moving technology and health care and
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Speaker 2: the human condition forward. And it's been a great journey
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Speaker 2: so far.
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Speaker 1: How did that experience with Athena's kind of like open
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Speaker 1: platform shape your view of how the data and technology
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Speaker 1: should go moving forward?
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Speaker 2: Yeah, it was a radical departure from enterprise software and
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Speaker 2: certainly from other incumbents in the space. And Jonathan brought
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Speaker 2: me in and had a radical mandate for me, which
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Speaker 2: was to put APIs all over the technology stack to
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Speaker 2: force the open platform. We called it more disruption, please,
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Speaker 2: even to be tongue in cheek about the whole thing.
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Speaker 2: We had conferences. We brought entrepreneurs in. And long story short,
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Speaker 2: and I still believe this, and I've replicated it at
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Speaker 2: Signify and DataVant, distribution is one of the hardest things
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Speaker 2: in healthcare. And especially as you get into the provider
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Speaker 2: space and or the payer space or pharma, contracting, selling,
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Speaker 2: account managing, it's really, really difficult. And so if you
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Speaker 2: can find a natural channel partner, like back in the day, Athena,
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Speaker 2: for all those startups, we really lowered that barrier for them.
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Speaker 2: And More Disruption Pleased, now called The Marketplace, is one
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Speaker 2: of the highest, margin, fastest growing parts of Athena still
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Speaker 2: to this day. And I think it was all built
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Speaker 2: on the premise that healthcare is so complicated, so multivariant
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Speaker 2: that you need others to help actually solve the problem.
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Speaker 2: You can't do everything yourself. And if you can build
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Speaker 2: that stable foundation, that platform to allow others to innovate
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Speaker 2: and build new technologies on, you can actually move the
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Speaker 2: ball much further. And Jonathan gets a lot of credit
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Speaker 2: for that vision. And I came in and helped shape
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Speaker 2: that with him and executed on it. But in doing so,
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Speaker 2: I got to meet every company in healthcare, right? Because
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Speaker 2: Athena was such a fast growing cloud-based platform. It was
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Speaker 2: such a disruptive technology in this space. I'd go out
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Speaker 2: to the J.P. Morgan conference or HIMSS or all these
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Speaker 2: different events, health, and everyone wanted to integrate with us.
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Speaker 2: And so we built out this amazing team and it
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Speaker 2: gave me a really amazing front row seat in an
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Speaker 2: education to a whole diverse array of different situations and
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Speaker 2: companies in healthcare that really accelerated my career, my ability
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Speaker 2: to make a positive impact for folks in this space.
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Speaker 1: That's awesome. I mean, we just had Bob on from
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Speaker 1: Athena recently, and that vision is alive and well, the
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Speaker 1: open platform at Athena. So maybe switching gears here and
6:21
Speaker 1: thinking about your next step, what brought you to Signify?
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Speaker 2: Yeah, it's a funny story. When I was at Athena,
6:27
Speaker 2: I was bidding on a company called Kinzer, and it's
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Speaker 2: a home health company based in Austin, Texas. Spent a
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Speaker 2: lot of time with the CEO, Chris Hester, still remember
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Speaker 2: his name. He's a great guy. And we had... you know,
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Speaker 2: gone to our board. We were public at the time,
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Speaker 2: Athena and bid as much as we thought we possibly could.
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Speaker 2: And I was, you know, we had just moved into
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Speaker 2: the hospital space. I then wanted to get in the home.
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Speaker 2: My whole thesis with Jonathan and the management team was let's,
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Speaker 2: let's cover the entire continuum of care. Okay. Right. Not
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Speaker 2: just the ambulatory, the clinic space where Athena was dominant,
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Speaker 2: but let's go inpatient all the way to the home
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Speaker 2: and all the way to the patients. We wanted to
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Speaker 2: build this whole, you know, capacity out, if you will. Uh,
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Speaker 2: TPG then showed up with a few days of diligence
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Speaker 2: and outbid us materially on it. And I stepped back
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Speaker 2: and I was like, well, I believe healthcare is going
7:13
Speaker 2: into the home. Jonathan was running Athena and I wanted
7:17
Speaker 2: to go run something again myself and met Matt Holt
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Speaker 2: over at New Mountain. He had been spending a lot
7:23
Speaker 2: of time with me, mentoring me. And anytime I was
7:26
Speaker 2: in New York, if he was in Boston, we would
7:27
Speaker 2: spend time together. And he's like, look, like we've got
7:29
Speaker 2: this big home thesis we want to play out and
7:31
Speaker 2: we've got number two and three in a space and
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Speaker 2: we can simultaneously close and merge them together. And let's
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Speaker 2: go build this big in-home company, which became Signify. And so, yeah,
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Speaker 2: like most things, it was it was born through loss
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Speaker 2: and missing out on something that I really wanted to
7:48
Speaker 2: bring into the Athena fold. But it turned out to
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Speaker 2: be an amazing, you know, chapter of my career, launching
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Speaker 2: Signify with Matt and the New Mountain team and that
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Speaker 2: amazing management team that I've pulled together.
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Speaker 1: I think we'll come back to Signify in a second,
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Speaker 1: but what happened to that legacy company? Where is it today?
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Speaker 2: Kinter's a part of Metaware now. Yeah, and it's still
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Speaker 2: out there. Chris did it the right way, too. He
8:06
Speaker 2: started like Athena started with the small practices and sold
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Speaker 2: and did the hard work of aggregating, like, real volume
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Speaker 2: in the market. And Athena started selling the small practices, too.
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Speaker 2: That was always its special thing. sauce is that they
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Speaker 2: could go out to the single one, two, three door,
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Speaker 2: five doc practices and then scale up to Ascension, their
8:25
Speaker 2: big clients from there. Kinzer had done the same thing
8:27
Speaker 2: and that was super impressive. And yeah, Chris just, he
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Speaker 2: built an amazing company and I always think what would
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Speaker 2: have happened had we'd actually landed that thing and where
8:34
Speaker 2: would Athena be today? But yeah, it's doing great. Still
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Speaker 2: a part of the TPG portfolio.
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Speaker 1: Amazing story. So going back to Signify, you know, you
8:42
Speaker 1: guys smashed together a couple of businesses. Talk about scaling
8:45
Speaker 1: and the challenges of putting those businesses together and really
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Speaker 1: going maybe to market as one company.
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Speaker 2: Yeah. One of the businesses had a great technology platform.
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Speaker 2: The other business had amazing network capacity for providers who
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Speaker 2: were going into the home and really big contracts. And
9:01
Speaker 2: so we brought it all together. And Signify was a
9:04
Speaker 2: big utilization game. And I tell a lot of folks
9:07
Speaker 2: like it was a. Logistics and routing problem, like the
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Speaker 2: traveling salesman problem, one of the oldest computer science problems.
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Speaker 2: It was health care also, but it was moving clinical
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Speaker 2: capacity into the home with dynamic supply and demand. And
9:19
Speaker 2: it was a wild, you know, gnarly problem that we
9:23
Speaker 2: were facing in every county of the United States. So
9:26
Speaker 2: the scale was just tremendous. And, you know, we were
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Speaker 2: I think they're doing close to five million visits, unique
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Speaker 2: visits almost this year. So it's grown in scale just
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Speaker 2: to this amazing size. To me, the business was represented
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Speaker 2: two things. One, risk adjustment had expanded and Medicare Advantage
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Speaker 2: had leaned in to use it.
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Speaker 1: Very heavily.
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Speaker 2: Yeah, very heavily. And it also opened up dual eligibles
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Speaker 2: and all these other populations that never got care and
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Speaker 2: no one ever went to visit. And there was no
9:54
Speaker 2: reason to do so because there was poor economic incentives
9:57
Speaker 2: to actually drive behavior change there. And so. you know,
10:00
Speaker 2: it was an amazing company. Like we would go into
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Speaker 2: these homes and the number one question we got asked is,
10:05
Speaker 2: when are you coming back? Like the amount of social
10:07
Speaker 2: isolation we would run into, the amount of seniors putting
10:09
Speaker 2: their hands in paper bags, trying to figure out their pills,
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Speaker 2: like the plans and signify we're going in to try
10:14
Speaker 2: to educate, coach and nurture these folks to get them
10:17
Speaker 2: into a better spot. Um, and keep in mind, like
10:20
Speaker 2: we were cold calling these seniors and offering this to them.
10:24
Speaker 2: They were accepting it because they were, there's a gap
10:27
Speaker 2: out there in market. Like they weren't getting all the
10:28
Speaker 2: care that they needed and they weren't getting all the
10:30
Speaker 2: information they needed and the coordination that they needed. And so, um, yeah,
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Speaker 2: I'm super proud of what that business, you know, was
10:36
Speaker 2: and how we scaled it up. The thing we did
10:38
Speaker 2: that was unique is we walked EBITDA back several quarters.
10:43
Speaker 2: So we walked, you know, the proxy for profitability, um,
10:46
Speaker 2: unencumbered cashflow back. because we wanted to invest heavily in tech.
10:50
Speaker 2: And so I sat down with Matt and the New
10:51
Speaker 2: Mountain team and said, look, we can automate so much
10:54
Speaker 2: of this call center, but I'm going to need to
10:55
Speaker 2: burn some cash in the short term. We can automate
10:58
Speaker 2: a lot of the logistics and routing, especially as we
11:00
Speaker 2: get more schedule density in, but we're going to need
11:01
Speaker 2: to burn some cash in the short term. And that's
11:03
Speaker 2: what makes a great private equity partner. I think somebody
11:06
Speaker 2: who is not looking to just cut costs or like,
11:09
Speaker 2: you know, drive efficiency at the expense of like building
11:12
Speaker 2: an enduring business. We dug in hard, and that's part
11:15
Speaker 2: of the reason why I think we had such a
11:17
Speaker 2: successful exit that was transformational for me, the team, our customers,
11:22
Speaker 2: for everybody that was involved from New Mountain, because we
11:25
Speaker 2: did it the right way. And one thing that I'm
11:27
Speaker 2: super proud of, and CVS Etna is still a big
11:29
Speaker 2: client of mine, now a data van, is Signify hit
11:33
Speaker 2: every single number we told them when we moved it
11:35
Speaker 2: over there. And I've seen a lot of guys in healthcare,
11:38
Speaker 2: and in general, and sell companies, and they kind of
11:41
Speaker 2: fall apart once they go into the host. I would
11:44
Speaker 2: be embarrassed by that. And I think it's a real
11:47
Speaker 2: testament to what the team built and all the energy
11:49
Speaker 2: we put into it. This amazing engine still inside CVS
11:53
Speaker 2: and it's still making an impact.
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Speaker 1: It's funny you say that, you know, putting my equity
11:56
Speaker 1: analyst hat on. It's funny that CVS are not funny,
12:00
Speaker 1: but to your point, they would still disclose the signify
12:03
Speaker 1: visits each quarter and they were very strong. And I
12:05
Speaker 1: think it's a testament to how strong the growth was
12:09
Speaker 1: and the trend and momentum that was there. Because typically,
12:11
Speaker 1: like you said, you know, once you go into this
12:13
Speaker 1: bigger organization, it's just, oh, that's part of the XYZ division.
12:17
Speaker 2: Yeah, that's exactly right. And I would say the team there,
12:21
Speaker 2: just fantastic. Prem, Katrina, all the folks that I worked
12:24
Speaker 2: with over there, David Joyner, they leaned in and made
12:28
Speaker 2: me feel like a part of the management team. You know,
12:30
Speaker 2: I was, when Karen was there and Sean Gerton, like
12:33
Speaker 2: we all were running together and they invested in Signify
12:36
Speaker 2: and they made sure to protect the asset and to
12:39
Speaker 2: give us the resources we need to grow We got
12:42
Speaker 2: aligned with Aetna and helped shape a great experience for
12:45
Speaker 2: the Aetna members. So they get a lot of credit
12:47
Speaker 2: to just the team there on the ground.
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Speaker 1: Was it a hard transition going from being the CEO
12:53
Speaker 1: of a public company to now being just one of
12:57
Speaker 1: the leaders at a much larger enterprise?
12:58
Speaker 2: Yeah, it was definitely interesting. It was fun. CDS internally.
13:04
Speaker 2: Was fast paced and like the breadth and the scale
13:07
Speaker 2: that they have as an organization is unprecedented. And so
13:10
Speaker 2: it was really cool to, to dream and imagine with
13:13
Speaker 2: that management team, how we could make very small tweaks
13:17
Speaker 2: and have a tremendous impact in individuals' lives. And so
13:20
Speaker 2: I really, really enjoyed that. Look, it was a, it
13:23
Speaker 2: is a big company, way bigger than, you know, anything
13:25
Speaker 2: I've worked at. And I certainly think I thrive in
13:28
Speaker 2: a place that is purely, you know, something that I
13:32
Speaker 2: can run with a management team and where I, you know,
13:34
Speaker 2: have alignment with the capital partner that I work with.
13:37
Speaker 2: And so that is the reason I wanted to pivot
13:39
Speaker 2: back out. I knew that I had landed Signify. It
13:42
Speaker 2: was in a great spot. I had good succession built
13:45
Speaker 2: out there and could elevate those individuals to have an
13:47
Speaker 2: opportunity to run and scale things. I knew that CVS
13:50
Speaker 2: was going to be in a good place and that
13:52
Speaker 2: Aetna was going to be in a good place because
13:54
Speaker 2: I knew whatever I did afterwards. And I was already
13:56
Speaker 2: thinking about DataVant, you know, with Matt around that time,
13:59
Speaker 2: like they were probably going to be a customer again.
14:01
Speaker 2: And it was really important for me reputationally, that we
14:04
Speaker 2: delivered something that was of great value to them and
14:05
Speaker 2: something they were proud of.
14:07
Speaker 1: So maybe let's just talk about that transition then back to,
14:11
Speaker 1: you know, a private equity-sponsored firm and DataVant. You know,
14:15
Speaker 1: what did you see as an opportunity? And then I
14:17
Speaker 1: guess maybe, can you wrap that with the history of
14:19
Speaker 1: the company? I mean, we think of the two pieces, right?
14:21
Speaker 1: The legacy DataVant business and then the SIOX piece that
14:25
Speaker 1: came together. What attracted you to the opportunity so much?
14:28
Speaker 2: Yeah, it's actually how I met Matt back in the day,
14:32
Speaker 2: he had come to Boston and wanted to talk to me.
14:36
Speaker 2: I was running product at Athena at the time about
14:38
Speaker 2: digitizing some of our medical records to get them to payers. And, um,
14:43
Speaker 2: you know, I, I naively said, well, like I can
14:45
Speaker 2: just do that here. We'll build it out here. And
14:47
Speaker 2: he kind of laughed. And so the big irony is that,
14:50
Speaker 2: you know, full circle had come back to like run
14:51
Speaker 2: the other thing, uh, data vent now on the other
14:54
Speaker 2: side of it. Um, yeah, it was, it was funny.
14:58
Speaker 2: Like we at Athena had, mastered moving information between the practices.
15:02
Speaker 2: And we could get referrals out, prior authorizations. We were digitizing, like,
15:06
Speaker 2: all the provider-centric transactions. Like, we're doing a really good
15:09
Speaker 2: job at it. We had a huge, you know, multi-hundred-person
15:12
Speaker 2: integration team globally that was just focused on bidirectional integration
15:16
Speaker 2: into lab systems or pharmacy systems, whatever it might be,
15:21
Speaker 2: other scheduling systems. But moving healthcare data at that time from,
15:27
Speaker 2: you know, the provider groups, into the payers, the life
15:29
Speaker 2: insurance companies, legal companies, pharmaceutical companies. It's very manual. And
15:34
Speaker 2: SIOX back then, and this was 15 years ago, was
15:38
Speaker 2: one of the largest users, if not the largest user,
15:40
Speaker 2: of the U.S. Postal Service. They had their own zip
15:42
Speaker 2: code because there's so much physical volume being sent around. Yeah,
15:47
Speaker 2: but that was healthcare, right? And there's still... Send a record. Yeah,
15:50
Speaker 2: send a record. And there's still physical records everywhere when
15:53
Speaker 2: you go into... These health systems, it's a problem that's
15:57
Speaker 2: going to die away as individuals pass away, frankly, because
16:02
Speaker 2: they can't digitize all of that information. Like it's warehouses
16:05
Speaker 2: full of legacy records. And so Cyox came and solved
16:11
Speaker 2: a lot of that problem. And it was brute force.
16:13
Speaker 2: And Matt had the vision of aggregating all of the
16:16
Speaker 2: supply side volume, if you will, all of the providers
16:19
Speaker 2: out in market. And they bought Aero, Healthport. There's a
16:22
Speaker 2: whole list of companies that came together. And then the CEO,
16:26
Speaker 2: there's several CEOs, but the CEO right before me, Pete McCabe,
16:30
Speaker 2: who's an amazing operator, came in and kind of standardized everything,
16:33
Speaker 2: calmed operations down, got everything flowing. They had really good metrics,
16:37
Speaker 2: performance metrics to show, you know, incrementing and decrementing of inventory,
16:42
Speaker 2: and clients were happy. What I came in to do, though,
16:45
Speaker 2: was to finish the job Pete started and digitize things
16:48
Speaker 2: with the real technology and product team and really push,
16:52
Speaker 2: you know, the boundaries and of what healthcare data could
16:55
Speaker 2: be used for. Because as you digitize it, you actually
16:58
Speaker 2: open up new use cases and manual slow interchange of
17:01
Speaker 2: data doesn't allow. And so our growth has been tremendous
17:06
Speaker 2: over the last two and a half years. But a
17:07
Speaker 2: lot of that is because of how much work the
17:09
Speaker 2: team is putting into digitizing. And the supply side, on
17:13
Speaker 2: the supply side, all the demand side has all these
17:15
Speaker 2: new use cases that are opening up as a result
17:17
Speaker 2: of all that new digital information flooding into them.
17:20
Speaker 1: So maybe just taking a step back, I mean, the
17:22
Speaker 1: problem you're trying to solve is the fragmentation problem. Can
17:25
Speaker 1: you talk a little bit about that and why we
17:27
Speaker 1: have such a fragmentation problem in healthcare? Yeah.
17:30
Speaker 2: I mean, one of our biggest, I don't know if
17:33
Speaker 2: I'd call it a mistake, but it was a mistake.
17:35
Speaker 2: When we rolled out the Affordable Care Act and pushed
17:38
Speaker 2: EMRs everywhere, we did not put interoperability standards in. That
17:42
Speaker 2: was our moment to mandate it. And think about the
17:45
Speaker 2: ATM networks. You have Star and Nice. You and I
17:48
Speaker 2: could go to London tomorrow and pull cash out of
17:50
Speaker 2: an ATM machine because they're all interconnected with a clean,
17:54
Speaker 2: seamless way to interchange information. Like healthcare should have that.
17:58
Speaker 2: And that's what I believe DataVant is becoming and has
18:00
Speaker 2: become because that gap between these systems and their ability
18:05
Speaker 2: to talk to one another was profound. And so instead
18:08
Speaker 2: of thinking about data fluidity and all of these things
18:11
Speaker 2: that are necessary now, we were just implementing things and
18:13
Speaker 2: building towers in the sky that were completely disconnected. If
18:17
Speaker 2: you add that into the multifaceted reality of how many
18:21
Speaker 2: different actors sit around this healthcare data and their systems
18:24
Speaker 2: and their economics and their governance structures. And then you
18:28
Speaker 2: layer on HIPAA, privacy, compliance. There's over 100,000 regulations that
18:34
Speaker 2: we deal with at DataVant, both nationally and at the
18:36
Speaker 2: state level, to get medical record data out of a
18:39
Speaker 2: hospital for whatever use case. And it's important to say,
18:42
Speaker 2: we do not have agency. DataVant doesn't wake up and
18:45
Speaker 2: decide to sell someone's data Every bit of our data
18:49
Speaker 2: has consent or authorization attached to it, either from a
18:51
Speaker 2: patient or somewhere that a patient's delegated those rights to
18:55
Speaker 2: as a part of their relationship with their health plan,
18:57
Speaker 2: et cetera.
18:58
Speaker 1: Maybe spend a little bit of time, you know, for
18:59
Speaker 1: the layperson who's listening to this, you know, what are
19:01
Speaker 1: the solutions that you provide to those different groups, whether
19:04
Speaker 1: it's payers, life sciences, providers?
19:06
Speaker 2: Yeah, absolutely. So we have four divisions, and I'll start
19:09
Speaker 2: with provider, which is kind of the core of our business.
19:13
Speaker 2: On the provider side, there is a department called release
19:16
Speaker 2: of information. And that release of information department is regulated
19:21
Speaker 2: and has to release this information based upon consent and
19:23
Speaker 2: authorization to patients, other providers, law firms, life insurance, pharmaceutical companies,
19:31
Speaker 2: and insurance companies, health insurance companies. It's really hard for
19:34
Speaker 2: providers to do this and staff it themselves. I just
19:36
Speaker 2: told you there's 100,000 different iterations to get it out.
19:40
Speaker 2: There's a tremendous amount of red tape and integration work
19:45
Speaker 2: that needs to be done. And so what DataVan has
19:47
Speaker 2: done is we've aggregated almost half of the volume in
19:49
Speaker 2: the United States and we've gone out and digitized the
19:52
Speaker 2: majority of it and standardized the ability for hospitals to
19:56
Speaker 2: fulfill that information in a quick, seamless fashion to all
20:00
Speaker 2: those recipients who want it on the other side. And
20:02
Speaker 2: so the core of our provider business is just running
20:04
Speaker 2: that function for the hospitals and then increasing the digitizing
20:08
Speaker 2: it so we can expand use cases and go out
20:10
Speaker 2: and create these other markets. Payers are second largest vertical
20:16
Speaker 2: with respect to like number of clients and just volume.
20:19
Speaker 2: And on the payer side, they're predominantly looking for medical
20:22
Speaker 2: records for risk adjustment, gaps in care, stars and heat
20:26
Speaker 2: as to quality programs. And so we help fulfill that
20:28
Speaker 2: for them. Payer is extremely digital. It's an area that
20:32
Speaker 2: we've been digitizing for over 10 years. And so their
20:34
Speaker 2: ability to get medical records um cleanly and seamlessly from
20:38
Speaker 2: the provider organizations is something that we facilitated and again
20:42
Speaker 2: there's hundreds of payers there's tens of thousands hundred thousand
20:46
Speaker 2: provider organizations they can't all connect with one another we
20:50
Speaker 2: solve that problem right we standardize it and have a
20:52
Speaker 2: set of tools that goes in and takes all that
20:54
Speaker 2: chaos and regulatory work away and do it in a
20:57
Speaker 2: clean efficient secure privacy focused way um for those clients
21:02
Speaker 2: and so Our payers trust us to get information from
21:06
Speaker 2: the hospitals that we run, but also anywhere in the U.S., frankly,
21:11
Speaker 2: where there could be medical data. We connect to other systems.
21:15
Speaker 2: We will physically send somebody somewhere if they need to
21:16
Speaker 2: go get a manual chart. We do whatever it takes
21:19
Speaker 2: to satisfy those payer customers. Then once the payer gets
21:23
Speaker 2: the chart, it needs to be coded appropriately. And so
21:25
Speaker 2: we do a lot of coding work to make sure
21:28
Speaker 2: the chart is– construct in a way where they can
21:31
Speaker 2: submit it for reimbursement or submit it for their quality program,
21:33
Speaker 2: whatever they might need as well. Then we have legal
21:38
Speaker 2: and life insurance, and they're looking for charts for mass
21:43
Speaker 2: tort cases, medical malpractice, child custody. They're looking for underwriting
21:49
Speaker 2: on the life insurance side to ensure that they have
21:52
Speaker 2: a full view of an individual for the issue of policy.
21:54
Speaker 2: So it's a battery of different use cases over there.
21:57
Speaker 2: We purchased a company called Antelis that has an amazing
22:01
Speaker 2: product called ChartSwap that helps digitally fulfill all of that.
22:04
Speaker 2: And so we've moved a lot of our manual volume
22:07
Speaker 2: for that demand side, the life insurance and the legal companies,
22:11
Speaker 2: and have digitized a lot of that throughout this year. However,
22:14
Speaker 2: and this is for all verticals, no one actually wants
22:16
Speaker 2: a medical record at the end of the day. The
22:18
Speaker 2: payers want it to be coded appropriately. Life insurance and
22:21
Speaker 2: legal need it integrated back into their underwriting system or
22:25
Speaker 2: into their paralegal case management system. And so we also
22:28
Speaker 2: bought an AI-centric company called Digital Owl that does all
22:31
Speaker 2: the abstraction work from the charts and puts it into
22:34
Speaker 2: a way that they can actually use it for their case,
22:37
Speaker 2: for their trial, or for their underwriting case as well.
22:39
Speaker 2: And so that's the third division. Then the final division
22:43
Speaker 2: is our life sciences division. And it's a little bit
22:47
Speaker 2: more complicated. So there's three things that we do really
22:49
Speaker 2: well in that division. One, we are the token of
22:52
Speaker 2: record for 20 of the top 20 pharma customers. And
22:55
Speaker 2: what does that mean? We've effectively built out the identity
22:58
Speaker 2: layer that connects 350 real-world data partners, including ourselves and
23:02
Speaker 2: all the data I just mentioned to you, in an
23:04
Speaker 2: ecosystem where pharma can use it for either identified, if
23:07
Speaker 2: they have consent and authorization, or de-identified to speed up
23:11
Speaker 2: clinical trials, to do epidemiology studies, to do safety work,
23:17
Speaker 2: and to do trial recruitment as well on the commercialization side.
23:21
Speaker 2: We then, second, have a privacy product because when you
23:24
Speaker 2: move into clinical trials, especially epidemiology or mortality studies, et cetera,
23:30
Speaker 2: they need an expert to certify frequently that it is
23:34
Speaker 2: absolutely certain that this data is private. And that's a
23:37
Speaker 2: big business for us that we've built out. We did
23:39
Speaker 2: some acquisitions of Mirador and other companies back in the day.
23:42
Speaker 2: But that's a great layer across that 350 real-world data
23:45
Speaker 2: partners on the ecosystem. We can stamp with a good
23:48
Speaker 2: housekeeping seal of approval, data van seal of approval, that
23:51
Speaker 2: is absolutely private when it comes through us. And then finally,
23:54
Speaker 2: the inside clinical trials in particular, when they have their
23:59
Speaker 2: cohort of patients, they want clinical information on them. And
24:02
Speaker 2: so we also deliver for patients and the pharmaceutical companies consented, identified,
24:10
Speaker 2: medical records so they can use them for the trial.
24:12
Speaker 2: And that's really hard, right, for patients to get them
24:14
Speaker 2: themselves or for pharma companies to get it.
24:16
Speaker 1: Is that from the investigators, the central lab?
24:18
Speaker 2: You got it, everything. Yep, everything and beyond, right, all
24:22
Speaker 2: the way through, you know, multi-phases and, again, mortality studies
24:26
Speaker 2: on the back side. We are running longitudinally that token
24:33
Speaker 2: and data discovery program. for the entire life cycle of
24:36
Speaker 2: a trial through drug delivery, adherence, and mortality. And so
24:41
Speaker 2: we have become the identity layer for life sciences. That
24:45
Speaker 2: identity layer is now moving into academic medical centers. We're
24:48
Speaker 2: also moving it into the payers. And so this notion
24:50
Speaker 2: of us being this single source of truth to connect
24:54
Speaker 2: healthcare data and wherever it's found is really the future
24:56
Speaker 2: of data and where we're pursuing now. So it's not
24:59
Speaker 2: just connecting supply and demand It's also bringing in other
25:03
Speaker 2: sources of supply and other sources of demand. And us
25:05
Speaker 2: being this clearinghouse, if you will, for all healthcare data
25:08
Speaker 2: that's secure, connected, private, and authorized across the country and
25:12
Speaker 2: now internationally.
25:13
Speaker 1: Well, that commonality is just fascinating. I mean, for somebody
25:16
Speaker 1: who's not a technologist like myself, what is the commonality
25:19
Speaker 1: across all those different buckets or customer bases?
25:22
Speaker 2: Yeah, it's wildly varied is the answer. And we do
25:27
Speaker 2: a lot of... coaching and education back to the source
25:31
Speaker 2: of the data, so the supply side, if you will,
25:33
Speaker 2: on adding new fields or changing the way that they
25:36
Speaker 2: capture something on intake, whatever it might be, to drive
25:39
Speaker 2: the match rate up with the broader ecosystem of data,
25:41
Speaker 2: which makes their data more valuable as well. But that's
25:44
Speaker 2: a big part of what we do. We have a
25:45
Speaker 2: huge internal consulting data management, data ninja team that goes
25:50
Speaker 2: in and helps you tune up your data so it
25:52
Speaker 2: can be more valuable and more connected into the broader ecosystem.
25:54
Speaker 1: Well, how does the network effect work for this over time?
25:57
Speaker 1: I mean, I imagine that as you get more people,
26:00
Speaker 1: the 350 that you mentioned, all the providers, that you
26:03
Speaker 1: become kind of like that single source of truth, right?
26:06
Speaker 2: Yeah, that's absolutely the goal. And I had dinner last
26:08
Speaker 2: night here in the city with the chief actuary from
26:11
Speaker 2: one of the major national plans. And he pushed on us.
26:15
Speaker 2: He's like, I want to overhaul my actuarial function. I
26:17
Speaker 2: can't get all the data I need to think about labs, genomics,
26:22
Speaker 2: all these other variables I could have on these individuals
26:24
Speaker 2: when I'm thinking about risk and how we're underwriting. And
26:27
Speaker 2: so it is bleeding into this source of truth across
26:30
Speaker 2: a whole bunch of different use cases for clients in
26:33
Speaker 2: all four of those verticals that I've mentioned. The thing
26:35
Speaker 2: that is uniform though, and I've mentioned this before, but
26:38
Speaker 2: I'll just make it a point again, they're not looking
26:40
Speaker 2: for us to throw data over the wall. They want
26:42
Speaker 2: us to build finished products. And in pharma today, we're
26:45
Speaker 2: building agents as a service where we bring in all
26:47
Speaker 2: of that data, all the identity layers, all the privacy,
26:50
Speaker 2: all the security tied into all of their internal systems.
26:53
Speaker 2: And then their scientists or their analysts or their, you know,
26:57
Speaker 2: marketing team, whatever it might be, can go and talk
26:59
Speaker 2: to one of our agents and just get information pulled
27:01
Speaker 2: back to them, right? They don't want to build and
27:04
Speaker 2: construct all themselves. It's a lot of the same agent
27:06
Speaker 2: chassis that folks need like to solve these problems. And
27:09
Speaker 2: so we're moving away from a world where it's, analytics
27:12
Speaker 2: and dashboards and instead like real time engagement with data.
27:16
Speaker 2: We've got all the supply of the data and we're
27:19
Speaker 2: now chasing and helping to shape how demand actually consumes it,
27:22
Speaker 2: which is the future of where we're spending a lot
27:24
Speaker 2: of our time.
27:25
Speaker 1: Maybe just going back to one of the things you mentioned,
27:27
Speaker 1: you know, probably a couple of minutes ago, but you
27:29
Speaker 1: mentioned that, you know, you were doing half the volume
27:31
Speaker 1: of providers. What's happening in the other half? Is that
27:34
Speaker 1: just still the fragmented old system or is there competition
27:37
Speaker 1: there who's also chasing the same thing?
27:39
Speaker 2: Yeah, I would say two things. So if you zoom
27:41
Speaker 2: way out, the provider market for data exchange is about 70% outsourced.
27:46
Speaker 2: So someone's doing something with it. The other 30%, and
27:48
Speaker 2: there are a lot of the big academic medical centers
27:52
Speaker 2: or the big multi-state health systems, a few of them,
27:56
Speaker 2: they want to sell their own data or have build
27:58
Speaker 2: their own data markets and they have enough volume or
28:00
Speaker 2: sway in a market or payer concentration or whatever it
28:03
Speaker 2: might be that they still do it themselves. So that's 30%.
28:06
Speaker 2: We're moving into that 30% because we're doing it more
28:08
Speaker 2: efficient and effective than ever before. And so that's been
28:11
Speaker 2: a big source of growth for us. But in the
28:13
Speaker 2: world we play in, that 70% that is outsourced, there's
28:17
Speaker 2: a whole bunch of mom and pop shops. There's a
28:18
Speaker 2: few other smaller incumbents. No one has all the demand
28:23
Speaker 2: side digital connectivity that we have. That is the differentiator
28:25
Speaker 2: for us. It's not just managing the supply and what
28:28
Speaker 2: was historically just staffing the function. It's building out all
28:32
Speaker 2: the digital rails and you need scale to pull that off, right?
28:36
Speaker 2: You've got to move the needle both on supply and
28:38
Speaker 2: demand to get them to agree to do the technology
28:41
Speaker 2: lift to actually make it happen. It is not a
28:43
Speaker 2: technology problem. It is an agency problem and a prioritization problem.
28:47
Speaker 2: And you have to have enough volume to make it happen.
28:49
Speaker 2: And that's where we've been able to really differentiate.
28:51
Speaker 1: Is there a use case that you could maybe give
28:52
Speaker 1: us around that from the demand side?
28:55
Speaker 2: Where scale matters?
28:56
Speaker 1: Where scale matters and an example. It could even be figurative.
28:59
Speaker 2: Yeah, no, I can give several. I mean, clinical trials
29:02
Speaker 2: is a great one, right? Like it's finding a needle
29:04
Speaker 2: in a haystack unless you have enough provider capacity where
29:06
Speaker 2: it actually makes sense to them to go survey everything. Otherwise,
29:09
Speaker 2: they're going to one provider at a time, manually pulling charts.
29:12
Speaker 2: And so because we've digitized so much for payers and
29:15
Speaker 2: life insurance, that digital fulfillment chassis we have internally, we're
29:19
Speaker 2: able to then point it into these other use cases
29:21
Speaker 2: very rapidly and solve problems that were not solvable before.
29:25
Speaker 1: Got it. It's funny, when I think of DataVant, I
29:27
Speaker 1: think of tokens. And tokens have taken on a completely
29:29
Speaker 1: different meaning these days in the age of AI. But
29:31
Speaker 1: I can recall, you know, talking to an analytics provider
29:34
Speaker 1: years ago, and they mentioned, oh, DataBand's doing all of
29:37
Speaker 1: our tokenization. Can you just talk about that technology and
29:40
Speaker 1: what that means?
29:41
Speaker 2: Yeah. Our tokenization is, as I mentioned, there's a big
29:44
Speaker 2: identity component to it, and there's a big just linking
29:47
Speaker 2: data component to it, which requires identity, obviously. And so
29:51
Speaker 2: you can think of us as the, you know, skeleton
29:54
Speaker 2: key for pulling all this healthcare data together in a secure, private,
29:58
Speaker 2: and compliant way, both identified or de-identified. And that's really
30:02
Speaker 2: the special sauce. And yes, now we talk about tokens
30:05
Speaker 2: in a million different ways, but for us, it's predominantly identity, security,
30:10
Speaker 2: and the ability to identify, de-identify, and then link all
30:13
Speaker 2: these data sets together. I'll give you a great example.
30:16
Speaker 2: CVS and Walgreens, big competitors. They do not want their
30:19
Speaker 2: data being commingled in a way that would give them
30:21
Speaker 2: a competitive disadvantage. With our token, they could mingle their
30:25
Speaker 2: data de-identified together, and sell both their data sets for
30:28
Speaker 2: more because it's more powerful and aggregate. And that's where
30:30
Speaker 2: we step in to allow the linkage and matching of everything,
30:34
Speaker 2: which makes an even more powerful data set for the
30:36
Speaker 2: demand side versus trying to aggregate all this stuff. That's
30:39
Speaker 2: exactly right.
30:40
Speaker 1: That's fascinating. Talk about maybe the role that you play
30:44
Speaker 1: from a neutrality perspective. You're a neutral player in all this.
30:48
Speaker 1: Do you think that ever changes?
30:50
Speaker 2: Yeah, I think neutrality is important. We sit in between
30:54
Speaker 2: organizations that negotiate with each other every day, right? Payers
30:56
Speaker 2: and providers negotiate all day long different contracts. For us,
31:01
Speaker 2: neutrality is defined as delivering a clean, secure product that
31:04
Speaker 2: has a source of truth, right? We do not have agency.
31:07
Speaker 2: We're not making decisions on contract negotiations between the two
31:11
Speaker 2: of them, but we're supplying all information that there's authorization
31:14
Speaker 2: and consent for in a clean, consistent digital way. And
31:17
Speaker 2: so For us, I think we never want to fall
31:20
Speaker 2: into the trap of starting to drive behavior change in
31:24
Speaker 2: a particular client where we're facilitating it. If they want
31:27
Speaker 2: to build products or things around the data that's interchanged
31:31
Speaker 2: with us, that's great. That's what a lot of them do.
31:33
Speaker 2: But we don't want to get into the space where
31:34
Speaker 2: we're actually driving agency. We want to be neutral. We
31:37
Speaker 2: want to be the clean connectivity layer beneath everything, building
31:41
Speaker 2: AI on top of it, again, to automate and make
31:43
Speaker 2: their lives easier at the end of the day.
31:45
Speaker 1: Maybe let's tease out that AI piece. I mean, if
31:48
Speaker 1: I think about where we're going, at some point it's
31:49
Speaker 1: machine talking to machine. Is that where we're going to
31:52
Speaker 1: get to in the next couple of years?
31:53
Speaker 2: Yeah, we're seeing some of that already. So I would
31:56
Speaker 2: say we are deploying AI in three ways today. One,
31:59
Speaker 2: a bunch of internal use cases where we're overhauling our
32:02
Speaker 2: ability to QA software or launch a user experience rapidly
32:08
Speaker 2: or update some legacy code very quickly. And we have
32:10
Speaker 2: a bunch of agents that are monitoring, talking to one another,
32:14
Speaker 2: giving updates to our engineers. And so our engineering efficiency
32:17
Speaker 2: is up about 40% across the board. And so I've
32:19
Speaker 2: been super proud of all the work that's been done there. Two,
32:23
Speaker 2: we are using AI internally to launch new products and
32:27
Speaker 2: to build AI agents for clients. As I mentioned before,
32:30
Speaker 2: on the life sciences side, we're doing some of that
32:32
Speaker 2: for payers where we move all the data in because
32:36
Speaker 2: only 7% of healthcare data is available to the frontier models. Right,
32:39
Speaker 2: it's all behind.
32:40
Speaker 1: Sorry, what percentage?
32:41
Speaker 2: Only about 7%. 7%. Yeah, so it's very low because
32:43
Speaker 2: a lot of it hides, hides, lowercase h, behind HIPAA, security, compliance,
32:49
Speaker 2: firewalls inside these internal systems. And so you can't just
32:53
Speaker 2: like turn it on with OpenAI or Clod or pick
32:55
Speaker 2: your poison. You need all of the layers of security, trust,
33:00
Speaker 2: and work that we put in and the layers of
33:03
Speaker 2: compliance we put in to actually facilitate that interchange. And
33:06
Speaker 2: so when we build agents... And we partner with a
33:08
Speaker 2: whole bunch and we're agnostic to who we work with
33:11
Speaker 2: on that front, who clients want us to work with.
33:13
Speaker 2: We're flooding it with highly relevant, fresh data that's up
33:17
Speaker 2: to date and moving the needle materially on real-time decision-making,
33:22
Speaker 2: not something that they get from a legacy claim set
33:24
Speaker 2: or something that it rears. And so that's been a
33:25
Speaker 2: big push for us. And so we've been saying to
33:28
Speaker 2: clients or talking about to clients as agents as a
33:30
Speaker 2: service or whatever you want to call it. But the
33:32
Speaker 2: most important thing is we're flooding it with connected private,
33:36
Speaker 2: secure data that they can use with their populations as
33:39
Speaker 2: consent and off always again with it to make rapid decisions.
33:43
Speaker 1: So it sounds like you're the foundational layer.
33:45
Speaker 2: That's right. Yep.
33:46
Speaker 1: Okay.
33:47
Speaker 2: Yeah, we've got the data connectivity built out in healthcare
33:50
Speaker 2: that's uniquely us. And we're facilitating and pushing forward with
33:55
Speaker 2: our clients hand in hand their ability to deploy AI
33:58
Speaker 2: at scale.
33:59
Speaker 1: When you see some of the marketplace, you know, you
34:01
Speaker 1: talked about providers doing it themselves or some of these
34:03
Speaker 1: systems who want to sit on their data and monetize it.
34:07
Speaker 1: I mean, what are they doing wrong? You know, where
34:09
Speaker 1: are they falling short primarily?
34:11
Speaker 2: Yeah, I think it goes back to, you know, I
34:13
Speaker 2: think back to my Athena days, like when we would
34:15
Speaker 2: roll in and we wanted to kick out the client server,
34:17
Speaker 2: you know, application, there was a CIO who she had,
34:22
Speaker 2: you know, hundreds of employees and her turf and all
34:26
Speaker 2: of these data centers and all of the spend and like,
34:28
Speaker 2: It's getting over that hump internally. And we are focused
34:34
Speaker 2: on removing administrative burden from providers. We do not charge
34:37
Speaker 2: providers fees. We don't go in. We're not in the
34:39
Speaker 2: business of that. We want to build businesses with them
34:41
Speaker 2: where we can remove a bunch of costs or help
34:44
Speaker 2: them build out programs where they can grow and scale
34:46
Speaker 2: data connectivity at large. And I think that's a big
34:50
Speaker 2: differentiator to get. Into digitization, though, it's two things. One,
34:55
Speaker 2: you need to be big enough to move the needle
34:57
Speaker 2: for them. So something that's going to actually take enough
34:58
Speaker 2: cost or allow them to build a business because they
35:01
Speaker 2: have enough volume that they can go out and create
35:03
Speaker 2: a business around selling the data potentially. And two, you
35:07
Speaker 2: need to have the demand side tied up. You can't
35:10
Speaker 2: just digitize them. That doesn't do anything. It's got to
35:12
Speaker 2: be digitized all the way to the finished product on
35:15
Speaker 2: the demand side. So it's useful for them as well.
35:17
Speaker 2: Then you create a willingness to pay. And so the
35:20
Speaker 2: only way to facilitate that is scale. You have to
35:23
Speaker 2: have enough volume to make the needle materially move on
35:25
Speaker 2: both sides. And so when we go into these folks
35:27
Speaker 2: who have these legacy departments or are doing various things,
35:33
Speaker 2: it's mid-rev cycle is where you would say we fall.
35:36
Speaker 2: It's interesting that clinical data exchange falls in rev cycle,
35:39
Speaker 2: but that's just where it sits. But it's anything from
35:42
Speaker 2: coding to CDIs or clinical document integrities where they're hoping
35:47
Speaker 2: to update charts to make sure that they're valid for
35:49
Speaker 2: everything that the doc found. to release of information, all
35:53
Speaker 2: the way down to denials, prior authorization. So all this
35:55
Speaker 2: stuff sits in this mid-rev cycle function. Our goal is
35:58
Speaker 2: to start to partner and expand our services to take
36:01
Speaker 2: more of that load off the providers because there's one
36:03
Speaker 2: key to all of it. It's clinical data. Everything I
36:06
Speaker 2: just mentioned needs clinical data to thrive and become more efficient.
36:09
Speaker 2: We are the best in the world at moving that around.
36:11
Speaker 2: And so our roadmap is to go push deeper. And
36:13
Speaker 2: as we push deeper into that space, digitize more and
36:17
Speaker 2: open up the aperture to have more digital data flow
36:19
Speaker 2: into the demand side as well.
36:21
Speaker 1: So how would you characterize where the, this is going
36:23
Speaker 1: to sound strange, where's the greatest demand on the demand side?
36:27
Speaker 1: What sort of use cases are there for our customers?
36:29
Speaker 2: Yeah, on the demand side, it's real-time clinical data, like
36:32
Speaker 2: no doubt. And they are often, as I mentioned before,
36:36
Speaker 2: looking for needles in a haystack. So the fact that
36:38
Speaker 2: we go all the way to a one-doc clinic, to
36:40
Speaker 2: a critical access hospital, all the way up to an
36:42
Speaker 2: academic medical center, they want breadth too, right? Because they
36:45
Speaker 2: don't always know where these members are or potential trial
36:48
Speaker 2: participants or how they're going to form their mass tort case.
36:52
Speaker 2: And is there enough individuals out there to actually underwrite it?
36:55
Speaker 2: And so breadth matters a ton and it's speed and
36:58
Speaker 2: speed is everything. Like if you're preparing for trial, like
37:02
Speaker 2: you can't wait around like months to get the clinical
37:05
Speaker 2: data that's core to the MedMal case, right? Like you
37:07
Speaker 2: need that quickly. You need to put into your system
37:10
Speaker 2: quickly and extract it from the chart to the things
37:12
Speaker 2: that you need. And so speed and breadth, but also
37:16
Speaker 2: the finished product concept, like it is what they're looking
37:18
Speaker 2: for more than ever.
37:20
Speaker 1: Got it. Maybe switching a little bit gears here to,
37:23
Speaker 1: you know, some capital decisions. You know, you've bought a
37:25
Speaker 1: couple of companies over the last couple of years. What
37:27
Speaker 1: goes into that buy versus build decision for you guys?
37:30
Speaker 1: I mean, you're not a small company anymore, I imagine,
37:32
Speaker 1: and you have a lot of capabilities on the technology side.
37:35
Speaker 1: You know, what makes some of these companies that you've
37:38
Speaker 1: bought so attractive that, you know, you decided not to
37:40
Speaker 1: just build it yourself?
37:41
Speaker 2: Yeah, absolutely. I look at our core differentiators as trust
37:44
Speaker 2: with our clients, the ability to manage data securely and compliantly,
37:47
Speaker 2: like I mentioned, and then distribution. right? And so the
37:51
Speaker 2: companies we brought in, Apixio, great example, we've moved it
37:54
Speaker 2: to 100% of our enterprise payer clients, blew all the
37:56
Speaker 2: synergies out because we had the distribution built on the
37:59
Speaker 2: retrieval side. Now we are coding more charts this year
38:02
Speaker 2: via Apixio than we're retrieving, right? So it's just a
38:04
Speaker 2: huge success on that front. If we look at ATN
38:07
Speaker 2: and Life Sciences, we had signed large enterprise contracts with
38:11
Speaker 2: the pharma companies, and we're pushing a ton of data
38:14
Speaker 2: into them, and they're like, time out. We need some
38:16
Speaker 2: tools and some agents and some AI to help extract
38:20
Speaker 2: this information, consolidate it, build cohorts, and do all the
38:23
Speaker 2: work I just mentioned to you. ATM was a great
38:25
Speaker 2: fit for us. And so to me, it's about speed
38:29
Speaker 2: and if they can leverage our distribution more than anything.
38:32
Speaker 2: On TELUS and building that new division out, we were
38:34
Speaker 2: sitting on hundreds of millions of dollars of legal and
38:38
Speaker 2: life insurance records that were being manually fulfilled. We bought
38:43
Speaker 2: the best digital fulfillment engine that's installed in 100% of
38:46
Speaker 2: all law firms in the country. and then built or
38:49
Speaker 2: bought extraction tools via DigitalOwl. It's a whole AI native
38:52
Speaker 2: company to be able to get that into the systems
38:54
Speaker 2: of record finished product that the demand side needed as well.
38:57
Speaker 2: And so if there's a easy thing that we can take,
39:00
Speaker 2: push through our distribution and scale and hit synergies on,
39:02
Speaker 2: that's great. We're launching dozens of new products internally as
39:06
Speaker 2: well though, across all verticals. And so we are doing
39:08
Speaker 2: a bunch of building ourselves, but if there's something we
39:12
Speaker 2: can go out and buy and integrate quickly, The team
39:14
Speaker 2: that's with me was largely at Signify and did all
39:17
Speaker 2: of the integration work. It's run by Annie Hurst, who's
39:20
Speaker 2: been with me for a long time. We just have
39:23
Speaker 2: a really good track record of aligning incentives, focusing on
39:26
Speaker 2: culture first, keeping the customer at the forefront, and letting
39:29
Speaker 2: the financials work themselves out with those things. And so
39:32
Speaker 2: we have a really good integration playbook that we've done
39:34
Speaker 2: for quite some time.
39:35
Speaker 1: Well, talking about new products, I mean, I know you
39:37
Speaker 1: probably won't disclose too much, but if we look at
39:40
Speaker 1: your technology roadmap or product roadmap for the next couple
39:42
Speaker 1: of years, what are you most excited about?
39:44
Speaker 2: Yeah, to me, it's something I alluded to earlier, moving
39:48
Speaker 2: the token forward. the linkage and the identity service into payers,
39:53
Speaker 2: more providers, and then into the legal and life insurance space.
39:57
Speaker 2: It is, it has been transformational for life sciences. Like
40:00
Speaker 2: we were predominantly sold just to the real world data
40:03
Speaker 2: companies for a long time, the token work. We now are,
40:05
Speaker 2: as I mentioned, are selling these full life cycle, longitudinal
40:09
Speaker 2: enterprise token contracts to life sciences. Like, and it's changed
40:12
Speaker 2: that industry. And it's been so excited to see Arnab,
40:15
Speaker 2: who reports to me, runs that division, what he's been
40:18
Speaker 2: able to come in and do. I want to bring
40:20
Speaker 2: that same scale and velocity to our other verticals. And
40:23
Speaker 2: so we have a big focus on that. Two, I
40:28
Speaker 2: mentioned on the provider side, we want to take our
40:30
Speaker 2: clinical data and solve more problems for them and remove
40:32
Speaker 2: administrative burden, help them cut costs, help them drive more
40:36
Speaker 2: reimbursement where they're due. And I think every one in
40:40
Speaker 2: our ecosystem does better if our providers do better. And
40:43
Speaker 2: I really believe that. And I think that... We've left
40:46
Speaker 2: our provider organizations in this country in a sad state
40:48
Speaker 2: of affairs, like reimbursements tough, med mal insurance is expensive.
40:54
Speaker 2: Their ability to get data and to have information at
40:56
Speaker 2: their fingertips is increasingly hard. And it's really hard to
41:00
Speaker 2: run a hospital. I don't believe you should be charging
41:03
Speaker 2: them money. I believe you should be saving the money
41:05
Speaker 2: and taking a piece or finding the money and taking
41:07
Speaker 2: a piece. And so we're very focused on that as
41:09
Speaker 2: a core of how we operate with them.
41:11
Speaker 1: Well, that's maybe a good segue. Can you talk about
41:12
Speaker 1: the revenue model across the different customer bases?
41:16
Speaker 2: Yeah. So on provider, again, we don't charge them fees.
41:18
Speaker 2: We run the division for them. And then inside payer
41:22
Speaker 2: and life insurance and legal, they pay per medical record
41:26
Speaker 2: or medical data element that they get out. And then
41:29
Speaker 2: if we do additional finished product work on it, like
41:31
Speaker 2: coding or mapping into their system, there's an additional fee
41:34
Speaker 2: for that. And then on the life sciences side when
41:38
Speaker 2: they get records it's the same thing to pay for
41:40
Speaker 2: the record or if we do any work and on
41:42
Speaker 2: the token it's utilization based and so it's um no
41:45
Speaker 2: more akin to visa or master card like we're agnostic
41:49
Speaker 2: we're neutral if you use more tokenization you pay for
41:52
Speaker 2: more of.
41:53
Speaker 1: It sure yeah so in in terms of like the
41:55
Speaker 1: business model you know where's the leverage in it uh
41:58
Speaker 1: our financial leverage you know what what drives profitability the
42:00
Speaker 1: most yeah it's scale.
42:02
Speaker 2: Right yeah we're able to drop unit economics on a
42:05
Speaker 2: per transaction basis because we have so much transactions that
42:08
Speaker 2: flow through us. And it's the ability to connect supply
42:10
Speaker 2: and demand like no one else can. So you remove
42:13
Speaker 2: all the manual work and you're able to digitize things.
42:16
Speaker 1: That's great. You know, if we think about where you
42:18
Speaker 1: want to be in, I don't know, an arbitrary three
42:20
Speaker 1: to five years, you know, when we do this again,
42:22
Speaker 1: you know, in 2031, you know, what will have changed
42:26
Speaker 1: for DataBand?
42:26
Speaker 2: Yeah, I want us to continue to expand, focus on
42:29
Speaker 2: client-centric products. There's a plethora of additional data, you know,
42:36
Speaker 2: needs inside the healthcare space. And I believe we are
42:38
Speaker 2: uniquely suited to do that. I want us to be
42:40
Speaker 2: at the forefront of creating a genuine, safe, secure, and
42:45
Speaker 2: compliant AI-centric world for healthcare too, that's powered through all
42:50
Speaker 2: the data that we've worked very hard as a country
42:52
Speaker 2: and as companies to digitize over the last several years.
42:57
Speaker 2: And for us, I want us to be a big
42:58
Speaker 2: diversified organization. Like I think that There's room in market
43:03
Speaker 2: to have a big diversified strategic that can acquire and
43:07
Speaker 2: build that has neutrality as its basis. And there's a
43:10
Speaker 2: lot of others that have tried to do that where
43:12
Speaker 2: neutrality is not in the cards. But I think there's
43:15
Speaker 2: a lot of room for that. My team's fired up
43:17
Speaker 2: about that. And we are getting big. We're looking at
43:20
Speaker 2: what going public could be like next year or beyond.
43:25
Speaker 2: And I want to continue to motivate and bring top
43:29
Speaker 2: talent in too. to all of this. And I think,
43:31
Speaker 2: you know, people come to healthcare because they want to
43:34
Speaker 2: make an impact. They stay because they feel the impact
43:36
Speaker 2: and see the growth. And so us getting capital and
43:40
Speaker 2: making sure that we can deploy new products, recruit the
43:42
Speaker 2: best talent, and go out and do some M &
43:45
Speaker 2: A as we continue to grow is super important and
43:47
Speaker 2: top of mind for me.
43:48
Speaker 1: What are the one or two, I guess, either competitive
43:51
Speaker 1: or policy or regulatory risks to maybe achieving that?
43:54
Speaker 2: Yeah, the number one thing, and I spend a lot
43:57
Speaker 2: of time in DC, my whole team does, We have
43:59
Speaker 2: information blocking regs that are live in D.C. and not
44:03
Speaker 2: being enforced. And we're starting to see some traction in
44:06
Speaker 2: the Senate and the House to push enforcement. But if
44:09
Speaker 2: anyone in the health care ecosystem in any space or
44:12
Speaker 2: any of the verticals I just mentioned is trying to
44:14
Speaker 2: block patients and or someone who has authorization to get information,
44:18
Speaker 2: we should stop that. Meaningful use was taxpayer dollars. We
44:22
Speaker 2: funded all medical records. Athena, Epic, Cerner, you pick your poison.
44:26
Speaker 2: That was all taxpayer dollars, number one. Number two, we
44:31
Speaker 2: have to keep the patient in mind, right? And there
44:32
Speaker 2: is no case in the world when the patient wants
44:35
Speaker 2: their data or someone authorized to have their data, should
44:38
Speaker 2: we be blocking it? Like that doesn't help anybody in
44:40
Speaker 2: any scenario ever. And so keeping that at the forefront
44:44
Speaker 2: is super important to me.
44:45
Speaker 1: You know, you've been doing this for a long time.
44:46
Speaker 1: You know, I think if you asked yourself, you know,
44:49
Speaker 1: what do you believe today that's wildly different than maybe
44:52
Speaker 1: when you walked through the doors of Athena? What has
44:54
Speaker 1: surprised you most about the change in the healthcare system,
44:57
Speaker 1: you know, throughout your career?
44:58
Speaker 2: Yeah, I would say two things. One, I do Rose
45:03
Speaker 2: and Thorn with my kids every night. I'm asking what
45:04
Speaker 2: their rose for the day was at Thorn. The day
45:06
Speaker 2: Rose would be, we have brought a ton of new technology, business,
45:13
Speaker 2: and critical thinking talent into healthcare in the last 20
45:17
Speaker 2: years that I've been in it that did not exist
45:20
Speaker 2: when I first came in. Like health tech, when I
45:22
Speaker 2: first started at the end, it was kind of sleepy.
45:23
Speaker 2: It was client servers and you went to HIMSS and
45:26
Speaker 2: Jonathan famously called it the boat show. Like everyone's just
45:29
Speaker 2: showing off their like big servers and stuff like that.
45:31
Speaker 2: It was like the antithesis of helping people to be
45:35
Speaker 2: efficient and effective. And so I do believe we've got
45:38
Speaker 2: a bunch of great folks and a bunch of great
45:39
Speaker 2: companies that are moving the needle on that. My thorn
45:43
Speaker 2: or the thing that we need to work more on,
45:46
Speaker 2: you know, we have not solved incentives and reimbursement and
45:50
Speaker 2: we have a whole bunch of legacy companies laws and
45:53
Speaker 2: red tape and not enforcing information blocking to actually drive
45:58
Speaker 2: behavior change. And the government, in my opinion, has gotten
46:01
Speaker 2: too fixated on regulation and failed things like TEFCA versus
46:06
Speaker 2: pushing actual incentives to allow private industry and the regulated
46:11
Speaker 2: parts of the business, like the insurance companies and the
46:13
Speaker 2: hospitals to actually have behavior change at their core. And
46:17
Speaker 2: I think until we do that, like we're not going
46:18
Speaker 2: to actually see healthcare become efficient, effective at scale. And
46:22
Speaker 2: I think they need to put way more demands on
46:24
Speaker 2: real-time clinical data across the entire ecosystem as well, not
46:26
Speaker 2: just to help DataVamp, but to help themselves.
46:29
Speaker 1: Well, in terms of that, you mentioned you'd like to
46:31
Speaker 1: get rid of the blocking. I think that's an obvious one.
46:33
Speaker 1: But what's the one incentive you'd like to see?
46:35
Speaker 2: Yeah, we need to start to pay for performance more
46:36
Speaker 2: across healthcare. If your car breaks and it doesn't work,
46:39
Speaker 2: you're not paying the mechanic. We need to go in
46:42
Speaker 2: and ensure, whether it's insurance companies, driving care management programs,
46:46
Speaker 2: doctors performing procedures, the handoffs of care, readmissions, all of
46:51
Speaker 2: this needs to be relooked at. from a genuine incentive standpoint.
46:55
Speaker 2: And I think a lot of the value-based care work
46:56
Speaker 2: we've done is trying to put a Band-Aid over a
46:59
Speaker 2: bullet hole versus actually getting to the root of it,
47:01
Speaker 2: which is how are we paying and motivating individuals, including patients,
47:06
Speaker 2: to actually take care of themselves in this country?
47:07
Speaker 1: And you can't do that without data.
47:09
Speaker 2: Can't do it without data.
47:10
Speaker 1: Kyle, I like to wrap these up on a personal note.
47:13
Speaker 1: And so I tend to ask the guests if there's
47:16
Speaker 1: something from their personal or professional life that they see
47:18
Speaker 1: as a catalyst for their own personal mission? Is there
47:21
Speaker 1: something that comes to mind?
47:22
Speaker 2: Yeah, I'm blessed to have five children, and I want
47:26
Speaker 2: to leave this. I have four boys and a little girl.
47:29
Speaker 2: A lot of roses and thorns. A lot of roses
47:31
Speaker 2: and thorns. We have big dinner conversations. But I think
47:35
Speaker 2: it is our generation's purpose and cause to leave healthcare
47:40
Speaker 2: better than we found it. And it is at a
47:44
Speaker 2: tipping point where if we don't, I believe we're going
47:46
Speaker 2: to go into a really dark place. We already, as
47:48
Speaker 2: you know and everyone knows, we're top of the spend
47:51
Speaker 2: and near the bottom of the outcomes. Like we've got
47:53
Speaker 2: to stop that and we've got to get incentives in place.
47:56
Speaker 2: We've got to get data flowing and we've got to
47:57
Speaker 2: modernize a lot of the legacy infrastructure that's out there.
48:01
Speaker 2: And I want my kids to have a seamless, easy,
48:04
Speaker 2: you know, path through health care, not something like that
48:06
Speaker 2: I had experience with my father and my grandmother and
48:08
Speaker 2: how they passed away. I want them to be able
48:10
Speaker 2: to and their friends and, you know, that generation to
48:13
Speaker 2: feel like we conquered health care in this country and
48:16
Speaker 2: we're the best at delivering it. We're the best at
48:17
Speaker 2: doing it efficiently and effectively. And that's what gets me
48:20
Speaker 2: up every day and motivates me. And what I would
48:23
Speaker 2: love to say, I made a small impact in at
48:24
Speaker 2: the end of my life.
48:25
Speaker 1: Well, I think you're doing a great job. And I
48:27
Speaker 1: thank you. And I'm sure kids will thank you as well.
48:30
Speaker 2: We'll see.
48:30
Speaker 1: Well, thank you so much for taking some time to
48:32
Speaker 1: share your story and your journey. I can't wait to
48:34
Speaker 1: see what you and the DataVant team do next. That's
48:37
Speaker 1: Kyle Armbruster, CEO of DataVant. Thank you for listening to
48:41
Speaker 1: this episode of the Vanguards of Healthcare podcast. And don't
48:44
Speaker 1: forget to click the follow button on your favorite podcast
48:47
Speaker 1: app or website so you never miss an interview with
48:49
Speaker 1: the leaders rewriting the playbook on healthcare innovation. Until next time,
48:53
Speaker 1: take care.
49:16
Speaker 2: Thank you. Thank you.