Study Objective-To compare drug adherence rates among patients with gout, hypercholesterolemia, hypertension, hypothyroidism, osteoporosis, seizure disorders, and type 2 diabetes mellitus by using a standardized approach. Design-Longitudinal study. Data Source-Health care claims data from 2001-2004.Patients-A total of 706,032 adults aged 18 years or older with at least one of the seven medical conditions and with incident use of drug therapy for that condition.Measurements and Main Results-Drug adherence was measured as the sum of the days' supply of drug therapy over the first year observed. Covariates were age, sex, geographic residence, type of health plan, and a comorbidity score calculated by using the Hierarchical Condition Categories risk adjuster. Bivariate statistics and stratification analyses were used to assess unadjusted means and frequency distributions. Sample sizes ranged from 4984 subjects for seizure disorders to 457,395 for hypertension. During the first year of drug therapy, 72.3% of individuals with hypertension achieved adherence rates of 80% or better compared with 68.4%, 65.4%, 60.8%, 54.6%, 51.2%, or 36.8% for those with hypothyroidism, type 2 diabetes, seizure disorders, hypercholesterolemia, osteoporosis, or gout, respectively. Age younger than 60 years was associated with lower adherence across all diseases except seizure disorders. Comorbidity burden and adherence varied by disease. As comorbidity increased, adherence among subjects with osteoporosis decreased, whereas adherence among those with hypertension, hypercholesterolemia, or gout increased. Addon drug therapies and previous experience with taking drugs for the condition increased adherence among subjects with hypertension, type 2 diabetes, hypothyroidism, or seizure disorders but not the other conditions. Our assessment of the published empiric evidence revealed few comparisons of drug nonadherence rates across medical conditions. Nearly all adherence studies have focused on a single disease, and comparisons across studies are difficult given the wide variety of methods used to calculate drug nonadherence rates. 4 The objective of our study was to apply a uniform method for comparing adherence rates across a range of chronic medical conditions that are commonly treated with long-term drug therapy. Conclusion-This Methods Study Population and Data SourcesThe study sample included approximately 1.3 million individuals aged 18 years or older who had a diagnosis of gout, hypercholesterolemia, hypertension, hypothyroidism, osteoporosis, seizure disorders, or type 2 diabetes during the study period of [2001][2002][2003][2004]. These conditions were selected because they are chronic, because they commonly occur in adults, and because regular and persistent drug therapy is recommended as treatment. In addition, the subjects must have started new drug therapy for their condition between January 1, 2002, and December 31, 2003. Table 1 lists the diagnostic codes and drug therapies for these disorders.Our analysis focused on rec...

OBJECTIVE: Up to 32% of older patients take less medication than prescribed to avoid costs, yet a comprehensive assessment of risk factors for cost-related nonadherence (CRN) is not available. This review examined the empirical literature to identify patient-, medication-, and provider-level factors that influence the relationship between medication adherence and medication costs. DESIGN:We conducted searches of four databases (MEDLINE, CINAHL, Sciences Citations Index Expanded, and EconLit) from 2001 to 2006 for English-language original studies. Articles were selected if the study included an explicit measure of CRN and reported results on covarying characteristics. MAIN RESULTS:We found 19 studies with empirical support for concluding that certain patients may be susceptible to CRN: research has established consistent links between medication nonadherence due to costs and financial burden, but also to symptoms of depression and heavy disease burden. Only a handful of studies with limited statistical methods provided evidence on whether patients understand the health risks of CRN or to what extent clinicians influence patients to keep taking medications when faced with cost pressures. No relationship emerged between CRN and polypharmacy.CONCLUSION: Efforts to reduce cost-related medication nonadherence would benefit from greater study of factors besides the presence of prescription drug coverage. Older patients with chronic diseases and mood disorders are at-risk for CRN even if enrolled in Medicare's new drug benefit.

No abstract

Comparative effectiveness research includes cohort studies and registries of interventions. When investigators design such studies, how important is it to follow patients from the day they initiated treatment with the study interventions? Our article considers this question and related issues to start a dialogue on the value of the incident user design in comparative effectiveness research. By incident user design, we mean a study that sets the cohort's inception date according to patients' new use of an intervention. In contrast, most epidemiologic studies enroll patients who were currently or recently using an intervention when follow-up began. We take the incident user design as a reasonable default strategy because it reduces biases that can impact non-randomized studies, especially when investigators use healthcare databases. We review case studies where investigators have explored the consequences of designing a cohort study by restricting to incident users, but most of the discussion has been informed by expert opinion, not by systematic evidence.

This study detected the highest level of antipsychotic use in NHs in over a decade. Most atypicals were prescribed outside the prescribing guidelines and for doses and indications without strong clinical evidence. Failure to detect positive relationships between behavioral symptoms and antipsychotic therapy raises questions about the appropriateness of prescribing.