| Purpose: A big data platform was established for the epidemiological study of tracheobronchial tuberculosis.Methods: The national epidemiological study of tracheobronchial tuberculosis is a multicenter cross-sectional study.First,the sample size was estimated and a detailed research plan was developed through multidisciplinary discussion.Secondly,according to the category of the content of the study program,the study program was divided into 10 different question groups,including the standard of admission,basic information of patients,symptoms and so on.Then,the standard fields were constructed by consulting the guide,literature and so on,and a total of129 standard fields were constructed.Then 129 standard fields are assembled into question groups to complete the template construction.Finally,different question groups were added to the blank case report form.The feasibility and scientificity of the platform were verified through the application of the platform by 70 hospitals and the analysis of the data.Results: The big data platform applied to TBTB epidemiologicalstudy was successfully constructed by means of template design,terminology standardization and field assembly.From July 2019 to February 2020,70 hospitals enrolled 634 TB patients using the big data platform for the national epidemiological study of tracheobronchial tuberculosis.Among them,313 patients were confirmed to be TBTB and321 patients were confirmed to be negative for TBTB.It is proved that the big data platform can be applied to the epidemiological study of tracheobronchial tuberculosis.Conclusions: The emergence of big data platform brings a new working mode for clinical research.We successfully built the first big data platform for epidemiological research on TBTB by combining clinical research with the big data platform. |
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