基于人工智能的技术的卫生技术评估框架
Rossella Di Bidino1,2, Signe Daugbjerg1, Sara C Papavero1
1Graduate School of Health Economics and Management, Universita Cattolica del SacroCuore (ALTEMS), 00168Rome, Italy.
International journal of technology assessment in health care
|November 21, 2024
概括
专家们通过卫生技术评估 (HTA) 确定了48个关键主题,用于评估人工智能 (AI) 健康技术 (AIHTs). 关键领域包括人工智能模型的准确性,患者安全和数据偏差,突出了新的HTA框架的需要.
科学领域:
- 医疗技术评估 (HTA) 是指对医疗技术进行评估.
- 医疗保健中的人工智能 (AI)
- 医疗信息学 医疗信息学
背景情况:
- 基于人工智能 (AI) 的健康技术 (AIHT) 在临床环境中越来越多地使用.
- 现有的医疗技术评估 (HTA) 框架缺乏对AIHTs的标准化.
- 对AIHTs.需要一个全面的评估框架.
研究的目的:
- 为AIHTs确定标准化HTA框架的关键主题.
- 确定专家对评估医疗保健人工智能的重要组成部分的共识.
- 为AI-Mind项目制定HTA框架提供信息.
主要方法:
- 进行了两轮的Delphi调查,其中46名专家参与了调查.
- 专家评价了65个主题的AIHT HTA的重要性.
- 根据专家一致评分对主题进行了分类,70%的人表示高度一致.
主要成果:
- 在提出的65个主题中,48个被认为对AIHT HTA框架至关重要.
- 最关键的话题包括人工智能模型的准确性 (97.78%),患者安全 (95.65%),道德利益危害平衡 (95.56%) 和数据偏差 (91.30%).
- 现有的EUnetHTA核心模型不足,20个额外主题中有14个被确定为关键.
结论:
- 在AI相关的HTA主题上建立专家共识对于一个强大的评估框架至关重要.
- 开发的框架将支持对人工智能工具用于早期痴呆症诊断的评估.
- 这项工作是欧洲AI-Mind项目的基础.
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