OBJECTIVES: Methods for efficient medication reconciliation are increasingly important in primary care. Aggregated pharmacy data within the native electronic health record (EHR) may create a new opportunity for efficient and systematic medication reconciliation in practice. Our objective was to identify the prevalence and predictors of medication discrepancies between pharmacy claims data and the medication list in a primary care EHR. STUDY DESIGN: Retrospective cohort study. METHODS: We conducted a retrospective cohort study of patients prescribed a new antihypertensive in a large primary care practice network between January 2011 and September 2012. We compared patients' active medications recorded in the practice EHR with those listed in pharmacy claims data available through the EHR. The primary outcome was the presence of a medication discrepancy. RESULTS: Of 609 patients, 468 (76.9%) had at least 1 medication discrepancy. Significant predictors of discrepancies included the total medication count (odds ratio [OR], 2.18; 95% CI, 1.85-2.57) and having a recent emergency department visit (OR, 2.58; 95% CI, 1.03-6.45). The identified discrepancies included 171 patients (28.1%) with 229 controlled substance discrepancies. CONCLUSIONS: Our study revealed a high rate of discrepancies between pharmacy claims data and the provider medication list. Aggregated pharmacy claims data available through the EHR may be an important tool to facilitate medication reconciliation in primary care.
OBJECTIVES: Methods for efficient medication reconciliation are increasingly important in primary care. Aggregated pharmacy data within the native electronic health record (EHR) may create a new opportunity for efficient and systematic medication reconciliation in practice. Our objective was to identify the prevalence and predictors of medication discrepancies between pharmacy claims data and the medication list in a primary care EHR. STUDY DESIGN: Retrospective cohort study. METHODS: We conducted a retrospective cohort study of patients prescribed a new antihypertensive in a large primary care practice network between January 2011 and September 2012. We compared patients' active medications recorded in the practice EHR with those listed in pharmacy claims data available through the EHR. The primary outcome was the presence of a medication discrepancy. RESULTS: Of 609 patients, 468 (76.9%) had at least 1 medication discrepancy. Significant predictors of discrepancies included the total medication count (odds ratio [OR], 2.18; 95% CI, 1.85-2.57) and having a recent emergency department visit (OR, 2.58; 95% CI, 1.03-6.45). The identified discrepancies included 171 patients (28.1%) with 229 controlled substance discrepancies. CONCLUSIONS: Our study revealed a high rate of discrepancies between pharmacy claims data and the provider medication list. Aggregated pharmacy claims data available through the EHR may be an important tool to facilitate medication reconciliation in primary care.