Complexities, variations, and errors of numbering within clinical notes: the potential impact on information extraction and cohort-identification

Abstract Background Numbers and numerical concepts appear frequently in free text clinical notes from electronic health records. Knowledge of the frequent lexical variations of these numerical concepts, and their accurate identification, is important for many information extraction tasks. This paper...

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Bibliographic Details
Main Authors: David A. Hanauer, Qiaozhu Mei, V. G. Vinod Vydiswaran, Karandeep Singh, Zach Landis-Lewis, Chunhua Weng
Format: Article
Language:English
Published: BMC 2019-04-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12911-019-0784-1
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Summary:Abstract Background Numbers and numerical concepts appear frequently in free text clinical notes from electronic health records. Knowledge of the frequent lexical variations of these numerical concepts, and their accurate identification, is important for many information extraction tasks. This paper describes an analysis of the variation in how numbers and numerical concepts are represented in clinical notes. Methods We used an inverted index of approximately 100 million notes to obtain the frequency of various permutations of numbers and numerical concepts, including the use of Roman numerals, numbers spelled as English words, and invalid dates, among others. Overall, twelve types of lexical variants were analyzed. Results We found substantial variation in how these concepts were represented in the notes, including multiple data quality issues. We also demonstrate that not considering these variations could have substantial real-world implications for cohort identification tasks, with one case missing > 80% of potential patients. Conclusions Numbering within clinical notes can be variable, and not taking these variations into account could result in missing or inaccurate information for natural language processing and information retrieval tasks.
ISSN:1472-6947