BACKGROUND: : In January 2008, the Food and Drug Administration (FDA) communicated concerns about the efficacy of ezetimibe, but did not provide clear clinical guidance, and substantial media attention ensued. We investigated the proportion of patients who discontinued therapy and switched to a clinically appropriate alternative after the FDA communication. METHODS: : Using claims data from a national pharmacy benefits manager, we created a rolling cohort of new users of ezetimibe between January 2006 and August 2008 and created a supply diary for each patient in the year after cohort entry. A patient was identified as nonpersistent if a gap of 90 days was seen in the diary. Using segmented linear regression, we compared rates of nonpersistence before and after the FDA communication and assessed patient-level characteristics associated with discontinuation. Among nonpersistent patients, we determined whether a patient made a clinically appropriate switch in the subsequent 90 days by adding a new cholesterol-lowering medication or by increasing the dose of an existing one. We used a weighted t test to compare the rates of appropriate switching before and after the communication. RESULTS: : Among 867,027 new ezetimibe users, 407,006 (46.9%) were nonpersistent in the first year. After the FDA communication, the monthly level of ezetimibe nonpersistence increased by 5.7 percentage points (P<0.0001). Younger patients, those who lived in low-income zip codes, and female patients were less likely to discontinue therapy (P<0.0001 for all). Among nonpersistent patients, rates of clinically appropriate switching increased from 10.8% before to 16.5% after the FDA warning (P=0.004). CONCLUSIONS: : A substantial increase in ezetimibe nonpersistence rates was seen after an FDA communication regarding its efficacy and following associated media attention, and a small proportion of patients made a clinically appropriate switch after discontinuation. Further consideration is needed to deliver messages that promote appropriate use of chronic therapy rather than simply reduce use.

BACKGROUND: The AFFIRM (Atrial Fibrillation Follow-Up Investigation of Rhythm Management) trial demonstrated that rate control and rhythm control strategies result in similar survival and quality of life for patients with atrial fibrillation (AF). Because of superior safety and lower cost, rate control is now the recommended strategy for the management of most elderly, high-risk AF patients. OBJECTIVE: To determine the extent to which the AFFIRM trial results have been adopted into actual practice. METHODS: We conducted a time-series analysis of 3 population-based cohorts of patients with AF who were 66 years of age or older in Pennsylvania and Ontario. We stratified patients in Ontario by socioeconomic status (SES) and examined changes in quarterly prescription rates for rate control and rhythm controlling medications as well as cardioversion procedures before and after publication of the AFFIRM trial. RESULTS: The publication of the AFFIRM trial resulted in statistically significant reductions in the use of rhythm controlling medications in all 3 cohorts (p < 0.01). The magnitude of these changes in the non-low SES Canadian cohort was approximately 1% per quarter and was greater than the magnitude observed in the other cohorts (p < 0.001). The use of cardioversion procedures also decreased in all study regions (p < 0.01). In contrast, AFFIRM publication was also associated with a small increase in the use of rate controlling medications in Canada (p < 0.01) but not in the US (p = 0.23). CONCLUSIONS: Publication of the AFFIRM trial resulted in small but statistically significant changes in the care of patients with AF.

BACKGROUND: Medication errors represent a major public health concern, and inadequate prescription drug labels have been identified as a root cause of errors. A new prescription medication labeling system was implemented by Target pharmacies in May 2005 and aimed to improve health outcomes. OBJECTIVES: To evaluate whether the new Target label influenced patient health services utilization. SUBJECTS: Derived from 2 large health plans. RESEARCH DESIGN AND MEASURES: Using administrative claims, we identified patients with 1 of 9 chronic diseases who filled prescriptions at Target pharmacies and a matched sample who filled prescriptions at other community pharmacies. We stratified our cohort into new and prevalent medication users and evaluated the impact of the Target label on outpatient, emergency department and inpatient health services use. We used linear regression and segmented linear regression to evaluate the new-user and prevalent-user analyses, respectively. RESULTS: Our sample included 23,745 Target pharmacy users and 162,369 matched non-Target pharmacy users. In the new-user analysis, we found no significant change in rates of both outpatient (event rate ratio: 0.53; 95% CI: 0.15-1.86) and inpatient and emergency department (Event rate ratio: 0.88; 95% CI: 0.62-1.24) health services utilization in Target users after implementation when compared with non-Target users. Similarly, in the prevalent user analysis, we found no change in the level or slope of outpatient or emergency/inpatient services in Target users after implementation of the new label when compared with non-Target users. CONCLUSIONS: We found no statistically significant change in health services use attributable to the implementation of the new prescription drug label at Target pharmacies. These findings highlight the challenge of influencing health outcomes with interventions to improve health literacy.

BACKGROUND: Prescription medication labels contain valuable health information, and better labels may enhance patient adherence to chronic medications. A new prescription medication labeling system was implemented by Target pharmacies in May 2005 and aimed to improve readability and understanding. OBJECTIVE: We evaluated whether the new Target label influenced patient medication adherence. DESIGN AND PATIENTS: Using claims from two large health plans, we identified patients with one of nine chronic diseases who filled prescriptions at Target pharmacies and a matched sample who filled prescriptions at other community pharmacies. MEASUREMENTS: We stratified our cohort into new and prevalent medication users and evaluated the impact of the Target label on medication adherence. We used linear regression and segmented linear regression to evaluate the new-user and prevalent-user analyses, respectively. RESULTS: Our sample included 23,745 Target users and 162,368 matched non-Target pharmacy users. We found no significant change in adherence between new users of medications at Target or other community pharmacies (p = 0.644) after implementing the new label. In prevalent users, we found a 0.0069 percent reduction in level of adherence (95% CI -0.0138-0.0; p < 0.001) and a 0.0007 percent increase in the slope in Target users (the monthly rate of change of adherence) after implementation of the new label (95% CI 0.0001-0.0013; p = 0.001). CONCLUSIONS: We found no changes in adherence of chronic medication in new users, and small and likely clinically unimportant changes in prevalent users after implementation of the new label. While adherence may not be improved with better labeling, evaluation of the effect of labeling on safety and adverse effects is needed.