parseMedExtractR: Parse medExtractR NLP Output

In EHR: Electronic Health Record (EHR) Data Processing and Analysis Tool

Parse medExtractR NLP Output

Description

Takes files with the raw medication extraction output generated by the medExtractR natural language processing system and converts it into a standardized format.

Usage

parseMedExtractR(filename)

Arguments

filename

File name for a single file containing medExtractR output.

Details

Output from different medication extraction systems is formatted in different ways. In order to be able to process the extracted information, we first need to convert the output from different systems into a standardized format. Extracted expressions for various drug entities (e.g., drug name, strength, frequency, etc.) each receive their own column formatted as "extracted expression::start position::stop position". If multiple expressions are extracted for the same entity, they will be separated by backticks.

The medExtractR system returns extractions in a long table format, indicating the entity, extracted expression, and start:stop position of the extraction. To perform this initial parsing, entities are paired with the closest preceding drug name. The one exception to this is the dose change entity, which can occur before the drug name (see Weeks, et al. 2020 for details).

See EHR Vignette for Extract-Med and Pro-Med-NLP as well as Dose Building Using Example Vanderbilt EHR Data for details.

Value

A data.table object with columns for filename, drugname, strength, dose, route, freq, dosestr, dosechange and lastdose. The filename contains the file name corresponding to the clinical note. Each of the entity columns are of the format "extracted expression::start position::stop position".

Examples

mxr_output <- system.file("examples", "lam_mxr.csv", package = "EHR")
mxr_parsed <- parseMedExtractR(mxr_output)
mxr_parsed

EHR documentation built on Dec. 28, 2022, 1:31 a.m.