Beyond Connected Diabetes Technologies: Toward an Orchestrated Digital Healthcare Ecosystem for Diabetes Care

Diabetes care increasingly relies on continuous glucose monitoring (CGM), automated insulin delivery, connected devices, digital nutrition tools, and artificial intelligence (AI). However, data connectivity does not ensure timely, accountable clinical action. Building on World Health Organization digital health principles and established diabetes care models, we propose the Digital Diabetes Care Ecosystem (DDCE), a conceptual implementation framework centered on clinical orchestration. Its distinctive contribution is an auditable signal-to-action accountability pathway comprising seven elements: signal identification and provenance, risk stratification, assigned professional responsibility, defined response intervals, permitted actions and automation boundaries, escalation procedures, and outcome reassessment. DDCE extends existing digital diabetes ecosystems and the Chronic Care Model by specifying how digital signals may be translated into coordinated, time-bounded, and reviewable care. Medical nutrition therapy is a core application, integrating CGM and dietary data with dietitian-led assessment, personalized nutrition interventions, and critical appraisal of AI-generated dietary recommendations. Diabetes self-management education and support (DSMES), guided by the seven self-care behaviors of the Association of Diabetes Care & Education Specialists (ADCES7), links professional interventions to patient-centered self-management and measurable behavioral outcomes. Four testable propositions address data integration, signal-to-action performance, human–AI safety, and continuous learning. The proposed framework requires prospective validation, with outcomes extending beyond glycated hemoglobin and algorithmic accuracy to include timeliness, therapeutic inertia, dietary and self-management behaviors, safety, clinician workload, equity, and cost.