Exploring the integration of medical and preventive chronic disease health management in the context of big data
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...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1547392/full |
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| author | Yueyang Wang Yueyang Wang Ruigang Deng Xinyu Geng |
| author_facet | Yueyang Wang Yueyang Wang Ruigang Deng Xinyu Geng |
| author_sort | Yueyang Wang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-85495edc452d446baf82cf4e208c4442 |
| institution | OA Journals |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj-art-85495edc452d446baf82cf4e208c44422025-08-20T02:12:19ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-04-011310.3389/fpubh.2025.15473921547392Exploring the integration of medical and preventive chronic disease health management in the context of big dataYueyang Wang0Yueyang Wang1Ruigang Deng2Xinyu Geng3Office of Medical Defense Integration, The Fourth People's Hospital of Sichuan Province, Chengdu, ChinaSchool of Computer Science and Software Engineering, Southwest Petroleum University, Chengdu, ChinaOffice of Medical Defense Integration, The Fourth People's Hospital of Sichuan Province, Chengdu, ChinaSchool of Computer Science and Software Engineering, Southwest Petroleum University, Chengdu, ChinaChronic 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.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1547392/fullchronic disease managementhealth care and prevention integrationrisk prediction modelingbig datapreventive management |
| spellingShingle | Yueyang Wang Yueyang Wang Ruigang Deng Xinyu Geng Exploring the integration of medical and preventive chronic disease health management in the context of big data Frontiers in Public Health chronic disease management health care and prevention integration risk prediction modeling big data preventive management |
| title | Exploring the integration of medical and preventive chronic disease health management in the context of big data |
| title_full | Exploring the integration of medical and preventive chronic disease health management in the context of big data |
| title_fullStr | Exploring the integration of medical and preventive chronic disease health management in the context of big data |
| title_full_unstemmed | Exploring the integration of medical and preventive chronic disease health management in the context of big data |
| title_short | Exploring the integration of medical and preventive chronic disease health management in the context of big data |
| title_sort | exploring the integration of medical and preventive chronic disease health management in the context of big data |
| topic | chronic disease management health care and prevention integration risk prediction modeling big data preventive management |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1547392/full |
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