Biomedical Informatics, Columbia University, New York, NY 10027,
J Am Med Inform Assoc. 2013 Jan 1;20(1):117-21. doi: 10.1136/amiajnl-2012-001145. Epub 2012 Sep 6.
The national adoption of electronic health records (EHR) promises to make an unprecedented amount of data available for clinical research, but the data are complex, inaccurate, and frequently missing, and the record reflects complex processes aside from the patient's physiological state. We believe that the path forward requires studying the EHR as an object of interest in itself, and that new models, learning from data, and collaboration will lead to efficient use of the valuable information currently locked in health records.
国家采用电子健康记录 (EHR) 有望为临床研究提供前所未有的大量数据,但这些数据复杂、不准确且经常缺失,并且记录反映了除患者生理状态之外的复杂过程。我们认为,前进的道路需要将 EHR 本身作为研究对象,并通过从数据中学习和协作来构建新模型,从而有效地利用目前锁定在健康记录中的有价值信息。