When Zach Henderson says he goes “way back” with Tea Leaves Health, he’s not exaggerating. He’s been involved since the beginning. “I have a soft spot in my heart for Tea Leaves and the team here,” he said. In the past, Zach’s work with LexisNexis concentrated on the physician side and claims data, but he’s made a shift to the consumer side. Specifically, he’s working on social determinants of health (SDOH) and how innovation can impact quality while reducing costs and improving the patient experience.
The first step is separating myth from reality. “There’s a lot of hype out there, and so as you are trying to separate the wheat from the chaff, hopefully, we can help you do that,” he said. “The real question is how do we do something about it? What data do we use, and how do we make sure we don’t misuse it?” With that, Zach dispelled five primary myths and their related truths.
Myth: Socioeconomic data is “noise.”
Truth: Social, economic and environmental factors determine 50% of overall health.
Myth: All data regarding lifestyle, environment, a person’s situation and behaviors relates to SDOH.
Truth: While data may be useful, not all data on a person is a SDOH. In other words, Zach said, the value of any attribute is much better if taken in a holistic sense.
Myth: Examining only individual socioeconomic attributes about a person allows for an accurate prediction about that patient’s overall risk.
Truth: Focusing on individual attributes, rather than the combination of risk factors, can be misleading.
Myth: Aggregated data at the ZIP code or census level can be used to personalize care.
Truth: For personalizing care, individual-level data is necessary to explore the combined impact of socioeconomic data.
Myth: Socioeconomic data is only useful in combination with clinical and claims data.
Truth: Socioeconomic data is valuable with or without clinical data.
“Data on consumers has been around for a long time,” Zach said. “We are currently in the third generation.” First-generation data came from the county or ZIP-code level. The second generation is where people saw it as “noise” because it was not complete or conclusive. The third generation of socioeconomic data, Zach says, is at the patient level, addressing multiple categories with the ability of delivering increased-life or existing-risk models and unlocking care management opportunities. “The challenge to next generation social determinants is to find data sources, achieve patient-level detail, and then correlate it to health risk,” Zach said. And it’s organizations like LexisNexis and Tea Leaves that are creating that next generation of data to help streamline care management, retain and grow patient populations and take the patient experience to the next level.
“There are a lot of folks that are experimenting with way out-of-the-box strategies when it comes to dealing with social determinants such as isolation and other reasons people fail to follow a care plan. I think that’s exciting,” Zach said.
On the provider side, how do you generate value? According to Zach, it involves three elements:
- Create an SDOH-based predictive model – one that will accurately place a patient in a risk pool
- Risk stratify at the member level, and
“When you can do this, then you have the power and opportunity to enroll the patient into a personalized care management program to address both medical and social determinants,” Zach said.
So, what’s the takeaway? When you have good data and you use it appropriately, you can definitely improve outcomes, drive expense reduction, and ultimately, retain patients and be seen as the people who take care of the community. Contact us to get started today.