将患者偏好纳入医疗决策算法和模型的方法,以及它们的量化,平衡和评估:一个范围审查协议
Jakub Fusiak1, Ulrich Mansmann, Verena S Hoffmann
1Institute for Medical Information Processing, Biometry and Epidemiology - IBE, Faculty of Medicine, LMU Munich, Munich, Germany.
JBI evidence synthesis
|August 28, 2024
概括
本范围审查绘制了将患者偏好整合到医疗算法和模型中的方法. 它确定了这些偏好是如何量化,平衡和评估的,用于个人决策.
科学领域:
- 医疗信息学 医疗信息学
- 健康决策科学健康科学
- 计算健康 计算健康
背景情况:
- 医疗算法和模型对于临床决策至关重要.
- 患者的偏好往往没有被整合,这可能会限制算法的有效性和接受度.
- 整合患者的偏好对于改善共享决策至关重要.
研究的目的:
- 识别和映射将患者偏好纳入医疗算法和模型的方法.
- 通过计算方法分析患者偏好的量化,平衡和评估.
- 专注于个人层面的偏好集成和应用类型.
主要方法:
- 根据JBI的方法进行范围审查.
- 在多个数据库 (PubMed, Web of Science, ACM, IEEE, Cochrane, OpenGrey, NTTL, Google Scholar) 中进行全面的文献搜索.
- 包括各种来源:同行评审的文章,指南,灰色文献,报告和专家意见.
主要成果:
- (结果将在审查完成后填写)
结论:
- (结论将在审查完成后填写)
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