Social determinant of health (SDoH) factors have a great influence on the quality and care management of a population’s health. As technology advances to better capture SDoH factors, clinicians can explore new ways to integrate this data into clinical workflows to proactively identify patients at high risk for adverse outcomes – resulting in better quality care.
On this episode of Value-Based Care Insights, host Daniel J. Marino and Amy Valley, Vice President of Clinical Strategy and Technology Solutions at Cardinal Health, discuss the importance of incorporating social determinants into care management.
- There are five main categories of SDoH: medical, environmental, physical, behavioral and social. These factors create a proliferation of data that can be difficult for clinicians to manage, however, new technology aims to identify the signals of a potentially high-risk situation for a patient.
- SDoH provide a perspective into health conditions - and incorporating these factors into clinical workflows help to proactively identify patients at risk for adverse outcomes.
- The recent staffing shortages are forcing organizations to re-evaluate their approach to navigating care. Analytic platforms are a necessity to support care delivery. These tools have been proven to increase efficiencies and improve clinical outcomes.
Daniel J. Marino
Managing Partner, Lumina Health Partners
Vice President of Clinical Strategy and Technology Solutions, Cardinal Health
Daniel Marino: Welcome to another episode of value based care insights. I'm your host, Daniel Marino. In today's environment, as we start to move into value based care, many organizations are at different places in managing the outcomes of their populations. Some that are just getting into value based care or focusing on the high risk population or the rising risk population, and really focusing on some of the claims data to make sense of what's happening with their population. And in some cases, the clinical data, then incorporating into their analytic platform, again, addressing chronic diseases, and so forth. But as organizations become more proficient with population health, they recognize that there are other factors that come into play that really influence the health condition of the populations that they manage. And, really, it's the social determinant outcomes or activities that occur in one's life that has a really strong influence on everyone's health, whether it's how much money you make, or it's your ability to get health care, or it could be your age, it could be your job, it could be a number of socioeconomic factors or social determinant factors. Research has shown that this plays a significant role in everyone's health condition. And as organizations start to move into more of the maturity journey of managing populations, they recognize that getting the social determinant data and integrating that data into their full analytics tool is a pretty big challenge. It's hard. And it's hard on a number of fronts, mostly because that data is blinded, if you will, it's hard to get that data incorporated into a way that makes sense. So you're able to really integrate it in with your clinical data, or your claims data, and so forth. Well, there are a number of organizations, a number of individuals, who are passionate about social determinant data and really passionate about trying to integrate it into the technologies. So today, I am very pleased to be joined by Amy Valley. Amy is Clinical Strategy and Technology Solutions Executive at Cardinal Health. She's a seasoned pharmaceutical expert with more than 25 years of experience in the field, and just a tremendous amount of experience in technology. I know she's passionate about social determinant data and health disparities and so forth. So happy to have her here. Amy, welcome to the program.
Amy Valley: Thanks so much for having me. I'm really excited to be talking with you today.
Daniel Marino: So Amy, as I said, I've worked with organizations for probably 20 years around Population Health and Clinical Integration, and there's this journey that that all organizations move towards in trying to manage the populations, but all of them recognize that there are external factors that are influencing the health conditions of the populations that they're treating. And it's this social determinant data. And it's challenging to incorporate some of this or at least to make sense of it. What are some of the things that you're seeing as you're working with organizations or just understanding some of the challenges with social determinant data?
Amy Valley: Yeah, I think you've really described a lot of the landscape really well, Dan, and I think that there is now a recognition, I don't think anyone disagrees with the importance of what I call the non clinical elements in determining healthcare outcomes. I mean, specifically, when we think about determinants of health, you have folks that are experts in this area that live and breathe this every single day. There's five main categories, there's medics, there are the behavioral, environmental, physical, and social factors. And then of course, there's medical care. And so we've been focused on dealing with all of the data created by medical care, all of the laboratory data and the radiographic data. You know, everything that's in the medical record, that in and of itself has been challenging to collate and lift up insights from that and then you superimpose genetics into that. And I work a lot with oncology specialists where there's just been this proliferation of information on the importance of molecular data, not just in determining risk for certain cancers or prognosis, but now as a target for therapeutics. And so you've superimposed that proliferation of data. And so we're getting better and better at the technology to manage those massive amounts of data. But largely, it's been very difficult for the non-clinical things like the social and behavioral and environmental, et cetera, et cetera, factors to incorporate that in. I think the exciting thing is that the technology is just as rapidly advancing as is the science and this knowledge. So it creates a perfect environment to really innovate, and create tools that help these clinicians manage this massive amount of data and find those patients that they really can make a difference for. So I think this is great.
Daniel Marino: Yeah, right. And, you know, when you think about all of the data platforms that are out there, whether it be claims data, and then the clinical data, you have finance data, and then you have the social determinants of health (SDOH) data. All four of those categories really have different data structures. And the first three that I mentioned, because they're within an organization, there's a linkage there that can connect that data to the patient. Oftentimes, with social determinant data, it's identified data, it's data around trends, trends that are occurring around segments of the population or other categories that might exist. But it is powerful information, nonetheless, if you can make sense of it. And so what I see is organizations that have been successful in making sense of the social determinant data is one, they've created technology that helps integrate the data into those other three data platforms that I've mentioned. But they've also then built sophisticated models to help the end users or in most cases, the physicians, understand or make sense of the data, and really identify some key insights that will help them make decisions. Is that some of what you're seeing, or is there other technology that is more advanced in helping to integrate the social determinant data?
Amy Valley: Well, I do think that there's technology that's advancing now to marry the two in a way that is right in the clinical workflow for the clinician to be able to really not have to, you know, mine that data or spend a lot of time collecting it. You know, I think it's great to have specific data on the patient that you're seeing. But to your point, Dan, there's also this wealth of population data as well, that is very robust and meaningful. So we have partnered with a company called Jvion specifically looking at what we liked about their machine. And they're not the only player that does this, but the point to make is that there are technologies out there that marry the clinical information with this population health data, and can surface meaningful insights. I liked what you said about those rising risk patients. I think there's a growing understanding that we already know the highest risk patients, and that was the low hanging fruit we've picked to find the people already at risk. But many times you can't influence someone who's already at high risk. So finding those rising risk patients where you can still intervene and make a difference. That's where I think we're making some of the greatest strides to really be able to influence healthcare outcomes, and putting those tools right in the hands of clinicians and care coordinators, again, who can act on the information. So that's where I think we're making some advances and really proving this isn't theory. This really works. And it really does influence health outcomes.
Related Article: Patient Risk Scores Are the Key to Value-Based Payment
Daniel Marino: Well, as you're talking, it reminds me of a work that I had done probably about four or five years ago with a large organization. There was a research project that they had done within a community and they were looking at older male adults, those were over 65 years old, 70 years old and so forth. It was a research project that they did. And they noticed that these individuals, these males, were in good health and that some of them their health declined. And so that they're really the research project was around well, why was there such a drop off and declining of health, and a lot of it was the chronic diseases there, BMIs went up, a lot of them had high blood pressure. What they determined was for those individuals, and they discovered this from the social determinant data, this was fascinating. What they determined was for certain individuals where the wife was the predominant caregiver, when either the wife became ill, or in some cases, the wife might have passed, the male had to take care of everything on their own, and they did not do a very good job doing it. So consequently, their health conditions declined. And not only did they discover that, and they were able to identify a segment of the population, but they were to your point, able to incorporate it into care management, and proactively provide outreach to these individuals within the community. It was a fascinating project, to really show the power of social determinant data, and how it could be integrated with clinical conditions to not only treat what's occurring and understand what's occurring, but to get in front of it.
Amy Valley: Right. And I think following on that example, that endpoint of them losing a wife, or losing that spousal support, you know, if you're only seeing the patient once a year, every six months, and those things pop up in between, you don't know that they're happening. So even if you're a clinician who really explores those social elements in your regular care of your patients, how would you know that? How could you proactively do that? So I think picking up these signals and kind of a tap on the shoulder to the care team of, hey, something has happened for one of your patients, that's really important. It just helps to prioritize the work every day that these care delivery teams are charged with doing and helps them focus on the plate, again, those patients where you can make an impact.
Daniel Marino: Right. So when you think about the social determinant data, what often comes back to me, and most of this is coming from the Chief Medical Officers or the Medical Directors in charge of population health. They realize the importance of it, they realize the obvious clinical significance of the social determinant data. But they also realize how tough it is. Right? So what are you seeing now that's really helping to incorporate some of the social determinant data into these analytic platforms? Is it getting easier to take some of this data and to incorporate it into somebody's analytics, Population Health analytic tools, so they can actually work through it? What are some of the things that you're seeing?
Amy Valley: Absolutely, I think it is getting easier. Our experience, again, focusing in the specialty area, we took a look at some of the challenges that practices were having and any that were participating in the oncology care model, and thought, wow, if we could lift up these insights and incorporate the social and behavioral determinants of health information somehow into their population health, you know, we think there's an opportunity to improve their performance in the oncology care model by proactively identifying patients at high risk for adverse outcomes. And those adverse outcomes often result in poor quality and higher cost of care. And so we basically married the clinical data with the SDOH data. And again partnered with a company called Jvion to really point their machine in the oncology area. And we superimposed this machine on practices that were already performing well, in the oncology care model. And we were able to show that when we superimposed this machine into their care coordination environments, that we were able to increase identification at patients at risk for ER visits, hospitalizations, severe pain and depression, and also clinical deterioration and even mortality. And so that became almost like another data point, if you will, that the clinicians had to consider. And we were able to incorporate it into their clinical workflow in a customized way so that patients that were all of a sudden showing up on the high risk list for three or more of these adverse outcomes could be intervened, and brought in and triaged appropriately, and it made a difference. It made a huge difference. And so that's just a real working example of it really does work, it really produces incremental results. And it is not difficult to put into an established clinical workflow.
Daniel Marino: I often say when we help organizations build their analytic strategies and help them understand, kind of work through the analytic insights that is absolutely necessary to manage the populations, I often say that the clinical claims data tells you what's going on, but doesn't tell you why the clinical data tells you why. But the social determinants of health data is even a deeper answer to the wide question. I mean, it really provides a whole new perspective as to why things are coming, why things are occurring. And even with your example, with the oncology care model, I can't help but think that there are external factors that are really going into the influences of risk factors of these patients. And, as you mentioned, I think understanding this is really key, but incorporating it into the clinical workflow, because then you can do something about it, right? I mean, you have the ability to really, physicians have the ability to really understand it, and create some real actions around what this data means.
Amy Valley: I do think there's also a learning curve, you know, as we launched the tool, there's a lot of suspicion about, is this tool really going to tell? I mean, I know my patients, I manage them, you know, closely, is this going to really add to my ability, and it was very interesting to watch the physicians journey from being skeptical to being amazed. And then really incorporating that tool into how they manage their patients. So the early stories that they told about patients that wow, I would have never known that this was going on. It was very powerful to hear those examples. And that is part of the journey. I think as you know, AI and the belief that SDOH does need to be acted on and incorporated into care management as that grows, and there becomes more comfort with these AI enabled types of tools. That just opens the door to more opportunities to impact more patients.
Daniel Marino: I agree with you. I want to turn our conversation around a little bit about how social determinants of health data can help to understand and maybe target health, better treatment outcomes to areas of populations, I guess where I'm going to is, how are you seeing right now social determinants of health data, or maybe the models that you're seeing that are being created. How are they impacting health inequities of care or health disparities that are occurring within certain segments of the population? Maybe those that are more socially economically challenged? Are you seeing this playing a key role?
Amy Valley: I do. I think the tools are also evolving. I think the first generation AI tools around population health, you know, they just told you who is at risk. So they were just really finding the patient. But now we see them becoming more sophisticated. And the tools we work with, say, not only who's at risk, but why they're at risk. So you know exactly why. And then there may be multiple reasons why. And so then the third thing is okay, I know who's at risk. I know why they're at risk, but what are the most impactful interventions I could make? And so the tools we work with actually give a ranked order prioritized intervention list. I was always amazed (my background initially, I was a pharmacist) so if I saw that the reason for poor medication adherence was, okay, this patient is at risk for an ER visit. And the number one reason is medication adherence. Of course, I think they need to spend more time with a pharmacist. And it was amazing to me that in our pilots, the number one intervention for some of those patients was yes, they need a medication review with their pharmacist. But sometimes it was transportation. They needed an Uber ride to pick up their prescription, or they needed a delivery service to deliver that prescription that had nothing to do with more time with a pharmacist. So I think that as the tools continue to get smarter, and we have this population health, and we're really doing our job with the tech and continuously learning, we're going to be able to figure out those interventions, most likely. So then if I'm the care navigator for that patient in my region I may have a deal with a transportation provider or a delivery service that's going to get that prescription to the patient versus scheduling an appointment for them with a clinician to review medication.
Daniel Marino: That's where I think this level of information becomes so powerful in really implementing the health conditions of populations, because it expands the ability to provide care management, not just internally out of the physician's office or out of the provider's office, but allows you to take it directly to the community. And as you said, whether it's providing transportation to patients so that they can get their refills, or maybe it's providing a fan for populations who may not necessarily have air conditioning, you know, so they're not getting overheated, things like that can have a significant impact. And yet, you know, for a lot of people it's common knowledge. To be able to understand that out of the data and impact and really create some impactful actions out of it. To me, it's just so powerful.
Amy Valley: I totally agree. And it's real, it's not just all futuristic stuff. I think the other thing I get excited about is that it's really here and now. And what we need to do is get more adoption of these tools in health systems in the community. And it has to be affordable for them. I mean, technology out of the gate was really only available to a very, you know, well funded health system that was really interested in innovating in this area. But the real opportunity is in the community, in community practices. And so it has to be affordable and accessible to those individuals as well, if we're going to get the most value, it can't only be available to a university based health system that's in one region in a state or something like that. So that's I think the challenge now is how do we get this in the hands of as many, you know, care providers and this possible?
Daniel Marino: As much as it is a challenge, I think for many organizations, it's a barrier. They just don't know how to do it. And frankly, when you think about building an analytics platform, at least one that is really going to drive results, it's not cheap. It's expensive to put something together. So how do you see or what some of the advice that you would give to Chief Data Officers who are interested in incorporating this? Where do they start?
Amy Valley: I think the opportunity that's being created a little bit by some of the staffing shortages across the country, is that these tools are huge. Not only do they make a difference in clinical outcomes, they're huge efficiency tools. They allow a team of care navigators to care for an order of magnitude greater number of patients. So I think that's the important thing to be aware of, like you may flinch at a price tag. But if you think about the fact that, wow, I can't get enough nurses or lay navigators in my health system to be using these tools and to be proactively reaching out but wow, I could care for a lot more patients. I'm spending more money on tech than people. And I know I have to because I can't find enough people. So I think that that's maybe going to create a tipping point for not just the data teams but the quality leaders and organizations to look at things a little differently. So that's I guess a piece of advice is to understand the return on the investment in terms of how and where you spend your money and how sustainable that may be. It might be more sustainable than depending upon the staffing challenges, especially in some areas of the country that may have more of a challenge with maintaining that staff.
Daniel Marino: Well, it's such an important point, we work with organizations all the time on helping them identify the ROI on investing in some of these solutions. And we put together what we call our Value Model, which helps to quantify what the return on the investment is in a population health setting. And it's a tough goal, right? Because, you know, you're investing in this technology with the goal of assuming that these activities are not going to occur. So what are the outcomes related to the cost savings? How does it influence your value based care contracts? How does it put you in a better position to provide some cost savings that economically will benefit the organizations. It's a tough go, but it's important nonetheless. And that is the only way that you really make this work. Organizations have to start really building these ROI models. And to quantify the results of a platform like this in order to really see these results.
Amy Valley: I do think there's a role for government policy to play a role as well. I mean, if we think about how every clinician loves to hate their EMR, you know, we know that. But yeah, some of the requirements around meaningful use really did drive the adoption. And there are tremendous benefits, I believe, to enable these technologies and to be part of that electronic medical record. So I think in order to get costs down and to drive adoption, if there were incentive programs or policy changes that this is not an unproven thing to incorporate this into health care. So how do you from a policy standpoint, put requirements in place or encouragements to encourage the adoption, number one, but also, perhaps to find reimbursement to offset. To make it affordable for clinicians who want to do this, but have the barrier of price. I think that I'm not an expert in figuring out the details on that, but I think there's an opportunity, and I think it shouldn't be ignored because of just the impact on health outcomes.
Daniel Marino: Yeah, I absolutely agree. And it's a significant impact. No, no doubt about it. And through all the years that I've been working in population health and within clinical integration, this plays a significant, significant role. Amy, this has been, this has been a great discussion. Obviously, something that I'm passionate about, you're clearly passionate about. If folks want to get a hold of you, or learn a little bit more about maybe different solutions, or just pick your brain a little bit, how can they get a hold of you?
Amy Valley: Certainly always willing and looking forward to engaging with people through LinkedIn, that's always an easy way to start a conversation. But also on our website, Cardinalhealth.com/vitalsource or cardinalhealth.com/navista. Either one of those are another easy way to engage with our team and to, again, get a conversation going. But we're very excited about the work that we've done thus far. And that we continue to do because we really believe this is the future to help providers navigate value based care and for patients to get the most from it.
Daniel Marino: I absolutely agree. Well we'll include your contact information as well on Luminahp.com website, our Insights page, we'll put your information on there as well. Well, this is great. I really want to thank you for joining the program today. Before we wrap up any pieces of advice, final comments you may give to our audience or folks that are out there that are really interested or passionate about social determinants of health data.
Amy Valley: I'd say if you're not already doing it, then get started. And if you are doing it, go the next step with your tools to really make sure that your tools are lifting up those insights for your care team.
Daniel Marino: Yeah, I agree. I think at some point, everybody's going to have to do this. Great, great advice, and might as well start sooner than later at least being able to incorporate some level of insight. Well, thank you again, Amy. I really appreciate it.
Amy Valley: Thanks, Dan. Thank you for having me.
Daniel Marino: In closing, social determinants of health data place such a key role on managing the population, especially as you're starting to think about, as we've talked about many times on the program, managing the risk of your contract, managing the risk of your of your population, it becomes such an important tool on driving this level of outcomes. I'm sure this will be a topic that we will continue to talk about in the future, I think we've only scratched the surface on what social determinants of health data can do and how it could really influence a lot of the health outcomes of our populations and even close the health disparities in many of our communities. Well, thanks for listening today, and until next time this is Value-Based Care Insights, I'm Daniel Marino, have a wonderful day.
About Value-Based Care Insights Podcast
Value-Based Care Insights is a podcast that explores how to optimize the performance of programs to meet the demands of an increasingly value-based care payment environment. Hosted by Daniel J. Marino, the VBCI podcast highlights recognized experts in the field and within Lumina Health Partners.