Department of Critical Care Medicine, Jinhua Municipal Central Hospital, Jinhua Hospital of Zhejiang University, Jinhua 321000, China.
Ann Transl Med. 2015 Nov;3(20):303. doi: 10.3978/j.issn.2305-5839.2015.11.26.
Electronic medical record (EMR) system has been widely used in clinical practice. Instead of traditional record system by hand writing and recording, the EMR makes big data clinical research feasible. The most important feature of big data research is its real-world setting. Furthermore, big data research can provide all aspects of information related to healthcare. However, big data research requires some skills on data management, which however, is always lacking in the curriculum of medical education. This greatly hinders doctors from testing their clinical hypothesis by using EMR. To make ends meet, a series of articles introducing data management techniques are put forward to guide clinicians to big data clinical research. The present educational article firstly introduces some basic knowledge on R language, followed by some data management skills on creating new variables, recoding variables and renaming variables. These are very basic skills and may be used in every project of big data research.
电子病历（EMR）系统已在临床实践中得到广泛应用。与传统的手写记录方式相比，EMR 使得大数据临床研究成为可能。大数据研究最重要的特点是其真实环境。此外，大数据研究可以提供与医疗保健相关的各个方面的信息。然而，大数据研究需要一些数据管理技能，而这些技能在医学教育课程中往往是欠缺的。这极大地阻碍了医生通过 EMR 检验他们的临床假设。为了解决这个问题，我们提出了一系列介绍数据管理技术的文章，以指导临床医生进行大数据临床研究。本文首先介绍了 R 语言的一些基础知识，然后介绍了一些数据管理技能，包括创建新变量、重新编码变量和重命名变量。这些都是非常基本的技能，可能会在每个大数据研究项目中使用。
