Development of a text mining algorithm for identifying adverse drug reactions in electronic health records.

ABSTRACT:

Objective

Adverse drug reactions (ADRs) are a significant healthcare concern. They are often documented as free text in electronic health records (EHRs), making them challenging to use in clinical decision support systems (CDSS). The study aimed to develop a text mining algorithm to identify ADRs in free text of Dutch EHRs.

Materials and methods

In Phase I, our previously developed CDSS algorithm was recoded and improved upon with the same relatively large dataset of 35 000 notes (Step A), using R to identify possible ADRs with Medical Dictionary for Regulatory Activities (MedDRA) terms and the related Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT) (Step B). In Phase II, 6 existing text-mining R-scripts were used to detect and present unique ADRs, and posit

SUBMITTER: van de Burgt BWM 

PROVIDER: S-EPMC11328534 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature