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
Topics
Type
Healthcare Analytics
Poster
Evaluating the Impact of a Combined Real-Time CGM/Digital Health Solution on Glucose Control for People with Type 2 Diabetes
Welldoc®, a digital health leader revolutionizing chronic care, today announced the presentation of data at the 15th International Conference on Advanced Technologies & Treatments for Diabetes (ATTD), evaluating how the combination of real-time CGM (rtCGM) with a digital health solution impacts glucose control for individuals with Type 2 diabetes not treated with insulin. For all participants and subgroups that were examined, the time in range (TIR) and glucose management indicator (GMI) improved significantly, demonstrating that a combined CGM and digital therapeutic solution has the potential to improve Type 2 diabetes management and glycemic control.
Abhimanyu Kumbara, Anand Iyer, Keri Leone, Mansur Shomali
Healthcare Models and FrameworksPatient Experience
Article
Complementarity of Digital Health and Peer Support: “This Is What’s Coming”
This collaborative study, with Dr. Edwin Fisher PhD of University of North Carolina, Peers for Progress and Vanguard Medical Group, assess the effectiveness of the Welldoc solution and peer support in providing health management and education for adults with Type 2 Diabetes.
Patrick Y. Tang, Janet Duni, Malinda M. Peeples, Sarah D. Kowitt, Nivedita L. Bhushan, Rebeccah L. Sokol and Edwin B. Fisher
Patient ExperiencePopulation HealthReal World Evidence
White Paper
Estimating the Economic Value of a Digital Therapeutic in Type 2 Diabetes
Truven Health Analytics, part of IBM Watson Health, conducted an analysis of commercial and Medicare consumers within the MarketScan databases for Welldoc. The research findings show Welldoc's ability to help lower and control A1C and generate savings per user per month.
IBM Watson Health
Healthcare Models and FrameworksPopulation Health
Article
A Payer Digital Health Study Shows Scalable Approach to Cost Savings and Outcomes
Health plans must find a scalable solution that reduces healthcare use and costs among those with chronic conditions. This study from Aetna/CVS Health, Welldoc, and LifeScan explores health plan strategies that take advantage of digital health relative to outcomes.
David Shearer, MD, Anand Iyer, PhD, and Malinda Peeples, MS
Healthcare Analytics
Poster
Consistent Engagement with a Digital Health Solution Enhances the Effect of Medication Changes on Blood Glucose Control
This research, conducted by Welldoc in collaboration with the Robert H. Smith School of Business Center for Health Information and Decision Systems, evaluated the performance of a Welldoc automated method for detecting significantly adverse glucose events and, further, classifying those events by level of severity.
Shiping Liu, Mansur Shomali, Abhimanyu Kumbara, Kenyon Crowley, Michelle Dugas, Anand K. Iyer, Malinda Peeples, Guodong Gao
Healthcare Analytics
Poster
Identifying Digital Health Habits Correlated with Improved Blood Glucose Control
This research, conducted by Welldoc in collaboration with the Robert H. Smith School of Business Center for Health Information and Decision Systems, evaluated the performance of a Welldoc automated method for detecting significantly adverse glucose events and, further, classifying those events by level of severity.
Shiping Liu, Mansur Shomali, Abhimanyu Kumbara, Kenyon Crowley, Michelle Dugas, Anand K. Iyer, Malinda Peeples, Guodong Gao
