Description of the condition

Atrial fibrillation (AF) is the most common arrhythmia in clinical practice (Kirchhof 2016). The lifetime risk of developing AF is approximately one in four among people aged 40 years or older (Lloyd‐Jones 2004; McManus 2012). The incidence and prevalence of AF is rising (Chugh 2014; Colilla 2013; Krijthe 2013).The prevalence of AF dramatically increases with age, rising from 0.5% at 40 to 50 years of age to 5% to 15% at 80 years (Chugh 2014; Colilla 2013; Heeringa 2006; Krijthe 2013; Lane 2017; Lloyd‐Jones 2004; Miyasaka 2006), with the prevalence being slightly higher in men than in women (Lloyd‐Jones 2004; McManus 2012). One US population‐based study (N = 4618) found the age‐ and sex‐adjusted incidence of AF per 1000 person‐years was 3.04 (95% CI 2.78 to 3.31) in 1980, increasing to 3.68 (95% CI 3.42 to 3.95) in 2000, amounting to a relative increase of 12.6% (Miyasaka 2006). Similar findings in the European Rotterdam Study (N = 6806) found that the overall prevalence of AF was 5.5% to 6.0% in men and 5.1% in women (Heeringa 2006). Recent analyses of the Clinical Practice Research Datalink in the UK demonstrate a constant yearly rise in the prevalence of AF nationally, increasing from 700,000 patients in 2010 to a projected prevalence of between 1.3 million and 1.8 million patients by 2060 (Lane 2017). AF is associated with a five‐fold greater risk of stroke and thromboembolism (Wolf 1991), and the incidence of stroke attributable to AF also increases with age (Lip 2006). AF‐related stroke is likely to be more severe than non‐AF related stroke (Sheikh 2015; Wolf 1991). When including hospital admissions, treatment costs, and long‐term nursing home care, AF accounts for 1% of the total UK healthcare expenditure (Sheikh 2015). Given the increasing incidence and prevalence of AF, these figures are likely to rise.

Patients with an increased risk of stroke (as determined by stroke risk stratification models) should receive long‐term oral anticoagulant therapy (OAT): either vitamin K antagonists (VKA) such as warfarin, or non‐vitamin K antagonist oral anticoagulants (NOAC) such as apixaban, dabigatran, edoxaban, or rivaroxaban, unless contraindicated. In a meta‐analysis, dose‐adjusted OAT, resulting in international normalized ratio (INR) values in the range of 2.0 to 3.0, significantly reduced the risk of ischaemic stroke or thromboembolism in patients with non‐valvular AF by 39% (95% CI 22% to 52%) and 64% (95% CI 41% to 62%), respectively, compared with either aspirin or placebo (Hart 2007). Whilst OAT dramatically reduces stroke risk, the therapeutic range of the INR is narrow and must be maintained. This can be problematic, with INRs greater than 3.0 increasing the risk of major and minor bleeding and INRs less than 2.0 increasing the risk of thromboembolism (Lip 2006). Regular INR monitoring is essential and patients need to carefully adhere to dietary and lifestyle restrictions (Ansell 2004). A retrospective analysis of OAT in the UK demonstrated that only patients with the greatest INR control increased their time to stroke occurrence, with only patients spending over 71% of their time in the target therapeutic range (TTR) benefiting (Morgan 2009). In practice, 51% of patients at high risk of stroke (CHADS₂ score 2 or more) remained outside of the target therapeutic range for at least 50% of the time (Morgan 2009). Further, a post hoc analysis of patients enrolled in the Atrial Fibrillation Clopidogrel Trial With Irbesartan for Prevention of Vascular Events (ACTIVE), which randomised AF patients with one additional stroke risk factor to receive clopidogrel 75 mg/day plus aspirin (75 to 100 mg/day recommended dose) or OAT, found that patients with a TTR less than 58% gained no benefit from OAT. The INR must be within the therapeutic range for at least 58% of the time to confer benefit in terms of stroke risk reduction (Connolly 2008). Thus, maintenance of INR is a major concern for both AF patients and healthcare professionals. Furthermore, whilst interventions targeting this patient group ultimately aim to reduce the risk of stroke, patients' TTR is a good short‐term indicator of whether the patients will experience adverse events in the long‐term, thus presenting a useful trial endpoint.

The inherent difficulties associated with VKAs (narrow therapeutic range; drug, alcohol, and food interactions; regular blood tests) have led to the development of NOACs, which have sought to overcome these problems by providing an efficacious and safe alternative treatment that does not require regular monitoring. Several NOACs are now available (apixaban, dabigatran, edoxaban, and rivaroxaban) and all are non‐inferior to warfarin for the prevention of stroke and systemic embolism, with similar (for dabigatran 150 mg twice daily and rivaroxaban) or better safety profiles (dabigatran 110 mg twice daily, apixaban, and edoxaban) and a significant reduction in intracranial haemorrhage for all NOACs (Connolly 2009; Giugliano 2013; Granger 2011; Patel 2011). The use of NOACs may shift the focus of interventions for this patient group, but VKAs (i.e. warfarin) are still widely used in AF patients and it is important to investigate ways in which we can improve the outcomes of patients still taking VKAs and whether the principles used for interventions with this group are also relevant for those taking NOACs.

Given that AF is a chronic condition that places patients at increased risk of mortality and morbidity ‐ particularly from stroke ‐ and often requires life‐long treatment, including chronic OAT, the educational materials and the support given to patients when they are first prescribed OAT are crucial for the maintenance of their treatment regimens.

Description of the intervention

Attempts to support behaviour change can take numerous forms. At the individual level they almost always fall into the category of 'education or communication' and may use one or more behaviour change techniques (Michie 2011; NICE 2007). While some interventions are designed to target regimen simplicity or access to testing, education is vital to enable patient uptake and adherence (to medication, treatment regimen, and lifestyle changes). Indeed, patient education for OAT has attempted to influence behaviour by improving knowledge, attitudes, and practices that are necessary to improve health outcomes (Wofford 2008). Yet very few studies define their intervention components in a standardised way, despite novel guidelines that give explicit guidance on how to do so (Michie 2011).

In recent years increased attention has been paid to the classification of behaviour change techniques to aid the development and design of interventions. The behaviour change taxonomy describes 93 distinct techniques that can be applied to understanding a range of health‐related behaviours. The taxonomy was validated using obesity and tobacco use as examples, but can be applied to a range of health behaviours including adherence. Defining an intervention using these techniques at the development stage could influence the success of the intervention (Michie 2009; Michie 2013).

Techniques used in delivering patient education cover a wide spectrum, including the use of booklets and videos as media to transmit information either alone or in addition to self‐management interventions (such as INR self‐monitoring) and interventions that use decision aids (Khan 2004; Man‐Son‐Hing 1999). Patient knowledge surrounding OAT varies with age, with elderly patients (> 75 years) demonstrating poorer knowledge (Tang 2003). In one study, less than half of participants were able to name even one specific benefit, risk, or lifestyle change associated with warfarin (Coehlo‐Dantas 2004). In several cases, spouses were more knowledgeable than the patients and appeared to play a vital role in monitoring the individuals' treatment regimens (Coehlo‐Dantas 2004). Therefore, educational interventions for this patient group may prove to be particularly beneficial.

Other interventions focus on behavioural and practical aspects of lifestyle change and treatment. Behavioural interventions aim to modify patients’ behaviour towards treatment and symptoms (NICE 2007). Interventions that use these principles to promote change include cognitive behavioural therapy (CBT), motivational interviewing, and heart rate variability biofeedback. CBT is a goal‐oriented, systematic procedure which aims to solve problems concerning dysfunctional emotions, behaviours, and cognitions and to promote positive attitude, self efficacy, and planning. However, with any complex intervention it is difficult to determine which component has influenced the behavioural outcome, as researchers often do not define the active components of the intervention and interventions vary in duration and levels of support. Clearly it is important for trials to be explicit about the content and delivery of their interventions and to choose appropriate evaluative tools in order to examine how and why their interventions are successful, by using an applied behaviour change model (Kok 2016; Michie 2011).

How the intervention might work

Interventions for patients with AF who receive OAT should ultimately aim to improve clinical outcomes, primarily reducing the prevalence of stroke and mortality. However, in the short‐term we can aim to increase patients' TTR by focusing on factors that affect treatment adherence. Many factors can affect INR control, such as drug‐drug interactions and variable dietary vitamin K intake (Holbrook 2005), but with adequate knowledge surrounding treatment and lifestyle factors, interventions should aim to encourage behaviour change.

It has been suggested that several factors influence adherence (Horne 2013; Lane 2015; Thrall 2004), and these factors are either intentional or unintentional. Intentional non‐adherence can occur when patients make a decision not to take their treatment as a result of their personal motivations or beliefs, or both (Horne 2013). Unintentional non‐adherence refers to an individual’s skills or ability to take his or her medications (for example problems with remembering to take tablets). Poor INR control could result from both unintentional and intentional non‐adherence (Horne 2013). Where patients' knowledge of their condition and their OAT is limited, this may impact on their practical ability to manage treatment (unintentional) and their perceptions surrounding treatment necessity (intentional). Indeed several studies have demonstrated that patients have poor knowledge of AF and its treatment (Lane 2006; Lip 2002; Nadar 2003; Tang 2003).

There is evidence that patient knowledge correlates significantly with TTR (Tang 2003), with more knowledgeable patients having a better TTR. Thus if education can demonstrate an improvement in TTR, it could have important clinical benefits (that is the reduction of adverse events such as stroke and major bleeding). Decision aids are informative interventions designed to help people make specific choices surrounding their medications, and they may also increase patient knowledge. These interventions aim to reduce decision conflict, which refers to the patient's uncertainty in making health‐related decisions and the factors relating to that uncertainty, which may subsequently impact on treatment uptake and adherence.

Intentional non‐adherence may be more difficult to target and interventions need to focus on inaccurate perceptions of medications. The common sense model (Horne 1999) suggests that patients hold beliefs about the necessity of their prescribed medication (Specific‐Necessity) and concerns about prescribed medication based on beliefs about the danger of dependence and long‐term toxicity as well as the disruptive effects of the medication (Specific‐Concerns). The model also describes general beliefs about medication, assessing beliefs that medicines are addictive and harmful (General‐Harm) and that medicines are over‐prescribed by doctors (General‐Overuse). These beliefs, and the way in which patients balance their concern about medications, have been widely used in predicting medication adherence in a variety of chronic conditions including rheumatoid arthritis (Neame 2005), asthma (Jessop 2003), type II diabetes (Farmer 2006), and depression (Aikens 2005).

A comparison of beliefs about medications between adherent, unintentional non‐adherent, and intentionally non‐adherent patients found significant differences in medication‐related beliefs in patients with a range of chronic illnesses after being newly prescribed medication for the last 10 days (Clifford 2008). Compared with adherers, intentional non‐adherers had significantly lower scores on the necessity sub‐scale of the Beliefs about Medication Questionnaire (P = 0.012), higher scores on the concerns sub scale (P = 0.008), and lower scores on the necessity‐concerns differential (P = 0.001). There were no significant differences between adherers and unintentional non‐adherers (Clifford 2008). Evidently, whilst unintentional non‐adherers may benefit from memory aids (that is reminders, tablet dosettes), intentional non‐adherers may need to address both their perceptions of their medication and misinformation, which may be achieved by increasing patient education surrounding their treatment. Intentional non‐adherers appear to doubt their personal need for their medication and have concerns about taking it when compared to adherers.

More recent models critique the categories of ‘intentional’ and ‘unintentional’, as there is overlap between the categories. For example, whilst forgetting is unintentional it may be influenced by intentional or motivational factors (McHorney 2011). The capability, opportunity and motivation (COM‐B) model of behaviour was developed in order to choose interventions that are most likely to be effective and specific for the individual behaviour (Jackson 2014). This model hypothesises that the interaction between an individual’s capability, opportunity and motivation (COM) cause the performance of behaviour (B). Thus the model provides explanations for why patients do not adhere to treatment regimens. Patient’s capability includes their psychological and physical capacity to engage in necessary thought processes including disease comprehension, cognitive functioning (e.g. memory capacity) and executive function (e.g. capacity to plan). A complex medication regimen, such as with a VKA (i.e. warfarin), might be beyond the psychological planning capabilities of some patients. Motivation is defined as brain processes that energise and direct behaviour such as the perception of illness, beliefs about treatment, self‐efficacy and outcome expectancies. Some evidence suggests that individuals with complex regimens for several conditions choose to take the medication that offers the most symptom relief, or is treating the most feared condition (Nunes 2009). Opportunity is defined as the physical opportunity provided by the environment including cost, access, physical characteristics of the medicine, regimen complexity, social support and the relationship with the health‐care provider (HCP). For VKAs this may include the barriers to regular INR testing, and the social support required to attend appointments and make and maintain lifestyle changes. This model provides a more precise method of defining the causes of non‐adherence, going beyond the dichotomies of intentional and unintentional, and thus may prove to be a useful model when developing interventions with this patient group.

Research suggests that interventions with the greatest likelihood of success are theoretically underpinned, and precisely describe the behavioural change techniques employed to address the needs of target patient group (Michie 2009; Michie 2013).

Why it is important to do this review

AF is a condition that is increasing in prevalence (Chugh 2014; Lane 2017; Miyasaka 2006) and requires treatment with OAT to reduce associated stroke risk. However, patients on VKAs need to maintain a narrow therapeutic INR range, which may be difficult to achieve in practice (Morgan 2009). Patients need sufficient information to make informed choices and actively participate in the management of their own treatment (Lane 2015; Thrall 2004). Patient education aims to influence patient behaviour and improve knowledge, attitudes, and practices that are necessary to improve health outcomes (Wofford 2008), but the efficacy of patient interventions designed to improve AF patient adherence to OAT is not clear. By increasing patient knowledge and understanding surrounding AF and OAT we may reduce the prevalence of intentional and unintentional non‐adherence, and increase patient motivation to adhere, in addition to providing patients with the tools to improve their planning and capability to incorporate the regimen required with VKA therapy into their lifestyle (Jackson 2014), which may subsequently increase TTR. TTR is important and has been shown to be a predictor of thromboembolic or haemorrhagic complications, although it is a surrogate for the hard endpoints such as reductions in mortality and stroke that OAT is aimed at achieving. Many factors influence TTR, including adherence to medication and lifestyle factors (e.g., alcohol intake, diet and other medications), however, TTR does give an indication as to whether patients are adhering to the regimen required for VKA therapy, which should translate into a reduction in stroke and major bleeding events. We updated our previous review (Clarkesmith 2013) to evaluate the value of educational and behavioural interventions for patients with AF who were currently prescribed VKA (mainly warfarin), including the impact on TTR and secondary outcomes such as decision conflict, patient knowledge, and quality of life.