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

Abstract

BackgroundThe BlueStar (Welldoc) digital health solution for people with diabetes incorporates data from multiple devices and generates coaching messages using artificial intelligence. The BlueStar app syncs glucose data from the G6 (Dexcom) real-time continuous glucose monitoring (RT-CGM) system, which provides a glucose measurement every 5 minutes. ObjectiveThe objective of this real-world study of people with type 2 diabetes (T2D) using the digital health solution and RT-CGM was to evaluate change in glycemic control and engagement with the program over 3 months. MethodsParticipants were current or former enrollees in an employer-sponsored health plan, were aged 18 years or older, had a T2D diagnosis, and were not using prandial insulin. Outcomes included CGM-based glycemic metrics and engagement with the BlueStar app, including logging medications taken, exercise, food details, blood pressure, weight, and hours of sleep. ResultsParticipants in the program that met our analysis criteria (n=52) were aged a mean of 53 (SD 9) years; 37% (19/52) were female and approximately 50% (25/52) were taking diabetes medications. The RT-CGM system was worn 90% (SD 8%) of the time over 3 months. Among individuals with suboptimal glycemic control at baseline, defined as mean glucose >180 mg/dL, clinically meaningful improvements in glycemic control were observed, including reductions in a glucose management indicator (–0.8 percentage points), time above range 181-250 mg/dL (–4.4 percentage points) and time above range >250 mg/dL (–14 percentage points; all P<.05). Time in range 70-180 mg/dL also increased by 15 percentage points (P=.016) in this population, which corresponds to an increase of approximately 3.5 hours per day in the target range. Over the 3-month study, 29% (15/52) of participants completed at least one engagement activity per week. Medication logging was completed most often by participants (23/52, 44%) at a rate of 12.1 (SD 0.8) events/week, and this was closely followed by exercise and food logging. ConclusionsThe combination of an artificial intelligence–powered digital health solution and RT-CGM helped people with T2D improve their glycemic outcomes and diabetes self-management behaviors.