Medical Education Must Move From the Information Age to the Age of Artificial Intelligence. (August 2018)

• Record Type: Journal Article
• Authors: Wartman, Steven A.; Combs, C. Donald
• Is Part Of: Academic medicine. Volume 93:Number 8(2018)
• Publication Date: 2018-08
• Subjects: Medical education -- Periodicals; Medical policy -- Periodicals; Medical personnel -- Periodicals; Periodicals; 610.711
• DOI: 10.1097/ACM.0000000000002044
• Languages: English
• ISSNs: 1040-2446

Abstract

Abstract : Noteworthy changes coming to the practice of medicine require significant medical education reforms. While proposals for such reforms abound, they are insufficient because they do not adequately address the most fundamental change—the practice of medicine is rapidly transitioning from the information age to the age of artificial intelligence. Increasingly, future medical practice will be characterized by: the delivery of care wherever the patient happens to be; the provision of care by newly constituted health care teams; the use of a growing array of data from multiple sources and artificial intelligence applications; and the skillful management of the interface between medicine and machines. To be effective in this environment, physicians must work at the top of their license, have knowledge spanning the health professions and care continuum, effectively leverage data platforms, focus on analyzing outcomes and improving performance, and communicate the meaning of the probabilities generated by massive amounts of data to patients, given their unique human complexities. The authors believe that a "reboot" of medical education is required that makes better use of the findings of cognitive psychology and pays more attention to the alignment of humans and machines in education and practice. Medical education needs to move beyond the foundational biomedical and clinical sciences. Systematic curricular attention must focus on the organization of professional effort among health professionals, the use of intelligence tools involving large data sets, and machine learning and robots, all the while assuring the mastery of compassionate care.