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The data management plan describes the activities to be conducted in the course of processing data. Key topics to cover include the SOPs to be followed, the clinical data management system (CDMS) to be used, description of data sources, data handling processes, data transfer formats and process, and quality control procedure
A clinical data management system or CDMS is a tool used in clinical research to manage the data of a clinical trial. The clinical trial data gathered at the investigator site in the case report form are stored in the CDMS. To reduce the possibility of errors due to human entry, the systems employ various means to verify the data.
Test data can be produced in a focused or systematic manner, as is typically the case in domain testing, or through less focused approaches, such as high-volume randomized automated tests. [3] Test data can be generated by the tester or by a program or function that assists the tester. It can be recorded for reuse or used only once.
Examples include—MODIFY and—DECOD, which are equivalent terms for a --TRT or—TERM topic variable, --TEST and—LOINC which are equivalent terms for a --TESTCD. Record Qualifiers define additional attributes of the observation record as a whole (rather than describing a particular variable within a record).
Good clinical data management practice (GCDMP) is the current industry standards for clinical data management that consist of best business practice and acceptable regulatory standards. In all phases of clinical trials , clinical and laboratory information must be collected and converted to digital form for analysis and reporting purposes.
Health data are classified as either structured or unstructured. Structured health data is standardized and easily transferable between health information systems. [4] For example, a patient's name, date of birth, or a blood-test result can be recorded in a structured data format.
Often, a clinical trial management system provides data to a business intelligence system, which acts as a digital dashboard for trial managers. [5] [6] [7] CTMSs allow experts easily to access centralized data and thus reducing the number of delayed trials. Sponsors can work with a database of previously researched contacts and names of ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]