Review research progress, critical reflections and future prospects of digital care for chronic diseases
- 1School of Nursing, Tongji Medical College, Huazhong University of Science and Technology
Abstract
The global prevalence of chronic diseases is becoming increasingly severe, and traditional care models are confronted with multiple challenges, including uneven distribution of medical resources, insufficient continuity of care, and inadequate patient self-management capacity. The rapid iteration of digital technologies and the catalyst of the COVID-19 pandemic have driven chronic disease care into a new phase of digital transformation. Based on relevant studies published from 2021 to 2026, this paper structures its analysis around a core logical framework: evidence-based evidence, care models, population adaptability and practical implementation. It systematically reviews the core technical systems and innovative characteristics of care models in digital chronic disease care, deeply analyzes the adaptive differences across diverse populations and disease types, and conducts critical reflections from the perspectives of evidence quality, health equity, clinical applicability, and homogeneity in intervention design. Finally, it puts forward future development directions centered on precision, localization, equity, and integration. The study reveals that digital chronic disease care has formed four core technological systems in application: intelligent sensing, digital behavioral intervention, immersive technology, and artificial intelligence (AI) and big data. Care models demonstrate innovative trends of nurse leadership, multi-dimensional collaboration, and caregiver empowerment. Nevertheless, prominent issues persist, such as insufficient high-quality evidence, a striking digital divide, difficulties in clinical integration, and a lack of personalized design. In the future, deep integration of technological innovation with clinical demands, enhanced targeted interventions for vulnerable populations, implementation of localized long-term studies, and improvement of policy and ethical guarantee systems are required. These efforts will promote the shift of digital chronic disease care from technology-driven to evidence-driven and demand-driven models, ultimately improving the overall efficiency of chronic disease management and health equity.
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BibTeX
@article{zhou2026review,
title = {{Review research progress, critical reflections and future prospects of digital care for chronic diseases}},
author = {Yingchao Zhou and Ruizhe Cao and Yanwei Su},
journal = {Frontiers in Public Health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1968554},
url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1968554/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Review research progress, critical reflections and future prospects of digital care for chronic diseases
AU - Yingchao Zhou
AU - Ruizhe Cao
AU - Yanwei Su
PY - 2026
DA - 2026/10/13
JO - Frontiers in Public Health
DO - 10.3389/fpubh.2026.1968554
UR - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1968554/full
AB - The global prevalence of chronic diseases is becoming increasingly severe, and traditional care models are confronted with multiple challenges, including uneven distribution of medical resources, insufficient continuity of care, and inadequate patient self-management capacity. The rapid iteration of digital technologies and the catalyst of the COVID-19 pandemic have driven chronic disease care into a new phase of digital transformation. Based on relevant studies published from 2021 to 2026, this paper structures its analysis around a core logical framework: evidence-based evidence, care models, population adaptability and practical implementation. It systematically reviews the core technical systems and innovative characteristics of care models in digital chronic disease care, deeply analyzes the adaptive differences across diverse populations and disease types, and conducts critical reflections from the perspectives of evidence quality, health equity, clinical applicability, and homogeneity in intervention design. Finally, it puts forward future development directions centered on precision, localization, equity, and integration. The study reveals that digital chronic disease care has formed four core technological systems in application: intelligent sensing, digital behavioral intervention, immersive technology, and artificial intelligence (AI) and big data. Care models demonstrate innovative trends of nurse leadership, multi-dimensional collaboration, and caregiver empowerment. Nevertheless, prominent issues persist, such as insufficient high-quality evidence, a striking digital divide, difficulties in clinical integration, and a lack of personalized design. In the future, deep integration of technological innovation with clinical demands, enhanced targeted interventions for vulnerable populations, implementation of localized long-term studies, and improvement of policy and ethical guarantee systems are required. These efforts will promote the shift of digital chronic disease care from technology-driven to evidence-driven and demand-driven models, ultimately improving the overall efficiency of chronic disease management and health equity.
SN - 2296-2565
ER -