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Clinical Data Management (CDM) is a key part of clinical trials, generating high-quality and reliable data and helping to significantly reduce the time from drug development to market. CDM includes various procedures such as Case Report Form (CRF) designing and annotation, database designing and validation, discrepancy management, medical coding, data extraction, database locking, and quality assessment. CDM aims to provide high-quality data by minimizing the number of errors and missing data and collecting as much data as possible for analysis. CDM team should set standards for data quality to meet appropriate expectations and adapt to the rapidly changing technology. With the implementation of regulatory compliant data management tools, the CDM team can meet the regulatory requirements.
Fig.1 List of clinical data management activities (Barich, 2012)
In multicentric trials, the Clinical Data Management Systems (CDMS) have been used to handle the huge amount of data. Commonly used CDM tools are eClinical Suite, ORACLE CLINICAL, CLINTRIAL, MACRO, and RAVE. These software tools are commercial and more or less similar. They are expensive and need sophisticated information technology infrastructure to function. In addition to the commercial tools, a few open-source tools are available as well, such as OpenClinica, OpenCDMS, TrialDB, and PhOSCo. These software tools are available free of cost and can be downloaded from their respective websites. It is important to maintain an audit trail of data management activities in regulatory submission studies. The CDMS tools help in the management of discrepancies and ensure the audit trail.
There are some guidelines and standards that CDM must be followed. The Code of Federal Regulations (CFR), 21 CFR Part 11 describes the standards in electronic data capture. This regulation applies to the creation, modification, maintenance, archiving, retrieval, or transmission of records in electronic format. The CDM needs to ensure the accuracy, reliability, integrity, authenticity, and confidentiality of data. The submitted data should be entered and processed in 21 CFR part 11-compliant systems. The Good Clinical Data Management Practices (GCDMP) guideline is a document that provides the standards on the accepted practices in CDM that are consistent with regulatory practices. In addition, the Clinical Data Interchange Standards Consortium (CDISC) has developed standards to support the acquisition, exchange, submission, and archival of clinical research data and metadata.
The CDM process is designed to keep the deliverable in view and should start early, even before the finalization of the study protocol. The objective of CDM is to deliver an error-free, valid, and statistically sound database. For the review and finalization of study documents, Data Management Plan (DMP) is developed as a road map to handle the data and describes the CDM activities to be followed in the trial. The CDM activities include the database design, data entry and data tracking guidelines, quality control measures, SAE reconciliation guidelines, discrepancy management, data transfer/extraction, and database locking guidelines. Data Validation Plan (DVP) is another document to help in cleaning up the data by identifying the discrepancies.
Fig.2 Discrepancy management. (Barich 2012)
The members of a CDM team have different roles and responsibilities, and they should be graduation in life science and have knowledge of computer applications. Some key roles are essential to all CDM teams including Data Manager, Database Programmer/Designer, Medical Coder, Clinical Data Coordinator, Quality Control Associate, and Data Entry Associate. The data manager is responsible for overseeing the entire CDM process, preparing the DMP, approving the CDM procedures and all internal documents related to CDM activities.
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