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Updated: Jan 20, 2026

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care
Published on: February 16, 2011
Rich Text Formatted EHR Narratives: A Hidden and Ignored Trove
Zexian Zeng1, Yuan Zhao1, Mengxin Sun2
1Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Abstract:
This study presents an approach for mining structured information from clinical narratives in Electronic Health Records (EHRs) by using Rich Text Formatted (RTF) records. RTF is adopted by many medical information management systems. There is rich structural information in these files which can be extracted and interpreted, yet such information is largely ignored. We investigate multiple types of EHR narratives in the Enterprise Data Warehouse from a multisite large healthcare chain consisting of both, an academic medical center and community hospitals. We focus on the RTF constructs related to tables and sections that are not available in plain text EHR narratives. We show how to parse these RTF constructs, analyze their prevalence and characteristics in the context of multiple types of EHR narratives. Our case study demonstrates the additional utility of the features derived from RTF constructs over plain text oriented NLP.
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