Building a multi-source heterogeneous data fusion platform for clinical data centers has become a common consensus in the medical information industry. The data fusion platform built by a certain hospital consisted of five parts: data acquisition module, data processing module, data comparison and repair module, data subscription and application module, and data fusion management platform. Data quality check was conducted on data scattered across the hospital′s operational systems with different structures and types, diverse patterns and states, different sizes and versions. The platform could handle duplicate and redundant metadata, collect, transform, process, distribute, and load data as needed, and maintain data consistency through comparison and repair. This platform is capable of automatically capturing, analyzing, governing, and integrating different types of data across databases, operating systems, and hardware environments, meeting diverse medical data application needs, and supporting the high-quality development of intelligent hospitals

ObjectiveThis paper aims to analyze the current status of outcome indicators in randomized controlled trials （RCT） of traditional Chinese medicine （TCM） for treating chronic atrophic gastritis （CAG）， so as to provide references for constructing the core outcome set （COS） of TCM in the treatment of CAG. MethodChina National Knowledge Infrastructure （CNKI）， Wanfang， VIP， SinoMed， PubMed， Embase， and Cochrane Library databases were searched for RCTs of TCM in the treatment of CAG in the last five years. The risk of bias of included studies was evaluated， and the selection status of outcome indicators was statistically analyzed. ResultA total of 150 RCTs were included， with a sample size of 44-398 cases. 164 outcome indicators were reported， with an application frequency of 1 229 times. The outcome indicators were classified into seven indicator domains according to functional attributes， followed by physical and chemical examination （69.41%）， TCM syndrome （12.69%）， symptoms and signs （11.15%）， safety indicators （5.37%）， quality of life （0.65%）， long-term prognosis （0.65%）， and economic evaluation （0.08%）. According to the statistical analysis， there were problems in the selection of outcome indicators in RCTs of TCM for treating CAG， including various indicators， non-standard name reports， unclear primary and secondary indicators， random combination of subjective and objective indicators， neglected patient report outcome indicators， missing long-term prognosis and economic indicators， insufficient reporting of safety indicators， and inconsistent measurement tools and measurement time points. ConclusionIn the past five years， there have been many problems in the selection of outcome indicators in RCTs of TCM for treating CAG. It is necessary to actively promote the construction of the COS of TCM in the treatment of CAG and promote the high-quality development of clinical research of TCM.