Work

Development of a natural language processing system to identify timing and status of colonoscopy testing in electronic medical records.

Year: 2009

Type: article

Abstract: Colorectal cancer (CRC) screening rates are low despite proven benefits. We developed natural language processing (NLP) algorithms to identify temporal expressions and status indicators, such as "patient refused" or "test scheduled." The authors incorporated the algorithms into the KnowledgeMap Concept Identifier system in order to detect references to completed colonoscopies within electronic text. The modified NLP system was evaluated using 200 randomly selected electronic medical records (EMRs) from a primary care population aged >/=50 years. The system detected completed colonoscopies with recall and precision of 0.93 and 0.92. The system was superior to a query of colonoscopy billing codes to determine screening status.

Source: PubMed Central

Authors: Joshua C Denny, Josh F Peterson, Neesha N Choma, Hua Xu, Randolph A Miller, Lisa Bastarache, Neeraja B Peterson

Institutions: Vanderbilt University, United States Department of Veterans Affairs, Vanderbilt University Medical Center

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W133035964

FWCI: 0.535

Cites: 2

Cited by: 10

Related to: 10