Comparison of Clinical Knowledge Bases for Summarization of Electronic Health Records

被引:0
|
作者
McCoy, Allison B. [1 ]
Sittig, Dean F. [1 ]
Wright, Adam [2 ]
机构
[1] Univ Texas Sch Biomed Informat Houston, Houston, TX 77030 USA
[2] Brigham & Womens Hosp, Harvard Med Sch, Boston, MA USA
关键词
Electronic health records; knowledge bases; data collection; machine learning;
D O I
10.3233/978-1-61499-289-9-1217
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Automated summarization tools that create condition-specific displays may improve clinician efficiency. These tools require new kinds of knowledge that is difficult to obtain. We compared five problem-medication pair knowledge bases generated using four previously described knowledge base development approaches. The number of pairs in the resulting mapped knowledge bases varied widely due to differing mapping techniques from the source terminologies, ranging from 2,873 to 63,977,738 pairs. The number of overlapping pairs across knowledge bases was low, with one knowledge base having half of the pairs overlapping with another knowledge base, and most having less than a third overlapping. Further research is necessary to better evaluate the knowledge bases independently in additional settings, and to identify methods to integrate the knowledge bases.
引用
收藏
页码:1217 / 1217
页数:1
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