Data Management in Clinical Trials

Dr. Feng Li

What is Data Management in Clinical Trials? Clinical Data Management (CDM) is designing and implementing quality strategies and tactics for acquiring, managing and securing prospective or retrospective clinical data. That clinical data is used to generate or support hypotheses in the development of medical treatments and interventions to advance global healthcare. Or in simpler terms, clinical data management is the handling of clinical trial information to be used for calculation and analysis to support clinical hypotheses. CDM activities include case report form (CRF) design, database design and edit check programming, data acquisition, data validation and review, medical coding, data integration, data standards, and database finalization. These activities are normally categorized into three different stages: Study Start-up, Study Conduct, and Study Closeout.

Although CDM professionals should generally follow standard practices to perform those tasks, one should realize that the phase and therapeutic area of a study can lead to differences in tasks and how each task should be performed. For example, a global Late Phase Registry study with many sites and subjects requires a different approach than a single site Phase I Oncology study does. During the study start-up phase, CDM professionals work closely with team members from other functional areas to create the Data Management Plan (DMP) document, design paper or electronic CRFs, create and test the clinical databases and specify, program, and validate edit checks. They typically work with the project manager, clinical research associate (CRA), investigator/study coordinator, SAS programmer, biostatistician, and regulatory specialist. The DMP defines the roles and responsibilities, processes, standards, and timelines around all data management activities. It must comply with all applicable regulatory guidelines such as ICH and FDA and each organization’s standard operating procedures (SOPs). The DMP is a living document throughout the study’s life cycle so that any protocol amendments or other related changes to the study resulting in data management process changes can be documented. CRFs are among the basic instruments used in clinical trials to collect data. Therefore they are critical to the entire data management process. Whether it’s traditional paper CRFs that the CRAs will collect from the sites and send to CDM personnel for entering into the database or electronic CRFs that the study coordinators at sites will directly complete online, the basic principle of CRF development is the same — the CRFs need to collect data specified by the protocol in an easy-to-use way. Well-designed CRFs can reduce the time and effort of all CDM activities from sites completing the CRFs to producing clean data for analysis. Some key points that should be considered when developing CRFs include thorough understanding of the protocol, avoiding collection of extraneous data that will not be used for analysis, using clear and concise prompts and instructions, avoiding redundant data points, and using industry and organization standards.



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