Paul Cerrato has more than 30 years of experience working in healthcare as clinician, medical editor and educator. He and John Halamka, MD, have co-authored "Realizing the Promise of Precision Medicine" (Elsevier/Academic Press). He has written extensively on electronic health records, protected health information security, practice management and clinical decision support. He has served as editor of InformationWeek Healthcare, executive editor of Contemporary OB/GYN, senior editor of RN and contributing writer/editor for the Yale University School of Medicine, the American Academy of Pediatrics, Information Week, Medscape, Healthcare Finance News, IMedicalapps.com and Medpage Today.
CIO John Halamka, MD, and his team at Beth Israel Deaconess System use big data and machine learning to create real-world applications that improve clinical decision-making, control costs, and drive efficiencies.
In this session, Dr. Halamka and colleague Paul Cerrato (they collaborated on the book Realizing the Promise of Precision Medicine) cut through the machine-learning hype and present evidence of what it can, and can’t do. Along the way, Dr. Halamka will discuss some of the dozen or so machine-learning projects underway at Beth Israel. These include managing ICU census, decreasing specialty appointment no-shows, and forwarding patient-consent forms to the right OR staffers.
- Machine learning may be at the top of the Gartner Hype Cycle, but it’s real, impactful, and can be implemented today.
- Machine learn will augment physicians, not replace them.
- Machine learning and data analytics can personalize patient care.