A NEW FRONTIER- USING PHARMACY CLAIMS WITHIN THE EHR TO CONDUCT MEDICATION RECONCILIATION IN PRIMARY CARE PRACTICE
Author(s)
Comer D1, Couto J1, Aguiar R2, Wu P2, Elliott D2
1Jefferson School of Population Health, Philadelphia, PA, USA, 2Christiana Care Health System, Newark, DE, USA
OBJECTIVES: Medication reconciliation is a necessary process for the delivery of optimal patient care, yet can be difficult to do in the primary care setting due to limited time and resources. Dramatic improvements in health information technology may facilitate accurate and real-time medication reconciliation. The purpose of this study is to determine the potential impact of linked pharmacy claims within to the primary care electronic health record (EHR) to inform medication reconciliation in primary care practice. METHODS: We conducted a retrospective cohort study in patients that were prescribed a new antihypertensive between January 2011 and September 2012. We compared patients’ active medications as recorded in a primary care practice EHR with those that were listed in pharmacy claims data available through the EHR. Only medications that were active in the 120 days prior to the new antihypertensive were considered. Medications that appeared in one data source but not the other were categorized as discrepancies. The primary outcome was the presence of at least one discrepancy. Predictors of discrepancy risk were calculated through logistic regression. RESULTS: A total of 609 patients qualified for study. Amongst all patients, 2947 medications were reconciled, with 1401 as discrepancies. The majority of patients (468, 76.9%) had at least one discrepancy. Predictors of the risk of having discrepancies included total medication count (OR: 0.17, p=<0.0001), at least one non-cardiovascular related comorbidity (OR: 0.84 p=0.0001) and a hospitalization in the previous year (OR: 0.48, p=0.007). CONCLUSIONS: A high rate of medication discrepancies was found amongst patients, along with significant predictors of occurrence. The use of linked pharmacy claims was able to show a more complete picture of a patient’s medication use patterns. Such automated solutions could be used to screen available data sources to uncover discrepancies and identify patients who may benefit from tailored clinical interventions.
Conference/Value in Health Info
2014-05, ISPOR 2014, Palais des Congres de Montreal
Value in Health, Vol. 17, No. 3 (May 2014)
Code
PCV122
Topic
Real World Data & Information Systems
Topic Subcategory
Health & Insurance Records Systems
Disease
Cardiovascular Disorders