Clinical Research

In this journal article, Welldoc builds upon prior research focused on advancing chronic care through the use of digital health and real-time connected devices. This study examines the impact of combing real-time continuous glucose monitoring (RT-CGM) with an AI-driven digital health solution on helping individuals with type 2 diabetes to improve their glycemic metrics like time in range (TIR).

In this study, Welldoc builds upon our prior research on advancing digital health AI through machine learning (ML) and connection with real-time connected devices, such as continuous glucose monitoring (CGM). This study examines how CGM data combined with digital health My E-Diary for Activities and Lifestyle (MEDAL) data and behavior patterns can lead to better understanding of optimal digital health feature utilization and ML models, which can be used to predict future Time in Range (TIR). This research continues Welldoc's efforts in advancing our AI models and developing next generation digital health solutions geared towards personalized prevention and prediction.

Welldoc continues to focus our research on advancing digital health through connection with real-time connected devices, such as continuous glucose monitoring (CGM). Building on prior clinical research, which showed an improvement in glucose outcomes and reduction in diabetes distress with the use of an app-based CGM-informed insulin bolus calculator, this study demonstrates qualitatively how these same individuals interacted with the technology and how it made them feel. People with type 1 and type 2 diabetes who inject bolus insulin often find their diabetes to be overwhelming. Here, Welldoc found there was a significant proportional connection between those who felt less distress about their diabetes and felt positively about the technology, versus those who felt more distressed. This research reinforces the power of combining digital health with CGM in not only supporting individuals with a more personalized digital health solution that they enjoy using, but also providing clinicians with additional tools to support people with diabetes distress management.

Building on Welldoc's research focused on advancing digital health through connection with real-time connected devices, such as continuous glucose monitoring (CGM), this study demonstrates how utilization of early CGM and My E-Diary for Activities and Lifestyle (MEDAL) behavior patterns may support prediction of future health outcomes, such as Time in Range (TIR). Here, Welldoc establishes that analysis of the first 30 days of CGM + MEDAL engagement patterns can lead to accurately predicting future TIR patterns. This research reinforces the power of combining CGM with digital health in not only supporting individuals with more personal and precise insights, but also in developing highly accurate machine learning models into the next generation of AI and predictive digital health solutions.

Building on Welldoc's previous work on the safety of using CGM data for insulin dose calculations, this study combines results from two clinical trial sites, MedStar Health Research Institute and Northwestern University, to demonstrate that people using the CGM insulin bolus calculator (IBC) embedded into Welldoc's FDA cleared BlueStar® mobile application improved their time in range without increasing hypoglycemia. Overall, there was a clinically meaningful increase in time in range of 4%. The improvement was greater in people who had type 2 diabetes (6.5%) and in those who used the IBC between 30 to 60 times per month (6.0%). This analysis reinforces the benefit of combining a digital health tool with CGM and other emerging real-time device innovations. This study adds to the continued research Welldoc is leading to demonstrate the value of digital health tools in supporting chronic condition self-management, positive health outcomes.

A digital health solution that assists people with diabetes self-management and insulin dosing may reduce diabetes distress, particularly around their treatment regimen and interpersonal relationships.