Foundations of Clinical Data and its Applications
4 credits, Fall Semester
Data generated by the health system (“clinical data”) as part of patient care is diverse and complex to interpret, mainly when used to create predictive algorithms, configure precise study cohorts, identify co-morbidities, evaluate outcomes, etc. Furthermore, since each data type may exclude information necessary to a given project goal, it is essential that users understand the nature, limitations, and opportunities of each data source before selecting one and using it for scientific inquiry. This introduction to clinical data types will cover those sources most typically used in human health research, such as electronic health records, national databases, insurer data, and commercially available consolidated databases. It will provide an essential foundation for students evaluating publications and research deriving from these sources.
Sebastian Schneeweiss, MD, ScD
Professor of Medicine, Harvard Medical School
Professor in Epidemiology, Harvard T.H. Chan School of Public Health