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The Effectiveness of Medication Adherence Interventions Among Patients With Coronary Artery Disease: A Meta-analysis

Chase, Jo-Ana D. PhD, APRN-BC; Bogener, Jennifer L. BSN; Ruppar, Todd M. PhD, RN; Conn, Vicki S. PhD, RN, FAAN

The Journal of Cardiovascular Nursing: July/August 2016 - Volume 31 - Issue 4 - p 357–366
doi: 10.1097/JCN.0000000000000259
ARTICLES: Systematic Reviews and Meta-analyses

Background: Despite the known benefits of medication therapy for secondary prevention of coronary artery disease (CAD), many patients do not adhere to prescribed medication regimens. Medication nonadherence is associated with poor health outcomes and higher healthcare cost.

Objective: The purpose of this meta-analysis was to determine the overall effectiveness of interventions designed to improve medication adherence (MA) among adults with CAD. In addition, sample, study design, and intervention characteristics were explored as potential moderators to intervention effectiveness.

Methods: Comprehensive search strategies helped in facilitating the identification of 2-group, treatment-versus-control–design studies testing MA interventions among patients with CAD. Data were independently extracted by 2 trained research specialists. Standardized mean difference effect sizes were calculated for eligible primary studies, adjusted for bias, and then synthesized under a random-effects model. Homogeneity of variance was explored using a conventional heterogeneity statistic. Exploratory moderator analyses were conducted using meta-analytic analogs for analysis of variance and regression for dichotomous and continuous moderators, respectively.

Results: Twenty-four primary studies were included in this meta-analysis. The overall effect size of MA interventions, calculated from 18,839 participants, was 0.229 (P < .001). The most effective interventions used nurses as interventionists, initiated interventions in the inpatient setting, and informed providers of patients’ MA behaviors. Medication adherence interventions tested among older patients were more effective than those among younger patients. The interventions were equally effective regardless of number of intervention sessions, targeting MA behavior alone or with other behaviors, and the use of written instructions only.

Conclusions: Interventions to increase MA among patients with CAD were modestly effective. Nurses can be instrumental in improving MA among these patients. Future research is needed to investigate nurse-delivered MA interventions across varied clinical settings. In addition, more research testing MA interventions among younger populations and more racially diverse groups is needed.

Jo-Ana D. Chase, PhD, APRN-BC Assistant Professor, S343 School of Nursing, University of Missouri, Columbia.

Jennifer L. Bogener, BSN Nursing Student, School of Nursing School of Health Professions, University of Missouri, Columbia.

Todd M. Ruppar, PhD, RN Assistant Professor, S423 School of Nursing, University of Missouri, Columbia.

Vicki S. Conn, PhD, RN, FAAN Potter-Brinton Professor and Associate Dean for Research, S317 School of Nursing University of Missouri Columbia.

Supported by Award Number R01NR011990 (Conn-PI) 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.

The authors have no conflicts of interest to disclose.

Correspondence Jo-Ana D. Chase, PhD, APRN-BC, S343 School of Nursing, University of Missouri, Columbia, MO 65211 (

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Heart disease is the leading cause of death among adults in the United States.1,2 Coronary artery disease (CAD), the most common form of heart disease, is responsible for 385,000 deaths and $108.9 billion in healthcare expenditures annually.1,2 Secondary prevention for CAD is a multi-intervention approach involving therapeutic lifestyle changes and evidence-based medical therapies, such as prescribed medications. Between 1980 and 2000, these therapies have contributed to a 50% reduction in CAD-related deaths.3 Research suggests that the greatest contributor to this reduction is medications for secondary prevention of CAD.3

Unfortunately, medication nonadherence is highly prevalent.4 Approximately one-third of patients who have had a myocardial infarction do not adhere to prescribed medication regimens.5 Nonadherence is associated with increased risk for all-cause and cardiovascular mortality, revascularization procedures, hospitalization, and higher healthcare cost.6–8 Effective interventions to improve medication adherence (MA) in this population are critically needed.

Efficacy of MA interventions varies.9–14 Few systematic reviews have focused on MA interventions among patients with CAD.15–18 Prior reviews have been limited by narrow search strategies, unclear inclusion criteria, lack of a quantitative synthesis, or absent exploration of potential moderating variables.16 To date, no current meta-analyses addressing MA intervention effectiveness among patients with CAD exist. Thus, the overall effectiveness of MA interventions in this population is unclear; furthermore, the most effective types of interventions are yet unknown.

A meta-analysis and moderator analysis of MA interventions among patients with CAD could promote efficiency in developing future interventions and provide clinicians with guidance to promote MA in clinical practice. The purposes of this systematic review and meta-analysis were to describe and quantify the overall effectiveness of the body of MA intervention research among patients with CAD and to explore potential moderators of intervention effectiveness. In addition, we identified limitations in the extant research and suggested areas for future study.

The following research questions guided this study:

  • 1) What is the overall effectiveness of MA interventions on MA outcomes among patients with CAD?
  • 2) Does intervention effectiveness vary based on intervention, sample, or design characteristics?
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The systematic review and meta-analysis were performed using standard meta-analysis techniques and PRISMA guidelines.19,20 This project was part of a larger parent study examining MA outcomes of MA interventions across multiple chronic and acute illnesses.

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Search Strategies

We consulted an expert health sciences reference librarian to ensure comprehensive search strategies.21 Databases that were searched included the following: MEDLINE, PubMED, PsychINFO, CINAHL, EBSCO, PQDT, Cochrane Central Trials Register, Cochrane Database of Systematic Reviews, IndMed, ERIC, International Pharmaceutical Abstracts, EBM Reviews-Database of Abstracts of Reviews of Effects, as well as Communication and Mass Media. Broad MeSH terms were used, which included the following: patient compliance, medication adherence, drugs, prescription drugs, pharmaceutical preparations, generic, dosage, compliant, compliance, adherent, adherence, noncompliant, noncompliance, nonadherent, nonadherence, medication(s), regimen(s), prescription(s), prescribed, drug(s), pill(s), tablet(s), agent(s), improve, promote, enhance, encourage, foster, advocate, influence, incentive, ensure, remind, optimize, increase, impact, prevent, address, decrease. Fifty-seven relevant journals were hand-searched, and author searches and ancestry searches of prior reviews’ bibliographies were conducted to identify additional potentially eligible studies.

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Inclusion Criteria

We included 2-group, treatment-versus-control comparison studies testing interventions to increase MA in patients 18 years or older with a diagnosis of CAD, defined by the primary studies. Medication adherence interventions are deliberate actions performed or directed by investigators to increase adherence to specified medication regimens. Examples include education, reminders, and special packaging. Studies with varied types of MA measurement (eg, electronic monitoring devices, pharmacy refills, self-report) were included, given the diversity of MA measures in this research area. Eligible studies needed to contain enough data to calculate an effect size (ES). The research team attempted to contact corresponding authors to obtain missing outcome data.

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Data Extraction

To extract relevant data from primary studies, a coding strategy was developed from prior research and expert consultations. The codebook was developed through an iterative process and pilot tested. Data extracted included the primary study source, publication date, dissemination type (eg, journal article, dissertation), presence of funding, participant demographics (eg, age, gender, ethnicity, comorbidities), research methods, intervention details, and MA outcomes. Multiple descriptors of primary study research methods were coded, such as sample size, randomization, and intention-to-treat analyses. Method of MA measurement and follow-up interval were recorded. Varied intervention characteristics were coded, including content (eg, problem solving, self-monitoring, goal setting), delivery (eg, face-to-face, telephone), dose (eg, length/number of sessions), and setting (eg, clinic, home).

Included studies were independently coded by 2 extensively trained research specialists, then compared and discussed until consensus was reached. A doctorally prepared senior research specialist supervised the coding process to ensure coding integrity and reviewed all ES data. Questionable items were resolved in team meetings with the study principal investigator.

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Data Analysis

All data were analyzed using Comprehensive Meta-Analysis Software.22 Standardized mean difference effect sizes (d, ES) were calculated for each 2-group treatment-versus-control posttest comparison. The standardized mean difference ES between the groups was calculated by dividing the difference between treatment and control group postintervention means by the pooled standard deviation. Additional ES analyses were conducted within the groups by subtracting the outcome scores from the baseline scores and dividing by the baseline standard deviation. Effect sizes were weighted by the inverse of variance to account for sample size and adjust for bias, then synthesized using a random-effects model.23 A random-effects model was chosen a priori, given the expected within- and between-study variance across primary studies. Data were examined for possible outliers on the basis of standardized residuals of each primary study’s ES. Publication bias was examined by assessing the symmetry of a funnel plot constructed by plotting each primary study’s standard error against its ES.23

Homogeneity of variance was tested using a conventional heterogeneity statistic (Q), to quantify observed heterogeneity across studies, and I,2 to determine the proportion of observed heterogeneity due to true differences in effects across studies.23 Exploratory moderator analyses were used to examine possible associations between study characteristics and intervention effectiveness. Dichotomous variables were evaluated using subgroup analysis, and continuous variables were evaluated using meta-regression.23

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Twenty-four primary reports were eligible for analysis.9–14,24–41 Additional coding information was found in 4 companion reports about the same primary studies.42–45 Three primary study reports contained multiple comparison groups.33,36,37 There were 28 treatment-versus-control-group posttest comparisons, 9 treatment group pretest-posttest comparisons, and 6 control group pretest-posttest comparisons. Few smaller studies with negative findings were included, indicating evidence of publication bias.

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Primary Study Characteristics

The primary studies that were included in this meta-analysis included 24 journal articles, 3 dissertations, and 1 presentation. Six studies were disseminated before 2000. Seventeen studies were supported by funding.

Primary study characteristics are presented in Table 1. Majority of the samples were males. The median of the mean age for participants was 62.9 years. Only 7 studies reported data on ethnicity. Of those, most subjects were white. Some studies reported additional chronic diseases among their subjects including the following: hypertension (k = 17), undifferentiated diabetes (k = 16), hyperlipidemia (k = 12), heart failure (k = 4), stroke (k = 3), lung disease (k = 3), renal disease (k = 2), osteoarthritis (k = 1), asthma (k = 1), atrial fibrillation (k = 1), nephritic syndrome (k = 1), thyroid disorder (k = 1), and cerebral vascular disease (k = 1).



Primary studies reported diverse methods. The median number of intervention sessions was 2 (k = 17). The median number of days for MA intervention duration was 35 (k = 23). Only 1 study reported intervention session duration. Outcome data of MA were collected with a median of 124.5 days after intervention (k = 14). Studies reported diverse methods of collecting MA outcomes including pharmacy refill (k = 7), self-report (k = 18), biological measures (k = 2), and pill counts (k = 1).

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Overall Effects of Medication Adherence Interventions of Medication Adherence Outcomes

Overall MA ESs are presented in Table 2. The ESs were calculated for 28 treatment-versus-control-group comparisons containing 18,839 subjects. The overall ES for these comparisons was 0.229 (P < .001), indicating significant improvements in MA outcomes in the treatment over the control group (Figure). When the 3 largest sample studies were excluded, the ES for these comparisons demonstrated minimal change (d = 0.269, P < .001). The ESs were significantly heterogeneous.





We also calculated overall ESs for the 9 treatment group pretest-posttest comparisons and for the 6 control group pretest-posttest comparisons. Although the former ES was positive (0.183) and the latter negative (−0.014), neither were statistically significant. Lack of statistical significance may reflect low power from the small number of comparisons.

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Moderator Analyses

Continuous and dichotomous moderator analyses are displayed in Tables 3 and 4, respectively. Although all studies from the main analysis were examined for moderating variables, only those moderators reported for a sufficient number of comparisons were included in the analyses.





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Intervention Moderators

Studies in which health care providers were given information about subjects’ MA revealed a significantly greater ES (0.387) than when the providers were not given information on MA (0.151). An example of this type of intervention component could involve using a questionnaire on participants’ baseline MA and barriers to MA.24 Studies with nurse interventionists (0.428) reported significantly higher MA than studies without nurse interventionists (0.127). Studies with and without physician and pharmacist interventionists had similar ESs. Interventions started when participants were inpatients had significantly larger effects (0.590) than interventions that did not start with inpatients (0.141); however, there was little difference when the intervention was delivered at home versus in the clinic. With regards to the mode of intervention delivery, we saw no significant differences among telephone, written materials only, or face-to-face delivery. Interventions using mail delivery were less effective (0.060) than interventions without mail delivery interventions (0.292). There were several nonsignificant variables, including: utilization of theory, number of sessions, duration of intervention, time point for measuring outcome MA, goal setting, interventions delivered at home, interventions delivered in clinic, problem solving, succinct written instructions, any written instructions, behavior target (MA or multiple behaviors), physician or pharmacist interventionists, telephone and face-to-face delivery, and written instructions only.

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Report and Sample Moderators

The age of subjects had a significant positive slope (0.014), revealing that MA interventions led to greater adherence improvement in samples of older patients. Interventions were equally effective regardless of publication status, funding, and location. Other nonsignificant moderators included year of publication, percentage of women and underrepresented groups, and socioeconomic status.

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Design and Methods Moderators

Although sample size had a statistically significant negative slope, this finding is not clinically substantive. Other potential moderators related to design, such as blinding, allocation concealment, random assignment, and intention-to-treat analyses, were not associated with MA effectiveness.

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Findings from this meta-analysis, which is the first of its kind, that suggest interventions to increase MA among participants with CAD were significantly effective. These positive findings are similar to prior meta-analyses examining MA outcomes from MA interventions among underrepresented groups and from packaging intervention effects.46,47 Although poor MA has been linked to negative health outcomes in patients with CAD,4,6,7 consensus on how much MA is needed to improve varied CAD-related outcomes is not yet clear. Prior research exploring MA and blood pressure outcomes48,49 as well as cardiovascular disease risk exists.49 However, further research is needed to quantify the amount of MA needed to mitigate additional CAD-related outcomes. Moreover, the dose of MA intervention needed to change MA behavior among patients with CAD is yet to be determined. Due to the small number of comparisons using similar measures of MA, we were unable to convert the ES to a clinical metric of adherence. Future MA intervention research among patients with CAD should include explicit information regarding intervention dose.

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Moderator Findings

We found several interesting moderators. Interventions in which healthcare providers were given information regarding participants’ MA were more effective than interventions without this component. Awareness of patients’ MA behavior can motivate and guide providers to address issues related to MA. Clinicians working with patients with CAD should assess issues with or barriers to MA to identify the possible need to intervene. Future research might directly compare an intervention that provides patient MA status to healthcare providers to a similar intervention without this provision.

Medication adherence interventions delivered by nurses were especially effective. Nurses have considerable access to patients with CAD in outpatient settings, such as cardiac rehabilitation and clinics. In addition, nurses working in the inpatient setting spend approximately 25% to 37% of their time providing direct patient care and 11% to 21% of their time in medication-related tasks.50,51 In addition to substantial access to this patient population, nurses also have clinical skills to promote MA. For example, nurses have delivered efficacious MA interventions through counseling,52 follow-up communication,27,53,54 and case management.55,56 Nurses should play an active role in developing and implementing MA interventions among patients with CAD. Research exploring nursing interventions to increase MA among patients with CAD could focus on testing or comparing specific intervention strategies such as education, counseling, and managing barriers. Specific nurse type and training were not clearly reported among the studies, hindering the comparison of MA intervention effectiveness across different types of nurses. Investigators of future studies should explicitly identify types of nurses delivering MA interventions among patients with CAD.

Medication adherence interventions initiated in the inpatient setting were more effective. The inpatient setting may provide an opportunity for clinicians to inform patients and families about the importance of medications for secondary prevention of CAD as well as strategies for MA. Moreover, the dire nature of hospitalization may influence patient and family receptivity to MA interventions. Most MA interventions initiated in the inpatient setting included follow-up intervention content after discharge. Continued reinforcement of MA after discharge may positively affect MA outcomes. For those patients who may start medications outside the hospital, interventions delivered at home or in the clinic were equally effective. Future research might directly compare MA interventions initiated in the inpatient setting to MA interventions initiated after hospitalization.

Regarding sample characteristics, only age appeared to impact intervention effectiveness. As the age of the sample increased, so did the intervention effectiveness. These findings support prior research related to statin MA and low-density lipoprotein goal attainment.57,58 Chi and colleagues57 postulated that older individuals are more likely to have multiple comorbidities and may be more attentive to prescribed medication regimens. Additional primary research is needed to identify effective MA interventions among younger populations with CAD. Furthermore, more primary research involving more diverse samples is needed. Deaths related to CAD are higher among African Americans than whites and other groups.2,59 Rates of MA for various chronic diseases also differ across race and ethnicity, with minority groups being less adherent to prescribed medications.60,61 However, few primary studies included in this meta-analysis reported racially or ethnically diverse groups. Thus, future primary research testing MA interventions among patients with CAD must strive to include minority groups to reduce this disparity.

We found some interesting nonsignificant moderators. Interventions focusing solely on MA were as effective as interventions that had multiple behavioral foci. Thus, clinicians may take the opportunity to introduce strategies for MA while discussing other health behaviors with CAD patients. The use of only written material did not impact intervention effectiveness, suggesting that providers should consider using more than this type of delivery when promoting MA among patients with CAD. Future MA intervention research among patients with CAD should incorporate additional forms of intervention delivery beyond written materials. Number of intervention sessions did not appear to be a significant moderator. It is possible that even 1 or 2 intervention sessions may be effective in changing MA behavior among patients with CAD. However, additional research testing or comparing various aspects of intervention dose could help identify the most effective dose needed to change MA behavior. We did not identify any specific intervention strategy that increased MA intervention effectiveness; however, lack of statistical significance of these moderators may be related to the small number of comparisons.

Medication adherence interventions delivered by physicians or pharmacists were equally effective as interventions not delivered by these providers. Although these findings suggest that involving these providers may not increase MA intervention effectiveness, the number of studies incorporating these types of interventionists was small. Future research could directly compare similar MA interventions among patients with CAD delivered by different clinicians. Additional research may also explore variations in MA intervention delivery across diverse healthcare providers.

This meta-analysis was limited by some primary study characteristics. Although efforts were made to contact corresponding authors, some studies were excluded because critical data were missing from primary study reports. Primary study reporting limits the generalizability of this study’s findings to more diverse populations. Primary study quality is an important issue in meta-analysis work. Multiple strategies are recommended to manage primary study quality.62,63 We used specific inclusion criteria to capture reports with more rigorous study designs, employed analysis techniques accounting for study heterogeneity, and explored study quality empirically through moderator analyses. Some publication biases were present. Smaller, negative studies are less likely to be published; therefore, access to these studies is limited. Despite extensive search strategies, capturing these relevant studies was a challenge.

Primary study reporting affected the ability to identify effective combinations of MA components. Several studies used multiple intervention strategies; however, combinations of strategies were inconsistent. Thus, determining the most effective combination of MA intervention strategies was not possible.

Measurement error within the primary studies could have introduced bias toward overestimation of MA intervention effects. Objective measures are the most sensitive and specific means of measuring MA64,65; however, most included studies used self-reported MA, which is known to overestimate patients’ MA.66 Future MA intervention research conducted among patients with CAD should consider using objective measures of MA to reduce bias.

Meta-analyses are observational studies. The moderator findings of this study are intended to promote additional exploration in this area of study. The scope of this meta-analysis is limited to MA among patients with CAD. Therefore, interpretation of these findings may not be possible among patients with other chronic illnesses or other forms of heart disease.

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Medication management is an important aspect of secondary prevention for CAD. Nonadherence to prescribed medications for CAD has been linked with multiple poor outcomes. Findings from this meta-analysis suggest that MA interventions among patients with CAD are effective, especially among older patients. Clinicians working with patients with CAD evaluate patients’ MA behavior before initiating interventions to improve MA. Nurses are on the front lines of health behavior promotion among these patients and can be effective MA interventionists. Future research is needed to explore MA interventions among younger populations and more racially diverse groups.

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What’s New and Important?

  • Interventions designed to increase MA among patients with CAD are modestly effective.
  • In this patient population, nurse-delivered MA interventions were more effective than interventions not delivered by nurses.
  • Among patients with CAD, MA interventions initiated in the inpatient setting can be more effective than interventions initiated in the outpatient setting.
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    coronary artery disease; medication adherence; meta-analysis; patient compliance

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