In this course, you’ll learn to collect and care for the data gathered during your trial and how to prevent mistakes and errors through quality assurance practices. Clinical trials generate an enormous amount of data, so you and your team must plan carefully by choosing the right collection instruments, systems, and measures to protect the integrity of your trial data. You’ll learn how to assemble, clean, and de-identify your datasets. Finally, you’ll learn to find and correct deficiencies through performance monitoring, manage treatment interventions, and implement quality assurance protocols.
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Get Started / More InfoMathematical modelling is increasingly being used to support public health decision-making in the control of infectious diseases. This specialisation aims to introduce...
The Center for Humanitarian Emergencies is a partnership between CDC's Emergency Response and Recovery Branch and the Rollins School of Public Health that drives...
This course aims to provide managers and developers of contact tracing programs guidance on the most important indicators of performance of a contact tracing program,...
The People, Power, and Pride of Public Health provides an engaging overview of the incredible accomplishments and promise of the public health field. The first module...