Based on evidence-based medicine (EBM) and from the viewpoint of providing scientific evidence for clinical application, we found that Traditional Chinese Medicine (TCM) was short of adequate evidence to support its therapeutic effects due to lack of high quality clinical research. Data management plays a very important role in clinical research. Lack of adequate data management may lead to low quality clinical research. Thus, it is of great importance to establish a set of standards for data management so as to improve the quality of clinical research. Based on the real practice in Myocardial Infarction Secondary Prevention Study in TCM (MISPS-TCM), this article introduces methods on data audit in clinical trials of TCM.
Data management system is a major factor affecting the quality of clinical trial. Development of data management system include a steering group and data safety and monitoring board, data collection, database, performance of the data safety and monitoring, as well as locking of database. This article provides key issues of the five parts so as to help researchers understand the clinical trial data management system.
Poor compliance in clinical studies is a risk factor leading to bias of results of clinical research. However, while the subject compliance has received extensive attention, researcher compliance has not been paid enough attention. The problem of researcher compliance runs through the whole process of clinical research. How to control and evaluate the researcher compliance is the key problem in clinical research. Based on the current situation of poor compliance of clinical researchers, this paper summaried the information of five different dimensions that affects the researcher compliance in clinical research, clarified the relevant factors that may affect the researcher compliance in the process of clinical research, and analyzed the influence of the factors related to the researcher compliance on the quality control of clinical research, hence establishing a foundation for further research on control strategies and evaluation techniques of researcher compliance.
With the increasing improvement of real-world evidence as a research system and guideline specification for pre-market registration and post-market regulatory decision support of clinically urgent drug and mechanical products, identifying an approach to ensure the high quality and standards of real-world data and establishing a basis for the generation of real-world evidence is receiving increasing attention and concern from regulatory authorities. Based on the experience of Boao hope city real-world data research pattern and ophthalmic data platform construction, this paper discussed the "source data-database-evidence chain" generation process, data management, and data governance in real-world study from the special features and necessity of multiple sources and heterogeneity of data, multiple research designs, and standardized regulatory requirements, and provided references for further construction of comprehensive research data platforms in the future.