| Literature DB >> 27652572 |
Katie Chockley1, Ezekiel Emanuel2.
Abstract
Radiology faces at least three major, potentially fatal, threats. First, as care moves out of the hospital, there will be a decrease in demand for imaging. More care in patients' homes and in other nonhospital settings means fewer medical tests, including imaging. Second, payment reform and, in particular, bundled payments and capitation mean that imaging will become a cost rather than a profit center. These shifts in provider payment will decrease the demand for imaging and disrupt the practice of radiology. Potentially, the ultimate threat to radiology is machine learning. Machine learning will become a powerful force in radiology in the next 5 to 10 years and could end radiology as a thriving specialty.Entities:
Keywords: Machine learning; future of health care; payment reform; technology
Mesh:
Year: 2016 PMID: 27652572 DOI: 10.1016/j.jacr.2016.07.010
Source DB: PubMed Journal: J Am Coll Radiol ISSN: 1546-1440 Impact factor: 5.532