Learning Health Systems strive to deliver exceptional care by leveraging the clinical mission with research and educational missions. This starts with a clinician who intuitively feels that one patient or a group of patients are different and may represent a new subgroup of diagnosis and treatment. Next, clinicians are empowered with data science platforms to help them securely collect and analyze clinical data, EHR data, clinical notes, medical imaging, time series, and genomics data.
This system also involves bringing new prediction algorithms back into clinical care and evaluating them for their effectiveness. Our group has helped lead efforts at Johns Hopkins to develop the Precision Medicine Analytics Platform (PMAP), which is a secure Azure environment for clinical data with analytical environments.
Ten of our graduate courses use the PMAP environment to train researchers in data science tools with clinical data. The PMAP environment leverages open medical standards such as DICOM, FHIR, and OMOP. We also use many leading open source tools that are at the forefront of conducting research on clinical data. Many faculty and staff take these courses to learn how to conduct research at Johns Hopkins. Our students frequently collaborate with our clinical researchers.
Faculty members in this research area include Chris Chute, MD, DrPH, FACMI, a Bloomberg Distinguished Professor and Chief Research Informatics Officer for Johns Hopkins Medicine; Paul Nagy, PhD, FSIIM, who leads the Observational Health Data Science and Informatics (OHDSI) efforts at Johns Hopkins, and Khzyer Aziz, MD, the Chief Medical Information Officer of the Johns Hopkins Children’s Center and an associate director of the BIDS training program.