Project 1. Develop and evaluate the impact of a hands-on course and data use support structures for using real-world data for clinical and translational research.
Real-world data includes data routinely collected for administrative purposes, such as electronic health record data, medical claims billing data, and data gathered from digital sources. While real-world data users typically come to translational research with clinical experience and some statistical training, a barrier in translational science is a lack of training specific to the use of electronic health records and other real-world data. Our approach in project 1 is distinct and complementary to statistical support from iBERD and courses in statistics and epidemiology in focusing on unique aspects of electronic health records and medical claims data. This Project addresses an important translational science gap, which, if successfully addressed, will accelerate translational research with real-world data.