人工智能辅助指示选择对成像临床决策支持的适当性顺序评分的影响
Lauren A Shreve1, Jessica G Fried2, Fang Liu3
1Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.
Journal of the American College of Radiology : JACR
|June 30, 2023
概括
一个人工智能 (AI) 工具改善了先进的门诊成像的适当性评分和结构化订单输入. 然而,由于供应商和基础设施障碍,近一半的订单仍然没有得分.
科学领域:
- 放射学和医学成像学 医学成像学
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
背景情况:
- 先进的门诊成像订单依赖于准确的适宜性指示.
- 自由文本指示对自动化分析和临床决策支持提出了挑战.
- 实施人工智能 (AI) 工具可能会改善成像订单的结构化输入和评分.
研究的目的:
- 评估人工智能工具对适当性评分和在门诊成像中对自由文本指示的结构化顺序输入的影响.
- 评估AI实施后得分和结构化订单比例的变化.
主要方法:
- 一项多中心研究分析了AI工具部署前后的门诊高级成像订单.
- 数据包括临床决策支持得分和指示类型 (结构化与自由文本).
- 统计分析包括千二测试和多变量逻辑回归.
主要成果:
- 在AI实施后,得分订单从30%增加到52% (P < .001).
- 结构化指示显著上升,从34.6%上升到67.3% (P < .001).
- 订单更有可能通过人工智能工具得分 (OR,2.7),但47.8%的订单仍然没有得分.
结论:
- 人工智能在临床决策支持中的整合增强了结构化订单和得分的可能性.
- 供应商的行为和基础设施的局限性导致了大量未得分的订单.
- 需要进一步优化,以克服障碍,并最大限度地提高AI在成像订单管理方面的优势.
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