Tidepool Showcases New Real-World Clinical Data and Landmark Women’s Health Initiative at ADA 2026

Key Takeaways

• 24‑week program cut HbA1c by 1.59% in safety‑net clinics
• Time‑in‑Range rose 13.4% using Tidepool’s CGM dashboard
• Women’s health initiative aims to build largest opt‑in biometric dataset
• Study shows approximate meal logging still improves post‑prandial glucose for AID users

Pulse Analysis

Tidepool’s recent showcase at the American Diabetes Association highlighted how real‑world evidence is reshaping care delivery for the most vulnerable patients. By integrating continuous glucose monitoring into a remote patient monitoring workflow, the 24‑week Diabetes Care Management Program enabled clinicians to triage outreach efficiently, delivering a 1.59% drop in HbA1c and a 13.4% rise in Time‑in‑Range. These outcomes demonstrate that data‑driven tools can generate clinically significant improvements without straining limited resources, a model that could be replicated across safety‑net health systems nationwide.

Equity in diabetes research received a dedicated push through Tidepool’s women’s health initiative, which seeks to compile the largest opt‑in, anonymized collection of biometric and device data. Partnering with the Diabetes Center Berne, ŌURA and other health leaders, the effort targets under‑represented lifecycle stages such as menstrual cycles and menopause. By providing a robust evidence base, the dataset promises to inform targeted therapies and device algorithms tailored to women, addressing a long‑standing gap in clinical insights and fostering more personalized treatment pathways.

The third pillar of Tidepool’s announcement centered on reducing the daily burden of meal logging for type 1 diabetics using automated insulin delivery (AID) systems. A collaborative study revealed that even when users log meals approximately, consistent patterns still yield better post‑prandial glucose outcomes. This insight supports Tidepool Loop’s roadmap to relax strict carb‑counting requirements, leveraging real‑world data to refine AID algorithms. As the industry moves toward more intuitive, user‑friendly solutions, such research underscores the potential for technology to simplify management while maintaining—or improving—glycemic control.