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Review
. 2025 Apr 15:13:1547392.
doi: 10.3389/fpubh.2025.1547392. eCollection 2025.

Exploring the integration of medical and preventive chronic disease health management in the context of big data

Affiliations
Review

Exploring the integration of medical and preventive chronic disease health management in the context of big data

Yueyang Wang et al. Front Public Health. .

Abstract

Chronic non-communicable diseases (NCDs) pose a significant global health burden, exacerbated by aging populations and fragmented healthcare systems. This study employs a comprehensive literature review method to systematically evaluate the integration of medical and preventive services for chronic disease management in the context of big data, focusing on pre-hospital risk prediction, in-hospital clinical prevention, and post-hospital follow-up optimization. Through synthesizing existing research, we propose a novel framework that includes the development of machine learning models and interoperable health information platforms for real-time data sharing. The analysis reveals significant regional disparities in implementation efficacy, with developed eastern regions demonstrating advanced closed-loop management via unified platforms, while western rural areas struggle with manual workflows and data fragmentation. The integration of explainable AI (XAI) and blockchain-secured care pathways enhances clinical decision-making while ensuring GDPR-compliant data governance. The study advocates for phased implementation strategies prioritizing data standardization, federated learning architectures, and community-based health literacy programs to bridge existing disparities. Results show a 30-35% reduction in redundant diagnostics and a 15-20% risk mitigation for cardiometabolic disorders through precision interventions, providing a scalable roadmap for resilient public health systems aligned with the "Healthy China" initiative.

Keywords: big data; chronic disease management; health care and prevention integration; preventive management; risk prediction modeling.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
6 V’s of big data.
Figure 2
Figure 2
Big Data modeling roadmap.
Figure 3
Figure 3
Healthcare prevention fusion data prototype diagram.
Figure 4
Figure 4
Prototype architecture diagram for precision health management integration within a public hospital system.
Figure 5
Figure 5
Roadmap for development in the field of healthcare prevention integration.

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