Comparison of clinical knowledge bases for summarization of electronic health records.
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.
The University of Texas School of Biomedical Informatics at Houston, Houston, TX, USA.
Allison B
AB
McCoy
Dean F
DF
Sittig
Adam
A
Wright
D001185:Artificial Intelligence; D057286:Electronic Health Records / Q000145:classification* / Q000706:statistics & numerical data*; D008498:Medical Record Linkage / Q000379:methods*; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D018511:Systems Integration; D014481:United States; D018875:Vocabulary, Controlled