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. 2013 Jun 24;6(Suppl 1):7-16.
doi: 10.4137/BII.S11634. Print 2013.

Analysis of cross-institutional medication description patterns in clinical narratives

Sunghwan Sohn  1 , Cheryl Clark, Scott R Halgrim, Sean P Murphy, Siddhartha R Jonnalagadda, Kavishwar B Wagholikar, Stephen T Wu, Christopher G Chute, Hongfang Liu
Affiliations

Analysis of cross-institutional medication description patterns in clinical narratives

Sunghwan Sohn et al. Biomed Inform Insights. .

Abstract

A large amount of medication information resides in the unstructured text found in electronic medical records, which requires advanced techniques to be properly mined. In clinical notes, medication information follows certain semantic patterns (eg, medication, dosage, frequency, and mode). Some medication descriptions contain additional word(s) between medication attributes. Therefore, it is essential to understand the semantic patterns as well as the patterns of the context interspersed among them (ie, context patterns) to effectively extract comprehensive medication information. In this paper we examined both semantic and context patterns, and compared those found in Mayo Clinic and i2b2 challenge data. We found that some variations exist between the institutions but the dominant patterns are common.

Keywords: electronic medical record; medication extraction; natural language processing.

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Figures

Figure 1
Figure 1
i2b2 medication semantic patterns (top 95%).
Figure 2
Figure 2
Mayo medication semantic patterns mapped to i2b2 (top 95%).
Figure 3
Figure 3
Mayo vs. i2b2 medication semantic patterns in list (top 95%).
Figure 4
Figure 4
Mayo vs. i2b2 medication semantic patterns in narrative (top 95%).
Figure 5
Figure 5
i2b2 vs. Mayo vs. Mayo10K medication semantic patterns with moving average trend (top 95%).
See this image and copyright information in PMC

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