Dr. Amol Navathe | Leveraging Data, Incentives, and Behavioral Economics to Transform Healthcare

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Healthcare Unbound Intro/Outro:
Welcome to Healthcare Unbound, a podcast powered by Clarify Health, where healthcare's changemakers discuss ways to advance care outcomes, cost, and affordability.

Saul Marquez:
Principles of behavioral economics, including inertia, loss aversion, choice overload, and relative social ranking have been applied to motivate personal health decisions, retirement planning, and even savings behavior. However, they have more recently been studied in healthcare, specifically regarding the design of physician incentive programs to reward performance and engage physicians to boost their success working with value-based payment models. Systematic incorporation of the principles of behavioral economics in the design of physician incentives holds promise to incentivize high-quality, cost-conscious care, and we're excited, as part of this podcast, to share and shed more light on this powerful concept. Welcome to the Healthcare Unbound podcast powered by Clarify Health.

Saul Marquez:
Hey everybody, and welcome to the Healthcare Unbound podcast, powered by Clarify Health, where we have conversations advancing the business of healthcare. Joining me today for our first podcast in a series of episodes focused on incentives and finding ways to attain operational efficiencies while delivering high-quality care is Dr. Amol Navathe. He's an associate professor of medical ethics and health policy at the Perelman School of Medicine at the University of Pennsylvania. He's also co-director of the Healthcare Transformation Institute and associate director of the Center of Health Incentives and Behavioral Economics at Penn. Dr. Navathe was the co-founder of Embedded Health, a healthcare technology company that brings behavioral economics solutions to improving affordability and quality. And he joined Clarify Health, a leading healthcare analytics, and value-based payments company, when Clarify Health acquired Embedded in 2019. Dr. Navathe is so glad that you could join us, welcome.

Amol Navathe:
Thank you so much for having me.

Saul Marquez:
It's a true pleasure, and look, I'd love to just begin the conversation, really unlocking and understanding your work. So what is your passion for work in the physician incentives area, and what inspires that work?

Amol Navathe:
So as you noted, I'm a physician myself, and in fact, one of the reasons I decided to become a physician is to truly understand what it means to take care of patients, but also recognize that physicians played an important role in society as stewards of resources, as agents for their patients, but also for society, and that dual role is actually something that makes being a physician both interesting on-one hand and challenging on the other. And physicians, as you would recognize, are humans just like anyone else, and so we are subject to the same kinds of heuristics and biases as any other human. And so the way that we design systems, the way that we design incentives undoubtedly plays a huge role in how physicians end up behaving, personally, you would also hear, importantly, professionally. And so I got very interested in the psychology of physicians and how that influences the way that they actually care for patients and how we might be able to leverage, for example, their natural altruism to try to get to a more efficient, high-quality health system.

Saul Marquez:
Thank you, Dr. Navathe, and this juxtaposition of the altruistic side versus getting things done in a way that's both efficient for the system and great for the patient is key. As we evaluate value-based models in our health system, what do you think is missing today in them?

Amol Navathe:
I think value-based models were created really with the destination in mind, not the journey, and let me unpack that for a second. So what I mean is I think policymakers and health policy wonks, not unlike myself, I would count myself in that group, thought about, hey, we want a system where we're paying for value, we're paying for outcomes, we're not just paying for activity. And so our traditional historic system was one that was what we call fee for service, meaning that we pay for people to do things. And guess what? If you pay clinicians and healthcare organizations and hospitals more to do stuff, they do a lot more stuff. So it makes sense, doesn't it? Let's just pay for the outcome, let's pay for value. Let's say we want to give you incentives to produce more health on a tighter budget, sounds great. What's missing, in fact, is the psychology, the pragmatism around that journey of how we get there. Turns out it's not imminently obvious how to change healthcare. And so, what we need are intermediary steps that distill what the destination needs to look like into a concrete set of steps and to make this discrete and actionable, and that's really been the core focus of my work over the last decade. Is we want to get to that destination, but how do we make it more achievable? How do we make it a step-by-step process, as opposed to this marathon that nobody knows how we actually get through it?

Saul Marquez:
That's a really great call out, Amol, and it's that step-by-step that oftentimes gets missed. Even when we think about quality outcomes, we forget about the workflow, which is the step-by-step path to the outcome. I love that you brought forth that idea. Why haven't incentives worked with past value-based models?

Amol Navathe:
I think, plainly, the incentives were designed poorly. So let me give you a very simple example, right? Most value-based payment models, even today, are designed in a fashion that you start in a given year, say, January 1st of 2023, right? But you get your bonus check for doing great work in April or maybe even June of 2024, so that's a 16 or 18-month lag. In behavioral economics, or the psychology of how people make decisions, there's a principle called immediacy. That's, simply means if you want people to change behavior, give them their reward or their penalty immediately right next to the behavior, right? It's not to sound pejorative here, but it's how you train animals, right? It's how we educate children. It's how we think about reading habits, right? Pavlov, in a sense, right? And so this applies to sophisticated professionals too, not to overly simplify it. And so, if you think about that, the value-based payment incentives don't exhibit any form of immediacy. And so that's an example where we have a chasm between how the models are operating and how, at least in an ideal, from a human psychology perspective, way that we would want them to implement it, to stimulate people, to change their behavior, change their practice patterns. In this case, that's what we're leaving on the table.

Saul Marquez:
That's a great call out. And so, why have the systems today, and you did mention the outcome, not the journey, but why is it that we've set the systems in place that take forever to reward or penalize?

Amol Navathe:
Yeah, it's a great question, and I think I don't want to over-trivialize it because I think there's a lot of smart people out there who've done this thinking. And I think, for one, there's a benevolence in thinking about the system in the way that policymakers did. So what do I mean by that? What I mean is, if you're Medicare or you're Aetna or you're a health insurance company, you're a regulator, you don't want to mandate that providers and clinicians do things a certain way, right? And so I think there was this thought that we don't want to intervene, we want to set the target and say, here's where we need to steer the ship. Now you're the docs and the nurses and the physical therapists and the hospital executives caring for patients, right? So we're going to defer to your expertise to figure out how to do that. So I think there's actually a positive intention in how that got implemented. Now, I think it also turns out, by the way, that it's not like anybody had a roadmap in their back pocket of the step by step, right? So I think that's another reason it was easy to say we want a more efficient, high-quality system, it's a lot harder to figure out what the steps are to stimulate that. I think that's one big reason. The second reason is the administrative complexity of the US healthcare system is astronomical. And it turns out that even when you go to see your doctor, the doctor doesn't get paid that day. Oftentimes the doctor's office might take a month or two before they actually submit that bill to Humana, or Aetna, or Blue Cross Blue Shield of whichever state, and then that insurance company takes a few weeks to process that payment and eventually pay it. So there's what we call a claims lag of months, and in the Medicare program, the government programs that can be up to six months. By the time you actually know whether you're achieving the outcome or not, half a year has passed. And so some of this, again, is just kind of the way that our system is designed. I would argue that's not a reason that we shouldn't be thinking about how to design better programs and better incentives, but there is logic underneath why the models work the way they do, even if they're behaviorally suboptimal.

Saul Marquez:
Great call out. Now, thank you for that. It's worth unpacking that a bit. Embedded Healthcare, tell us about your work there, now Clarify Health, what was the impetus for bringing the two companies together?

Amol Navathe:
Sure. Briefly, what Embedded Healthcare is, it's a financial incentive and physician engagement platform, right? So the idea is to align incentives across the patient-first, mission-driven companies so patients have to save money, the physicians next, and then the payers, who are ultimately accountable for the spending. So this was a way to really align incentives across this triangle. But coming back to our points around what are the kind of failures of the gaps in value-based payment models, a lot of that had to do with whether docs and practices had information about the behaviors they were actually doing, like who I refer a patient to or which MRI center a patient gets an MRI at, right, and the timing. So do I have the data, and do I have a timing of being rewarded? And those are the two dimensions that Embedded Healthcare sought to close this gap, and I think we actually proved it. So we did it in a number of different markets, and we showed a few armed docs with the right incentives and the right data, they want to do right by their patient, they want to send them to the highest quality facility that costs the least. And guess what? They win too. So it works. One of the stumbling blocks, or at least challenges friction points, let's call it, to scaling this very quickly across the country, is you need fantastic data and analytics. In Embedded Healthcare, the way that we started, we were dependent on the customer to actually provide that data. Clarify Health had the deed in the analytics at the ready, and so this was a match made in heaven, right? This is exactly what you want to bring. Embedded Healthcare is like the change agent arm that gets out there and actually motivates change, but it needs to be powered by data and analytics, and that, those data and analytics are powered by Clarify Health, and that's why it was a match made in heaven as I said.

Saul Marquez:
That's awesome. Yeah, no, it's great when you have these types of synergies happen and as we seek to find solutions for some of the biggest problems in healthcare, it's, collaboration is the new currency. So this marriage is a phenomenal one, and exciting to really understand more and share that with the listeners. Well, let's dive into behavioral economics. That's core and a big thing that you do, and think about. How does it relate to physician incentives, cost avoidance, and value-based care?

Amol Navathe:
Yeah, so let's just take a step back and make sure we're all on the same page about what behavioral economics is. Behavioral economics is really the amazing discipline that's come about in the last 20, 30 years. It's born out of psychology, and it's, psychology meets economics, essentially. And what do I mean by that? So we, as humans, we make decisions all the time, a lot of times we don't have all the information, we have imperfect information or we have imperfect timing. We can't go through and read everything in the stock market, brochures, or what have you, and so we use shortcuts because we're making thousands of decisions a day. We can't possibly research every one perfectly. So those are called heuristics or decision-making shortcuts, and they subject us to this vulnerability that we might make a decision that is suboptimal based on our own metrics. What are our own values, what are our own objectives? And sometimes, we make decisions that aren't really great for us. You know, there's classic examples that are like people exercise less than they would like to exercise. If you ask them what their values are in the next year, I want to make sure I exercise an average of twice a week or whatever it is, and then you look at a year later and turn around and look back, we don't actually achieve that. And a lot of that is because, on a daily basis, it's hard to make that optimal decision that's aligned with our year-long value. So that's what behavioral economics is about, is understanding what those heuristics and decision-making errors and shortcuts are that are based in psychology, and then behavioral economics is taking that and applying it to economic decisions. So in the context of incentives, this is exactly where you have this meeting of the disciplines in the health space. So physicians are oftentimes trying to do right by their patients, but guess what? They have to operate a physician group also and keep it financially sustainable, and how the payers are paying for drugs or paying for healthcare in certain ways, certainly going to influence them. And so you get this milieu of information, financial incentives, and then they're making the best decisions that they can, If you can make that good decision, the easy decision, if you can empower them with the shortcut information that they need to make the decision that they would want to make if they had full information, boom, you make something happen that wouldn't otherwise happen, and that's really what behavioral economics is in terms of meeting physician incentives, value-based, and the like.

Saul Marquez:
That's great and it's powerful. And as you take behavioral economics and fit it into these incentive models, that's where I think the magic happens. So let's talk about creating incentives with the goal of reducing costs and increasing better outcomes. How does behavioral economics become a part of that?

Amol Navathe:
Behavioral economics becomes a key part of that because when we bring data around healthcare costs and quality, and we don't deliver it to physicians or clinicians on the front line, kind of like drinking from a fire hose, right? The idea is not to just drown them in information, rather, the idea is, can we design the way we deliver information and incentives in a way that is matched with the way they practice medicine, the psychology of how they make decisions for patients to some extent, even just the workflow, the practice operations. So really understanding the environment, what we would call in behavioral economics, the quote-unquote choice architecture, right? What is the environment in which they're making decisions, and how that environment actually leads you to certain decisions over others? If we can bring incentives and information in a way that is very salient and very easy to process, then we can help docs make decisions that are better for their patients and better for themselves. And I think in no small part, the fact that the founders of Embedded Healthcare, myself and Emmanuel, for example, were physicians, right? So we think of this as design for physicians by physicians. We have we can be in the head of a physician because guess what? We are physicians.

Saul Marquez:
Totally.

Amol Navathe:
That's a part of it.

Saul Marquez:
And I think that's so important. You know, you literally, you read my mind, Amol, because I'm like, what better way to do it than to have somebody that's been there, done that, understands the depth and the nuance of the workflow to have design that choice architecture like you called it. And so, how do we motivate somebody to make those better decisions becomes the question. Let's, can we dive into that?

Amol Navathe:
Yeah, absolutely. To some extent, if I put my academician's hat on, we're literally diving in and understanding what are the heuristics that clinicians are using. And again, it's not that clinicians are any different than any other human, it's just that it has to be in the context of their environment.

Saul Marquez:
Totally, yeah.

Amol Navathe:
So we mentioned immediacy before, which is you want to tie the reward very closely to the action or the behavior, right? There's others as well. So medicine as a field has very strong professional norms, right? So what do I mean by that? There's the American Medical Association. There's the American College of Cardiology. There's the American College of Physicians for Primary Care, right? So there's a number of different professional societies that say these are our values, here's how we practice medicine, these are the evidence standards. So if you have a patient who has a high cardiovascular risk, meaning they have a high risk of heart attack, they should be on medications like statins that reduce their cholesterol and reduce their heart attack risk. And so the American College of Cardiology and the American Heart Association, they put out very specific detailed guidelines that cardiologists and primary care docs are supposed to follow. We have very clear standards and guidelines that set up norms, meaning when my colleague next door doesn't practice that way, it makes me feel uncomfortable and I may or may not even say something to them. But if you tell me that I'm not practicing to the standard and I'm practicing inferior to Dr. Sue next door, then that's going to motivate me to change. That is called a principle of peer comparisons, relative social ranking, that applies in society generally, but it really is strong in medicine because of these professional norms that we have. So if we go step by step and really understand where the behavioral architecture of how clinicians make decisions, then we can say, aha, if we deliver comparative feedback in a very salient, timely, actionable way, then we can empower clinicians to fix some of the areas that they might have developed not a great heuristic in how they make decisions. If you give them the financial incentive to make sure they read that report so they can win by spending that extra minute on it, then you can really cut through that friction, right? So these are the ways in which we can understand the opportunity, but then get to the ultimate destination, which, as we talked about at the very beginning, is a higher quality, more cost-efficient, more equitable system. We can start to distill that down to specific actions that we can influence, and that's again, that's really the goal of Embedded Healthcare and Clarify Health.

Saul Marquez:
Yeah, that's great. And the combination of having the data in hand and then the choice architecture to really help inform it, the outcome in mind, and the entire workflow step-by-step journey, that is like the secret sauce to making value-based care happen, and I'm so glad that you've shared these insights with us. Where does your work in behavioral economics and incentive models fit into all of this? I'd love to just dig deeper on that and understand.

Amol Navathe:
Yeah, so my work in part is about taking some of these principles and applying, and most importantly, testing them in the laboratory environment, so call it the research environment, right? And then, to take those and apply them in the real world in commercial settings. And that's where Embedded Healthcare and Clarify Health really come in as, the best way to scale ideas. I'll tell you, one of our early investors was a gentleman that you've heard of named Bill Gates, and he told us, he said, I remember sitting across from him and he said, there's nothing like a commercial model to scale a good idea. And so that was really the goal, when Zeke and I started this company, we started as a mission-driven company focused on, we even contemplated a nonprofit. Like we were like, this is about the social mission of it. But it turns out that these are the ways to really drive impact at scale, and it's a way to take these insights that you and I have been talking about here and really turn them into something that can stick in the real world. Because in my day job, in a sense as an academician, writing papers and policy briefs, that doesn't stick. It doesn't stick with, the way that it does to actually design a product that people can touch and feel and that they actually live and breathe in their daily practice. And so that's really the goal here, and that's how this fits in. I think the goal of this work is really to be a driver of the type of change that we've been chasing over the past decade-plus.

Saul Marquez:
That's the ultimate compliment, right? To get that from Bill Gates, a commercial model that can make great ideas stick. You're doing it, I want to give you and the team major kudos for what you've done thus far. Do you have any examples of which type of programs are beginning to change? We talked about these rewards being severely delayed. Any examples of programs that are already trying to change that, where the rewards come sooner?

Amol Navathe:
So Medicare, I give them a lot of credit. They have actually been very good at listening to feedback from healthcare organizations and from physician practices. One of the pain points has been groups that have less resources, particularly the ones that are caring for lower-income patients, marginalized patients, those underserved communities, those provider groups, and healthcare organizations just don't have the same resources to invest. So one of the things that CMS has started doing, that's Medicare, started doing is offering advanced payments. So they basically prepay on the bat that there's going to be some savings and they say, you know what, we're going to take those dollars that we expect to achieve at 18 months down the road and we're going to pay them to you upfront so you can make the investments that you need to actually start to change practice. Otherwise, you're always chasing your tail. So they're trying to solve the chicken and the egg problem there and give them a lot of credit because as a regulator, as a government entity, it's not always easy to spend taxpayer dollars up front, but I think they're finding ways to do that. And so some of the programs that ACO, Accountable Care Organization programs, they're starting to do this and they are trying to innovate over and above what the legacy programs look like.

Saul Marquez:
That's fantastic to hear about some of those changes already in place. And on the concept of ideas, there's no thing more powerful than an idea whose time has come. And I think the time has come for these types of changes to take effect, for incentive programs to be things that actually move the needle on outcomes and cost. I've really enjoyed this conversation with you, Dr. Navathe. Is there anything else that you'd like to leave us with or anything you'd like to add?

Amol Navathe:
I would just highlight that change is hard, changing healthcare, just like any other type of change is hard, and I think it's great that we have a healthcare system that is willing to activate around this change. And I think, you know, COVID, of course, unfortunately, had a lot of negative things. I think one of the things that did teach us is that the health system is resilient and what it needs to, it can change on a dime, and so we need to harness that adaptability and flexibility to try to really make substantive change.

Saul Marquez:
Yeah, totally agree. And again, I want to thank you so much, Dr. Navathe, for joining us on the Unbound podcast and really looking forward to staying in touch with you.

Amol Navathe:
Great! Thanks for having me, Saul.

Healthcare Unbound Intro/Outro:
Thank you for listening to Healthcare Unbound. We hope today's episode was insightful. If you want more information on how Clarify Health can help you, please visit ClarifyHealth.com.

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