Purpose

Evidence grading on this site is practical: it explains how confident a reader should be in a claim and what type of source supports it, rather than forcing every policy or market-access question into a clinical-trial hierarchy.

Plain-English answer

The site grades evidence by claim type. A statute, regulation, or agency rule is strong evidence for authority. A validated dataset is useful for scale. A systematic review or well-designed study is useful for clinical or health-services claims. Payer policies and procurement records are useful for access. Interviews and market diligence can be valuable, but they should be presented as implementation evidence or strategic interpretation.

Why evidence grading matters

Clinical medicine has formal evidence traditions, including GRADE and systematic review methods. Those traditions are important, but U.S.-China healthcare strategy also asks questions that clinical hierarchies alone cannot answer. Whether a device can be marketed is a regulatory question. Whether it will be paid is a payer question. Whether a Chinese hospital will adopt it can depend on procurement rules, hospital tier, department economics, service burden, physician incentives, and local implementation.

Evidence grading on this site therefore asks two questions. First, how close is the evidence to the claim? Second, how much judgment is required to move from the evidence to the conclusion? A direct FDA page is stronger for FDA pathway description than a consulting deck. A CMS page is stronger for Medicare process than a journal article summarizing Medicare. A peer-reviewed outcomes study is stronger for clinical effectiveness than a company brochure. A local tender is stronger for procurement mechanics than a national market-size estimate.

Evidence grades used here

GradeBest useExamples
Primary authorityRules, pathways, definitions, legal obligations.FDA, CMS, NMPA, NHSA, NHC, laws, regulations, official notices.
Official dataScale, enrollment, spending, facilities, workforce, disease indicators.NBS, NHC statistical reports, NHSA reports, WHO, CDC, OECD.
Peer-reviewed evidenceClinical, epidemiologic, economic, and health-services claims.Trials, registries, systematic reviews, implementation studies.
Operational evidenceAdoption, procurement, payer behavior, hospital workflow.Tenders, local reimbursement, hospital purchasing, interviews, account-level diligence.
Strategic inferenceMarket-entry interpretation based on multiple sources.Reasoned conclusions about sequencing, risk, partner choice, or evidence gaps.

Clinical and public-health standards

GRADE is useful because it treats certainty as a structured judgment, not a decoration. CDC's ACIP materials describe systematic review and GRADE-based evidence assessment for vaccine recommendations, including domains such as risk of bias, inconsistency, indirectness, imprecision, and publication bias. AHRQ methods guidance similarly emphasizes risk of bias, directness, consistency, precision, and publication bias when grading bodies of evidence. Those domains are helpful whenever the page makes claims about health effects, clinical performance, or public-health intervention strength.

Market-access standards

Market-access claims need a different kind of grading. A product can have strong clinical evidence but weak reimbursement evidence. It can have regulatory authorization but no clear code, coverage, payment level, hospital budget pathway, or local procurement route. For these claims, a high-confidence statement usually requires official payer or procurement material plus field validation. When the evidence is only directional, the page should say so.

Practical rule

Do not make a claim sound more certain than its source allows. Call legal authority legal authority, data data, clinical evidence clinical evidence, implementation evidence implementation evidence, and inference inference. This is especially important in U.S.-China healthcare because the most important errors often occur between systems: approval is mistaken for access, coverage is mistaken for affordability, and market size is mistaken for adoption.

Research anchors