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 Today on Town Hall

(INTRO)   the old adage is, I think so true. And again, increasingly being recognized, your zip code is often more important than your genetic code. When we think about health and health outcomes.

My name is Bill Russell. I'm a former CIO for a 16 hospital system and creator of This Week Health.

Where we are dedicated to transforming healthcare, one connection at a time. Our town hall show is designed to bring insights from practitioners and leaders. on the front lines of healthcare.

Today's episode is sponsored by Meditech and Doctor First .

Alright, let's jump right into today's episode.

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 Good day, everyone. Welcome to Town Hall, a podcast of This Week Health and Al's AI Insight Podcast. I'm Dr. Al Villarin, your host. This month, I'm honored to be joined by Dr. Michael Poku, who is the Chief Clinical Officer at Equality Health. In this session, we will explore the principles of leveraging social determinants of health, SDOH data, to improve health equality.

Dr. Poku, welcome to the podcast.

Thank you very much for having me, Al. Excited to be with you and your listeners. Please tell us a little about

yourself.

Yeah, sure. I'm the Chief Clinical Officer for Equality Health, which we are a unabashedly Medicaid first, value based care enablement organization supporting independent practices to drive better outcomes for their patients and the members that we serve together.

I'm a practicing internal medicine physician. I'm also a board certified in clinical informatics. Well, welcome to the program. Let's start out by explaining the role of SDOH in healthcare and how Potentially, AI can enable some social care  aspects to address these determinants of social determinants.

Yeah, and many folks have heard about social determinants of health at this point, fortunately, but SDOH, as it's called, are those non medical factors that influence all of our health outcomes. And it's been increasingly recognized in the health and human services ecosystem of the just intensified importance that social determinants of health, non medical drivers of health play in our ecosystem when we think about health and we think about well being and we think about health care services.

As far as ability to leverage artificial intelligence and AI enabled technologies, there is an immense opportunity for those technologies to play a significant role in addressing the social determinants of health, which increasingly it is the non medical drivers of health that are that contribute and influence and often dictate one's health outcomes.

So the ability to take all of the various data sources out there that form up these various social factors and non medical drivers, and to make sense of that through a technology enabled processing system, and then to integrate those insights into care in an actionable manner, and cannot be overstated.

Those technologies really have the power to transform how we think about health, how we think about health care, both in terms of taking care of individuals as well as populations and communities, which is pretty exciting.   📍 From my perspective as a clinician, when we think about what we're doing at Equality Health to really drive towards narrowing and eliminating health disparities.

Excellent point. As we know, in recent studies around Cleveland, there's just two different zip codes had significantly different clinical outcomes for those patients, just because of their locations and their environments that they were raised in. So these factors are definitely part of the healthcare matrix that we need to take consideration and care for our patients.

And Alex, the old adage is, I think so true. And again, increasingly being recognized, your zip code is often more important than your genetic code. When we think about health and health outcomes.

Excellent statement. I love that. You recently spoke about some five principles for leveraging SDOH data to improve health quality.

Can you elaborate on those principles that you spoke about in other venues?

Yeah, so to quality health where we really focus on supporting Both practices taking care of folks with disproportionate Medicaid, and then those folks living with Medicaid. We've developed system and a framework by which we should be thinking about social determinants of health in order to promote health equity.

And it really starts, unsurprising, with understanding the data and leveraging analytics in a simple way that's actionable at a point of care and point of service. So how do we take, again, The often fragmented data ecosystem and how do we put it through a processing funnel and make it actionable to whomever is needing that to use that data, whether it's a clinician, whether it's a community health worker, whether it's a social worker or somebody else sitting in a community based organization.

And then we've got conviction in terms of the second piece that we really thinking about is that everyone ought to have a medical home. So driving that impact. at the medical home for that primary care provider and making sure that he or she is powered with that actionable data to be able to impact individuals and populations that he or she is serving.

Followed there is really thinking about making that data available across the care continuum and service continuum. Oftentimes. Folks may be screening for non medical drivers of health and social determinants of health, but that doesn't get to every place it needs to go, Al. I think you've seen in numerous times, making sure that we are getting that information to the appropriate individuals who are taking care of that.

Patient, individual, population, again, across the spectrum of care. So, making sure that we are democratizing that. Similarly, how we are filtering out information that's related to chronic care conditions and everything else. We have strong conviction that non medical drivers of health, social determinants of health data, should also be communicated out to other stakeholders taking care of individuals and populations.

Thank you. And then the fourth thing we really think about is making sure that we're not only filtering that data out and getting it into the proper hands, but we're also then empowering communities and empowering community based organizations to be able to take good care of those individuals, clients, patients, members, depending on the side, which side of the elephant that you're on, so we can really take good care of folks in a holistic, whole person manner.

And then finally, in a true sort of PDSA style, making sure we're always measuring our impact and we're iterating and we're pivoting on the basis of that. So it's one thing to be able to screen for unmet social needs, and then it's a whole other thing to be able to refer if you've got somebody that's got unsecure housing food insecurity, et cetera.

But then it's also a next level to make sure that you are durably closing out those unmet social needs. And you're addressing that fitfully and robustly. And then if you're not, if you've got somebody who's experiencing homelessness, unstable housing, and there is a six month wait list for a housing resource.

That's something that we then need to measure that need, measure that gap in service, and then work to modify our interventions, work to make sure that we are filling those gaps for that individual, for the communities, and that we can always think through what the true closed loop is.

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 Excellent. In January 2024, you authored an article entitled, How Value Based Care Can Address Health Equities. In it, you noted, Effectively implementing value based care necessitates upfront investments in people led outreach, intelligently bolstered by technology and data science. Can you provide some examples of these as they impact primary care physicians at the front lines?

Yeah, for sure. Particularly thinking about my role at Equality Health, one thing that we do pretty intentionally is empowering our practices by providing wraparound services, particularly with regard to our community health worker workforce, as well as our chaplain workforce. But it starts not just dropping in those resources, but we're actually hiring folks from the communities that we're serving with lived experience, with the approaching Patients, members with that cultural humility, but the experience of being in that particular environment, but again, we are then out arming those folks with the appropriate technology that quite frankly, for many, particularly independent practices, it's a tough thing to invest in, given the current margin, particularly for independent primary care practices, making sure that we're giving them the data.

That again, that fragmented data ecosystem that we've talked about, it's pulling all those data, making sense of it, and being able to risk stratify populations on the basis of need, on the basis of perspective, expected costs, then being able to have the prescriptive analytics to help that community health worker understand how best to go about interacting with and helping to address the unmet social needs for that particular individual.

And I think that's the real interesting and increasingly important piece again, as we all collectively understand and recognize the importance of SDOH and non medical drivers of health. It's how do we use some of these newer technologies and how does the advent of AI help us in this space because of the drive that it has, that it's not always, The medication that I'm able to prescribe, it's one's ability to pick up the medication.

So if we know that somebody's had issues in the past picking up that medication, shouldn't that, and how should it, impact how we go about addressing a particular patient we're trying to serve that particular day?

Excellent point. The technology is moving so rapidly. That just last year at this time, AI was just a thought of the InfoMasters, like yourself and myself.

Remembering robotic process automation, where we can move it for the future, and now it's embedded in everything we even talk about around health care, especially clinical determinants of health and social determinants of health. So, how do you see our industry aligning the technology and the data with those who need it most in primary care?

Yeah, I see it as both a social an economic imperative, So, using this technology to maximize the impact, particularly, again, our focus on quality health, those living with Medicaid, who are often, most impacted by health disparities, whether it's cut along the socioeconomic status, race, gender, ethnicity, what have you.

So the ability to take these technologies, which as you mentioned now are so transformative, and point it towards those that historically are living in disinvested communities and I have been marginalized with respect to healthcare access in really flipping the paradigm on its head in making sure that everyone is afforded the access to care in the dignity that we all deserve is going to be and continues to be the really big problem, the hair on fire problem to solve.

And it's exciting because there's so much opportunity. It's at the same time harrowing because, as you and your audience knows, Al, healthcare costs continue to be persistently high and stubborn, and this is the economic imperative that exists. And if we can really drive superior outcomes for those living with Medicaid, we can really impact the healthcare trajectory and the healthcare spend from a national perspective quite dramatically.

So in terms of the future, looking ahead, where do you see the future of social determinants of health and health care itself?

Yeah, so a couple of different things. Again, I see, and again, bias as a primary care clinician, but I see More organizations such as us at Equality Health that are really focusing in on narrowing and eliminating disparities, focusing in on the Medicaid space, focusing in on those living in historically disinvested communities, and leveraging those technologies here as a really big opportunity.

And I think to your point, the technologies are not improving linearly, they're improving logarithmically. So I'm equally excited about the use cases. So we've been talking about social determinants of health and how we understand potentially one's unmet social needs and describe that. But then it's how do we then predict who's going to have unmet social needs?

And then increasingly it's this prescriptive piece. It's what am I actually telling somebody to do or what, how am I helping somebody on the front lines do what they can do better, faster, more efficiently as a big thing. And then increasingly they're technologies that are pointed. Towards patients, clients, members, again, depending on you sit in the ecosystem.

And how do we empower individuals in this day and age where we have access to more data, technology, information than anyone in human history to better drive those outcomes. Think about change management, thinking about motivational interviewing to, to really help in this whole stream from multiple different channels and multiple different angles.

So it's a pretty exciting time when you think about the future and you think about all the challenges that we have today and just the immense impact that data science informed tech enabled services can really help drive.

Excellent points. I think the future. It is very bright for us clinicians to take care of the patients we have to regain their trust after the last several decades around this and AI is formidable and a positive tool for us to take care of them.

We just have to use it appropriately, evidence based, rigorously unbiased and build their trust, both for the clinicians as well as for the patients we care for.

Yeah, Al, I think that's incredibly well said. I think, again, bias as well, as a clinician, there's also this view of AI and these technologies replacing you and I and others, but I always think there's going to be a human touch component that we really, again, are incredibly intentional about at Equality Health as well, that while the technologies are there, and again, with that logarithmic improvement, I've got a lot of conviction, our organization has a lot of conviction that it really, to get somebody through the last mile, it's that human touch component.

So how do we use that technology and data in an evidence based manner, embrace cultural humility, and it's meeting folks where they are. But how do we do it without losing the connectedness? So using the technology to truly augment. And reach out and touch somebody deeper, reach out and touch more individuals, but not losing sight of the humanness of the whole thing.

Agreed. Healthcare is a human aspect. Without humans there is no compassion, there's no healthcare. So utilizing technology, like you said, embracing it for what it value brings will help us be better clinicians and the future of healthcare relies on that. Yep, 100%. Dr. Poku, it was an honor to have you participate in today's discussion on social determinants of health and how you and your company have advanced health equity through technological innovation.

Any last words?

No, just that we are, again, at Equality Health unabashedly Medicaid focused. We have a strong drive on promoting health equity and the leveraging technologies to do that. Again, maintaining that humanity, maintaining the human connection, and we welcome, Al, you and your audience along on this journey.

We think there's a lot of opportunity here and a lot of good to do. Thank you and thank audience for having me.

Thankful for your participation today. Thank you all for joining us. We look forward to seeing you at our next Town Hall by this week, Health and Al's AI Insights.

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