3.0

credits

Average Course Rating

Explores the opportunities and potential of Electronic Health Record (EHR) data for biomedical research, with an emphasis on statistical frameworks and methods for clinical investigation. Introduces types of clinical data captured in EHR systems, including demographics, diagnoses, procedures, medications, laboratory results, imaging, and vital signs. Reviews statistical and analytical challenges inherent in EHR data, such as missingness, measurement errors, and time-dependent structures. Examines recent developments in statistical methods and inferences for addressing these challenges and generating robust clinical evidence. Emphasizes practical considerations for choosing the appropriate statistical methods when leveraging EHR data in evidence generation and knowledge discovery.