使用人工智能的公平性 死亡率预测以准护理目标 文件
Gina M Piscitello1,2, Shari Rogal3,4, Jane Schell5,6
1Division of General Internal Medicine, Section of Palliative Care and Medical Ethics, University of Pittsburgh, Pittsburgh, PA, USA. ginapiscitello@pitt.edu.
Journal of general internal medicine
|June 10, 2024
概括
人工智能 (AI) 风险评分有助于针对患者进行医疗目标对话. 然而,人工智能可能无意中使没有分数的患者处于不利地位,可能会扩大健康差异.
科学领域:
- 医疗信息学 医疗信息学
- 健康 公平 卫生 公平
- 临床决策支持 临床决策支持
背景情况:
- 人工智能 (AI) 越来越多地被用于识别患有高死亡风险的患者,以讨论医疗目标 (GOC).
- 这种做法旨在积极地让患者参与终身护理计划.
研究的目的:
- 评估人工智能产生的死亡风险得分存在或不存在与中国政府对话的记录之间的关联.
- 根据AI风险评分分配,调查中国政府文件中的潜在差异.
主要方法:
- 对13710名住院成年患者进行了回顾性横截面研究.
- 使用严重疾病风险指标 (SIRI) 评分来定义高 (>30%的90天死亡风险) 或不存在的评分.
- 员工倾向得分匹配和后勤回归来比较中国政府的文档率.
主要成果:
- 与没有得分 (aOR 2.1,p<0.0001) 的患者相比,患有SIRI得分升高的患者更有可能拥有中国医疗机构的文档.
- 缺乏SIRI评分的患者更有可能是年轻的,非白人,并且有医疗补助保险.
- 该干预的目标是增加中国政府对AI风险得分较高的患者的文件.
结论:
- 对中国政府文档的AI驱动准可能会导致差异,可能使没有AI分数的患者处于不利地位.
- 缺乏人工智能产生的分数的重病患者,通常来自少数群体和较低的社会经济群体,可能会收到更不针对性的GOC文档.
- 这强调了需要在临床护理途径中公平地实施人工智能的需要.
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