Episode 38: How Velox Helps Payers Measure Data Usability

In this episode of The Informonster Podcast, Charlie Harp sits down with Michael Klotz, Founder and CEO of Velox, to explore how Velox is helping payers move toward smarter, more streamlined access to clinical data. They discuss how the Velox platform helps payers benchmark and improve data quality, and how shared standards and smart analytics are laying the groundwork for a more connected, responsive healthcare system. The episode also covers our partnership, which merges Velox’s data platform with tools like PIQXL Gateway to score the quality and remediate issues. Plus, hear the story behind Velox’s signature “green donut” dashboard—an eye-catching KPI that’s becoming a symbol for clean, real-time, FHIR-based clinical data.

Learn more about our partnership here.

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Transcript

Charlie Harp (00:02.15)

Hi, I'm Charlie Harp, and this is the Informonster podcast. Today on the Informonster podcast, I am joined by Michael Klotz of Velox. And we're going to talk a little bit about Michael and Velox and what Clinical Architecture and Velox are going to be doing together. Michael, welcome.

MK (Michael Klotz) (00:25.47)

Thank you, Charlie.

Charlie Harp (00:27.66)

So one of the things I thought we would start off with is, if you don't mind, sharing a little bit about your background and your journey, the journey that brought you to where you are today in health care.

MK (00:39.15)

Sure. Yeah. So I got it into healthcare almost by happenstance or by coincidence about 15, over 15, 2008, 2007, 2008. Over fifteen to two thousand eight two thousand seven two thousand and eight I grew up in Austria in the Alps, and I got educated as an electrical engineer. And then I went to USC in LA to get a business degree and sort of, you know, got stuck like many people do. Turns out the US sort of fit me really well. And I think it still does. And, you know after getting that degree, I started a pretty typical consulting career implementing ERP systems, specifically JD Edwards and Oracle. And then the dot-com era came around. And so I got involved into integrating front-end e-commerce systems and back-end business systems, which led me to middleware and Microsoft. So was a Microsoft partner. I had my first business, was a services business as a Microsoft Gold partner.

MK (01:39.58)

I sold that in 2008. And what happened along the way, I had a client ah starting in 2007, which happened to be in a medical records collection abstraction business. Which at the time was really weird to me and didn't make much sense. And there was a little disbelief on why would people do things that way and all that. But that was really my introduction to the world of healthcare IT, the world of payers, the world of HEDIS, the world of risk adjustment along the way. What came out of that was that client happened to go bankrupt and ended up owing my company a bunch of money. But I owned the IP we built for them. So there, I got to start my first business around that IP, which became Health Data Vision.

Charlie Harp (02:22.42)

Thank you.

MK (02:27.36)

So we raised the Series A and built what I think was at the time a pretty well advanced sort of workflow platform with as much automation as you could possibly have, trying to streamline and improve on that medical records collection, abstraction workflow, if you will, that we then had a bunch of payer clients. So that's how I got into healthcare.

Charlie Harp (02:55.05)

So the whole notion of trying to sift useful information out of the byproduct of data that we produce in healthcare is not a new thing for you. It sounds like it's...

MK (03:06.95)

Ah no, definitely not. And yet all along, you know I have been wondering, you know why are we doing things that way and how could we do it better?

Charlie Harp (03:17.34)

All right, and that brings us to Velox. How about Velox’s origin story?

MK (03:22.95)

Yeah, so it kind of goes right back, even though there's probably 10 years from where I just left off. What I always thought about was, you know, why are we not using structured data for this? And realized pretty quickly that we're not really any standards or any intentions or any sort of organized efforts around that. But, you know, all along I had this desire to do something differently. And I thought also in the long term, you know, I'd rather cannibalize my own business than, you know, have somebody else do it to me. Of course, I didn't fully realize just how slow things move in healthcare. But even so, I still am, you know, foolishly believing in how we think we can and should make things better. So within that timeframe, we saw CURES Act pass, which to me was sort of a milestone because it was a pretty big signal that you know other people were thinking about that and there might even be sort of a useful framework around that, both from ah from a regulatory perspective and the fire was emerging. And it was pretty obvious at that point, I think that FHIR would could be that standard that eventually bring brings the parties together and makes this much more palatable and much more real time and all the other things we're talking about every day today.

MK (04:47.17)

So with CURES and FHIR sort of, you know for us being foregone conclusions even before the rules really dropped in 2020, which I think was another big milestone because I think there were really meaningful rules and still are. We had this idea that, you know, it's not just about having a standard for the data, but also that FHIR obviously includes the whole concept of APIs. But we also thought about, well, how does the internet work, right? The internet basically works with this thing called DNS, and most people only know it when it doesn't work. But it dynamically and sort of seamlessly makes you get to the right source and grab data in a way that your browser understands. And so we thought, well, that's kind of the metaphor, the model we should really pursue to make clinical data flow directly and seamlessly and dynamically, not to ignore security and the other considerations, of course.

MK (05:48.97)

So we had this idea of where we wanted to end up and you know to you know sort of the foregone conclusion is we're not there yet. And we kind of know that we know we're not at dynamic yet. We're gonna be, you know, in two, three years out, but we built a prototype, and we started working on a patent towards that. But we also knew that that's not where we could start as a company, as you know, revenue producing viable, business entity, we would need to start somewhere where A) customer gets it and B) where we can add instant value. And so that's where we came up with what we were in market with today, which is called the payer enablement platform.

Charlie Harp (06:30.18)

And a lot of it and correct me if I'm miss misinterpreting or misstating this, a lot of it is the payers want to get access to good clinical data to supplement what they're doing. And the real question is, is the juice worth the squeeze? You know when you when you look at the data that's available, you know how much, and I'm probably totally oversimplifying it, but to me, a lot of it seems like what's available, how much work is it to get it? How easy is it going to be to on-board it?

MK (07:00.71)

Yeah.

Charlie Harp (07:03.29)

And then what we're talking about with the PIQXL Gateway and PIQI is, you know, how clean is the data? What's the quality of the data once you onboard it? Is that a fair statement?

MK (07:11.95)

Right. Yeah, absolutely. But I think there is another dimension to this. And we've, we've talked about this before, which we call the completeness sort of dimension, which is, you know, while I think Payers typically go, oh, you know, I get this data from this network, ah you know, participant, or I get data from an HIE and, you know, it, I get a good number of members data from that. Nobody knows if it really covers all what we call clinical events. So encounters and laps and things like that for a given member.

MK (07:47.96)

And if you have all if you have all your members covered, right? You get more is better these days, but nobody knows what a hundred percent is. So we got we got more, but we are we at 70? Are we at 75? Usually, we don't know. And so that's also what we're looking to solve for is like, you know, define completeness and then attempt to reach completeness. And certainly, within the context of which what's complete and useful for the given use cases we're trying to service, right?

Charlie Harp (08:16.89)

Okay. Now, for folks that aren't familiar with the payer market, is that is the reason the payers want the clinical data, is it is it purely value-based care? Is it about improving their ability to understand what's going on from the perspective of HEDIS? In a nutshell, what is the reason why payers care about the clinical data on their members?

MK (08:42.61)

Well, it's all of the above. So there's a number of use cases I think we're currently tracking more than 10. Some of them are most, you know, purely or not just purely, but in part compliance driven, right? You need to do your risk adjustment and you need to have your evidence. You have to report HIDIS rates and therefore you need to have the clinical data, at least for certain measures to substantiate that or to even come up with denominators and numerators for those measures.

MK (09:12.41)

But a big part of it is also, you know, how do you run a profitable, viable business and how do you service your members well within that, which, you know, and not that they're mutually exclusive, of course.

Charlie Harp (09:27.19)

So doing like care management, case management type things to help improve their wellness?

MK (09:30.91)

Yes, all the way to fraud, waste, abuse, ah you know, prior auth is now a hot topic, of course. And others, right? So care coordination, care management, population health, you know, depending on how you slice and dice it, basically, member outreach, provider outreach. So a lot of things sort of go in there. I think gap closure is a big one in the in the context of the quality use cases besides the reporting, right?

Charlie Harp (10:02.14)

Sure. So in the stark, bleak world before Velox, how do payers find the data now?

MK (10:12.09)

Well, effectively, I think, you know, everybody starts with their network, I would say, right? They know who their in-network providers or groups are, and, you know, they may have data feeds. So if you look at HEADIS, typically everybody talks about supplemental data feeds, and for the most part, those are custom files, custom flat files, right? So that's usually where you get sort of your maturity of data today, again, not to speak to completeness of that data. And then you add to that with other things. Some clinical information actually comes from claims, right? But medical records review collection is still a big thing. And obviously that's expensive and painful and doesn't always yield what you're looking to get. So oftentimes, you know you need to engage vendors you need to pay a lot per record. And then if there's a manual process or NLP or something involved to actually what I call reintroduce structure into unstructured data that used to be structured if we just go far back far enough to the source.

Charlie Harp (11:19.33)

Charlie Harp

Well, I think it's interesting because the other thing too is, and we've been working in the payer market for a while and I hear people talk about data acquisition, data acquisition. And the cool thing about what you guys are doing is, you know it's one thing to know where to go to get the data, but for anybody that's onboarding data, it's a slog. Even the best data is takes effort to onboard. And one of the things that I think is kind of is extremely cool, not kind of cool, but extremely cool about what you guys are doing is it's giving you insight, not in not just in the there's data here and, you know, here's how they deliver it, but it kind of gives you an idea of how easy it is as a consumer of data. How easy is it going to be to get the data? How much work is going to have to go into getting it? And the really cool thing about that is once you guys are ubiquitous, that's going to affect how people produce data because their goal is to make their data look as easy to consume as the next guy's data. And right now, all of that is cloaked in mystery, right?

MK (12:28.11)

Right.

Charlie Harp (12:28.43)

Right.

MK (12:28.60)

And it's going to be a lot easier if you all move towards a standard and move towards you know an infrastructure where you know we use the same standards and we are much more real time and where, like you say, we can actually benchmark the sources and say, hey, you are you you're still on USCDI 3 or not even that when you know other sources at 5. And again, you know there's a lot of potential there to not just do it through regulation, but through market forces, right? I mean, you know, I don't know how many people notice, but, you know, typical payers have agreements with their in-network providers that they have to provide clinical or medical records for free or for a, you know, very reasonable fee.

Charlie Harp (13:07.74)

Thank you.

MK (13:16.53)

And yet that is laborious. It's, very what they call abrasive, right? So, abrasion is big a big word still. And you know at the same time, we could leverage APIs they had to stand up already for you know ah patient access and you know improve on that tremendously. So it can be a total win-win and it can be incented through those, you know what we would call updated provider ah contracting and on and on and on. So in value-based now there's data should be shared both ways and we've seen some success stories you know around that as well. So I think it could be a total win-win, but yes, to your point, you know when we have standard ways of measuring and inventory and capturing what we are focused on, the metadata around these endpoints and the quality of the data coming from you, ah then you know it's almost like, I forget which Malcolm Gladwell book it was, but where he had this thought experiment where you know if enough people tattoo their IQ on their forehead, then everybody else will do it too.

Charlie Harp (14:22.01)

Social pressure. Absolutely.

MK (14:23.23)

Exactly, in that spirit. Right

Charlie Harp (14:27.08)

So when contrasted to the way it is now, if for somebody who's leveraging the Velox platform, how do you characterize the value or the speed to value of the approach you guys are taking it at identifying this? Because I also want to point out that you're not, and I could be wrong, you tell me, but you're not just saying, you know, here's a source and it's fire, but you're actually doing your own analytics on what's going on with that source. And you have an algorithm that scores the completeness and the usability of the data. And I'm probably characterizing it terribly, the value of that, I would imagine, is a real accelerant for people who want to take advantage of clinical data.

MK (15:19.75)

Absolutely. No, no. Yeah I think your characterization is good. You know we It's obviously a journey. We're at the pretty rudimentary stages of that, but that's exactly what we're doing. And what we're doing even before that is we inventory score and instead basically on a standardized scale benchmark existing data operation of the plan, right? So we can tell them within hours or within minutes of them uploading data metadata, which is not a whole lot of work, exactly how they score both internally and externally against best practices internally and against you know their peers and this concept of completeness externally. So you know we analyze the data channels they have, and then we farm from the ecosystem the opportunities they have to improve on that.

MK (16:18.72)

Right and yes, all that is on a standardized scale with a standardized framework. So it's meaningful scoring ah along all the dimensions that matter around clinical data and it's benchmarkable and it applies you know across existing and future ah data channels, which you know the future ones we call opportunity. So those are all possible data sources and ways of getting data that we know that they're currently not yet using. That are relevant to that plan, right?

Charlie Harp (16:49.70)

And I would imagine that be pretty valuable to get that kind of information. Do you think, I find this in the work that we do at Clinical Architecture, that sometimes I almost have to get through kind of a denial where people don't, it's an educational process for people to get to the point where they understand and see the value in what we're trying to do, whether it's data quality or semantic normalization or whatever. Do you kind of see the same thing? Do you feel like most payers get it? They're just waiting for your for a product like yours to be available? Or do you think there's going to be an education process where they're going to have to either see or experience it to really wrap their head around it?

MK (17:31.88)

There's definitely a process to that. So, you know, we think we're creating a new category and that's the burden you take on, right?

Charlie Harp (17:35.19)

Yeah.

MK (17:39.90)

It's as cool as it is, or as powerful as it is, it's not obvious on first sight, I will say, right? The things we do are typically not very sexy, but the results we produce should be and can be and will be, right? Right? But yeah, no, we're absolutely in evangelizing mode if you want to use a Microsoft term, right? And we know we'll be in that evangelizing mode for quite a while. But what we're doing over time, you know we're onboarding more and more payers and we have quite a few plans on the platform now. We're starting to farm some of those KPIs and really start pushing out some analytics where people, even if they're not yet on the platform, they go, oh, I can relate to that number. I can relate to that statistic. I kind of know where I would be, or I think I'm behind. I better get on this. So you know we believe that five years from now, you know vocabulary like channels and opportunities will be ubiquitous.

Charlie Harp (18:33.54)

Yeah.

MK (18:43.27)

That's clearly our goal.

Charlie Harp (18:43.96)

Yeah.

MK (18:44.83)

Right, but when I talk about channels and opportunities right now, people go like, what are you talking about? And that's the journey we're on.

Charlie Harp (18:51.15)

Well, you're creating a vocabulary. Yeah.

MK (18:54.53)

Right. But, you know, I have to say we we're making progress. We have many successes along the way. And I think the ah the indication is that we're doing something really useful and something that is actually catching up.

Charlie Harp (19:10.86)

Well, I think it's as somebody who's been evangelizing in my space for, I think in coming up on my 18th year here Clinical Architecture, it's gratifying that when people start to, when the light bulb goes on and it's almost like, okay, so I, I wasn't crazy. This is a real thing.

MK (19:29.60)

Right. Yeah.

Charlie Harp (19:30.71)

And, I think about, you know, you and I met kind of at the beginning of the PIQI journey, with the PIQXL Gateway, and I remember us sitting around, was it HIMSS in Orlando when we had that first conversation?

MK (19:46.07)

Yes. Yes. A very noisy, big lunch area, I think. Yeah.

Charlie Harp (19:51.16)

And it just kind of the stars kind of aligned, you know, what you were doing and what we're doing. I think that, Will likes to say it, so we can make fun of Will a little bit, but the idea of being better together, I think what you guys are doing is great, and obviously I believe strongly in what we're doing.

MK (20:05.31)

Thank you.

Charlie Harp (20:13.51) 

And I think that you know the combination of the two, I think it's good for what you guys are doing, but it's also good for us to see a practical application of the PIQI Framework in a way where it adds into a picture of insight around how we can leverage information to make use of it and also maybe create some of that social pressure because if you care about something, you measure it and then you can improve upon it.

Charlie Harp (20:40.21)

So, you know, I'm very excited about the potential for us to collaborate on this. And I think there's a lot of benefit because I think you know, one of the things I feel in getting to know you over the last year or so is that you're another one of those people who's very passionate. It's not just about, you know, doing business and revenue. It's about the bigger picture.

Charlie Harp (21:07.94)

We can do more than we've done. We can be better than we are. And I just think that it's great when you when you encounter somebody who's who resonates with you on that level. So I've really appreciated the time.

MK (21:19.44)

Yeah, no, same here. And, you know, I, you know, sometimes say there's probably easier ways to make money, but, you know, unfortunately, that's my bone and I'm the dog kind of thing. Right.

Charlie Harp (21:31.33)

Yeah, I'm with you. So before we wrap up, I want to I want to talk about the elephant in the room. I want to talk about the green donut. Now, as the as the inventor of the Informonster, which my marketing team gave me a lot of grief when I first came up with the Informonster. So what's the origin of the green donut? And I love the green donut mascot on your website.

MK (22:00.30)

Yeah, marketing totally ran with that. They sort of grabbed it from me and I'm glad they did. So, you know, if anybody's ever seen our sort of our main dashboard for payers, there's one KPI specifically, which is a donut. A donut infographic, which shows basically the mix of you know data channels and opportunities color-coded. So you know from all the way to red, which is custom, which is the worst, to you know various colors along the way, to green being FHIR in real-time version 4.X or higher, which is obviously the best. So you know we had this we had this conversation, I think internally, where it probably was Will saying, so in one sentence, tell me what I’m so what am I supposed to do with this platform, right? And I said, it's very simple. Your job is to make the donut green. And I didn't that that was just sort of like you know how I ah thought about it, right? That's clearly what's supposed to happen, right? You move towards you know all FHIR-based, standards-based, real-time structured clinical data. And so they they kind of went like, oh, green donut, great. Like, let's do something with that, right? And that's where the green donut was born. You know I'll say this and you know I may get some grief for that, but they I didn't like the sprinkles, but I kind of got used to them. Because of course, you know, I am an engineer by training. So to me, it should have looked a lot more like a three-dimensional infographic and not like a donut you can eat. But, you know, I love the guy. What can I say? Right. So there it is.

Charlie Harp (23:54.73)

Well, it's I think it's brilliant. And I think it's, it honestly, you know, the Informonster was all, you know, was my son kind of explaining to him, why do why do I exist? Because there's a lot of Informonsters out there that people create and it doesn't help them. It's chaos. So we're there to help them tame their Informonster. But I love the green, I wish I could steal the green donut for the PIQXL Gateway.

MK (24:17.17)

Well, you can borrow it, you know.

Charlie Harp (24:20.12)

Maybe I'll make an orange donut. 

MK (24:22.48)

Hey, really we can we can figure it out, I'm sure.

Charlie Harp (24:25.97)

Michael, is there anything else that you'd like to share with the with the audience about Velox and the journey or anything?

MK (24:34.03)

Yeah, well, more than anything, I just want to encourage everybody to, to I think, you know sharing our optimism, right? I think we we're not completely delusional when we believe in a clinical data ecosystem that can be standardized and real time and secure. And you know where we know where we're going to get, and we can we can very quickly move to actually working on use cases, whether it be care or you know running ah running a viable business, rather than fretting about silly things like, you know what why is this file not here? Or why did they change this file again? And but why are the code sets not like, or they way off? Stuff like that. We wouldn't be the first ones to figure out and we can figure it out. So I think it's all about let's stick our heads together. Let's focus on the things that work. And I think everybody, if they if they look hard enough, they will find why it's good for them too.

Charlie Harp (25:38.85)

Well, I resonate with that because sometimes when I talk about PIQI, people say, Charlie, no one cares about the data they send out. And what's the point? They're not going to want to show it. They're not going to want to see what their score is because they don't care. And, and you know, like you, I'm kind of an optimist and I say, well, maybe it's not that they don't care. Maybe they don't know.

MK (26:00.42)

Oh, there's that. And I think then, yeah, you have to you have to align the money with the desired outcome. And I think, again, in this ecosystem, there's a lot of room for that. I think it can be total win-win. And you know the mechanism for achieving that is obviously the stuff we are talking about, right?

Charlie Harp (26:19.39)

Yeah, and absolutely. Well, hey, thank you so much for taking the time today. I really appreciate it and excited about the what we'll be able to accomplish together. And for those of you listening, thank you for tuning in today. I hope you enjoyed it. I'm Charlie Harp, with Michael Klotz. Thank you so much again. And this has been the Informonster Podcast. Take care.