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Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study
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ORIGINAL ARTICLE
Heart, Lung and Circulation (2019) -, -–1443-9506/19/$36.00 https://doi.org/10.1016/j.hlc.2019.11.012
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Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study Adrienne Pacleb, BN a,b,c, Nicole Lowres, PhD b,d, Sue Randall, PhD a, Lis Neubeck, PhD a,e, Robyn Gallagher, PhD a,b,* a
Sydney Nursing School, University of Sydney, Sydney, NSW, Australia Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia c Nepean Hospital, Sydney, NSW, Australia d Heart Research Institute, Sydney, NSW, Australia e School of Health and Social Care, Edinburgh Napier University, Edinburgh, Scotland b
Received 22 May 2019; received in revised form 13 November 2019; accepted 24 November 2019; online published-ahead-of-print xxx
Background
Non-adherence to medications is common in patients with atrial fibrillation (AF), increasing the risk of stroke, co-morbidities, and AF symptoms. Understanding factors influencing medication adherence is important in providing holistic care to patients with AF. This study aimed to explore medication adherence in patients with AF, and explore associations with health literacy, cognition, or AF knowledge.
Methods
A single-centre pilot study, using survey questionnaires and open questions. Patients with a primary cardiac diagnosis, with AF as primary or secondary diagnosis, were eligible for recruitment. During hospitalisation, adherence to cardiac medications was assessed using the Basel Assessment of Adherence to Immunosuppressive Medication Scale (BAASIS). Health literacy, cognition, and AF knowledge were assessed through validated questionnaires. Facilitators and barriers for medication adherence were obtained through open-ended question and coded using a content analysis approach.
Results
Fifty-four (54) patients were recruited (61% male, mean age 71611). Twenty-two (22) participants (41%) were classified as non-adherent using the BAASIS; with a corresponding self-reported adherence of 87.7% in non-adherent participants compared to 97.8% in adherent participants. No associations were identified between medication adherence and cognition, health literacy, or AF knowledge. Facilitators for adherence included external assistance, routines, and medication knowledge, and these were reported by both adherent and non-adherent participants. Non-adherent participants reported more barriers including medication concerns, forgetfulness, and lifestyle factors.
Conclusions
Large numbers of AF patients are likely to be non-adherent to medications. Medication adherence is influenced by multiple factors, individual to each patient. Diverse strategies are required to ensure adherence to cardiac medications.
Keywords
Atrial fibrillation Medication adherence Health literacy Cognition
Background It is estimated that .33.5 million people have atrial fibrillation (AF) worldwide [1]. AF is an important global health
concern because it is associated with a five-fold increased risk of ischaemic stroke, and a two-fold increased risk of allcause mortality and heart failure [1]. The prevalence of AF increases with age: affecting w1% of people ,60 years, rising
*Corresponding author at: Robyn Gallagher, Room 2210, Level 2, Building D17 Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia. Tel.: +61 2 86270279., Email: [email protected] Ó 2019 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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to w30% of people .80 years [2]. Of note, it is predicted that the prevalence of AF in Australia will double by the year 2034, reaching an estimated 600,000 people diagnosed with AF [3]. Atrial fibrillation rarely occurs in isolation, rather the majority of people with AF have at least one additional cardiac-related comorbidity requiring treatment [4,5]. Of the 10,614 AF patients from the Garfield registry, 78% had hypertension, 39% hypercholesterolaemia, 21% heart failure, and 19% coronary artery disease [4]. It is, therefore, important to consider the patients adherence to the entirety of their cardiac medications. However, adherence and persistence to both oral anticoagulants and cardiac medications is known to be poor, with adherence rates of only w50% [6,7]. If adherence to oral anticoagulation is poor, there is an increased risk of death, HF and stroke [8]. Similar adverse outcomes are noted when adherence to hypertension and cardiac medications is poor [9]. It was noted in a systematic review that adherence levels did not differ across individual cardiac medications [9]. Furthermore, it is noted that behaviour in one medication often more broadly reflects medication adherence behaviours across all medications [10]. The majority of research in AF patients has focussed on adherence to oral anticoagulant (OAC) medications, with little focus on compliance to cardiac medications as a whole. Medication adherence is a measure of taking the medication as prescribed, that is, the number of doses taken, timing of doses, and adhering to any other lifestyle or dietary requirements of the medication [11]. The factors impacting medication adherence are complex and comprise multiple factors including health system-related, social/ economic-related, therapy-related, condition-related, and patient-related factors [12]. Patient-level factors are similar for both patients with cardiac disease and for those with AF, including factors such as health literacy, cognition, and health-related knowledge [13,14]. When low health literacy is coupled with poor AF knowledge, this can lead to an underestimation of health risks which means patients do not understand the need to take their medications [15]. Cognitive impairment is an important issue to consider for people with AF in relation to medication adherence; as cognitive decline is 16% greater in AF and the risk of dementia is 23% higher [16]. The pattern of cognitive decline in AF more commonly affects new learning, attention, and executive function, which play an important role in creating flexible routines to support medication taking in daily life [17]. This may affect medication adherence due to difficulties remembering rationales for taking medications, and medication regimes. It is therefore important to understand the impact these patient-related factors may have on the AF patient’s adherence to their cardiac medications. Therefore, this study aimed to explore adherence to cardiac medications in patients with AF; explore the factors and behaviours that may influence adherence; and determine if adherence is associated with cognition, health literacy, AF knowledge, or other socio-demographic factors.
A. Pacleb et al.
Methods This was a pilot study at a single centre using a combination of survey questionnaires and open questions to explore aspects of medication adherence. The study was conducted between July 2016 and June 2017 at the Nepean Hospital, a tertiary hospital in Sydney, Australia. Ethical approval was provided by the Nepean Ethics Committee on June 2016 (Approval Number: 16/28/LNR/16/Nepean/48). The investigation conforms with the principles outlined in the Declaration of Helsinki (Br Med J 1964; ii: 177).
Study Population Participants were recruited from the cardiology ward of the Nepean Hospital, Sydney, Australia. Eligible patients were identified by two investigators (AP and JS), through review of the ward list, in consultation with the cardiology ward nursing staff. Patients were eligible if their primary diagnosis was cardiac, and AF was a primary or secondary diagnosis on admission to hospital, and they had electrocardiograph (ECG) diagnosed AF documented in their medical file; were aged 18 years; and could communicate sufficiently in English. Patients were excluded if they had severe visual or hearing impairment, or a documented diagnosis of dementia. The registered nurse in charge of each patient was consulted regarding the patient’s capacity to provide informed consent and participate in the study. Eligible patients were approached during the inpatient stay and provided with study information. Patients providing written informed consent were recruited.
Assessment Procedure The assessment was completed during the inpatient stay. Sociodemographics and clinical data were collected from the participant and the participant’s medical record using a modified version of a previously designed data collection check-list [5]. The check-list consisted of nine questions including, sex, age, ethnicity, marital status, highest education level achieved, primary reason for hospital admission, co-morbidities, AF frequency, admission date and hospital length of stay. Participants then completed four assessments in the following sequence: medication adherence, AF knowledge, health literacy, and then cognitive function. Medication adherence Medication adherence was assessed using the Basel Assessment of Adherence to Immunosuppressive Medication Scale (BAASIS) [18]. This questionnaire was originally developed and validated to measure medication adherence for immunosuppressive medications [18]. To make the questions relevant to our study population, we modified the questionnaire by substituting the words “heart medications” whenever the questionnaire stated “immunosuppressive medications” (Supplement 1). The questionnaire assessed adherence to cardiac medications through questions about medication behaviour over the prior 4-week period (i.e. prior to hospitalisation).
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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Participants are required to list their cardiac medications prior commencing the questionnaire. Part 1 of BAASIS (questions 1a–4) comprises five yes-no questions which classify a person as ‘adherent’ or ‘non-adherent’. These questions relate to forgetting, omitting and/or delaying medications, dosages and timing. Participants are considered non-adherent if they respond ‘yes’ to any of these questions. Part 2 of the BAASIS (question 5) is a self-rating of medication adherence, using a visual analogue scale from 0–100%. In a sub-sample of 24 participants (recruited consecutively), open-ended questions were asked to elicit qualitative information on the skills and behaviours affecting medication adherence in their home setting to enhance understanding of medication adherence in a way that the BAASIS was unable to elucidate. This open-ended question was based on a study that emphasised the importance of motivational interviewing by health care professionals to identify each patients’ experience, self-management skills and behaviours that may affect their adherence to medications [19]. The starting question “What do you do to help you with your medications?” was asked directly after completing the BAASIS questionnaire on medication adherence. Participant responses were recorded verbatim. Atrial fibrillation knowledge Atrial fibrillation knowledge was assessed using a modified version of the original AF Knowledge Scale which was developed in Holland [20]. Modifications were made with approval from the original authors, and included removal of one question specifically relating to their AF Clinic in Holland, and linguistic modifications for the Australian vernacular. The modified questionnaire was previously tested in Australia [21]. The modified questionnaire consisted of 10 multiple-choice questions covering pathophysiology, causes of AF, medications, physical exercise and general information about AF. Additional information regarding AF knowledge was gained by using two open-ended questions: “Can you tell me a little bit about AF?” and “Can you tell me the symptoms of AF?”. These questions were previously developed and tested in an AF population [21]. Health literacy Health literacy was assessed using the Rapid Estimate of Adult Literacy in Medicine Short Form (REALM-SF) [22]. The REALM-SF is a shortened version of the 66-item REALM. The REALM-SF includes seven-word recognition items, and is administered by the investigator. Participants are allocated one point for each word they are able to state correctly within 5 seconds, with a maximum total score of 7 representing a high level of health literacy. Cognitive function Cognitive function was examined using the Montreal Cognitive Assessment (MoCA) tool which was developed to test for mild cognitive impairment (CI) [23]. The MoCA consists of eight subject areas related to cognitive domains
for visuospatial, naming, memory, attention, language, abstraction, delayed recall and orientation skills. Each section is scored differently and is added to achieve a maximum score of 30. A score 26 is considered normal.
Objectives and Outcomes 1. Describe adherence to cardiac medications for people with AF; 2. Describe facilitators and barriers to medication adherence, by exploring open-ended questions on the patient’s experiences and strategies; and 3. Determine if medication adherence has any associations with socio-demographic factors, health literacy, cognition levels, or AF knowledge.
Statistical Analyses Data were collated and entered into the Statistical Package for the Social Science Version 24.0 (IBM Corp. SPSS Statistics for Windows, Version 24.0, Armonk, NY, USA). Continuous variables were reported as means 6 standard deviations (SD), and categorical variables as numbers and percentages. Statistical significance was set at p,0.05, using two-tailed tests. As this was a pilot study, we did not calculate a sample size, instead we recruited a convenience sample within the allocated timeframe of the study. The classification into ‘adherent’ and ‘non-adherent’ from BAASIS PART 1 (questions 1a–4) was assessed against BAASIS PART 2 (self-rating of adherence) using nonparametric t-tests, and a correlation analysis. ‘Adherent’ and ‘non-adherent’ participants were compared for all variables using independent t-test continuous variables, and Pearson’s chi-square test for discrete or dichotomous data. Associations between medication adherence and sociodemographic variables (including health literacy, cognition, AF knowledge, age, and years of education) were assessed in a correlation analysis using a two-tailed Spearman correlation co-efficient. A binomial logistic regression was performed using medication adherence as the dichotomous dependent variable and independent variables of cognition, AF knowledge and health literacy. Qualitative data from the open questions on medication adherence were independently reviewed and coded using a content analysis approach, by two independent investigators (AP and RG). An iterative process was used to identify highlevel categories, which were barriers and facilitators. Within these categories sub-categories were identified. Discrepancies were discussed and reviewed until consensus was reached. A third investigator (SR) reviewed and validated the categories and codes.
Results During the study-period 89 patients were approached, and 54 consented to participate (Figure 1). Participant age ranged from 41–89 years (mean 71611 years), and 61% were male
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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Table 1 Participant Characteristics (n=54). Participant Characteristics
Mean 6 SD
Age
70.8 6 11.1
Sex (male)
n (%)
33 (61)
Ethnicity Caucasian
50 (93)
Other Education Years
print & web 4C=FPO
379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443
A. Pacleb et al.
4 (7) 10.7 6 2.9
,12 years formal education
41 (76)
12 years formal education
13 (24)
Hospital length of stay Days
5.5 6 5.6
Primary admission diagnosis 21 (39) 7 (13)
AF Chest pain
Figure 1 Study flow.
Chronic cardiac failure
6 (11)
MI, syncope, non-STEMI,
7 (13)
22nd AV block
3 (6)
Surgery
(Table 1). The primary admission diagnosis for hospitalisation was AF in 39% of participants. The majority of participants (75.9%) had #12 years of formal education. Overall, participants had a high level of health literacy: 70.4% scored 7/7 on the REALM-SF, with the mean score 6.461.2. The majority of participants (70.4%) were classified with either mild to severe level cognitive impairment: the ‘delayed recall’ and ‘attention’ domains were the areas most affected. The overall level of AF knowledge measured by the AF knowledge questionnaire was moderate (mean 5.662.7), similar to results from other Australian studies.[21] The main questions answered incorrectly were: “Atrial fibrillation is relatively harmless if the right medication is taken (true/ false)”; “Why is it important to take my medication for atrial fibrillation the correct way?”; and “Atrial fibrillation is a rare condition (true/false)”. Participants were taking a mean of 2.261.0 (range 1–5) cardiac-related medications. Medications related to AF are outlined in Table 2. Only 54% of this AF population were prescribed oral-anticoagulants, and 35% were prescribed anti-platelet therapy (Table 2).
11 (20)
Other Co-morbidities Hypertension Type 2 diabetes mellitus
34 (63) 21 (39)
Hypercholesterolaemia
9 (17)
Chronic kidney disease
6 (11)
Cognitive impairment* Normal ( 26)
16 (29)
Mild (18 – 25)
29 (54)
Moderate (10 – 17)
8 (15)
Severe (0 – 9) Health literacy Score#
1 (2) 6.4 6 1.2
Category#
38 (70)
High school [score = 7]
14 (26)
7th – 8th grade (score = 4 – 6)
2 (4)
3rd – 6th grade (score = 0 – 3)
AF Knowledgeb Total score
5.6 6 2.7
Abbreviations: Non-STEMI, Non-ST Elevation Myocardial Infarction; AV,
Medication Adherence Twenty-two (22) participants (41%) were classified as ‘nonadherent’ to their medications according to the BAASIS Part 1 (questions 1a–4) (Table 3). Incorrect timing of medication intake and missed dosages were the most common issues causing non-adherence. The mean self-reported medication adherence identified through BAASIS Part 2 (question 5) was high at 94613% (range 40–100%). ‘Non-adherent’ participants had lower mean adherence (87.7%) compared to ‘adherent’ participants (97.8%) p=0.016. Bivariate correlations also identified a significant correlation between medication adherence classification (BASSIS Part 1) and self-reported medication adherence (BAASIS Part 2) (0.459, p,0.001).
Atrioventricular; COPD, Chronic Obstructive Pulmonary Disease; AF, Atrial Fibrillation. *Montreal Cognitive Assessment [Score range 0-30; #25 indicates cognitive impairment]. #
Rapid Estimate of Adult Literacy in Medicine Short Form [0= lowest
literacy; 7= highest literacy]. b
Modified Atrial Fibrillation Knowledge score [0= poor knowledge; 10=
highest knowledge].
Analysis of associations There were no associations or independent predictors identified between adherence to cardiac medications and the variables of cognition, health literacy, or AF knowledge
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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(Table 4). Both adherent and non-adherent participants reported utilisation of assistance, stating it played an important role to ensure proper medication intake. Barriers were more likely to be reported by non-adherent participants: only one adherent participant reported a barrier. Barriers included medication concerns, forgetfulness, and lifestyle difficulties preventing the establishment of a routine (Table 4). Medication concerns were the most common barrier, and were reported by a third of participants, who were mainly non-adherent. Concerns included medication changes (either type, dose, name, or schedule), multiple prescriptions, side effects, and unfamiliarity with medication purpose. Difficult and unpredictable work routines were often reported as a cause of non-adherence despite these participants being generally younger, and aware of the specific risks related to medication non-adherence.
Table 2 Atrial fibrillation medications. Medication
n (%)
Anti-coagulants Warfarin
14 (25.9)
Novel oral anti-coagulants
15 (27.8)
Anti-platelet Aspirin Clopidogrel
16 (29.6) 3 (5.6)
Anti-hypertensives Beta blockers
34 (63.0)
Angiotensin receptor blocker
9 (16.7)
Calcium channel blocker
7 (13.0)
Angiotensin converting enzyme
4 (7.4)
inhibitors
2 (3.7)
a1 blocker Other anti-arrhythmic/rate control Digoxin
Discussion
10 (18.5)
Amiodarone
3 (5.6)
Flecainide
1 (1.9)
Slow-K
1 (1.9)
when assessed through either binomial logistic regression, or bivariate correlations (Supplement 2). Analysis of sociodemographic characteristics and clinical data identified no differences on the basis of whether participants were adherent or non-adherent to medications (Supplement 2). The bivariate correlation did identify statistically significant associations between increasing age and decreasing cognition (0.413, p=0.002); years of education and health literacy (0.359, p=0.008); AF knowledge and health literacy (0.463, p,0.001); AF knowledge and cognition (0.534, p,0.001); and health literacy and cognition (0.358, p=0.008). Barriers and Facilitators for Medication Adherence The major facilitators arising from the analysis were assistance, establishment of a routine, and medication knowledge
Our study identified that 41% of participants with AF were non-adherent to their cardiac medications, with a mean selfreported adherence rate of 87.7%. Our results highlight the complex nature of medication adherence in this population. We did not find any associations between medication adherence levels and cognition, health literacy, or AF knowledge. However, we identified many facilitators to increase medication adherence, which were often used by participants with cognitive impairment. In general, facilitators were reported by both adherent and non-adherent participants, and included aids and assistance (pre-packaged medications, direct family help, routines), and good medication awareness and understanding. Our study also identified that busy unpredictable work schedules can be a barrier to adherence, and therefore younger patients may be less adherent to medications compared to elderly patients who have no or less work obligations. Our study focussed on adherence to overall cardiac medications and did not specifically assess adherence to OACs, unlike the majority of other studies on medication adherence in AF. Oral anticoagulant adherence is a widespread problem
Table 3 Medication Adherence classification. The Basel Assessment of Adherence to Immunosuppressive Medication Scale PART 1 (questions 1a – 4)
Non-adherent (n=22)
Adherent (n=32)
Took medication more than 2 hours
18
0
before or after allocated time (n) Missed a dose at least once (n)
11
0
Skipped two or more doses (n)
6
0
Altered prescribed amount (n) Stopped medication within the last year (n)
4 2
0 0
PART 2 (question 5)
Non-adherent (n=22)
Adherent (n=32)
Overall (n=54)
Self-reported adherence % (mean 6 SD)
87.7 6 17.8
97.8 6 5.4
93.7 6 12.9
Abbreviation: SD, standard deviation.
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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Table 4 Facilitators and Barriers for medication adherence (n=24). FACILITATORS
Adherent (n=13)
Non-adherent (n=10)
Assistance
11
9
(Consists of aid coming from family, pre-packaged medications, such as Webster packs, pill boxes or own medication containers) “I keep my medication in a little box and I sort them out before I drink them. Sister reminds me to take my medication sometimes...I know why I need to take my medications...it is a routine” [74 year-old male] “I keep medications in an ice cream tub and I write down what I take” [57 year-old male] “Husband helps me take medications when I’m sick or he reminds me to take medications” [47 year-old female] 9
Routine
4
(Included medication intake as part of their daily activity and became a habit) “I keep my medication in a plastic container near the bench where I make breakfast so I won’t forget” [75 year-old female] “I always place it near the kettle so when I’m making coffee or tea in the morning, medications won’t be forgotten” [58 year-old female] “I put an alarm on the clock to take my medications” [47 year-old female] Medication knowledge (Have knowledge about their medications, such as side effects, and knows the risks
6
4
and consequences of non-adherence) “I’m aware of the consequences of not taking my medication...I remember that I ended up in a coma and I don’t want that to happen again” [75 year-old female] “I learnt from my parents’ situation” [47 year-old female] “I was a nurse before so I know why medications should be taken the right way” [86 year-old female] BARRIERS
Adherent (n=1)
Non-adherent (n=8)
Medication concerns
1
7
(Change in medication such as doses or names, assistance or routine; multiple medications or different dosage times; unfamiliar with medications’ purpose and reasons for taking; side effects) “Have not taken medications in the past, I have neglected myself...change of name of medications to generic names” [65-year old male] “Difficult when medications are on different times... Doctor didn’t advice the specific time to drink medications for example, 1 table in either morning or afternoon” [79 year-old male] “Wife used to help but when she has her own medications, she doesn’t help anymore” [81 year-old male] “I stopped taking apixaban because I thought I was well and nothing was wrong with me, I still think that there is nothing wrong with me because I don’t feel anything bad, I always through I was healthy” [56 year-old male] 0 4 Forgetfulness (Lack in remembering to take a dose/s) “Occasionally forgets especially when there is a routine change for example, when eating out I don’t bring medications” [71 year-old male] “I leave medication for today’s dose until the next day if forgotten” [84-year old male] Worried about warfarin the most, when I miss a dose of warfarin, I take an extra dose plus in addition to prescribed warfarin” [79 year-old male] 0
Difficult routine lifestyle
3
(Inability to take medications due to distractions or other activities and commitments, such as work) “I miss my medication because of working long days and sometimes due to my health condition that makes me too tired or sick...drink medications varied time depending on what time I wake up” [75 year-old female] “I drink medications at different times because of hard schedule, I drop off my daughter to work...when going out and busy, I do not take my medications” [57 year-old male]
and varies globally, with reported OAC persistence rates of 43% after 24 months in China; persistence rates of 70% after 18 months in Scotland; 48% completed prescription refills over 12 months in the United States; and 54.9% reporting high levels of adherence in Australia [13]. Our results were similar, as they showed 59% were adherent to their cardiac medications. So, it is likely that medication adherence in AF patients is not
limited to factors directly related to OACs such as fear of bleeding, and that overall medication adherence results from a combination of factors beyond patient-level factors, such as health system-related factors. In contrast to our results, which focussed on cardiac medications, recent research has demonstrated that OAC adherence is associated with level of OAC knowledge, and
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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also with health literacy [24]. An online survey in Australia has also shown that additional factors influence OAC adherence including age, gender, medication cost, and ‘information overload’ [25]. Research in China has also identified that higher levels of AF knowledge and a belief in the importance of medications are associated with increased warfarin adherence; and non-adherence was generated from strong negative beliefs and fear of medications, primarily because of the perceived adverse effects of warfarin [26]. However, it is possible to overcome the barrier regarding fear of bleeding, as a systematic review has shown that when patients are educated correctly, the majority of patients are willing to accept an increase in bleeding risk in order to reduce their risk of having a stroke [27]. Of interest, patients taking warfarin have been shown to have higher levels of knowledge of overall OAC medications than those taking non-vitamin K antagonist oral anticoagulants (NOACs) [28], and in a European survey it was found that people have less knowledge about NOAC medications than warfarin, especially in relation to bleeding risk and need for regular international normalised ratio (INR) testing [29], Despite this persistence in newly diagnosed AF patients is shown to be higher at one year for those taking NOACs (dabigatran) compared to those taking warfarin [30]. There are many modifiable barriers affecting adherence to cardiac medications, including concerns about medications and their side effects, forgetfulness, difficulty getting repeat prescriptions, and difficulty opening the medication packaging [14]. Furthermore, it is suggested younger people may be less adherent due to barriers caused by the demand of their busy social activities and work commitments [26,31]. These barriers are in line with our findings, and may indicate a need for development of specific interventions tailored to a younger population. The time commitment of an intervention or medication regime also affects the likely compliance with the regime: medication adherence reduces as the number of daily doses increases [31]. Furthermore, patients have reported they have a preference for less complicated medication regimes, including single doses per day [27]. Practical implications for health professionals Health professionals have a pivotal role in assessing and maximising medication adherence in their patients. The new Australian guidelines for management of AF advocate for patient centred care and decision making, and also implementation of individualised strategies to increase medication adherence [32]. The guidelines also recommend structured follow-up for patients on medicinal treatment, to provide continuous education, support, and assessment of selfmanagement [32]. Regular follow-up allows for early identification of any adverse medication effects, and early identification of adherence or non-persistence issues [32]. To achieve this, it is important to assess each patient to identify their understanding, cognition, their personal barriers, and the facilitators and assistance that is available to them. Where appropriate, family should also be involved in the development of strategies to improve adherence, as
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family and caregivers have been shown to significantly improve adherence in patients with cardiac disease [33]. Discussions with family can provide valuable insight into the patient’s current methods to manage medications, identification of difficulties or challenges, beliefs and medication concerns, and suitability of alternative strategies and assistance (e.g. Webster packs, pillboxes, reminders). Identification and establishment of appropriate routines, systems and structures is important, and these interventions are demonstrated to improve adherence [34]. However they may not be effective if there are underlying knowledge deficits or beliefs that medications have negative side-effects. As cognitive impairment is common in patients with AF [35], education and intervention strategies may need to be altered to accommodate the patient’s cognitive deficit. The timing, delivery and choice of education materials is important, to ensure the information is understood and knowledge is retained. Educating the patient with use of decision aids has been shown to improve knowledge and acceptance of treatment and medications in other chronic disease groups such as diabetes, leading to increased compliance with treatment [36]. Decision aids could be considered as a method to assist education of patients with AF, but it is integral that the patient perspective is taken into consideration during this process [37]. Limitations This was a pilot study at a single centre. As the sample size was 54 participants, it is possible that statistically significant differences were unable to be detected. Some participants may have been newly diagnosed with AF on admission to hospital, and it is possible that this may reflect in lower AF knowledge scores. Thus, this limits the generalisability of the results to wider populations, and the results should be considered as hypothesis generating only. Furthermore, as the BAASIS questionnaire is a self-report instrument requiring patient recall for the previous 4 weeks period, recall bias may affect the results for medication adherence, and accurate measurement of medication adherence with questionnaires is known to be a problem due to the complex nature of medication adherence [38]. This study highlights the issue of poor medication adherence in AF patients which has been identified in previous research, however the extent of the underlying factors impacting medication adherence in AF patients remain undetermined. It is important to holistically understand the issues impacting poor adherence to cardiac medications in patients with AF. To achieve this, large multi-centre studies are warranted to also investigate the broader factors of adherence in addition to the patient-related factors. These factors should include health service factors such as the provision of systematic teaching (what is taught and how well); what strategies are implemented for patients; is cognitive impairment assessed and what provisions are made to account for cognitive impairment. Future studies should assess adherence in hospital and then at regular intervals after discharge, to also determine the time-course of
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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adherence. It is also recommended to continue to use open questions to supplement the data obtained through the standard adherence questionnaires.
Conclusion Many patients with AF are non-adherent to their medications. Medication adherence is a complex issue influenced by multiple factors that determine each patient’s capability to adhere to cardiac medications accurately. This study highlights the importance for health professionals to assess facilitators and barriers on an individual basis, assessing knowledge and correcting misperceptions. Treatment plans should be tailored in order to optimise medication adherence including strategies to create routines and prompt patients to take their medications, with regular follow-up appointments, and consideration of all cardiac medications and not solely OACs. Future large-scale research is warranted to identify the holistic multi-factorial issues impacting poor adherence to cardiac medications in patients with AF.
A. Pacleb et al.
[5]
[6]
[7]
[8]
[9]
[10] [11]
[12]
[13]
Declaration of Conflicting Interests The authors declare no conflict of interests.
[14]
Funding
[15]
N Lowres is funded by a NSW Health Early Career Fellowship (H16/ 52168). This research received no financial support for the research, authorship, and/or publication of this article
[16]
Acknowledgments Q3
Nil.
[17]
Appendices. Supplementary Data
[18]
Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j. hlc.2019.11.012.
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ORIGINAL ARTICLE
Heart, Lung and Circulation (2019) -, -–1443-9506/19/$36.00 https://doi.org/10.1016/j.hlc.2019.11.012
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Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study Adrienne Pacleb, BN a,b,c, Nicole Lowres, PhD b,d, Sue Randall, PhD a, Lis Neubeck, PhD a,e, Robyn Gallagher, PhD a,b,* a
Sydney Nursing School, University of Sydney, Sydney, NSW, Australia Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia c Nepean Hospital, Sydney, NSW, Australia d Heart Research Institute, Sydney, NSW, Australia e School of Health and Social Care, Edinburgh Napier University, Edinburgh, Scotland b
Received 22 May 2019; received in revised form 13 November 2019; accepted 24 November 2019; online published-ahead-of-print xxx
Background
Non-adherence to medications is common in patients with atrial fibrillation (AF), increasing the risk of stroke, co-morbidities, and AF symptoms. Understanding factors influencing medication adherence is important in providing holistic care to patients with AF. This study aimed to explore medication adherence in patients with AF, and explore associations with health literacy, cognition, or AF knowledge.
Methods
A single-centre pilot study, using survey questionnaires and open questions. Patients with a primary cardiac diagnosis, with AF as primary or secondary diagnosis, were eligible for recruitment. During hospitalisation, adherence to cardiac medications was assessed using the Basel Assessment of Adherence to Immunosuppressive Medication Scale (BAASIS). Health literacy, cognition, and AF knowledge were assessed through validated questionnaires. Facilitators and barriers for medication adherence were obtained through open-ended question and coded using a content analysis approach.
Results
Fifty-four (54) patients were recruited (61% male, mean age 71611). Twenty-two (22) participants (41%) were classified as non-adherent using the BAASIS; with a corresponding self-reported adherence of 87.7% in non-adherent participants compared to 97.8% in adherent participants. No associations were identified between medication adherence and cognition, health literacy, or AF knowledge. Facilitators for adherence included external assistance, routines, and medication knowledge, and these were reported by both adherent and non-adherent participants. Non-adherent participants reported more barriers including medication concerns, forgetfulness, and lifestyle factors.
Conclusions
Large numbers of AF patients are likely to be non-adherent to medications. Medication adherence is influenced by multiple factors, individual to each patient. Diverse strategies are required to ensure adherence to cardiac medications.
Keywords
Atrial fibrillation Medication adherence Health literacy Cognition
Background It is estimated that .33.5 million people have atrial fibrillation (AF) worldwide [1]. AF is an important global health
concern because it is associated with a five-fold increased risk of ischaemic stroke, and a two-fold increased risk of allcause mortality and heart failure [1]. The prevalence of AF increases with age: affecting w1% of people ,60 years, rising
*Corresponding author at: Robyn Gallagher, Room 2210, Level 2, Building D17 Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia. Tel.: +61 2 86270279., Email: [email protected] Ó 2019 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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to w30% of people .80 years [2]. Of note, it is predicted that the prevalence of AF in Australia will double by the year 2034, reaching an estimated 600,000 people diagnosed with AF [3]. Atrial fibrillation rarely occurs in isolation, rather the majority of people with AF have at least one additional cardiac-related comorbidity requiring treatment [4,5]. Of the 10,614 AF patients from the Garfield registry, 78% had hypertension, 39% hypercholesterolaemia, 21% heart failure, and 19% coronary artery disease [4]. It is, therefore, important to consider the patients adherence to the entirety of their cardiac medications. However, adherence and persistence to both oral anticoagulants and cardiac medications is known to be poor, with adherence rates of only w50% [6,7]. If adherence to oral anticoagulation is poor, there is an increased risk of death, HF and stroke [8]. Similar adverse outcomes are noted when adherence to hypertension and cardiac medications is poor [9]. It was noted in a systematic review that adherence levels did not differ across individual cardiac medications [9]. Furthermore, it is noted that behaviour in one medication often more broadly reflects medication adherence behaviours across all medications [10]. The majority of research in AF patients has focussed on adherence to oral anticoagulant (OAC) medications, with little focus on compliance to cardiac medications as a whole. Medication adherence is a measure of taking the medication as prescribed, that is, the number of doses taken, timing of doses, and adhering to any other lifestyle or dietary requirements of the medication [11]. The factors impacting medication adherence are complex and comprise multiple factors including health system-related, social/ economic-related, therapy-related, condition-related, and patient-related factors [12]. Patient-level factors are similar for both patients with cardiac disease and for those with AF, including factors such as health literacy, cognition, and health-related knowledge [13,14]. When low health literacy is coupled with poor AF knowledge, this can lead to an underestimation of health risks which means patients do not understand the need to take their medications [15]. Cognitive impairment is an important issue to consider for people with AF in relation to medication adherence; as cognitive decline is 16% greater in AF and the risk of dementia is 23% higher [16]. The pattern of cognitive decline in AF more commonly affects new learning, attention, and executive function, which play an important role in creating flexible routines to support medication taking in daily life [17]. This may affect medication adherence due to difficulties remembering rationales for taking medications, and medication regimes. It is therefore important to understand the impact these patient-related factors may have on the AF patient’s adherence to their cardiac medications. Therefore, this study aimed to explore adherence to cardiac medications in patients with AF; explore the factors and behaviours that may influence adherence; and determine if adherence is associated with cognition, health literacy, AF knowledge, or other socio-demographic factors.
A. Pacleb et al.
Methods This was a pilot study at a single centre using a combination of survey questionnaires and open questions to explore aspects of medication adherence. The study was conducted between July 2016 and June 2017 at the Nepean Hospital, a tertiary hospital in Sydney, Australia. Ethical approval was provided by the Nepean Ethics Committee on June 2016 (Approval Number: 16/28/LNR/16/Nepean/48). The investigation conforms with the principles outlined in the Declaration of Helsinki (Br Med J 1964; ii: 177).
Study Population Participants were recruited from the cardiology ward of the Nepean Hospital, Sydney, Australia. Eligible patients were identified by two investigators (AP and JS), through review of the ward list, in consultation with the cardiology ward nursing staff. Patients were eligible if their primary diagnosis was cardiac, and AF was a primary or secondary diagnosis on admission to hospital, and they had electrocardiograph (ECG) diagnosed AF documented in their medical file; were aged 18 years; and could communicate sufficiently in English. Patients were excluded if they had severe visual or hearing impairment, or a documented diagnosis of dementia. The registered nurse in charge of each patient was consulted regarding the patient’s capacity to provide informed consent and participate in the study. Eligible patients were approached during the inpatient stay and provided with study information. Patients providing written informed consent were recruited.
Assessment Procedure The assessment was completed during the inpatient stay. Sociodemographics and clinical data were collected from the participant and the participant’s medical record using a modified version of a previously designed data collection check-list [5]. The check-list consisted of nine questions including, sex, age, ethnicity, marital status, highest education level achieved, primary reason for hospital admission, co-morbidities, AF frequency, admission date and hospital length of stay. Participants then completed four assessments in the following sequence: medication adherence, AF knowledge, health literacy, and then cognitive function. Medication adherence Medication adherence was assessed using the Basel Assessment of Adherence to Immunosuppressive Medication Scale (BAASIS) [18]. This questionnaire was originally developed and validated to measure medication adherence for immunosuppressive medications [18]. To make the questions relevant to our study population, we modified the questionnaire by substituting the words “heart medications” whenever the questionnaire stated “immunosuppressive medications” (Supplement 1). The questionnaire assessed adherence to cardiac medications through questions about medication behaviour over the prior 4-week period (i.e. prior to hospitalisation).
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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Participants are required to list their cardiac medications prior commencing the questionnaire. Part 1 of BAASIS (questions 1a–4) comprises five yes-no questions which classify a person as ‘adherent’ or ‘non-adherent’. These questions relate to forgetting, omitting and/or delaying medications, dosages and timing. Participants are considered non-adherent if they respond ‘yes’ to any of these questions. Part 2 of the BAASIS (question 5) is a self-rating of medication adherence, using a visual analogue scale from 0–100%. In a sub-sample of 24 participants (recruited consecutively), open-ended questions were asked to elicit qualitative information on the skills and behaviours affecting medication adherence in their home setting to enhance understanding of medication adherence in a way that the BAASIS was unable to elucidate. This open-ended question was based on a study that emphasised the importance of motivational interviewing by health care professionals to identify each patients’ experience, self-management skills and behaviours that may affect their adherence to medications [19]. The starting question “What do you do to help you with your medications?” was asked directly after completing the BAASIS questionnaire on medication adherence. Participant responses were recorded verbatim. Atrial fibrillation knowledge Atrial fibrillation knowledge was assessed using a modified version of the original AF Knowledge Scale which was developed in Holland [20]. Modifications were made with approval from the original authors, and included removal of one question specifically relating to their AF Clinic in Holland, and linguistic modifications for the Australian vernacular. The modified questionnaire was previously tested in Australia [21]. The modified questionnaire consisted of 10 multiple-choice questions covering pathophysiology, causes of AF, medications, physical exercise and general information about AF. Additional information regarding AF knowledge was gained by using two open-ended questions: “Can you tell me a little bit about AF?” and “Can you tell me the symptoms of AF?”. These questions were previously developed and tested in an AF population [21]. Health literacy Health literacy was assessed using the Rapid Estimate of Adult Literacy in Medicine Short Form (REALM-SF) [22]. The REALM-SF is a shortened version of the 66-item REALM. The REALM-SF includes seven-word recognition items, and is administered by the investigator. Participants are allocated one point for each word they are able to state correctly within 5 seconds, with a maximum total score of 7 representing a high level of health literacy. Cognitive function Cognitive function was examined using the Montreal Cognitive Assessment (MoCA) tool which was developed to test for mild cognitive impairment (CI) [23]. The MoCA consists of eight subject areas related to cognitive domains
for visuospatial, naming, memory, attention, language, abstraction, delayed recall and orientation skills. Each section is scored differently and is added to achieve a maximum score of 30. A score 26 is considered normal.
Objectives and Outcomes 1. Describe adherence to cardiac medications for people with AF; 2. Describe facilitators and barriers to medication adherence, by exploring open-ended questions on the patient’s experiences and strategies; and 3. Determine if medication adherence has any associations with socio-demographic factors, health literacy, cognition levels, or AF knowledge.
Statistical Analyses Data were collated and entered into the Statistical Package for the Social Science Version 24.0 (IBM Corp. SPSS Statistics for Windows, Version 24.0, Armonk, NY, USA). Continuous variables were reported as means 6 standard deviations (SD), and categorical variables as numbers and percentages. Statistical significance was set at p,0.05, using two-tailed tests. As this was a pilot study, we did not calculate a sample size, instead we recruited a convenience sample within the allocated timeframe of the study. The classification into ‘adherent’ and ‘non-adherent’ from BAASIS PART 1 (questions 1a–4) was assessed against BAASIS PART 2 (self-rating of adherence) using nonparametric t-tests, and a correlation analysis. ‘Adherent’ and ‘non-adherent’ participants were compared for all variables using independent t-test continuous variables, and Pearson’s chi-square test for discrete or dichotomous data. Associations between medication adherence and sociodemographic variables (including health literacy, cognition, AF knowledge, age, and years of education) were assessed in a correlation analysis using a two-tailed Spearman correlation co-efficient. A binomial logistic regression was performed using medication adherence as the dichotomous dependent variable and independent variables of cognition, AF knowledge and health literacy. Qualitative data from the open questions on medication adherence were independently reviewed and coded using a content analysis approach, by two independent investigators (AP and RG). An iterative process was used to identify highlevel categories, which were barriers and facilitators. Within these categories sub-categories were identified. Discrepancies were discussed and reviewed until consensus was reached. A third investigator (SR) reviewed and validated the categories and codes.
Results During the study-period 89 patients were approached, and 54 consented to participate (Figure 1). Participant age ranged from 41–89 years (mean 71611 years), and 61% were male
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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Table 1 Participant Characteristics (n=54). Participant Characteristics
Mean 6 SD
Age
70.8 6 11.1
Sex (male)
n (%)
33 (61)
Ethnicity Caucasian
50 (93)
Other Education Years
print & web 4C=FPO
379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443
A. Pacleb et al.
4 (7) 10.7 6 2.9
,12 years formal education
41 (76)
12 years formal education
13 (24)
Hospital length of stay Days
5.5 6 5.6
Primary admission diagnosis 21 (39) 7 (13)
AF Chest pain
Figure 1 Study flow.
Chronic cardiac failure
6 (11)
MI, syncope, non-STEMI,
7 (13)
22nd AV block
3 (6)
Surgery
(Table 1). The primary admission diagnosis for hospitalisation was AF in 39% of participants. The majority of participants (75.9%) had #12 years of formal education. Overall, participants had a high level of health literacy: 70.4% scored 7/7 on the REALM-SF, with the mean score 6.461.2. The majority of participants (70.4%) were classified with either mild to severe level cognitive impairment: the ‘delayed recall’ and ‘attention’ domains were the areas most affected. The overall level of AF knowledge measured by the AF knowledge questionnaire was moderate (mean 5.662.7), similar to results from other Australian studies.[21] The main questions answered incorrectly were: “Atrial fibrillation is relatively harmless if the right medication is taken (true/ false)”; “Why is it important to take my medication for atrial fibrillation the correct way?”; and “Atrial fibrillation is a rare condition (true/false)”. Participants were taking a mean of 2.261.0 (range 1–5) cardiac-related medications. Medications related to AF are outlined in Table 2. Only 54% of this AF population were prescribed oral-anticoagulants, and 35% were prescribed anti-platelet therapy (Table 2).
11 (20)
Other Co-morbidities Hypertension Type 2 diabetes mellitus
34 (63) 21 (39)
Hypercholesterolaemia
9 (17)
Chronic kidney disease
6 (11)
Cognitive impairment* Normal ( 26)
16 (29)
Mild (18 – 25)
29 (54)
Moderate (10 – 17)
8 (15)
Severe (0 – 9) Health literacy Score#
1 (2) 6.4 6 1.2
Category#
38 (70)
High school [score = 7]
14 (26)
7th – 8th grade (score = 4 – 6)
2 (4)
3rd – 6th grade (score = 0 – 3)
AF Knowledgeb Total score
5.6 6 2.7
Abbreviations: Non-STEMI, Non-ST Elevation Myocardial Infarction; AV,
Medication Adherence Twenty-two (22) participants (41%) were classified as ‘nonadherent’ to their medications according to the BAASIS Part 1 (questions 1a–4) (Table 3). Incorrect timing of medication intake and missed dosages were the most common issues causing non-adherence. The mean self-reported medication adherence identified through BAASIS Part 2 (question 5) was high at 94613% (range 40–100%). ‘Non-adherent’ participants had lower mean adherence (87.7%) compared to ‘adherent’ participants (97.8%) p=0.016. Bivariate correlations also identified a significant correlation between medication adherence classification (BASSIS Part 1) and self-reported medication adherence (BAASIS Part 2) (0.459, p,0.001).
Atrioventricular; COPD, Chronic Obstructive Pulmonary Disease; AF, Atrial Fibrillation. *Montreal Cognitive Assessment [Score range 0-30; #25 indicates cognitive impairment]. #
Rapid Estimate of Adult Literacy in Medicine Short Form [0= lowest
literacy; 7= highest literacy]. b
Modified Atrial Fibrillation Knowledge score [0= poor knowledge; 10=
highest knowledge].
Analysis of associations There were no associations or independent predictors identified between adherence to cardiac medications and the variables of cognition, health literacy, or AF knowledge
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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(Table 4). Both adherent and non-adherent participants reported utilisation of assistance, stating it played an important role to ensure proper medication intake. Barriers were more likely to be reported by non-adherent participants: only one adherent participant reported a barrier. Barriers included medication concerns, forgetfulness, and lifestyle difficulties preventing the establishment of a routine (Table 4). Medication concerns were the most common barrier, and were reported by a third of participants, who were mainly non-adherent. Concerns included medication changes (either type, dose, name, or schedule), multiple prescriptions, side effects, and unfamiliarity with medication purpose. Difficult and unpredictable work routines were often reported as a cause of non-adherence despite these participants being generally younger, and aware of the specific risks related to medication non-adherence.
Table 2 Atrial fibrillation medications. Medication
n (%)
Anti-coagulants Warfarin
14 (25.9)
Novel oral anti-coagulants
15 (27.8)
Anti-platelet Aspirin Clopidogrel
16 (29.6) 3 (5.6)
Anti-hypertensives Beta blockers
34 (63.0)
Angiotensin receptor blocker
9 (16.7)
Calcium channel blocker
7 (13.0)
Angiotensin converting enzyme
4 (7.4)
inhibitors
2 (3.7)
a1 blocker Other anti-arrhythmic/rate control Digoxin
Discussion
10 (18.5)
Amiodarone
3 (5.6)
Flecainide
1 (1.9)
Slow-K
1 (1.9)
when assessed through either binomial logistic regression, or bivariate correlations (Supplement 2). Analysis of sociodemographic characteristics and clinical data identified no differences on the basis of whether participants were adherent or non-adherent to medications (Supplement 2). The bivariate correlation did identify statistically significant associations between increasing age and decreasing cognition (0.413, p=0.002); years of education and health literacy (0.359, p=0.008); AF knowledge and health literacy (0.463, p,0.001); AF knowledge and cognition (0.534, p,0.001); and health literacy and cognition (0.358, p=0.008). Barriers and Facilitators for Medication Adherence The major facilitators arising from the analysis were assistance, establishment of a routine, and medication knowledge
Our study identified that 41% of participants with AF were non-adherent to their cardiac medications, with a mean selfreported adherence rate of 87.7%. Our results highlight the complex nature of medication adherence in this population. We did not find any associations between medication adherence levels and cognition, health literacy, or AF knowledge. However, we identified many facilitators to increase medication adherence, which were often used by participants with cognitive impairment. In general, facilitators were reported by both adherent and non-adherent participants, and included aids and assistance (pre-packaged medications, direct family help, routines), and good medication awareness and understanding. Our study also identified that busy unpredictable work schedules can be a barrier to adherence, and therefore younger patients may be less adherent to medications compared to elderly patients who have no or less work obligations. Our study focussed on adherence to overall cardiac medications and did not specifically assess adherence to OACs, unlike the majority of other studies on medication adherence in AF. Oral anticoagulant adherence is a widespread problem
Table 3 Medication Adherence classification. The Basel Assessment of Adherence to Immunosuppressive Medication Scale PART 1 (questions 1a – 4)
Non-adherent (n=22)
Adherent (n=32)
Took medication more than 2 hours
18
0
before or after allocated time (n) Missed a dose at least once (n)
11
0
Skipped two or more doses (n)
6
0
Altered prescribed amount (n) Stopped medication within the last year (n)
4 2
0 0
PART 2 (question 5)
Non-adherent (n=22)
Adherent (n=32)
Overall (n=54)
Self-reported adherence % (mean 6 SD)
87.7 6 17.8
97.8 6 5.4
93.7 6 12.9
Abbreviation: SD, standard deviation.
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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A. Pacleb et al.
Table 4 Facilitators and Barriers for medication adherence (n=24). FACILITATORS
Adherent (n=13)
Non-adherent (n=10)
Assistance
11
9
(Consists of aid coming from family, pre-packaged medications, such as Webster packs, pill boxes or own medication containers) “I keep my medication in a little box and I sort them out before I drink them. Sister reminds me to take my medication sometimes...I know why I need to take my medications...it is a routine” [74 year-old male] “I keep medications in an ice cream tub and I write down what I take” [57 year-old male] “Husband helps me take medications when I’m sick or he reminds me to take medications” [47 year-old female] 9
Routine
4
(Included medication intake as part of their daily activity and became a habit) “I keep my medication in a plastic container near the bench where I make breakfast so I won’t forget” [75 year-old female] “I always place it near the kettle so when I’m making coffee or tea in the morning, medications won’t be forgotten” [58 year-old female] “I put an alarm on the clock to take my medications” [47 year-old female] Medication knowledge (Have knowledge about their medications, such as side effects, and knows the risks
6
4
and consequences of non-adherence) “I’m aware of the consequences of not taking my medication...I remember that I ended up in a coma and I don’t want that to happen again” [75 year-old female] “I learnt from my parents’ situation” [47 year-old female] “I was a nurse before so I know why medications should be taken the right way” [86 year-old female] BARRIERS
Adherent (n=1)
Non-adherent (n=8)
Medication concerns
1
7
(Change in medication such as doses or names, assistance or routine; multiple medications or different dosage times; unfamiliar with medications’ purpose and reasons for taking; side effects) “Have not taken medications in the past, I have neglected myself...change of name of medications to generic names” [65-year old male] “Difficult when medications are on different times... Doctor didn’t advice the specific time to drink medications for example, 1 table in either morning or afternoon” [79 year-old male] “Wife used to help but when she has her own medications, she doesn’t help anymore” [81 year-old male] “I stopped taking apixaban because I thought I was well and nothing was wrong with me, I still think that there is nothing wrong with me because I don’t feel anything bad, I always through I was healthy” [56 year-old male] 0 4 Forgetfulness (Lack in remembering to take a dose/s) “Occasionally forgets especially when there is a routine change for example, when eating out I don’t bring medications” [71 year-old male] “I leave medication for today’s dose until the next day if forgotten” [84-year old male] Worried about warfarin the most, when I miss a dose of warfarin, I take an extra dose plus in addition to prescribed warfarin” [79 year-old male] 0
Difficult routine lifestyle
3
(Inability to take medications due to distractions or other activities and commitments, such as work) “I miss my medication because of working long days and sometimes due to my health condition that makes me too tired or sick...drink medications varied time depending on what time I wake up” [75 year-old female] “I drink medications at different times because of hard schedule, I drop off my daughter to work...when going out and busy, I do not take my medications” [57 year-old male]
and varies globally, with reported OAC persistence rates of 43% after 24 months in China; persistence rates of 70% after 18 months in Scotland; 48% completed prescription refills over 12 months in the United States; and 54.9% reporting high levels of adherence in Australia [13]. Our results were similar, as they showed 59% were adherent to their cardiac medications. So, it is likely that medication adherence in AF patients is not
limited to factors directly related to OACs such as fear of bleeding, and that overall medication adherence results from a combination of factors beyond patient-level factors, such as health system-related factors. In contrast to our results, which focussed on cardiac medications, recent research has demonstrated that OAC adherence is associated with level of OAC knowledge, and
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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also with health literacy [24]. An online survey in Australia has also shown that additional factors influence OAC adherence including age, gender, medication cost, and ‘information overload’ [25]. Research in China has also identified that higher levels of AF knowledge and a belief in the importance of medications are associated with increased warfarin adherence; and non-adherence was generated from strong negative beliefs and fear of medications, primarily because of the perceived adverse effects of warfarin [26]. However, it is possible to overcome the barrier regarding fear of bleeding, as a systematic review has shown that when patients are educated correctly, the majority of patients are willing to accept an increase in bleeding risk in order to reduce their risk of having a stroke [27]. Of interest, patients taking warfarin have been shown to have higher levels of knowledge of overall OAC medications than those taking non-vitamin K antagonist oral anticoagulants (NOACs) [28], and in a European survey it was found that people have less knowledge about NOAC medications than warfarin, especially in relation to bleeding risk and need for regular international normalised ratio (INR) testing [29], Despite this persistence in newly diagnosed AF patients is shown to be higher at one year for those taking NOACs (dabigatran) compared to those taking warfarin [30]. There are many modifiable barriers affecting adherence to cardiac medications, including concerns about medications and their side effects, forgetfulness, difficulty getting repeat prescriptions, and difficulty opening the medication packaging [14]. Furthermore, it is suggested younger people may be less adherent due to barriers caused by the demand of their busy social activities and work commitments [26,31]. These barriers are in line with our findings, and may indicate a need for development of specific interventions tailored to a younger population. The time commitment of an intervention or medication regime also affects the likely compliance with the regime: medication adherence reduces as the number of daily doses increases [31]. Furthermore, patients have reported they have a preference for less complicated medication regimes, including single doses per day [27]. Practical implications for health professionals Health professionals have a pivotal role in assessing and maximising medication adherence in their patients. The new Australian guidelines for management of AF advocate for patient centred care and decision making, and also implementation of individualised strategies to increase medication adherence [32]. The guidelines also recommend structured follow-up for patients on medicinal treatment, to provide continuous education, support, and assessment of selfmanagement [32]. Regular follow-up allows for early identification of any adverse medication effects, and early identification of adherence or non-persistence issues [32]. To achieve this, it is important to assess each patient to identify their understanding, cognition, their personal barriers, and the facilitators and assistance that is available to them. Where appropriate, family should also be involved in the development of strategies to improve adherence, as
7
family and caregivers have been shown to significantly improve adherence in patients with cardiac disease [33]. Discussions with family can provide valuable insight into the patient’s current methods to manage medications, identification of difficulties or challenges, beliefs and medication concerns, and suitability of alternative strategies and assistance (e.g. Webster packs, pillboxes, reminders). Identification and establishment of appropriate routines, systems and structures is important, and these interventions are demonstrated to improve adherence [34]. However they may not be effective if there are underlying knowledge deficits or beliefs that medications have negative side-effects. As cognitive impairment is common in patients with AF [35], education and intervention strategies may need to be altered to accommodate the patient’s cognitive deficit. The timing, delivery and choice of education materials is important, to ensure the information is understood and knowledge is retained. Educating the patient with use of decision aids has been shown to improve knowledge and acceptance of treatment and medications in other chronic disease groups such as diabetes, leading to increased compliance with treatment [36]. Decision aids could be considered as a method to assist education of patients with AF, but it is integral that the patient perspective is taken into consideration during this process [37]. Limitations This was a pilot study at a single centre. As the sample size was 54 participants, it is possible that statistically significant differences were unable to be detected. Some participants may have been newly diagnosed with AF on admission to hospital, and it is possible that this may reflect in lower AF knowledge scores. Thus, this limits the generalisability of the results to wider populations, and the results should be considered as hypothesis generating only. Furthermore, as the BAASIS questionnaire is a self-report instrument requiring patient recall for the previous 4 weeks period, recall bias may affect the results for medication adherence, and accurate measurement of medication adherence with questionnaires is known to be a problem due to the complex nature of medication adherence [38]. This study highlights the issue of poor medication adherence in AF patients which has been identified in previous research, however the extent of the underlying factors impacting medication adherence in AF patients remain undetermined. It is important to holistically understand the issues impacting poor adherence to cardiac medications in patients with AF. To achieve this, large multi-centre studies are warranted to also investigate the broader factors of adherence in addition to the patient-related factors. These factors should include health service factors such as the provision of systematic teaching (what is taught and how well); what strategies are implemented for patients; is cognitive impairment assessed and what provisions are made to account for cognitive impairment. Future studies should assess adherence in hospital and then at regular intervals after discharge, to also determine the time-course of
Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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adherence. It is also recommended to continue to use open questions to supplement the data obtained through the standard adherence questionnaires.
Conclusion Many patients with AF are non-adherent to their medications. Medication adherence is a complex issue influenced by multiple factors that determine each patient’s capability to adhere to cardiac medications accurately. This study highlights the importance for health professionals to assess facilitators and barriers on an individual basis, assessing knowledge and correcting misperceptions. Treatment plans should be tailored in order to optimise medication adherence including strategies to create routines and prompt patients to take their medications, with regular follow-up appointments, and consideration of all cardiac medications and not solely OACs. Future large-scale research is warranted to identify the holistic multi-factorial issues impacting poor adherence to cardiac medications in patients with AF.
A. Pacleb et al.
[5]
[6]
[7]
[8]
[9]
[10] [11]
[12]
[13]
Declaration of Conflicting Interests The authors declare no conflict of interests.
[14]
Funding
[15]
N Lowres is funded by a NSW Health Early Career Fellowship (H16/ 52168). This research received no financial support for the research, authorship, and/or publication of this article
[16]
Acknowledgments Q3
Nil.
[17]
Appendices. Supplementary Data
[18]
Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j. hlc.2019.11.012.
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Please cite this article in press as: Pacleb A, et al. Adherence to Cardiac Medications in Patients With Atrial Fibrillation: A Pilot Study. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.11.012
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