利用信息学优化临床研究参与者的选择
Optimizing Clinical Research Participant Selection with Informatics.
作者信息
Weng Chunhua
机构信息
Department of Biomedical Informatics, Columbia University, 622 W 168 Street, PH-20, Room 407, New York, NY 10032, USA.
出版信息
Trends Pharmacol Sci. 2015 Nov;36(11):706-709. doi: 10.1016/j.tips.2015.08.007.
Abstract
Clinical research participants are often not reflective of real-world patients due to overly restrictive eligibility criteria. Meanwhile, unselected participants introduce confounding factors and reduce research efficiency. Biomedical informatics, especially Big Data increasingly made available from electronic health records, offers promising aids to optimize research participant selection through data-driven transparency.
摘要
由于入选标准过于严格，临床研究参与者往往不能反映真实世界的患者情况。与此同时，未经筛选的参与者会引入混杂因素并降低研究效率。生物医学信息学，尤其是电子健康记录中越来越多的大数据，为通过数据驱动的透明度优化研究参与者选择提供了有前景的辅助手段。
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