Development and evaluation of an interoperable natural language processing system for identifying pneumonia across clinical settings of care and institutions.

ABSTRACT:

Objective

To evaluate the feasibility, accuracy, and interoperability of a natural language processing (NLP) system that extracts diagnostic assertions of pneumonia in different clinical notes and institutions.

Materials and methods

A rule-based NLP system was designed to identify assertions of pneumonia in 3 types of clinical notes from electronic health records (EHRs): emergency department notes, radiology reports, and discharge summaries. The lexicon and classification logic were tailored for each note type. The system was first developed and evaluated using annotated notes from the Department of Veterans Affairs (VA). Interoperability was assessed using data from the University of Utah (UU).

Results

The NLP system was comprised of 782 rules and achieved moderate-t

SUBMITTER: Chapman AB 

PROVIDER: S-EPMC9801965 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature