重新审视患者偏好预测因素:在技术上可行,在伦理上可取,但必须在临床上具有相关性
Andrea Ferrario1,2,3, Beatrix Göcking1,4, Giovanna Brandi4,5
1Institute of Biomedical Ethics and History of Medicine, University of Zurich, Zurich, Switzerland.
预测患者对残疾人的治疗偏好是一项挑战. 目前的算法由于缺乏临床相关性而失败,而不是技术或伦理问题,阻碍了符合目标的护理.
科学领域:
- 医学伦理 医学伦理
- 医疗信息学 医疗信息学
- 临床决策支持 临床决策支持
背景情况:
- 符合目标的护理对于以患者为中心的医学至关重要.
- 确定失能患者的治疗偏好是一个重大的临床挑战.
- 预测患者偏好的现有算法模型尚未成功实施.
研究的目的:
- 分析患者治疗偏好预测算法模型缺乏临床实施的原因.
- 提出一种新的设计视角,以提高这些模型的临床相关性.
- 探索改进的算法模型在严重急性脑损伤患者的神经重症监护中的应用.
主要方法:
- 对预测患者治疗偏好的现有算法方法的概念分析.
- 一个以神经密集护理为重点的案例研究,针对严重急性脑损伤患者.
- 讨论技术设计原则的临床相关性.
主要成果:
- 当前算法的失败源于一个设计缺陷:将它们视为预先指令的抽象复制品,忽视特定环境因素.
- 技术复杂性和伦理考虑本身并不能保证临床实用性.
- 为了成功实施,需要一个新的设计视角,专注于临床相关性.
结论:
- 预测患者偏好的算法模型必须以临床相关性为核心而设计.
- 特定于背景,时间和关系因素对于准确和有用的偏好预测至关重要.
- 成功实施需要从技术复制转向环境意识,临床综合设计.
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