Five-Year Glycemic Trends in a Remote Diabetes Monitoring Program (RDMP): Contributions of Program Engagement and Evolving Pharmacotherapy Adoption and Adherence
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Background
Digital diabetes programs have expanded quickly, but evidence of durable long-term benefit remains limited. In addition, as diabetes treatment guidelines changed to include cardiorenal-protective antihyperglycemics as first-line therapy, the effects of their adoption on glycemic control and program engagement within these programs remain poorly understood.
Objective
To characterize longitudinal trends in glycemic control and estimate the extent to which these trends are associated with time-invariant and time-varying domains, among adults with T2D participating in Teladoc Health’s Remote Diabetes Monitoring Program (RDMP).
Methods
This was a retrospective, longitudinal cohort study of adults with T2D participating in the Teladoc RDMP from 2021-2025. Domains were split into time-invariant (i.e. demographics and baseline clinical characteristics) and time-varying covariates (e.g. antihyperglycemic treatment complexity/adherence, program utilization/engagement, and adoption of cardiorenal protective antihyperglycemics). Primary outcome was estimated A1c (eA1c), calculated from fasting blood glucose (FBG) measurements captured through cellular-enable smart glucose meters. Longitudinal mixed-effects models were used to estimate adjusted annual trends in eA1c over 5 years, and Gelbach decomposition to quantify statistical contributions across domains. Secondary analyses examined attainment of eA1c <7% using GEE and complementary decomposition methods.
Results
A total of 56,754 members with mean age 64.2 (SD 10.4) and 49% female were included in the analysis. Mean eA1c declined by 0.06 percentage points per year (95% CI −0.06 to −0.06) and remained significantly lower after full adjustment for demographic, antihyperglycemic treatment and cardiorenal-protective therapy adherence, and program engagement factors (β=−.04 percentage points/year; 95% CI −.04 to −.03), demonstrating durable glycemic improvement over the five-year study period. The full model attenuated 48.6% of the declining glycemic trend, indicating that glycemic improvements were only partially explained by demographic, treatment, and engagement factors. Gelbach decomposition attributed most of the difference between the base and fully adjusted trends to cardiorenal-protective therapies (170.8%). Program engagement factors contributed an offsetting share of the explained trend (−71.9%), although greater FBG monitoring and application engagement were associated with lower eA1c in adjusted analyses, while treatment history and complexity contributed minimally (1.1%). Adjusted odds of attaining eA1c <7% increased 8.0% annually (OR 1.08; 95% CI 1.07-1.09), corresponding to a 1.21-percentage-point annual increase in probability; adjusted predicted glycemic control increased from 75.2% in 2021 to 80.1% in 2025.
Conclusion
In this long-term experience with a large cohort of patients enrolled in a digital diabetes management program, progressive improvement in glycemic control was observed over the five years of follow-up. The pattern of glycemic improvement was consistent regardless of background exposure to GLP1-RAs and SGLT-2is therapies, including in participants who were never exposed to these therapies. These observations support guideline recommendations which include both the use of indicated medical therapies as well as lifestyle modification which can be facilitated with digital monitoring programs.
