T/XJBX 0206-2026 Drug safety data quality management and control specifications
T/XJBX 0206-2026 Drug safety data quality management and control specifications
Basic Information
Scope
Drug safety surveillance is an important institutional arrangement to ensure the safety and effectiveness of drugs after they are put on the market. Its core task is to identify, assess, and control drug risks in a timely manner by continuously and systematically collecting, analyzing, and evaluating adverse drug reactions and other safety-related information. Drug safety surveillance activities rely heavily on data support. Adverse drug reaction reports, individual safety reports, literature monitoring data, information on the implementation of risk management plans, and results of post-marketing safety studies all flow through the entire process of drug safety surveillance in the form of data. The authenticity, completeness, accuracy, timeliness, and traceability of drug safety surveillance data directly determine the scientificity and reliability of signal detection, risk assessment, and regulatory decision-making. In practice, drug safety surveillance data sources are extensive and diverse, including data generated by spontaneous reporting systems, clinical studies, real-world studies, literature and database searches, patient support programs, and data shared by collaborators. Data from different sources vary significantly in terms of collection methods, quality standards, structuring levels, and update frequencies. Without unified data quality management and control requirements, problems such as missing information, inconsistent logic, duplicate records, coding errors, version confusion, and traceability difficulties may arise, thereby affecting the sensitivity of safety signal detection and the reliability of risk assessment conclusions. Moreover, with the widespread application of information and digital technologies in drug safety surveillance, data management is gradually shifting from manual recordkeeping to information systems and database management, placing higher demands on data standardization, process control, and systematic quality management.