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Welcome to this Week in Health, it influence where we discuss the influence of technology on health with the people who are making it happen. My name is Bill Russell, recovering healthcare, CIO, and creator of this week in Health. it a set of podcasts and videos dedicated to developing the next generation of health IT leaders.
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If you're interested in either of those services, check 'em out on the website. Today we're starting another of our interviews from the Health Analytics Summit in Salt Lake City, put on by Health Catalyst If you're trying to apply data as a transformative part of your healthcare strategy, this is a fantastic event.
Had a wonderful conversation at the conference with Alias Duka, the GM of Life Sciences for Health Catalyst, and we just sat down and talked about what this new endeavor for Health Catalyst was about. They have collected, uh, so much data through their network of trusted providers and partners. We, we talked about improving outcomes for patients, providers, pharma, new therapeutics, and accelerating that whole path.
So great conversation. Hope you enjoy. So I'm with Alia Tuka, who's the GM of Life Sciences for Health Catalyst. Welcome. So this is a, you know, fairly new, uh, new role for you and a new, uh, endeavor for Health Catalyst. Can you give us some background on it? Absolutely. Yeah. So I joined Health Catalyst a year ago.
Uh, to build out a new business unit in the life sciences. Um, and by life sciences we mean med device companies, pharma, biotech, digital therapeutics, a pretty wide, uh, wide, uh, industry. Um, the, the thinking behind it was that, you know, over 10 years we've accumulated incredible expertise and relationships and a trusted network of providers and, uh, reach into, uh, hundreds of millions of patients, uh, and their
Um, and their data. And so on the premises of that, we thought we should try to pursue our mission further in this new industry. That's awesome. So the, uh, so what's the aims and the goals of life sciences in general for, uh, for Health Catalyst? Yeah, so I think because of our, uh, commitment in our mission to patient outcome improvement, clinical improvement, financial improvement for providers, uh, we have a pretty unique way of looking at the life sciences.
We know that there are many companies out there. That are basically data brokers. They accumulate data, they resell data, um, they license data. Um, when we approached the life sciences, we wanted to take a very different spin that was aligned with our mission. Um, and so while yes, there is a lot of data available from our, uh, provider base and across our patient.
Uh, um, population we really wanted to focus on inside generation, uh, that could improve outcomes. And so the way we think about it is we take un mathematical needs. We take areas where both patients and providers and pharma can benefit where they're developing new therapeutics and help them accelerate that path to success, to getting the right drug in the right patient.
Is there, uh. You know, one of the concerns is obviously selling data, and you've already sort of addressed that, but are there certain things you're going, you're not going to do based on your mission? Yeah, it's a great question. We actually, uh, thought hard about what we don't want to do and what we're not going to do.
Um, and so some of the things we're not going to do. Are any engagements that are branded and brand specific, any engagements that relate to advertising to pure, you know, commercial activities related to, to one or the other. Uh, drug. Uh, the other thing is that we're not gonna . Uh, resell data. So we're not gonna park, you know, the data of our providers and our patients, uh, at one or the other.
Um, you know, uh, industry clients, we will provide access to generate insights, but on projects that we approved that were, that we feel are mission aligned. So those are two big areas that, you know, we are very keen to avoid doing as we build this out. So Health Catalyst is a cloud-based solution. So essentially you're
Um, you're brokering access on behalf of the, um, of the providers, but really in with a focus around the patient. So you're anonymizing the data and giving people access. Yeah, and even the access to data is only in certain areas where research, uh, you know, research scientists from these industries would want to work with us.
Right. So the drivers of the project will be the providers. And our teams. Um, and sometimes of course there are great data science teams within those industries that want to work with us, and we'll be open to that on our cloud. Um, but really the ultimate goal is also to shift away from this data discussion of just having data and generating insights to what we've been good at for the past 10 years at Health Catalyst, which is actually to drive the action, the transformation, the change.
At the provider. So let's say, you know, uh, a life sciences company asks us to look at, you know, how a certain disease, um, you know, is handled currently at our providers to understand, you know, patient characteristics and, and other, uh, and other features. We would ask them, you know, why are you trying to do that?
And what do you actually want the ultimate outcome to be? And how can we help you pick the right providers amongst our network of providers to work with, to ultimately, ultimately go beyond the insight? To the actual change. So, for example, deploying new guidelines, you know, that are national guidelines that are, you know, that, that, uh, industry partners would want to deploy further and better across our providers or deploying a clinical study, uh, for a new drug.
Interesting. So, um, you know, there's, so Cosmos was all the talk a couple weeks ago. Um, and, and, and there's other players out here. IIBM bought company's name escapes me right now, but . Um, uh, a little while back, a startup, but they had accumulated all the data and they were, uh, in that same space. Um, what, you know, what differentiates your approach?
Is it the number of data elements? Is it, uh, the providers? I mean, what, so I would start from the fundamental sort of philosophy of Health Catalyst and track record of Health Catalyst. I think the first differentiator is that we have proven over and over again. Um, that we are focused entirely on outcome improvement and we have great expertise, track record.
Um, in that space. And so that's the, the first major difference. Um, the second difference is that while, you know, cosmos and other companies have focused, uh, and other initiatives have focused on EMRs, uh, the EMR is really about, you know, five to 10% of the data that you need to drive population health and personalized medicine and so on.
We, you know, published a white paper recently on that, and there's a lot of research showing that to drive these more sophisticated behaviors like population health. And personalized medicine, you need a lot more than the EMR. And so since Health Catalyst has been ingesting more than 300 data sources, and on average ingest, you know, 50 to a hundred data sources at our clients, we have much deeper, broader access to the patient, uh, to understanding the patient journey.
Uh, for example, you know, it's great to understand their clinical journey, but if you don't understand their cost. Or the patient flow or how operationally they're handled. It's very hard to really understand how you can change things on the ground. Um, so I would say on the one hand, the outcome improvement success and on and on the other, the depth of the data that we had, it was, yeah.
One of the questions I'm gonna have, or one of the conversations I'm gonna have a little later was I didn't realize how much, um, . Around financials and operations that Health Catalyst was, uh, participating in to, uh, really help the efficiency, overall efficiency of health systems. And I would imagine that data on a , I don't know how you, how you share that on a global basis and anonymize it, but it would be interesting to look at where the inefficiencies are across
The entire, uh, health ecosystem. Yeah. And I think that's why we're receiving a lot of interest because, you know, a lot of positioning a new product, you know, a new therapeutic. On the one hand, obviously you have the clinical trial, you show that it's effective and that it's, you know, improving certain symptoms or, you know, uh, or uh, or length of life.
But on the other hand, there is all the economics of it. How can I price it? What's the right price? How can I show that the outcomes are tied to, especially as we move more to risk-based contracts and so on. So, you know, also, for example, as we work with digital therapeutics companies, you know, we announced recently our partnership with um.
Med rhythms a digital therapeutic company that has a product for stroke. A lot of it was about, I mean, they already know the clinical side of things 'cause obviously they've been developing this therapeutic, right? But a lot of it is understanding the health economic out outcome model and understanding if I bring this therapeutic in, what am I replacing?
What cost elements am I replacing and what can I charge and, and how can I charge for it? So, uh, certainly having the, the combination of clinical . And financial and operational is, uh, is very, very important to truly drive, you know, new therapies to, to success. It's interesting with all those data points, one of the things that, you know, Dale Sanders shared yesterday was he had a, he had a fuzzy picture of a family, and then he had a clear picture of a family.
And that's what really what we're trying to get to. And I, I guess when you, you look at all those data points we're getting closer. Um, . But there's still so many other, I mean, genomics are, are, are you guys bringing genomics in to sort of, yeah. So it's, it's interesting you mentioned that We actually have our first live demo here, uh, at our summit today, uh, of our, uh, we call it molecular mar.
So all the genomics data. Uh, that we've, uh, put together for about 50 million patients so far, and growing every week, um, uh, which is absolutely crucial. Obviously, it's becoming, you know, it shifted from being a research interest to now driving daily decisions, you know, for personalized medicine products, for all the new innovative therapies that we require, uh, a molecular, uh, a molecular marker.
Um, so yeah, we're definitely gonna be bringing more and more genomics data and generally speaking, I think we've now created . You know, an accepted ecosystem where it becomes easy for third parties to come in and plug in their data. And for us to rapidly ingest other data types and build partnerships to extend the ecosystem.
I wonder, well, I'll probably ask somebody else about this, but, you know, are people coming to you saying, Hey, we wanna make sure our data gets into your platform, or are you still, is it still a go out and try to figure out That's, uh, it's actually, yeah, that's starting to happen. The reversal of the trend is starting to happen.
Um, so we've, we've had . Very interesting inbound requests. Uh, because, you know, especially when you look at anything that is sort of, uh, researched or molecular images, you know, the companies that have been leading the wave in genomics and in imaging, um, unless they can put it in the context of clinical operation and financial, it's, it's very hard to make it meaningful.
And so there's definitely been a shift. So you're, you're doing a lot of work overseas. You're going to conferences Singapore and other places. Um, you know what? Yeah. What's the challenges of that? Is it, I mean, 'cause you're, I mean, the data's handled very different differently in other countries and I mean, it's pretty complex, the endeavor you're heading off into.
Yeah, it's a, it's a great question. Yeah. So I think partly because of my background, I lived and worked in Asia, Europe, and, and, and North America. Um, and partly because of the mission, uh, that I have, I always think globally when, when I think of how we're building out our business. Also, our clients are completely global.
When you're talking to . At Top 10 Pharma, um, you literally don't know where they're taking the call from. And usually there's people on the call from different continents and different, uh, countries and regions. Um, so yes, as we started expanding our operations outside of the US and specifically, you know, where, uh, with our opening of an office in Singapore, uh, and with some of the work we do in the uk, um, there's definitely challenges.
They're not actually, you know, the technical ones I think are the ones that are easy for Health Catalyst because . You know, the joke is sort of, if we manage to handle all the diversity and heterogeneity and, and complexity of US healthcare systems, which are running on so many different types of, uh, systems, uh, what it definitely, what doesn't scare us is like a different character symbol or language that's, uh, that's not, you know, the, the biggest challenge, um, the biggest challenge, which I think we're, we're dealing with reasonably well.
Is that you really need to adapt your go-to market strategy. You need to understand what that country's trying to achieve. Um, you need to come in as a, as a true partner. You don't go in, which I think the health catalyst culture, again, helps a lot because we're very long-term focused, very outcome focused.
If you go in and sort of look at it as a sales account and try to call close some short term deals, that's definitely the wrong way to approach it, but. You know, when we look at Singapore, it's a country that has, you know, at its forefront, the, the wellbeing of, of their citizens in so many ways. Uh, and so when, when you work with countries like this and you say, Hey, we're here for the long term.
We want to accompany you on a healthcare transformation journey, and really try to understand how best to do it with all the players and stakeholders, um, then you start to have, you know, really interesting engagement. The other thing that is a bit different is because some of the countries are not fully digitized yet.
Uh, what you see is an interesting interplay with where, for example, life sciences companies are interested and willing to fund the digitization of entire countries, or at least the top health systems. So they, and you know, this is not new. It's been happening in the last years, uh, in various countries where different technology companies have been approached by life sciences companies.
Working with the governments and saying, look, you know, we, as long as, you know, we, we need access to data to understand your patient population. It's nothing to do with our current products. You know, it's not about, again, kind of advertising a product. It's about really understanding how patients are doing in your country.
Therefore, we'll come in and fund digitization. So there is a much tighter ecosystem interplay in these countries. Interesting. What, so participation, how does, how does a health system participate are, if there are Health Catalyst, . Client, do they naturally participate or, yeah. So that's, that's another, um, very interesting aspect we've made now touch.
So Touchstone is the environment where we de-identify and aggregate . Data across our clients, and it used to be sort of a separate product that, you know, had been launched and also had mostly a, a focus on benchmarking and on some visual apps. Uh, now we've just made it part of Doss, so it's not, Doss is our platform for managing data right at our clients.
And so now it's a normal part of Doss and our normal sort of engagement includes already . You know, the identification and aggregation, of course, you know, clients are free to opt out if they don't want to be in. Um, but the beauty is that sort of, it's all there and as long as they want to be engaged and as long as they're interested in hearing from us about opportunities that are emerging in life sciences, they're basically already in.
So compared to, you know, other companies that have been around in the last few years and made the headlines, we're another company that has to go and build something. We've built it in the past 10 years and now we can leverage both the. Uh, relationships and, uh, and the data. The, the other thing that I would say is so different is that, you know, other companies out there that have some kind of real world data package that they sell to pharma, you know, they build out a specific data model, they update it maybe on a quarterly basis.
Um, and that's it. You, you see what you see is what you get, right? And if you don't find a specific data point that you're interested in, there's no way to go back and add it. In our case, we have 90 feeds from all our clients. We have good relationships with all our clients. So if there is an interesting project, then we need to bring in an extra specials, TMR or some, you know, new patient reported outcome table.
We can just go and work with our providers and do it just a couple. You make it sound so easy. I'm sure when I talk to Dale he'll be like, a little harder than that, but, um, well, a lot of it is in our, in our, what we call source marts. That's the whole lining approach. Yeah. So, so it is almost that easy. So I have to say, honestly, in several projects that we've been doing recently, it is that easy.
Yeah. That's really interesting. Anything else you'd leave with, uh, providers that, that is important for 'em to know? Yeah, I, I guess, uh, you know, two things. Uh, the first one is that, you know, we often talk about how this can be also an opportunity for diversifying revenues for providers. And sometimes that's interpreted in an, in an odd way as if this was sort of profit making activities that are not aligned to mission.
Uh, but really we select priorities. And opportunities that are very deeply aligned to their mission as not-for-profit entities, as many of them are with our mission. Um, so, you know, the, when we say about revenue diversification, what we mean is paying extra clinical research coordinators or nurses or, you know, our staff to run interest in clinical studies that are hopefully aligned with their, you know, with their priorities and, and their interests.
Um, and the other thing is that as part of this adventure, we've started tackling things like molecular and genomics and other things, which we're now realizing regardless of the life sciences, uh, clients, the providers are becoming very interested in. And so there's an opportunity to integrate, I would say, more of the, uh, research offices, you know, the clinical trial offices, and really start creating an integrated care model that goes between research and operations.
So the last question. Is, uh, is really for my daughter who transcribes these things and she's always saying, what does that mean for the patient? Mm-Hmm, . So I'm curious, what does that mean for the, let, let's just stay in the US for now, just 'cause that's where we're sitting. Uh, what does that mean for the US patient, the work that you guys are doing?
Yeah. So, and this probably most important question. I think ultimately what it means is that by working across a wide provider network, integrating all of this data, having the depth of data to link, you know, outcomes, cost. Um, and clinical care that we can gradually shift to becoming a company that really serves the patients and make sure that the patients are getting the best value for the best outcome, uh, in the easiest and most accessible way.
Yeah, makes sense. Well, Alia, thank you. Thank you very much. Appreciate it. Thanks for listening. We have several other great interviews from has 19. Uh, please check them out on the website, iTunes or YouTube, and, uh, please come back every Friday for more great interviews with influencers. And don't forget, every Tuesday we take a look at the news that is impacting health.
It this show is a production of this week in Health It for more great content, you can check out our website at. This week, health.com or the YouTube channel this week, health.com. Just go to the top, click on the YouTube link and it'll take you there. Thanks for listening. That's all for now.