Design and Usability of a Heart Failure mHealth System: A Pilot Study

Mapping the Landscape of Digital Health Intervention Strategies: 25-Year Synthesis

BACKGROUND

Digital health interventions have emerged as promising tools to promote health behavior change and improve health outcomes. However, a comprehensive synthesis of strategies contributing to these interventions is lacking.

OBJECTIVE

This study aims to (1) identify and categorize the strategies used in digital health interventions over the past 25 years; (2) explore the differences and changes in these strategies across time periods, countries, populations, delivery methods, and senders; and (3) serve as a valuable reference for future researchers and practitioners to improve the effectiveness of digital health interventions.

METHODS

This study followed a systematic review approach, complemented by close reading and text coding. A comprehensive search for published English academic papers from PubMed, Web of Science, and Scopus was conducted. The search employed a combination of digital health and intervention-related terms, along with database-specific subject headings and filters. The time span covered 25 years, from January 1, 1999, to March 10, 2024. Sample papers were selected based on study design, intervention details, and strategies. The strategies were identified and categorized based on the principles of Behavior Change Techniques and Behavior Strategies.

RESULTS

A total of 885 papers involving 954,847 participants met the eligibility criteria. We identified 173 unique strategies used in digital health interventions, categorized into 19 themes. The 3 most frequently used strategies in the sample papers were "guide" (n=492, 55.6%), "monitor" (n=490, 55.4%), and "communication" (n=392, 44.3%). The number of strategies employed in each paper ranged from 1 to 32. Most interventions targeted clients (n=844, 95.4%) and were carried out in hospitals (n=268, 30.3%). High-income countries demonstrated a substantially higher number and diversity of identified strategies than low- and middle-income countries, and the number of studies targeting the public (n=647, 73.1%) far exceeded those focusing on vulnerable groups (n=238, 26.9%).

CONCLUSIONS

Digital health interventions and strategies have undergone considerable development over the past 25 years. They have evolved from simple approaches to sophisticated, personalized techniques and are trending toward multifaceted interventions, leveraging advanced technologies for real-time monitoring and feedback. Future studies should focus on rigorous evaluations, long-term effectiveness, and tailored approaches for diverse populations, and more attention should be given to vulnerable groups.

Wearable Devices for Supporting Chronic Disease Self-Management: Scoping Review

BACKGROUND

People with chronic diseases can benefit from wearable devices in managing their health and encouraging healthy lifestyle habits. Wearables such as activity trackers or blood glucose monitoring devices can lead to positive health impacts, including improved physical activity adherence or better management of type 2 diabetes. Few literature reviews have focused on the intersection of various chronic diseases, the wearable devices used, and the outcomes evaluated in intervention studies, particularly in the context of primary health care.

OBJECTIVE

This study aims to identify and describe (1) the chronic diseases represented in intervention studies, (2) the types or combinations of wearables used, and (3) the health or health care outcomes assessed and measured.

METHODS

We conducted a scoping review following the Joanna Briggs Institute guidelines, searching the MEDLINE and Web of Science databases for studies published between 2012 and 2022. Pairs of reviewers independently screened titles and abstracts, applied the selection criteria, and performed full-text screening. We included interventions using wearables that automatically collected and transmitted data to adult populations with at least one chronic disease. We excluded studies with participants with only a predisposition to develop a chronic disease, hospitalized patients, patients with acute diseases, patients with active cancer, and cancer survivors. We included randomized controlled trials and cohort, pretest-posttest, observational, mixed methods, and qualitative studies.

RESULTS

After the removal of 1987 duplicates, we screened 4540 titles and abstracts. Of the remaining 304 articles after exclusions, we excluded 215 (70.7%) full texts and included 89 (29.3%). Of these 89 texts, 10 (11%) were related to the same interventions as those in the included studies, resulting in 79 studies being included. We structured the results according to chronic disease clusters: (1) diabetes, (2) heart failure, (3) other cardiovascular conditions, (4) hypertension, (5) multimorbidity and other combinations of chronic conditions, (6) chronic obstructive pulmonary disease, (7) chronic pain, (8) musculoskeletal conditions, and (9) asthma. Diabetes was the most frequent health condition (18/79, 23% of the studies), and wearable activity trackers were the most used (42/79, 53% of the studies). In the 79 included studies, 74 clinical, 73 behavioral, 36 patient technology experience, 28 health care system, and 25 holistic or biopsychosocial outcomes were reported.

CONCLUSIONS

This scoping review provides an overview of the wearable devices used in chronic disease self-management intervention studies, revealing disparities in both the range of chronic diseases studied and the variety of wearable devices used. These findings offer researchers valuable insights to further explore health care outcomes, validate the impact of concomitant device use, and expand their use to other chronic diseases.

TRIAL REGISTRATION

Open Science Framework Registries (OSF) s4wfm; https://osf.io/s4wfm.

Data Collection and Management of mHealth, Wearables, and Internet of Things in Digital Behavioral Health Interventions With the Awesome Data Acquisition Method (ADAM): Development of a Novel Informatics Architecture

Unlabelled

The integration of health and activity data from various wearable devices into research studies presents technical and operational challenges. The Awesome Data Acquisition Method (ADAM) is a versatile, web-based system that was designed for integrating data from various sources and managing a large-scale multiphase research study. As a data collecting system, ADAM allows real-time data collection from wearable devices through the device's application programmable interface and the mobile app's adaptive real-time questionnaires. As a clinical trial management system, ADAM integrates clinical trial management processes and efficiently supports recruitment, screening, randomization, data tracking, data reporting, and data analysis during the entire research study process. We used a behavioral weight-loss intervention study (SMARTER trial) as a test case to evaluate the ADAM system. SMARTER was a randomized controlled trial that screened 1741 participants and enrolled 502 adults. As a result, the ADAM system was efficiently and successfully deployed to organize and manage the SMARTER trial. Moreover, with its versatile integration capability, the ADAM system made the necessary switch to fully remote assessments and tracking that are performed seamlessly and promptly when the COVID-19 pandemic ceased in-person contact. The remote-native features afforded by the ADAM system minimized the effects of the COVID-19 lockdown on the SMARTER trial. The success of SMARTER proved the comprehensiveness and efficiency of the ADAM system. Moreover, ADAM was designed to be generalizable and scalable to fit other studies with minimal editing, redevelopment, and customization. The ADAM system can benefit various behavioral interventions and different populations.

Assessment of Heart Failure Post-discharge Management Strategies, Needs and Acceptance of Mobile Application-based Remote Patient Management in South India

The demand for digital platforms in managing heart failure (HF) is expected to increase with promising effects on readmission and health expenditure. The study aims to explore current post-discharge management strategies and identify the need and acceptance of digital platforms, to ensure the development of a user-friendly mobile application for HF patients. Using a cross-sectional analytical research design, 90 consecutive patients diagnosed with HF who were discharged from a Tertiary Care Center were enrolled. Tele-interview was conducted using a self-developed and validated tool. The mean age of participants was 55.54 ± 10.33 years. The participants' adherence to HF management strategies was low in terms of physical exercise and weight monitoring. More than one-third were willing to self-record their measurements and use a mobile application. The common mobile application features requested were medication information/reminder (88.6%), health education (84.3%), chat with nurses (84.3%), physical activity (81.4%), symptoms (78.6%), diet (78.6%) and weight management (72.9%). The findings from this initial phase of mobile development are expected to help leverage better development of digital interventions for HF patients.

The role of patient-oriented mHealth interventions in improving heart failure outcomes: A systematic review of the literature

Heart failure (HF) is a debilitating disease with 26 million patients worldwide. Consistent and complex self-care is required on the part of patients to adequately adhere to medication and to the lifestyle changes that the disease necessitates. Mobile health (mHealth) is being increasingly incorporated in patient interventions in HF, as smartphones prove to be ideal platforms for patient education and self-help assistance. This systematic review aims to summarize and report on all studies that have tested the effect of mHealth on HF patient outcomes. Our search yielded 17 studies, namely 11 randomized controlled trials and six non-randomized prospective studies. In these, patients with the assistance of an mHealth intervention regularly measured their blood pressure and/or body weight and assessed their symptoms. The outcomes were mostly related to hospitalizations, clinical biomarkers, patients' knowledge about HF, quality of life (QoL) and quality of self-care. QoL consistently increased in patients who received mHealth interventions, while study results on all other outcomes were not as ubiquitously positive. The first mHealth interventions in HF were not universally successful in improving patient outcomes but provided valuable insights for patient-oriented application development. Future trials are expected to build on these insights and deploy applications that measurably assist HF patients.

Empowerment Enabled by Information and Communications Technology and Intention to Sustain a Healthy Behavior: Survey of General Users

BACKGROUND

Most people with chronic conditions fail to adhere to self-management behavioral guidelines. In the last 2 decades, several mobile health apps and IT-based systems have been designed and developed to help patients change and sustain their healthy behaviors. However, these systems often lead to short-term behavior change or adherence while the goal is to engage the population toward long-term behavior change.

OBJECTIVE

This study aims to contribute to the development of long-term health behavior changes or to help people sustain their healthy behavior. For this purpose, we built and tested a theoretical model that includes enablers of empowerment and an intention to sustain a healthy behavior when patients are assisted by information and communications technology.

METHODS

Structural equation modeling was used to analyze 427 survey returns collected from a diverse population of participants and patients. Notably, the model testing was performed for physical activity as a generally desirable healthy goal.

RESULTS

Message aligned with personal goals, familiarity with technology tools, high self-efficacy, social connection, and community support played a significant role (P<.001) in empowering individuals to maintain a healthy behavior. The feeling of being empowered exhibited a strong influence, with a path coefficient of 0.681 on an intention to sustain healthy behavior.

CONCLUSIONS

The uniqueness of this model is its recognition of needs (ie, social connection, community support, and self-efficacy) to sustain a healthy behavior. Individuals are empowered when they are assisted by family and community, specifically when they possess the knowledge, skills, and self-awareness to ascertain and achieve their goals. This nascent theory explains what might lead to more sustainable behavior change and is meant to help designers build better apps that enable people to conduct self-care routines and sustain their behavior.

Designing personalised mHealth solutions: An overview

INTRODUCTION

Mobile health, or mHealth, is based on mobile information and communication technologies and provides solutions for empowering individuals to participate in healthcare. Personalisation techniques have been used to increase user engagement and adherence to interventions delivered as mHealth solutions. This study aims to explore the current state of personalisation in mHealth, including its current trends and implementation.

MATERIALS AND METHODS

We conducted a review following PRISMA guidelines. Four databases (PubMed, ACM Digital Library, IEEE Xplore, and APA PsycInfo) were searched for studies on mHealth solutions that integrate personalisation. The retrieved papers were assessed for eligibility and useful information regarding integrated personalisation techniques.

RESULTS

Out of the 1,139 retrieved studies, 62 were included in the narrative synthesis. Research interest in the personalisation of mHealth solutions has increased since 2020. mHealth solutions were mainly applied to endocrine, nutritional, and metabolic diseases; mental, behavioural, or neurodevelopmental diseases; or the promotion of healthy lifestyle behaviours. Its main purposes are to support disease self-management and promote healthy lifestyle behaviours. Mobile applications are the most prevalent technological solution. Although several design models, such as user-centred and patient-centred designs, were used, no specific frameworks or models for personalisation were followed. These solutions rely on behaviour change theories, use gamification or motivational messages, and personalise the content rather than functionality. A broad range of data is used for personalisation purposes. There is a lack of studies assessing the efficacy of these solutions; therefore, further evidence is needed.

DISCUSSION

Personalisation in mHealth has not been well researched. Although several techniques have been integrated, the effects of using a combination of personalisation techniques remain unclear. Although personalisation is considered a persuasive strategy, many mHealth solutions do not employ it.

CONCLUSIONS

Open research questions concern guidelines for successful personalisation techniques in mHealth, design frameworks, and comprehensive studies on the effects and interactions among multiple personalisation techniques.

Feasibility, Acceptability, and Intervention Description of a Mobile Health Intervention in Patients With Heart Failure

Mobile health (mHealth) is used to encourage and support self-management skills in patients with heart failure. The purpose of the study was to describe the feasibility, fidelity, usability, and acceptability of mHealth interventions. This pilot study used a randomized 3-group (enhanced usual care, mHealth, and mHealth plus, which included a nurse practitioner and community health worker) repeated-measure design to determine the feasibility of using a self-management behavior app and a Bluetooth-enabled scale for daily self-monitoring of weights and medications. In the 2 mHealth groups, of the 48 patients, 38 (79%) engaged partially in recording daily weights and medications, and of the 74 patients in the sample, we obtained partial to complete data on 63 (85%) of the patients during follow-up outcome phone calls. Most patients found the intervention to be feasible, usable, and acceptable, and (93%) patients in the mHealth group and 100% of patients in the mHealth plus group agreed or strongly agreed that they learned how to self-manage their heart failure using the app. The intervention was reasonable to implement and provided insight for future intervention improvements.

Preferences of Older Adult Veterans With Heart Failure for Engaging With Mobile Health Technology to Support Self-care: Qualitative Interview Study Among Patients With Heart Failure and Content Analysis

BACKGROUND

Heart failure (HF) affects approximately 6.5 million adults in the United States, disproportionately afflicting older adults. Mobile health (mHealth) has emerged as a promising tool to empower older adults in HF self-care. However, little is known about the use of this approach among older adult veterans.

OBJECTIVE

The goal of this study was to explore which features of an app were prioritized for older adult veterans with HF.

METHODS

Between January and July 2021, we conducted semistructured interviews with patients with heart failure aged 65 years and older at a single facility in an integrated health care system (the Veterans Health Administration). We performed content analysis and derived themes based on the middle-range theory of chronic illness, generating findings both deductively and inductively. The qualitative questions captured data on the 3 key themes of the theory: self-care maintenance, self-care monitoring, and self-care management. Qualitative responses were analyzed using a qualitative data management platform, and descriptive statistics were used to analyze demographic data.

RESULTS

Among patients interviewed (n=9), most agreed that a smartphone app for supporting HF self-care was desirable. In addition to 3 a priori themes, we identified 7 subthemes: education on daily HF care, how often to get education on HF, support of medication adherence, dietary restriction support, goal setting for exercises, stress reduction strategies, and prompts of when to call a provider. In addition, we identified 3 inductive themes related to veteran preferences for app components: simplicity, ability to share data with caregivers, and positive framing of HF language.

CONCLUSIONS

We identified educational and tracking app features that can guide the development of HF self-care for an older adult veteran population. Future research needs to be done to extend these findings and assess the feasibility of and test an app with these features.

Improving outpatient care for heart failure through digital innovation: a feasibility study

BACKGROUND

Heart failure (HF) affects over 26 million people worldwide. Multidisciplinary management strategies that include symptom monitoring and patient self-care support reduce HF hospitalization and mortality rates. Ideally, HF follow-up and self-care support includes lifestyle-change recommendations and remote monitoring of weight and HF symptoms. Providing these via a digital solution may be ideal for improving HF disease outcomes and reducing the burden on providers and healthcare systems. This study's main objective was to assess the feasibility of a digital solution including remote monitoring, lifestyle-change, and self-care support for HF outpatients in Iceland.

METHODS

Twenty HF patients (mean age 57.5 years, 80% males) participated in an 8-week study. They were provided with a digital solution (SK-141), including lifestyle-change and disease self-care support, a remote symptom monitoring system, and a secure messaging platform between healthcare providers and patients. This feasibility study aimed to assess patient acceptability of this new intervention, retention rate, and to evaluate trends in clinical outcomes. To assess the acceptability of SK-141, participants completed a questionnaire about their experience after the 8-week study. Participants performed daily assigned activities (missions), including self-reporting symptoms. Clinical outcomes were assessed with the Hospital Anxiety and Depression Scale and the Kansas City Cardiomyopathy Questionnaire at the study's beginning and end with an online survey.

RESULTS

Of the 24 patients invited, 20 were elected to participate. The retention rate of participants throughout the 8-week period was high (80%). At the end of the 8 weeks, thirteen participants completed a questionnaire about their experience and acceptability of the SK-141. They rated their experience positively including on questions whether they would recommend the solution to others (6.8 on a scale of 1-7), whether the solution had improved their life and well-being (5.7 on a scale of 1-7), and whether it was user friendly (5.5 on a scale of 1-7). Many of the clinical parameters studied exhibited a promising trend towards improvement over the 8-week period.

CONCLUSION

The digital solution, SK-141, was very acceptable to patients and also showed promising clinical results in this small feasibility study. These results encourage us to conduct a longer, more extensive, adequately powered, randomized-controlled study to assess whether this digital solution can improve the quality of life and clinical outcomes among HF patients.

Art education lecturers' intention to continue using the blackboard during and after the COVID-19 pandemic: An empirical investigation into the UTAUT and TAM model

The success of faculty in adopting technology in this digital era has a direct impact on the success of the students and, eventually, the educational institution. Many teachers, on the other hand, have yet to implement technological tools such as Canvas into their classes. As a result, this study looked at art universities lecturers' opinions of variables influencing actual blackboard use, as well as their desire to utilize the lesson plan in learning and teaching during the COVID-19 Pandemic. The TAM model and the unified theory of acceptance and use of technology (UTAUT) were used to analyze lecturers' satisfaction with the blackboard and their desire to continue using it, as well as the actual usage of blackboards. A survey of 159 professors using Canvas in art instruction at five Saudi Arabian public institutions yielded the research findings. In addition, structural equation modeling (SEM) was used to evaluate the study model as well as the mediating relationship between factors influencing the desire to implement the lesson in learning and teaching during the COVID-19 Pandemic. According to the study's findings, superior impact, performance expectation, effort expectations, enabling conditions, and reported enjoyment all had statistically significant effects on perceived usefulness (PU) and perceived ease of use. The current study discovered that PU and perception of use had statistically significant influence on behavior intent, actual blackboard usage, and lecturers' happiness with utilizing blackboard in learning and teaching during the COVID-19 Pandemic. Furthermore, the results demonstrate that lecturer's intention to continue utilizing chalkboard in learning and teaching during and after COVID-19 Pandemic was influenced by actual usage of blackboard and reported pleasure. The findings are useful for education based, regulators, and practitioners who seek to create and enhance effective methods to use e-learning systems during and after the COVID-19 Pandemic.

Theory-Based Problem Formulation and Ideation in mHealth

This article reports on an investigation into how to improve problem formulation and ideation in Design Science Research (DSR) within the mHealth domain. A Systematic Literature Review of problem formulation in published mHealth DSR papers found that problem formulation is often only weakly performed, with shortcomings in stakeholder analysis, patient-centricity, clinical input, use of kernel theory, and problem analysis. The study proposes using Coloured Cognitive Mapping for DSR (CCM4DSR) as a tool to improve problem formulation in mHealth DSR. A case study using CCM4DSR found that using CCM4DSR provided a more comprehensive problem formulation and analysis, highlighting aspects that, until CCM4DSR was used, weren’t apparent to the research team and which served as a better basis for mHealth feature ideation.

Smart Home Technology Solutions for Cardiovascular Diseases: A Systematic Review

Cardiovascular diseases (CVD) are the leading cause of mortality globally. Despite improvement in therapies, people with CVD lack support for monitoring and managing their condition at home and out of hospital settings. Smart Home Technologies have potential to monitor health status and support people with CVD in their homes. We explored the Smart Home Technologies available for CVD monitoring and management in people with CVD and acceptance of the available technologies to end-users. We systematically searched four databases, namely Medline, Web of Science, Embase, and IEEE, from 1990 to 2020 (search date 18 March 2020). “Smart-Home” was defined as a system using integrated sensor technologies. We included studies using sensors, such as wearable and non-wearable devices, to capture vital signs relevant to CVD at home settings and to transfer the data using communication systems, including the gateway. We categorised the articles for parameters monitored, communication systems and data sharing, end-user applications, regulations, and user acceptance. The initial search yielded 2462 articles, and the elimination of duplicates resulted in 1760 articles. Of the 36 articles eligible for full-text screening, we selected five Smart Home Technology studies for CVD management with sensor devices connected to a gateway and having a web-based user interface. We observed that the participants of all the studies were people with heart failure. A total of three main categories—Smart Home Technology for CVD management, user acceptance, and the role of regulatory agencies—were developed and discussed. There is an imperative need to monitor CVD patients’ vital parameters regularly. However, limited Smart Home Technology is available to address CVD patients’ needs and monitor health risks. Our review suggests the need to develop and test Smart Home Technology for people with CVD. Our findings provide insights and guidelines into critical issues, including Smart Home Technology for CVD management, user acceptance, and regulatory agency’s role to be followed when designing, developing, and deploying Smart Home Technology for CVD.

Voice activated remote monitoring technology for heart failure patients: Study design, feasibility and observations from a pilot randomized control trial

BACKGROUND

Heart failure (HF) is a serious health condition, associated with high health care costs, and poor outcomes. Patient empowerment and self-care are a key component of successful HF management. The emergence of telehealth may enable providers to remotely monitor patients' statuses, support adherence to medical guidelines, improve patient wellbeing, and promote daily awareness of overall patients' health.

OBJECTIVE

To assess the feasibility of a voice activated technology for monitoring of HF patients, and its impact on HF clinical outcomes and health care utilization.

METHODS

We conducted a randomized clinical trial; ambulatory HF patients were randomized to voice activated technology or standard of care (SOC) for 90 days. The system developed for this study monitored patient symptoms using a daily survey and alerted healthcare providers of pre-determined reported symptoms of worsening HF. We used summary statistics and descriptive visualizations to study the alerts generated by the technology and to healthcare utilization outcomes.

RESULTS

The average age of patients was 54 years, the majority were Black and 45% were women. Almost all participants had an annual income below $50,000. Baseline characteristics were not statistically significantly different between the two arms. The technical infrastructure was successfully set up and two thirds of the invited study participants interacted with the technology. Patients reported favorable perception and high comfort level with the use of voice activated technology. The responses from the participants varied widely and higher perceived symptom burden was not associated with hospitalization on qualitative assessment of the data visualization plot. Among patients randomized to the voice activated technology arm, there was one HF emergency department (ED) visit and 2 HF hospitalizations; there were no events in the SOC arm.

CONCLUSIONS

This study demonstrates the feasibility of remote symptom monitoring of HF patients using voice activated technology. The varying HF severity and the wide range of patient responses to the technology indicate that personalized technological approaches are needed to capture the full benefit of the technology. The differences in health care utilization between the two arms call for further study into the impact of remote monitoring on health care utilization and patients' wellbeing.

Barriers to and Facilitators of Using a One Button Tracker and Web-Based Data Analytics Tool for Personal Science: Exploratory Study

Background

Individuals’ self-tracking of subjectively experienced phenomena related to health can be challenging, as current options for instrumentation often involve too much effort in the moment or rely on retrospective self-reporting, which is likely to impair accuracy and compliance.

Objective

This study aims to assess the usability and perceived usefulness of low-effort, in-the-moment self-tracking using simple instrumentation and to establish the amount of support needed when using this approach.

Methods

In this exploratory study, the One Button Tracker—a press-button device that records time stamps and durations of button presses—was used for self-tracking. A total of 13 employees of an academic medical center chose a personal research question and used the One Button Tracker to actively track specific subjectively experienced phenomena for 2 to 4 weeks. To assess usability and usefulness, we combined qualitative data from semistructured interviews with quantitative results from the System Usability Scale.

Results

In total, 29 barriers and 15 facilitators for using the One Button Tracker were found. Ease of use was the most frequently mentioned facilitator. The One Button Tracker’s usability received a median System Usability Scale score of 75.0 (IQR 42.50), which is considered as good usability. Participants experienced effects such as an increased awareness of the tracked phenomenon, a confirmation of personal knowledge, a gain of insight, and behavior change. Support and guidance during all stages of the self-tracking process were judged as valuable.

Conclusions

The low-effort, in-the-moment self-tracking of subjectively experienced phenomena has been shown to support personal knowledge gain and health behavior change for people with an interest in health promotion. After addressing barriers and formally validating the collected data, self-tracking devices may well be helpful for additional user types or health questions.

Patient Perspectives of a Non-Invasive Telemonitoring Tool for Patients with Heart Failure

Aim

Advancements in telemonitoring (TM) for patients with heart failure (HF) are incongruous because of the effect of TM intervention and various types of TM. This study aimed to clarify patients’ experiences in using the TM tool.

Methods

This was a qualitative study. Data were evaluated using qualitative content analysis. Nine patients with heart failure → HF participated and completed the 1-month study period.

Results

The experience of this TM tool was determined using semi-structured interviews followed by qualitative content analysis. Finally, five themes emerged: habituation of self-care behaviour, no burden for use, a feeling of security, additional functions and advice rather than guidance.

Conclusion

This TM tool is easy to use and has the potential to promote self-management in patients with HF. Based on the aforementioned findings, we revised this tool and added some functions and will perform additional tests.

MOBILE APP MAPPING FOR HEART FAILURE CARE: A SCOPING REVIEW

ABSTRACT Objective: to map mobile apps for care in heart failure. Method: this is a scoping review based on the method proposed by the Joanna Briggs Institute. The following research question was used: which mobile apps on heart failure are used by health professionals, people with heart failure and their family/caregivers? Health bases and portals were analyzed through the search with the descriptors “Heart Failure”, “Mobile Applications”, “Patients”, “Health Personnel”, “Family” and “Caregivers” and the keyword “Applications”. Forty-seven studies were selected for analysis. Results: a total of 47 published studies were analyzed, which allowed mapping 39 mobile applications from four continents, among which 20 (51.3%) were intended for co-management and 19 (48.7%) had as target population patients and health professionals; 23 (58.9%) applications did not use theoretical framework for its construction. The prevalent theme and resources involved daily care (36; 92.3%) and data management (37; 94.9%), respectively. Conclusion: the themes and resources of the applications assisted patients, family members and professionals in heart failure management. However, a gap was identified in several themes involving individuals and their surroundings, essential for comprehensive care.

Use of mobile applications for heart failure self-management: a systematic review of experimental and qualitative studies (Preprint)

Background

Heart failure self-management is essential to avoid decompensation and readmissions. Mobile apps seem promising in supporting heart failure self-management, and there has been a rapid growth in publications in this area. However, to date, systematic reviews have mostly focused on remote monitoring interventions using nonapp types of mobile technologies to transmit data to health care providers, rarely focusing on supporting patient self-management of heart failure.

Objective

This study aims to systematically review the evidence on the effect of heart failure self-management apps on health outcomes, patient-reported outcomes, and patient experience.

Methods

Four databases (PubMed, Embase, CINAHL, and PsycINFO) were searched for studies examining interventions that comprised a mobile app targeting heart failure self-management and reported any health-related outcomes or patient-reported outcomes or perspectives published from 2008 to December 2021. The studies were independently screened. The risk of bias was appraised using Cochrane tools. We performed a narrative synthesis of the results. The protocol was registered on PROSPERO (International Prospective Register of Systematic Reviews; CRD42020158041).

Results

A total of 28 articles (randomized controlled trials [RCTs]: n=10, 36%), assessing 23 apps, and a total of 1397 participants were included. The most common app features were weight monitoring (19/23, 83%), symptom monitoring (18/23, 78%), and vital sign monitoring (15/23, 65%). Only 26% (6/23) of the apps provided all guideline-defined core components of heart failure self-management programs: education, symptom monitoring, medication support, and physical activity support. RCTs were small, involving altogether 717 participants, had ≤6 months of follow-up, and outcomes were predominantly self-reported. Approximately 20% (2/10) of RCTs reported a significant improvement in their primary outcomes: heart failure knowledge (P=.002) and self-care (P=.004). One of the RCTs found a significant reduction in readmissions (P=.02), and 20% (2/10) of RCTs reported higher unplanned clinic visits. Other experimental studies also found significant improvements in knowledge, self-care, and readmissions, among others. Less than half of the studies involved patients and clinicians in the design of apps. Engagement with the intervention was poorly reported, with only 11% (3/28) of studies quantifying app engagement metrics such as frequency of use over the study duration. The most desirable app features were automated self-monitoring and feedback, personalization, communication with clinicians, and data sharing and integration.

Conclusions

Mobile apps may improve heart failure self-management; however, more robust evaluation studies are needed to analyze key end points for heart failure. On the basis of the results of this review, we provide a road map for future studies in this area.

Patient Perspectives on Innovative Telemonitoring Enhanced Care Program for Chronic Heart Failure (ITEC-CHF): Usability Study

Background

Telemonitoring enables care providers to remotely support outpatients in self-managing chronic heart failure (CHF), but little is known about the usability and patients’ willingness to engage with this technology.

Objective

This study aims to evaluate feedback from patients with CHF following participation in the Innovative Telemonitoring Enhanced Care program for CHF (ITEC-CHF) study.

Methods

The telemonitoring intervention consisted of three components: remote weight monitoring, structured telephone support, and nurse-led collaborative care. Participants were provided with electronic weighing scales (W550; ForaCare), and a computer tablet (Galaxy Tab A; Samsung). They were asked to weigh themselves on the provided scales daily. Telemonitoring was integrated with a personal assistance call service and a nurse care service according to their workflows in usual care. Feedback on the usability of ITEC-CHF was collected via survey from study participants following 6 months of receiving telemonitoring care for their body weight. Survey responses were provided on a 5-point Likert scale and through open-ended questions to determine participants’ perceived benefits and barriers to using ITEC-CHF.

Results

A total of 67 participants (49/67, 73% male), with a mean age of 69.8 (SD 12.4) years completed the survey. The majority of participants agreed or strongly agreed that the ITEC-CHF program was easy to use (61/67, 91%), easy to navigate (51/65, 78%), useful (59/65, 91%), and made them feel more confident in managing their weight (57/67, 85%). Themes related to participants’ perceptions of telemonitoring included increased support for early intervention of clinical deterioration, improved compliance to daily weighing, a sense of reassurance, and improved self-care and accountability, among others.

Conclusions

ITEC-CHF was rated highly on usability and was well accepted by users as part of their routine self-management activities. Participants were willing to use telemonitoring because they perceived a broad spectrum of benefits for CHF management.

Trial Registration

Australian New Zealand Clinical Trial Registry ID ACTRN 12614000916640; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366691.

Voice Interface Technology Adoption by Patients With Heart Failure: Pilot Comparison Study

Background

Heart failure (HF) is associated with high mortality rates and high costs, and self-care is crucial in the management of the condition. Telehealth can promote patients’ self-care while providing frequent feedback to their health care providers about the patient’s compliance and symptoms. A number of technologies have been considered in the literature to facilitate telehealth in patients with HF. An important factor in the adoption of these technologies is their ease of use. Conversational agent technologies using a voice interface can be a good option because they use speech recognition to communicate with patients.

Objective

The aim of this paper is to study the engagement of patients with HF with voice interface technology. In particular, we investigate which patient characteristics are linked to increased technology use.

Methods

We used data from two separate HF patient groups that used different telehealth technologies over a 90-day period. Each group used a different type of voice interface; however, the scripts followed by the two technologies were identical. One technology was based on Amazon’s Alexa (Alexa+), and in the other technology, patients used a tablet to interact with a visually animated and voice-enabled avatar (Avatar). Patient engagement was measured as the number of days on which the patients used the technology during the study period. We used multiple linear regression to model engagement with the technology based on patients’ demographic and clinical characteristics and past technology use.

Results

In both populations, the patients were predominantly male and Black, had an average age of 55 years, and had HF for an average of 7 years. The only patient characteristic that was statistically different (P=.008) between the two populations was the number of medications they took to manage HF, with a mean of 8.7 (SD 4.0) for Alexa+ and 5.8 (SD 3.4) for Avatar patients. The regression model on the combined population shows that older patients used the technology more frequently (an additional 1.19 days of use for each additional year of age; P=.004). The number of medications to manage HF was negatively associated with use (−5.49; P=.005), and Black patients used the technology less frequently than other patients with similar characteristics (−15.96; P=.08).

Conclusions

Older patients’ higher engagement with telehealth is consistent with findings from previous studies, confirming the acceptability of technology in this subset of patients with HF. However, we also found that a higher number of HF medications, which may be correlated with a higher disease burden, is negatively associated with telehealth use. Finally, the lower engagement of Black patients highlights the need for further study to identify the reasons behind this lower engagement, including the possible role of social determinants of health, and potentially create technologies that are better tailored for this population.

Effects of a Transitional Telehealth Program on Functional Status, Rehospitalization, and Satisfaction With Care in Thai Patients with Heart Failure

Limited functional status is a common health problem in patients living with heart failure (HF), which often requires rehospitalization.Home-based transitional telehealth programs (TTPs) focused on health monitoring, education, promotion of self-management, and multidisciplinary team consultation have been shown to improve functional status and satisfaction with care while reducing rehospitalization rates in this population. Nonetheless, these variables and outcomes have yet to be assessed in a Thai patient with HF. Thus, the aim of this study was to investigate the effectiveness of a TTP on functional status, rehospitalization, and satisfaction with care in Thai patients with HF. Eligible participants (N = 146) were randomly assigned to either the control or TTP group. The TTP included in-hospital discharge planning and 6-week telemonitoring via a mobile phone application to provide follow-up home care. Data on the outcome variables were collected at 6 and 8 weeks post-enrollment and analyzed by descriptive statistics, independent t-tests, repeated measures ANOVA, and Z-tests. Functional status and satisfaction with care scores in the TTP group were significantly higher than those of the control group, and rehospitalization rates in the TTP group were significantly lower than those of the control group at 6 and 8 weeks post-enrollment. Thus, the TTP effectively improved functional status, increased satisfaction with care, and reduced rehospitalization rates in Thai patients with HF. TTP implementation could be considered to improve the quality of transitional care in Thailand.

mHealth education interventions in heart failure

BACKGROUND

Heart failure (HF) is a chronic disease with significant impact on quality of life and presents many challenges to those diagnosed with the condition, due to a seemingly complex daily regimen of self-care which includes medications, monitoring of weight and symptoms, identification of signs of deterioration and follow-up and interaction with multiple healthcare services. Education is vital for understanding the importance of this regimen, and adhering to it. Traditionally, education has been provided to people with heart failure in a face-to-face manner, either in a community or a hospital setting, using paper-based materials or video/DVD presentations. In an age of rapidly-evolving technology and uptake of smartphones and tablet devices, mHealth-based technology (defined by the World Health Organization as mobile and wireless technologies to achieve health objectives) is an innovative way to provide health education which has the benefit of being able to reach people who are unable or unwilling to access traditional heart failure education programmes and services.

OBJECTIVES

To systematically review and quantify the potential benefits and harms of mHealth-delivered education for people with heart failure.

SEARCH METHODS

We performed an extensive search of bibliographic databases and registries (CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, IEEE Xplore, ClinicalTrials.gov and WHO International Clinical Trials Registry Platform (ICTRP) Search Portal), using terms to identify HF, education and mHealth. We searched all databases from their inception to October 2019 and imposed no restriction on language of publication.

SELECTION CRITERIA

We included studies if they were conducted as a randomised controlled trial (RCT), involving adults (≥ 18 years) with a diagnosis of HF. We included trials comparing mHealth-delivered education such as internet and web-based education programmes for use on smartphones and tablets (including apps) and other mobile devices, SMS messages and social media-delivered education programmes, versus usual HF care.

DATA COLLECTION AND ANALYSIS

Two review authors independently selected studies, assessed risks of bias, and extracted data from all included studies. We calculated the mean difference (MD) or standardised mean difference (SMD) for continuous data and the odds ratio (OR) for dichotomous data with a 95% confidence interval (CI). We assessed heterogeneity using the I2 statistic and assessed the quality of evidence using GRADE criteria.

MAIN RESULTS

We include five RCTs (971 participants) of mHealth-delivered education interventions for people with HF in this review. The number of trial participants ranged from 28 to 512 participants. Mean age of participants ranged from 60 years to 75 years, and 63% of participants across the studies were men. Studies originated from Australia, China, Iran, Sweden, and The Netherlands. Most studies included participants with symptomatic HF, NYHA Class II - III. Three studies addressed HF knowledge, revealing that the use of mHealth-delivered education programmes showed no evidence of a difference in HF knowledge compared to usual care (MD 0.10, 95% CI -0.2 to 0.40, P = 0.51, I2 = 0%; 3 studies, 411 participants; low-quality evidence). One study assessing self-efficacy reported that both study groups had high levels of self-efficacy at baseline and uncertainty in the evidence for the intervention (MD 0.60, 95% CI -0.57 to 1.77; P = 0.31; 1 study, 29 participants; very low-quality evidence).Three studies evaluated HF self-care using different scales. We did not pool the studies due to the heterogenous nature of the outcome measures, and the evidence is uncertain. None of the studies reported adverse events. Four studies examined health-related quality of life (HRQoL). There was uncertainty in the evidence for the use of mHealth-delivered education on HRQoL (MD -0.10, 95% CI -2.35 to 2.15; P = 0.93, I2 = 61%; 4 studies, 942 participants; very low-quality evidence). Three studies reported on HF-related hospitalisation. The use of mHealth-delivered education may result in little to no difference in HF-related hospitalisation (OR 0.74, 95% CI 0.52 to 1.06; P = 0.10, I2 = 0%; 3 studies, 894 participants; low-quality evidence). We downgraded the quality of the studies due to limitations in study design and execution, heterogeneity, wide confidence intervals and fewer than 500 participants in the analysis.

AUTHORS' CONCLUSIONS

We found that the use of mHealth-delivered educational interventions for people with HF shows no evidence of a difference in HF knowledge; uncertainty in the evidence for self-efficacy, self-care and health-related quality of life; and may result in little to no difference in HF-related hospitalisations. The identification of studies currently underway and those awaiting classification indicate that this is an area of research from which further evidence will emerge in the short and longer term.

Value of Eye-Tracking Data for Classification of Information Processing-Intensive Handling Tasks: Quasi-Experimental Study on Cognition and User Interface Design

Background

In order to give a wide range of people the opportunity to ensure and support home care, one approach is to develop medical devices that are as user-friendly as possible. This allows nonexperts to use medical devices that were originally too complicated to use. For a user-centric development of such medical devices, it is essential to understand which user interface design best supports patients, caregivers, and health care professionals.

Objective

Using the benefits of mobile eye tracking, this work aims to gain a deeper understanding of the challenges of user cognition. As a consequence, its goal is to identify the obstacles to the usability of the features of two different designs of a single medical device user interface. The medical device is a patient assistance device for home use in peritoneal dialysis therapy.

Methods

A total of 16 participants, with a subset of seniors (8/16, mean age 73.7 years) and young adults (8/16, mean age 25.0 years), were recruited and participated in this study. The handling cycle consisted of seven main tasks. Data analysis started with the analysis of task effectiveness for searching for error-related tasks. Subsequently, the in-depth gaze data analysis focused on these identified critical tasks. In order to understand the challenges of user cognition in critical tasks, gaze data were analyzed with respect to individual user interface features of the medical device system. Therefore, it focused on the two dimensions of dwell time and fixation duration of the gaze.

Results

In total, 97% of the handling steps for design 1 and 96% for design 2 were performed correctly, with the main challenges being task 1 insert, task 2 connect, and task 6 disconnect for both designs. In order to understand the two analyzed dimensions of the physiological measurements simultaneously, the authors propose a new graphical representation. It distinguishes four different patterns to compare the eye movements associated with the two designs. The patterns identified for the critical tasks are consistent with the results of the task performance.

Conclusions

This study showed that mobile eye tracking provides insights into information processing in intensive handling tasks related to individual user interface features. The evaluation of each feature of the user interface promises an optimal design by combining the best found features. In this way, manufacturers are able to develop products that can be used by untrained people without prior knowledge. This would allow home care to be provided not only by highly qualified nurses and caregivers, but also by patients themselves, partners, children, or neighbors.

Methods and Measures Used to Evaluate Patient-Operated Mobile Health Interventions: Scoping Literature Review

BACKGROUND

Despite the prevalence of mobile health (mHealth) technologies and observations of their impacts on patients' health, there is still no consensus on how best to evaluate these tools for patient self-management of chronic conditions. Researchers currently do not have guidelines on which qualitative or quantitative factors to measure or how to gather these reliable data.

OBJECTIVE

This study aimed to document the methods and both qualitative and quantitative measures used to assess mHealth apps and systems intended for use by patients for the self-management of chronic noncommunicable diseases.

METHODS

A scoping review was performed, and PubMed, MEDLINE, Google Scholar, and ProQuest Research Library were searched for literature published in English between January 1, 2015, and January 18, 2019. Search terms included combinations of the description of the intention of the intervention (eg, self-efficacy and self-management) and description of the intervention platform (eg, mobile app and sensor). Article selection was based on whether the intervention described a patient with a chronic noncommunicable disease as the primary user of a tool or system that would always be available for self-management. The extracted data included study design, health conditions, participants, intervention type (app or system), methods used, and measured qualitative and quantitative data.

RESULTS

A total of 31 studies met the eligibility criteria. Studies were classified as either those that evaluated mHealth apps (ie, single devices; n=15) or mHealth systems (ie, more than one tool; n=17), and one study evaluated both apps and systems. App interventions mainly targeted mental health conditions (including Post-Traumatic Stress Disorder), followed by diabetes and cardiovascular and heart diseases; among the 17 studies that described mHealth systems, most involved patients diagnosed with cardiovascular and heart disease, followed by diabetes, respiratory disease, mental health conditions, cancer, and multiple illnesses. The most common evaluation method was collection of usage logs (n=21), followed by standardized questionnaires (n=18) and ad-hoc questionnaires (n=13). The most common measure was app interaction (n=19), followed by usability/feasibility (n=17) and patient-reported health data via the app (n=15).

CONCLUSIONS

This review demonstrates that health intervention studies are taking advantage of the additional resources that mHealth technologies provide. As mHealth technologies become more prevalent, the call for evidence includes the impacts on patients' self-efficacy and engagement, in addition to traditional measures. However, considering the unstructured data forms, diverse use, and various platforms of mHealth, it can be challenging to select the right methods and measures to evaluate mHealth technologies. The inclusion of app usage logs, patient-involved methods, and other approaches to determine the impact of mHealth is an important step forward in health intervention research. We hope that this overview will become a catalogue of the possible ways in which mHealth has been and can be integrated into research practice.

Elements of Social Convoy Theory in Mobile Health for Palliative Care: Scoping Review

BACKGROUND

Mobile health (mHealth) provides a unique modality for improving access to and awareness of palliative care among patients, families, and caregivers from diverse backgrounds. Some mHealth palliative care apps exist, both commercially available and established by academic researchers. However, the elements of family support and family caregiving tools offered by these early apps is unknown.

OBJECTIVE

The objective of this scoping review was to use social convoy theory to describe the inclusion and functionality of family, social relationships, and caregivers in palliative care mobile apps.

METHODS

Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Review guidelines, a systematic search of palliative care mHealth included (1) research-based mobile apps identified from academic searches published between January 1, 2010, and March 31, 2019 and (2) commercially available apps for app stores in April 2019. Two reviewers independently assessed abstracts, app titles, and descriptions against the inclusion and exclusion criteria. Abstracted data covered app name, research team or developer, palliative care element, target audience, and features for family support and caregiving functionality as defined by social convoy theory.

RESULTS

Overall, 10 articles describing 9 individual research-based apps and 22 commercially available apps were identified. Commercially available apps were most commonly designed for both patients and social convoys, whereas the majority of research apps were designed for patient use only.

CONCLUSIONS

Results suggest there is an emerging presence of apps for patients and social convoys receiving palliative care; however, there are many needs for developers and researchers to address in the future. Although palliative care mHealth is a growing field, additional research is needed for apps that embrace a team approach to information sharing, target family- and caregiver-specific issues, promote access to palliative care, and are comprehensive of palliative needs.

Automated analysis of free-text comments and dashboard representations in patient experience surveys: a multimethod co-design study

Background

Patient experience surveys (PESs) often include informative free-text comments, but with no way of systematically, efficiently and usefully analysing and reporting these. The National Cancer Patient Experience Survey (CPES), used to model the approach reported here, generates > 70,000 free-text comments annually.

Main aim

To improve the use and usefulness of PES free-text comments in driving health service changes that improve the patient experience.

Secondary aims

(1) To structure CPES free-text comments using rule-based information retrieval (IR) (‘text engineering’), drawing on health-care domain-specific gazetteers of terms, with in-built transferability to other surveys and conditions; (2) to display the results usefully for health-care professionals, in a digital toolkit dashboard display that drills down to the original free text; (3) to explore the usefulness of interdisciplinary mixed stakeholder co-design and consensus-forming approaches in technology development, ensuring that outputs have meaning for all; and (4) to explore the usefulness of Normalisation Process Theory (NPT) in structuring outputs for implementation and sustainability.

Design

A scoping review, rapid review and surveys with stakeholders in health care (patients, carers, health-care providers, commissioners, policy-makers and charities) explored clinical dashboard design/patient experience themes. The findings informed the rules for the draft rule-based IR [developed using half of the 2013 Wales CPES (WCPES) data set] and prototype toolkit dashboards summarising PES data. These were refined following mixed stakeholder, concept-mapping workshops and interviews, which were structured to enable consensus-forming ‘co-design’ work. IR validation used the second half of the WCPES, with comparison against its manual analysis; transferability was tested using further health-care data sets. A discrete choice experiment (DCE) explored which toolkit features were preferred by health-care professionals, with a simple cost–benefit analysis. Structured walk-throughs with NHS managers in Wessex, London and Leeds explored usability and general implementation into practice.

Key outcomes

A taxonomy of ranked PES themes, a checklist of key features recommended for digital clinical toolkits, rule-based IR validation and transferability scores, usability, and goal-oriented, cost–benefit and marketability results. The secondary outputs were a survey, scoping and rapid review findings, and concordance and discordance between stakeholders and methods.

Results

(1) The surveys, rapid review and workshops showed that stakeholders differed in their understandings of the patient experience and priorities for change, but that they reached consensus on a shortlist of 19 themes; six were considered to be core; (2) the scoping review and one survey explored the clinical toolkit design, emphasising that such toolkits should be quick and easy to use, and embedded in workflows; the workshop discussions, the DCE and the walk-throughs confirmed this and foregrounded other features to form the toolkit design checklist; and (3) the rule-based IR, developed using noun and verb phrases and lookup gazetteers, was 86% accurate on the WCPES, but needs modification to improve this and to be accurate with other data sets. The DCE and the walk-through suggest that the toolkit would be well accepted, with a favourable cost–benefit ratio, if implemented into practice with appropriate infrastructure support.

Limitations

Small participant numbers and sampling bias across component studies. The scoping review studies mostly used top-down approaches and focused on professional dashboards. The rapid review of themes had limited scope, with no second reviewer. The IR needs further refinement, especially for transferability. New governance restrictions further limit immediate use.

Conclusions

Using a multidisciplinary, mixed stakeholder, use of co-design, proof of concept was shown for an automated display of patient experience free-text comments in a way that could drive health-care improvements in real time. The approach is easily modified for transferable application.

Future work

Further exploration is needed of implementation into practice, transferable uses and technology development co-design approaches.

Funding

The National Institute for Health Research Health Services and Delivery Research programme.

Connected Health Technology for Cardiovascular Disease Prevention and Management

PURPOSE OF THE REVIEW

Advances in computing power and wireless technologies have reshaped our approach to patient monitoring. Medical grade sensors and apps that were once restricted to hospitals and specialized clinic are now widely available. Here, we review the current evidence supporting the use of connected health technologies for the prevention and management of cardiovascular disease in an effort to highlight gaps and future opportunities for innovation.

RECENT FINDINGS

Initial studies in connected health for cardiovascular disease prevention and management focused primarily on activity tracking and blood pressure monitoring but have since expanded to include a full panoply of novel sensors and pioneering smartphone apps with targeted interventions in diet, lipid management and risk assessment, smoking cessation, cardiac rehabilitation, heart failure, and arrhythmias. While outfitting patients with sensors and devices alone is infrequently a lasting solution, monitoring programs that include personalized insights based on patient-level data are more likely to lead to improved outcomes. Advances in this space have been driven by patients and researchers while healthcare systems remain slow to fully integrate and adequately adapt these new technologies into their workflows. Cardiovascular disease prevention and management continue to be key focus areas for clinicians and researchers in the connected health space. Exciting progress has been made though studies continue to suffer from small sample size and limited follow-up. Efforts that combine home patient monitoring, engagement, and personalized feedback are the most promising. Ultimately, combining patient-level ambulatory sensor data, electronic health records, and genomics using machine learning analytics will bring precision medicine closer to reality.

Patients' Experiences of Using a Consumer mHealth App for Self-Management of Heart Failure: Mixed-Methods Study

BACKGROUND

To support the self-management of heart failure, a team of hospital clinicians, patients, and family caregivers have co-designed the consumer mobile health app, Care4myHeart.

OBJECTIVE

This research aimed to determine patient experiences of using the app to self-manage heart failure.

METHODS

Patients with heart failure used the app for 14 days on their own smart device in a home setting, following which a mixed-methods evaluation was performed. Eight patients were recruited, of whom six completed the Mobile Application Rating Scale and attended an interview.

RESULTS

The overall app quality score was "acceptable" with 3.53 of 5 points, with the aesthetics (3.83/5) and information (3.78/5) subscales scoring the highest. The lowest mean score was in the app-specific subscale representing the perceived impact on health behavior change (2.53/5). Frequently used features were weight and fluid restriction tracking, with graphical representation of data particularly beneficial for improved self-awareness and ongoing learning. The use of technology for self-management will fundamentally differ from current practices and require a change in daily routines. However, app use was correlated with potential utility for daily management of illness with benefits of accurate recording and review of personal health data and as a communication tool for doctors to assist with care planning, as all medical information is available in one place. Technical considerations included participants' attitudes toward technology, functionality and data entry issues, and relatively minor suggested changes.

CONCLUSIONS

The findings from this usability study suggest that a significant barrier to adoption is the lack of integration of technology into everyday life in the context of already established disease self-management routines. Future studies should explore the barriers to adoption and sustainability of consumer mobile health interventions for chronic conditions, particularly whether introducing such apps is more beneficial at the commencement of a self-management regimen.

Mobile Health Apps: Improving Usability for Older Adult Users

With smartphone use among older populations on the rise, older adults have increased access to health-focused mobile apps. Despite their potential benefits for managing health, currently no guidelines exist for designing these apps specifically for older adult users. We evaluated the usability of one medication management app and two congestive heart failure management apps using cognitive walkthroughs, heuristic analysis, and user testing. We identified design issues that may affect usability for older users, including poor navigation, small button sizes, and inadequate data visualizations. We provide guidelines for developers of health apps to facilitate use by older adults.

A Cloud-Based Virtual Outpatient Clinic for Patient-Centered Care: Proof-of-Concept Study

BACKGROUND

Most electronic health (eHealth) interventions offered to patients serve a single purpose and lack integration with other tools or systems. This is problematic because the majority of patients experience comorbidity and chronic disease, see multiple specialists, and therefore have different needs regarding access to patient data, communication with peers or providers, and self-monitoring of vital signs. A multicomponent digital health cloud service that integrates data sharing, collection, and communication could facilitate patient-centered care in combination with a hospital patient portal and care professionals.

OBJECTIVE

This study aimed to assess the feasibility and functionality of a new cloud-based and multicomponent outpatient clinic, the "Virtual Outpatient Clinic" (VOC).

METHODS

The VOC consists of 6 digital tools that facilitate self-monitoring (blood pressure, weight, and pain) and communication with peers and providers (chat and videoconferencing) connected to a cloud-based platform and the hospital patient portal to facilitate access to (self-collected) medical data. In this proof-of-concept study, 10 patients from both Departments of Internal Medicine and Dermatology (N=20) used all options of the VOC for 6 weeks. An eNurse offered support to participants during the study. We assessed the feasibility, usage statistics, content, adherence, and identified technical issues. Moreover, we conducted qualitative interviews with all participants by following a standard interview guide to identify user experiences, including barriers, facilitators, and potential effects.

RESULTS

Most participants successfully used all options of the VOC and were positive about different tools and apps and the integral availability of their information. The adherence was 37% (7/19) for weight scale, 58% (11/19) for blood pressure monitor, and 70% (14/20) and 85% (17/20) for pain score and daily questions, respectively. The adherence for personal health record was 65% (13/20) and 60% (12/20) for the patient portal system. Qualitative data showed that performance and effort expectancy scored high among participants, indicating that using the VOC is convenient, easy, and time-saving.

CONCLUSIONS

The VOC is a promising integrated Web-based technology that combines self-management, data sharing, and communication between patients and professionals. The system can be personalized by connecting various numbers of components, which could make it a relevant tool for other patient groups. Before a system, such as the VOC, can be implemented in daily practice, prospective studies focused on evaluating outcomes, costs, and patient-centeredness are needed.

Mobile Phone Apps to Support Heart Failure Self-Care Management: Integrative Review

Background

With an explosive growth in mobile health, an estimated 500 million patients are potentially using mHealth apps for supporting health and self-care of chronic diseases. Therefore, this review focused on mHealth apps for use among patients with heart failure.

Objective

The aim of this integrative review was to identify and assess the functionalities of mHealth apps that provided usability and efficacy data and apps that are commercially available without supporting data, all of which are to support heart failure self-care management and thus impact heart failure outcomes.

Methods

A search of published, peer-reviewed literature was conducted for studies of technology-based interventions that used mHealth apps specific for heart failure. The initial database search yielded 8597 citations. After filters for English language and heart failure, the final 487 abstracts was reviewed. After removing duplicates, a total of 18 articles that tested usability and efficacy of mobile apps for heart failure self-management were included for review. Google Play and Apple App Store were searched with specified criteria to identify mHealth apps for heart failure. A total of 26 commercially available apps specific for heart failure were identified and rated using the validated Mobile Application Rating Scale.

Results

The review included studies with low-quality design and sample sizes ranging from 7 to 165 with a total sample size of 847 participants from all 18 studies. Nine studies assessed usability of the newly developed mobile health system. Six of the studies included are randomized controlled trials, and 4 studies are pilot randomized controlled trials with sample sizes of fewer than 40. There were inconsistencies in the self-care components tested, increasing bias. Thus, risk of bias was assessed using the Cochrane Collaboration’s tool for risk of selection, performance, detection, attrition, and reporting biases. Most studies included in this review are underpowered and had high risk of bias across all categories. Three studies failed to provide enough information to allow for a complete assessment of bias, and thus had unknown or unclear risk of bias. This review on the commercially available apps demonstrated many incomplete apps, many apps with bugs, and several apps with low quality.

Conclusions

The heterogeneity of study design, sample size, intervention components, and outcomes measured precluded the performance of a systematic review or meta-analysis, thus introducing bias of this review. Although the heart failure–related outcomes reported in this review vary, they demonstrated trends toward making an impact and offer a potentially cost-effective solution with 24/7 access to symptom monitoring as a point of care solution, promoting patient engagement in their own home care.

Deep learning for cardiac computer-aided diagnosis: benefits, issues & solutions

Cardiovascular diseases are one of the top causes of deaths worldwide. In developing nations and rural areas, difficulties with diagnosis and treatment are made worse due to the deficiency of healthcare facilities. A viable solution to this issue is telemedicine, which involves delivering health care and sharing medical knowledge at a distance. Additionally, mHealth, the utilization of mobile devices for medical care, has also proven to be a feasible choice. The integration of telemedicine, mHealth and computer-aided diagnosis systems with the fields of machine and deep learning has enabled the creation of effective services that are adaptable to a multitude of scenarios. The objective of this review is to provide an overview of heart disease diagnosis and management, especially within the context of rural healthcare, as well as discuss the benefits, issues and solutions of implementing deep learning algorithms to improve the efficacy of relevant medical applications.