title: Usefulness of pharmacy claims for medication reconciliation in primary care.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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.
authors.forename: Dominique
authors.initials: D
authors.lastname: Comer
authors.forename: Joseph
authors.initials: J
authors.lastname: Couto
authors.forename: Ruth
authors.initials: R
authors.lastname: Aguiar
authors.forename: Pan
authors.initials: P
authors.lastname: Wu
authors.affiliation: Christiana Care Health System, 4755 Ogletown-Stanton Rd, Newark, DE 19718. E-mail: delliott@christianacare.org.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Elliott
mesh_terms: D000367:Age Factors; D000959:Antihypertensive Agents / Q000008:administration & dosage; D003625:Data Collection / Q000379:methods*; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005260:Female; D006760:Hospitalization; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data*; D008297:Male; D059065:Medication Reconciliation / Q000379:methods*; D010593:Pharmaceutical Services / Q000706:statistics & numerical data*; D011320:Primary Health Care / Q000706:statistics & numerical data; D044469:Racial Groups; D012189:Retrospective Studies; D012737:Sex Factors
chemical_list: D000959:Antihypertensive Agents