July 25, 2024




Teladoc Health (NYSE: TDOC) unveiled new research showcasing its AI-driven predictive modeling capabilities to aid members with type 2 diabetes. The studies, presented at the American Diabetes Association’s 84th Scientific Sessions, highlight a 3X increase in engagement and an additional 0.4 reduction in A1c (from 8.2% to 7.8%) for members receiving personalized health nudges. These nudges, powered by AI, identify at-risk individuals for early intervention. Additionally, members receiving tailored next-best actions in their emails were 50% more likely to engage with health coaches. This underscores Teladoc’s ability to forecast health risks and enhance preventive measures.

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  • 3X increase in engagement among diabetes members.

  • An additional 0.4 reduction in A1c (from 8.2% to 7.8%) due to personalized health nudges.

  • 50% increased likelihood of health coach engagement from personalized emails.

  • Effective use of AI in predicting health risks more than a year in advance.

Teladoc Health has released compelling data demonstrating the effectiveness of their predictive AI-modeling in managing type 2 diabetes. By using AI to identify individuals at risk of uncontrolled diabetes, Teladoc can target these individuals with personalized health nudges, leading to a significant 3X increase in engagement and a notable reduction in A1c levels from 8.2% to 7.8%. This reduction is clinically meaningful as it lowers the risk of diabetes complications.

Such results are promising because they highlight how data-driven approaches can enhance personal health management. Early identification and timely intervention are key strategies in chronic disease management and Teladoc’s AI model appears effective in these areas. For stakeholders, particularly healthcare providers and insurers, these findings suggest potential for improved patient outcomes and cost savings.

Given the escalating prevalence of type 2 diabetes, interventions that enhance management and engagement are crucial. However, it’s essential to critically evaluate the scalability and real-world application of these findings. While the results are based on substantial data, broader application across diverse demographics will be key to confirming these benefits on a larger scale.

From a financial standpoint, Teladoc Health’s new data underscores the potential for their diabetes management program to deliver cost savings and drive member engagement. The ability to reduce A1c levels by 0.4% is significant, as it can lead to decreased healthcare costs associated with complications from uncontrolled diabetes.

The increased engagement metrics also imply higher utilization rates of Teladoc’s services, which could translate to greater revenue streams. Personalized health interventions are a growing trend in the healthcare sector and Teladoc’s ability to leverage AI for predictive modeling places them at the forefront of this innovation. This could enhance their competitive position and appeal to both current and potential clients, including employers and health plans looking for effective chronic disease management solutions.

However, investors should consider the sustainability of these outcomes. While the data is promising, the long-term financial impact will depend on consistent performance and broader adoption. It’s also worth noting the potential regulatory and data privacy challenges associated with AI-driven health interventions.

Teladoc Health’s use of predictive AI-modeling to enhance diabetes management represents a significant technological advancement in digital health. AI’s ability to accurately forecast risk levels and personalize health interventions is transformative, providing timely and actionable insights that can improve patient outcomes.

The technology behind these personalized health nudges and tailored email content is based on sophisticated algorithms that analyze a multitude of data points. This approach not only predicts but also helps in preemptively managing chronic conditions by prompting behavioral changes through digital engagements. The 50% higher engagement rate in coaching services highlights the efficacy of these digital nudges in driving user participation and adherence to health programs.

For the tech community, Teladoc’s advancements showcase how AI can be effectively integrated into health services to provide real-time, personalized care. This could pave the way for further innovations in other chronic disease management areas.

Nevertheless, the efficacy of these AI models in real-world settings beyond controlled studies will need continuous validation. Ensuring the accuracy and fairness of AI predictions, while addressing ethical considerations, remains critical for broader acceptance and trust in such technologies.









Proprietary model forecasts risk of uncontrolled diabetes with high degree of accuracy, enabling more effective, timely interventions

PURCHASE, NY, June 24, 2024 (GLOBE NEWSWIRE) — 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.

The full abstracts are available on the ADA website here.

About Teladoc Health

Teladoc Health empowers all people everywhere to live their healthiest lives by transforming the healthcare experience. As the world leader in whole-person virtual care, Teladoc Health uses proprietary health signals and personalized interactions to drive better health outcomes across the full continuum of care, at every stage in a person’s health journey. Teladoc Health leverages more than two decades of expertise and data-driven insights to meet the growing virtual care needs of consumers and healthcare professionals. For more information, please visit www.teladochealth.com.

Source: Teladoc Health, Inc. – General

Contact 
Lou Serio 
[email protected]
+1 202-569-9715

A photo accompanying this announcement is available at









FAQ



What impact did Teladoc Health’s AI-modeling have on diabetes members’ engagement?


Teladoc Health’s AI-modeling led to a 3X increase in engagement among diabetes members.


How much did A1c levels reduce for members targeted with AI-powered personalized health nudges?


A1c levels reduced by an additional 0.4, from 8.2% to 7.8%, for members targeted with AI-powered personalized health nudges.


What was the increase in likelihood of engaging with a health coach for members receiving personalized next-best actions via email?


Members receiving personalized next-best actions via email were 50% more likely to engage with a health coach.


How accurate is Teladoc Health’s AI in forecasting the risk of uncontrolled diabetes?


Teladoc Health’s AI can proactively identify at-risk individuals for uncontrolled diabetes more than a year in advance.


What event was the new data from Teladoc Health presented at?


The new data from Teladoc Health was presented at the American Diabetes Association’s 84th Scientific Sessions.





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