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

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.