Work

Real-World Implementation and Evaluation of a Digital Health Platform for Children Living With Type 1 Diabetes: Protocol for a Real-World Implementation Study

Year: 2026

Type: article

Abstract: Background Digital platforms that integrate continuous glucose monitoring, 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 This study evaluates 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 less than 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 A 1c , continuous glucose monitoring device-derived time in range over 12 months, and diabetes self-care behaviors. 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. Health care improvement outcomes will include patient and caregiver experience, clinician experience, and operational workflow indicators. Results Study funding commenced in January 2023. Patient recruitment began in September 2026, and 7 participants had consented as of October 2026. Data collection is anticipated to conclude by December 2027, with analysis to follow. Study findings are expected to be published in summer 2028. 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.

Source: JMIR Research Protocols

DOI: 10.2196/107634