The proliferation of real-world data (RWD) is providing researchers with greater opportunity to study clinical outcomes in diverse approaches outside of traditional randomized clinical trials. These real-world data based on observational studies can include retrospective studies (eg, clinical/hospital record/chart review, administrative data/insurance claims database studies, and electronic medical records data studies), or prospective studies (eg, registries, health surveys, prospective observational studies, or post-authorization safety studies). While RWD studies have great potential to study once-unattainable questions, they also pose their own set of challenges.
This course will introduce the different types of RWD-based studies and address their fundamental design strategies as well as inherent challenges such as validity, quality of data and confounding. Presenters will also introduce study design aspects such as the research question, data sources, population, sample size, endpoints, and internal and external validity considerations.