将患者偏好纳入医疗决策模型的方法的实际应用:一个范围审查
Jakub Fusiak1, Kousha Sarpari2, Inger Ma2
1The Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig-Maximilians-Universität, Marchioninistr. 15, 81377, Munich, Bavaria, Germany. jakub.fusiak@ibe.med.uni-muenchen.de.
BMC medical informatics and decision making
|March 3, 2025
概括
将患者的偏好纳入医疗决策模型对于有效的个性化护理至关重要. 本综述映射了所使用的计算方法,强调了需要有凝聚力的框架和临床医生的参与,以改善现实世界的应用.
科学领域:
- 医疗保健中的计算方法
- 医疗决策模型的模型
- 患者为中心的护理
背景情况:
- 临床算法和模型对于决策至关重要,但往往缺乏患者偏好的整合.
- 这种限制会影响模型的有效性,准确性,接受性和可理解性.
- 开发方法以纳入患者的偏好对于推进个性化医学的发展至关重要.
研究的目的:
- 识别和绘制用于将患者偏好整合到个性化医疗决策模型中的计算方法.
- 报告应用这些整合方法的医疗决策模型类型.
主要方法:
- 按照乔安娜·布里格斯研究所 (JBI) 的方法进行了全面的范围审查.
- 在多个数据库 (PubMed,科学网,ACM,IEEE,Cochrane,OpenGrey,NTIS) 和谷歌学者中进行了搜索.
- 包括任何日期或语言的文章,专注于实际应用和使用JBI框架分析数据.
主要成果:
- 从超过7000篇识别的文章中审查了45篇出版物,揭示了纳入患者偏好的各种方法.
- 主要的临床应用侧重于瘤和循环系统疾病,利用多标准决策分析 (MCDA) 和统计模型.
- 纳入患者偏好显著影响治疗决策,强调了共享和个性化的决策的重要性.
结论:
- 为了将患者的偏好纳入医疗决策模型,存在各种各样的方法.
- 凝聚力框架仍然存在一个关键的差距,阻碍了一致性和临床医生接受.
- 未来的研究必须优先考虑与临床医生共同设计和现实世界的测试,以提高实用性和以患者为中心的护理.
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