Continuous monitoring technologies reduced HbA1c by 0.2% to 0.5% compared to usual care in patients with chronic non-communicable diseases, improving overall clinical outcomes.
Do continuous monitoring technologies improve treatment adherence, quality of life, and clinical outcomes in patients with chronic conditions?
Patients with chronic non-communicable diseases (including diabetes mellitus, cardiovascular diseases, and neurodegenerative disorders) synthesized from 32 key studies.
Continuous Monitoring (CM) technologies including Continuous Glucose Monitoring (CGM), remote Electrocardiography (ECG), wearable biosensors, and AI-driven predictive analytics.
Traditional episodic, reactive care or standard care.
Treatment adherence and Quality of Life (QoL).
Continuous monitoring technologies offer significant clinical benefits for chronic disease management but require careful implementation to mitigate negative psychosocial impacts like device-induced anxiety.
Background: The escalating prevalence of chronic non-communicable diseases (NCDs), including diabetes mellitus, cardiovascular diseases, and neurodegenerative disorders, presents a significant challenge to global healthcare systems. The traditional paradigm of episodic, reactive care is increasingly proving insufficient. Consequently, a digital transformation is underway, characterized by the adoption of Continuous Monitoring (CM) technologies such as Continuous Glucose Monitoring (CGM), remote Electrocardiography (ECG), and wearable biosensors. Objectives: This narrative review aims to provide a comprehensive overview of emerging trends in continuous monitoring technologies from 2020 to 2025. Specifically, it evaluates the impact of these technologies on treatment adherence and Quality of Life (QoL), analyzes the integration of Artificial Intelligence (AI) and Digital Twins, and identifies sociotechnical barriers to widespread implementation. Methodology: A rigorous narrative review was conducted based on a systematic search of high-impact literature. Thirty two key studies, including systematic reviews, meta-analyses, and technical frameworks, were synthesized to explore the intersection of technological innovation (IoMT, AI) and social science dimensions (behavioral change, patient empowerment, and equity). Results: Current evidence indicates that CM technologies significantly improve clinical outcomes, including HbA1c reduction in diabetes and decreased hospital readmission rates for heart failure. However, the impact on QoL is bidirectional: while fostering empowerment and safety, continuous surveillance can also induce anxiety and symptom preoccupation. Novel frameworks like Digital Twins and AI-driven predictive analytics offer promising avenues for personalized medicine but raise ethical and privacy concerns. Conclusion: Continuous monitoring serves as a critical enabler of proactive health management. Future advancements must prioritize user-centered design, interoperability, and equitable access to realize the full potential of these technologies in improving societal health and well-being.
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Maria Rajkowska
Bernard Myszewski
Aleksandra Iwona Włodarczyk
International Journal of Innovative Technologies in Social Science
Medical University of Lodz
Copernicus Memorial Hospital
Le Loch Healthcare (Poland)
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Rajkowska et al. (Thu,) conducted a other in Chronic Non-Communicable Diseases. Continuous Monitoring Technologies vs. Standard care or Usual care was evaluated on Reduction in HbA1c and decreased hospital readmission rates (RR 0.76, 95% CI 0.68-0.85, p=<0.001). Continuous monitoring technologies reduced HbA1c by 0.2% to 0.5% compared to usual care in patients with chronic non-communicable diseases, improving overall clinical outcomes.
www.synapsesocial.com/papers/69b3aaa802a1e69014ccb6b9 — DOI: https://doi.org/10.31435/ijitss.1(49).2026.4700