Building longitudinal medication dose data using medication information extracted from clinical notes in electronic health records.

ABSTRACT:

Objective

To develop an algorithm for building longitudinal medication dose datasets using information extracted from clinical notes in electronic health records (EHRs).

Materials and methods

We developed an algorithm that converts medication information extracted using natural language processing (NLP) into a usable format and builds longitudinal medication dose datasets. We evaluated the algorithm on 2 medications extracted from clinical notes of Vanderbilt's EHR and externally validated the algorithm using clinical notes from the MIMIC-III clinical care database.

Results

For the evaluation using Vanderbilt's EHR data, the performance of our algorithm was excellent; F1-measures were ≥0.98 for both dose intake and daily dose. For the external validation using MIMIC-I

SUBMITTER: McNeer E 

PROVIDER: S-EPMC7973457 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature