Using natural language processing to improve efficiency of manual chart abstraction in research: the case of breast cancer recurrence.

ABSTRACT: The increasing availability of electronic health records (EHRs) creates opportunities for automated extraction of information from clinical text. We hypothesized that natural language processing (NLP) could substantially reduce the burden of manual abstraction in studies examining outcomes, like cancer recurrence, that are documented in unstructured clinical text, such as progress notes, radiology reports, and pathology reports. We developed an NLP-based system using open-source software to process electronic clinical notes from 1995 to 2012 for women with early-stage incident breast cancers to identify whether and when recurrences were diagnosed. We developed and evaluated the system using clinical notes from 1,472 patients receiving EHR-documented care in an integrated health care system

SUBMITTER: Carrell DS 

PROVIDER: S-EPMC3939853 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature