Patient, Physician, and Payment Predictors of Statin Adherence

Abstract

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: 14,257 patients insured by Horizon Blue Cross Blue Shield of New Jersey (BCBSNJ) 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 (PDC). 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 (ED) 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-ofpocket costs, our overall ability to explain adherence remains poor. Administrative data likely do not capture many complex mechanisms underlying adherence.

Multilevel factors are associated with immunosuppressant nonadherence in heart transplant recipients: The international BRIGHT study

“…This multicontinental study is the first in transplantation and one of the first in chronically ill patient populations6, 15, 33 to simultaneously investigate patient‐, healthcare provider/family‐, healthcare organization‐ and healthcare system‐related factors’ associations with medication nonadherence. Its main strengths are its large geographical coverage (11 countries) as well as its use of theory to select potential multilevel correlates 6, 19, 20, 38…”

“…However, the focus has been primarily on patient‐level factors 1, 8, 13, 14. In fact, most patient‐level factors are only weakly associated with medication nonadherence, suggesting that other‐level variables also play roles 6, 11, 15. In addition, few studies exploit theoretical models that guide selection of factors for investigation 16, 17, 18…”

“…6, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32 Reflecting this perspective, a multilevel approach to medication nonadherence is novel,15, 33 as multilevel medication nonadherence factors have received little attention in transplantation 6, 11, 13, 14, 34. Should this new perspective reveal independent multilevel immunosuppressant nonadherence correlates, addressing such correlates would demand interventional approaches targeting not only patients but healthcare workers/family, organizations, and policymakers 6, 21, 24…”

The Challenges of Oral Agents as Antineoplastic Treatments

“…However, the relationship between these factors and adherence have been inconsistent; and most studies have found weak associations (< 0.15 r) with nonadherence. 25,26 No simple explanation for nonadherence exists. Nonetheless, the following are the patient, disease, and system factors found in the literature associated with nonadherence (See Table 1).…”

“…26,88 Lack of adherence to oral chemotherapy can contribute to variability in a drug's antineoplastic agent effect if a clinician incorrectly attributes the patient's worsening condition to an absence of drug activity and may lead to unnecessary testing and hospitalization. 31 …”