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Multicenter data confirms CloudCare improves treatment satisfaction and shifts care delivery without compromising glycemic control
New interim results from a four-country prospective cohort extend earlier single-center findings, supporting the generalizability of the CloudCare pathway across diverse diabetes care settings.
Earlier published data from Diabeter showed that CloudCare — our CE-marked population health management application for remote glucose monitoring and triage — was associated with a 60% reduction in face-to-face consultations while glycemic outcomes were maintained (van Beers CAJ et al., BMC Endocrine Disorders 2025;25(1):88).
A logical next question was whether those effects would carry over to clinics with different patient populations, baseline glycemic profiles, and care pathways. Interim results from a four-center prospective observational cohort study now provide that evidence.
Study setup
The cohort included 333 people with type 1 diabetes across four centers: Diabeter (Rotterdam, NL), Maastricht UMC+ (NL), Imelda Hospital (Bonheiden, BE), and Landspítali (Reykjavik, IS). Outcomes were assessed at baseline and at 6 months on the CloudCare pathway, covering treatment satisfaction (DTSQc), diabetes-related distress (PAID-5), glycemic metrics (GMI, time in range, time above and below range), and the number and type of contacts between patients and healthcare professionals.
Key findings at 6 months
Treatment satisfaction improved significantly. Median DTSQc reached +7 points, where 0 indicates no change (p<0.001). Effects were consistent across centers (p=0.42).
Diabetes-related distress remained stable. Median PAID-5 was unchanged at 5.0, with no significant differences between centers.
Glycemic control was maintained. There were no significant changes in GMI (p=0.44), time in range (p=0.71), time below range (p=0.70), or time above range (p=0.61), and no significant differences between centers.
Care delivery shifted, total volume did not. Face-to-face contacts decreased significantly (p<0.001), while non-face-to-face contacts increased significantly (p<0.001). Total contact volume between patients and care teams was unchanged (p=0.27).
Why the consistency across centers matters
The four participating centers differ substantially in baseline glycemic profile, patient age, insulin therapy mix (pump vs. MDI), and the way diabetes care is organized locally. The fact that the direction and magnitude of effects were comparable across these settings suggests that the CloudCare pathway is not dependent on a single optimized environment — it appears to work across heterogeneous real-world diabetes care.
Practical implication for clinics
For diabetes teams under growing pressure from rising patient numbers and expanding data volumes, the multicenter results point to a tangible model: continuous insight between visits, automated triage at population level, and clinician time concentrated where it changes outcomes — without trading away clinical control or patient experience.
Longer-term follow-up will further clarify durability of these effects and impact on care efficiency at scale.