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ARTICLES: Outcomes

Effects of eHealth-Based Interventions on Adherence to Components of Cardiac Rehabilitation

A Systematic Review

Kebapci, Ayda RN, PhD; Ozkaynak, Mustafa PhD; Lareau, Suzanne C. RN, MS, FAAN, ATSF

Author Information
The Journal of Cardiovascular Nursing: January/February 2020 - Volume 35 - Issue 1 - p 74-85
doi: 10.1097/JCN.0000000000000619
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Abstract

Coronary artery disease is the most frequent cause of death.1 Given the burgeoning population of patients with cardiovascular disease, effective treatment modalities for secondary prevention are urgently needed. According to the European Society of Cardiology, cardiac rehabilitation (CR) is one intervention repeatedly shown to be effective in the secondary prevention of cardiovascular disease,2 including a 20% to 30% reduction in hospital readmissions and a 15% to 31% reduction in all-cause and cardiac mortality.3 International guidelines recommend that CR should focus on health, lifestyle change, modification of risk factors, and psychosocial well-being.4,5 Despite the well-established benefits of CR, challenges occur in maximizing these benefits, such as lack of accessibility, referral, and adherence.6 Unfortunately, as many as 80% of the eligible population do not enroll in CR. Furthermore, adherence in center-based programs is low, and dropout rates are high.7,8 Poor adherence has been associated with those with lower educational level, lack of social support, high burden of family responsibilities, economic challenges, lack of or limited healthcare insurance, and lower age (<65 years).9,10 Novel approaches could reduce dropout rates and increase availability. Because home-based CR has been shown to be as effective as traditional center-based CR, it could be an option for patients who have difficulty accessing a program.11–13

eHealth is the use of information and communication technologies to facilitate improving health. eHealth is an effective approach for disseminating health information and behavioral interventions via technology and the Internet. eHealth also has the potential to educate one on one, at a convenient time and place for the patient. Advantages to eHealth include an individualized learning environment at a lower cost than hospital-based interventions.14,15 eHealth can provide patient assessment, physical activity promotion, nutritional and tobacco counseling, weight management, dyslipidemia and hypertension monitoring, and psychosocial support.16 There has been increasing attention to eHealth-based CR as an alternative or complement to traditional CR programs.17 The World Health Organization has acknowledged the supportive role of eHealth-based methods.18 Video education for self-care,19 tele-monitoring,20–22 telephone support,23 and mhealth (mobile technology/text messages and website support)24 have been shown to have a positive effect on self-care behaviors in CR programs.

Cardiac rehabilitation is a multicomponent strategy consisting of 3 phases. Phase 1 typically takes place in the inpatient setting during recovery from a cardiac event. Phase 2 is typically held in a hospital-based outpatient facility with patients attending weekly sessions, and phase 3 includes health maintenance by the patient in the home. Phase 2 includes an individualized treatment plan, exercise prescription, education classes, and assistance with risk reduction (eg, tobacco dependence and hyperlipidemia). The third phase of CR requires independent maintenance of risk factor modification and management by patients, with periodic physician evaluation.25 Novel interventions have the potential to enable components of CR to be accessible and economical and decrease risk factors, similar to traditional, phase 2 programs.26 However, there are concerns that adherence to components of CR via eHealth-based interventions may be affected by numerous barriers, such as lack of time and motivation of the patient, technical problems, and technological literacy.27–29 To understand the effectiveness of eHealth-based interventions in CR, it would be useful to determine the current state of knowledge of eHealth use, in respect to acceptability of its components by evaluating adherence.

Methods

Main Outcome Measures

Adherence to eHealth-based components of CR is the main outcome of interest in this systematic review. Adherence is the degree to which a patient behaves in response to mutually agreed-upon recommendations with the healthcare provider.30 Compliance, on the other hand, is defined as the extent to which the patient's behavior matches the healthcare provider's recommendations.31 For this work, we considered adherence and compliance as interchangeable terms.

Literature Search Strategy

A research librarian conducted searches in 6 electronic databases: Medline, Embase, CINAHL, EBSCO, Web of Science, the Cochrane Database of Systematic Reviews, and Cochrane Central databases, for studies published from January 1996 to December 2017. The search strategies were based on the terms health information technology, cardiac rehabilitation, adherence, and compliance using multiple free text terms and subject headings to describe them (Appendix 1). All retrievals were downloaded to the Endnote X7 bibliographic management software to remove duplicate records. In addition to the electronic databases, searches were also conducted in reference lists, relevant conference lists, and other gray literature.

Study Selection

The Figure displays the Preferred Reporting Items for Systematic Reviews and Meta-Analyses32 flow diagram of reviewed and included studies. The total set of titles and abstracts of papers were reviewed by AK and MO, who were blinded to the journal titles and authors. Studies were reviewed for relevance to evaluate the effects of eHealth-based interventions on patient adherence to components of CR. Disagreements between reviewers were resolved by multiple discussions, with all decisions reached by consensus. The inclusion criteria were as follows: prospective studies, randomized controlled trials (RCTs), and pilot studies. eHealth-based interventions for components of phase 2 or 3 CR included patients with the following cardiac conditions: coronary artery diseases; myocardial infarction; angina or heart failure; coronary artery bypass graft surgery; percutaneous coronary intervention, including coronary angioplasty (balloon angioplasty) and stenting; valve replacement; pacemaker; or implantable cardioverter defibrillator. Studies were required to be published in full text and indicate that they evaluated adherence/compliance as a primary or secondary outcome. Studies in which adherence was solely defined and measured as attendance, participation, and enrollment in a CR were excluded. Other exclusion criteria were (a) not reported in English, (b) primary prevention studies, (c) interventions that were not delivered by healthcare professionals, (d) qualitative studies, or (e) posters, abstracts, or conference papers.

FIGURE 1
FIGURE 1:
Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram: the effect of eHealth-based interventions on patient adherence to components of cardiac rehabilitation (CR). Boxes on the left represent each stage of search strategy; boxes on the right represent the number of articles retained and excluded by stage of analysis.

Data Synthesis and Analysis

References and abstracts were imported into Microsoft Excel and duplicates were removed. When 2 or more articles reported on the same study, the article reporting the longest period of data collection was included. Because this review included a heterogeneous group of study designs, the authors attempted to qualitatively describe the effect of eHealth on adherence to components of CR. Therefore, results were synthesized into a narrative approach.

Data extraction

Outcome data were extracted independently by AK and MO. Jadad scale scores33 assess the methodological quality of a clinical trial. Scores were calculated for each RCT. Studies with 2 points or lower were considered low, and those with 3 points or higher were considered “high quality.” The quality of the non-RCTs were assessed based on Risk Of Bias in Nonrandomized Studies I (ROBINS-I) tool.34

Results

Study Selection and Characteristics

The search yielded 1520 articles, with 22 duplicates excluded, leaving 1498 for screening. After the titles and abstracts were screened, 1393 articles were excluded, with 105 retrieved for full review and data extraction. After full-text review, 90 more articles were excluded (Figure). Our search did not result in including articles from reference lists, conference lists, or gray literature. Gray literature refers to a variety of unpublished or informally published documents from different groups such as professional associations, research institutes, government agencies, and nonprofit organizations. Studies were characterized by measurement method, definition of adherence, and others (Table 1). The type and quality of the study, the characteristics of patients, and the findings are reported in Table 2. Fifteen studies were RCTs and 6 were either non-RCT prospective, crossover design, pilot project, or controlled studies. The quality of the non-RCTs was poor based on Risk of Bias in Nonrandomized Studies I. Therefore, we reviewed in-depth the 15 RCTs for this report. Five studies were conducted in the United States,19,35–38 and 7 in Europe.20,22,23,39–42 Canada,43 New Zealand,24 and Jordan reported 1 study each.44 Sample sizes ranged from 19 to 382, with duration of follow-up, which refers to the time after the intervention is completed, from 30 days to 1 year.

TABLE 1
TABLE 1:
Purpose, Adherence and Interventions to Components of Cardiac Rehabilitation Programs in 15 Studies
TABLE 2
TABLE 2:
Type and Rating of Quality of Study, Phase of Cardiac Rehabilitation, Follow-up, Sample and Findings in 15 Studies

Technology Interventions

Of 15 studies, 7 found a statistically significant improvement from eHealth-based CR interventions on adherence via short message system or general messages,45 step counters,43 video education,19 telemonitoring and web-based applications for self-care behaviors,20,22,40 and telephone feedback with accelerometer use.23 Adherence outcomes were related to medication,19,20,45 diet,19,44 weight,19,20,22 fluid intake,19,20,22 and activity level.19,20,22,23,41,42 Studies that had a significant improvement in at least 1 outcome were considered to have a positive effect.

In many studies, there was no information as to whether feedback was given to patients during the study period.19,22,36,38,41,42 In some studies, patients received personalized text message medication reminders37 or received only text message reminders.39 In studies where feedback was given, patients were either called,23 received bidirectional daily messages,24 or received telephone interactions43 or individualized feedback by smartphone.40

Measurement and Evaluation Methods of Adherence to Components of Cardiac Rehabilitation

Different methods for measuring adherence levels to outcomes such as medications, physical activity, diet, sodium restriction, fluid restriction, daily weighing, and smoking were used without providing numerical parameters of adherence versus nonadherence.23,36,39,41–43 Outcomes were mainly measured with self-report or self-measurement of health behaviors19,20,22,24 and self-care behaviors with or without drug intake.19,20,22,24,36,37,40,43 In several studies, the 8-item Morisky Medication Adherence Questionnaire Scales,24,37,44 the Medication Adherence Rating Scale,40 36-item Likert scale for self-care,19 and medication intake35 were used to measure patient adherence to medication. In 2 studies, The Heart Failure Compliance Scale was used20,22 (Table 1).

Patient Satisfaction With the eHealth-based Interventions

The 8-item Client Satisfaction Questionnaire36 and the System Usability Scale40 were used to evaluate patient satisfaction with eHealth, whereas the Mobile Phone Use Questionnaire was used for feasibility and patient satisfaction with receiving text messages.37 The aim of the Mobile Phone Use Questionnaire is to obtain patients' experience with using mobile phones for medication reminders and/or education. In addition, a 12-item questionnaire, developed by the authors, was used to measure acceptance and satisfaction of patients.41 Patient satisfaction was significantly higher in 3 of 4 studies in the intervention group.37,40,41

Fidelity of the eHealth-Based Interventions

The fidelity of the eHealth-based intervention was measured in only 1 of the 15 studies.24 In this study, a high level of fidelity was found to the text messaging of the mHealth program, which included daily short text messages via website.

Discussion

This systematic review aimed to determine the effect of eHealth-based interventions on patient adherence to components of CR. Because of the many components of CR, there were many outcomes that could be evaluated for adherence, with each outcome evaluated by different measures. This was reflected in the variety of outcome measures used in the 15 studies (Table 1). Most studies used 1 outcome measure, whereas 5 used more than 1 outcome measure of adherence.14,15,20,22,44 In 11 of the 15 studies, medication adherence was evaluated with 1 or 2 of the following 8 outcome measures: electronic pill cap monitor, Morisky Adherence Survey Questionnaire, electronic monitoring device, Heart Failure Compliance Scale, a 36-item Likert scale, Medication Adherence Rating Scale, medication possession ratio dispensing record in e-diary, or self-reports. There are a number of reported reasons patients may be unable to adhere to their medications, such as failure to record information properly, suboptimal medical literacy,46 poor understanding of medication instructions,47 ineffective communication between the primary care physician and the patient,48 cost of medication,47 work schedule (resulting in missed dosage), and insufficient healthcare provider support.49 For example, reporting accurate pill counts may not always be possible. Patients may be unable to follow the detailed instructions of the mobile application to record their drug intake accurately. On the other hand, the number of pills absent from a container does not assure the researcher that the pills were consumed by the patient.50 Patients may discard pills to appear to be adherent. In addition, there were issues relating to cutoff levels for acceptable missed doses, such as consistent parameters for the threshold of allowable missed doses of medication.35–37 Adherence issues for some outcomes may differ for economic reasons, as in the case of medications and exercise.30 Patients may not be able to afford medication, and the cost associated with exercising is generally not a factor.49 Although medication use was the predominant outcome, medications are only one of several elements addressed in CR programs.

Subjective reports were the most frequently used method for evaluation of adherence to diet, weight, and exercise/activity. Self-reports, although useful, do not have the precision of objective measures. It is therefore difficult to compare objective with subjective findings of adherence and draw strong conclusions about the success of the intervention. The information obtained with subjective reports, for example, may not reflect true daily adherence behaviors because of lack of recall or fear of disappointing the provider.31 The act of measurement can in itself affect the patient's behavior; that is, if a patient knows that adherence is being monitored, patients may report falsely high adherence.31 Others indicate that self-reports are a reliable method, particularly while measuring nonadherent behavior.32,51,52

Adherence is a phenomenon that must be present in sufficient levels to be meaningful, and the levels have to be realistic. Therefore, cutoff points for each outcome of CR must be established and ideally, minimal clinically important differences should be established. For example, requiring measurement of daily weights 100% of the time is not realistic for most individuals. On the other hand, weighing 90% of the time, or not missing more than 1 weight per week, may be a more realistic goal. Identifying and using the minimal clinically important differences for this outcome could provide interpretation that is more meaningful. The rationale for measuring self-care behaviors must be discussed with the patient.53 This is a sophisticated process and not fully explained in the studies. Future research should focus on developing reliable measurement methods to evaluate adherence to all components of eHealth-based CR, taking into account issues related to technology that may influence patient adherence.

Feedback has been shown to be important in other areas of telehealth (software app) and interventions, such as Internet-based cognitive behavioral therapy.54 Interactions such as brief telephone calls, postcards, a short message system, or email could increase the motivation of patients.55 In only 5 studies was structured feedback or a personalized approach provided to patients.23,24,35,40,43 In 1 study, telephone support23 was used, and a positive effect on adherence was found. A meta-analysis found that telephone text messaging increases medication adherence rates by 18% in chronic diseases.56 Social isolation, depression, and anxiety are often related to patient outcomes in cardiovascular diseases and may result in poor adherence to health behaviors.41 Glozier et al57 found that in people with depression and a high level of cardiovascular disease risk, an Internet-delivered cognitive behavior therapy program produced an increase in adherence to health behaviors.

Behavioral and cognitive behavioral theory is based on the assumption that all behavior is learned.58 These theories endorse strategies to promote behavior change, including self-monitoring, problem solving, goal setting, cognitive restructuring, social support, stress management, and prevention.59 Tate et al60 found that a structured, Internet-delivered cognitive behavior therapy intervention for weight management, which included weekly e-mail feedback, provided significant weight loss after 6 months and was more effective than web-based education. The European Association of Cardiovascular Prevention and Rehabilitation indicates that psychosocial risk factors may act as barriers to lifestyle changes and treatment adherence.61 Most of the studies failed to consider the effect of psychological distress, depression, or anxiety on adherence. In only 3 studies was the psychological status of patients evaluated.22,23,38 In one, where the primary outcomes were improved, the level of depression was lower in the eHealth-based treatment group at 3 months.22 Conversely, with text message, internet support, and telehealth, Dale et al24 reported an improvement in medication adherence, but significantly greater levels of anxiety were seen at 6 months in the treatment group. It has been reported that CR provides an opportune time to diagnose emotional disorders and help patients cope with the challenges of coronary artery disease.62,63 Use of behavior change theories when designing and implementing eHealth-based interventions in CR programs enables clinicians to leverage proven strategies and provide the framework for patient-centered interventions.64

The minimum follow-up period in this review was 30 days.35–37 Patients who participate in CR have been shown to have low adherence and greatest decline in adherence during the first 3 to 6 months. By the sixth month, only 30% to 60% of the patients who attended CR continued to exercise.65 In addition, about 90% of patients who participate in CR quit the program within a year.51 Most of the studies in this review followed patients for less than 6. Those studies with at least a 6-month follow-up were in relation to short message text and website,24 a mobile app,42 and telemonitoring,20 where positive effects were seen in adherence. The duration of studies should be taken into consideration when evaluating and designing studies. For example, it may take more than 90 days for patients to change their behavior and lifestyle.19

Cardiac rehabilitation is a multidisciplinary team effort.66 According to the American Heart Association, the CR team is also composed of family members. No studies in this review, however, addressed family support.

Use of Technology Interventions to Improve Adherence to Components of Cardiac Rehabilitation

Telemonitoring and web-based applications for self-care behaviors in home-based settings were most effective in promoting adherence to medication, diet, weight, physical activity, fluid restriction, smoking, and alcohol consumption.20,22,24,40 The effectiveness of eHealth on patient adherence depends heavily on the design and implementation of eHealth.66 Adherence may require significant lifestyle changes. Technologies benefit patients most, if feedback can be provided. It has been shown that even when patients know adherence is being monitored, nonadherence is common.35 eHealth can be implemented within the setting of traditional CR as a means of promoting adherence and in a home-based setting, as a means of expanding the eligible population. In this review, eHealth was mostly introduced in a home-based CR.

Patient Satisfaction for and Fidelity of the eHealth-Based Interventions

A misfit between technology characteristics and patient routines can negatively affect the benefits of technology.67 The design and implementation of technology should support it being a part of the patient's daily routine, rather than be disruptive to their routine in the home.68

In this review, only 1 study evaluated the fidelity of the intervention and 4 evaluated patient satisfaction with eHealth. eHealth programs have the potential to affect CR program outcomes and the generalizability of results. However, few research works have been conducted to evaluate patient satisfaction with eHealth-based programs. We recommend that those studying the impact of technology on adherence to components of CR assess the fidelity and the patient's satisfaction with the technology and revise the technology to ensure a sufficient level of both. Understanding the reasons for the lack of satisfaction with eHealth will be important in designing robust eHealth-based interventions.

Limitations

This systematic review is limited by the quality of the randomized controlled studies and heterogeneity of the studies, such as different study designs for the same outcome, different patient population, sample size, type of eHealth, and others. The primary aim of this study was to determine the effects of eHealth-based interventions on patient adherence to components of CR. Most studies lacked a measure of fidelity. Variations in how adherence was measured for the same outcome and the wide range of eHealth used limited our ability to come to strong conclusions about the effectiveness of eHealth on adherence.

Conclusion

This review summarized different measurement and evaluation methods of components of CR. Variations in results of adherence to eHealth-based interventions were observed. One of the great challenges with CR is patient adherence. eHealth may be able to address this issue, since many of the studies found that eHealth-based interventions had a positive effect on adherence. Although medication adherence was the most targeted area, there are many areas of importance. In addition, a lack of threshold for adherence made it difficult to interpret results between studies. Interventions aimed at improving adherence in CR should be specific (and preferably consistent). The measurement of adherence should be based on an explicit definition of adherence and should be measured with validated scales tested in CR.

What’s New and Important

  • There is variety in the definition and measurement of adherence to HIT-based interventions and this requires further clarification.
  • Psychometrically tested measures to evaluate adherence specific to CR should be identified (or developed) to compare results among HIT interventions on adherence.
  • Healthcare providers should account for the psychological status and technological literacy of patients, which may affect the patient's ability to optimally adhere.

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Appendix 1
Appendix 1:
Literature Search Methods
Keywords:

adherence; cardiac rehabilitation; health information technology

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