The development of RWE in China is at a critical juncture, urgently requiring a breakthrough to fix current bottlenecks faced by RWD. With a wealth of successful cases and practical experiences accumulated over the past several years in China, significant opportunities present themselves. We attempt to analyze this from the perspectives of macro-level policies, a comprehensive guideline system, innovative tools and methods, and professional knowledge.

The “Healthy China 2030” blueprint has identified the prevention and treatment of diseases and the improvement of population health as a national goal [5], which has greatly driven the demand for data in clinical and public health fields. In this context, the government has invested in numerous cohort studies, greatly enriching available RWD sources in China.

As of 2019, China had over 300 published natural population cohorts and disease-specific cohorts [13]. One of the most representative cohort studies is the China Kadoorie Biobank (CKB), which covers more than 500,000 healthy adults across ten provinces and has a follow-up period of nearly 20 years [14]. To enhance cohort data information sharing and collaboration, a platform called the China Cohort Consortium (CCC), covering the information of 145 cohorts, was also established in 2017 [15].

In addition, as an important action stressed in the "Healthy China 2030" plan, China has established 488 national-level and 807 provincial-level comprehensive prevention and control demonstration areas for chronic diseases [16]. These demonstration areas focus on conducting early screening and health management for residents and promoting information connectivity across medical and public health institutions. These efforts have been generating substantial RWD, such as health monitoring data and physical examination data.

Another national data strategy is the “National Plan for the Layout of Digital China" released in 2023 [17], which emphasizes strengthening data infrastructure, promoting the collection and utilization of public data, and establishing national databases for public health. In the era of Digital China, it is expected that Chinese RWD will be more abundant, accessible, and regulated.

With the support of open national strategies, regional policies have begun piloting support for RWD development as well. As a great example,  the Boao Lecheng pilot zone in Hainan province established an RWD platform to collect the clinical records of the pre-authorized use of pharmaceutical products and medical devices [18, 19]. This platform documents precious real-world use data of medical products urgently needed in clinical practice. As collection, curation, and management strictly adhere to the released RWD guidelines, these data can satisfy the requirements of drug registration studies. This provides an important model for the governance of high-quality RWD platforms in China. In addition, Hainan Province is also piloting the integration of data from medical institutions, health insurance, and drug regulatory systems, which has created approximately nine million interconnected health records [20].

While supportive policies have created the demand and environment for RWD development, effectively transforming RWD into high-quality RWE requires the guidance of actionable frameworks. China’s real-world study (RWS) guideline system is continuously evolving and aligning with global regulatory advancements.

Global interest in leveraging RWD and RWE to support regulatory decision making for drugs and medical devices is growing. The United States, Europe, the United Kingdom, Canada, Japan, and China have released technical guidelines on RWS [21]. Recently, the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) released the first global guideline draft on utilizing RWD for drug safety assessment [22], marking a new milestone in global regulatory science with RWS.

Since joining the ICH in 2017, China has established a world-leading RWS guideline system (Fig. 2) [21, 23]. Led by these guidelines, China has made extensive explorations of applying RWE in various aspects. In particular, the National Medical Products Administration (NMPA) has accumulated a wealth of practical experience in RWE supporting regulatory decision making for medical products, resulting in successful cases of new drug and device registrations, indication approvals, label expansions, and safety modifications [24]. By the end of 2023, 13 healthcare products were approved for marketing through the Boao Lecheng pilot zone [24].

Current guideline system on real-world studies of drugs. RWS real-world study

China’s RWS guideline system is relatively comprehensive, but still evolving with updates for guidelines on common RWS data sources and specific RWD application areas. For example, in 2023, the NMPA drafted a guideline on disease registries [25], a data source with unique value for RWS of rare diseases. In 2024, the NMPA released the latest guideline on using RWD to support proactive drug safety monitoring [26], which provides a significant reference for the development of a national RWD-based active pharmacovigilance system.

China’s immense population provides a wealth of clinical and public health data, presenting unique opportunities for generating RWE. Nowadays, many existing data sources have gradually matured while new RWD sources continue to emerge. However, researchers have not yet fully integrated and utilized the potential of these data sources (Fig. 3).

Diverse real-world data (RWD) sources in China

In terms of clinical data, China has seen a surge in disease registries and databases targeting specific diseases. As an example, the Guangzhou Institute of Respiratory Health collaborated with 33 hospitals nationwide to conduct the first severe asthma registry study in China (C-BIOPRED) [27]. This registry revealed the unmet treatment needs of Chinese patients with severe asthma and provided rich clinical characteristic data. Similarly, in response to the high prevalence of chronic kidney disease in China, the China Renal Data System (CRDS) has been established, which now covers clinical data of kidney patients from 24 hospitals [28]. Based on this database, researchers have successfully produced high-quality RWE with global impact [29].

Public health data is an important complement to clinical data. The China Chronic Disease and Risk Factors Surveillance study is a nationwide cross-sectional study conducted every 3 years since 2004, covering 170 million people across 31 provinces, collecting data on common chronic diseases, risk factors, physical measurements, and routine laboratory tests, which has unique value for generating RWE [30]. Another resource is China’s national mortality surveillance system, which provides total and cause-specific mortality data and plays a crucial role in assessing the impact of policies, interventions, and treatment strategies on mortality [31].

While China possesses abundant RWD sources, their heterogeneity and fragmented distribution hinder the full realization of their research potential. Consequently, fostering the integration of complex data sources and creating data platforms is an essential path for leveraging RWD effectively in China. Currently, several technological and methodological solutions for promoting data platforms have been explored, with corresponding practical cases of implementation.

The integration of RWD data sources refers to two dimensions. The first dimension is the cross-institutional data integration of the same type of RWD (e.g., electronic health records [EHR]). The major challenge lies in limited exchangeability due to the heterogeneous terminologies, formats, and structures of different institutions. The Observational Medical Outcomes Partnership (OMOP) common data model (CDM), an open community data standard, was designed to address this issue [32]. In China, OMOP is used not only to integrate EHR but also to integrate cohort data. For example, researchers from Peking University have established a large-scale respiratory disease cohort based on five mature community cohorts and four clinical disease cohorts in China [33].

The second dimension of integration is the linkage of various types of RWD sources, which helps to obtain life-course health data. As an innovative case, the Chinese Medical Association (CMA) and the Chinese Center for Disease Control and Prevention (China CDC) are piloting the linkage of the Chinese Medicine Clinical Case Repository (CMCR) database with the national death registration data to create a clinical disease-specific cohort database. The case report data primarily serve as valuable resources for physician training and experience sharing. By combining these with death registry data, their application will be further expanded to investigate the survival outcomes and prognostic factors influencing these outcomes by conducting RWS.

Confidentiality concerns often pose barriers to data sharing. Federated networks (FN) analysis offers a solution by allowing data to remain within the institution’s information system while still supporting collaborative research [34]. In this model, researchers can send analysis codes to the participating institutions remotely, and only the aggregated results, not patient-level data, are returned, ensuring privacy. This decentralized technology is increasingly used in China.

The ultimate goal of RWD integration in China is to establish a national-level health data ecosystem. Leveraging the opportunities mentioned above, Shandong Province has issued policy and piloted the establishment of the National Health and Medical Big Data Center (North) [35]. One of the remarkable fruits of this center is the Cheeloo Lifespan Electronic Health Research Data Library (Cheeloo LEAD) [36]. Using CDM and FN, Cheeloo LEAD integrates data from 5,152,597 individuals across 4909 hospitals and primary healthcare institutions in 39 urban areas of Shandong Province, China, with a follow-up period of approximately 14 years. The data encompasses demographic information, diseases, medications, laboratory tests, and surgical records. This foundation provides high-quality data for RWS and offers valuable experience for the development of a national-level data platform in the future.

In previous discussions about the development of RWD and RWE, the importance of talent has often been overlooked. As China experiences rapid growth in RWD and RWE, it is crucial to recognize and address the increasing demand for skilled professionals in this field.

Currently, some universities are creating interdisciplinary RWD talent programs. For example, the Medical Dataology major at Shandong University offers education in medicine, epidemiology, mathematics, and computer science, preparing talents for RWS [37]. The healthcare industry is also collaborating with academia to enhance talent reserves. Universities provide expertise, while the industry offers RWS project opportunities. For instance, AstraZeneca (AZ) and Peking University (PKU) Health Science Center jointly established the PKU-AZ RWE Research Laboratory [38], allowing students to participate in RWS projects in pharmaceutical companies. At the same time, utilizing this RWS platform, AZ and PKU jointly generated high-quality RWE to enrich evidence-based medicine and advance chronic disease prevention, diagnosis, and treatment.