This week I am talking to Sanjula Jain, PhD (@sanjula_jain), SVP Market Strategy & Chief Research Officer at Trilliant Health (@TrilliantHealth), a company focused on healthcare industry expertise, market research, and predictive analytics to create evidence-based direction for Healthcare.
Sanjula has like many of my guests an interesting background and origin story but in her case set her on a path of greater influence and focusing on the bigger picture and the importance of data and policy to bring about change. Along the way, Sanjula managed to take the keen insights and data approach and update it with more recent claims data that allows for more current insights.
We discuss the challenge of inequity and disparities and the challenges of extracting out these differences with data that can already be biased and as you will hear finding ways to supplement this with other data sets and allowing for proxy inference from other resources
We dive into the process of influence and the use of data and as Sanjula says we need a whole additional hour for this but there is good news – she wrote a book on this area with some co-authors: The New Health Economy: Ground Rules for Leaders so for those as interested as me you can pick up a copy. Leadership is hard and especially so in Healthcare and critical to effective leadership is wide knowledge and understanding of the work gins of healthcare supplemented by data.
Listen in to hear the importance of understandings of the system and components, the inclusion of data in the conversation, and how we can go about bringing about change to our healthcare system by having critical and data-based debates that ask questions and challenge each other.
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Raw Transcript
Nick van Terheyden
And today, I’m delighted to be joined by Sanjula Jain. She is a Chief Research Officer at trilliant Health Sigalert. Thanks for joining me today.
Sanjula Jain
Thanks for having me, make us feel pleasure.
Nick van Terheyden
So if you would you have an interesting background, I think highly relevant to the conversation we’re going to have. Tell us a little bit about how you got here, what your sort of career path is to this point. And you know, a little bit of the highlights if you would.
Sanjula Jain
Sure. So like most people in healthcare, we all have some type of, you know, personal story or exposure that kind of shaped our frame of the world. The short story for me is that I grew up in a family with elderly grandparents who had a range of health care condition. And as a young child, who was also interested in science, I started asking questions of, you know, a lot of this could be prevented by diet and lifestyle and education, right. I’m talking a lot about chronic conditions like diabetes and hypertension. And it kind of led me down this really education and information and, you know, how do patients get information from their physicians? And what are you know, coming from an Indian family? What are the differences, you know, culturally, you know, you there’s a lot about, our culture is ingrained in food, and that it kind of occurred to me that, well, so much of what my grandparents were doing was, actually because that’s how they were taught culturally, maybe not realizing that some of those things that they were doing, maybe not have been the best for their health, so to speak. And so, you know, as I started going on the path, and well, I think I want to be a clinician or a physician, rather, who could really help educate patients and give them the information they need to make better healthcare decisions. And so my mind is always thinking about decision making and how to influence that psychology. I won’t bore you with all the details. So I went down that path with a lot of research, you know, working at MD Anderson, and you know, thinking about nutrition and all of these things. And I ended up majoring in psychology, you know, exactly for that reason. And along the way, I realized, I don’t know that it’s so much a patient information issue. That’s a big component of it. But it’s also the system, right? What is the information that a lot of our healthcare systems and institutions, what are they using to then make decisions about how they make policy thing, decision, they’re how they’re treating patients, or how they’re reimbursing you ever since of the care, I somehow I went from the patient level, to more of the organizational level, because I, from my vantage point, felt that the organizational level played a more maybe not more significant, but they maybe had more of a scale ability to directly influence that patient level behavior. And so I set out on how do I best equip decision makers of important institutions that ultimately have that influence to make these changes. And that led me down a path of research. And so I’m a trained health economist and part time faculty over at Hopkins, you know, I’ve authored some books, right. So I think a lot about how to think about collecting the right information. But being an academia, I realized, well, the decision makers, you know, we’re running hospitals who are writing health plans, those, you know, we’re both on the DC area, those of us that are, you know, on the hill, right, they’re not necessarily making all their decisions by reading papers in champ, right, that’s like one of many inputs and the way that healthcare moves so fast, and it’s so complicated. And, you know, if you’re running a health system, for example, right, you’ve got to be up to speed on telehealth and Medicare and, you know, new innovations and clinical practice, you have to know a lot of things. And it’s it’s a lot as a decision maker to process that information and speed. And so, I had spent some time working in industry in a couple of learning organizations focused on peer learning with C suite executives in particular. And so really, I went down this path of by knowing how C suite executives were making decisions, their day to day priorities, the types of information they were consuming. It wasn’t the academic stuff that I was, you know, spending so much time on. And so I wanted to find way to bring the academic rigor of research and information to that stakeholder group. And so that ultimately kind of has led me down to do a couple of different things and applied research in the business world. So I’ll jump over straight to, you know, try and help, which is basically an academic stream. Because the reason I really came over here is Trillian, health has access to an all payer national claims database, right, which, you know, not get so in the weeds is something that academics don’t usually have the privilege to have access to, because it’s a lot of data, it’s really expensive. Most academic research will look at just Medicare, or you’ll be lucky if you have a partnership with one health plan. So you can you can run studies looking at all Blue Cross or you know, Blue Cross, just a Massachusetts, right, but this dataset allows me to see all of it. And we’re also a qualified entity with CMS. And so I get direct feeds, you know, from there as well. So, having access to data that reflects really, the entirety of the American population is truly a privilege that I have as a researcher, and then that data is very recent. So as you know, right? In academic literature, most studies usually have a lag, right, it takes so long, and usually you’ll be reading something in 2022. And the data is from 2020. The data that I get to play with while it’s updated monthly, right claims are rolling in on an ongoing basis. So it’s really given me the ability to look at trends and what’s changing across the ecosystem, whether it’s by geography by pay type, by patient, population, disease, state, you name it, I can see that longitudinal patient 30, and not to be restricted to what’s happening in one health system or one payer. And so that I think has afforded the ability to help decision makers now have a little bit of a different set of facts set of information. And what I spend my time doing day in and day out is trying to Virtus, that rich data set to help extract, you know, new insights and emerging trends that I think decision makers across all aspects of healthcare should be aware of.
Nick van Terheyden
So I phenomenal sort of background and also backstory that, you know, I think, brings a tremendous amount of relevance. And it’s an interesting pathway different to, you know, for example, mine where, you know, similar sort of impacts, and, you know, shaping of that, but in your particular instance, you know, looking at that from a broader higher level perspective, what really strikes me and you said something back there that I sort of noted down, which was, you know, I don’t want to say I have more influence, but you know, more impact. And I think you do, and, you know, I’m sure that lots of my clinical colleagues in many respects, and vie that capacity to influence in a broader behavior. We, as physicians love that one to one interaction, and do our best. But you know, many cases fail, because we’re not acting on the appropriate data. So I think your P value is fantastic in terms of impact. And then you talk about this data set. And you know, we’re going to dive a little bit into that in a second. And obviously, tremendous value, because it’s real time. But one of the things that I just want to talk about here is, you know, the huge expose a that we’ve seen in terms of racial inequity. And the question that I have in this is this is great, it’s claims data. But does it actually capture the full extent because in many instances, those are the individuals that aren’t, I would imagine not captured. I wonder how you sort of address that, because it must be one of the primary issues that you think about on a day to day basis.
Sanjula Jain
So with any research, right, any study design, there are numerous methodologies, different approaches, and they’re always strengths and limitations. So claims based analyses have their limitations, no doubt, but they also have their strengths. And so one of those limitations in a traditional sense, I would say is right, like, I get a lot of questions about well, how do you see what the uninsured are doing? Or how do you see kind of that cash pay population? And there’s a couple of things right, so it’s about looking at the signals. So when we think about health equity and disparities, well, I do see Medicaid, right, and a lot of the underserved population is reflected in the Medicaid population. So it’s not everybody, but it’s it’s a very representative group that we know that So many of the challenges are healthcare system is trying to solve, when it comes to those disparities really starts with the Medicaid population or what I would call, maybe even Medicaid lookalikes. Right? So a lot of the discussion in the health services health policy world is, well, some of the individuals that need health care the most, Medicaid is that safety net program for them. So even if they’re not enrolling into into the program, right, there are a lot of things that we can learn from what we know about the health care behaviors and utilization patterns and psychographics of a typical kind of Medicaid individual. That said, there are other ways we can start looking at a, let’s call it proxies, if you will, right. One of the things like I said, I’m not an expert in this area. But as a researcher, I think a lot about we talk about disparities, we tend to go straight to race and ethnicity. And that is surely an important factor. That said, there are a lot of correlations that are statistically significant that we know that some a lot of the disparities come down to socio economic conditions, right, your education status, your income, where you live, and your zip code. And so by and large workplaces can be limited. Well, what I can see in the dataset is I can I also routine, stitches together other datasets. So we look at things like from EZRI consumer datasets, which we use machine learning to, to kind of tokenize that to the healthcare activities. So that affords me the ability now to look at things at the zip code level. And you can make a lot of you can glean a lot of insights from what you see by geography and by income. And by education. That is a pretty good one, too, or I can’t show it to you from the data perspective. But if you read any of the literature and other experts who look at that, from a survey perspective, it’s pretty aligned. So long winded way of saying, you know, there are other ways to get to it. And because the claims data set can be stitched together with other geographic data set, there are ways to ultimately get to that. Those questions, I think you see that in some of the utilization patterns, but I think we know enough, across the industry of generally, which populations are affected and why. And so I think we spent almost too much time in the industry rehashing things that we know, as opposed to really thinking about, Okay, let’s take individual examples of health care behaviors or conditions and figure out what’s it going to take to move the needle? Right. So the example of that is other it’s telehealth or behavioral health, right? Like, are there differences? And what we’re seeing in some of those geographies, or groups like Medicaid that are different, right? So if you look at telehealth utilization trends, there is a difference by geography. But more importantly, there’s a difference by payer group and consumer subset. When we look at behavioral health, we see that, you know, there are utilization trends across all geographies and all patients segments, it just, there’s maybe less differential in terms of some notable things that people are doing differently here or there. So depending on what you’re studying, you’re gonna get different questions, but sorry, different answers. But ultimately, you know, where claims can be limited? If you think beyond a black and white approach, and really think about all the things we know, what are the factors that influence those outcomes and both populations, it’s about looking at the right variables as opposed to, you know, variable that we might think we’re looking at.
Nick van Terheyden
So for those of you just joining, I’m Dr. Nick the incrementalist today I’m talking to Sanjay Jain. She’s the Chief Research Officer at Trillium Health, we were just diving deep, deep into the data sets the ability to sort of tease out find proxies, I think extremely important in terms of representation and other see supplementation with other datasets that, you know, truly fascinating. And, you know, there was something else that you mentioned, that I wanted to just get a little bit deeper into, which was, you know, your understanding of the C suite that you sort of talked about, and you know, what influences them because ultimately, you know, one of the things that I say repeatedly online is, you know, I appeal to these people at the leadership because they’re the ones most equipped to actually affect real change. And I mean, the notion that anybody comes in trying to do harm or do a poor job is just it’s doesn’t sit with me. I think everybody comes in with the right intent, but they struggle because of the data. What have you learned, when it comes to that influence? What are the components that contribute to that group? And how do we help provide them with the appropriate decision making Who’s you’ve obviously found some pathway to that, right?
Sanjula Jain
Absolutely. And we probably have to have a whole other hour just to do that. But I agree with you. And, you know, a large part of what I had recently written a book during the pandemic, about leadership, about, you know, ground rules for leaders in the new health economy. And, you know, I think there are a lot of factors at play. But the starting point that what you alluded to is that leadership is hard. And it’s particularly challenging in healthcare because of how complex the industry is, right? And how much knowledge you need to have. And it’s a highly regulated industry. Right? So that’s one piece of it, I think we have a lot of silos in the industry, right? So you know, you have to be even if you are a health system executive, right, you have to maybe know about clinical care, like a lot of things that you know, you would, as a medical training would have to be aware of right how to think about position management and patience and keeping up with the innovative science and technology. But you also have to be aware about policy and reimbursement and the ins and outs of Medicare and Medicaid, right. And then you have to know about all the things about governance and how to think about running a board really, you so much domain knowledge and a lot of ways across a lot of areas, no matter where you sit, right, a farmer can be really deep in the clinical innovation side and know everything there. But, you know, where farmer can be hampered is not knowing enough about the realities of what it takes to facilitate change management at the bedside, right? Like, I’m just kind of throwing that out there. But the lack of silos, I think, is another piece of that. And then the other part is, because of how complex healthcare is, right? There’s a lot of historical information that I think we tend to miss. So and I experienced this coming in the industry, right? I’m, I’m still pretty young in my career and doesn’t when I teach students in the classroom, right, it’s like, you have these great bushy eyed students are like, I’m, you know, I think we should build this innovation, right? Or this technology, and this is going to be great. And it’s, it’s not that that’s a bad idea. But then I’ll say, well, that’s actually may have already been tried 20 years ago, or have you thought about what, how are you going to get physicians to adopt it in their clinical practice when they’re already doing 30? Other things, and you may have, you know, a bunch of other companies pitching them different point solutions. Right. Thanks. So there’s a lot of that context, right. Or in some ways, I would also argue that history almost like repeats itself, right. So today, we’re talking a lot about value based payment models, and ACOs. And all of that. Well, to some extent, we were kind of going through that back in the 90s, with HMOs. And some of those models, right. So they’re just, we’re iterating on a lot of the same things that we’ve been talking about for years. And so if you don’t have all of that context, you can spend a lot of time as a leader, whether you’re a new leader, or even an experienced leader, trying to just catch up on that, right. And you may be spending a lot of time on something that maybe it had, you know, and about another kind of component or what it takes you back some of that. So that’s a long winded way of saying, right, it’s hard, right? It’s really challenging a lot of information. And you almost have to just survive in your day to day operations to run, you know, I’ll put on the hospitals again, right? You have to just keep the hospital lights on and get the IDI working in operation going that sometimes it can be hard to take a step back as a busy executive and say, Okay, this is my today’s date, what are all the things need to be thinking about and know about how to prepare, you know, for that feature of date? And so, how do you solve it? I mean, I think it’s not a silver bullet. And it’s a matter of a lot of bringing different stakeholders to the table, I think we have far too long been way too siloed. And we have to have more conversations where you have payers sitting next to providers, right, you have to have more information exchange and learning the shared understanding. Ultimately, I also think the system is working to some extent the way it’s designed. And that’s a whole other conversation we could have for another day. Right. But a lot of the financial incentives and policy structures and, you know, who was lobbying for what that explains a lot of the challenges that we’re all having. And so until we’ve all come to the table and say, We they’re all agree that we need to move to change some of the incentives right for the good health care for the, you know, American population versus for the good of, you know, being profitable and making a lot of money for our respective business. Right. There’s a lot of things that are happening based off the way the system is designed. And so there’s some inherent things that make it difficult for leaders that, you know, it’s probably a several years long, you know, coming together moment that we would have to think about, but that aside, I think it’s just about are equipping leaders with as much information in a way that’s consumable, and can get them to think and anticipate what might be coming down the pike. And I think one thing that I focused a lot about on is the idea of peer comparison, and rate of change. So one thing I have learned and working with a lot of executives is, it’s far too common to get into the pigeonhole of best practices, right? So we say, oh, you know, how system a had this really cool initiative, and, you know, patient engagement, whatever it may be, then all of a sudden, you have another, you know, hospital saying, Great, we’re gonna go emulate. There’s a lot you can learn from each other. But it’s also important to understand, are you comparing apples to apples? Do you have comparable patient population? Do you have comparable economic conditions, right, because how you weight and burn from different people also depends on what is relevant to your own unique situation. So I think, I don’t know how you want to frame that, but more of nuanced exchange of information and trying to help people make the right comparisons or thinking about the right peer groups. So the best example I have is, you know, you look at the US News World Report, right? Everyone kind of says, Oh, well, mayo and Cleveland Clinic, right, they’re the gold standard. You could ask them hospitals, you know, across the country, they’re like, Well, I want to be just like mayo, right? Well, there are a lot of things that are just inherently gonna make that never true, right, just based off of your markets, and your patients and everything about your organizational model. But yet, we’ve spent a lot of time saying we’re gonna go learn about those things. So I think there’s a better sense of data driven comparisons that can help leaders move forward. And the second part is rate of change, right? So I think sometimes we have a tendency to extract, you know, things that we read about in headlines, or things that we’re hearing from our peers to say, Okay, well, that’s going to be the new shiny object. Let’s go now go focus on a whole new initiative to stand that up. Well, have we actually taken a step back to contextualize across all of these things that are happening? What’s actually moving the needle and not right? Is this just a fad? Is this affecting 10% of our populations, or 20% of our population? Depending on the answer to that, we might make a different decision of what we do as an organization. Right. So I can bore you with a couple of examples there. But I think you can kind of get the conceptual point. So I think leaders are in a tough spot. And the more that we just have a shared understanding and have a data driven conversation around what’s happening in the ecosystem, I think that takes away the subjectivity. And the opinions of what I’m doing is better than you, or this is the right approach, prove it, write the number, show the measures, show the outcome, explain how it works, what’s the magnitude of change, I think if we started holding ourselves with that level of rigor and discipline in, in our conversations, we would see a very different set of decisions being made across the industry.
Nick van Terheyden
So I’m just going to say that the density of knowledge and insight in your content is just extraordinary. You rank in the top list of people I want to break bread with and spend an awful lot of time just to understand and dive into so many areas. You know, you raise a point that I repeatedly make, you know, the system is not broken, it’s working as designed. And we have to fix that, you know, that’s not always a popular notion, but it’s the reality. And I think, you know, you’re sort of attempting to do that. I found it fascinating, you know, talking about these sort of innovations. And I hate to crush that. But you know, that’s one of the things that happens over time. And, you know, I’m brought back to my father in law, in this case, who always used to say you can’t put an old head on young shoulders, which is, you know, another way of saying it’s very hard to gain that experience. And that’s not to say those individuals don’t but you know, and ultimately, as you sort of describe it, you know, those various elements of finding peer companies and what I think importantly, this data driven conversation, I think, for me, is the anchor point in all of this in if you could do you have a sense of what you could do, or what would be the most value to you to really help change the trajectory?
Sanjula Jain
Oh, that’s a loaded question. So if I had to condense that, I would say, Well, I think we have to almost take a step back in all except that the way we’ve been doing things is In working, right, and I think we almost need to open our eyes to different methodologies and not take things that are presented to us at face value. And so, to me a lot of the issues stemmed from a read a headline, I’ll pick up the telehealth example again, right. Well, Americans love telecom. Okay, well, that’s going to be the guiding point. Should we really critically ask the questions about how do we come to that conclusion? Which which populations were surveyed? Is that a temporary versus a permanent trend? Right? Like, we don’t really take a step back, sometimes industry to critically debate and ask those questions and challenge each other. And so I think if we just had that level of candor and discussion, maybe going, that might start exposing some of the things we need to work on as phase two of that.
Nick van Terheyden
So unfortunately, as we do each and every week, we have run out of time. That’s a terrible tragedy in this particular instance, but that doesn’t mean say that we can’t repeat this and go in into more detail. It just remains for me to thank you, San Angelo, for joining me on the show. Thanks for joining me.
Sanjula Jain
Thanks so much for having me, Nick. Appreciate it.
