Introduction

Over the past decades, important progress in medical and pharmaceutical sciences led to the development of new efficacious treatments for diverse chronic conditions. However, the ultimate impact of any drug treatment—often measured as the effectiveness—also depends on the patients’ adherence to it. Treatments with high efficacy in clinical trials may turn out to be only moderately effective due to incomplete medication adherence with recommended dosing regimens in real-world settings. Non-adherence was therefore identified as a major public health problem by constituting a barrier to the effective, safe and cost-effective use of drugs [1]. Conclusively, the World Health Organization (WHO) reported non-adherence as a worldwide medical problem associated with excess morbidity, mortality and unnecessary costs [2]. WHO defined adherence ‘as the extent to which a person’s behaviour—taking medication, following a diet and/or executing lifestyle changes—corresponds with agreed recommendations from a health care provider’ [2]. Taking this further, Vrijens et al. [3] recently introduced a new taxonomy for describing and defining adherence to medication. It was proposed to uniformly use the term ‘medication adherence’, which was defined as ‘the process by which patients take their medications as prescribed, composed of initiation, implementation and discontinuation’. In accordance with this new taxonomy, the term ‘medication adherence’ will be used throughout this manuscript. In arterial hypertension—defined as a systolic blood pressure of 140 mmHg or higher and/or a diastolic blood pressure of 90 mmHg or higher—lack of medication-adherence to prescribed medicines is a major reason for unsatisfying therapeutic outcomes and therefore a major challenge [4]. Similar to other chronic conditions, including diabetes and overweight, a main reason for problems in patients’ adherence is the asymptomatic nature of the disease. Other previously reported factors contributing to non-adherence include the long-term disease course of hypertension and thus the necessity for lifelong treatment and multiple daily dosing [5, 6].

Improving the adherence to therapeutic regimens could substantially improve therapeutic outcomes, especially in high-income countries, where effective drugs are widely available for everybody. It may prove most cost effective to increase the effectiveness of already licensed drugs by improving medication adherence rather than focussing on developing further new therapeutic products. A better understanding of causes of non-adherence is, however, necessary to ultimately improve effectiveness of current drugs. Thus, the aim of this study was to evaluate adherence to long-term medication in Austria and determine its causes, with a special focus on social parameters and behavioural theories.

Methods

Data presented in this article stem from the European Union (EU) funded project ‘Ascertaining Barriers for Compliance: policies for safe, effective and cost-effective use of medicines in Europe’ (ABC). Cumulative data for the entire European cohort were published in June 2012 in the Final Study Report of the ABC Project and in ‘Value in Health’ (in press). This manuscript describes in detail findings of this survey restricted to Austria.

Patients were recruited via advertisements (posters and printed material) in community pharmacies across Austria, which were randomly selected from a list provided by the national prescription pricing authority. A total of 1272 pharmacies were contacted. Patients were eligible if they were 18 years of age or older, had a diagnosis of arterial hypertension, were currently prescribed medication against arterial hypertension and were self-responsible for drug administration. Exclusion criteria were lack of consent, presence of a self-reported psychiatric condition and living in a nursing home or similar facility. The questionnaire was completed via a web-based survey tool provided by SurveyMonkey.com.

Measuring adherence

In this study, adherence was measured by the four-item Morisky Medication Adherence Scale (MMAS-4). The MMAS-4 is the most frequently used questionnaire measuring adherence to medication [7]. This scale, originally designed to evaluate medication adherence in hypertensive patients, has been validated and found to be reliable in a variety of medication adherence studies [8].

Patients were categorized as non-adherent if they answered one or more question of the MMAS-4 with ‘yes’. They were classified as intentionally non-adherent when either item 3 or 4 or both were answered with ‘yes’ (see also Table 1). Items 1 and 2 of the MMAS-4 (i.e. ‘Do you ever forget to take your high blood pressure medicine?’ and ‘Do you ever have problems remembering to take your blood pressure medicine?’) are related to the implementation of the dosing regimen and are more non-intentional whereas items 3 and 4 (i.e. ‘When you feel better, do you sometimes stop taking your high blood pressure medicine?’ and ‘Sometimes, if you feel worse when you take your blood pressure medicine, do you stop taking it?’) are related to treatment discontinuation and are intentional.

Table 1 Demographic data and missing data for overall study population (n = 323)
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Measurement of variables and instruments used

The Stanford Self-Rated Health Scale was used to measure health status; the Revised Life Orientation Test was used to determine dispositional optimism [9]; the Beliefs about Medicines Questionnaire (BMQ-S11) was applied to evaluate beliefs about medicine [10]; and to measure attitudes, normative beliefs, barriers, facilitators, intention and self-efficacy, a theory of planned behaviour (TPB) questionnaire was used. TPB is a theory in psychology about the link between beliefs and behaviour [11]. A questionnaire of the European Task Force on Patient Evaluation in General Practice was used to measure satisfaction with the practitioner and her/his practice [12]; the Building Research Initiative Group: Chronic Illness Management and Adherence in Transplantation (BRIGHT) was used for barriers and social support [13, 14]; and the Brief Illness Perception Questionnaire (BIPQ) was applied to assess parameters of illness perception [15].

Ethical considerations

Ethical approval was obtained by the national ethics committee in Austria (590/2011). Participants provided informed consent by checking a box in the online survey to confirm that they had read and understood all participant information. Access to the survey was denied if the box was not checked. SurveyMonkey®, where the questionnaire responses were stored initially, guaranteed data safety. SurveyMonkey® has signed up to the Safe Harbor agreement. This agreement was created to enable the transfer of ‘personal data’ between the EU and USA following the introduction of the EU’s Data Protection Directive (1995). SurveyMonkey® was asked in written to completely delete survey data from its servers after the termination of the survey.

Data analysis

The primary outcome of this study was the estimation of the percentage of non-adherent patients defined as patients having answered ‘yes’ to at least one of the four items of the Morisky questionnaire. For binominal variables, a Fisher’s test was applied to calculate differences in distribution between adherent and non-adherent patients. For continuous variables, a Mann–Whitney test was computed. Binary logistic regression analysis was performed to compute a multivariate model including parameters with a significant difference in distribution between adherent and non-adherent patients. Complete case analysis was used. Normal approximation of the binomial distribution was used to derive 95 % confidence intervals. Statistical analysis was performed with ‘R’, version 3.0.2.

Results

A total of 323 participants completed the questionnaire; 178 (55.1 %) were men and 145 (44.9 %) women. Median age was 62 years (25th– 75th percentile: 51–69 years; range: 25–89 years). For more demographic data, see Table 1.

Table 2 Multivariable model investigating association between various variables and non-adherence
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In the overall study population, 109 (33.7 %) participants had a Morisky score of 1 or more and were therefore classified as non-adherent; 56 patients (17.3 %) were classified as intentionally non-adherent. In detail, 84 (26.0 %) participants answered item 1 of the MMAS-4 with yes, 33 (10.2 %) item 2, 40 (12.4 %) item 3 and 33 (10.2 %) participants item 4.

Factors influencing non-adherence

In univariate analysis, young age was associated with non-adherence. The rate of non-adherence was also significantly higher in working patients or students compared with retired or unemployed ones. Conversely, adherent patients were prescribed a higher number of different drugs (p = 0.001), tablets per day (p = 0.008) and had more items on the last prescription (p = 0.028).

Patients classified as adherent had a high score in the perceived necessity section of the Beliefs About Medicine Questionnaire, the attitude, normative beliefs, intention and self efficacy section of the Theory of Planned Behaviour Questionnaire and the perceived illness consequences, illness timeline, personal control, treatment control and illness coherence part of the BIPQ. Satisfaction with the treating practitioner and his practice were significantly higher in adherent patients. In contrast, the use of cost coping strategies and a high score in the perceived barriers section of the BRIGHT questionnaire were associated with non-adherence.

In a multivariable model, older age (odds ratio (OR): 0.94, 95 % confidence interval (CI): 0.89–0.99; p = 0.02) and self-efficacy (i.e. the personal sense of control; TPB); OR: 0.66, 95 % CI: 0.52–0.83; p < 0.001) were associated with adherence, whereas intention (TPB; OR: 1.44, 95 % CI: 1.04–2.16; p = 0.04) and perceived barriers (BRIGHT; OR: 1.11, 95 % CI: 1.02–1.23; p = 0.02) were linked to non-adherence (see Table 2).

Intentional non-adherence

Intentional non-adherence was significantly more frequent in participants reporting regular employment or students than in retired or unemployed (15.0 vs. 33.7 %; p = 0.01). Use of cost coping strategies was associated with intentional non-adherence (Mann–Whitney U: p = 0.048). Scores in the variables attitudes, intention, self-efficacy and normative believes (TPB) and illness timeline and treatment control (BIPQ) were lower in patients classified as intentionally non-adherent. Also, a high score in perceived barriers (BRIGHT) was significantly associated with intentional non-adherence. Due to the small case numbers, multivariable analysis was omitted.

Discussion

Non-adherence to antihypertensive medication was 33.7 % in our patient population. These data therefore demonstrate a clear need for improvement of patient care even in high-income countries, where universal access to healthcare is guaranteed. The observed proportion is considerably higher than for other medical conditions with a more symptomatic disease course including multiple sclerosis or follow-on therapy after acute coronary syndrome [16, 17]. However, other European countries had considerably higher proportions of non-adherence, for example, accounting for up to 70 % of patients in Hungary [18].

In our multivariable analysis, we identified four risk factors significantly influencing the adherence to antihypertensive medication.

Young age was shown to be associated with non-adherence. Although this is a non-modifiable factor, young patients may require specially tailored information or advice to improve adherence. This may be of particular importance because young patients are most likely to benefit from improved adherence to antihypertensive drugs, in that they can decrease the cardiovascular risk of a long-term hypertensive disease.

Among the modifiable risk factors low self-efficacy (TPB), high intention (TPB) and high perceived barriers to medication adherence (BRIGHT) were identified as predictors for non-adherence. Self-efficacy is the personal sense of behavioural control, and its crucial importance in several different settings was shown previously [19–21]. People who believe that they have the ability to behave in the manner necessary to solve a problem become more inclined to do so and feel more committed to their decisions and behaviours [22]. Self efficacy can be influenced by a person’s own experience, the experiences of others, social persuasion and by their psychological status [23]. Also, barriers including perceived or actual side effects of drugs or forgetfulness should be specifically addressed in all patients with hypertension to optimize therapeutic outcomes. This also shows that personal beliefs and social influences are more important for adherence than the clinical situation or factors attributable to the disease itself. Paradoxically, we also found high behavioural intention to be associated to non-adherence. This finding stands in contrast to literature [24], and we speculate that it might be an artefact of statistical analyses, especially because intention was already very high in the overall study population (median 10 out of 10 points).

Our results also show the crucial role of allowing enough time in personal communications between the practitioner and patients to make interventions possible and successful. Such risk factors can be influenced by a range of interventions. Self-efficacy might be increased by programs such as the herz.leben program, which was established in Styria, Austria. This programme provides structured training for patients on several aspects of the treatment and control of the disease (e.g. adequate nutrition, physical exercise, blood measurement training) and was shown to significantly decrease blood pressure and the risk of a cardiovascular event [25].

Limitations of this study included the way of data acquisition possibly leading to a selection bias in the study population. Questionnaires and responses were provided via Internet leading to the impossibility to confirm diagnoses or responses. Importantly, patient groups without Internet access were most likely underrepresented in this survey. The so-called self-serving bias, defined as the distortion of cognition of perception to maintain self-esteem, might have confounded our results, and the impact of non-responders was not assessable during this survey. However, the anonymity of this survey may also be regarded as strength, as responders are less likely to conceal non-adherence compared with personal interviews.

In summary, this study reports a high proportion of non-adherence to antihypertensive medication in Austria, but identifies modifiable variables influencing adherence. This survey may provide important insights for the treatment of arterial hypertension and other chronic conditions. Future studies should evaluate specific interventions to improve adherence to therapeutic regimens. This could help to ameliorate effectiveness and efficiency of existing drugs.

Funding

This work was supported by the European Union’s Seventh Framework Programme FP7/2007–2013 ‘Ascertaining Barriers to Compliance (ABC) project’ under grant agreement number 223477. The work was supported by the Landsteiner Gesellschaft.

Conflict of interest

The authors declare that they have no conflict of interest.