走向基于证据的实践2.0:在医疗保健中利用人工智能
Per Nilsen1,2, David Sundemo3,4, Fredrik Heintz5
1School of Health and Welfare, Halmstad University, Halmstad, Sweden.
Frontiers in health services
|June 26, 2024
概括
人工智能 (AI) 可以通过改进数据处理和潜在地提高患者参与度来帮助克服基于证据的实践 (EBP) 中的挑战. 需要进一步的研究来验证AI在基于证据的医疗保健中的作用.
科学领域:
- 医疗保健创新 医疗保健创新
- 临床决策支持系统临床决策支持系统
- 医学中的人工智能
背景情况:
- 基于证据的实践 (EBP) 整合了证据,临床经验和患者偏好,以获得最佳的决策.
- 尽管EBP有好处,但存在重大障碍,阻碍其在临床环境中的一致应用.
- 人工智能 (AI) 正在成为增强临床决策和应对EBP挑战的工具.
研究的目的:
- 确定EBP的三个核心组成部分中的关键挑战.
- 探索AI在克服这些已识别的EBP挑战方面的潜力.
- 评估AI对推进基于证据的医疗保健实践的贡献.
主要方法:
- 进行了选择性的文献综述.
- 审查的重点是关于EBP挑战的现有研究.
- 该审查审查了人工智能在医疗保健中的整合和潜在应用.
主要成果:
- 由于证据稀缺,传播延迟以及将研究结果应用于不同患者群体的困难,EBP面临着局限性.
- 临床医生的偏见,患者的健康素养和沟通障碍阻碍了共同的决策.
- 人工智能在处理复杂数据方面表现出潜力,在图像分析等领域提供帮助,并可以提高临床医生的效率和患者参与度.
结论:
- 人工智能为增强基于证据的医疗保健提供了有前途的解决方案,可能迎来"EBP 2.0"时代.
- 关于人工智能对基于证据的医疗保健的确切影响,仍然存在不确定性.
- 实证研究对于验证人工智能的有效性和将其整合到临床实践中至关重要.
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