[Effect of data management quality on clinical research evidence evaluation]

Current clinical evaluation of literature quality has various ways. Most of them lay special emphasis on the evaluation of the design quality, but the evaluation of the implementation process quality is not perfect. Especially data management is not fully emphasized during the enforcement of clinical trials. Data from clinical research were bases for evaluating clinical findings. Although strict specifications and requirements for data management might be strictly written clearly in research protocols, they were not embodied in current clinical research evidence evaluation system. Data management is an important part of implementing the whole clinical trial process, which is a comprehensive reflection of data collecting, logging, sorting, and managing. Its objective is to obtain high quality research data for statistical analysis, thereby coming to a true and reliable conclusion. In order to overall evaluating clinical design and implement, we suggest that present quality evaluation indicators of clinical trails should be completed, and add data management quality evaluation during the whole implement process. Data management plans, standards and requirements for data checking, and management regulations for disobeying data and exception data should be added in quality evaluation indicators for clinical research evidence. The effect of data management quality on clinical research evidence evaluation should be emphasized.