ClinicalCodes: An Online Clinical Codes Repository to Improve the Validity and Reproducibility of Research Using Electronic Medical Records
ClinicalCodes: An Online Clinical Codes Repository to Improve the Validity and Reproducibility of Research Using Electronic Medical Records
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DOI：
10.1371/journal.pone.0099825
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发表时间：
2014-06-18
期刊：
影响因子：
3.7
通讯作者：
Reeves, David
中科院分区：
文献类型：
--
作者：
Springate, David A.;Kontopantelis, Evangelos;Reeves, David
临床代码列表是使用电子病历（EMR）进行研究的基础。如果临床代码列表不可用，评审员无法确定研究的有效性，完全的研究复制是不可能的，研究人员无法进行有效的比较研究，新代码列表的构建受到许多重复工作的影响。尽管如此，临床代码的出版很少是获得赠款，验证协议或出版研究的要求。在PubMed上索引的450篇EMR主要研究文章的代表性样本中，我们发现只有19篇（5.1%）附有全套已发表的临床代码，32篇（8.6%）声明代码列表可应要求提供。为了帮助解决这些问题，我们建立了一个在线存储库，使用EMR的研究人员可以上传和下载临床代码列表。该数据库将使临床研究人员能够更好地验证EMR研究，建立在以前的代码列表上，并比较研究中的疾病定义。它还将协助卫生信息学家复制数据库研究，通过时间跟踪疾病定义或临床编码实践的变化，并将临床编码信息作为研究对象跨平台和数据源共享。
Lists of clinical codes are the foundation for research undertaken using electronic medical records (EMRs). If clinical code lists are not available, reviewers are unable to determine the validity of research, full study replication is impossible, researchers are unable to make effective comparisons between studies, and the construction of new code lists is subject to much duplication of effort. Despite this, the publication of clinical codes is rarely if ever a requirement for obtaining grants, validating protocols, or publishing research. In a representative sample of 450 EMR primary research articles indexed on PubMed, we found that only 19 (5.1%) were accompanied by a full set of published clinical codes and 32 (8.6%) stated that code lists were available on request. To help address these problems, we have built an online repository where researchers using EMRs can upload and download lists of clinical codes. The repository will enable clinical researchers to better validate EMR studies, build on previous code lists and compare disease definitions across studies. It will also assist health informaticians in replicating database studies, tracking changes in disease definitions or clinical coding practice through time and sharing clinical code information across platforms and data sources as research objects.