The growing prevalence of chronic diseases such as diabetes, cardiovascular diseases (CVDs), and hypertension calls for innovative strategies for disease surveillance and management. Digital health technologies (DHTs) offer a transformative approach to chronic disease management through real-time, personalized health monitoring and enhanced patient engagement; however, they also present inherent limitations. This narrative review synthesizes current applications of DHTs in the management of diabetes, CVDs, and hypertension, with a focus on advancements in artificial intelligence, digital therapeutics, and remote patient monitoring. A framework of solutions is proposed, comprising six key pillars: (1) data accuracy and standardization through artificial intelligence-enhanced calibration and multisensor fusion; (2) user engagement and compliance supported by gamification and behavioral science; (3) interoperability and clinical integration through Fast Healthcare Interoperability Resources and Health Level Seven standards; (4) accessibility and cost barriers addressed through frugal innovation, open-source platforms, reimbursement policies, and user education; (5) privacy and ethics, employing blockchain and federated learning for secure data governance; and (6) regulatory and policy considerations, advocating for global harmonization and supportive reimbursement models. This framework aims to enhance the reliability, accessibility, and effectiveness of DHTs in chronic disease management. The review provides actionable insights for stakeholders, including developers, healthcare professionals, and policymakers, on optimizing the design, implementation, and regulation of DHTs, ultimately improving chronic disease outcomes.
Keywords: Digital health technologies; artificial intelligence; cardiovascular diseases; chronic disease management; diabetes mellitus; hypertension; remote patient monitoring; wearable devices.
© The Author(s) 2025.