在治疗中制定和应用基于共识的建议的方法:叙事性审查
Rowan Haffner1, Brian Mathew2, Francesco Brigo3
1Department of Neuroscience, Duke University, Durham, North Carolina, USA.
Epilepsia
|December 15, 2025
概括
在证据稀缺的情况下,基于共识的建议 (CBR) 对治疗至关重要. 德尔菲技术是最常见的,但开发CBR的最佳方法取决于研究目标和资源.
科学领域:
- 神经学 神经学
- 医疗保健服务研究 医疗服务研究
- 医疗信息学 医疗信息学
背景情况:
- 基于共识的建议 (CBR) 在有限或相互矛盾的证据中指导医疗保健决策.
- 像Delphi,名义组技术 (NGT) 和RAND/UCLA适当性方法 (RAM) 这样的既定方法促进了CBR的开发.
- 由于的复杂性和不断变化的性质,管理往往需要CBR.
研究的目的:
- 为了回顾Delphi,NGT和RAM的优缺点.
- 检查这些共识方法在治疗中的应用和频率.
- 为选择适合管理的共识方法提供信息.
主要方法:
- 在PubMed (2017-2022) 的叙事评论中,确定了描述Delphi,NGT和RAM的文章.
- 从1966年到2023年,使用共识方法对病研究进行了全面的审查.
- 包括的研究分析了方法的应用,优点和缺点.
主要成果:
- 16篇文章描述了共识方法,其中Delphi是最常用的 (64个研究中的58个).
- 德尔菲适用于一般管理,罕见疾病和怀孕期间的.
- NGT和RAM用于特定的应用,如大麻的使用,道德决策,成像建议和质量指标.
结论:
- 达成共识的方法对于在管理中开发强大的CBR至关重要,尤其是在缺乏临床指导方针的情况下.
- 德尔菲技术为有限的证据或远程参与提供了适应性.
- 选择共识方法 (Delphi,NGT,RAM) 应该与具体的研究目标和有效治疗的可用资源保持一致.
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