The Outline of the 15th Five Year Plan has made strategic arrangements for "accelerating the construction of a healthy China", emphasizing "promoting the digitalization of national health and promoting the sharing and mutual recognition of inspection and testing results", which has pointed out the direction for building a high-quality and efficient medical and health service system and strengthening the public health security barrier. How to promote the transformation and application of technological innovation achievements, drive the innovation of health management service models with digital technology, and shift from "passive medical care" to "active health"? This issue invites experts to discuss relevant issues. How can innovative health management service models achieve continuous and effective health management, shifting from "passive medical care" to "active health"? Fu Qiang (Director of the National Center for Mental Health and Prevention): People's health is an important symbol of socialist modernization. During this year's National People's Congress and Chinese People's Political Consultative Conference, General Secretary Xi Jinping proposed to "promote the transformation and application of scientific and technological innovation achievements, and advance the digitalization of national health. The digitalization of national health is a comprehensive and systematic reshaping of health services, governance, and industrial systems driven by new generation information technologies such as artificial intelligence, the Internet of Things, and cloud computing, with data as the key production factor. Through dynamic monitoring, scientific evaluation, and systematic intervention of the entire population and life cycle, we aim to promote the shift of medical services from disease centered to people-centered health. By December 2025, the number of Internet medical users will be 411 million. The scope of Internet medical services has gradually expanded from online consultation, re consultation and prescription to health management, chronic disease follow-up and remote consultation, effectively promoting the inclusive sharing of high-quality medical resources. With the increasing awareness of people's health, the demand for health management continues to grow. Traditional health management services are facing practical bottlenecks such as fragmented health monitoring, cumbersome and inefficient processes, and "managing physical examinations for one year", which restrict the long-term benefits that health management should have released. At its root, it mainly lies in the deep-seated constraining factors on both sides of supply and demand. The supply side faces challenges such as incomplete technological coverage, imbalanced resource structure, and numerous data barriers, while the demand side faces challenges such as information asymmetry, current preferences for individual health actions, and insufficient support for preventive health management through medical insurance payments. For some families, the long-term returns of health management may be replaced by more urgent expenses in decision-making. Digital facilities represented by artificial intelligence, wearable devices, and big data platforms are injecting unprecedented transformative power into health management. Smart watches, health trackers, smart glasses, smart clothing, etc. can not only monitor users' physical status in real time, but also provide personalized health advice to help users better manage their own health. These devices are becoming increasingly widely used in heart rate monitoring, sleep quality monitoring, exercise data recording, stress monitoring, and other areas, providing real-time and accurate data support for health management. Currently, the size of the national health management market exceeds one trillion yuan, with the digital health management market reaching one billion yuan. The popularization of smart wearable devices and the full coverage of remote medical networks provide technical support for the upgrade of health management. Looking towards the future, promoting the digitalization of national health should be driven by digital technology to innovate health service models, promote the transformation and application of more technological innovation achievements, and fully embody the concept of "investing in people". One is to deepen the empowerment of digital intelligence and achieve precise health interventions. Accelerate the integration and integration of national level public health information platforms, and break down data barriers. Continuously collecting multidimensional health data through IoT devices, integrating physiological indicators and psychological behavior information, and constructing a complete personal health digital portrait. On this basis, artificial intelligence is used to construct a predictive model covering psychosomatic risks, promoting the shift of disease warning from a single physiological indicator to comprehensive health assessment. The second is to improve the collaborative mechanism of the "three medical" (medical, medical insurance, and pharmaceuticals) and establish a governance system guided by health benefits. On the server side, we will continue to implement the strong foundation project for medical and health care, promote the deep integration of digital tools with grassroots medical networks, implement family doctor contract services, provide high-quality and continuous basic public health and health management services to the entire population, especially key populations, and create a continuous service loop for psychological support and chronic disease management. On the payment side, deepen the reform of medical insurance payment methods and accelerate the establishment of an evaluation and payment mechanism centered on health outcomes and health benefits. On the regulatory side, establish a standard evaluation system that adapts to the development of digital health, enhance system integration and efficient collaboration capabilities, and guide resource allocation towards promoting health. The third is to innovate incentive models and cultivate an active health culture of "physical and mental well-being". The emergence of psychological problems is often accompanied by adverse physical symptoms, and a positive psychological state can help improve the effectiveness of health management. To promote mental health as an important component of health management, and truly achieve a happy heart and healthy body. Explore incentive mechanisms guided by overall physical and mental health, promote innovative development of personal health data value, widely implement the health points system, and incorporate health management behaviors such as regular exercise, stress management, and physical and mental assessment into incentive categories, combined with substantial gains in insurance, medical treatment, public services, and other aspects. How to standardize the collection, ownership, and use of data while promoting health and medical data sharing and reducing duplicate checks by breaking down barriers to cross regional medical data? Qiu Wuqi (Director and Researcher of the Public Health Strategic Intelligence Research Office at the Institute of Medical Information, Chinese Academy of Medical Sciences): Data is the core production factor in the digital age, and efficient sharing and standardized governance of health data are the fundamental support for the construction of national health digitalization. During the 14th Five Year Plan period, over 1.25 billion people nationwide have opened electronic medical insurance codes, and scanning codes for medical treatment without a card has become the norm; The online filing and direct settlement of cross provincial medical treatment have been fully realized, with a cumulative direct settlement of over 600 million people. At the same time, as the demand for cross regional medical treatment continues to grow, whether the examination and testing results can be accessed and mutually recognized across institutions has become a prominent issue affecting the efficiency of medical services and the burden on patients. Mutual recognition of inspection and testing results and sharing of medical data among medical institutions can not only save time and costs for patients seeking medical treatment in different locations without having to repeatedly queue for inspections, but also enable medical staff to have complete medical records, assist in accurate diagnosis and treatment, and promote the improvement of inspection and testing quality in medical institutions. By 2025, all provinces in China will have achieved mutual recognition of inspection and testing results among medical institutions within their own cities, with over 200 projects. 25 provinces will have established provincial-level imaging clouds, and a total of over 350 million medical images will have been accessed; 9073 second level and above public hospitals, 503000 first level public hospitals, and grassroots medical and health institutions are connected to the regional platform to achieve cross institutional and cross regional data exchange. Currently, electronic health records are widely established in medical institutions at all levels. However, in reality, it is still difficult to achieve mutual recognition of some examination and testing results when patients receive cross hospital diagnosis and treatment. This is mainly because the health and medical data governance system is not yet mature, and data sharing has shortcomings in terms of rules, incentives, and trust. Firstly, the unclear boundary of responsibility leads to reluctance to use it. Once the inspection results are used for diagnosis and treatment decisions, they are directly related to medical safety and legal responsibilities. In the absence of unified quality identification, time window rules, institutional qualification stratification, and responsibility sharing mechanisms, the potential risks of using results from external institutions are significantly amplified. The national level mutual recognition management measures have clearly defined the basic principles of mutual recognition work, and are promoting mutual recognition with the bottom line of ensuring quality and safety and the standard of judgment of receiving physicians. Secondly, inconsistent institutional incentives lead to unwillingness to share. Mutual recognition means a reduction in duplicate inspections, and the business volume and performance structure of some institutions will be adjusted accordingly. If there is a strong binding relationship between medical insurance payments, hospital performance, and examination income, data sharing will conflict with existing incentive mechanisms. In this regard, Hangzhou's exploration provides a more specific landing sample. On the one hand, through institutional construction and digital collaboration, we will promote the mutual recognition and sharing of inspection and testing results throughout the city, clarify mutual recognition projects, institutions, and rules, and recognize standardized and complete reports and original images within 30 days under the premise of quality and safety, thus breaking the "no recognition" rule. On the other hand, the medical insurance side has made incentive adjustments synchronously, clarifying in the operating rules that the total budget of the medical insurance fund will not be reduced due to cost reduction caused by mutual recognition, and establishing a responsibility sharing mechanism for surplus retention and overspending sharing, to alleviate "unwillingness to recognize" from an institutional perspective. This is actually a combination of mutual recognition of inspection and testing results, cost control and quality improvement, and collaborative efficiency enhancement through adjustments to payment budgets and assessment rules. Thirdly, the mismatch between standards and quality leads to poor usability. Even for similar inspection projects, different medical institutions may have differences in equipment configuration, testing methods, reference intervals, and quality control. Mutual recognition is not simply a one size fits all approach, but should be steadily promoted according to risk classification and project classification. For those that can be directly recognized, those that require additional conditions for mutual recognition, and those that are only for reference, they should be listed and regulated. Otherwise, mutual recognition will be difficult to truly enter clinical practice. In the process of promoting data sharing and reducing duplicate checks, the real difficulty lies not in building more platforms, but in standardizing data collection, ownership, and use, and improving the "soft infrastructure" of data governance. Only under the premise of clear rights and responsibilities, compatible incentives, clear rules, and controllable privacy and security, can health and medical data truly support hierarchical diagnosis and health management, allowing the public to run fewer errands, reduce duplicate checks, and unnecessary expenses. One is to promote data collection from a "filing oriented" to a "clinical and health management oriented" approach. The reason why electronic health records have limited practical applications is that their data structure serves more for management rather than continuous care. Priority should be given to promoting the standardization of data items that can be reused across institutions, focusing on high-frequency scenarios such as chronic disease follow-up, medication management, examination and testing reuse, referral collaboration, and discharge follow-up. Priority should be given to addressing the issues that can minimize duplicate examinations and improve efficiency. The second is to clarify the ownership and usage boundaries of health and medical data. Health data not only involves personal privacy and rights, but also carries the responsibility of medical institutions for data quality and security. By calling for traceability, permission auditing, and accountability tracing, the cost of violations can be increased, and data flow can always be kept under institutional constraints. Applying advanced technologies such as privacy computing and blockchain, hierarchical authorization is carried out according to specific usage scenarios, roles, and purposes, achieving "using what is needed without crossing boundaries", ensuring that the data that is truly needed can flow in compliance and efficiently, while preventing unauthorized calls and illegal access, gradually establishing public trust in digital health services. The third is to establish a trust mechanism for cross institutional mutual recognition. Mutual recognition is not just about system integration, but about ensuring that each inspection and testing result has verifiable sources, methods, time, and quality control information, making the calling process traceable, auditable, disputes recheckable, and responsibilities definable, thereby reducing clinical use risks. We should continue to promote the interconnection and intercommunication between regional health information platforms and medical consortia, and promote the sharing and mutual recognition of data within the authorized scope. How to accelerate the implementation of smart healthcare applications and overcome the integration barriers between technology applications and existing medical insurance payments and hospital performance systems, in order to achieve universal access to smart healthcare? Wang Jun (Vice Dean of the Health China Research Institute at Renmin University of China): Digital technologies or products represented by wearable devices, artificial intelligence assisted diagnosis and treatment, and remote healthcare are driving medical services to shift from focusing on disease treatment