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将电子健康记录概念与医疗保健流程事件相关联。

Correlating electronic health record concepts with healthcare process events.

机构信息

Biomedical Informatics, Columbia University, New York, New York, USA.

出版信息

J Am Med Inform Assoc. 2013 Dec;20(e2):e311-8. doi: 10.1136/amiajnl-2013-001922. Epub 2013 Aug 23.

Abstract

OBJECTIVE

To study the relation between electronic health record (EHR) variables and healthcare process events.

MATERIALS AND METHODS

Lagged linear correlation was calculated between five healthcare process events and 84 EHR variables (24 clinical laboratory values and 60 clinical concepts extracted from clinical notes) in a 24-year database. The EHR variables were clustered for each healthcare process event and interpreted.

RESULTS

Laboratory tests tended to cluster together and note concepts tended to cluster together. Within each of those two classes, the variables clustered into clinically sensible groupings. The exact groupings varied from healthcare process event to event, with the largest differences occurring between inpatient events and outpatient events.

DISCUSSION

Unlike previously reported pairwise associations between variables, which highlighted correlations across the laboratory-clinical note divide, incorporating healthcare process events appeared to be sensitive to the manner in which the variables were collected.

CONCLUSION

We believe that it may be possible to exploit this sensitivity to help knowledge engineers select variables and correct for biases.

摘要

目的

研究电子健康记录(EHR)变量与医疗保健过程事件之间的关系。

材料和方法

在 24 年的数据库中,计算了 5 个医疗保健过程事件与 84 个 EHR 变量(24 个临床实验室值和 60 个从临床记录中提取的临床概念)之间的滞后线性相关性。为每个医疗保健过程事件聚类和解释 EHR 变量。

结果

实验室测试往往聚集在一起,而笔记概念往往聚集在一起。在这两类中的每一类中,变量都聚类成具有临床意义的分组。具体的分组因医疗保健过程事件而异,住院事件和门诊事件之间的差异最大。

讨论

与之前报告的变量之间的成对关联不同,这些关联突出了实验室记录之间的相关性,而纳入医疗保健过程事件似乎对变量的收集方式敏感。

结论

我们相信,利用这种敏感性来帮助知识工程师选择变量和纠正偏差是可能的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f73d/3861922/34f6e57a6c0f/amiajnl-2013-001922f01.jpg

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