Gabrial Brat is a trauma surgeon and assistant professor of surgery at Beth Israel Deaconess Medical Center and an instructor in biomedical informatics at Harvard Medical School. As the director of the Surgical Informatics Lab, Dr. Brat has a broad research focus on informatics tools to improve surgical outcomes. His interests include clinical decision support to optimize surgical opioid prescribing as well as leveraging large-scale database and machine learning models to inform surgical planning and improve outcomes. As the co-founder of a successful venture-backed machine learning and computer vision company, he now teaches health IT innovation courses at the medical school and mentors several digital health startups. Gabriel has an undergraduate degree in bioengineering and a graduate degree in public health and biostatistics from the London School of Hygiene and Tropical Medicine. He completed his medical training at Stanford University and his surgical residency at Johns Hopkins Hospital.
(Analytics Best Practices, Innovative Data and Analytics Transformation, Machine Learning/AI — Course Level: Intermediate)
As COVID-19 makes timely access to comprehensive, accurate patient data increasingly urgent, healthcare organizations, pharma, and public health agencies are struggling to procure needed clinical information. An answer to this data challenge is a national data set that leverages deep, aggregated electronic health record data from patients across the United States, including patient history, comorbidities, vitals, treatment pathways, labs, and more. A proliferation of local standards and a lack of a standard COVID-19 definition has generated problems at the national level, driving the need for a standard COVID-19 patient type definition and registry. Only with this comprehensive, transparent view of patient health and the public health trends can providers, researchers, and policy makers make lasting, impactful progress against the outbreak. Discover how, with aggregated outbreak information from health systems across the United States, a standard COVID-19 definition and registry can accommodate the rapidly changing disease landscape and fill in critical gaps in clinical understanding.