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Clinical data management (CDM) is a critical process in clinical research, which leads to generation of high-quality, reliable, and statistically sound data from clinical trials. [1] Clinical data management ensures collection, integration and availability of data at appropriate quality and cost.
In such CDMSs, the investigators directly upload the data on CDMS, and the data can then be viewed by the data validation staff. Once the data are uploaded by site, the data validation team can send the electronic alerts to sites if there are any problems. Such systems eliminate paper usage in clinical trial validation of data.
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.
Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]
An electronic data capture (EDC) system is a computerized system designed for the collection of clinical data in electronic format for use mainly in human clinical trials. [1] EDC replaces the traditional paper-based data collection methodology to streamline data collection and expedite the time to market for drugs and medical devices.
An electronic trial master file (eTMF) is a trial master file in electronic (digital content) format.It is a type of content management system for the pharmaceutical industry, providing a formalized means of organizing and storing documents, images, and other digital content for pharmaceutical clinical trials that may be required for compliance with government regulatory agencies.
Data verification helps to determine whether data was accurately translated when data is transferred from one source to another, is complete, and supports processes in the new system. During verification, there may be a need for a parallel run of both systems to identify areas of disparity and forestall erroneous data loss .
[3] [4] OMOP developed a Common Data Model (CDM), standardizing the way observational data is represented. [3] After OMOP ended, this standard started being maintained and updated by OHDSI. [1] As of February 2024, the most recent CDM is at version 6.0, while version 5.4 is the stable version used by most tools in the OMOP ecosystem. [5]