Elsevier

Journal of Cardiac Failure

Volume 14, Issue 7, September 2008, Pages 603-614
Journal of Cardiac Failure

Clinical Investigation
Predictors of Medication Adherence Using a Multidimensional Adherence Model in Patients With Heart Failure

https://doi.org/10.1016/j.cardfail.2008.02.011Get rights and content

Abstract

Background

Medication adherence in heart failure (HF) is a crucial but poorly understood phenomenon. The purpose of this study was to explore factors contributing to medication adherence in patients with HF by using the World Health Organization's multidimensional adherence model.

Methods and Results

Patients (N = 134) with HF (70% were male, aged 61 ± 12 years, 61% with New York Heart Association III/IV) were studied to determine the predictors of medication adherence derived from the multidimensional adherence model. Medication adherence was measured objectively using the medication event monitoring system for 3 months. Three indicators of adherence were assessed by the medication event monitoring system: 1) dose-count, the percentage of prescribed doses taken; 2) dose-days, the percentage of days the correct number of doses were taken; and 3) dose-time, the percentage of doses that were taken on schedule. Barriers to medication adherence, ethnicity, and perceived social support predicted dose-count (P < .001). New York Heart Association functional class, barriers to medication adherence, financial status, and perceived social support predicted dose-day (P < .001). Barriers to medication adherence and financial status predicted dose-time (P = .005).

Conclusion

A number of modifiable factors predicted medication adherence in patients with HF, providing specific targets for intervention.

Section snippets

Study Design

This study was conducted in the context of a prospective study in which we determined the role of medication adherence in determining the outcomes in patients with HF.43 In the current analysis, we determined whether factors making up the 5 dimensions of the MAM predicted medication adherence. At baseline, patients completed questionnaires and started medication adherence monitoring. Medication adherence was monitored for 3 months, and outcomes were tracked for 6 months.

Sample and Settings

Patients were enrolled

Sample Characteristics

A total of 134 patients with HF were included in this study. The mean age of patients in the sample was 61 ± 11 years. The most common HF cause was ischemic heart disease. The sample consisted largely of patients with advanced HF as reflected by their NYHA functional class. The average left ventricular ejection fraction reflected the enrollment of patients with and without systolic dysfunction. Only 9% of patients had no comorbidities, whereas the remainder had 1 or more, with 44% of patients

Discussion

This is the first study in patients with HF in which the factors hypothesized to contribute to adherence hypothesized in the MAM, a multivariate medication adherence model, were tested.40 The findings of this study supported some, but not all, of the relationships hypothesized in the MAM. In multivariate analyses, worse NYHA functional class, more barriers to medication adherence, minority ethnicity, lower financial status, and lack of perceived social support were related to objectively

Limitations

Although there was sufficient power to demonstrate significant differences, a larger sample size and more heterogeneous sample may be needed to more thoroughly investigate predictors of adherence and to generalize the result to a larger population.

Conclusions

Although patient adherence is often difficult for a variety of patient, provider, and health care system-related factors, it is essential to optimal patient outcomes. Thus, health care providers and researchers must identify ways to enhance medication adherence. One important way is to identify the factors that contribute to poor adherence.

Barriers to medication adherence were the only significant predictor of all 3 indicators of objectively measured adherence. In addition to barriers to

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    This study was supported by funding from the Philips Medical-American Association of Critical Care Nurses Outcomes Grant; University of Kentucky General Clinical Research Center (M01RR02602), and Gill Endowment. Also the project was supported by grant number R01 NR008567 from the National Institute of Nursing Research. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Nursing Research or the National Institutes of Health.

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