Discussion
The primary objective of this study was to identify interventions led by HCPs to improve medication adherence following ACS. Meta-analysis revealed a small effect of HCP-led interventions on medication adherence. Our results are consistent with previous meta-analysis studies that have looked at the effectiveness of adherence interventions in other cardiac patient populations.5 17
In line with recent adherence literature,49 the majority of intervention studies identified were delivered by nurses or pharmacists. However, we found no indication that study effectiveness was moderated by the HCP delivering the intervention. Studies that included nurses in their delivery had a negligible effect towards better medication adherence, which does not correspond to findings from another meta-analysis that found that nurse-led interventions had a small to medium effect on adherence in patients with CAD.5 Six pharmacist-led interventions had a small but non-significant effect on medication adherence, which is congruous with previous reviews across cardiac-related diseases.5 17 Objectively, pharmacists should be ideal candidates to deliver adherence interventions due to the necessary knowledge and skills they possess to promote and support medication-taking behaviour.50 A meta-analysis of 771 medication adherence intervention trials found that the most effective interventions were delivered by pharmacists,49 which suggests that pharmacists may be better utilsied in other patient populations. Our findings should, however, be interpreted with caution due to the small number of pharmacist-led studies included in our analyses.
In terms of delivery method, interventions that included phone contact had higher odds of medication adherence compared with interventions delivered exclusively in person. Phone-delivered interventions may be a more convenient method to reach patients after discharge to monitor and encourage good medication adherence over time. Half of the interventions that included phone contact also contained a face-to-face predischarge component. Cutrona et al
51 found that two-thirds of interventions delivered at discharge were effective at improving adherence to cardiovascular medicines. Periods of care transition such as during hospital discharge are ideal opportunities to discuss treatment to pre-empt potential barriers to regimen adherence. Moreover, the dynamic nature of adherence dictates that monitoring of medication-taking behaviour over time by both patients and/or HCPs is crucial to ensure therapy maintenance for long-term conditions such as ACS.
We expected to find a greater proportion of interventions that used theoretical approaches to change medication-taking behaviour. There were only four studies that reported a theoretical basis, of which just one was based on a model of medication-taking behaviour (necessity–concerns framework52). A review by Conn et al
53 found that theory-driven interventions had a significant but modest effect on medication adherence. Our findings suggest that theory-driven adherence interventions for ACS are lacking, thus highlighting an important avenue for future research.
Coding intervention content
To our knowledge, this review is the first to use the BCT taxonomy to code interventions that targeted adherence across all cardiac medications following ACS. The BCT taxonomy provided a useful tool to analyse the content of adherence interventions, and we found that one-third of all BCTs detailed in the taxonomy were identified in at least one intervention. This relatively small number of total BCTs identified was unsurprising as many were not applicable to medication-taking behaviour. It is likely that additional strategies may have been used among interventions but were not identified due to a lack of detail in the description of the intervention. A lack of transparency in study reporting is an issue that limits the usability and replicability of interventional research. Checklists such as TIDieR54 are becoming commonplace to improve the quality of intervention reporting.
Written, verbal or visual information provision about the consequences of adherence (BCT 5.1) was by far the most frequently used BCT among HCP-led interventions. Discussing the consequences of non-adherence may help to strengthen patients’ beliefs in the necessity of their medications, which have been shown to predict non-adherence.55 While information is necessary to improve patients’ knowledge, it is not sufficient as a standalone strategy to change behaviour. Information-only strategies have been found to be generally ineffective at changing complex behaviours such as adherence.56
Clinical and research implications
Medication taking is a complex behaviour that can be difficult to change. Targeting patients identified with an adherence issue rather than all medication-takers may be one strategy to improve the effectiveness of adherence interventions. Cutrona et al
57 reported that ‘broad’ interventions (target all medication-takers) were less effective than ‘focused’ (target non-adherers only). None of the studies identified in this review targeted non-adherers; therefore, it is not yet known whether ‘focused’ interventions would be more appropriate for patients with ACS.
There were a variety of adherence measures used among included interventions, most of which were non-validated self-report tools. While an approach that combines self-reporting with an objective measure (eg, prescription refill records) is considered best practice, just two interventions followed this guidance. No studies used electronic monitors (eg, Medication Event Monitoring System) that provide real-time data on medication-taking behaviour58 and have been used to good effect in studies with patients with hypertension,59 heart failure60 and CAD.61 There is potential for objective measures to be used in conjunction with self-report tools to provide a more reliable and accurate representation of medication-taking behaviour of patients with ACS.
Strengths and limitations
The strengths of this study include the adoption of a comprehensive search strategy that comprised eight online databases and a supplementary grey literature search. Additionally, we applied an existing behaviour change framework to identify specific techniques used among HCP-led adherence interventions, which we believe is a novel approach for trials with patients with ACS. Our study does also include certain limitations. First, while we were successful in BCT identification, there were insufficient data to determine the effectiveness of particular BCTs. A larger data set would be required to undertake the type of meta-regression analyses that have recently been reported within the adherence literature.62 Second, we found relatively high levels of statistical heterogeneity in our random-effects models, which is inherent when comparing methodologically diverse behavioural interventions. We accounted for this variability by removing outliers, which resulted in our final model having moderate statistical heterogeneity. Third, only one researcher was involved in all aspects of the identification, screening, data extraction and risk of bias assessments, although dual-raters coded interventions independently using the BCT taxonomy. Best practice would be to include multiple independent raters in all stages of the review to ensure methodological rigour. Fourth, we decided not to exclude studies based on how medication adherence was measured, which was often done using unreliable self-report methods. A previous review by Santo et al
63 circumvented this issue somewhat by including stricter adherence measurement eligibility criteria. Ultimately, all methods of adherence measurement are limited in terms of practicality, reliability and cost, which represents a wider issue across the adherence literature.