The use of the term “population health” has grown in popularity since the idea originated in the early 90’s. Since then, value-based care initiatives aimed at addressing population health have expanded early definitions of the word, encompassing more than just a consideration of disease states, but of location, race, social determinants of health and more.
Moving toward a more holistic view of population health that encompasses both medical and environmental conditions is key to addressing social determinants of health and improving member outcomes. And yet, such broad strokes can easily leave many members overlooked by the healthcare system, or left behind as initiatives designed to serve greater populations don’t meet individual needs or circumstances.
Here’s three ways digital health can help support health plans in delivering a more personalized population healthcare experience.
Even with very specific member demographics, there’s a lot of variability in individual circumstances.
For example, in Boston, a simple change in zip code can be the difference between living to 68 or 94 years old. And in other counties—like Orange County—just a city block can be the difference between exclusive gated communities and hidden homelessness in motels, cars, and couch surfing.
Without living in these communities, it’s difficult for health plans to know exactly what social determinants each member faces regularly. Routine check-ins that screen for access to healthy food, safe living environments, and more can help health plans and case managers quickly identify individuals who need assistance and connect them with organizations that support social determinants.
Ensuring that these check-ins are regular and through a platform that members are already using.
For example, Wellth periodically polls members as part of their daily check-ins. Because members are already using the app, and the questions take just seconds to answer, it’s easier to get that feedback regularly and respond quickly to outstanding socioeconomic needs.
Population-driven healthcare prerogatives fall short when they fail to offer customization that meets individual needs. But with high buying and implementation costs, building these highly customized programs can seem overwhelming—especially for smaller health plans.
Digital health that has AI learning capabilities provides a solution for tailoring programs affordably.
For example, many health plans have tried implementing incentive programs to encourage healthy behaviors and preventative care, but have been unsuccessful in creating change. Just recently, the state of Ohio implemented state-wide incentives to encourage residents to receive the COVID-19 vaccine. While vaccination rates increased 43 percent the first week, subsequent weeks showed steep declines and little long-term progress in achieving desired outcomes.
Using personalized digital motivators that go beyond monetary incentives can increase adherence where traditional incentive programs have fallen short. Instead of static gift cards, offering flexible rewards that members can use to address their own specific needs can be a great start. Coupling those flexible rewards with personalized, AI-driven motivators can further improve program participation and long-term results.
As organizations grow, maintaining a high level of personalized care becomes increasingly difficult.
Digital health platforms can help care feel personal by leveraging human member support teams—rather than IVR calls or automated phone directories—to help members with program enrollment and to check-in when engagement dips. This targeted, personal outreach makes a significant difference in improving member satisfaction with the program and building long-term member loyalty and success.
“The Wellth Program helped me change my diet and take all my medicine. Wellth always calls whenever there’s a problem and everyone is so nice. Joining is easy because the enrollment specialists give you the instructions on how to use the program and then help you.”
As we’re able to address and improve personal outcomes, the overall health of populations will increase, too—decreasing high-cost utilization, improving clinical metrics, and achieving better health outcomes.
Digital health platforms can support this process by learning, adapting, and automating personalized member journeys—making individualized care not only possible, but scalable and cost-effective, too.
See Linda’s journey