Accepted for/Published in: JMIR Research Protocols
Date Submitted: Jul 24, 2026
Open Peer Review Period: Jul 31, 2026 - Aug 24, 2026
Date Accepted: Sep 30, 2026
(closed for review but you can still tweet)
Protocol for the Real-World Implementation and Evaluation of a Digital Health Platform for Children Living with Type 1 Diabetes
ABSTRACT
Background:
Digital platforms that integrate continuous glucose monitoring (CGM), patient-generated data, and clinical decision support could enable more proactive pediatric type 1 diabetes (T1D) care. Sustained uptake of digital platforms in routine practice is limited, and the evidence of effectiveness is mixed. Implementation-science approaches are needed to clarify how context, workflows, and strategies shape adoption and outcomes. Haibu Diabetes is a new platform that brings together wearable, patient-reported, and clinical diabetes data to generate personalized, data-driven insights for patients and clinicians.
Objective:
We will evaluate the clinical effectiveness and implementation processes of Haibu Diabetes in routine pediatric T1D care using a hybrid design guided by an Implementation Research Logic Model.
Methods:
We will conduct a nonrandomized, quasi-experimental, type 2 hybrid implementation-effectiveness trial at a hospital that provides multidisciplinary pediatric diabetes care. Youth aged 3 to <18 years with T1D and caregivers will be onboarded to Haibu Diabetes as part of routine workflows; health care providers will use a clinician dashboard to review data, assign tasks/forms, and communicate asynchronously. Effectiveness analyses will compare Haibu Diabetes users to a matched control group drawn from the BC Pediatric Diabetes Registry. Effectiveness outcomes are hemoglobin A1c (HbA1c), continuous glucose monitoring device-derived time-in-range (TIR) over 12 months, and diabetes self-care behaviours. Implementation outcomes will be assessed using mixed methods guided by an Implementation Research Logic Model that links determinants, implementation strategies, mechanisms, and outcomes. These outcomes will include reach, adoption, feasibility, acceptability, and maintenance. Healthcare improvement outcomes will include patient and caregiver experience, clinician experience, and operational workflow indicators.
Results:
Recruitment and data collection are planned; findings will report comparative glycemic and self-care outcomes and describe determinants and mechanisms influencing implementation.
Conclusions:
This trial will generate real-world evidence on both effectiveness and the conditions required to implement and sustain a data-integrating digital platform in pediatric T1D care, informing scale-up and optimization. Clinical Trial: NCT07712809
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