An Analysis of Two Sources of Cardiology Patient Data to Measure Medication Agreement

Research output: Contribution to journalArticlepeer-review

Abstract

Errors and incompleteness in electronic health record (EHR) medication lists can result in medical errors. To reduce errors in these medication lists, clinicians use patient self-reported data to reconcile EHR data. We assessed the agreement between patient self-reported medications and medications recorded in the EHR for six medication classes related to cardiovascular care and used logistic regression models to determine which patient-related factors were associated with the disagreement between these two information sources. From our 297 patients, we found self-reported medications had an overall above-average agreement with the EHR (? = .727). We observed the highest agreement level for statins (? = .831) and the lowest for other antihypertensives (? = .465). Agreement was less likely for Hispanic and male patients. We also performed an in-depth error analysis of different types of disagreement beyond medication names, which revealed that the most frequent type of disagreement was mismatched dosages.

Original languageEnglish (US)
Pages (from-to)267-275
Number of pages9
JournalAMIA ... Annual Symposium proceedings. AMIA Symposium
Volume2021
StatePublished - 2021

ASJC Scopus subject areas

  • Medicine(all)

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