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International Journal of Cardiology Cardiovascular Risk and Prevention 20 (2024) 200234

Available online 24 December 2023 2772-4875/© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/).

Medication adherence in adults after hospitalization for heart failure: A cross-sectional study

Manuela Huber a,e, Ada Katrin Busch b, Irene Stalder-Ochsner c, Andreas J. Flammer c, Gabriela Schmid-Mohler d,f,*

a Educational Center for Health and Social, Weinfelden, Switzerland b Institute of Nursing, ZHAW School of Health Science, Winterthur, Switzerland c Department of Cardiology, University Heart Center, University Hospital Zurich, Switzerland d Center of Clinical Nursing Science, University Hospital Zurich, Switzerland e Clinic for General, Visceral, Transplant, Vascular and Thoracic Surgery, Cantonal Hospital St. Gallen, Switzerland f Department of Pulmonology, University Hospital Zurich, Switzerland

A R T I C L E I N F O

Handling Editor: D Levy

Keywords: Medication adherence Heart failure MARS-5

A B S T R A C T

Background: Medication non-adherence in heart failure (HF) leads to increased mortality, morbidity and healthcare costs. However, no study has investigated HF patients’ post-hospitalization medication non-adherence in Switzerland. Objectives: Our primary aim was to assess the prevalence of post-discharge medication non-adherence in patients with HF. A secondary objective was to identify differences between fully and partially adherent patients regarding selected unplanned therapy-related inpatient/outpatient cardiology visits. Methods: A non-experimental cross-sectional study was applied. The prevalence of medication adherence was assessed with a German-translated version of the Medication Adherence Report Scale (MARS-5) and analyzed descriptively. Differences between adherent and partially adherent patients’ numbers of medications, dosing per day and 180-day unplanned inpatient stays or cardiology outpatient visits were explored. Results: Of 153 recruited patients, 72 participated in the survey. Of these, 26.4 % were not fully adherent. Their most common reason was forgetfulness (23.7 %). There were no significant group differences regarding therapy- related variables or 180-day unplanned cardiology stays/visits. Conclusions: Considering that over one-quarter of surveyed HF patients were not fully medication adherent, Swiss cardiology nurses need to be sensitized to this issue and trained in adherence-enhancing interventions. Reaching acceptable adherence levels in patients with HF will require further research and action.

1. Background

Heart failure (HF) is a clinical syndrome with high mortality and morbidity, resulting in high treatment costs for the general population [1]. The primary pillar of treatment is medication. If adhered to as indicated, i.e., regarding taking, timing and dosage, these medications control symptoms, slow disease progression and improve survival [2]. However, patients with heart failure commonly do not take their medication as prescribed. This is referred to as medication non-adherence [2,3]. Studies to date show rates of self-reported medi- cation non-adherence across all HF patient groups between 14 and 28 % [4–7].

Patients who have been hospitalized for heart failure are particularly vulnerable for poor medication adherence, as hospitalization is often associated with changes in medication [8]. In this context, a US retro- spective cohort study showed a 35 % prevalence of medication non-adherence in patients over 65 years of age at one year post-discharge [9]. In HF patients, medication non-adherence results in increased mortality, morbidity and healthcare costs [10–13].

A 2015 World Health Organization (WHO) report named therapy- related factors as especially relevant contributors to non-adherence [3]. Studies in heart failure found that greater dosing frequency as well as higher total daily numbers of cardiac medications were associ- ated with decreasing medication adherence [14,15]. Another

* Corresponding author. University Hospital Zurich, Center of Clinical Nursing Science, Raemistrasse 100, CH-8091, Zurich, Switzerland. E-mail address: [email protected] (G. Schmid-Mohler).

Contents lists available at ScienceDirect

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https://doi.org/10.1016/j.ijcrp.2023.200234 Received 18 September 2023; Received in revised form 19 December 2023; Accepted 21 December 2023

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treatment-related factor is rehospitalization. Of all patients hospitalized with HF, 29.3 % are rehospitalized due to cardiac decompensation within six months of their initial discharge [14].

Medication non-adherence is a known contributor to rehospitaliza- tion [14–16]. In turn, as noted, medication changes during rehospitali- zation can contribute to non-adherence [19,20]. This cyclic relationship makes strong medication adherence doubly important. Therefore, it is crucial to ensure that, after discharge, HF patients continue to take their medications consistently and correctly in their home environment. To our knowledge, there is currently no study investigating medication non-adherence in patients after hospitalization for HF in Switzerland.

2. Objectives

Therefore, this study’s primary objective was to investigate the prevalence of post-discharge medication non-adherence in patients’ rehospitalizations—whether planned or unplanned—for heart failure.

Its secondary objective was to investigate whether fully adherent patients differ from partially adherent patients regarding selected treatment-related variables, i.e., number of cardiac medications, doses per day, as well as number of unplanned inpatient stays or outpatient cardiology visits within 180 days post-discharge.

Fig. 1. Flowchart recruitment process.

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3. Methods

3.1. Design

A non-experimental cross-sectional study was applied. A cross- sectional design is useful for testing relationships between variables with a single survey. It is also economical and easy to handle. [17] To enable good reporting, the authors followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) state- ment [22].

3.2. Setting

The present study was conducted in a Swiss tertiary hospital that serves as a leading national and international reference center for the treatment and prevention of cardiovascular diseases. Medication ad- justments follow national and international treatment guidelines.

3.3. Sample

Inclusion criteria were ≥18 years of age, a diagnosis of heart failure and hospitalization with DRG code F62 (F62A = heart failure and shock with extremely severe complications or comorbidities and dialysis or resuscitation or specific procedure or complicating diagnosis, or multidrug-resistant pathogens; F62B = heart failure and shock with extremely severe complications or comorbidities or specific procedure or evaluation for heart transplantation; F62C = heart failure and shock with severe complications or comorbidities; F62D = heart failure and shock) between 1 January 2020 and 31 July 2021 (19 months). Patients were excluded if they were unable to understand or answer a ques- tionnaire in German due either to difficulty understanding German or to cognitive or mental illness.

3.4. Recruitment

Participants were recruited in three steps (see Fig. 1): First, relevant cases were extracted from the study hospital’s digital clinical informa- tion system (KISIM). The resulting list included all patients who fulfilled the inclusion criteria. Second, the first author reviewed and adapted the initial list by checking the available information from the electronic patient file. If all inclusion criteria were fulfilled and no exclusion criteria were present, the clinical and project managers sent each involved patient a letter informing them about the study and inviting them to participate in a third step. The information pack also included a consent form and a stamped, preaddressed envelope. One week later, the first author contacted the patients by telephone and informed them verbally about the study. Patients who consented to participate then signed the consent form and mailed it back to the study group. When the consent form was received, a questionnaire were sent to each patient. If the completed questionnaire was not received within three weeks, a reminder letter was sent. In case of incomplete questionnaires, a tele- phone enquiry was made by the first author.

3.5. Variables

3.5.1. Socio-demographic variables Age, gender, language, nationality, marital status, living situation,

educational attainment and employment data were collected by written questionnaire.

3.5.2. Therapy-related variables Therapy-related variables were assessed by questionnaire. These

included a list of all current cardiac medications, their dosage(s) and dosing time(s) and the person responsible for preparing them. The cause of each patient’s heart failure and its applicable New York Heart Asso- ciation (NYHA) classification, as well as comorbidities and number of unplanned inpatient stays or outpatient cardiology visits in the first 180 days following discharge from the study hospital, were extracted from their electronic patient file.

3.5.3. Medication adherence Self-reported medication adherence was assessed with the 5-Item

Medication Adherence Report Scale (MARS-5 -©Professor Rob Horne) [18]. The instrument originates in England, and was developed with the help of people with diabetes, hypertension and asthma [19]. It consists of five items about non-adherent behavior: (1) I forget to take my medication; (2) I change the dose of my medication; (3) I do not take the medication for a certain period of time; (4) I deliberately skip a dose of medication; and (5) I take less medication than prescribed. These questions are answered on a 5-point Likert-type scale (1 = always, 2 = often, 3 = sometimes, 4 = seldom, 5 = never), with possible sum scores ranging between 5 and 25 points and higher scores indicating higher adherence. Testing of the German version of the MARS-5 (the MARS-D) showed acceptable internal consistency (Cronbach’s alpha = 0.60–69) and test-retest reliability (Pearson’s r = 0.61–0.63) [25]. As has been done in previous studies, we dichotomized the total scores into partially adherent (≤24 points) and fully adherent patients (25 points) [20–22].

3.6. Data analysis

Socio-demographic and therapy-related data were analyzed descriptively using frequencies, means and standard deviations or me- dians and interquartile ranges (Q75-Q25) as appropriate to the distri- bution of data.

Medication non-adherence prevalence was calculated based on the number of affected patients classified as partially adherent expressed as a percentage of the overall number of persons included in the study [23]. For the group comparison of the two samples (numbers of daily cardiac medications, daily dosing times and unplanned inpatient stays or outpatient cardiology visits in the 180 days following hospital discharge), the Mann-Whitney U test was used because the dependent variable was not normally distributed [30]. For this statistical test pro- cedure, the significance level was set at alpha <0.05 [24]. The data were analyzed using the SPSS version 28.0 statistical software package.

4. Ethical considerations

The study complies with the Declaration of Helsinki [31], the

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guidelines of Good Clinical Practice (GCP) and all relevant Swiss regu- lations. The Ethics Committee of the Canton of Zurich has granted approval for this study (BASEC No. 2021–01733).

5. Results

5.1. Sample

Of the 153 patients we invited, 72 participated in the study, a response rate of 47.1 %. The sample consisted of 49 male (68.1 %) and 23 female (31.9 %) patients. The mean age was 71.3 (SD = 13.3) years. Almost half (44.4 %) of participants were married or in a relationship. On average, respondents took five heart medications per day (SD = 1.6) across two dosing times (SD = 0.5). All but one (98.6 %, n = 71) had comorbidities; and one-fourth (25.1 %, n = 18) had been rehospitalized within six months of their initial hospital discharge. Further socio- demographic and treatment-related data are displayed in Table 1

5.2. Medication adherence

The mean MARS-D sum score measuring self-reported medication adherence as 23.9 points (SD = 2.7; range: 11–25). The median score was 25 points, the 25th percentile 24 points and the 75th percentile 25 points. Overall, 73.6 % of patients (n = 53) were classified as fully adherent and 26.4 % (n = 19) as partially adherent. The most common reason for partial adherence, given by 23.7 % (n = 17) of all patients was forgetting to take the medication. An eighth (12.5 %; n = 9) of patients deliberately changed their dosages, and 11.1 % (n = 8) deliberately skipped a dose. Eight stopped taking all of their cardiac medication for a period of time (11.1 %) or took less than their prescribed dosage (11.1 %). Table 2 shows the relative and absolute frequencies of the five relevant MARS-D items.

5.3. Group comparison

There were no statistically significant differences between the groups of fully adherent and partially adherent patients with respect to the number of daily cardiac medications taken (p = 0.341, z = − 0.953), number of daily medication dosing times (p = 0.775, z = − 0.286) and number of unplanned inpatient stays or outpatient cardiological visits within 180 days after hospital discharge (p = 0.737, z = − 0.336). Table 3 illustrates the subdivision of the groups of fully adherent and partially adherent patients and presents the clinical and treatment- related variables in both groups.

Table 1 Sample characteristics (n = 72).

Variable Missing data (%)

Mean (SD) or absolute numbers (% from n)

Number of participants 72 Age in years 0 71,33 (SD 13,25) Sex 0

Female 23 (31,9 %) Male 49 (68,1 %)

Civil status 0 Single 14 (19,4 %) Married, (registered) partnership 32 (44,4 %) Separated, divorced, widowed 26 (36,1 %)

Mother language 0 German 60 (83,3 %) Other language 12 (16,7 %)

Education degree 0 Compulsory school 14 (19,4 %) Secondary education II 40 (55,6 %) Tertiary education 18 (25,0 %)

Medication preparation 0 Patient himself 55 (76,4 %) Others (pharmacy, spouse, nursing home, home care nursing, general practitioner)

17 (23,6 %)

Number of heart medications taken daily per day

0 5,21 (SD 1,59)

2–3 medications 8 (11,1 %) 4–5 medications 35 (48,6 %) ≥ 6 medications 29 (40,3 %)

Active ingredients taken daily 0 ACE-Inhibitor, angiotension II receptor blocker (ARB), angiotensin receptor neprilysin inhibitor

40 (55,6 %)

Sodium-glucose cotransporter 2 (SGLT2 inhibitor)

13 (18,1 %)

Loop diuretics 59 (81,9 % Thiazide diuretics 10 (13,9 %) Mineralocorticoid receptor antagonist 17 (13,9 %) Beta blockers 53 (73,6 %) Calcium channel blockers 19 (26,4 %) Digitalis glycosides 3 (4,2 %) Other antiarrhythmic 10 (13,9 %) Combination preparations (isosorbide dinitrate þ hydrochlorothiazid/ACE-II þ amlodipine/diuretics þ ACE- inhibitors etc.)

3 (4,2 %)

Other antihypertensives 14 (19,4 %) Platelet aggregation inhibitors 19 (26,4 %) Anticoagulants 54 (75,0 %) Statins 50 (69,4 %)

Number of dosing times for heart medication per day

0 2.19 (SD 0,54)

One dosing time 5 (6,9 %) Two dosing times 48 (66,7 %) Three dosing times 19 (26,4 %)

Cause of heart failure 0 Ischemic heart disease 25 (35,2 %) Hypertensive heart disease 8 (11,3 %) Non-ischemic cardiomyopathy 15 (21.1 %) Cardiac arrhythmias 4 (5,6 %) Valvular disease 17 (23,9 %) Congenital heart disease 8 (11,3 %) Pericardial disease 1 (1,4 %) Unclear cause 12 (16,9 %)

Comorbidities Cardiac arrhythmias 44 (61,1 %) Coronary heart disease 35 (48,6 %) Valvular disease 36 (50,0 %) Hypertension 46 (63,9 %) Diabetes mellitus 25 (34,7 %) Obesity 13 (18,1 %) Kidney disease 58 (80,6 %) Chronic respiratory disease 38 (52,8 %) Gout and arthritis 15 (20,8 %) Neurological disease 22 (30,6 %)

Table 1 (continued )

Variable Missing data (%)

Mean (SD) or absolute numbers (% from n)

Peripheral vascular disease 25 (34,7 %) Cancer 11 (15,3 %) Mental illness 4 (5,6 %) Other disease 71 (98,6 %)

NYHA-classification 29.2 (%) NYHA 2 8 (11,1 %) NYHA 3 32 (44,4 %) NYHA 4 11 (15,3 %)

Number of unplanned inpatient stays outpatients cardiological visits within 180 days of leaving the hospital

0 0,32 (SD 0,64)

No cardiological case 54 (75,0 %) One cardiological case 13 (18,1 %) Two cardiological cases 4 (5,6 %) Three cardiological cases 1 (1,4 %)

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6. Discussion

This study investigated the prevalence of self-reported medication non-adherence and therapy-related risk factors for non-adherence in adult patients who had been hospitalized due to heart failure within the past 18 months. Roughly one quarter of those who participated (26.4 %) reported partial adherence, most commonly giving forgetfulness as the reason. Intentional non-adherence was rare.

The reported 26.4 % HF medication non-adherence rate is in line those reported elsewhere in HF. Previous studies’ prevalence rates have ranged from 14 to 28 % [4–7]. However, as adherence rates depend on the study group’s operationalization and definition of adherence, they vary widely. In our study, we used a cut-off point of 24 (any indication of non-total adherence), which has also been applied in other studies [25, 26]. Only one other heart failure study has used the MARS-5. However, that research group used an adherence threshold of 23 points, which yielded an 86 % adherence rate [5].

As noted, forgetting to take medication was the current study’s most commonly-given reason for non-adherence. Once again, these data are congruent with those of similar studies, which give forgetfulness rates ranging from 50 % to 84.9 % [27–29]. The reason for non-adherence is critical because each dosage missed increases patients’ risk of disease progression, secondary diseases and other health disadvantages.

Given the high prevalence of mobile technologies in Switzerland, the use of smartphone apps to remind patients to take their medication has great potential to improve adherence in heart failure. A 2020 systematic review and meta-analysis reported that, in chronic disease populations, the use of mobile apps was generally well accepted and accompanied significant improvements in medication adherence [30].

In our study, no statistically significant difference was found be- tween the fully adherent and partially adherent groups regarding either

the complexity of their medication regimes, i.e., the number of cardiac medications taken daily, or the number of medication dosing times per day. While other studies have reported not finding significant correla- tions between regimen complexity or numbers of dosing times and non- adherence [38–40], the majority indicate that the prevalence of non-adherence correlates significantly both with regimen complexity and with the number of single doses prescribed per day [31–34]. Considering this tendency’s prominence in the literature, our results must be interpreted with caution. If interpreted independently, the limited power of our rather small sample size may have obscured sig- nificant correlations.

Our rehospitalization rate of 25.1 % within six months due to heart failure is comparable to results reported by Wideqvist et al. who re- ported a 6-month rehospitalization rate of 29.1 % [14], increasing over one year to 38.4 % [14].

Our study also revealed no statistically significant differences be- tween the fully adherent and partially adherent patients regarding their numbers of unplanned cardiac outpatient visits or inpatient stays within 180 days of hospital discharge. This contradicts a published finding that poor medication adherence was a predictor of rehospitalizations. Additionally, our analyses suggest that the number of unplanned reho- spitalizations is predominantly related to comorbidities [14], while rehospitalizations for heart failure per se are multifactorial [14,35]. Again, these results must be interpreted with caution due to the small sample size.

7. Strengths and weaknesses

One notable strength of the present study was the use of a validated instrument to measure self-reported medication adherence [36]. Our early assessment of this study’s feasibility the survey instrument’s

Table 2 Descriptive statistics for the MARS-5. Relative and absolute frequencies of n (n = 72).

Total number of cases n = 72 Absolute frequencies (% from n)

never n (%)

rare n (%)

sometimes n (%)

often n (%)

always n (%)

I forgot to take my heart medication. 55 (76,4 %) 11 (15,3 %) 4 (5,6 %) 1 (1,4 %) 1 (1.4 %) I altered the dose of my heart medication. 63 (87,5 %) 4 (5,6 %) 4 (5,6 %) 1 (1,4 %) 0 (0 %) I stopped taking my heart medication for a while. 64 (88,9 %) 4 (5,6 %) 3 (4,2 %) 1 (1,4 %) 0 (0 %) I decided to miss out a dose of my heart medication. 64 (88,9 %) 6 (8,3 %) 3 (4,2 %) 1 (1,4 %) 0 (0 %) I took less heart medication than prescribed. 64 (88,9 %) 4 (5,6 %) 3 (4,2 %) 1 (1,4 %) 0 (0 %)

Table 3 Group comparison of fully adherent and partially adherent patients with respect to treatment-related variables (n = 72).

Variable Fully adherent (n = 53)

Partially adherent (n = 19)

z p

Number of heart medications taken daily M ± SD 5,34 ± 1,60 4,84 ± 1,53 − 0,953 0,341

Mdn 5,00 5,00

Q.25- Q.75 %

4,00–6,00 4,00–6,00

min-max 3–10 2–8

Number of drug dosing times per day M ± SD 2,21 ± 0,532 2,16 ± 1,53 − 0,286 0,775 Mdn 2,00 2,00 Q.25- Q.75 %

2,00–3,00 2,00–3,00

min-max 1–3 1–3 Number of unplanned cardiology treatments inpatient/outpatients within 180 days

after hospital discharge M ± SD 0,34 ± 0,678 0,32 ± 0,582 − 0,336 0,737 Mdn 0,00 0,00 Q.25- Q.75 %

0,00-0,50 0.00–1,00

min-max 0–3 0–2

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feasibility also offered a relevant advantage. Knowing that patients could reliably self-assess their medication adherence using the ques- tionnaire greatly reduced the organizational effort and costs.56 Because it was sent to the respondents’ homes, they could complete it according to their own schedule, at a pace of their choosing.

However, certain limitations should also be noted. First, the sample size (72 patients) was rather small. As a result, its limited statistical power could have obscured the significance of inter-group differences. Another limitation is that the numbers of unplanned inpatient stays/ outpatient visits were only counted if they occurred at the study hos- pital. Patients could also have been treated in other hospitals or in their cardiologists’ or general practitioners’ practices. Also, medication adherence was assessed solely by self-report, with no objective mea- surement methods used. Due to the possibility of social desirability bias, which plays a particularly important role in the context of medication adherence, it is possible that non-adherence was underestimated [37].

Further research is recommended to expand this study to multiple centers, which would greatly enhance sample size. For this purpose, a nationwide study on medication adherence in heart failure, including an investigation of the influencing factors, may be considered. As no suit- able measurement instruments yet exist to optimally capture adherence in individual patient situations,57 any instrument developed for this purpose will need to be fully validated regarding medication adherence.

8. Conclusions and recommendations

Poor medication adherence in Swiss patients with heart failure after hospitalization is frequent, with forgetting reported as the main barrier. Considering the possible negative consequences of such non-adherence, further attention and action are needed to tackle this problem in clinical practice. This will require multi-level interventions that are embedded in both inpatient and outpatient paths, and that account for patients’ co- morbidities.

Our findings have direct practical implications. This group’s high rehospitalization rate highlights strong needs both to identify patients at risk for rehospitalization and to assess risk factors for non-adherence. Further, in addition to newly-admitted patients’ standard medical in- formation, their extended medication and adherence histories should be assessed, including dosages and any adverse drug reactions [38]. Most HF patients enter the hospital directly through the central emergency department, where time constraints, resource shortages and urgent pa- tient needs often rule out the gathering of information that is not immediately necessary. Therefore, time-intensive tasks such as extended medication histories could be added to the standard patient history taken in the cardiology unit. This would allow care teams to detect potential medication-related issues in their early stages and in- terventions chosen to target the necessary adherence dimensions. Where no such interventions exist, they can be developed with patient input [39]. Later, as the patient’s stay is drawing to a close, the care team’s discharge plans should address the issue of medication adherence. At this point, to train patients to adhere to their prescribed regimens, nurses can play key roles, providing not only information, but also counselling and training regarding medication self-management [40].

As medication non-adherence leads to increased healthcare use and higher costs, there is a strong economic argument for medication adherence training. However, regarding lasting behavioral changes, single education sessions are ineffective [41]. For patients to develop the necessary skills, they need ongoing post-discharge adherence support.17,

51

Patient motivation plays a major role [3]. Bolstering it requires more frequent patient contact, training and participatory decision-making. In consultations with advanced practice nurses (APNs), interventions to improve adherence should address multiple aspects of training, including communicative counselling on drug therapy, combined with behavior-modifying interventions [42,43]. As shown by our data, forgetting to take medication was the most common reason for partial

adherence behavior. To prevent this and other types of unintentional non-adherence, the use of medication dosing systems or reminder apps should also be topics of individual APN counselling [30,44].

Credit author statement

Ada Katrin Busch: Conceptualization, Writing – review & editing. Gabriela Schmid-Mohler: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervi- sion, Writing – original draft, Writing – review & editing. Andreas Flammer: Conceptualization, Writing – review & editing. Irene Stalder- Ochsner: Conceptualization, Writing – review & editing. Manuela Huber: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing.

Declaration of competing interest

AJF received personal fees from Alnylam, Amgen, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Fresenius, Imedos, Medtronic, MSD, Mundipharma, Orion, Pierre Fabre, Pfizer, Roche, Schwabe, Vifor and Zoll, and grants and personal fees from AstraZeneca and Novartis, all of which are independent of and outside the submitted work. All other authors have no funding or conflicts of interest to disclose. There were no clients or sponsors.

Acknowledgments

We thank Chris Shultis for editing support. We thank the Department of General Practice and Health Services

Research and the Departement of Internal Medicine VI, Clinical Phar- macology and Pharmacoepidemiology, University Hospital Heidelberg, Heidelberg, German, for permission to use the German translation of the MARS-5.

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