The foundation of our clinical rigor
Proven science drives everything we do. Through rigorous research, we demonstrate how our health technology delivers real results: better patient outcomes, greater value for healthcare systems, and more advanced AI capabilities. Key areas include:
Our AI transforms complex health data into personalized insights and guidance when individuals need it most.
We convert continuous glucose data into personalized guidance that elevates traditional diabetes care standards.
We address interconnected health conditions, turning digital engagement into measurable clinical improvements.
We offer FDA-cleared solutions for T1 and T2 diabetes that simplify treatment while addressing daily health challenges.
Public-Private-Industry Learning Network: Digital Health Expands the Reach and the Role of the Diabetes Care and Education Specialist
Welldoc collaborated with the state of Montana and the Montana Diabetes Digital Health Learning Network (MDDHLN) to integrate digital health into their diabetes program. The intent was to scale services to better support Montana’s rural, frontier communities. This population typically has limited access to health resources and can benefit from innovative tools, like digital health platforms, to help better self-manage their diabetes. This article highlights the many learnings and best practices to efficiently and effectively implement novel cardiometabolic care models that integrate in-person, virtual and digital capabilities.
Malinda Peeples, MS, RN, CDCES, FADCES, Marci Butcher, RD, CDCES, FADCES, Jennifer Scarsi, RD, CDCES, Deb Bjorsness, MPH, BC-ADM, RD, CDCES, Melissa House, MBA, and Janice Macleod, MA, RD, CDCES, FADCES
Use of a Diabetes Digital Health Solution Leads to Improvements in Cardiometabolic Outcomes
In this research, Welldoc demonstrates the potential for digital health solutions focused on diabetes to also address a broader set of cardiometabolic outcomes. A multi-condition approach could help health plans, health systems and care teams to better manage the complexities associated with diabetes, while also addressing other cardiometabolic health comorbid conditions. This work can also support better understanding of digital health engagement patterns and the impact to specific health outcomes, ultimately contributing to the development of predictive models and advanced artificial intelligence capabilities.
Abhimanyu Kumbara, MS, Anand Iyer, PhD, and Mansur Shomali, MD, CMO
Using Early Engagement Data from a Digital Health Solution to Predict Future Glycemia Risk Index (GRI)
In this real-world analysis, Welldoc builds upon prior research to show early engagement data from a digital health solution can predict the future Glycemic Risk Indicator (GRI) metric* in people with type 1 or type 2 diabetes using a continuous glucose monitoring (CGM) device. This research could enable care teams to use early digital health engagement data to build more personalized and optimized care plans for individuals, and supports Welldoc's efforts in developing next-generation digital health solutions that can improve efficiencies and health outcomes.
Reference: Klonoff DC, et al. A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings. J Diabetes Sci Technol. 2023 Sep;17(5):1226-1242. doi: 10.1177/19322968221085273. Epub 2022 Mar 29. PMID: 35348391.
Junjie Luo, MS, Abhimanyu Kumbara, MS, Anand Iyer, Ph, Mansur Shomali, MD, and Gordon Gao, PhD
The Use of a Digital Health Tool with AI-coaching for Patients Enrolled in a Virtual Diabetes Program is Associated with Improvements in Weight and Blood Pressure
In this real-world analysis, Welldoc shows how AI-driven digital coaching can provide personalized, whole-person support for individuals with multiple cardiometabolic conditions, like diabetes, hypertension, and obesity, and amplify the benefits of visits and communication with providers. These outcomes demonstrate how overall cardiovascular risk can be reduced in a high-risk population in a scalable manner, and support Welldoc’s efforts in developing next-generation digital health solutions that can improve health outcomes and increase access to care.
Mansur Shomali, MD, CM, Abhimanyu Kumbara, MS, MBA, and Anand Iyer, PhD, MBA
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
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
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
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
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
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
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
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
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
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
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
The Combined use of rtCGM and a Digital Health Tool Positively Impacts ADCES-7 Behaviors
Individuals living with type 2 diabetes were enrolled in a program that provided the Dexcom G6 system and BlueStar to understand how engagement with the combined solution influenced the Association of Diabetes Care and Education Specialists’ 7 self-care (ADCES7) behaviors. Data showed that those who continuously used real-time CGM (rtCGM) engaged with the app 13% more than those who used it intermittently. In addition, this data showed that engagement with a digital solution, coupled with continuous rtCGM use, can help individuals with T2D — even those who are not prescribed insulin — improve adherence to ADCES7 behaviors.
Guodong Gao
Using a Digital Health Solution to Scale Diabetes Self Care across the State of Montana
Welldoc partnered with The Montana Diabetes Digital Health Learning Network (MDDHLN) to introduce the BlueStar app was into their Diabetes Care and Education Specialist (DCES) program. People with diabetes (PWD) who engaged with the app saw A1C improvement after 6 months of use and 87% of the population with an A1C of 8 or less demonstrated positive health outcomes. The average persistence in app use is 18 months with 20% of people still using the app at 2 years. In addition to this sustained engagement, over 53% of the participants sent the SMART Visit ReportTM to their DCES at least once per month showing ongoing support for DCES’ between office visits. This data shows that using a digital health solution can not only support diabetes education for PWD between office visits but that use also creates value in the information and feedback they receive, thus generating continued engagement.
Marci Butcher, RD, CDCES, FADCES, Deb Bjorsness, MPH, RD, BC-ADM, CDCES, Melissa House, MBA, Jennifer Scarsi, RD, CDCES, and Malinda Peeples MS, RN, CDCES, FADCES
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
Development of Self-Management Behavior Scores and Profiles with Digital Health Data
Assessing the individual factors or "micro behaviors" that lead an individual to better self-management and health outcomes is the key to optimizing a personalized, AI-driven journey. Establishing standardized behavior scores shows how Welldoc is leading the way in understanding how different individuals leverage digital health to support their health. This work will continue the evolution of our product offerings and engagement approaches towards better personalization, engagement and value.
M. Dugas, D. Hu, A. Kumbara, S. Liu, K. Crowley, A. K. Iyer, M. Peeples, M. Shomali, and G. Gao
Blood Pressure Improvement in People Using a Digital Health Solution for Comprehensive Diabetes Self-management
Hypertension affects roughly 70% of people with diabetes (PWD) and is twice as common in PWD compared to those without. Moreover, hypertension in PWD amplifies the risk of chronic kidney disease, cardiovascular complications, ischemic cerebrovascular disease, retinopathy, and sexual dysfunction (Lago RM, Singh PP, Nesto RW. Diabetes and hypertension. Nat Clin Pract Endocrinol Metab. 2007 Oct;3(10):667).
This research is a signifiant step in advancing Welldoc's commitment and expertise in digital health across cardiometabolic conditions, beyond just that in diabetes. It aligns well with the recent launch of the Welldoc platform, which provides a comprehensive, total health approach to chronic conditions and co-morbidities.
Abhimanyu Kumbara, Anand Iyer, and Mansur Shomali
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
Individual Differences in Educational Engagement with a Digital Health Solution
Welldoc and the Center for Health Information and Decision Systems, University of Maryland studied what individual characteristics are associated with the likelihood of engaging with diabetes self-management education and support (DSMES) within a digital health platform. Users who aligned with the demographics most likely to interact with the platform showed that 74% complete at least one session and 49% complete at least one course supporting digital health platforms as a useful medium for delivering DSMES.
Shiping Liu, Mansur Shomali, Abhimanyu Kumbara, Kenyon Crowley, Michelle Dugas, Anand K. Iyer, Malinda Peeples, Guodong Gao
Human vs. Machine: A Comparative Study on CGM Event Detection and Classification
Welldoc partnered with Center for Health Information and Decision Systems, University of Maryland to study if an automated CGM event detection and classification system performed similarly to that achieved by human diabetes experts. Concluding that a system can be trained to detect and classify the CGM patterns and may be useful in automated patient coaching applications, remote monitoring of people with diabetes, and diabetes care decision support for clinicians.
Shiping Liu, Mansur Shomali, Abhimanyu Kumbara, Kenyon Crowley, Michelle Dugas, Anand K. Iyer, Malinda Peeples, Guodong Gao
Identifying Digital Health Habits Correlated with Improved Blood Glucose Control
Logging blood glucose, food, medications, sleep and labs were significant predictors of an improvement of BG. This paper is an introductory paper that aims to identify the "micro-behaviors" or "micro-engagements" that lead patients to better health outcomes. It's the foundation for understanding the next level of AI-driven personalization.
Shiping Liu, Mansur Shomali, Abhimanyu Kumbara, Kenyon Crowley, Michelle Dugas, Anand K. Iyer, Malinda Peeples, Guodong Gao
An Approach for Evaluating and Visualizing CGM Data in People with Diabetes
Welldoc collaborated with Center for Health Information and Decision Systems, University of Maryland to create a visual summary of of the data that can provide both average and variability-based insights for CGM users. The summary showed that visualization of the data based on the key CGM metrics may help users and their clinicians assess overall progress with glucose control over time.
Shiping Liu, Mansur Shomali, Abhimanyu Kumbara, Kenyon Crowley, Michelle Dugas, Anand K. Iyer, Malinda Peeples, Guodong Gao
Let’s partner to elevate cardiometabolic health.
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