Recently, the research team led by Professor Wang Hui, Dean of the School of Public Health, published an important review article titled “Digital Health Technologies in Proactive Health: Progress and Development Recommendations” in Strategic Study of CAE. This article systematically elaborates on the pivotal role of digital health technologies in advancing proactive health management. Grounded in the proactive health theoretical framework of “Proactive Sensing, Proactive Discovery, and Proactive Response,” it provides important theoretical support and practical pathways for the digital transformation of health management models in China.
Innovative Theoretical Framework: The “Three Proactives” Closed-Loop Management System
This article, for the first time ever, constructs and systematically elaborates on the closed-loop management framework of “Proactive Sensing, Proactive Discovery, and Proactive Response,” termed the “Three Proactives.” This framework represents a fundamental shift in the philosophy of health management from the traditional “disease treatment” to “health maintenance” covering the entire life cycle.
The Proactive Sensing layer serves as the cornerstone of the system. By leveraging smart wearable devices, IoT sensors, and mobile health applications, it enables continuous and dynamic monitoring of individuals' physiological parameters, behavioral patterns, and environmental factors. This breaks the temporal and spatial limitations of health data collection, extending monitoring scenarios from hospitals to daily life and constructing dynamic digital portraits of personal health.
At the Proactive Discovery layer, the framework emphasizes the use of artificial intelligence, big data analytics, and digital genomics to conduct in-depth mining and intelligent analysis of the massive data gathered by the sensing layer. Its core lies in constructing disease risk prediction models to achieve early warning and precise assessment of health threats, thus shifting the focus from “treating existing diseases” to “preventing potential diseases”.
The final Proactive Response layer integrates intervention methods such as digital therapeutics, telemedicine, and personalized health management platforms to formulate evidence-based personalized health promotion or disease management plans. These three interconnected stages form a digital closed-loop of “sensing-discovery-response”, providing a comprehensive methodological foundation for building a nationwide and forward-looking proactive health service system.
Technological Application Breakthroughs: From Health Sensing to Intelligent Intervention
The review systematically outlines the progress and application status of key technologies in each segment. In health sensing, smart wearables have advanced beyond basic heart rate and step tracking to enable continuous, non-invasive monitoring of blood pressure, blood glucose, blood oxygen saturation, electrocardiograms and other vital signs. The medical IoT, through device interconnectivity and real-time data synchronization, provides robust support for chronic disease management and home-based elderly care. Examples include smart pillboxes that effectively remind medication intake and environmental sensors that can warn of fall risks, significantly improving the efficiency and responsiveness of health management.
At the health risk discovery stage, technology integration demonstrates enormous potential. Digital genomics, especially techniques such as liquid biopsy, has significantly advanced the screening window for major diseases including cancer. The combination of medical big data and artificial intelligence has enabled the automatic identification of lesions and prediction of disease risks from massive volumes of imaging, pathological, and electronic medical record data. For instance, AI-assisted diagnostic systems have achieved sensitivity and specificity levels that are close to, or even partially exceed, those of senior physicians in screening for diseases such as pulmonary nodules and diabetic retinopathy, providing an efficient tool for large-scale population-based early screening.
In the proactive response segment, digital health technologies are catalyzing new service models. Digital therapeutics, as software-driven, evidence-based intervention programs, have demonstrated unique value in chronic disease management and psychological-behavioral interventions. The proliferation of telemedicine and online consultations has shattered geographical barriers to high-quality medical resources, thereby enabling patients to conveniently access follow-up services, specialist consultations, and professional guidance. Taking this a step further, intelligent health management platforms integrate a suite of functions including dietary recognition, physical activity monitoring, and emotional state sensing, delivering comprehensive and personalized health promotion regimens to users.
Core Challenges & Key Tech Directions
The article objectively points out that digital health technologies still face a series of challenges on the path to widespread adoption and deep application. Technically, there is room for improvement in the measurement accuracy, battery life, and anti-interference performance of sensing devices; medical data, characterized by being multi-source, heterogeneous, and highly sensitive, presents technical bottlenecks for secure, compliant sharing and integrated analysis; the clinical interpretability, robustness, and cross-population generalizability of AI models require further strengthening. At the application ecosystem level, "data silos" persist, and interoperability between different systems and devices is insufficient. Simultaneously, the digital divide issue is prominent, with differences in technology accessibility, usage ability, and health literacy among groups from different regions, ages, and income levels, potentially exacerbating health inequities.
Looking ahead, this review outlines several key technological directions that are expected to break through current bottlenecks. Next-generation flexible biosensing and microfluidic technologies strive to achieve more comfortable and accurate non-invasive continuous monitoring. Multimodal data fusion and analysis technologies aim to integrate multi-dimensional information such as genomics, imaging, and behavioral data, thereby constructing more comprehensive personal health risk models. Privacy-preserving computing technologies, including federated learning and blockchain, provide a feasible pathway for data value mining and collaboration while protecting data privacy. In addition, immersive telemedicine and artificial intelligence-driven personalized digital therapeutics will further expand the scenarios and depth of health management.
Academic Value & Social Significance
This review holds significant academic value and practical guidance. Academically, its value lies not only in systematically outlining the global frontier progress of digital health technologies but, more importantly, in originally proposing the "Three Proactives" theoretical framework. This provides a clear logical structure and analytical tool for understanding and developing proactive health technology systems, thereby advancing theoretical construction in this field.
In terms of social practice, the article closely aligns with the needs of “Healthy China” initiative and national conditions, offering highly targeted development recommendations. Examples include calls for improving policy support and medical insurance payment mechanisms to incentivize proactive health behaviors, strengthening core technology R&D to break through bottlenecks in sensors and algorithms, promoting the equitable application of technology to narrow the digital divide, and establishing robust data security and ethical governance systems to ensure the healthy and sustainable development of the industry. These recommendations provide decision-making references for government departments formulating relevant industrial policies, industry standards, and development plans, and also point out key directions for technology R&D and market application for industry, academia, and research communities.
In summary, this is not merely a systematic synthesis of knowledge but also an action guide for promoting the digital transformation of health management models. Its publication is expected to further foster the interdisciplinary integration of digital technology and health science, accelerate the construction of China's proactive health ecosystem, and contribute technological wisdom and solutions to enhancing national health levels.
Author Information:
The first author of this article is Zhou Dan, Assistant Researcher at the Shanghai Jiao Tong University School of Public Health. The corresponding author is Professor Wang Hui from the same school. The research was supported by the National Natural Science Foundation of China, the National Key R&D Program, and the Strategic Research and Consulting Project of the Chinese Academy of Engineering.
Wang Hui is Level-2 Professor, Distinguished Professor, and doctoral supervisor at Shanghai Jiao Tong University, serving as Dean of the School of Public Health and Executive Dean of the Digital Medicine Research Institute. She is a recipient of the National Science Fund for Distinguished Young Scholars, a member of the National Ten Thousand Talents Program, a winner of the China Young Women in Science Award, and an expert enjoying special government allowances from the State Council. She also holds positions as a member of the Expert Committee of the State Council Food Safety Commission, a National Health Science Popularization Expert, the Chief Expert in China's nutrition field, Chair of the Microbiology Subcommittee of the First National Food Safety Standard Evaluation Committee, and President of the Shanghai Society of Toxicology. Her long-term research focuses on proactive health, chronic disease prevention and control, and nutrition and food safety, with over 260 papers published in prestigious journals including Nature and JAMA. She is recognized as a Highly Cited Researcher by Elsevier and a Chief Scientist of key projects under the Ministry of Science and Technology.
Zhou Dan is currently an Assistant Researcher at the School of Public Health, Shanghai Jiao Tong University. She obtained her doctoral degree from the University of Chinese Academy of Sciences and subsequently completed postdoctoral research training in Clinical Medicine at Tongji University School of Medicine, during which she was the recipient of funding from the Shanghai “Super Postdoctoral” Incentive Program. Her primary research interests include digital proactive health management and intelligent emergency response; aging and the construction of public health service systems; as well as public health governance and health policy innovation. To date, she has published more than 30 academic papers in domestic and international journals, participated in over 10 horizontal and vertical research projects, and authored 5 academic monographs.
