Text Parsing-Based Identification of Patients with Poor Glaucoma Medication Adherence in the Electronic Health Record.

ABSTRACT:

Purpose

To assess the feasibility of automated text parsing screening of physician notes in the electronic health record (EHR) to identify glaucoma patients with poor medication compliance.

Design

Cross-sectional study.

Methods

An automated EHR extraction identified a cohort of patients at the University of Michigan with a diagnosis of glaucoma, ≥40 years old, taking ≥1 glaucoma medication, and having no cognitive impairment. Self-reported medication adherence was assessed with 2 validated instruments: the Chang scale and the Morisky medication adherence scale. In tandem, a text parsing tool that abstracted data from the EHR was used to search for combinations of the following words in patient visit notes: "not," "non," "n't," "no," or "poor" accompanied by "adherence

SUBMITTER: Hamid MS 

PROVIDER: S-EPMC9047064 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature