Heart failure remote monitoring: evidence from the retrospective evaluation of a real-world remote monitoring program

Telehealth care and remote monitoring strategies in heart failure patients: A systematic review and meta-analysis

BACKGROUND

Heart failure (HF) is a cardiac clinical syndrome that involves complex pathological aetiologies. It represents a growing public health issue and affects a significant number of people worldwide.

OBJECTIVES

To synthesize evidence related to the impact of telemonitoring strategies on mortality and hospital readmissions of heart failure patients.

METHODS

A systematic literature review was conducted using PubMed, Scopus, CINAHL, IEEE Xplore Digital Library, Engineering Source, and INSPEC. To be included, studies had to be in English or Italian and involve heart failure patients of any NYHA class, receiving care through any telecare, remote monitoring, telemonitoring, or telehealth programmes. Articles had to contain data on both mortality and number of patients who underwent rehospitalizations during follow-ups. To explore the effectiveness of telemonitoring strategies in reducing both one-year all-cause mortality and one-year rehospitalizations, studies were synthesized through meta-analyses, while those excluded from meta-analyses were summarized narratively.

RESULTS

Sixty-one studies were included in the review. Narrative synthesis of data suggests a trend towards a reduction in deaths among monitored patients, but the number of rehospitalized patients was higher in this group. Meta-analysis of studies reporting one-year all-cause mortality outlined the protective power of care models based on telemonitoring in reducing one-year all-cause mortality. Meta-analysis of studies reporting the number of rehospitalized patients in one-year outlined that telemonitoring is effective in reducing the number of rehospitalized patients when compared with usual care strategies.

CONCLUSION

Evidence from this review confirms the benefits of telemonitoring in reducing mortality and rehospitalizations of HF patients. Further research is needed to reduce the heterogeneity of the studies.

Clinical Efficiency and Safety Outcomes of Virtual Care for Oncology Patients During the COVID-19 Pandemic

PURPOSE

Telehealth has been an integral response to the COVID-19 pandemic. However, no studies to date have examined the utility and safety of telehealth for oncology patients undergoing systemic treatments. Concerns of the adequacy of virtual patient assessments for oncology patients include the risk and high acuity of illness and complications while on treatment.

METHODS

We assessed metrics related to clinical efficiency and treatment safety after propensity matching of newly referred patients starting systemic therapy where care was in large part replaced by telehealth between March and May 2020, and 206 newly referred patients from a similar time period in 2019 where all encounters were in-person visits.

RESULTS

Patient-initiated telephone encounters that capture care or effort outside of visits, time to staging imaging, and time to therapy initiation were not significantly different between cohorts. Similarly, 3 month all-cause or cancer-specific emergency department presentations and hospitalizations, and treatment delays were not significantly different between cohorts. There were substantial savings in travel time with virtual care, with an average of 211.4 minutes saved per patient over a 3-month interval.

CONCLUSION

Our results indicate that replacement of in-person care with virtual care in oncology does not lead to worse efficiency or outcomes. Given the increased barriers to patients seeking oncology care during the pandemic, our study indicates that telehealth efforts may be safely intensified. These findings also have implications for the continual use of virtual care in oncology beyond the pandemic.

Predictive analytics and tailored interventions improve clinical outcomes in older adults: a randomized controlled trial

This study explored the potential to improve clinical outcomes in patients at risk of moving to the top segment of the cost acuity pyramid. This randomized controlled trial evaluated the impact of a Stepped-Care approach (predictive analytics + tailored nurse-driven interventions) on healthcare utilization among 370 older adult patients enrolled in a homecare management program and using a Personal Emergency Response System. The Control group (CG) received care as usual, while the Intervention group (IG) received Stepped-Care during a 180-day intervention period. The primary outcome, decrease in emergency encounters, was not statistically significant (15%, p = 0.291). However, compared to the CG, the IG had significant reductions in total 90-day readmissions (68%, p = 0.007), patients with 90-day readmissions (76%, p = 0.011), total 180-day readmissions (53%, p = 0.020), and EMS encounters (49%, p = 0.006). Predictive analytics combined with tailored interventions could potentially improve clinical outcomes in older adults, supporting population health management in home or community settings.

Does remote patient monitoring reduce acute care use? A systematic review

OBJECTIVE

Chronic diseases are associated with increased unplanned acute hospital use. Remote patient monitoring (RPM) can detect disease exacerbations and facilitate proactive management, possibly reducing expensive acute hospital usage. Current evidence examining RPM and acute care use mainly involves heart failure and omits automated invasive monitoring. This study aimed to determine if RPM reduces acute hospital use.

METHODS

A systematic literature review of PubMed, Embase and CINAHL electronic databases was undertaken in July 2019 and updated in October 2020 for studies published from January 2015 to October 2020 reporting RPM and effect on hospitalisations, length of stay or emergency department presentations. All populations and disease conditions were included. Two independent reviewers screened articles. Quality analysis was performed using the Joanna Briggs Institute checklist. Findings were stratified by outcome variable. Subgroup analysis was undertaken on disease condition and RPM technology.

RESULTS

From 2050 identified records, 91 studies were included. Studies were medium-to-high quality. RPM for all disease conditions was reported to reduce admissions, length of stay and emergency department presentations in 49% (n=44/90), 49% (n=23/47) and 41% (n=13/32) of studies reporting each measure, respectively. Remaining studies largely reported no change. Four studies reported RPM increased acute care use. RPM of chronic obstructive pulmonary disease (COPD) was more effective at reducing emergency presentation than RPM of other disease conditions. Similarly, invasive monitoring of cardiovascular disease was more effective at reducing hospital admissions versus other disease conditions and non-invasive monitoring.

CONCLUSION

RPM can reduce acute care use for patients with cardiovascular disease and COPD. However, effectiveness varies within and between populations. RPM's effect on other conditions is inconclusive due to limited studies. Further analysis is required to understand underlying mechanisms causing variation in RPM interventions. These findings should be considered alongside other benefits of RPM, including increased quality of life for patients.

PROSPERO REGISTRATION NUMBER

CRD42020142523.

Follow-up results in a specialised consultation after discharge for heart failure

BACKGROUND

Despite advances in the diagnosis and treatment of heart failure (HF), the condition still has high morbidity and mortality. Health education and the treatment of comorbidities have been shown to be effective, as has multidisciplinary care in specialised units, although this involves organisational and structural efforts that are not always feasible. We present the results of a simple outpatient consultation, focused on the specialised care of HF.

PATIENTS AND METHODS

The consultation included patients discharged after hospitalisation (index hospitalisation) for decompensated HF from an internal medicine department. The follow-up was conducted by internists especially dedicated (not exclusively) to HF and a nurse partially dedicated to HF. The follow-up consisted of fixed visits 1, 3, 6 and 12 months after the discharge, with more visits on demand if needed.

RESULTS

A total of 250 patients were included with a minimum follow-up of 1 year. The reduction in hospitalisations and emergency department visits was 56% and 61% (P<.05), respectively, for HF and 46% and 40% (P<.05), respectively, for any cause. Treatment optimisation was also achieved, with a significant increase in the evidence-based drug prescription rate and the reduction of other drugs, such as calcium antagonists.

CONCLUSION

A simple model based on a specialised care consultation for HF is effective in reducing readmissions and optimising the treatment. The lack of healthcare resources should not be an obstacle for specialised care for patients with HF.

Effectiveness of telemonitoring-enhanced support over structured telephone support in reducing heart failure-related healthcare utilization in a multi-ethnic Asian setting

Aims

Our study aimed to compare the effectiveness of telemonitoring over structured telephone support in reducing heart failure-related healthcare utilization.

Methods

This was a non-randomised controlled study comparing 150 recently discharged heart failure patients enrolled into telemonitoring and 55 patients who only received structured telephone support after rejecting telemonitoring. Patient activation, knowledge and self-management levels were measured at baseline and the one year upon programme completion using the Patient Activation Measure, the Dutch Heart Failure Knowledge Scale and the Self-Care of Heart Failure Index respectively. Differences in heart failure-related and all-cause hospitalization rates, total bed days and mortality rates at 180 days and at one year, knowledge and self-management scores and total cost of care between groups at one year were analysed.

Results

Average age of telemonitoring was 57.9 years and 63.9 years for structured telephone support. Significant difference in adjusted 180-day all-cause bed days (telemonitoring: five days versus structured telephone support: 9.8 days), heart failure-related bed days (telemonitoring: 1.2 days versus structured telephone support: six days) and adjusted one-year heart failure-related bed days (telemonitoring: 2.2 days versus structured telephone support: 6.6 days) were observed. Telemonitoring was associated with reduced all-cause one-year mortality (hazard ratio 0.32, p = 0.02). Estimated mean maintenance and confidence scores were significantly higher in the telemonitoring group at one year. No differences in all-cause and HF-related readmission rates and knowledge levels were observed. The one-year total cost of care was predicted to be Singapore dollars (SG$) 2774.4 lower ( p = 0.07) in telemonitoring.

Conclusion

In conclusion, telemonitoring was associated with lower all-cause and heart failure-related total bed days at 180 days, lower heart failure-related total bed days and total cost of care at one year as compared with structured telephone support.

A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data

BACKGROUND

Heart failure is one of the leading causes of hospitalization in the United States. Advances in big data solutions allow for storage, management, and mining of large volumes of structured and semi-structured data, such as complex healthcare data. Applying these advances to complex healthcare data has led to the development of risk prediction models to help identify patients who would benefit most from disease management programs in an effort to reduce readmissions and healthcare cost, but the results of these efforts have been varied. The primary aim of this study was to develop a 30-day readmission risk prediction model for heart failure patients discharged from a hospital admission.

METHODS

We used longitudinal electronic medical record data of heart failure patients admitted within a large healthcare system. Feature vectors included structured demographic, utilization, and clinical data, as well as selected extracts of un-structured data from clinician-authored notes. The risk prediction model was developed using deep unified networks (DUNs), a new mesh-like network structure of deep learning designed to avoid over-fitting. The model was validated with 10-fold cross-validation and results compared to models based on logistic regression, gradient boosting, and maxout networks. Overall model performance was assessed using concordance statistic. We also selected a discrimination threshold based on maximum projected cost saving to the Partners Healthcare system.

RESULTS

Data from 11,510 patients with 27,334 admissions and 6369 30-day readmissions were used to train the model. After data processing, the final model included 3512 variables. The DUNs model had the best performance after 10-fold cross-validation. AUCs for prediction models were 0.664 ± 0.015, 0.650 ± 0.011, 0.695 ± 0.016 and 0.705 ± 0.015 for logistic regression, gradient boosting, maxout networks, and DUNs respectively. The DUNs model had an accuracy of 76.4% at the classification threshold that corresponded with maximum cost saving to the hospital.

CONCLUSIONS

Deep learning techniques performed better than other traditional techniques in developing this EMR-based prediction model for 30-day readmissions in heart failure patients. Such models can be used to identify heart failure patients with impending hospitalization, enabling care teams to target interventions at their most high-risk patients and improving overall clinical outcomes.

HerzMobil, an Integrated and Collaborative Telemonitoring-Based Disease Management Program for Patients With Heart Failure: A Feasibility Study Paving the Way to Routine Care

Background

Heart failure is a major health problem associated with frequent hospital admissions. HerzMobil Tirol is a multidisciplinary postdischarge disease management program for heart failure patients to improve quality of life, prevent readmission, and reduce mortality and health care costs. It uses a telemonitoring system that is incorporated into a network of specialized heart failure nurses, physicians, and hospitals. Patients are equipped with a mobile phone, a weighing scale, and a blood pressure and heart rate monitor for daily acquisition and transmission of data on blood pressure, heart rate, weight, well-being, and drug intake. These data are transmitted daily and regularly reviewed by the network team. In addition, patients are scheduled for 3 visits with the network physician and 2 visits with the heart failure nurse within 3 months after hospitalization for acute heart failure.

Objective

The objectives of this study were to evaluate the feasibility of HerzMobil Tirol by analyzing changes in health status as well as patients’ self-care behavior and satisfaction and to derive recommendations for implementing a telemonitoring-based interdisciplinary disease management program for heart failure in everyday clinical practice.

Methods

In this prospective, pilot, single-arm study including 35 elderly patients, the feasibility of HerzMobil Tirol was assessed by analyzing changes in health status (via Kansas City Cardiomyopathy Questionnaire, KCCQ), patients’ self-care behavior (via European Heart Failure Self-Care Behavior Scale, revised into a 9-item scale, EHFScB-9), and user satisfaction (via Delone and McLean System Success Model).

Results

A total of 43 patients joined the HerzMobil Tirol program, and of these, 35 patients completed it. The mean age of participants was 67 years (range: 43-86 years). Health status (KCCQ, range: 0-100) improved from 46.2 to 69.8 after 3 months. Self-care behavior (EHFScB-9, possible range: 9-22) after 3 months was 13.2. Patient satisfaction in all dimensions was 86% or higher. Lessons learned for the rollout of HerzMobil Tirol comprise a definite time schedule for interventions, solid network structures with clear process definition, a network coordinator, and specially trained heart failure nurses.

Conclusions

On the basis of the positive evaluation results, HerzMobil Tirol has been officially introduced in the province of Tyrol in July 2017. It is, therefore, the first regular financed telehealth care program in Austria.

Extended, continuous measures of functional status in community dwelling persons with Alzheimer's and related dementia: Infrastructure, performance, tradeoffs, preliminary data, and promise

BACKGROUND

The past decades have seen phenomenal growth in the availability of inexpensive and powerful personal computing devices. Efforts to leverage these devices to improve health care outcomes promise to remake many aspects of healthcare delivery, but remain in their infancy.

NEW METHOD

We describe the development of a mobile health platform designed for daily measures of functional status in ambulatory, community dwelling subjects, including those who have Alzheimer's disease or related neurodegenerative disorders. Using Smartwatches and Smartphones we measure subject overall activity and outdoor location (to derive their lifespace). These clinically-relevant measures allow us to track a subject's functional status in their natural environment over prolonged periods of time without repeated visits to healthcare providers. Functional status metrics are integrated with medical information and caregiver reports, which are used by a caregiving team to guide referrals for physician/APRN/NP care. COMPARISON: with Existing Methods We describe the design tradeoffs involved in all aspects of our current system architecture, focusing on decisions with significant impact on system cost, performance, scalability, and user-adherence.

RESULTS

We provide real-world data from current subject enrollees demonstrating system accuracy and reliability.

CONCLUSIONS

We document real-world feasibility in a group of men and women with dementia that Smartwatches/Smartphones can provide long-term, relevant clinical data regarding individual functional status. We describe the underlying considerations of this system so that interested organizations can adapt and scale our approach to their needs. Finally, we provide a potential agenda to guide development of future systems.

Healthcare utilization in older patients using personal emergency response systems: an analysis of electronic health records and medical alert data : Brief Description: A Longitudinal Retrospective Analyses of healthcare utilization rates in older patients using Personal Emergency Response Systems from 2011 to 2015

BACKGROUND

Personal Emergency Response Systems (PERS) are traditionally used as fall alert systems for older adults, a population that contributes an overwhelming proportion of healthcare costs in the United States. Previous studies focused mainly on qualitative evaluations of PERS without a longitudinal quantitative evaluation of healthcare utilization in users. To address this gap and better understand the needs of older patients on PERS, we analyzed longitudinal healthcare utilization trends in patients using PERS through the home care management service of a large healthcare organization.

METHODS

Retrospective, longitudinal analyses of healthcare and PERS utilization records of older patients over a 5-years period from 2011-2015. The primary outcome was to characterize the healthcare utilization of PERS patients. This outcome was assessed by 30-, 90-, and 180-day readmission rates, frequency of principal admitting diagnoses, and prevalence of conditions leading to potentially avoidable admissions based on Centers for Medicare and Medicaid Services classification criteria.

RESULTS

The overall 30-day readmission rate was 14.2%, 90-days readmission rate was 34.4%, and 180-days readmission rate was 42.2%. While 30-day readmission rates did not increase significantly (p = 0.16) over the study period, 90-days (p = 0.03) and 180-days (p = 0.04) readmission rates did increase significantly. The top 5 most frequent principal diagnoses for inpatient admissions included congestive heart failure (5.7%), chronic obstructive pulmonary disease (4.6%), dysrhythmias (4.3%), septicemia (4.1%), and pneumonia (4.1%). Additionally, 21% of all admissions were due to conditions leading to potentially avoidable admissions in either institutional or non-institutional settings (16% in institutional settings only).

CONCLUSIONS

Chronic medical conditions account for the majority of healthcare utilization in older patients using PERS. Results suggest that PERS data combined with electronic medical records data can provide useful insights that can be used to improve health outcomes in older patients.

A Human-Centered Design Methodology to Enhance the Usability, Human Factors, and User Experience of Connected Health Systems: A Three-Phase Methodology

Background

Design processes such as human-centered design, which involve the end user throughout the product development and testing process, can be crucial in ensuring that the product meets the needs and capabilities of the user, particularly in terms of safety and user experience. The structured and iterative nature of human-centered design can often present a challenge when design teams are faced with the necessary, rapid, product development life cycles associated with the competitive connected health industry.

Objective

We wanted to derive a structured methodology that followed the principles of human-centered design that would allow designers and developers to ensure that the needs of the user are taken into account throughout the design process, while maintaining a rapid pace of development. In this paper, we present the methodology and its rationale before outlining how it was applied to assess and enhance the usability, human factors, and user experience of a connected health system known as the Wireless Insole for Independent and Safe Elderly Living (WIISEL) system, a system designed to continuously assess fall risk by measuring gait and balance parameters associated with fall risk.

Methods

We derived a three-phase methodology. In Phase 1 we emphasized the construction of a use case document. This document can be used to detail the context of use of the system by utilizing storyboarding, paper prototypes, and mock-ups in conjunction with user interviews to gather insightful user feedback on different proposed concepts. In Phase 2 we emphasized the use of expert usability inspections such as heuristic evaluations and cognitive walkthroughs with small multidisciplinary groups to review the prototypes born out of the Phase 1 feedback. Finally, in Phase 3 we emphasized classical user testing with target end users, using various metrics to measure the user experience and improve the final prototypes.

Results

We report a successful implementation of the methodology for the design and development of a system for detecting and predicting falls in older adults. We describe in detail what testing and evaluation activities we carried out to effectively test the system and overcome usability and human factors problems.

Conclusions

We feel this methodology can be applied to a wide variety of connected health devices and systems. We consider this a methodology that can be scaled to different-sized projects accordingly.

Remote Monitoring in Heart Failure: the Current State

OPINION STATEMENT

The treatment of congestive heart failure is an expensive undertaking with much of this cost occurring as a result of hospitalization. It is not surprising that many remote monitoring strategies have been developed to help patients maintain clinical stability by avoiding congestion. Most of these have failed. It seems very unlikely that these failures were the result of any one underlying false assumption but rather from the fact that heart failure is a progressive, deadly disease and that human behavior is hard to modify. One lesson that does stand out from the myriad of methods to detect congestion is that surrogates of congestion, such as weight and impedance, are not reliable or actionable enough to influence outcomes. Too many factors influence these surrogates to successfully and confidently use them to affect HF hospitalization. Surrogates are often attractive because they can be inexpensively measured and followed. They are, however, indirect estimations of congestion, and due to the lack specificity, the time and expense expended affecting the surrogate do not provide enough benefit to warrant its use. We know that high filling pressures cause transudation of fluid into tissues and that pulmonary edema and peripheral edema drive patients to seek medical assistance. Direct measurement of these filling pressures appears to be the sole remote monitoring modality that shows a benefit in altering the course of the disease in these patients. Congestive heart failure is such a serious problem and the consequences of hospitalization so onerous in terms of patient well-being and costs to society that actual hemodynamic monitoring, despite its costs, is beneficial in carefully selected high-risk patients. Those patients who benefit are ones with a prior hospitalization and ongoing New York Heart Association (NYHA) class III symptoms. Patients with NYHA class I and II symptoms do not require hemodynamic monitoring because they largely have normal hemodynamics. Those with NYHA class IV symptoms do not benefit because their hemodynamics are so deranged that they cannot be substantially altered except by mechanical circulatory support or heart transplantation. Finally, hemodynamic monitoring offers substantial hope to those patients with normal ejection fraction (EF) heart failure, a large group for whom medical therapy has largely been a failure. These patients have not benefited from the neurohormonal revolution that improved the lives of their brothers and sisters with reduced ejection fractions. Hemodynamic stabilization improves the condition of both but more so of the normal EF cohort. This is an important observation that will help us design future trials for the 50% of heart failure patients with normal systolic function.

Creating connections - the development of a mobile-health monitoring system for heart failure: Qualitative findings from a usability cohort study

Objective

There is significant interest in the role of digital health technology in enabling optimal monitoring of heart failure patients. To harness this potential, it is vital to account for users' capacity and preferences in the development of technological solutions. We adopted an iterative approach focussed on learning from users' interactions with a mobile-health monitoring system.

Methods

We used a participatory mixed methods research approach to develop and evaluate a mobile-health monitoring system. Fifty-eight heart failure patients were recruited from three health care settings in the UK and provided with Internet-enabled tablet computers that were wirelessly linked to sensor devices for blood pressure, heart rate and weight monitoring. One to two home visits were conducted with a subgroup of 29 participants to evaluate the usability of the system over a median follow-up period of six months. The thematic analysis of observational data and 45 interviews was informed by the domestication of technology theory.

Results

Our findings indicate that digital health technologies need to create and extend connections with health professionals, be incorporated into users' daily routines, and be personalised according to users' technological competencies and interest in assuming a proactive or more passive role in monitoring their condition.

Conclusions

Users' patterns of engagement with health technology changes over time and varies according to their need and capacity to use the technology. Incorporating diverse user experiences in the development and maintenance of mobile-health systems is likely to increase the extent of successful uptake and impacts on outcomes for patients and providers.

A Remote Medication Monitoring System for Chronic Heart Failure Patients to Reduce Readmissions: A Two-Arm Randomized Pilot Study

Background

Heart failure (HF) is a chronic condition affecting nearly 5.7 million Americans and is a leading cause of morbidity and mortality. With an aging population, the cost associated with managing HF is expected to more than double from US $31 billion in 2012 to US $70 billion by 2030. Readmission rates for HF patients are high—25% are readmitted at 30 days and nearly 50% at 6 months. Low medication adherence contributes to poor HF management and higher readmission rates. Remote telehealth monitoring programs aimed at improved medication management and adherence may improve HF management and reduce readmissions.

Objective

The primary goal of this randomized controlled pilot study is to compare the MedSentry remote medication monitoring system versus usual care in older HF adult patients who recently completed a HF telemonitoring program. We hypothesized that remote medication monitoring would be associated with fewer unplanned hospitalizations and emergency department (ED) visits, increased medication adherence, and improved health-related quality of life (HRQoL) compared to usual care.

Methods

Participants were randomized to usual care or use of the remote medication monitoring system for 90 days. Twenty-nine participants were enrolled and the final analytic sample consisted of 25 participants. Participants completed questionnaires at enrollment and closeout to gather data on medication adherence, health status, and HRQoL. Electronic medical records were reviewed for data on baseline classification of heart function and the number of unplanned hospitalizations and ED visits during the study period.

Results

Use of the medication monitoring system was associated with an 80% reduction in the risk of all-cause hospitalization and a significant decrease in the number of all-cause hospitalization length of stay in the intervention arm compared to usual care. Objective device data indicated high adherence rates (95%-99%) among intervention group participants despite finding no significant difference in self-reported adherence between study arms. The intervention group had poorer heart function and HRQoL at baseline, and HRQoL declined significantly in the intervention group compared to controls.

Conclusions

The MedSentry medication monitoring system is a promising technology that merits continued development and evaluation. The MedSentry medication monitoring system may be useful both as a standalone system for patients with complex medication regimens or used to complement existing HF telemonitoring interventions. We found significant reductions in risk of all-cause hospitalization and the number of all-cause length of stay in the intervention group compared to controls. Although HRQoL deteriorated significantly in the intervention group, this may have been due to the poorer HF-functioning at baseline in the intervention group compared to controls. Telehealth medication adherence technologies, such as the MedSentry medication monitoring system, are a promising method to improve patient self-management,the quality of patient care, and reduce health care utilization and expenditure for patients with HF and other chronic diseases that require complex medication regimens.

Trial Registration

ClinicalTrials.gov NCT01814696; https://clinicaltrials.gov/ct2/show/study/NCT01814696 (Archived by WebCite® at http://www.webcitation.org/6giqAVhno)

Medium-Term Effectiveness of a Comprehensive Internet-Based and Patient-Specific Telerehabilitation Program With Text Messaging Support for Cardiac Patients: Randomized Controlled Trial

Background

Cardiac telerehabilitation has been introduced as an adjunct or alternative to conventional center-based cardiac rehabilitation to increase its long-term effectiveness. However, before large-scale implementation and reimbursement in current health care systems is possible, well-designed studies on the effectiveness of this new additional treatment strategy are needed.

Objective

The aim of this trial was to assess the medium-term effectiveness of an Internet-based, comprehensive, and patient-tailored telerehabilitation program with short message service (SMS) texting support for cardiac patients.

Methods

This multicenter randomized controlled trial consisted of 140 cardiac rehabilitation patients randomized (1:1) to a 24-week telerehabilitation program in combination with conventional cardiac rehabilitation (intervention group; n=70) or to conventional cardiac rehabilitation alone (control group; n=70). In the telerehabilitation program, initiated 6 weeks after the start of ambulatory rehabilitation, patients were stimulated to increase physical activity levels. Based on registered activity data, they received semiautomatic telecoaching via email and SMS text message encouraging them to gradually achieve predefined exercise training goals. Patient-specific dietary and/or smoking cessation advice was also provided as part of the telecoaching. The primary endpoint was peak aerobic capacity (VO₂ peak). Secondary endpoints included accelerometer-recorded daily step counts, self-assessed physical activities by International Physical Activity Questionnaire (IPAQ), and health-related quality of life (HRQL) assessed by the HeartQol questionnaire at baseline and at 6 and 24 weeks.

Results

Mean VO₂ peak increased significantly in intervention group patients (n=69) from baseline (mean 22.46, SD 0.78 mL/[min*kg]) to 24 weeks (mean 24.46, SD 1.00 mL/[min*kg], P<.01) versus control group patients (n=70), who did not change significantly (baseline: mean 22.72, SD 0.74 mL/[min*kg]; 24 weeks: mean 22.15, SD 0.77 mL/[min*kg], P=.09). Between-group analysis of aerobic capacity confirmed a significant difference between the intervention group and control group in favor of the intervention group (P<.001). At 24 weeks, self-reported physical activity improved more in the intervention group compared to the control group (P=.01) as did the global HRQL score (P=.01).

Conclusions

This study showed that an additional 6-month patient-specific, comprehensive telerehabilitation program can lead to a bigger improvement in both physical fitness (VO₂ peak) and associated HRQL compared to center-based cardiac rehabilitation alone. These results are supportive in view of possible future implementation in standard cardiac care.

A Mobile Health Intervention Supporting Heart Failure Patients and Their Informal Caregivers: A Randomized Comparative Effectiveness Trial

Background

Mobile health (mHealth) interventions may improve heart failure (HF) self-care, but standard models do not address informal caregivers’ needs for information about the patient’s status or how the caregiver can help.

Objective

We evaluated mHealth support for caregivers of HF patients over and above the impact of a standard mHealth approach.

Methods

We identified 331 HF patients from Department of Veterans Affairs outpatient clinics. All patients identified a “CarePartner” outside their household. Patients randomized to “standard mHealth” (n=165) received 12 months of weekly interactive voice response (IVR) calls including questions about their health and self-management. Based on patients’ responses, they received tailored self-management advice, and their clinical team received structured fax alerts regarding serious health concerns. Patients randomized to “mHealth+CP” (n=166) received an identical intervention, but with automated emails sent to their CarePartner after each IVR call, including feedback about the patient’s status and suggestions for how the CarePartner could support disease care. Self-care and symptoms were measured via 6- and 12-month telephone surveys with a research associate. Self-care and symptom data also were collected through the weekly IVR assessments.

Results

Participants were on average 67.8 years of age, 99% were male (329/331), 77% where white (255/331), and 59% were married (195/331). During 15,709 call-weeks of attempted IVR assessments, patients completed 90% of their calls with no difference in completion rates between arms. At both endpoints, composite quality of life scores were similar across arms. However, more mHealth+CP patients reported taking medications as prescribed at 6 months (8.8% more, 95% CI 1.2-16.5, P=.02) and 12 months (13.8% more, CI 3.7-23.8, P<.01), and 10.2% more mHealth+CP patients reported talking with their CarePartner at least twice per week at the 6-month follow-up (P=.048). mHealth+CP patients were less likely to report negative emotions during those interactions at both endpoints (both P<.05), were consistently more likely to report taking medications as prescribed during weekly IVR assessments, and also were less likely to report breathing problems or weight gains (all P<.05). Among patients with more depressive symptoms at enrollment, those randomized to mHealth+CP were more likely than standard mHealth patients to report excellent or very good general health during weekly IVR calls.

Conclusions

Compared to a relatively intensive model of IVR monitoring, self-management assistance, and clinician alerts, a model including automated feedback to an informal caregiver outside the household improved HF patients’ medication adherence and caregiver communication. mHealth+CP may also decrease patients’ risk of HF exacerbations related to shortness of breath and sudden weight gains. mHealth+CP may improve quality of life among patients with greater depressive symptoms. Weekly health and self-care monitoring via mHealth tools may identify intervention effects in mHealth trials that go undetected using typical, infrequent retrospective surveys.

Trial Registration

ClinicalTrials.gov NCT00555360; https://clinicaltrials.gov/ct2/show/NCT00555360 (Archived by WebCite at http://www.webcitation.org/6Z4Tsk78B).