BACKGROUND: Effective therapies for the secondary prevention of coronary heart disease-related events are significantly underused, and attempts to improve adherence have often yielded disappointing results. Elimination of patient out-of-pocket costs may be an effective strategy to enhance medication use. We sought to estimate the incremental cost-effectiveness of providing full coverage for aspirin, beta-blockers, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and statins (combination pharmacotherapy) to individuals enrolled in the Medicare drug benefit program after acute myocardial infarction. METHODS AND RESULTS: We created a Markov cost-effectiveness model to estimate the incremental cost-effectiveness of providing Medicare beneficiaries with full coverage for combination pharmacotherapy compared with current coverage under the Medicare Part D program. Our analysis was conducted from the societal perspective and considered a lifetime time horizon. In a sensitivity analysis, we repeated our analysis from the perspective of Medicare. In the model, post-myocardial infarction Medicare beneficiaries who received usual prescription drug coverage under the Part D program lived an average of 8.21 quality-adjusted life-years after their initial event, incurring coronary heart disease-related medical costs of $114,000. Those who received prescription drug coverage without deductibles or copayments lived an average of 8.56 quality-adjusted life-years and incurred $111,600 in coronary heart disease-related costs. Compared with current prescription drug coverage, full coverage for post-myocardial infarction secondary prevention therapies would result in greater functional life expectancy (0.35 quality-adjusted life-year) and less resource use ($2500). From the perspective of Medicare, full drug coverage was highly cost-effective ($7182/quality-adjusted life-year) but not cost saving. CONCLUSIONS: Our analysis suggests that providing full coverage for combination therapy to post-myocardial infarction Medicare beneficiaries would save both lives and money from the societal perspective.

OBJECTIVES: To propose standardized methods for measuring concurrent adherence to multiple related medications and to apply these definitions to a cohort of patients with diabetes mellitus. STUDY DESIGN: Retrospective cohort study of 7567 subjects with diabetes prescribed 2 or more classes of oral hypoglycemic agents in 2005. METHODS: For each medication class, adherence for each patient was estimated using prescription-based and interval-based measures of proportion of days covered (PDC) from cohort entry until December 31, 2006. Concurrent adherence was calculated by applying these 2 measures in the following 3 ways: (1) the mean of each patient's average PDC, (2) the proportion of days during which patients had at least 1 of their medications available to them, and (3) the proportion of patients with a PDC of at least 80% for all medication classes. Because patients taking multiple related medications have distinct patterns of use, the analysis was repeated after classifying patients into mutually exclusive groups. RESULTS: Concurrent medication adherence ranged from 35% to 95% depending on the definition applied. Interval-based measures provide lower estimates than prescription-based techniques. Definitions that require the use of at least 1 drug class categorize virtually all patients as adherent. Requiring patients to have a PDC of at least 80% for each of their drugs results in only 30% to 40% of patients being defined as adherent. The variability in adherence is greatest for patients whose treatment regimen changed the most during follow-up. CONCLUSIONS: The variability in adherence estimates derived from different definitions may substantially impact qualitative conclusions about concurrent adherence to related medications. Because the measures we propose have different underlying assumptions, the choice of technique should depend on why adherence is being evaluated.

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.

BACKGROUND:: Although many patient, physician, and payment predictors of adherence have been described, knowledge of their relative strength and overall ability to explain adherence is limited. OBJECTIVES:: To measure the contributions of patient, physician, and payment predictors in explaining adherence to statins. RESEARCH DESIGN:: Retrospective cohort study using administrative data. SUBJECTS:: A total of 14,257 patients insured by Horizon Blue Cross Blue Shield of New Jersey who were newly prescribed a statin cholesterol-lowering medication. MEASURES:: Adherence to statin medication was measured during the year after the initial prescription, based on proportion of days covered. The impact of patient, physician, and payment predictors of adherence were evaluated using multivariate logistic regression. The explanatory power of these models was evaluated with C statistics, a measure of the goodness of fit. RESULTS:: Overall, 36.4% of patients were fully adherent. Older patient age, male gender, lower neighborhood percent black composition, higher median income, and fewer number of emergency department visits were significant patient predictors of adherence. Having a statin prescribed by a cardiologist, a patient's primary care physician, or a US medical graduate were significant physician predictors of adherence. Lower copayments also predicted adherence. All of our models had low explanatory power. Multivariate models including patient covariates only had greater explanatory power (C = 0.613) than models with physician variables only (C = 0.566) or copayments only (C = 0.543). A fully specified model had only slightly more explanatory power (C = 0.633) than the model with patient characteristics alone. CONCLUSIONS:: Despite relatively comprehensive claims data on patients, physicians, and out-of-pocket costs, our overall ability to explain adherence remains poor. Administrative data likely do not capture many complex mechanisms underlying adherence.

BACKGROUND: Medications for the prevention and treatment of cardiovascular disease save lives but adherence is often inadequate. The optimal role for physicians in improving adherence remains unclear. OBJECTIVE: Using existing evidence, we set the goal of evaluating the physician's role in improving medication adherence. DESIGN: We conducted systematic searches of English-language peer-reviewed publications in MEDLINE and EMBASE from 1966 through 12/31/2008. SUBJECTS AND INTERVENTIONS: We selected randomized controlled trials of interventions to improve adherence to medications used for preventing or treating cardiovascular disease or diabetes. MAIN MEASURES: Articles were classified as either (1) physician "active"-a physician participated in designing or implementing the intervention; (2) physician "passive"-physicians treating intervention group patients received patient adherence information while physicians treating controls did not; or (3) physicians noninvolved. We also identified studies in which healthcare professionals helped deliver the intervention. We did a meta-analysis of the studies involving healthcare professionals to determine aggregate Cohen's D effect sizes (ES). KEY RESULTS: We identified 6,550 articles; 168 were reviewed in full, 82 met inclusion criteria. The majority of all studies (88.9%) showed improved adherence. Physician noninvolved studies were more likely (35.0% of studies) to show a medium or large effect on adherence compared to physician-involved studies (31.3%). Among interventions requiring a healthcare professional, physician-noninvolved interventions were more effective (ES 0.47; 95% CI 0.38-0.56) than physician-involved interventions (ES 0.25; 95% CI 0.21-0.29; p < 0.001). Among physician-involved interventions, physician-passive interventions were marginally more effective (ES 0.29; 95% CI 0.22-0.36) than physician-active interventions (ES 0.23; 95% CI 0.17-0.28; p = 0.2). CONCLUSIONS: Adherence interventions utilizing non-physician healthcare professionals are effective in improving cardiovascular medication adherence, but further study is needed to identify the optimal role for physicians.

Low levels of statin adherence have been documented in patients with coronary artery disease (CAD), but whether coronary revascularization is associated with improved adherence rates has yet to be evaluated. We identified all Medicare beneficiaries enrolled in 2 statewide pharmacy assistance programs who were >/=65 years old, who had been hospitalized for CAD from 1995 through 2004, and who had been prescribed statin therapy within 90 days of discharge (n = 13,130). Statin adherence was measured based on the proportion of days covered with statin therapy after hospital discharge, and full adherence was defined as proportion of days covered >/=80%. Statin adherence was compared in patients with CAD treated with medical therapy (n = 3,714), percutaneous coronary intervention (n = 6,309), or coronary artery bypass graft surgery (n = 3,107). Statin adherence significantly increased over the period of the study from 70.5% to 75.4% (p <0.0001). After hospitalization for CAD, patients treated with percutaneous coronary intervention and coronary artery bypass graft surgery had full adherence rates of 70.6% and 70.2%, respectively. Full adherence rates were significantly lower for patients treated with coronary revascularization compared to patients treated with medical therapy (79.4%, p <0.0001). Independent predictors of higher statin adherence included treatment with medical therapy, later year of hospital admission, white race, previous statin use, and use of other cardiac medications after CAD hospitalization (p <0.01 for all comparisons). In conclusion, in patients receiving invasive coronary treatment, statin adherence remains suboptimal, despite strong evidence supporting their use. Given the health and economic consequences of nonadherence, these findings highlight the need for developing cost-effective strategies to improve medication adherence after coronary revascularization.