Helping companies understand data integration and the impact of physician network
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Understanding Physician Networks and Patterns of Influence with Greg Matthews, Founder and Principal at HealthQuant was automatically transcribed by Sonix with the latest audio-to-text algorithms. This transcript may contain errors. Sonix is the best way to convert your audio to text in 2020.
Welcome to the Outcomes Rocket podcast, where we inspire collaborative thinking, improved outcomes and business success with today’s most successful and inspiring health care leaders and influencers. And now your host, Saul Marquez.
Saul Marquez:
Welcome back to the Outcomes Rocket, Saul Marquez here and I have the privilege of hosting Greg Matthews. He’s an award-winning health innovation executive specializing in business development and alliance building, M&A integration, data and analytics, product development and commercialization, among other things we’re interested in as health leaders. He’s a multiple innovation award winner, including 2018’s Innovation Awards for Medical Marketing and Media Magazine and PM360 magazine and his work has been featured in numerous publications such as Forbes and Health Affairs. He is the founder of Austin-based HealthQuant. Matt is an expert in the integration and commercialization of health care data assets, market making for new products and services, and then leading a digital transformation across the health care industry, including pharma, medtech hospitals, and health systems, insurance companies and more. We’re going to be diving into a lot of things that he does. He’s also the host of Data Point. It’s a podcast about health care data analytics and innovation. He’s an advisor to the Mayo Clinic and South by Southwest. Among other things that he does. We’re gonna be diving into those today. So really, really a privilege to have you on the podcast today, Greg.
Greg Matthews:
Thank you so much. Saul, I would add, I’ve been a fan of the show for a long time, so it is an honor to be here.
Saul Marquez:
Yeah, it’s a privilege to have you on and curious what got you into health care to begin with.
Greg Matthews:
I actually actively avoided it for most of my life. My my dad was a practicing physician for 40 years and my mom was a nurse and then later a PhD counselling psychologist who practiced with him. So growing up, my primary goal was to stay away from health care. However, I wound up working in a human resources role for Accenture, which back in the day was Andersen Consulting. And in that role, I became aware of benefits and health plan management. And when I decided it was time to leave the consulting world, I actually went to work for Humana without really I worked in a human resources capacity. I wasn’t really thinking about the health care part of the business. And I was actually shocked to find that I had a real passion for it, that there were I was surrounded by 30,000 people who really, really believe that they were doing good and helpful things for people. And that was something that I knew I was going to want to be a part of for a long time.
Saul Marquez:
That’s funny, man. You know, it’s a great story. And I could just imagine you being there in disbelief. Oh, my God. I’m in health care and I love it.
Greg Matthews:
Well, In a health insurance company no less than the last place I expected to fall in love with health. But yeah, it turns out that the folks had been health insurance or at least the folks at Humana cared deeply about health and helping people to experience it better. So it was a pretty amazing experience.
Saul Marquez:
That’s cool. Yeah. Now we’ve we’ve had a couple leaders from Humana on the podcast. They’re doing some very cool stuff over there. Couldn’t agree with you more. So as the listeners wonder what needs to be front and center today in their agenda. Tell me what you think is going on here and what they should be thinking about in regards to it.
Greg Matthews:
So my major theme is really around integration and convergence. And I see that happening in health care in a lot of ways. But I think the way going to make. Yeah. So it looks a lot of different ways Saul. I think in one sense we see the subsectors of the industry beginning to converge. We’re seeing blurred lines between payer and provider. We’re seeing blurred lines between pharma and digital health. So I think that there were these very strict silos that had been built up over decades that I think the walls are beginning to come down. But for me, my real passion in the place where I think we’re gonna see real see change in the in the coming years is the integration of data. Healthcare generates so much data. Vast amounts of data. But it is so specialized and so segmented that we’re often not seeing full value for it. And so for the last several years, I’ve been really focused on getting my hands dirty, integrating different types of health care data to try and find patterns, to try and see around corners a little bit. And I think a lot of the reason we’ve seen separation in terms of data and a lack of integration and data is, number one, I’m not even going to go too deeply into sort of what organizations feel about letting their data go outside the walls. Right. there’s this kind of proprietary sense of ownership of data. If you’re a health insurance company or a hospital or whatever. I’m not even gonna touch that for a second. I’m thinking even inside the walls. We’ve seen a very distinct difference. There’s a very hard wall between all clinical data and patient data and any kind of external customer data or physician data. And so that’s legit, right? There are good reasons why we don’t want to have a free for all in terms of mixing clinical records with marketing data, but I think that we’ve gone. I think the pendulum swung so far that we’re now actually doing patients and clinicians a disservice by having our data so segmented. And so one of the things that I’m really focused on is helping companies to better integrate the data that should be integrated. I think we see the same thing in life sciences between research and clinical data, medical education data vs. marketing data. Again, some good reasons for that. And there should always be some segmentation. But I think that we’ve made, I think that we’ve set the bar too low just by saying no to data integration across the board.
Saul Marquez:
And when you talk about integration, are you saying integrating this data into programs, into platforms to offer insights? Is that is that what you’re referring to?
Greg Matthews:
So I think there are a number of different ways that that could look. Number one, when we think about life sciences, I know a lot of your audience works in the life sciences community in one way or another. We see one of the sets of data that I would like to see greater integration on is really around the real world, data that is collected by pharma and medical device companies. Real world data I think is going to become more important than it’s ever been. The med tech and pharma industries have been so focused on randomized controlled studies and clinical trials that I think we’ve made that put it on an artificial pedestal to some degree. Again, there is no substitute for RCT’s in terms of really vetting a product. But real-world data can provide so much value both to patients and to clinicians. But I think we in the life sciences industry have not done a great job in helping patients and clinicians to really understand how to use that as they’re making decisions in their lives. And so I would love to see a lot more real-world data integrated into the kinds of communications and programming that we do, both for clinicians and for patients.
Saul Marquez:
Gotcha. Gotcha. So around communications.
Greg Matthews:
Yeah.
Saul Marquez:
You want to integrate this into communications.
Greg Matthews:
And education, all kinds of programming where the patients and caregivers and physicians are making decisions every day that impact people’s health. And I think that there’s information that could be provided for them within the wealth of data that’s collected by the manufacturers that could be really useful. But not only do we need to make that data available, we need to make it available in a form that it can be used. But I also think that we need to make some investment and really, from a meta perspective, helping clinicians and patients to understand how to use that as they’re making decisions. How do I rank this real-world data versus that clinical trial result?
Saul Marquez:
Gotcha. Now, that’s interesting. And so give us an example, Greg, of how you’ve been able to either help a client or integrate some of this data and a clinical decision, support or communications.
Greg Matthews:
Sure. So one of the things that I had an opportunity to do is working with a large pharmaceutical manufacturer. And there was a really good I’m going to try and articulate this without revealing any any details that would get us too specific here because of verb our client confidentiality. But there’s a company that was joining a what was becoming a crowded market in their therapeutic area and had really, really strong real world data to contribute to that discussion, to contribute to the way that physicians were making decisions around how they were handling certain patients. And so one of the things that I and my team were able to do, we were able to look at we’re able to help them identify physicians who number one had shown a proclivity to adopting innovative technologies. And so one of the ways that we did that was by looking at several years, I think it was around six years of Medicare data for a particular therapeutic area where the standard of care had shifted during that six years. And so we looked at for all the doctors that were prescribing, which of them switched fastest to the new standard of care and which of them switched most completely to the new standard of care. And that gave us a proxy, you know, it helped us to figure out sort of who are the top 10 to 20 percent of physicians who are going to be watching for advances are and are going to be ready to make the switch. And then the second thing we did was to look at how do we help to position the Real-World data that we had with those physicians in such a way that it would be meaningful. And so in addition to doing the kind of things that are normally done, writing papers and making presentations at conferences, we also partnered with a leading media organization who did a large global survey in this topic area and then hosted a series of meetings between physicians and the experts and their panel to disseminate the results of this survey and talk about the real world data that was included in it to help them make decisions around how they were gonna handle their patients in the future with this new standard of care. So I know that it’s I hope it’s not too hard to grasp that given that I’m not telling you names. But those are some of the kind of things that I think are going to be necessary in order to really make this shift in terms of being able to integrate data for broader use.
Saul Marquez:
So I guess just to make sure I understand you work with the data able to segment a group of physicians that would be, I guess, the best ones to target for this therapeutic area. And then with that subset, you’re able to further dive deeper in to how to help them prescribe and take care of the patients?
Greg Matthews:
Yeah, exactly. And actually it was it was as much about how to interpret and to weigh the value of the Real-World data as it was the formal functional subject matter area, which I think it was an early effort, but I think an important one and one I think we’re going to be seeing more and more companies starting to focus on how do we help integrate real-world data into our research and our publication and our communication processes.
Saul Marquez:
For sure. You know, and and there is so much of it out there. I mean, you’re listening to this and you’re thinking to yourself, there’s a bunch of data that I’m working with. What I do with this? How can I get insights from it? But how can I put together a marketing campaign or put together a strategy based off of this that I’ve been generating, our patients have been generating. And this is a great topic of discussion Greg and and a great example of how to do it. Give me an example of when it hasn’t worked out and what you learned from it.
Greg Matthews:
Hoo. Well, I think one of the things that I have learned and it’s through hard experiences that is that I tend to be what I’m exploring a new area. I tend to get my hands very dirty. So even though, you know, I’ve been in the business for 30 years, I don’t often want other people going out to try and learn for me. So being able to experiment with data sets has been a really important part of my process. And so, for example, in 2011-2012, Fred Trotter and his team were able, through Freedom of Information Act requests to finally get prescribing and referral data from Medicare. And I was one of the first customers for that data. The reason that I mentioned that example is that one of the toughest things about this process is actually getting access to the data in a way that is usable. So I would say our early attempts to work with Medicare data were we struggled mightily and I would say in many ways failed simply because we weren’t ready for the vast quantity of data that we had. But we also weren’t ready for the, excuse me, I’m going to say the uneven quality of the data. There’s a lot of dirtiness in health care data. And so being ready for that is absolutely critical. Any kind of analytics project that I do, especially if it’s with an unfamiliar data set, always allocate a bunch of time upfront, maybe 20 percent of the total product time just to cleaning data. So I think that’s a place where failure has happened more often than not. But then there are other situations where just a lack of access to the quantity of data necessary was a big thing because it can be difficult to obtain data that gets into very specific populations. So other than Medicare, you know, if you’ve got the hundreds of thousands of dollars to spend in buying claims level data or other sorts of data sets, that’s that’s one thing. But for the data that’s accessible to sort of the regular guy. It can be pretty tricky.
Saul Marquez:
Yeah. Now that’s that’s very interesting. And so what about the other side of the coin? Greg, give me an example of something that you’re really proud of.
Greg Matthews:
This is the question on your list Saul, that I actually have struggled the most with because I have absolutely loved the time that I have spent working in health care. And so there are a lot of proud moments. I think probably if I’m going to pick a particular moment in time, it was when I was able to debut my very first homegrown product at the Mayo Clinic in 2012. At the time, I was working for a health care agency called W2O and had been working on the first-ever social analytics platform that was focused exclusively on targeting physicians and their online behavior. And in our case, mapping that to a physician registry. And after only three months of working in that data set with a prototype sort of moonlighting with it with a developer, I was able to stand up at the Mayo Clinic and debut initial results and put a prototype product out on the public app for people to look at. And I think that was that was one of the most exciting moments of my career. But the truth is, the real answer to that question is I really most proud and most gratified, I guess I would say, by the community that I’m a part of. I’ve been able to make connections with so many doctors around the world, with patients around the world, with health care companies as diverse as two person startups to the world’s biggest pharma company and that community, in spite of all the flaws of our health care systems around the world, is one that is really passionate. And I think being a part of that is the thing that’s most gratifying.
Saul Marquez:
Love it. Yeah, it’s a great ecosystem. Sounds like you’ve been able to work with all sizes of companies and all sorts of health care leaders. And today, Greg. What would you say is the most exciting project you’re focused on?
Greg Matthews:
So this is a really, I’m glad you asked that question. And it’s a it’s a bit of a tie on to the conversation that we started around real world data. But what are the things that I’ve recognized is that whatever happens in the health system, there’s really one important relationship. It’s the doctor and the patient. That’s where the rubber meets the road in health care. It always has. And to some degree it always will. And for me, being able to understand how physicians are interacting with each other, how they’re interacting with patients, how they’re interacting with any institution they might be affiliated with, that’s so important for companies that are working in life sciences or whether they are hospitals and health systems or digital health companies. And so what has got me really jazzed right now is that I’ve been focusing a lot of energy on really understanding the layers of physician networks. So all the connections that doctors have with each other. First off, who do they publish with? Who are they connected with online? Who have they done clinical trials with? Who are they on advisory boards with? All of these connections, help us to understand a physician’s ability to communicate with other doctors and to have their ideas be impactful to other doctors. And yet in life sciences and in hospitals, I see that being largely ignored. We focus a lot of attention on what doctor was on the podium. We focus a lot of attention on what doctor published in Nature, but we’re not really looking broadly at how physician networks really function. And so for the last year, I’ve been really, I guess I would have to say obsessed if I’m being honest, with trying to understand, measure and value physician networks to give better understanding to health care companies about how to engage with doctors.
Saul Marquez:
And what’s going to be the output of your study? Are you going to put a paper out? What does that look like?
Greg Matthews:
Yeah, I think it’s really likely that there’s going to be public research that I release very soon. I have been working with clients for the last year, really refining and honing this model. But I recently did my first non-client study, let’s call it. And I think the results of that is going to be something that I ultimately will publish. In this case, the industry that I was looking at are hospitals and health systems to help them better understand how to connect with physicians who are not affiliated with their institution, but really leveraging the value of the physicians who are affiliated with their institution. So essentially understanding how they can leverage their clinicians networks as their primary ambassadors ship for building the reputation of their organization, for identifying candidates to hire, for vetting candidates to hire and things like that. My hope is that it’s going to be a fairly disruptive thing in the hospital space.
Saul Marquez:
That’s neat. And I think about health care and it’s such a unique ecosystem. You could definitely do a lot of these studies, whether it be physician networks or how insurance companies works. I mean, you could do a pretty interesting anthropological study to better understand that. Right? I mean, there’s there’s something there. Maybe it turns into I don’t know if your intent is to is to make this a tool that helps marketers or a tool that that helps. I guess organizational strategy. I don’t know what would be the spin on it.
Greg Matthews:
I’ll let you in behind the curtain here Saul, you and your listeners. I think the way in is probably going to be through marketing, because I know that hospital marketers are really interested in understanding how they can raise the reputation of their institution among physicians, largely because the U.S. News and World Report best hospital rankings is such an important part of any hospital’s reputation now. And physicians have a real strong vote in that. I don’t know if it’s commonly known, but roughly a third of that score winds up coming from physicians. And so, you know, in the study that I just did, I looked at one hospital system in the southeast region of the United States and map there some of their connections with other physicians. And it’s really interesting. Do you mind if I share a couple of numbers? I can tease this study a little bit. So I looked at publications that were written by physicians that were affiliated with this hospital in SE and saw that for about 1800 of their doctors had published research in the last 5 years, there were 2500 publications and eight hundred and twenty eight outlets. But what’s really interesting is that they co-authored with over 7000 doctors who are not affiliated with their organization, and that is an implication that there is a network there that is built in of trust and respect. So that’s kind of interesting. Now I look a little deeper and see that of that seventy five hundred, more than fifteen hundred of them are in the region where that hospital is located. So they’re able to make referrals, they’re able to vote in the best hospitals rating, they’re able to be potentially hired by this organization. And then when I shifted perspective to looking at online connections, I just looked at one hundred clinicians that were active online and saw that those hundred individuals had 27000 unique followers. Three thousand of them were physicians. And that’s just for a hundred of their doctors. So I think that there’s a real opportunity for hospitals and health systems to really dig into this data and figure out how do I actually connect with the right doctors.? And it’s a lot of the same things that we see Life sciences teams doing when they’re trying to understand, you know, if they’re if they are launching a new product or going into a new market, they need to get to know the physicians in that marketplace. And we can use these same kind of techniques looking at physician networks to help them identify those doctors.
Saul Marquez:
Love it. It’s a great, great idea to explore. And it’s definitely interesting to hear how you’ve thought through ways to explore these networks and something for everybody else to think about. Greg, time for the Lightning Round. You ready for it?
Greg Matthews:
I’m ready.
Saul Marquez:
All right. What’s the best way to improve health care outcomes?
Greg Matthews:
Ensure that patients have easy access to all their own data.
Saul Marquez:
What’s the biggest mistake or pitfall to avoid?
Greg Matthews:
The idea that you can silo yourself off from the rest of the health system. Looking for productive ways to integrate is the key.
Saul Marquez:
How do you stay relevant despite constant change?
Greg Matthews:
I think always being willing to question the status quo, being curious, being willing to not have sacred cows in your organization. Absolutely critical. They represent blind spots when things are moving as fast as they are.
Saul Marquez:
What’s an area of focus that drives everything in your work?
Greg Matthews:
Network behavior. It’s all about understanding network science and being able to go deep in it. That’s where I think I’m going to make my biggest impact in health care.
Saul Marquez:
And what book would you recommend to the listeners, Greg?
Greg Matthews:
So this is another tricky question, because I love, love, love reading. But I’m going to point back to a book that people can actually get free. There’s a book called The Public Physician that was written by Dr. Brian Vato Beadie and I think in 2016. But it’s still one of my very, very favorite books, because he’s really shining a light on the fact that there’s been a cultural change in medical practice that allows a lot more freedom to physicians to have active voices publicly rather than just privately. And so I’m going to point to that one, because it’s been a big impact on me. And I know that that book is available free for download on his Web site, which is 33charts.com.
Saul Marquez:
Love it. Great recommendation. And folks, you know how to get to the resources of our podcast. Just go to outcomesrocket.health in the search bar type in Greg Matthews and you’ll be able to see that there. Before we conclude, Greg, I love if you could just share a closing thought with the listeners. And then the best place where they could get in touch with you.
Greg Matthews:
So I think probably the easiest way to reach me I’ll answer the second question first is on Twitter. I’m at @chimoose c.h.i.m.o. o. s. e and I’ll be happy to tell the story behind that and for the price of a beer the first time we meet. And I think as a closing thought, I would say look for ways to better target communications and to better learn from your audiences. Don’t accept the status quo that says you have to accept one of six personas as the closest you can get. We can do a lot better today.
Saul Marquez:
Love it. Great closing thought, Greg, and thanks for giving us some insights into physician networks and the work you’ve been up to. Really appreciate your time.
Saul Marquez:
Thank you so much Saul, glad to be here.
Thanks for listening to the Outcomes Rocket podcast. Be sure to visit us on the web at www.outcomesrocket.com for the show notes, resourses, inspiration and so much more.
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