Impact of Artificial Intelligence on Clinician Training, Practice

Proponents of artificial intelligence (AI) tout its potential to revolutionize healthcare delivery. Machine learning is identifying high-risk patients for preventive treatments, deep learning algorithms are scanning radiology images to spot cancer providers cannot see with their own eyes, and natural language processing is decreasing the time it takes providers to code for billing. This is the second of two-part series on the implications of artificial intelligence on patient care. With such broad potential impact, providers need to be prepared for their workflow to change as AI becomes more integrated into clinical practice. To do so, future and current providers will need training on how to better understand the tools and the ethical implications associated with adopting these technologies into clinical practice. Some physicians argue that using AI is not what they went to medical school to learn. Training prepared them to make diagnostic decisions to treat their patients, not understand how to use computer algorithms. However, big data and AI are integrated into clinical practice more each day. It’s becoming impossible for providers to avoid understanding these methods. “It’s no longer sufficient to read the New England Journal of Medicine, JAMA, and Academic Medicine in Nature and Science,” said C. Donald Combs, PhD, vice president of the School of Health Professions at Eastern Virginia Medical School (EVMS). “There’s no way to keep up with all the current information. We need to be teaching a strategy for trying to keep up with the information.”