Clinical Research

A resource to get the latest clinical evidence, studies, models and frameworks to advance knowledge of how best to manage chronic health conditions.

Welldoc is committed to our scientific research, advancing digital health, transforming chronic care, and driving value across healthcare. Areas of focus include digital health engagement, advancing artificial intelligence, cardiometabolic condition outcomes, cost and value, and real-world integration into the health ecosystem.

Behavioral Factors, Empowerment Bolsters Self-Management

The increasing use of web-based or technology-enabled solutions for health management presents opportunities to improve patient self-management…
A Novel Approach to Continuous Glucose Monitoring
Health Plan Opportunities to Control Costs Related to Chronic Disease
Moving the Dial in Lowering and Controlling A1C
The Power of Integrated Peer Support and Digital Health
A Novel Approach to Continuous Glucose Monitoring
Health Plan Opportunities to Control Costs Related to Chronic Disease
Health Plan Opportunities to Control Costs Related to Chronic Disease
Moving the Dial in Lowering and Controlling A1C
The Power of Integrated Peer Support and Digital Health
The Power of Integrated Peer Support and Digital Health
Topics
Clinical Bibliography Theme
Type
Clinical Bibliography Type
Healthcare AnalyticsPatient Experience
welldoc article
Article
Impact of a Combined Continuous Glucose Monitoring–Digital Health Solution on Glucose Metrics and Self-Management Behavior for Adults With Type 2 Diabetes: Real-World, Observational Study
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).

Abhimanyu B Kumbara; Anand K Iyer; Courtney R Green; Lauren H Jepson; Keri Leone; Jennifer E Layne; Mansur Shomali

Healthcare AnalyticsPatient Experience
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Poster
Examining The Ability of Different Machine Learning Approaches to Predict Health Outcomes with a Digital Health Platform
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.

Mansur Shomali, MD, CM, Abhimanyu Kumbara, MS, Junjie Luo, MS, Anand Iyer, PhD, Gordon Gao, PhD

Healthcare AnalyticsPatient Experience
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Poster
A Real-Time CGM-Enabled Digital Health Tool Highlights a Relationship Between Sentiment and Diabetes Distress in People Using Bolus Insulin
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.

Malinda Peeples, MS, RN, CDCES, FADCES, Mansur Shomali, MD, CM, Abhimanyu Kumbara, MS, Anand Iyer, PhD, Jean Park, MD, Grazia Aleppo, MD

Healthcare AnalyticsPatient Experience
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Poster
Using Early Engagement Data from a Digital Health Solution to Predict Future Health Outcomes
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.

Junjie Luo, MS, Abhimanyu Kumbara, MS, Anand Iyer, PhD, Mansur Shomali, MD, CM, Gordon Gao, PhD 

Healthcare AnalyticsPatient Experience
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Poster
The Use of a Novel CGM-Informed Insulin Bolus Calculator Mobile Application by People with Type 1 and Type 2 Diabetes Improves Time in Range
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.

Mansur Shomali, Colleen Kelly, Anand Iyer, Jean Park, Grazia Aleppo

Healthcare AnalyticsPatient Experience
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Poster
A Digital Health Solution with a CGM-informed Insulin Calculator Reduces Diabetes Distress in Individuals with Type 1 and Type 2 Diabetes
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.

Mansur Shomali, MD, CM, Abhimanyu Kumbara, MS, Anand Iyer, PhD, Jean Park, MD, Grazia Aleppo, MD

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Taking Diabetes Self-Management to the Next Level