In Clinical Trials Data Management and Quality Assurance, you’ll delve into the meticulous processes of collecting, managing, and safeguarding clinical trial data. The course encompasses the careful selection of data collection instruments, data assembly, statistical performance monitoring, intervention management, and quality assurance protocols.
Throughout the course, you will learn how to handle various aspects of data management, including data integrity, cleaning, and de-identification. Additionally, you will explore the critical stages of trial performance monitoring and intervention management, ensuring the integrity and quality of the trial data.
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Delve into the intricacies of data collection instruments, data management, assembly and distribution, performance monitoring, intervention management, and quality assurance protocols in this comprehensive course from Johns Hopkins University.
Explore the fundamental aspects of data collection instruments, encompassing definitions, design considerations, interactions with database systems, and revision protocols.
Gain insights into data management principles, including database systems, Excel usage, external data handling, data integrity, and overall data management processes.
Learn about critical stages such as data freeze, data cleaning, de-identification, data sharing, and adherence to data standards in the context of data assembly and distribution.
Discover the importance of performance monitoring throughout different trial stages, site visits, and overall trial performance assessment.
Understand the principles and examples of managing treatment interventions, including masking interventions, managing treatment supplies, and ensuring intervention integrity.
Master the implementation of quality assurance protocols across trial design, preparation, execution, and conclusion phases, ensuring trial data accuracy and integrity.
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