Teladoc Health (NYSE: TDOC), the global leader in whole-person virtual care, released new data today from two studies, presented at the American Diabetes Association’s 84th Scientific Sessions, that illustrate the company’s unmatched predictive modeling capabilities to help members with type 2 diabetes control their blood sugar through participation in Teladoc Health’s diabetes management program.
The new data shows a 3X increase in engagement leading to an additional 0.4 reduction in A1c (8.2 to 7.8) for members targeted with personalized health nudges (notifications that are sent to mobile or cellular connected devices) after being identified as at-risk for uncontrolled diabetes through artificial intelligence (AI). Additionally, diabetes members that received personalized next-best actions, powered by predictive modeling, in their weekly email were 50% more likely to engage with a health coach.
“Teladoc Health has a long-standing history of successfully using data to improve health outcomes for our members, and new applications of AI are helping us accelerate our impact,” said Sal Shafiq, chief data and analytics officer at Teladoc Health. “Our ability to use data to empower members in the moment is crucial, but the true power lies in our ability to predict health risks and make prevention a reality.”
Highlights from both studies are included below:
The Impact of Personalized Health Nudges on Clinical Outcomes
In this study, the company examined the effectiveness of personalized health nudges for improvement in self-monitoring of type 2 diabetes, particularly for those individuals that were previously identified as being at-risk for uncontrolled outcomes in the future. Data from the study conducted over nine months shows a clear connection between program engagement and improved clinical outcomes, with a 3X increase in engagement as well as an additional 0.4 reduction in A1c with members going from 8.2% to 7.8%.
The results come on the heels of previous research that demonstrated Teladoc Health’s ability to proactively identify a person at-risk for uncontrolled outcomes more than a year in advance using AI. The ability of AI to forecast this is crucial for the early detection and management of diabetes; it allows for more timely, personalized interventions to avoid complications, improve outcomes, and better control costs for employers and health plans.
The Impact of Personalized Content on Program Engagement and Utilization
Previous research indicates the use of dedicated coaching can improve diabetes control. In this study, the company evaluated how tailored email content can be used to increase 1:1 coaching in digital programs for type 2 diabetes. These newsletters used predictive models to suggest the next best action (coaching, digital activities, etc.) for managing their chronic condition based on members' engagement with Teladoc Health’s services. Members that received personalized next-best actions, powered by predictive modeling, in their enhanced weekly email were 50% more likely to engage in coaching services, compared to those who received the standard newsletter.
Studies are conducted by Teladoc Health to evaluate the efficacy and impact of the company's programs, particularly for partners and clients. Teladoc additionally publishes clinical research through the peer review process.