Podcast
Blending Compassion and Tech: Elevating the Clinical Perspective in Healthtech
Dr. Ramon Jacobs-Shaw + Mac Davis
On this episode of Healthcare Market Matrix, host John Farkas sits down with Mac Davis and Dr. Ramon Jacobs-Shaw from Belong Health where Mac serves as the VP of Digital Product and Data and Dr. Jacobs-Shaw is the Chief Clinical Officer. Belong Health delivers a more compassionate, straightforward insurance experience for Medicare-eligible individuals by partnering with regional health plans to help them launch or grow market-leading Medicare Advantage and Special Needs Plans. Additionally, Belong Health believes high-quality health care should be accessible to all, and local, regional health plans are best positioned to serve their communities as their trusted health insurance partners.Throughout the episode, Mac and Dr. Jacobs-Shaw expands on how Belong Health is doing a phenomenal job at addressing and finding solutions for care gaps in the healthtech industry.
Show Notes
(1:21) Introducing Mac Davis and Dr. Ramon Jacobs-Shaw
(13:01) How the Culture of Healthcare Systems Impact Consumer Transformation
(22:21) Leveraging Technology to Address Care Gaps for Underserved Populations
(36:48) Frustrations and Shortcomings within the HealthTech Sector
(45:46) Closing Thoughts
Listen Now
Transcript
Introducing Mac Davis and Dr. Ramon Jacobs-Shaw
John Farkas:
Hey everybody, and welcome to Healthcare Market Matrix. I’m your host, John Farkas, and today I’m joined by two remarkable people who are helping lead into the horizon of healthcare transformation. Mac Davis and Dr. Ramon Jacobs-Shaw are joining us from Belong Health. And Belong is working to expand the availability and improve the delivery of healthcare benefits to Medicare eligible people across the country with a special focus on special needs populations. And they’re partnering with regional health plans to bring a whole person model of care to patients who really need it the most. We’re talking medical, behavioral health, substance abuse, and social services coordination. Their platform is supporting the clinicians and the patients and the health plan teams that are working to serve those really complex and challenging populations.
As you guys know here on Healthcare Market Matrix, we’re exploring how technology companies can enhance their market presence to address the industry’s pressing challenges. And so today, in this episode, we get to play both sides of the equation. Ramon’s firsthand experience with the healthcare system as a chief clinical officer, and Mac’s perspective on working to advance data interoperability, are going to really work together to provide some really good insight, especially as we are considering solutions that serve those folks who are working to help underserved patient populations. So Ramon and Mac, welcome to Healthcare Market Matrix.
Mac Davis:
Thanks, John, for having us.
Dr. Ramon Jacobs-Shaw:
John, thanks so much. Happy to be here.
John Farkas:
Great. Let’s begin and dive in to learning more a little bit about what brought you into the place you are now. Mac, let’s start with you. What got you to this point?
Mac Davis:
Yeah. Like many people, I think, in health tech, I was hired by one of the large EMR companies out of undergrad and really cut my teeth on what good looks like. Working for a variety of analytics firms, including a startup that we then sold to Cotiviti, where I managed a variety of solutions and was able to cut my teeth in the payer side as well as the provider side. So my goal has largely been to make sure that we’re delivering solutions to both payers and providers that are driving efficiencies that are ultimately helping our members and patients at the end of the day. And so, a lot of my goal at Belong is to focus on how do we build products or deploy products that are helping us make that impact day in, day out, and enabling Ramon and his team to be the best that they can be.
John Farkas:
Awesome. When did you start in the HR world? How long ago was that now?
Mac Davis:
Oh, about 12 years ago.
John Farkas:
And this is throwing you on the spot a little bit here, but if you were to characterize what some of the major shifts that you’ve seen from the time… because I know there’s been a lot of movement in how that space is addressed. But when we’re talking especially around interoperability, what would you say has been some of the biggest moves that you’ve seen in that space and time?
Mac Davis:
Yeah. I mean, I think there’s been probably a couple of shifts explicitly. One, I think standards have become more standard. There’ve always been standards, but the ability of the ecosystem of vendors to actually execute well against those standards has had a lot of variation and that’s starting to close down. I think people have always argued about this standard or that standard when the reality is that vendors just need to conform to them, and I think we’ve started to see that with the industry coalescing around TEFCA and the next generation of interoperability.
But I think the other piece is the expansion of these core admin systems to include a larger scope. The more integrated and native capabilities that are within these core operating systems on the provider side, the better. I don’t think we’ve seen that same success rate on the payer side as much. So on the payer side, there isn’t a core operating system for a health plan the same way that there’s a core operating system that covers patient accounting, practice management, inpatient, outpatient that we see with the Epics or Oracle Cerners of the world that can perform a huge portion of the overall functions of the hospital with one core workflow tool.
So I think those would probably be two of the big pieces, and then I think the third would just be the expansion of what we think of as healthcare. A lot of these systems and tools were very much a let’s figure out how we take care of members-
John Farkas:
Hospital centric?
Mac Davis:
Yeah. How do we take care of these members within the four walls of this room? And now it’s about how do we take care of these members outside of these four walls, and then how do the systems evolve in order to account for that.
John Farkas:
Yeah, very cool. And yeah, I think that there’s definitely… it’s going to be an interesting even the next two years, seeing how those systems are going to move to incorporate broader and broader swaths of the operations. It’s interesting days for people in the healthcare technology realm, that’s for sure, as we watch a lot of the-
Dr. Ramon Jacobs-Shaw:
That’s an understatement, John. Understatement.
John Farkas:
Which folks listening to this are very well acquainted with. There’s a lot of waiting and seeing going on right now, and a lot of that has a lot of anxiety related to it, I think, on a number of fronts. But Ramon, how about you? Give us a little bit of your backdrop?
Dr. Ramon Jacobs-Shaw:
Yeah, absolutely. You summed up Belong Health and what we do so very well. Our focus is on those vulnerable populations. And listen, John, I come from a vulnerable population myself, and so growing up with less than ideal access to healthcare was definitely something that I was very much familiar with, and so can certainly relate to people, our members, our patients out there who don’t have the best access to healthcare. That for me was the trigger to go into medicine myself.
Yeah, I trained as both an internist and a pediatrician, and I’ve worked in health systems. I’ve worked in large academic medical centers and transitioned that work into organizations like CareMore Health, which is based out of southern California, where I worked as a regional medical officer and oversaw the largest market in the country; focusing on that Medicare population as well as the dual eligible population specifically.
And then took that work into a place like Oak Street Health where I helped to launch the New York market as the senior medical director. And for those of your subscribers that may not know Oak Street, Oak Street is an organization focused on primary care for the Medicare eligible population. That includes not only Medicare folks, but also dual eligibles. That’s where my life’s work has been.
And what resonated with me about Belong and joining Belong is that that mission and vision to focus on a population, the dual eligible population specifically, that has always been… I’ve always used the term overlooked and looked past by everyone in the system. Whether it’s health systems, providers, plans, you name it, people have kind of run away from the D-SNP population. And trust me, the dual eligible folks out there have certainly felt that, and so Belong has come along in order to really fill that gap, to bring the absolute best in care that we can via our platforms, our data, our analytics, our clinical solutions, in order to really take care of them. So that vulnerable population focus has been what has driven me throughout my career and certainly is what brought me to Belong.
John Farkas:
So let’s just stick the why behind the what a little bit. You said the organizations are running away from that population. Why is that? What’s the anatomy behind that problem and what’s caused that to be in place?
Dr. Ramon Jacobs-Shaw:
Yeah. By virtue of being a vulnerable population, they’ve been marginalized. And I think the thinking… not I think, I know the thinking has been that the folks who are dual eligible are sicker than your average population. Certainly sicker than your Medicare fee for service, certainly sicker than a person on Medicaid. So we know that they come with more chronic conditions, chronic medical conditions. We know that the rates of behavioral health, specifically mental health conditions, are more in this dual eligible population. We know that there are vulnerabilities when it comes to social determinants of health. And thinking about not just access to care, but some of these other social determinants. Think about transportation, think about housing security, food security; so many elements that affect someone’s health that in traditional healthcare have not been viewed as healthcare.
And so, we know with these multitude of conditions, of issues, there are more resources that need to be brought to bear in order to really address those needs, both primarily health related and primarily socially related that affect health. That’s why folks have kind of shied away from this, because it takes a lot more resources. And John, to be frank, it’s much more challenging. And what makes it so challenging is that, do folks who are frontline clinicians, like doctors, nurse practitioners, physician assistants, do they feel like they’re equipped enough to be able to deal with things that are social determinants as opposed to managing your congestive heart failure, or your COPD, or one of those things?
John Farkas:
Yeah, with a member of the more predictable population. Yeah, that’s a-
Dr. Ramon Jacobs-Shaw:
Right.
John Farkas:
So-
Dr. Ramon Jacobs-Shaw:
Listen, when we were going through school and our learning and our training, the focus was on the workflows and clinical guidelines and best evidence to address some of these conditions, be it medical or behavioral. But where was the training when we were going through school and residency on addressing some of these social determinants? And the answer is not much, if any.
How the Culture of Healthcare Systems Impacts Consumer Transformation
John Farkas:
Yeah. We’re talking a little bit about this. One of the questions I had, I’d love to hear you guys talk about how do you see the culture of a healthcare system and how it impacts and empowers consumer transformation to reach underserved populations? How’s that equation add up, and what are you seeing move in today’s world that is maybe pushing some in that direction?
Dr. Ramon Jacobs-Shaw:
Mac, you want to take a first stab?
Mac Davis:
Yeah. I mean, I think there’s a couple things that are pushing people to care more for these populations. One, I think people are starting to realize that the economic models that are underlying how you support these populations are beginning to change, and people are starting to purposely design models to basically enable and put the resources that are needed in excess of what was traditionally built around a medical only environment to do that. And so, I think that’s the first piece.
The second is, people have gotten better at being able to identify and collect and track the data to be able to enable more effective interventions. And frankly, it’s the idea that for a while we didn’t even know what interventions were effective. So you basically had to run… Every health plan in the country was running test cases where they were essentially saying, “I’ve got money. I’m going to put it into this intervention and I’m going to study to see if it works,” with no real idea if it was going to have an ROI or not. And now I think we’re past that, where we know, hey, the ROI is good if we can implement these programs really well. And now we need a sustainable funding source enable to achieve that ROI at scale.
And so, I think it’s just the general conversation of how it’s developed from this kind of tertiary thing on the sidelines to now it’s something that people have experimented enough to know that it’s somewhat proven. But now we’re learning how do we scale it and how do we do it more effectively so that we’re getting the best ROI we can from each of these interventions.
John Farkas:
Yeah. Ramon, given your backdrop in working with health systems, how have organizations approached integrating data, like Mac is talking about there, from different sources with the HR? And how has that historically impacted who’s eligible to receive care, and where’s that moving?
Dr. Ramon Jacobs-Shaw:
Such a great question, John. Do I think that health systems have done the best job at integrating data?
John Farkas:
I think I might know your answer to that question.
Dr. Ramon Jacobs-Shaw:
Can we poll the subscribers out there, the viewers who are listening to this? I don’t think that that’s been… Listen, hindsight is always 20-
John Farkas:
Not a strong suit.
Dr. Ramon Jacobs-Shaw:
… is always 20/20, right? I think what we know now is that, having access to the most integrated data to paint a more comprehensive picture of the patient that’s standing in front of us, if I’m a hospital, if I’m a primary care physician, that’s the ideal, right? That’s the dream, that’s the goal. And I think we know now that the more pieces that we have to the puzzle of a person, the better that the next person can take care of that patient. If Dr. Ramon here is seeing this member, this patient, and I’m doing my work, I want to know that I can have as much access to information as I can so that I can be as effective as I can be at delivering the best care I can to that patient that’s standing in front of me. And all of my clinician peers out there wants to be able to do that.
I think what we know now is that, yes, that’s what we need and we definitely have room to go on that. And I think that health systems are now very much aware, and I’m understating this, but very much aware that if we have more pieces to the puzzle ourselves, how can this help us and equip our people within our health system to take care of that patient that’s in the emergency room, or showing up into urgent care, or showing up into our primary care network so that we can make sure that we’re delivering the best care to that patient as possible. So I think that now there’s more alignment between everybody: health systems, plans, payers, as well as what our members and our patients out there want. They want people to know as much about them as possible, ideally without having to recreate the wheel with every interaction with the healthcare system as possible.
Mac Davis:
Yeah. I think-
John Farkas:
Yeah. Mac, can you put some wheels on that a little bit? What have you seen employed to help some of that happen? What are some of the strategies and ways that you’ve been able to prioritize relevant data points that can actually make a dent?
Mac Davis:
Yeah. I mean, I think there’s a couple pieces on the front side. I think it’s really about making sure that you’re holding… making as much of the data as real time as possible to the interventions that you have. So if I’ve got interventions that require data right now, I need to make sure that my infrastructure is set up to actually support that.
On the backside, there’s a significant number of interventions we can have with retrospective data too. Things like provider behavior change, et cetera. You don’t necessarily need to do those in the moment, you can try to affect activity moving forward. One of the larger challenges has been how do people take data from vastly different data sources with different contexts and try to provide those insights to a clinician or to a care manager, et cetera, in a way that consolidates the view without polluting the waters, essentially.
For a while, people always argued, well, do you have EMR data, or do you have claims data? And clinicians and health systems would always say, “Oh, EMR data is always better.” Well, the accuracy of that EMR data is relevant partially to the time and place it was created within that encounter, in the same way that the claims data downstream is valuable for other certain use cases. But in order to develop that bigger picture that Ramon’s talking about, I need both. And I need to be able to display that and combine that data to display to Ramon or others in a way that provides that complete picture without polluting or cross contaminating the purpose that that data is used for in the health system. Clinicians like EMR data because it’s built to document treatment. They think of claims as administrative data that’s created later. But really, there are areas of it that are very accurate summarizations of top level events, and so you can use that effectively essentially across the care continuum.
But you have to be careful. You don’t want to take claims data that’s been generated from EMR data and reverse engineer it into clinical data for broad sets of use cases. You have to be specific. And I think the industry has finally come to the realization that that’s… The VA has actually done that for a very long time, but broadly, and there were some challenges with that. And now I think the rest of the industry-
John Farkas:
And they have a lot more control over their data in that context.
Mac Davis:
Arguably. Not entirely. They’re getting better. I think they’d be the first to tell you they’ve got a fairly distributed network that they then try to centralize and standardize. But it’s a large challenge, because there are so many VA facilities across the country and so many people moving in and out of active duty over the last 25 years. So they led probably the charge in trying to convert that claims data into clinical data compared to others. But now I think we’re starting to see people do that more broadly but also more specifically. They’re doing it more often, but they’re doing it for specific use cases. And I think that’s where organizations and tech companies that are starting today need to have the flexibility to move across those multiple types of data that their customers are getting in order to inform how they’re surfacing insights to drive those actions. Because I want to be driving the actions no matter what the data source is. I don’t need to be married to one or the other, at least in the environment that we live in at Belong.
Leveraging Technology to Address Care Gaps for Underserved Populations
John Farkas:
Yeah. I mean, when we’re talking about closing gaps in care for underserved populations, I mean, the social determinant equation is obviously a critical one. And so, as we’re looking at things like economic and environmental factors as they are pulling into how they’re having an effect on patient health, how are we looking at addressing that? I mean, what are some of the practical ways that we’re… And I know this is a lot of what you guys are addressing. How are you going to leverage technology to bring that picture together?
Mac Davis:
Yeah.
Dr. Ramon Jacobs-Shaw:
Listen, I think that… Hey, Mac, I’ll take a stab at it and then you jump in there. How about that? Before we can deliver an action, we first off have to know what needs to be actioned. And I think one of the huge opportunities here is in data and gathering data about the populations that we serve, and doing it in a thoughtful, comprehensive as possible way. And I say that, for example, that there’s an opportunity here to really dive deep and get to know our populations, our membership, our patients more than ever. And one of the partners we’re working with right now is doing a really impressive dive into this work, specifically focused on health equity. And part of the challenge there that’s been recognized by them, certainly recognized by a lot of folks, is that we need to know what the issues are with our patients, with our members, so that we can really drive something actionable. And the people that can do that on such a really wonderful way, are those folks that are the regional community-based health plans, right? They’re embedded in the neighborhoods and communities. They know their membership the absolute best.
But we have to be thoughtful about knowing our people, and one of those ways is, how do we get structured, standardized data? How do we know the people that need access to more food resources, for example, for those who are suffering food insecurity? We’re in a high inflationary environment right now, so a lot of people out there, patients or members, everybody of all ages, are really experiencing some of that. But how do you know the folks who are the most vulnerable of your populations and what they’re experiencing if you don’t have the data to really help service those insights so you then know how to go action it? That’s one of the main things, I think, is making sure you know who your people are, your patients, your members, so that you can think about what actions can I do to do something for that group? And it all starts with that.
Mac, I don’t know if you have something different than that.
Mac Davis:
No, I think that’s really, really solid. The one thing I’d add is, people don’t think about social determinants of health data being radioactive. Like homelessness, right? It’s good right now, but someone could be housing insecure today and not in two months. Or they could be fine today, but not in two months. When you’re thinking about, whether it’s Belong… at least for us, as long as it’s… if it’s Belong Medical Group, or if it’s Belong’s care management on our payer side, the thing we care about most is that we’re collecting data about members at specific points in our workflow and our annual member journey to make sure that we’re getting updated views of these social determinants in a very purposeful way. And then, as Ramon mentioned, standardizing it back no matter what our collection method is. Whether it’s an HRA, or whether it’s their annual physical, or whether it’s an in-home visit, or whether it’s a call with one of our psychiatrists at post-discharge from a hospital.
Our goal is make sure that we’re capturing this information and then you’ve got the actions built upon it. But make sure you’re continually looking to collect information about your members and get status updates. I think that the biggest challenges with many social determinants where there’s a really impactful intervention with a high ROI, are the things that can change in a minute.
John Farkas:
Because what we’re talking about is pushing farther and farther into stuff that resides outside of the episode of care, right? I mean, it’s getting more and more understanding of the broader picture. We’re looking at related programs like diet and exercise and how it pertains to medication adherence and blood pressure and updates on blood sugar. And then we push into mental health, which is a whole other set of variables that are outside of, we’ll call it, the comfort zone or the well trodden trails that we have in the context of EHR. What are some of the fundamentals in what needs to change in that approach to data? How are we going to pull that stuff together into a picture that is going to make meaning in ways that is going to move the needle?
Mac Davis:
Yeah. I mean, I think there are a couple things that we’re doing. The first is we’re really focused around whole person-centered care. We talk about getting outside the episode. Episodic care. It’s important to be good during an episode, but to be honest, there’s only 40 to 60% of actual healthcare that’s delivered in the US can you shove into-
John Farkas:
In that box.
Mac Davis:
… into an episodic box. What do you do with the other care that providers are doing day in and day out? Whether it’s provider profiling and saying which doctors are the best, highest performing I want to send my members to, or whether it’s the actual care that we’re looking to provide members and measure the effectiveness of each member, episodic views are just an incomplete view across the board. They served a purpose in helping the country move along the value-based care journey, but I think we’re trying to focus on the recentralization of risk for our members and the centralization of services to our members around this whole person model. Both by making sure the financial incentive is there, and then making sure that our care model is supportive of the whole person, and then, hey, that means our data model needs to be too.
I think most people at this point probably have more comprehensive data models that they’ve built out in their solutions to support that, but I think for us it’s kind of entry criteria. It’s the first gate someone passes. Can we extend the data model to support this because we know it’s going to continue evolving? Or is it very rigid and it’s not something that’s going to flex to our needs and, frankly, the market’s needs moving forward?
John Farkas:
Mm-hmm. Ramon, do you have some examples of cases where data integration and analysis of really where you’ve seen it very directly lead to improvements in patient care? And what are some of things-
Dr. Ramon Jacobs-Shaw:
Absolutely. John, I got a-
John Farkas:
I thought you might.
Dr. Ramon Jacobs-Shaw:
I got a couple right off the top of my head. One of the things that we’ve been working on is, as a part of the work that we do, we have interdisciplinary care team meetings. This is the clinical team. This is our nurse care managers, our social workers, our community health workers, our care coordinators, our pharmacist and our physician, which is myself in this particular team, and what we do is we discuss our members. We discuss folks who have had health risk assessments that have come in with new conditions identified. We’ve had folks who have had a major event, a major change in their health condition, physical or mental. We’ve had people who’ve had transitions of care, so they’ve come out of hospitals, emergency rooms, skilled nursing facilities, and we need to kind of wrap them, envelope them in our care team and what we’re able to do for them.
In those discussions, we have access to so many different data points for our members, sitting in the seat that we’re in. In order to inform… Say, for example, one of our nurse care managers is coming to today’s ICT meeting. But in order to prepare to discuss that patient, they will have spent a lot of time, let’s just say, pulling from different data sources in order to prepare for that discussion. And what Mac and team have done is actually significantly reduced that amount of time by pulling information automatically from these different sources where we have access to information, and pulling that into a template for each individual member. Not just the whole population we’re talking about, each individual member.
We can pull that information in and say, “Okay. Mrs. Gonzalez. We’re talking about her today.” And I’m anonymizing, by the way. We’re talking about Mrs. Gonzales right now. And Mrs. Gonzalez has diabetes, she has hypertension, she has heart failure. And we’re looking at the list of medications that are coming over from our PBM, for example, with our partner, and we’re able to see, hey, we can check the EMR data access, or that last lab data, and say her diabetes is not that well controlled. And oh, look, her blood pressure is riding higher than normal in her last multiple visits with the primary care. Oh, and by the way, she’s morbidly obese. What’s the best treatment for her? And maybe the medications that are listed for her currently are not what’s optimal right now, because the guidelines shift and change for care. And I don’t know, John, if you thought you were going to get away from a podcast without mentioning things like Ozempic and Mounjaro and all of that stuff. The GLP-1s. But there are more treatments now that can affect not just the diabetes, but the outcome of what that diabetes affects, like heart disease, like risk of stroke, risk of other cardiovascular events.
And so having this data pulled into a place where we can review, discuss as a team, and then have that member, by the way, Mrs. Gonzalez, join that call and have this discussion with her while we’ve had access to all of this data there, that this data isn’t just sitting out there randomly, this is being pulled, having a discussion and impacting Mrs. Gonzalez, all happening all in the same setting. This is happening constantly with the way that we’re driving care here at Belong, so that’s just one example.
Mac Davis:
Yeah. And I think with that example, when I hear it from the tech side, it’s like, “Oh, you’re shoving a bunch of data sources into one.” And I think that’s been something that people have done for a long time, but what we’re doing that’s probably a little bit different is we’re basically contextualizing those data sources and helping our care team leap over the cognitive stepping stones that you have to get to take from information to action. And so, the goal isn’t to say, “Here’s just a bunch of raw data.” It’s to be able to summarize it in a way that identifies the problem across a variety of different data sources and contexts. That involves sometimes using AI, sometimes using traditional data engineering to accomplish those tasks and to be able to, frankly, do it at scale and whenever anyone on Ramon’s team wants it.
This at demand capability of summarizing vast amounts of data, I think AI has been a big help, but in some cases it’s not always the right tool set. We’re looking to apply those tool sets to help make sure that Ramon’s team isn’t spending time interpreting data, but is really spending time acting on data.
John Farkas:
Yeah, that’s definitely a good delineation there, because I think that it is so critical, as we are… And I work hard, I know, with our clients as they are interacting with the data. Many of our clients have incredible access or create large data sets. And the ability to approach that with how can we use and leverage that data to leverage or to inform other use cases or other elements within the systems and healthcare, that interoperative component ends up being so critical and is so often… I won’t say overlooked, but undervalued for sure in how I see people approaching it. I’m guessing that those are some of the bridges that you guys are helping to cross in that, is how are we going to pull that through into a place where it’s going to actually make a difference in the lives of human beings that need it. That’s super critical.
Ramon, from your past experience, if you could share a piece of advice with a health tech company from your clinical seat; and I know that this is stuff you’re applying now at Belong, but from back in your days in the clinical seat in a healthcare environment, what advice would you have for health tech companies that are trying to make their way in, that are trying to show their value to an organization? What are some pet peeves that you’ve-
Dr. Ramon Jacobs-Shaw:
How much time you got, John?
John Farkas:
Yeah.
Dr. Ramon Jacobs-Shaw:
How much time you got?
Frustrations and Shortcomings within the HealthTech Sector
John Farkas:
What are some pet peeves that you experienced? Yeah. Well, we’ve got some time. I wanted to leave some time for this question.
Dr. Ramon Jacobs-Shaw:
Listen, I’ll be brief. I think oftentimes what can certainly be missing out there is the individual person, the individual patient perspective. That’s what a person like myself, as the chief clinical officer at Belong, is to bring, given my experience with taking care of patients all over. I mean, I’ve been a hospital-based doctor, I’ve taken care of folks in their home, in skilled nursing facilities, and am a primary care physician. And so, I’ve been able to meet our patients where they are to deliver that care.
Our patients want to be listened to. And as I mentioned at the top of the hour, the dual eligible population, for example, has specifically been marginalized and looked past and overlooked. People just want to know that their voice is being heard, that their concerns are being heard.
I think for health tech companies specifically, I think I saw this on a LinkedIn post at some point this year. Someone made the point of, if you don’t have a clinical eye sitting in the seats where these discussions and these decisions are being made, then you’re just a tech company in healthcare. And so, I think it’s important to have the clinical voice be present in the rooms when discussions are being made about patients, about what we’re doing with people out there that are touching healthcare, some more frequently than others. And that clinical voice to be able to say, “Here’s what my patients actually feel,” versus what you think they might be feeling. That makes a huge difference. That’s just one.
John Farkas:
I’ve heard that from a number of… A lot of who we are talking to are healthcare executives, and what I hear very frequently when somebody’s coming to them with a technology solution is, “Okay, where’s your clinician? Where’s the person in the room that actually knows what I’m dealing with here? Because if I don’t see that, or you guys aren’t regarding that high enough to have somebody in this conversation coming from a informed clinical perspective, we’ve got a problem. There’s going to be a miss here.” And I think that anytime we’re touching real people in the context of their healthcare journey, having a really clearly informed… It’s not just about the tech, right? It’s about the people that are benefiting from the tech and what really needs to happen for that benefit to occur. We can imagine that when we’re developing software, but there has to be a real clear line to the actual clinical use case, real world scenario, understanding what happens in the pressure cooker. That has to be a big part of that.
How do you guys approach that as you are looking at the development of your products and how you’re connecting those to the market?
Mac Davis:
Yeah. I mean, there’s a couple things that were specifically… At least on the tech side, our developers are, I would say, very highly trained on what the workflows actually are. And then we empower our developers and analysts and others to essentially learn the operational role of those that they’re looking to support. I think one of the challenges is people thinking of their development shops as forward factories, assembly line factories for healthcare development, and that’s not how it works. Most of the solutions that take that approach have a harder time breaking into healthcare, because the people that are building the solutions aren’t contributing to how to solve the problem in the most efficient way. I mean, they’re either not in a position to, or they don’t have the knowledge from their business partners to do it.
I think we work very hard on breaking down those silos and making sure that our developers really understand why they’re developing what they’re developing, and how they’re developing. Why is the how the way that it is? And that’s something that I don’t think is super broad across many startups in the early days, so I would encourage everyone to say… We don’t just have developers. Your developers are an extension of your product team and your product team are an extension of your developers, and your clinicians should be an extension of both as well. Putting people in silos does not tend to work in healthcare like it can if I’m developing a fintech product or a marketing tech product.
John Farkas:
Yeah. Ramon, how do you see your role in that equation?
Dr. Ramon Jacobs-Shaw:
Gosh, almost like a translator. Is that a good way to put it, Mac?
Mac Davis:
Yeah.
Dr. Ramon Jacobs-Shaw:
Almost as like a translator.
Mac Davis:
I was going to say, sometimes it’s like a special ed teacher and translator. I mean, it’s the same thing. Sometimes you’re providing healthcare 101 lesson, or Ramon is providing healthcare 101 lessons, and sometimes he’s going really, really deep into the minute differences between two clinical codes. And those differences do matter at the very minute level, but also at the top line, 101 process level. Clinicians have to be good at going deep into the weeds and pulling up and knowing this is where… I think that’s where, frankly, we got lucky with Ramon and some of our other clinicians, is that they can do that. That’s also not a common skillset in clinicians, to be able to go really deep into the annals of coding or how a process really works and then pull up and to be able to say, “But the most important things to remember from a process standpoint are A, B, and C.” Because developers need the detail and they need the high level view to help center them on what’s important.
Dr. Ramon Jacobs-Shaw:
John, this is bidirectional too. As much as I’m an interpreter for this as well, my data and analytics colleagues here are doing the same thing and teaching me tons as well. Just that kind of experience and collaboration over the years informs being able to sit in the seat that I’m able to sit in and for Mac to be able to sit in as well. It’s that collective, but it’s bidirectional. We’re learning from each other and then innovating and revising and thinking about the next thing that we’re going to do and all of that stuff. It really is a partnership. It’s tons of teamwork here in order to make that happen. Silos don’t exist here.
Mac Davis:
Yeah. I think that partnership piece, I’ll just… I’ve worked with and seen organizations that have worked with very rigid clinicians that say, “This is the only way to do things,” and that typically does not get people the best result. The same thing on the tech side where they say, “This is the only way of doing it.” The answer usually is that there’s a middle ground that’s actually the best, and so both sides have to keep open ears and sometimes close mouths, which obviously Ramon wants me to do more since I’ve been talking a lot on this podcast.
Dr. Ramon Jacobs-Shaw:
No way. No way. No way. You’ve got way too much experience to not be able to share with this audience.
Closing Thoughts
John Farkas:
Well, guys, I am excited about what you’re doing in the context of Belong. As we’re thinking about closing gaps of care and how we can better make meaning and bring great service to underserved populations in our world, it’s obviously a huge need. And I know that technology and… Because, A, we don’t have enough clinicians to meet the need and that problem is not going to get easier in the next several years, it’s just going to continue to be a big challenge, technology has to play an important role in helping us be increasingly strategic and better pointed in the efforts that we have. So I’m grateful for the work that you’re doing and I think it’s obviously really important, and excited to continue to watch the story as things unfold in your world. Thanks for joining us today in this context. Any final thoughts or things that would be good to underscore as we conclude here?
Mac Davis:
I’ll give a plug for the health tech companies out there to focus on how… When you’re building algorithms or items that are looking to automate practices, make clinicians time go further, or be more effective, don’t forget about thinking about how do I inject compassion into my workflow or into this model so that you’re not automating some of the problems that I think we all face when we’re interacting with the health systems as patients ourselves. No one likes a decision to be made in the background without knowing why our care is being affected one way or another.
I think we see a lot of that with prior authorizations and denials. It’s very heavily in the news for payers today. That’s a great example where algorithms are used to make decisions and those decisions are not always explained to members in a timely or effective way. And so, we as an industry in health tech and analytics and data have to get better at making sure that we’re delivering those messages in as compassionate a way as possible. Because that’s the only way you’re going to convince somebody to either make a behavior change, or to help steer their own healthcare journey in a more effective way.
John Farkas:
Yeah, that’s a great word for sure. Ramon, anything from your perspective?
Dr. Ramon Jacobs-Shaw:
My plug would be, listen, for the health tech companies out there that are looking to do more, to do better, to do something deeper in the work that they’re doing, seeking out places like Healthcare Matrix to learn about what other people are doing. And listening to Belong Health Story, for example, just to get an idea of just what some of the possibilities are. We’re just touching the surface here. The goal is to go deeper into what we’re doing here.
John Farkas:
Yeah. The possibilities are pretty remarkable, and technology is going to be a really critical role. I mean, it just is. There’s so much coming forward. And when I hear Mac talking about the importance of interjecting compassion, when we’re dealing with clinicians who are so extremely pressed, and anything we can do to help relieve that burden, that might help have an opportunity to humanize care, where they’re able to focus more on delivering the kind of interactions that they want to be able to deliver; that’s obviously an important part of the mission here. And I know that that’s a lot of what you guys are endeavoring to do in helping people that really have a challenge in navigating what they’re up against in getting good care. To be able to be seen and to be understood and to be well cared for; super important. And so-
Dr. Ramon Jacobs-Shaw:
Absolutely.
John Farkas:
… great [inaudible 00:50:07]
Dr. Ramon Jacobs-Shaw:
That’s what we all want, John, right?
John Farkas:
That’s right.
Dr. Ramon Jacobs-Shaw:
To be seen and to be heard.
John Farkas:
It’s a critical part, especially when our health is on the line.
Dr. Ramon Jacobs-Shaw:
Absolutely.
John Farkas:
Mac, Ramon, thank you guys so much for joining us today, and best to you as you continue the journey with Belong Health, and grateful for your investment here with our audience.
Dr. Ramon Jacobs-Shaw:
Happy to be here. Thanks so much.
John Farkas:
Thank you.
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Transcript (custom)
Introducing Mac Davis and Dr. Ramon Jacobs-Shaw
John Farkas:
Hey everybody, and welcome to Healthcare Market Matrix. I’m your host, John Farkas, and today I’m joined by two remarkable people who are helping lead into the horizon of healthcare transformation. Mac Davis and Dr. Ramon Jacobs-Shaw are joining us from Belong Health. And Belong is working to expand the availability and improve the delivery of healthcare benefits to Medicare eligible people across the country with a special focus on special needs populations. And they’re partnering with regional health plans to bring a whole person model of care to patients who really need it the most. We’re talking medical, behavioral health, substance abuse, and social services coordination. Their platform is supporting the clinicians and the patients and the health plan teams that are working to serve those really complex and challenging populations.
As you guys know here on Healthcare Market Matrix, we’re exploring how technology companies can enhance their market presence to address the industry’s pressing challenges. And so today, in this episode, we get to play both sides of the equation. Ramon’s firsthand experience with the healthcare system as a chief clinical officer, and Mac’s perspective on working to advance data interoperability, are going to really work together to provide some really good insight, especially as we are considering solutions that serve those folks who are working to help underserved patient populations. So Ramon and Mac, welcome to Healthcare Market Matrix.
Mac Davis:
Thanks, John, for having us.
Dr. Ramon Jacobs-Shaw:
John, thanks so much. Happy to be here.
John Farkas:
Great. Let’s begin and dive in to learning more a little bit about what brought you into the place you are now. Mac, let’s start with you. What got you to this point?
Mac Davis:
Yeah. Like many people, I think, in health tech, I was hired by one of the large EMR companies out of undergrad and really cut my teeth on what good looks like. Working for a variety of analytics firms, including a startup that we then sold to Cotiviti, where I managed a variety of solutions and was able to cut my teeth in the payer side as well as the provider side. So my goal has largely been to make sure that we’re delivering solutions to both payers and providers that are driving efficiencies that are ultimately helping our members and patients at the end of the day. And so, a lot of my goal at Belong is to focus on how do we build products or deploy products that are helping us make that impact day in, day out, and enabling Ramon and his team to be the best that they can be.
John Farkas:
Awesome. When did you start in the HR world? How long ago was that now?
Mac Davis:
Oh, about 12 years ago.
John Farkas:
And this is throwing you on the spot a little bit here, but if you were to characterize what some of the major shifts that you’ve seen from the time… because I know there’s been a lot of movement in how that space is addressed. But when we’re talking especially around interoperability, what would you say has been some of the biggest moves that you’ve seen in that space and time?
Mac Davis:
Yeah. I mean, I think there’s been probably a couple of shifts explicitly. One, I think standards have become more standard. There’ve always been standards, but the ability of the ecosystem of vendors to actually execute well against those standards has had a lot of variation and that’s starting to close down. I think people have always argued about this standard or that standard when the reality is that vendors just need to conform to them, and I think we’ve started to see that with the industry coalescing around TEFCA and the next generation of interoperability.
But I think the other piece is the expansion of these core admin systems to include a larger scope. The more integrated and native capabilities that are within these core operating systems on the provider side, the better. I don’t think we’ve seen that same success rate on the payer side as much. So on the payer side, there isn’t a core operating system for a health plan the same way that there’s a core operating system that covers patient accounting, practice management, inpatient, outpatient that we see with the Epics or Oracle Cerners of the world that can perform a huge portion of the overall functions of the hospital with one core workflow tool.
So I think those would probably be two of the big pieces, and then I think the third would just be the expansion of what we think of as healthcare. A lot of these systems and tools were very much a let’s figure out how we take care of members-
John Farkas:
Hospital centric?
Mac Davis:
Yeah. How do we take care of these members within the four walls of this room? And now it’s about how do we take care of these members outside of these four walls, and then how do the systems evolve in order to account for that.
John Farkas:
Yeah, very cool. And yeah, I think that there’s definitely… it’s going to be an interesting even the next two years, seeing how those systems are going to move to incorporate broader and broader swaths of the operations. It’s interesting days for people in the healthcare technology realm, that’s for sure, as we watch a lot of the-
Dr. Ramon Jacobs-Shaw:
That’s an understatement, John. Understatement.
John Farkas:
Which folks listening to this are very well acquainted with. There’s a lot of waiting and seeing going on right now, and a lot of that has a lot of anxiety related to it, I think, on a number of fronts. But Ramon, how about you? Give us a little bit of your backdrop?
Dr. Ramon Jacobs-Shaw:
Yeah, absolutely. You summed up Belong Health and what we do so very well. Our focus is on those vulnerable populations. And listen, John, I come from a vulnerable population myself, and so growing up with less than ideal access to healthcare was definitely something that I was very much familiar with, and so can certainly relate to people, our members, our patients out there who don’t have the best access to healthcare. That for me was the trigger to go into medicine myself.
Yeah, I trained as both an internist and a pediatrician, and I’ve worked in health systems. I’ve worked in large academic medical centers and transitioned that work into organizations like CareMore Health, which is based out of southern California, where I worked as a regional medical officer and oversaw the largest market in the country; focusing on that Medicare population as well as the dual eligible population specifically.
And then took that work into a place like Oak Street Health where I helped to launch the New York market as the senior medical director. And for those of your subscribers that may not know Oak Street, Oak Street is an organization focused on primary care for the Medicare eligible population. That includes not only Medicare folks, but also dual eligibles. That’s where my life’s work has been.
And what resonated with me about Belong and joining Belong is that that mission and vision to focus on a population, the dual eligible population specifically, that has always been… I’ve always used the term overlooked and looked past by everyone in the system. Whether it’s health systems, providers, plans, you name it, people have kind of run away from the D-SNP population. And trust me, the dual eligible folks out there have certainly felt that, and so Belong has come along in order to really fill that gap, to bring the absolute best in care that we can via our platforms, our data, our analytics, our clinical solutions, in order to really take care of them. So that vulnerable population focus has been what has driven me throughout my career and certainly is what brought me to Belong.
John Farkas:
So let’s just stick the why behind the what a little bit. You said the organizations are running away from that population. Why is that? What’s the anatomy behind that problem and what’s caused that to be in place?
Dr. Ramon Jacobs-Shaw:
Yeah. By virtue of being a vulnerable population, they’ve been marginalized. And I think the thinking… not I think, I know the thinking has been that the folks who are dual eligible are sicker than your average population. Certainly sicker than your Medicare fee for service, certainly sicker than a person on Medicaid. So we know that they come with more chronic conditions, chronic medical conditions. We know that the rates of behavioral health, specifically mental health conditions, are more in this dual eligible population. We know that there are vulnerabilities when it comes to social determinants of health. And thinking about not just access to care, but some of these other social determinants. Think about transportation, think about housing security, food security; so many elements that affect someone’s health that in traditional healthcare have not been viewed as healthcare.
And so, we know with these multitude of conditions, of issues, there are more resources that need to be brought to bear in order to really address those needs, both primarily health related and primarily socially related that affect health. That’s why folks have kind of shied away from this, because it takes a lot more resources. And John, to be frank, it’s much more challenging. And what makes it so challenging is that, do folks who are frontline clinicians, like doctors, nurse practitioners, physician assistants, do they feel like they’re equipped enough to be able to deal with things that are social determinants as opposed to managing your congestive heart failure, or your COPD, or one of those things?
John Farkas:
Yeah, with a member of the more predictable population. Yeah, that’s a-
Dr. Ramon Jacobs-Shaw:
Right.
John Farkas:
So-
Dr. Ramon Jacobs-Shaw:
Listen, when we were going through school and our learning and our training, the focus was on the workflows and clinical guidelines and best evidence to address some of these conditions, be it medical or behavioral. But where was the training when we were going through school and residency on addressing some of these social determinants? And the answer is not much, if any.
How the Culture of Healthcare Systems Impacts Consumer Transformation
John Farkas:
Yeah. We’re talking a little bit about this. One of the questions I had, I’d love to hear you guys talk about how do you see the culture of a healthcare system and how it impacts and empowers consumer transformation to reach underserved populations? How’s that equation add up, and what are you seeing move in today’s world that is maybe pushing some in that direction?
Dr. Ramon Jacobs-Shaw:
Mac, you want to take a first stab?
Mac Davis:
Yeah. I mean, I think there’s a couple things that are pushing people to care more for these populations. One, I think people are starting to realize that the economic models that are underlying how you support these populations are beginning to change, and people are starting to purposely design models to basically enable and put the resources that are needed in excess of what was traditionally built around a medical only environment to do that. And so, I think that’s the first piece.
The second is, people have gotten better at being able to identify and collect and track the data to be able to enable more effective interventions. And frankly, it’s the idea that for a while we didn’t even know what interventions were effective. So you basically had to run… Every health plan in the country was running test cases where they were essentially saying, “I’ve got money. I’m going to put it into this intervention and I’m going to study to see if it works,” with no real idea if it was going to have an ROI or not. And now I think we’re past that, where we know, hey, the ROI is good if we can implement these programs really well. And now we need a sustainable funding source enable to achieve that ROI at scale.
And so, I think it’s just the general conversation of how it’s developed from this kind of tertiary thing on the sidelines to now it’s something that people have experimented enough to know that it’s somewhat proven. But now we’re learning how do we scale it and how do we do it more effectively so that we’re getting the best ROI we can from each of these interventions.
John Farkas:
Yeah. Ramon, given your backdrop in working with health systems, how have organizations approached integrating data, like Mac is talking about there, from different sources with the HR? And how has that historically impacted who’s eligible to receive care, and where’s that moving?
Dr. Ramon Jacobs-Shaw:
Such a great question, John. Do I think that health systems have done the best job at integrating data?
John Farkas:
I think I might know your answer to that question.
Dr. Ramon Jacobs-Shaw:
Can we poll the subscribers out there, the viewers who are listening to this? I don’t think that that’s been… Listen, hindsight is always 20-
John Farkas:
Not a strong suit.
Dr. Ramon Jacobs-Shaw:
… is always 20/20, right? I think what we know now is that, having access to the most integrated data to paint a more comprehensive picture of the patient that’s standing in front of us, if I’m a hospital, if I’m a primary care physician, that’s the ideal, right? That’s the dream, that’s the goal. And I think we know now that the more pieces that we have to the puzzle of a person, the better that the next person can take care of that patient. If Dr. Ramon here is seeing this member, this patient, and I’m doing my work, I want to know that I can have as much access to information as I can so that I can be as effective as I can be at delivering the best care I can to that patient that’s standing in front of me. And all of my clinician peers out there wants to be able to do that.
I think what we know now is that, yes, that’s what we need and we definitely have room to go on that. And I think that health systems are now very much aware, and I’m understating this, but very much aware that if we have more pieces to the puzzle ourselves, how can this help us and equip our people within our health system to take care of that patient that’s in the emergency room, or showing up into urgent care, or showing up into our primary care network so that we can make sure that we’re delivering the best care to that patient as possible. So I think that now there’s more alignment between everybody: health systems, plans, payers, as well as what our members and our patients out there want. They want people to know as much about them as possible, ideally without having to recreate the wheel with every interaction with the healthcare system as possible.
Mac Davis:
Yeah. I think-
John Farkas:
Yeah. Mac, can you put some wheels on that a little bit? What have you seen employed to help some of that happen? What are some of the strategies and ways that you’ve been able to prioritize relevant data points that can actually make a dent?
Mac Davis:
Yeah. I mean, I think there’s a couple pieces on the front side. I think it’s really about making sure that you’re holding… making as much of the data as real time as possible to the interventions that you have. So if I’ve got interventions that require data right now, I need to make sure that my infrastructure is set up to actually support that.
On the backside, there’s a significant number of interventions we can have with retrospective data too. Things like provider behavior change, et cetera. You don’t necessarily need to do those in the moment, you can try to affect activity moving forward. One of the larger challenges has been how do people take data from vastly different data sources with different contexts and try to provide those insights to a clinician or to a care manager, et cetera, in a way that consolidates the view without polluting the waters, essentially.
For a while, people always argued, well, do you have EMR data, or do you have claims data? And clinicians and health systems would always say, “Oh, EMR data is always better.” Well, the accuracy of that EMR data is relevant partially to the time and place it was created within that encounter, in the same way that the claims data downstream is valuable for other certain use cases. But in order to develop that bigger picture that Ramon’s talking about, I need both. And I need to be able to display that and combine that data to display to Ramon or others in a way that provides that complete picture without polluting or cross contaminating the purpose that that data is used for in the health system. Clinicians like EMR data because it’s built to document treatment. They think of claims as administrative data that’s created later. But really, there are areas of it that are very accurate summarizations of top level events, and so you can use that effectively essentially across the care continuum.
But you have to be careful. You don’t want to take claims data that’s been generated from EMR data and reverse engineer it into clinical data for broad sets of use cases. You have to be specific. And I think the industry has finally come to the realization that that’s… The VA has actually done that for a very long time, but broadly, and there were some challenges with that. And now I think the rest of the industry-
John Farkas:
And they have a lot more control over their data in that context.
Mac Davis:
Arguably. Not entirely. They’re getting better. I think they’d be the first to tell you they’ve got a fairly distributed network that they then try to centralize and standardize. But it’s a large challenge, because there are so many VA facilities across the country and so many people moving in and out of active duty over the last 25 years. So they led probably the charge in trying to convert that claims data into clinical data compared to others. But now I think we’re starting to see people do that more broadly but also more specifically. They’re doing it more often, but they’re doing it for specific use cases. And I think that’s where organizations and tech companies that are starting today need to have the flexibility to move across those multiple types of data that their customers are getting in order to inform how they’re surfacing insights to drive those actions. Because I want to be driving the actions no matter what the data source is. I don’t need to be married to one or the other, at least in the environment that we live in at Belong.
Leveraging Technology to Address Care Gaps for Underserved Populations
John Farkas:
Yeah. I mean, when we’re talking about closing gaps in care for underserved populations, I mean, the social determinant equation is obviously a critical one. And so, as we’re looking at things like economic and environmental factors as they are pulling into how they’re having an effect on patient health, how are we looking at addressing that? I mean, what are some of the practical ways that we’re… And I know this is a lot of what you guys are addressing. How are you going to leverage technology to bring that picture together?
Mac Davis:
Yeah.
Dr. Ramon Jacobs-Shaw:
Listen, I think that… Hey, Mac, I’ll take a stab at it and then you jump in there. How about that? Before we can deliver an action, we first off have to know what needs to be actioned. And I think one of the huge opportunities here is in data and gathering data about the populations that we serve, and doing it in a thoughtful, comprehensive as possible way. And I say that, for example, that there’s an opportunity here to really dive deep and get to know our populations, our membership, our patients more than ever. And one of the partners we’re working with right now is doing a really impressive dive into this work, specifically focused on health equity. And part of the challenge there that’s been recognized by them, certainly recognized by a lot of folks, is that we need to know what the issues are with our patients, with our members, so that we can really drive something actionable. And the people that can do that on such a really wonderful way, are those folks that are the regional community-based health plans, right? They’re embedded in the neighborhoods and communities. They know their membership the absolute best.
But we have to be thoughtful about knowing our people, and one of those ways is, how do we get structured, standardized data? How do we know the people that need access to more food resources, for example, for those who are suffering food insecurity? We’re in a high inflationary environment right now, so a lot of people out there, patients or members, everybody of all ages, are really experiencing some of that. But how do you know the folks who are the most vulnerable of your populations and what they’re experiencing if you don’t have the data to really help service those insights so you then know how to go action it? That’s one of the main things, I think, is making sure you know who your people are, your patients, your members, so that you can think about what actions can I do to do something for that group? And it all starts with that.
Mac, I don’t know if you have something different than that.
Mac Davis:
No, I think that’s really, really solid. The one thing I’d add is, people don’t think about social determinants of health data being radioactive. Like homelessness, right? It’s good right now, but someone could be housing insecure today and not in two months. Or they could be fine today, but not in two months. When you’re thinking about, whether it’s Belong… at least for us, as long as it’s… if it’s Belong Medical Group, or if it’s Belong’s care management on our payer side, the thing we care about most is that we’re collecting data about members at specific points in our workflow and our annual member journey to make sure that we’re getting updated views of these social determinants in a very purposeful way. And then, as Ramon mentioned, standardizing it back no matter what our collection method is. Whether it’s an HRA, or whether it’s their annual physical, or whether it’s an in-home visit, or whether it’s a call with one of our psychiatrists at post-discharge from a hospital.
Our goal is make sure that we’re capturing this information and then you’ve got the actions built upon it. But make sure you’re continually looking to collect information about your members and get status updates. I think that the biggest challenges with many social determinants where there’s a really impactful intervention with a high ROI, are the things that can change in a minute.
John Farkas:
Because what we’re talking about is pushing farther and farther into stuff that resides outside of the episode of care, right? I mean, it’s getting more and more understanding of the broader picture. We’re looking at related programs like diet and exercise and how it pertains to medication adherence and blood pressure and updates on blood sugar. And then we push into mental health, which is a whole other set of variables that are outside of, we’ll call it, the comfort zone or the well trodden trails that we have in the context of EHR. What are some of the fundamentals in what needs to change in that approach to data? How are we going to pull that stuff together into a picture that is going to make meaning in ways that is going to move the needle?
Mac Davis:
Yeah. I mean, I think there are a couple things that we’re doing. The first is we’re really focused around whole person-centered care. We talk about getting outside the episode. Episodic care. It’s important to be good during an episode, but to be honest, there’s only 40 to 60% of actual healthcare that’s delivered in the US can you shove into-
John Farkas:
In that box.
Mac Davis:
… into an episodic box. What do you do with the other care that providers are doing day in and day out? Whether it’s provider profiling and saying which doctors are the best, highest performing I want to send my members to, or whether it’s the actual care that we’re looking to provide members and measure the effectiveness of each member, episodic views are just an incomplete view across the board. They served a purpose in helping the country move along the value-based care journey, but I think we’re trying to focus on the recentralization of risk for our members and the centralization of services to our members around this whole person model. Both by making sure the financial incentive is there, and then making sure that our care model is supportive of the whole person, and then, hey, that means our data model needs to be too.
I think most people at this point probably have more comprehensive data models that they’ve built out in their solutions to support that, but I think for us it’s kind of entry criteria. It’s the first gate someone passes. Can we extend the data model to support this because we know it’s going to continue evolving? Or is it very rigid and it’s not something that’s going to flex to our needs and, frankly, the market’s needs moving forward?
John Farkas:
Mm-hmm. Ramon, do you have some examples of cases where data integration and analysis of really where you’ve seen it very directly lead to improvements in patient care? And what are some of things-
Dr. Ramon Jacobs-Shaw:
Absolutely. John, I got a-
John Farkas:
I thought you might.
Dr. Ramon Jacobs-Shaw:
I got a couple right off the top of my head. One of the things that we’ve been working on is, as a part of the work that we do, we have interdisciplinary care team meetings. This is the clinical team. This is our nurse care managers, our social workers, our community health workers, our care coordinators, our pharmacist and our physician, which is myself in this particular team, and what we do is we discuss our members. We discuss folks who have had health risk assessments that have come in with new conditions identified. We’ve had folks who have had a major event, a major change in their health condition, physical or mental. We’ve had people who’ve had transitions of care, so they’ve come out of hospitals, emergency rooms, skilled nursing facilities, and we need to kind of wrap them, envelope them in our care team and what we’re able to do for them.
In those discussions, we have access to so many different data points for our members, sitting in the seat that we’re in. In order to inform… Say, for example, one of our nurse care managers is coming to today’s ICT meeting. But in order to prepare to discuss that patient, they will have spent a lot of time, let’s just say, pulling from different data sources in order to prepare for that discussion. And what Mac and team have done is actually significantly reduced that amount of time by pulling information automatically from these different sources where we have access to information, and pulling that into a template for each individual member. Not just the whole population we’re talking about, each individual member.
We can pull that information in and say, “Okay. Mrs. Gonzalez. We’re talking about her today.” And I’m anonymizing, by the way. We’re talking about Mrs. Gonzales right now. And Mrs. Gonzalez has diabetes, she has hypertension, she has heart failure. And we’re looking at the list of medications that are coming over from our PBM, for example, with our partner, and we’re able to see, hey, we can check the EMR data access, or that last lab data, and say her diabetes is not that well controlled. And oh, look, her blood pressure is riding higher than normal in her last multiple visits with the primary care. Oh, and by the way, she’s morbidly obese. What’s the best treatment for her? And maybe the medications that are listed for her currently are not what’s optimal right now, because the guidelines shift and change for care. And I don’t know, John, if you thought you were going to get away from a podcast without mentioning things like Ozempic and Mounjaro and all of that stuff. The GLP-1s. But there are more treatments now that can affect not just the diabetes, but the outcome of what that diabetes affects, like heart disease, like risk of stroke, risk of other cardiovascular events.
And so having this data pulled into a place where we can review, discuss as a team, and then have that member, by the way, Mrs. Gonzalez, join that call and have this discussion with her while we’ve had access to all of this data there, that this data isn’t just sitting out there randomly, this is being pulled, having a discussion and impacting Mrs. Gonzalez, all happening all in the same setting. This is happening constantly with the way that we’re driving care here at Belong, so that’s just one example.
Mac Davis:
Yeah. And I think with that example, when I hear it from the tech side, it’s like, “Oh, you’re shoving a bunch of data sources into one.” And I think that’s been something that people have done for a long time, but what we’re doing that’s probably a little bit different is we’re basically contextualizing those data sources and helping our care team leap over the cognitive stepping stones that you have to get to take from information to action. And so, the goal isn’t to say, “Here’s just a bunch of raw data.” It’s to be able to summarize it in a way that identifies the problem across a variety of different data sources and contexts. That involves sometimes using AI, sometimes using traditional data engineering to accomplish those tasks and to be able to, frankly, do it at scale and whenever anyone on Ramon’s team wants it.
This at demand capability of summarizing vast amounts of data, I think AI has been a big help, but in some cases it’s not always the right tool set. We’re looking to apply those tool sets to help make sure that Ramon’s team isn’t spending time interpreting data, but is really spending time acting on data.
John Farkas:
Yeah, that’s definitely a good delineation there, because I think that it is so critical, as we are… And I work hard, I know, with our clients as they are interacting with the data. Many of our clients have incredible access or create large data sets. And the ability to approach that with how can we use and leverage that data to leverage or to inform other use cases or other elements within the systems and healthcare, that interoperative component ends up being so critical and is so often… I won’t say overlooked, but undervalued for sure in how I see people approaching it. I’m guessing that those are some of the bridges that you guys are helping to cross in that, is how are we going to pull that through into a place where it’s going to actually make a difference in the lives of human beings that need it. That’s super critical.
Ramon, from your past experience, if you could share a piece of advice with a health tech company from your clinical seat; and I know that this is stuff you’re applying now at Belong, but from back in your days in the clinical seat in a healthcare environment, what advice would you have for health tech companies that are trying to make their way in, that are trying to show their value to an organization? What are some pet peeves that you’ve-
Dr. Ramon Jacobs-Shaw:
How much time you got, John?
John Farkas:
Yeah.
Dr. Ramon Jacobs-Shaw:
How much time you got?
Frustrations and Shortcomings within the HealthTech Sector
John Farkas:
What are some pet peeves that you experienced? Yeah. Well, we’ve got some time. I wanted to leave some time for this question.
Dr. Ramon Jacobs-Shaw:
Listen, I’ll be brief. I think oftentimes what can certainly be missing out there is the individual person, the individual patient perspective. That’s what a person like myself, as the chief clinical officer at Belong, is to bring, given my experience with taking care of patients all over. I mean, I’ve been a hospital-based doctor, I’ve taken care of folks in their home, in skilled nursing facilities, and am a primary care physician. And so, I’ve been able to meet our patients where they are to deliver that care.
Our patients want to be listened to. And as I mentioned at the top of the hour, the dual eligible population, for example, has specifically been marginalized and looked past and overlooked. People just want to know that their voice is being heard, that their concerns are being heard.
I think for health tech companies specifically, I think I saw this on a LinkedIn post at some point this year. Someone made the point of, if you don’t have a clinical eye sitting in the seats where these discussions and these decisions are being made, then you’re just a tech company in healthcare. And so, I think it’s important to have the clinical voice be present in the rooms when discussions are being made about patients, about what we’re doing with people out there that are touching healthcare, some more frequently than others. And that clinical voice to be able to say, “Here’s what my patients actually feel,” versus what you think they might be feeling. That makes a huge difference. That’s just one.
John Farkas:
I’ve heard that from a number of… A lot of who we are talking to are healthcare executives, and what I hear very frequently when somebody’s coming to them with a technology solution is, “Okay, where’s your clinician? Where’s the person in the room that actually knows what I’m dealing with here? Because if I don’t see that, or you guys aren’t regarding that high enough to have somebody in this conversation coming from a informed clinical perspective, we’ve got a problem. There’s going to be a miss here.” And I think that anytime we’re touching real people in the context of their healthcare journey, having a really clearly informed… It’s not just about the tech, right? It’s about the people that are benefiting from the tech and what really needs to happen for that benefit to occur. We can imagine that when we’re developing software, but there has to be a real clear line to the actual clinical use case, real world scenario, understanding what happens in the pressure cooker. That has to be a big part of that.
How do you guys approach that as you are looking at the development of your products and how you’re connecting those to the market?
Mac Davis:
Yeah. I mean, there’s a couple things that were specifically… At least on the tech side, our developers are, I would say, very highly trained on what the workflows actually are. And then we empower our developers and analysts and others to essentially learn the operational role of those that they’re looking to support. I think one of the challenges is people thinking of their development shops as forward factories, assembly line factories for healthcare development, and that’s not how it works. Most of the solutions that take that approach have a harder time breaking into healthcare, because the people that are building the solutions aren’t contributing to how to solve the problem in the most efficient way. I mean, they’re either not in a position to, or they don’t have the knowledge from their business partners to do it.
I think we work very hard on breaking down those silos and making sure that our developers really understand why they’re developing what they’re developing, and how they’re developing. Why is the how the way that it is? And that’s something that I don’t think is super broad across many startups in the early days, so I would encourage everyone to say… We don’t just have developers. Your developers are an extension of your product team and your product team are an extension of your developers, and your clinicians should be an extension of both as well. Putting people in silos does not tend to work in healthcare like it can if I’m developing a fintech product or a marketing tech product.
John Farkas:
Yeah. Ramon, how do you see your role in that equation?
Dr. Ramon Jacobs-Shaw:
Gosh, almost like a translator. Is that a good way to put it, Mac?
Mac Davis:
Yeah.
Dr. Ramon Jacobs-Shaw:
Almost as like a translator.
Mac Davis:
I was going to say, sometimes it’s like a special ed teacher and translator. I mean, it’s the same thing. Sometimes you’re providing healthcare 101 lesson, or Ramon is providing healthcare 101 lessons, and sometimes he’s going really, really deep into the minute differences between two clinical codes. And those differences do matter at the very minute level, but also at the top line, 101 process level. Clinicians have to be good at going deep into the weeds and pulling up and knowing this is where… I think that’s where, frankly, we got lucky with Ramon and some of our other clinicians, is that they can do that. That’s also not a common skillset in clinicians, to be able to go really deep into the annals of coding or how a process really works and then pull up and to be able to say, “But the most important things to remember from a process standpoint are A, B, and C.” Because developers need the detail and they need the high level view to help center them on what’s important.
Dr. Ramon Jacobs-Shaw:
John, this is bidirectional too. As much as I’m an interpreter for this as well, my data and analytics colleagues here are doing the same thing and teaching me tons as well. Just that kind of experience and collaboration over the years informs being able to sit in the seat that I’m able to sit in and for Mac to be able to sit in as well. It’s that collective, but it’s bidirectional. We’re learning from each other and then innovating and revising and thinking about the next thing that we’re going to do and all of that stuff. It really is a partnership. It’s tons of teamwork here in order to make that happen. Silos don’t exist here.
Mac Davis:
Yeah. I think that partnership piece, I’ll just… I’ve worked with and seen organizations that have worked with very rigid clinicians that say, “This is the only way to do things,” and that typically does not get people the best result. The same thing on the tech side where they say, “This is the only way of doing it.” The answer usually is that there’s a middle ground that’s actually the best, and so both sides have to keep open ears and sometimes close mouths, which obviously Ramon wants me to do more since I’ve been talking a lot on this podcast.
Dr. Ramon Jacobs-Shaw:
No way. No way. No way. You’ve got way too much experience to not be able to share with this audience.
Closing Thoughts
John Farkas:
Well, guys, I am excited about what you’re doing in the context of Belong. As we’re thinking about closing gaps of care and how we can better make meaning and bring great service to underserved populations in our world, it’s obviously a huge need. And I know that technology and… Because, A, we don’t have enough clinicians to meet the need and that problem is not going to get easier in the next several years, it’s just going to continue to be a big challenge, technology has to play an important role in helping us be increasingly strategic and better pointed in the efforts that we have. So I’m grateful for the work that you’re doing and I think it’s obviously really important, and excited to continue to watch the story as things unfold in your world. Thanks for joining us today in this context. Any final thoughts or things that would be good to underscore as we conclude here?
Mac Davis:
I’ll give a plug for the health tech companies out there to focus on how… When you’re building algorithms or items that are looking to automate practices, make clinicians time go further, or be more effective, don’t forget about thinking about how do I inject compassion into my workflow or into this model so that you’re not automating some of the problems that I think we all face when we’re interacting with the health systems as patients ourselves. No one likes a decision to be made in the background without knowing why our care is being affected one way or another.
I think we see a lot of that with prior authorizations and denials. It’s very heavily in the news for payers today. That’s a great example where algorithms are used to make decisions and those decisions are not always explained to members in a timely or effective way. And so, we as an industry in health tech and analytics and data have to get better at making sure that we’re delivering those messages in as compassionate a way as possible. Because that’s the only way you’re going to convince somebody to either make a behavior change, or to help steer their own healthcare journey in a more effective way.
John Farkas:
Yeah, that’s a great word for sure. Ramon, anything from your perspective?
Dr. Ramon Jacobs-Shaw:
My plug would be, listen, for the health tech companies out there that are looking to do more, to do better, to do something deeper in the work that they’re doing, seeking out places like Healthcare Matrix to learn about what other people are doing. And listening to Belong Health Story, for example, just to get an idea of just what some of the possibilities are. We’re just touching the surface here. The goal is to go deeper into what we’re doing here.
John Farkas:
Yeah. The possibilities are pretty remarkable, and technology is going to be a really critical role. I mean, it just is. There’s so much coming forward. And when I hear Mac talking about the importance of interjecting compassion, when we’re dealing with clinicians who are so extremely pressed, and anything we can do to help relieve that burden, that might help have an opportunity to humanize care, where they’re able to focus more on delivering the kind of interactions that they want to be able to deliver; that’s obviously an important part of the mission here. And I know that that’s a lot of what you guys are endeavoring to do in helping people that really have a challenge in navigating what they’re up against in getting good care. To be able to be seen and to be understood and to be well cared for; super important. And so-
Dr. Ramon Jacobs-Shaw:
Absolutely.
John Farkas:
… great [inaudible 00:50:07]
Dr. Ramon Jacobs-Shaw:
That’s what we all want, John, right?
John Farkas:
That’s right.
Dr. Ramon Jacobs-Shaw:
To be seen and to be heard.
John Farkas:
It’s a critical part, especially when our health is on the line.
Dr. Ramon Jacobs-Shaw:
Absolutely.
John Farkas:
Mac, Ramon, thank you guys so much for joining us today, and best to you as you continue the journey with Belong Health, and grateful for your investment here with our audience.
Dr. Ramon Jacobs-Shaw:
Happy to be here. Thanks so much.
John Farkas:
Thank you.
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About Dr. Ramon Jacobs-Shaw + Mac Davis
Mac Davis
Mac Davis is responsible for Belong Health’s data and informatics to inform partners on growth and performance management strategies as well as Belong’s digital and technical product strategy. Mac has over 10-years of experience in provider and managed care analytics for risk-bearing organizations.
Prior to joining Belong Health, He served as a Director at Rowdmap (acquired by Cotiviti), where he was responsible for client success and adoption of the design of value-based, network, population health, and actuarial solutions. He worked closely with operations and provider leadership to create and optimize strategies to increase the delivery of high-value care and optimize care delivery networks for high-risk and underserved populations.
Mac also served as a key leader at Epic Systems where at different times he ran US Government Strategy, International Clinical Applications, the Foundation System, Neonatology Success, and Inpatient Go-Live Success. During his tenure, he was also responsible for the success of Epic’s implementations in the Middle East, large US health systems, and for the Department of Defense, Veterans Administration, and other Federal Health entities.
Ramon Jacobs-Shaw, MD, MPA
Dr. Ramon Jacobs-Shaw is responsible for the development and implementation of Belong Health’s care model, care delivery and clinical management programs for D-SNP populations. Dr. Jacobs-Shaw is a Harvard-trained physician executive who completed his residency and chief residency in both internal medicine and pediatrics at Massachusetts General Hospital and Boston Children’s Hospital. He has 10+ years of clinical leadership in value-based care for Medicare and D-SNP populations in academia and for care delivery organizations.
Prior to joining Belong Health, he served as a Senior Medical Director at Oak Street Health and Regional Medical Officer at CareMore Health, two physician-founded and physician-led care delivery systems that focus on improving and coordinating care for high-risk seniors in Medicare Advantage and Dual-Eligible plans.
He also has a passion for education in holistic, patient-centered care, having served as Associate Professor of Medicine at NYU School of Medicine and University of North Carolina at Chapel Hill.