Triad Radiology Associates, Winston Salem, North Carolina.
Hackensack Radiology Group, PA, River Edge, New Jersey.
J Am Coll Radiol. 2019 Sep;16(9 Pt B):1357-1361. doi: 10.1016/j.jacr.2019.05.004.
For data science tools to mature and become integrated into routine clinical practice, they must add value to patient care by improving quality without increasing cost, by reducing cost without changing quality, or by both reducing cost and improving quality. Artificial intelligence (AI) algorithms have potential to augment data-driven quality improvement for radiologists. If AI tools are adopted with population health goals in mind, the structure of value-based payment models will serve as a framework for reimbursement of AI that does not exist in the fee-for-service system.
为了使数据科学工具成熟并融入常规临床实践，它们必须通过提高质量而不增加成本、降低成本而不改变质量或同时降低成本和提高质量来为患者护理增加价值。人工智能 (AI) 算法有可能增强放射科医生的数据驱动质量改进。如果考虑到人口健康目标而采用 AI 工具，基于价值的支付模式的结构将作为一种报销框架，而这种报销在按服务收费系统中是不存在的。
