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Free eLearning course on Introduction to Data Management for Clinical Research Studies

Why not start the year with a free eLearning course on Introduction to Data Management for Clinical Research Studies?

Data management in clinical research relates to the process of gathering, capturing, monitoring, analysing and reporting on data. Data management begins with the development of the data management plan and design of the data capture instrument (e.g. the case report form), continues with data collection and regular quality control procedures, the database cleaning, locking and ends with the analysis, archiving and write-up. Good data management requires proper planning and as McFadden (2007) states ‘in parallel with the development of the protocol, the data to be collected to answer the study objectives should be defined’. Friedman et al (1998) pointed out that ‘no study is better than the quality of its data’.

This statement highlights the importance of capturing good quality data that is valid, auditable, and accurate, which can easily be replicated, and measures the intended variables in the research question. As high data quality is essential, recording the study data is the most crucial stage of the data management process. Therefore, developing the data management practices alongside the protocol ensures that all of the protocol-specified data are accurately captured on the case report form (CRF).

The objectives of good clinical data management are to ensure that the study database is: An accurate and true representation of what took place in the and study sufficiently clean to support the statistical analysis and its interpretation The European Clinical Research Infrastructures Network has written some helpful and straightforward guidance on good clinical practice (GCP) compliant data management in multinational clinical studies. Their website address is supplied this course's ‘Resources’ section course.

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