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
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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

Healthcare AnalyticsPatient Experience
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Presentation
Using Early Engagement Data from a Digital Health Solution to Predict Future Engagement Patterns
The adoption and implementation of a digital health solution can provide early CGM and self-management behavior data, via engagement patterns and segmentation, to help predict engagement outcomes associated with later points in the patient journey.

Abhimanyu Kumbara, MS, MBA

Healthcare AnalyticsPatient Experience
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Poster
Safety of a CGM-Informed Insulin Bolus Calculator Mobile Application for People with Type 1 and Type 2 Diabetes
Welldoc® and investigators at Northwestern University in Chicago partnered to demonstrate the safety of an investigational insulin bolus calculator (IBC*), based on continuous glucose monitoring (CGM) data. This IBC was designed to help people with diabetes dose their insulin. The IBC, embedded into Welldoc's FDA cleared BlueStar® mobile phone app, was designed to translate CGM data into simple trend arrows, indicating bolus insulin dose recommendations. The study demonstrated the saftey of the IBC, with no reported increased hypoglycemia measurements.

Mansur E. Shomali, Colleen Kelly, Anand K. Iyer, Grazia Aleppo

Healthcare AnalyticsPatient Experience
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Presentation
The Use of a Real-time CGM and Digital Health Solution Lowered A1C in People with Type 2 Diabetes
Welldoc® in collaboration with Dexcom developed a study to show how the utilization of a real-time CGM (rtCGM) system, Dexcom G6, in combination with Welldoc’s digital health solution, BlueStar®, can help support individuals with diabetes taking medications, lower their A1C. The study concluded that the combination of rtCGM and a digital health solution significantly improved an individual’s A1C after 12 and 24 weeks of use, regardless of baseline A1C or degree of CGM wear. Even though there was a decrease in A1C for all study participants, individuals who started with a high A1C, along with those who continuously used CGM, saw a greater decrease in their A1C.

Abhimanyu Kumbara, Anand Iyer, Keri Leone, Mansur Shomali

Healthcare AnalyticsPatient Experience
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Presentation
Real-world Digital Health Data Demonstrate the Utility of the Glycemia Risk Index (GRI) as a Composite CGM Metric
Welldoc® and Carey Business School of Johns Hopkins University (formerly CHIDS, University of Maryland) worked together to study how continuous glucose monitoring (CGM) and a digital health solution can help support better glycemic outcomes for individuals with type 1 and type 2 diabetes. A Glycemia Risk Index (GRI) metric was applied to this study to assist with the basic clinical interpretation of CGM data. GRI was calculated for each individual and classified into the five GRI zones from lowest (A: best) to highest (E: worst), with a breakdown by gender, age, and diabetes type. Our results showed that diabetes type was not a factor in GRI improvement, but, individuals whose baseline GRI started in higher zones improved GRI by at least 1 zone—supporting the use of CGM and a digital health solution in self-managing glycemia. In addition, the demographic data shows that GRI was significantly lower in females and individuals 65 years and older. The culmination of GRI and demographic data can help healthcare professionals support and manage individuals and populations with diabetes.

Junjie Luo, Mansur E. Shomali, Abhimanyu Kumbara, Anand K. Iyer, Guodong “Gordon” Gao

Healthcare AnalyticsPatient Experience
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Poster
Applying the Glycemia Risk Index (GRI) to User Data from a Digital Health Tool Reveals Patterns of Engagement That Differ by Type of Diabetes
Welldoc® and the Carey Business School of Johns Hopkins University (formerly CHIDS at University of Maryland) continue to research how a digital health solution, combined with CGM data, can help individuals living with diabetes improve lifestyle factors and support better glycemic outcomes. In this study, we applied the Glycemia Risk Index (GRI) metric to assist with the basic clinical interpretation of CGM data. Our findings show that the average individual with type 1 and type 2 diabetes improved their GRI by 6 points during the first 14 days of use of the combined CGM and digital health tool. Individuals with type 2 diabetes that engage in digital health features like medications and lifestyle increased the probability of improved GRI, whereas individuals with type 1 diabetes saw improvement based on CGM wear time. The continued use of the GRI metric will help us demonstrate self-management and behavior outcomes of individuals using a combination of a digital health solution and CGM while extending support for diabetes populations.

Junjie Luo, Mansur E. Shomali, Abhimanyu Kumbara, Anand K. Iyer, and Guodong “Gordon” Gao

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Taking Diabetes Self-Management to the Next Level