Trailblazing the Next Generation of Healthcare Analytics

Healthcare Rethink - Episode 74

What does the future of healthcare analytics look like, and how is PurpleLab shaping this landscape? This pivotal question sets the stage for a riveting discussion on the latest episode of Healthcare Rethink, where host Brian Urban is joined by Dr. Russell Robbins, Chief Medical Information Officer at PurpleLab. They delve into the transformative impact of analytics on healthcare, exploring new frontiers in data utilization.

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Brian Urban:

Yes, this is the Healthcare Rethink Podcast, I'm your host, Brian Urban. And today, we are trailblazing our way to the next generation of healthcare analytics with who other than PurpleLab. That's right, we have Dr. Russ Robbins joining our show here today, he's the chief medical information officer at PurpleLab, so we're excited to get into the conversation and get to know Russ a little bit more. Thank you for joining our show here today, Dr. Robbins.

Dr. Russell Rob:

Oh, thank you so much, Brian. I'm happy to be here and looking forward to sharing what we've been doing at PurpleLab. So, let's get started.

Brian Urban:

This is going to be so much fun. We haven't had too much time to get to know each other but already, in the short time that we were prepping here, I have a pretty good vibe on what you care about and why you're at PurpleLab but want to hear it from you. And before we touch on your work as a chief medical information officer at PurpleLab, let's go back a little bit, who is Russ. Before the MD, before the executive title, who are you and how did you find yourself into the healthcare ecosystem and now, really, on the really fun, cool side, the analytics side of it?

Dr. Russell Rob:

Yeah, no, that's a great question. So, I'm trained as a urologist, was in private practice for a number of years and then, when I left the group I was with, decided to go out and hang my own shingle, a lot of people at that time said to me, "It's running a business, you need some business courses." So, there was an MBA program where I was living at the time geared specifically to physicians, nurses and pharmacists who wanted to get an MBA but already had the clinical. So, it was an MBA program at Union College geared to clinicians and health sciences.

So, as part of that, I had to do a two-week internship in anything, in certain areas, got involved in healthcare data and healthcare informatics and thought, "Boy, this is a lot of fun, I had forgotten how much I enjoy doing that," and then one thing led to the next and I never looked back at opening up a practice again.

Brian Urban:

Wow, that's quite a 360, if you will. Getting deep on the business end geared toward medical professionals and then getting out of the private practice world which I can see being extremely stressful. You're balancing your own books, you're having to go through contract and negotiations with payers as well and then treating the patients, it's very difficult to imagine what it would even be like today as well, let alone back then.

Dr. Russell Rob:

Absolutely. No, you're absolutely right, Brian. And that was the other thing too is just the recognition. As I've been doing this now for as long as I have is you can't do what I do without the clinical training. It's not as if it's just, oh, I read a couple medical books and now I can do this, it's really having been in practice, having been in the operating room, having been working with health plans, working with employers, most importantly, working with patients and understanding all of those different aspects of healthcare that really has led me to where I am today.

And part of why I joined PurpleLab was specifically to put all of this together and just tie all of the loose ends that I've been observing for the last almost 30 years of healthcare and PurpleLab really is the place to put it all together.

Brian Urban:

I love the marriage you're speaking about. Actually treating individuals, knowing their needs from a clinical perspective and now you're seeing it from the overarching business perspective but from a data and then analytics as an output perspective which I think is so unique. And then, when we consider what PurpleLab does, it's really intriguing. So, let's get to know PurpleLab a little bit more. So, who is PurpleLab today?

Dr. Russell Rob:

Sure. So, at a very high level, we're healthcare claims data aggregators. So, we take medical claims and pharmacy claims, put them together in our analytics platform but then we've gone many steps beyond that. So, we also take social determinants of health information, through a relationship with Datavant, we tokenize all of the social determinants of health information, we tokenize all the medical claims and all of the pharmacy claims, put that together and then disaggregate any of the identifiable information.

So, what we're now left with at PurpleLab is we know, for any given healthcare provider, physician's assistant, nurse practitioner, social worker, you name it, we know what the demographics of that individual is and how he or she compares to their peers in the same specialty, in the geography in the state or nationally. We can do the same thing for hospital systems and the same thing for prescriptions. So, now, all of a sudden, you can use this data to understand disparities, inequities, you can make actionable uses out of the data because now you know things beyond just what the claims themselves are telling you,

Brian Urban:

I love where you're going and this is the world that we share and I think a love that we share as well is looking at non-clinical oriented data that's outside physician walls to really show what a person is struggling with that, if you address that, you're going to be able to address the health care realization, right size it, appropriate size it, et cetera. And you've been a part of a bunch of projects throughout your career, Russ. So, that's something I wanted to get into and you were alluding a little bit to some healthcare economics outcome research, real world data research as well.

So, what are some big emerging trends right now that PurpleLab is touching and what you're seeing from your purview as well? Is it organizations being hunger for ethnicity, race, for language data, SDOH? What's some of the big emerging trends you're starting to see unfold here?

Dr. Russell Rob:

Sure. Well, a few weeks ago, I was presenting at the SCOPE Conference with our colleagues at Parexel on how do you increase diversity in clinical trials. So, one of the things, if you look at the clinical trial data historically, it's about 85% of all participants are white and, within that group, most of them are men between the ages of 30 and 50. And so, from that, you now have to extrapolate to the rest of the population and you miss things. So, one of the questions is how do you meet the diversity requirements that the FDA has started to mandate to say we need more diversity in clinical trials. So, what our database is used for is specifically for that.

So, we know, let's say, if you are a pharmaceutical manufacturer and you are launching a new cardiology drug and you want to do a clinical trial in New York. So, what you can do is say we want to identify all of the cardiologists in the New York metro area who've had prior clinical trial experience who have 20% or more of their patient populations who are Black, Hispanic, low income. Well, before, with just the data, you can call a physician and go, "What percentage of your patients are Black?" because they would have no idea. You can't-

Brian Urban:

No clue. Right, right.

Dr. Russell Rob:

Right. You can't also say other things about the practice, the makeup of it. And so, what our data allows you to do is to say here's a list of physicians who meet all of that criteria, you can now start the outreach process, you can stratify and start the outreach process. And even if a physician says I'm not interested in participating in the clinical trial, you know that they have the right demographics of their patient population, that you can say, "Well, can we at least leave the materials in your office so, if some of your patients are interested, even if you're not participating, they know how to contact us and reach out to us?" So, that's really changing the way we look at how to use the data to change our behaviors.

Brian Urban:

I love that you mentioned that how is this data being used to change behaviors, clinical workflows, et cetera. Russ, what a great depiction that you laid out for us there and some good name-drops too in terms of organizations, Datavant and also Parexel, we've had some lovely folks from those organizations on the show here too. So, this is a real cool thing, I think we can start to envision of what another roundtable might look like with PurpleLab having a seat next to those two organizations.

But thinking about where you were going here, you serve a lot of clinical research organizations, you mentioned Parexel. You've had a lot of health economics outcome research projects in your background and what PurpleLab helps pharmaceutical manufacturers device, wow, it's so many different stakeholders that you serve now and a lot of data that you link. I think that's really what sets PurpleLab apart here. Unstructured data is great because you can look at it and cut it up yourself, a lot of manual effort there but how critical is it for your data to actually have links to it that actually can show populations that can be broken down and then you have a richer set of analytics that can come from that. But how important is that linking of data that PurpleLab helps supply to your stakeholders?

Dr. Russell Rob:

Yeah, it's critical because that's really what our customers, what our prospects are all coming to us looking for is how do we get further insights, further deeper into the layers than we are able to get today. So, it's maybe the social determinant of health information that we can then link to a medication, who's not getting the medication and why, who has a valid prescription and leaves it at the counter and never picks it up and why, what are the things that the pharmaceutical companies or the advertising companies need to do in order to lower some of those abandonment rates.

And so, it may be simple things of, oh, well, we know that this group isn't picking it up and, lo and behold, we don't have any information printed in the language that they understand so maybe that's all that's needed. Or maybe it's a benefit plan design that we know that, if you're in a lower income group, you're not picking up the drug, maybe we need to waive the copays. So, in health insurers, employers, the pharmaceutical companies, they're all using this information to make concrete changes in the way that they are going out there to get increased access to healthcare.

And then on a more different ways, our data is being used in a lot of different types of research as well as other news stories, just looking at potential barriers to care, who is or isn't getting a medication and what's going on. So, we've done a lot recently with the weight loss drugs and have been getting a lot of pickup there in terms of who does or doesn't have access to the drugs and what areas in the country we're seeing higher prescription rates than we would've expected. And we can look at written versus dispensed, we can look at age stratifications, gender stratifications, we can see trends of where things are going up or down and that really just helps set the stage of where do you need to go after this next.

Brian Urban:

I love the way that you put that together and I think even a step behind that is you really have a great network of partners helping put everything together. And when you were describing that, Russ, I was thinking about HealthNexus, this thing is your flagship analytic tool, it seems like, when you're looking at it at least from the outside. And the way that your site breaks it down in terms of how it puts data together and literally goes through a staged process of being able to pull out custom healthcare analytic reports for a user that's in the device, drug manufacturer space or research space is quite compelling.

So, I wanted to have this tool broken down a little bit more for us because it looks complex but I'm sure you could sum it up in a simpler way. But tell us about HealthNexus a little bit.

Dr. Russell Rob:

Sure. So, the HealthNexus analytic engine is really actually very simple to use. So, it's just a matter of ... And it was designed particularly to be easy to use. And that's part of, as an aside, PurpleLab, we're a play on the dog, which obviously is there when you look at our website, we got the big purple lab who's looking for that elusive purple squirrel but also the lab is the place where you can tinker with ideas, you can test different things so the HealthNexus platform is that place to do that.

So, what you do is you can set up in the different types of reports that you're looking to do what are the ... We've created what we call concept groups and we have several hundred thousand of them with diagnosis codes, procedure codes, drug codes and you can take any different combinations of those and then set your time parameters, your age and if you have specific geography parameters. Whatever it is you are looking for, you set that up in the HealthNexus platform, in about anywhere from five to 10 minutes, you get the report back. So, what you now are able to do is look at the results of that report and say, "Oh, now let me try tinkering with it and doing one or two extra, move this up a little bit, move that down a little bit," and then you rerun the report.

So, in the space of an hour, you might be able to generate 20 different reports for you to really do the detailed type of comparisons that you're looking for. And if you want to just say, "Hey, I don't really want to go through the platform, I want to take the underlying data, I want to run my own queries," we set that up for you as well. So, it's not that you are limited to the platform but what we find is, for the majority of our users, the access to the platform gets them what they need and then they don't need to go any further than that.

Brian Urban:

I really love that because I would not have assumed that you can really go off platform and just pull out different dataset and be able to actually play with that too. So, the lab, quite literally, of your brand is a learning lab, a very customizable, flexible environment. So, that is quite a unique feature, Russ, thank you for breaking that down for us a little bit more. And I know you have the free demo on the site so you can actually get a little toes in the water there before you go forward into the full blown out platform but really cool.

I want to shift directions for a second here into health economics outcome research. So, this is just such a blowing up space. We've had Dr. Chris Boone on our show here before, he's with Oracle, he's a professor at NYU and he's known as the data hippie which is a really fun term he started [inaudible 00:16:33] for himself. And what we've gained from him in our previous podcasting is, hey, this is a very dynamic space and I feel like health economic outcome research as a study and a discipline is ever evolving because there's so many different emerging datasets.

Can you help us understand, for our audience who might not be familiar with this, what is health economic outcome research, what are some projects affiliated with this work, maybe what PurpleLab's doing, maybe some emerging trends around it in terms of data consolidation or data application?

Dr. Russell Rob:

Sure. No, that's a great question, Brian, and it's obviously very broad and easy and hard to define simultaneously. So, if you look at it, depending on who you are, you might have different needs for health economic outcomes research. So, one of the things that we do with our claims when we get them into our system is we apply our own proprietary standardized pricing methodology. So, what that means now is where the claims are coming in from, sometimes we'll get ... Because of the relationship of how they're collected from the vendors, we may or may not be able to get all of the information about the physician or the hospital as well as the charged or the billed amounts because of the nature of the industry and what the regulations of what they're allowed to collect.

However, what we can do and what we have done is created our own standardized pricing so it doesn't matter from our perspective where the claim, who paid the claim because now we can apply standardized price. So, now you can start to do apples-to-apples comparisons of different physicians, different hospitals using the same codes and so, therefore, you can then understand where the differences are based on practice patterns because, if the widget is all set at the same price, if I'm buying 10 widgets and you're only using five widgets, I'm twice as expensive as you are and now it's no longer what your negotiated contract rate is that's driving some of those forces.

The other thing we've also done is we have built and applied risk adjustment scores to every physician based on his or her patient population. So, we can then start looking at utilization, we can start looking at other factors involved and say, your patients are sicker which is why they're costing more or you're utilizing more services and your patients are healthier which is why you're costing more. So, one of the things that I and my team have done here at PurpleLab is we've developed our own episode of care analytics engine that can start to look at this. I'm not the hippie of that but, really, I've been called the godfather of [inaudible 00:19:45].

Brian Urban:

Oh, I like it. I love that.

Dr. Russell Rob:

So, this is now the eighth episode of care engine that I have built in my career-

Brian Urban:

Wow, wow.

Dr. Russell Rob:

... and I'm very fortunate that the team who was building this one with me have built prior ones of different pieces in the past. So, now, we're all together for the first time which is really exciting.

Brian Urban:

Wow, that is really cool. So, you are a godfather historian of building these things, a godfather architect in a lot of ways, so that is ... I love that, we got to brand you with that, we got to get you your own URL and everything, Russ. But that's a really helpful definition for our audience who is quite broad, listens to our podcast, but I think also it lines up a very specific use as well and how you can be able to use, not only the codes as the base, but also the points of service as well. And episodic care estimations for cost can be wildly all over the place depending on where you are in the country but being able to have it, I think, from an analytic perspective, based off of the codes, I think that creates more of the flexibility, it seems like.

Dr. Russell Rob:

Yeah, no, and I must say I'm also very excited about the fact that we're a qualified entity with CMS. So, what that means is, because of the breadth of our data, because of the security that we have in place, we are one of ... When we were assigned, we were number 17, there are now 20 entities in the country that have access to 100% of the Medicare parts A, B and D data. So, with that application process, we also submitted our own proprietary methodology for evaluating physician performance and that was part of the application and that's been approved as the methodology. Our methodology was approved by CMS for reporting purposes. So, that also was a very nice thing for us to have that recognition as well.

Brian Urban:

Very nice to have that recognition and probably the affiliation as well with the partnership with CMS. As we move forward and advancing quality measures on data, we think about what NCQA has done with their HEDIS measures, the next big step is how is this woven into clinical workflows and how are physicians being paid off some of their interventions and outcomes so it's not just, of course, what we're straddling today and fee for service and some mix of pay for performance. I see you all as a huge influencer, not only being established and recognized by CMS, but I think PurpleLab's going to be big influencer in how CMS can direct the ship toward more value-based care and better outcomes, things like that.

Dr. Russell Rob:

Yeah, that would be nice if they do. Right now, they've just approved our methodology, we're not partners with them by any stretch of the imagination but at least having the recognition and the seal of approval is quite a cache. But to your other point, Brian, I think the other thing that we're seeing a lot of interest as well is looking at how do you use the information about the individual providers to understand better practice or better outcomes for the patients. So, one of the things that we've developed is what we call an innovation score. So, we're looking for, it could be around surgical procedures, it could be around ordering markers prior to administering chemotherapeutic agents.

So, you can look at specific targets and then see, for whatever you're measuring, is it a knee replacement, back surgery, a chemotherapy agent, what are some of the more standard types of things but also what are more innovative types of things. And you can then start to see which doctors are doing more innovative types of things and, as a patient, as a plan, as a pharmaceutical company, you can then start to figure out how you want to use that information to either increase your network or have better understanding of where you need to educate physicians on what are the protocols for before you administer potentially toxic drug if somebody doesn't have the marker. So, you can use all of this information to really change physician behaviors and improve outcomes for the patients.

And that's really the premise of what PurpleLab is all about is how do you make the data actionable. How do you just not take this information, say this is what we have but how do you use it? One of the things that Mark Brosso, our CEO, said to me during the hiring process for me was, "I'm tired of having everybody say this is how it's been for the last 20 years, the last 30 years, we can't change anything." Now that you make somebody aware of it, they can no longer say, "Oh, I didn't know that was happening," now they have to take responsibility and have to take the action. We don't necessarily tell them what they need to do, we can give them some ideas but it's really up to them and their organization to make the change but now they've seen it, now they can't continue to say it's not out there.

Brian Urban:

I love that you said that and this makes me immediately think about the use case for health plans, payers. And olden times, really maybe going back just the last decade here, I think there's been more control, emphasis put on providers trying to have a behavior change with network performance using benchmarks off total medical cost related to readmissions or infection rates and things like that. But when we're way upstream, having aid to alleviate this type of burden, whether it's a mental or stress burden on physicians, and actually guide them and help give them the information, not just from a, hey, we're paying you to do this, we expect you to perform this way, but, hey, we want to help you to improve how well you're providing care.

I feel like that's the richness of what your analytics offer to a payer to change a lot of the ongoing conflict that's been around forever. So, I would imagine there's a ton of desire from health plans, I don't think maybe you're diving into that segment maybe as much just yet, correct me if I'm wrong, but I feel like there's a huge use case for how you can help a lot of the traditional private payers out there that might not have acquired a healthcare system that are still, or even if they have, they're still working through developing better provider relations.

Dr. Russell Rob:

Yeah, no, we just signed our first health plan customer earlier this month and that's really because we recognize that's the next area for us to expand into. And the health plans we've spoken to have all been very interested in this, the consulting firms we speak to have all been interested in using our data and are currently using our data specifically for these type of activities of our data can sit on top of other datasets that they have and fill in some of those gaps. Because, unlike other organizations that take social determinants of health information and bring it to the three-digit zip level, we actually bring it to the individual doctor, the individual hospital.

So, now, all of a sudden it becomes much more actionable, it becomes something you can actually do something with rather than just saying, "Well, at the three-digit zip level, we can't do anything because it's too broad, it's not specific enough for creating a new type of program, a new intervention," our data can be used to do that. And that's what the plans are seeing is, in their enrollment files, they don't capture a lot of this type of information. So, they know that there are underserved segments in their enrollee population that they need to address but they don't really know where to go. They can create the program but which doctors do we really want to start with, which patients do we want to start to do more outreach, which employers do we want to do more outreach to.

So, we can help set some of those pieces in place so as they're, not only creating the programs, they can also then measure the success of that and tweak them as they need to go along as well.

Brian Urban:

That's really helpful, Russ, because I think the village that we need to have now has to be so well coordinated and connected. Professional service organizations, large or even small boutique consulting firms, not many experts there, a lot of generalists, they can put together a lot of things. Same with health plans, they don't have a lot of experts in this space that takes a lot of sophistication and specificity in the craft of different data strategies. So, being able to help them and start to actually change and improve some of the healthcare economic challenges that we've had in the US for many years is just so awesome to hear. I'm just so excited for what success you'll have in that segment going forward and no doubt you'll have it with you as the chief medical information officer, Russ.

So, I'm curious, I want to shift gears into academia for a little bit here before we start to wrap. What research projects could you maybe tease us with in the world of academia or maybe what you're aspiring to contribute towards some of the research space, unlocking your data for some really cool projects that are out there from a lot of different maybe public health departments and universities and colleges, virology, epidemiology, community health, all things under that sun. Any cool projects coming up or what [inaudible 00:30:13]?

Dr. Russell Rob:

Yeah, no, we have a couple really cool projects. So, one is, for the last two years, we've been working very closely with Boston University, with one of their graduate school programs where the students are using parts of our claims data to understand just healthcare data and how to use it and manipulate it and put together. But as part of that, I and several others from PurpleLab will mentor the students throughout that whole process and give them our experience of what you need to look for with data. So, we've really taken a very strong stand on training the next leaders in healthcare. So, it's not just here it is static and then just hope that somebody knows what it's doing.

The other thing that we've been and I'm really pleased about is we have a project that we've been working on with a very large cancer hospital and looking at our data. This is a project that actually started eight years ago at a barbecue at my house where the chair of the department said, "I've been thinking about this and I would love to see if my hypothesis is correct." And at the organization I was at the time, I pitched it and I was told not really interested, not really going to ... We don't really want to do that. When I got to PurpleLab, told my boss Mark Brosso this is what I think we should do, he was like, "Absolutely," and met with them last week at a conference.

And one of the things which is nice is we gave them the preliminary findings. And when you hear things like this is going to change the way cancer care is being done in the United States once we publish it, what more can you ask for?

Brian Urban:

Yeah, yeah. Well, first of all, I need an invite to the next barbecue you have even though we're still in wintertime, Russ. But if you have these types of great conversations, who wouldn't want to join that and also have a delicious dish. But this is exciting, I'm looking forward to hearing what comes of some of the work that's going to contribute toward cancer research and other projects you might be sharing on site in conferences with some academia as well.

But, Russ, I got to ask you, let's take a look into the future here. What's fueling the next generation of healthcare analytics? What else is happening in the space that you think PurpleLabs will contribute toward over the next three plus years?

Dr. Russell Rob:

Yeah. So, I think one of the things that we are just finishing the development of is what I think is going to be a groundbreaking type of tool for looking at precision medicine and that's really, I think, where the whole future of healthcare is coming is how do you make sure that the right individual is getting the drug that they will respond to. So, you may have a medical condition and, right now, you're just given the drug but you may not have the genetic markers that will metabolize a drug so you're just going to get the side effects without any of the benefits of the drug. So, it's really ... Or precision medicine in the terms of there are people who are being denied care because they're told, "Oh, you're not a good candidate," but they're not getting the test to say, yes, I am a good candidate.

So, what we've started to develop at PurpleLab is a way to look at medical diagnoses, what are the genetic markers that are used for that, what are the drugs that are used to treat those conditions and then what are the markers that are needed for those drugs before you administer those drugs to make sure that the person will be able to metabolize it. And then, more importantly, is how do you go from any step in that process forwards or backwards. So, if you know the drug, what are the markers, what are the diseases. If you have the disease, what are the markers, what are the drugs. And if you have the markers, what are the diseases, what are the drugs.

So, it's really to be able to go across the whole spectrum, that's what we're finishing the development process on, that's what several of our customers have already told us, as soon as it's ready, they want it. Because this is, to me, the next step of where we're going in healthcare.

Brian Urban:

It's a beautiful vision, it's utopic, I feel like you're going to make great contributions toward precision medicine, genomic studies. Even, I think, the precision aim here of now public health programs, a lot of things that are happening in social medicine, food is medicine which is, I think, a funny term because food directly impacts your health so of course it is. But so many beautiful things that are going to be happening for PurpleLab, I'm glad you're at their helm as a chief medical information officer. Dr. Russ Robbins, thank you so much for joining our show here today.

Dr. Russell Rob:

Oh, thank you, Brian, it was a real pleasure.

Brian Urban:

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