Social Determinants of Health: The Importance of Data, Part 2

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Tune into the second segment of the Avalere Health Essential Voice podcast series focused on social determinants of health (SDOH) data. In this segment, Avalere experts discuss how life sciences organizations are beginning to recognize the importance and impact of this data, particularly in real-world evidence value demonstration work.
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“I don’t think people really understand that social determinants not only affect outcomes like your likelihood of going to the hospital or the emergency room, but also the onset of conditions like diabetes and dementia.” Christie Teigland


Guest Speaker
John E. Linnehan , SVP, Customer Delivery, Inovalon
John E Linnehan leads a team of consultants, strategists, and data scientists focused on driving healthcare improvement through value demonstration, stakeholder engagement, predictive and applied analytics, and data innovations.
Guest Speaker
Christie Teigland , VP, Research Science and Advanced Analytics, Inovalon
Christie Teigland, PhD, leads the design and implementation of studies focused on comparative effectiveness, predictive analytics, and performance measure development and testing.

This interview was originally published as a podcast. The audio is no longer available, but you can read the transcript below. For updates on our newly released content, visit our Insight Subscription page.

If you would like to watch the video version, please visit our video page.


John: Hello, and welcome to the Avalere Health Essential Voice series focused on social determinants of health (SDOH). This is part 2 of our series. Hopefully, you’ve listened to part 1.

My name is John Linnehan, Practice Director of Avalere Health’s Economics and Advanced Analytics practice. I’m joined by Dr. Christie Teigland, a Principal in our group and one of our leading experts on SDOH, especially as it pertains to disparities and data analytics.

In part 1 of our podcast, we walked through the importance of bringing SDOH elements into research, trends that we’ve seen in the marketplace in terms of early looks at these data points from the health plan perspective, and types of data that bring SDOH elements in at a very granular level.

In part 2, we’ll talk about the trends that we’ve seen directly through our work, and elsewhere in the environment, around life sciences organizations, drug companies, biotech companies, medical device firms, and diagnostic companies bringing these elements into their real-world evidence value demonstration work. Much of this evidence gets put in front of payers to inform access decision making, and there’s considerable importance in making sure that these organizations do bring these data elements into research, especially given the trends that we talked about in part 1 in the health plan space.

So, Christie, to dive in, we have talked a lot about the risk factors that we’ve seen: household size, neighborhood, race, ethnicity. We’ve seen data points like, individuals with food insecurities are 50% more likely to get diabetes. If you’re lonely, you’re 64% more likely to develop dementia and 4 times more likely to visit the ER. People who live below the federal poverty level and have less than a high school education are much less likely to be adherent to their medicines. These are all elements that pertain to utilization of medicines, outcomes that could be addressed by biopharmaceutical interventions.

It’s clear that there are needs to be addressed, and there’s an opportunity to address them from a life sciences perspective. But from the first part of our podcast, it’s also clear that to really tell a value demonstration story that includes these elements, you need to know the data environment. You need the technical savvy to be able to bring these data elements together and link them to claims, which are still the primary source of medical resource use and cost data, especially from a health plan perspective. You need to know the right data sets to incorporate together to do this work.

I know we need to be cautious because some of our work is currently ongoing, but I’d be very interested to know how we’ve started to take advantage of these trends and support our clients, and how we’ve observed other clients working to bring SDOH data into value demonstration, real-world evidence generation work, from a biopharmaceutical perspective.

Christie: Yeah, you’re right. Health plans have been focused on this for a while. We’ve seen a flurry of interest from life sciences organizations and they’re realizing exactly what you pointed out. I don’t think people really understand that social determinants not only affect outcomes like your likelihood of going to the hospital or the emergency room, but also the onset of conditions like diabetes and dementia.

We’re currently working on several projects looking at some important outcomes, like hepatitis C, for example. For this study, we’re using our managed Medicaid data. We have access to about 70% of the nation’s managed Medicaid data, and believe it or not, 75% of Medicaid is now managed. It’s not fee-for-service Medicaid.

We’re looking at the impact of social risk factors on the likelihood that you will complete your treatment regimen and have good outcomes if you get hepatitis C. We’re comparing them to patients who are not treated at all or who don’t complete their treatment regimen. It’s going to be fascinating to see how certain social risk factors affect those health outcomes.

We’re also conducting a study of patients with severe mental illness, which includes conditions like bipolar mania, schizophrenia, and manic depression. You can imagine the impact of certain SDOH on adherence to your anti-psychotic medications. It’s low in this population to begin with, but we can only imagine that social risk factors will have an even bigger effect on those health outcomes in this population.

I saw a CDC statement that said that interventions to improve medication adherence would be much more effective if you consider patients’ health literacy. It means asking questions like: Do they understand the directions that you’re giving them? What is their cultural background? Do they trust that the medication will help them? What is their language proficiency? So, when you’re designing education materials, when you are thinking about programs to make sure that people take their medications, you really need to think about these other risk factors that can affect 80% of your health outcomes. It’s not just the clinical care.

We’re looking at other therapeutic areas, too. In one study, we’re looking at patients with liver cancer. We’re looking at another study on chronic kidney disease and the impact of social risk factors. So, like I said, these are just a few examples of the ongoing work. We’re getting inquiries from life sciences organizations every day who are understanding that these social risk factors are so important to the overall effectiveness of the treatments they’re developing. So, this is really going to help, not only the drug plans, but also the health plans, the payers, and the providers better understand and treat those patients and hopefully improve overall healthcare and reduce costs across the United States.

John: Absolutely. That’s the goal.

You hear of certain conditions, especially hepatitis C, having a key social determinant element to its precursors, and that has perhaps prevented individuals from getting the treatment they need. I think we’re seeing increased access in those types of environments and that’s crucial. Research like this has played a large role. It’s so interesting to see it moving into liver cancer in the oncology space, another area where personalized medicine is already key. This is an opportunity to bring a new element of personalized medicine to the table, so it’s great to see the activity.

The queries of how to look at these types of questions and the data sources needed to address them are becoming more frequent. Life sciences companies are taking other steps to address disparities, such as financial assistance programs, transportation, home delivery support, engagement, communications, health literacy work, mobile health, digital tracking, digital interconnectivity, and more. So, there are many around-the-pill types of interventions.

Our discussion today is focused on real-world evidence and bringing important disparities-related elements into work. Certainly, the other activities that organizations and manufacturers and device companies can provide is a topic for another podcast, so we’ll stop there for now.

Thank you to everyone for attending part 2 of our Avalere Health Essential Voice episode focused on SDOH. If you are interested in discussing any of the topics that we’ve addressed today further, feel free to reach out to Christie or me. Our information is available on Avalere’s website. You can find a recording of this podcast at Thank you, Christie, for joining us. Thank you everybody for listening, and we look forward to engaging with you around these topics and others.

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