Usefulness of pharmacy claims for 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.

Using aggregated pharmacy claims to identify primary nonadherence.

OBJECTIVES: Aggregate pharmacy claims available within an electronic health record (EHR) provide an opportunity to understand primary nonadherence in real time. The objective of this study was to use pharmacy claims data available within the EHR to identify the prevalence and predictors of primary nonadherence to antihypertensive drug therapy in a multi-payer primary care network. STUDY DESIGN: We conducted a retrospective cohort study of patients prescribed a new antihypertensive medication in a large primary care practice network between January 2011 and September 2012. METHODS: We matched prescriptions for the new antihypertensive to pharmacy claims listed in the EHR. The primary outcome was the presence of a fill for the new medication within 30 days of the prescription. RESULTS: Of 791 patients in our study cohort, two-thirds (522; 66%) filled their prescription within 30 days. The majority (409; 78.4%) of that group filled the prescription on the day it was issued. Lower diastolic blood pressure and Medicare coverage increased the probability of nonadherence. CONCLUSIONS: Medication fill data within the provider EHR can identify primary nonadherence in clinical practice. As adoption of this technology increases, it provides an opportunity to identify nonadherence, allowing for the effective design of interventions to improve adherence to therapy.

Effect of hospitalist workload on the quality and efficiency of care.

IMPORTANCE: Hospitalist physicians face increasing pressure to maximize productivity, which may undermine the efficiency and quality of care. OBJECTIVE: To determine the association between hospitalist workload and the efficiency and quality of inpatient care. DESIGN, SETTING, AND PARTICIPANTS: We conducted a retrospective cohort study of 20,241 admissions of inpatients cared for by a private hospitalist group at a large academic community hospital system between February 1, 2008, and January 31, 2011. EXPOSURES: Daily hospitalist workload as measured by relative value units and patient encounters from the hospitalist billing records. MAIN OUTCOMES AND MEASURES: The main outcomes were length of stay (LOS), cost, rapid response team activation, in-hospital mortality, patient satisfaction, and 30-day readmission rates. Key covariates included hospital occupancy and patient-level characteristics. RESULTS: The LOS increased as workload increased, particularly at lower hospital occupancy. For hospital occupancies less than 75%, LOS increased from 5.5 to 7.5 days as workload increased. For occupancies of 75% to 85%, LOS increased exponentially above a daily relative value unit of approximately 25 and a census value of approximately 15. At high occupancy (>85%), LOS was J-shaped, with significant increases at higher ranges of workload. After controlling for LOS, cost increased by $111 for each 1-unit increase in relative value unit and $205 for each 1-unit increase in census across the range of values. Changes in workload were not associated with the remaining outcomes. CONCLUSIONS AND RELEVANCE: Increasing hospitalist workload is associated with clinically meaningful increases in LOS and cost. Although our findings should be validated in different clinical settings, our results suggest the need for methods to mitigate the potential negative effects of increased hospitalist workload on the efficiency and cost of care.