round the world, regulators and payers are looking for ways to use real-world data (RWD) to make decisions without sacrificing trust, transparency, or rigor. In China, the answer is increasingly being built—not just debated—through new policies, standards, and data sharing infrastructure. A three-agency flywheel—comprising data infrastructure (National Data Administration [NDA]), regulatory standards (Center for Drug Evaluation [CDE]), and reimbursement incentives (National Healthcare Security Administration [NHSA])—is now in motion.

For clarity, in the context of this article RWD is defined as data relating to patient health status and/or the delivery of healthcare routinely collected from a variety of sources (e.g., electronic health records, medical claims data, product or disease registries, etc.) that can inform on health status, and RWE is defined as the clinical evidence about the usage and potential benefits or risks of a medical product derived from analysis of RWD. RWD becomes RWE when it is analyzed using appropriate scientific methods to generate clinical evidence.

Why Trusted Data Spaces Matter for Real-World Data in China Now

Since the second half of 2024, China’s national data agenda has shifted from positioning data as one of the “factors of production” to building practical mechanisms that enable safe and compliant use. One visible example is the rise of trusted data spaces: governed environments where multiple parties can analyze data together without transferring raw data sets.

In November 2024, the NDA issued the Trusted Data Space Development Action Plan (2024–2028). It emphasizes rule-based access, usage control, and accountability—elements that can enable compliant multi‑institution analyses while keeping raw data secure.

This infrastructure advancement creates the conditions for decision‑grade RWD and RWE to inform not only regulators, but also payers. Here, “decision‑grade” refers to data and analyses with clear provenance, fit‑for‑purpose quality controls, auditability, reproducibility, and governance that can withstand external scrutiny.

This infrastructure aligns with China’s national “Data Element ×” program (2024–2026), which highlights medical and health data as a prioritized scenario for application of data elements in key sectors such as the digital economy and public services, with healthcare identified as a prioritized domain. In early 2025, the NDA and the National Development and Reform Commission also issued a trial specification for authorized operation of public data resources, clarifying how government-held data can be accessed by qualified operators under defined safeguards.

Together, trusted data spaces and clearer authorization pathways create practical “guardrails” for scaling the generation and use of the solid evidence generated based on the RWD. This foundational framework enables the secure and governed flow of data, which supports a convergence between regulatory guidance and payer pilots.

How China’s Regulator is Making RWE More Usable

In parallel, the CDE is making RWE more reviewable in practice while aligning with International Council for Harmonisation (ICH) standards.

A recent anchor is ICH M14, a framework for noninterventional studies using RWD for medicines safety assessment. In January 2026, CDE released the official Chinese translation and implementation guidance, supporting more post‑authorization safety studies in China.

China has also contributed to emerging global guidance on using RWE for effectiveness evaluation. ICH’s E23 workstream (initiated in 2025) is expected to clarify when RWE can support effectiveness-related regulatory decisions.

Domestically, CDE has issued practical guidance on fit-for-purpose RWD and real-world study (RWS) design. A key 2024 addition focuses on using disease registries as a regulated RWD source. For example, multihospital registries can generate external control arms or post-approval safety and effectiveness evidence to support drug registration and, in some cases, reimbursement negotiation (e.g., National Reimbursement Drug List, NRDL) in both drug and medical devices.

How China’s Payer is Building an RWD Engine for Reimbursement

Between 2025 and 2026, China took concrete steps to formalize the use of RWE in healthcare insurance decision-making. NHSA launched pilot programs and released draft guidelines on real-world medical insurance comprehensive value evaluation, signaling a shift toward continuous, verifiable assessment based on full lifecycle evidence rather than one-time negotiation dossiers.

To support this approach, NHSA established a network of “trusted evaluation centers,” initially involving 79 hospitals, to pilot shared conventions, analytical methods, and governance frameworks. In parallel, commercial insurers have begun referencing RWE to inform differentiated coverage and value-based arrangements.

These developments are further reinforced by the State Council Office’s recent drug pricing policy, which explicitly highlights the use of RWE to support post-launch price refinement. Together, they reflect China’s growing emphasis on aligning evidence generation across the product lifecycle with evolving health policy and reimbursement needs.

In this framework, RWE helps characterize value across multiple dimensions; for example, real‑world clinical outcomes, healthcare resource use and budget impact, and patient‑reported experiences such as quality of life, treatment adherence, and preferences.

The direction is clear: Reimbursement evaluations are being set up to evolve as evidence accumulates, which raises expectations for data quality, study design, and transparent governance.

For global stakeholders, China’s trajectory matters because it links evidence generation to concrete decision points—regulatory review, reimbursement evaluation, and price refinement—within a governed, auditable environment.

Methodology is Catching Up

Academia and industry are also moving from “RWD availability” to decision‑grade RWE. Academic groups are advancing methods to address bias and confounding, while companies invest in standard definitions, privacy‑preserving analytics, reproducible pipelines, and governance that can be inspected by external stakeholders.

Implications

• Regulators: Trusted data spaces make provenance, audit trails, and protocol-driven analyses easier to verify—if standards for fit-for-purpose data quality and reproducibility are enforced consistently.
• Payers: “Trusted evaluation centers” create a route to comparable, lifecycle evidence updates. This supports risk-sharing and reassessment but also requires establishing clearer expectations and higher standards on data quality and study methodologies (for example, endpoints, confounding control, and transparency).

Industry: Competitive advantage will shift to those who can deliver reproducible, auditable analytics that simultaneously meet evolving regulatory (CDE) and value assessment (NHSA) standards. Building standardized, reusable data pipelines and demonstrating robust data governance will be essential.

Looking ahead, the opportunity is to move beyond enabling access to RWD toward the routine use of decision-grade RWE in regulatory, reimbursement, and healthcare decision-making. Achieving this will require continued alignment among regulators, payers, academia, and industry on data quality, methodological rigor, transparency, and governance. With these foundations in place, China is well positioned to demonstrate how trusted data ecosystems can translate real-world data into evidence that is both credible and actionable.