What question did this study set out to answer?

This study aims to evaluate the impact of continuous glucose monitoring (CGM) on glycemic control in adults with Type 2 Diabetes (T2D) enrolled in a digital health program.

June 7, 2026

1943-P: Improved CGM Measured Glycemic Control in Adults with Type 2 Diabetes in an Integrated Digital Health Program: Real-World Data from Primary Care and Endocrinology Clinics

Key Points

This study aims to evaluate the impact of continuous glucose monitoring (CGM) on glycemic control in adults with Type 2 Diabetes (T2D) enrolled in a digital health program.
Analyzed data from adults with T2D enrolled in iHealth Unified Care program from 2019-2025.
Utilized linear mixed-effects models to assess key CGM metrics like TIR, GMI, and GRI compared to a matched BGM control group.
Participants included 463 individuals with an average age of 64.8 years, stratified by baseline glycemic control and insulin use.
TIR increased by 0.16% weekly and GRI decreased by 0.17 per week (p<0.001).
In participants with baseline GMI ≥8.0% (n=64), TIR improved by +1.14% per week (p<0.001).
Average HbA1c decreased from 8.22% to 7.40% at 3 months in CGM users, compared to a decrease of −0.55% in matched BGM group (p=0.07).

Abstract

Introduction and Objective: CGM is increasingly used among adults with T2D, including non-insulin-treated patients in primary care. It may enable more timely assessment and care quality control during ongoing digital health interventions. This study evaluated weekly changes in CGM-derived glycemic metrics and compared HbA1c outcomes with BGM users in a digital health program. Methods: Data from adults with T2D enrolled in the iHealth Unified Care program across 48 clinics (46 primary care, 2 endocrinology) from 2019-2025 were analyzed. Participants used CGM or BGM synced with a care coordination platform and a mobile app. Physicians supervised care teams, including RDN and CDCES, delivered quarterly visits and daily coaching. Key CGM metrics, TIR, GMI and Glycemic Risk Index (GRI) were analyzed using linear mixed-effects models, stratified by baseline glycemic control and insulin use. A retrospective control group using BGM was matched to CGM users with HbA1c data by age, gender, baseline HbA1c, and medication use. Results: 463 participants (average age 64.8yr, 47.8% female, 64.2 % insulin users, 35.8% non-insulin users) with T2D who have completed at least one week of 70% CGM wear were selected. Their baseline average GMI was 7.03%, TIR increased by 0.16% and GRI decreased by 0.17 per week (p0.001). Participants with baseline GMI ≥8.0% (n=64) showed larger improvement (+1.14% TIR/week, +13.68% by 12 weeks, p0.001). Improvements were similar among insulin and non-insulin users. In a subset with HbA1c data (n=66), average HbA1c decreased from 8.22% to 7.40% at 3 months (−0.82%), slightly more reduction than matched BGM group (−0.55%, p=0.07 comparing CGM vs BGM users). Conclusion: Implementation of CGM in an integrated digital health program was associated with significant weekly improvements in CGM-derived metrics, supported by corresponding HbA1c reductions, demonstrating the clinical value of CGM metrics for timely care quality assessment in digital diabetes care. Disclosure L. Wang: Employee; Current; iHealth Labs, Inc. Y. Sun: Employee; Current; iHealth Labs, Inc. C. Zhang: None. W. Hou: Employee; Current; iHealth Labs, Inc. N. Ghamrawi: Employee; Current; iHealth Labs, Inc. Z. Liu: None. L.A. Groppo: None. R.S. Stafford: Research Support; Current; iHealth Labs, Inc.

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