Medication Accuracy in Electronic Health Records for Microbial Keratitis

Abstract

Importance: Electronic health records (EHRs) contain an abundance of health information. However, researchers need to understand data accuracy to ask appropriate research questions.

Objective: To investigate the concordance of the names of medications for microbial keratitis in the structured, formal EHR medication list and the text of clinicians' progress notes.

Design, setting, and participants: This cross-sectional study, conducted in the cornea section of an ophthalmology department in a tertiary care, referral academic medical center, examined the medications of 53 patients with microbial keratitis treated until disease resolution from July 1, 2015, to August 1, 2018. Documentation of medications was compared between the structured medication list extracted from the EHR server and medications written into the clinical progress note and transcribed by the study team.

Exposure: Medication treatment for microbial keratitis.

Main outcomes and measures: Medication mismatch frequency.

Results: The study sample included 24 men and 29 women, with a mean (SD) age of 51.8 (19.6) years. Of the 247 medications identified, 57 (23.1%) of prescribed medications differed between the progress notes and the formal EHR-based medication list. Reasons included medications not prescribed via the EHR ordering system (25 [43.9%]), outside medications not reconciled in the internal EHR medication list (23 [40.4%]), and medications prescribed via the EHR ordering system and in the formal list, but not described in the clinical note (9 [15.8%]). Fortified antimicrobials represented the largest category for medication mismatch between modalities (17 of 70 [24.3%]). Nearly one-third of patients (17 [32.1%]) had at least 1 medication mismatch in their record.

Conclusions and relevance: Almost 1 in 4 medications were mismatched between the progress note and formal medication list in the EHR. These findings suggest that EHR data should be checked for internal consistency before use in research.