Presentation (CTI)

OBJECTIVES: To identify structural, methodological, and regulatory barriers to RWD availability and RWE analytical credibility in Russian HTA and to propose solutions mapped to each barrier.
METHODS: A narrative synthesis drawing on expert experience with Russian data flows and legislation, supplemented by a targeted review of literature and regulatory documents on RWD/RWE, data protection, and HTA. Key topics included stakeholder roles, legal constraints, and RWE quality standards.
RESULTS: Four critical barriers were identified. First, Federal Law No. 152‑FZ prohibits direct data exchange among data holders, data operators, and end‑users, locking datasets within institutions and precluding national cohort formation and safety surveillance. Second, few federal registries exist; those available cover only a fraction of real patients, lack linkage with health information systems and mandatory health insurance (ФОМС) data, and provide scarce treatment effectiveness information. Third, health information systems are characterized by unstructured free text, paper-based records, high missing data rates, and incompatible data models. Fourth, most Russian RWE studies lack methodological safeguards against confounding and selection bias, operate without regulatory oversight, and demonstrate poor reproducibility.Proposed solutions: a three‑level anonymization framework compliant with Federal Law No. 152‑FZ combined with two‑stage blind‑analysis workflow; AI and NLP tools for structured extraction from clinical text; unified patient identifier; and mandatory minimum core data sets with interoperability standards. National RWE methodology guidelines and formal RWE acceptability criteria are proposed alongside a regulatory mechanism enabling research access to health data, integrated cross-database linkage, and unified disease-specific registries.
CONCLUSIONS: Full integration of RWE into Russian HTA requires simultaneous resolution of legal, infrastructural, data quality, and methodological barriers. Implementation of robust anonymization, blind analysis, AI‑driven data structuring, standardized health information infrastructure, and clear methodological frameworks will create necessary conditions for transforming health data into a credible evidence base for HTA decisions in Russia.