评估传统和基因组新生儿查计划的成本效益的数据相关和方法挑战
Ramesh Lamsal1, Hadley Stevens Smith2,3,4, Scott D Grosse5
1Precision Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401 East, Boston, MA, 02215, USA. Ramesh_Lamsal@hphci.harvard.edu.
Applied health economics and health policy
|November 12, 2025
概括
为扩大新生儿查 (NBS) 进行成本效益分析面临着重大数据和方法障碍. 应对这些挑战对于明智制定新NBS条件的政策至关重要.
科学领域:
- 卫生经济学 卫生经济学
- 公共卫生政策 公共卫生政策
- 基因组学就是基因组学.
背景情况:
- 新生儿查 (NBS) 计划正在扩大,需要经济评估来指导政策决策.
- 全球范围内不一致地使用经济评估来告知NBS计划扩张.
- 基因组技术的进步增加了适合NBS的条件的数量.
研究的目的:
- 审查NBS计划的成本效益分析 (CEA) 中的数据相关和方法方面的挑战.
- 要突出阻碍NBS扩张决策可靠证据生成的问题.
- 强调需要改进数据收集和方法方法的必要性.
主要方法:
- 对NBSCEA现有文献的叙述性审查.
- 识别和讨论数据缺口和方法限制.
- 探索基因组NBS特有的挑战.
主要成果:
- 在识别比较器和获取相关数据方面存在重大挑战.
- 了解查和非查人口的健康结果和成本的差距.
- 难以将查效应与治疗改进和有限的社会成本数据隔离起来.
- 基因组NBS引入了与同时条件识别和基因型-表型知识差距相关的复杂性.
结论:
- 解决数据和方法方面的挑战对于NBS计划的强大CEA至关重要.
- 需要改进数据收集和跨学科合作.
- 可靠的经济证据对于对NBS扩张的明智决策至关重要.
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