Predictors of adherence to statins for primary prevention
ABSTRACT Statins are potent drugs for reducing cholesterol and cardiovascular disease; however, their effectiveness is significantly compromised by poor adherence. This prospective study was designed to identify potentially modifiable patient factors including medication, disease, and diet beliefs related to statin adherence.
Veterans (n = 71) given their first prescription of a statin for primary prevention were interviewed at baseline, 3 months, and 6 months regarding medication, disease, and diet beliefs along with self-reported statin adherence.
At 6-month follow-up, 55% of the cohort was non-adherent with 10% reporting never having started their statin, 50% reporting misconceptions about the duration of treatment and a median use of <2 months among those who discontinued their statin. Multivariate predictors of non-adherence were expected short treatment duration (OR = 3.6, 1.4-9.4), low perceived risk of myocardial infarction (OR = 3.1, 1.1-8.7), concern about potential harm from statins (OR = 2.5, 1.0-6.3), being Hispanic (OR = 3.9, 1.0-15.2), and younger age (OR = 4.2, 1.1-15.8).
Poor adherence to statins was common in this primary prevention population with frequent early discontinuation despite access to low-cost medicines. Patient factors regarding the perception of risk, toxic effects of medication, expected treatment duration, as well as socio-demographic factors, were significant predictors of poor adherence and warrant further exploration.
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ABSTRACT: Pharmacologic treatment for secondary prevention of coronary heart disease (CHD) is critical to prevent adverse clinical outcomes. In a randomized controlled trial, we compared antiplatelet and statin adherence among patients with CHD who received: (1) text messages (TM) for medication reminders and education, (2) educational TM only, or (3) No TM. A mobile health intervention delivered customized TM for 30 days. We assessed and analyzed medication adherence with electronic monitoring devices [Medication Event Monitoring System (MEMS)] by one-way ANOVA and Welch tests, two-way TM response rates by t-tests, and self-reported adherence (Morisky Medication Adherence Scale) by Repeated Measures ANOVA. Among 90 patients (76% male, mean age 59.2 years), MEMS revealed patients who received TM for antiplatelets had a higher percentage of correct doses taken (p=0.02), percentage number of doses taken (p=0.01), and percentage of prescribed doses taken on schedule (p=0.01). TM response rates were higher for antiplatelets than statins (p=0.005). Self-reported adherence revealed no significant differences among groups. TM increased adherence to antiplatelet therapy demonstrated by MEMS and TM responses. Feasibility and high satisfaction were established. Mobile health interventions show promise in promoting medication adherence.Patient Education and Counseling 11/2013; DOI:10.1016/j.pec.2013.10.027 · 2.60 Impact Factor
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ABSTRACT: Coronary disease is the leading cause of death worldwide and increased levels of cholesterol, in particular low density lipoprotein cholesterol (LDL-C), have been shown to be risk factors in predicting adverse cardiac events. Statin therapy has been shown to be beneficial in secondary prevention by reducing coronary events and mortality in patients with known disease(1, 2). But, given the profound morbidity and mortality associated with CAD, methods of primary prevention are critically important and several large trials have shown the benefit of statin therapy in this regard. The West Scotland Coronary Prevention Study (WOSCOPS) showed lipid lowering therapy (LLT) was associated with a 32 percent reduction in rate of coronary events and a 22 percent reduction in total mortality (3). The Air Force/Texas Coronary Atherosclerosis Prevention Study (AFCAPS/TexCAPS) also showed benefit of therapy in patients with no history of coronary disease, and reported a similar 37 percent reduction in composite endpoint which included fatal or nonfatal myocardial infarction, sudden death or unstable angina (4). However, despite the overwhelming benefit, good safety profile and low cost of statin therapy, the rates of non-adherence are high even in patients with known disease (5). Not surprisingly, this rate is even higher in patients targeted for primary prevention, and on average is reported to be near 50 percent (5-7). A large retrospective study using a health maintenance organization database showed the risk of discontinuation of therapy in the clinic setting is highest in the first 6 months, estimating that about 20 percent of patients stop during this time period. This study also showed that significant predictors of discontinuation were age less than 50 years, female sex and previous LLT (8). Another prospective trial, from a large academic medical center in New York City, again found similarly poor adherence. In this study, veterans self- reported discontinuation at a rate of 55 percent at 6 months and after analysis of questionnaires regarding reasons for stopping the medication, the following were found to be predictive: expected short treatment duration, low perceived risk of myocardial infarction, concern about potential harm from statins, being Hispanic and younger age (9).
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ABSTRACT: Medication non-adherence, the extent to which a person's behavior does not coincide with medical or health advice, is a serious public health issue. Objectives: 1) Develop a new typology of medication non-adherence, 2) Develop models to predict different types of non-adherence based on Andersen Behavioral Model (ABM) and Leventhal's Common Sense Model (CSM), and 3) Test the models across two different medications used in treating disease conditions with varying symptomatology. Methodology: A new typology of medication non-adherence was developed through literature review of the frequently reported reasons for non-adherence based on the possibility of a cognitive process intervention directed towards patients and the mutability of interventions. The typology was analyzed qualitatively and quantitatively. A new self-reported scale to measure non-adherence was developed from the frequently reported reasons and compared to the Morisky scale. The conceptual models developed using ABM and CSM were tested using regression techniques to identify significant predictors of non-adherence. Results: Qualitative analysis supported the typology from the literature review, yet the quantitative exploratory factor analysis did not support it. Instead, four types of non-adherence each for cholesterol lowering (non-adherence due to managing issues, multiple medication issues, belief issues with medications, forgetfulness due to busy schedule) and asthma maintenance medications (non-adherence due to managing and availability issues, beliefs and convenience issues, cost issues, forgetfulness due to busy schedule) were identified. Predisposing factors such as concern beliefs in medications, enabling factors such as self efficacy, and need factors such as self health and illness perceptions, and severity of disease were significant predictors of medication non-adherence. The Reasons scale had moderate levels of agreement with the Morisky scale based on kappa coefficients. Conclusion: No one typology of medication non-adherence fit cholesterol lowering and asthma maintenance medications, and the typology was driven by type of disease condition and reasons for non-adherence. The Reasons scale measured and categorized non-adherence better than the Morisky scale. Adding CSM to ABM facilitated in identifying predictors of medication non-adherence.