Features and usability assessment of a patient-centered mobile application (HeartMapp) for self-management of heart failure

Design Requirements for Cardiac Telerehabilitation Technologies Supporting Athlete Values: Qualitative Interview Study

BACKGROUND

Cardiac telerehabilitation (CTR) interventions can provide accessible and affordable remote rehabilitation services. However, as cardiac rehabilitation (CR) primarily targets inactive patients, little is known about the experiences with CR of highly active patients (ie, recreational athletes or, simply, athletes) with established coronary artery disease. Consequently, existing CTR interventions do not address the specific needs of the athletic subpopulation. Understanding the needs and values of athletes is crucial for designing meaningful CTR interventions that enhance user acceptance and engagement, thereby facilitating effective rehabilitation for this patient subgroup.

OBJECTIVE

This study aimed to inform the design of technologies that facilitate CTR for athletes. We intended to identify athletes' values related to CR, including health and sports tracking, as well as high-level requirements for technologies that can facilitate the CTR of athletes according to the identified values.

METHODS

We used value-sensitive design with a human-centric design approach to elicit design requirements for CTR that can serve athletes with established coronary artery disease. To identify athletes' values, we conducted 25 value-oriented semistructured interviews with 15 athletic patients and 10 health care professionals involved in CR programs. In a second phase, we conducted 6 card-sorting focus group sessions with 13 patients and 7 health care professionals to identify desired CTR features. Finally, we derived high-level CTR technology requirements connected to the athletes' needs and values.

RESULTS

We defined 12 athlete values divided into 3 categories: body centric, care centric, and data and technology centric. We clustered findings from the card-sorting activity into CTR technology requirements, such as remotely monitored sport-specific training and training data representations next to clinical limitations, and paired them with corresponding values.

CONCLUSIONS

Athletes have distinct values and health goals in CR compared to general populations targeted by CTR interventions. Designing patient-centric CTR interventions that address these needs is crucial to support optimal recovery, safe return to sports, and adherence to CTR technologies in the home environment.

Reducing sedentary behavior improves depressive symptoms among patients with heart failure enrolled in a home-based mobile health app cardiac rehabilitation

BACKGROUND

Depressive symptoms are common, worsening heart failure (HF) progression and reducing quality of life. While supervised structured exercise training is effective for managing depressive symptoms, it often demands a substantial time commitment or intensive activity that may discourage participation.

OBJECTIVE

Evaluate the impacts of reducing sedentary time with short bouts of light physical activities or greater intensity levels on depressive symptoms after HF patients' enrollment in a home-based intervention.

METHODS

A total of 127 HF patients participated in an experimental two-group design, randomly allocated to either delayed or immediate decreasing sedentary time intervention. The immediate group started the intervention immediately, while the delayed group began after the first group finished their intervention. The 8-week intervention, guided by the Theory of Planned Behavior, focused on interrupting 30 min of sedentary behavior with short bouts of light- or greater intensity physical activities. Demographic and clinical variables were collected at baseline. Depressive symptoms were assessed at baseline, pre-intervention, and post-intervention. Physical activity (daily steps) was monitored daily during the study period using the Samsung mobile health app.

RESULTS

Both groups demonstrated reduced sedentary time during the intervention, with improvements in HF symptom burden. Repeated measures analysis of variance revealed a significant reduction in depressive symptoms in both groups post-intervention, with a greater reduction seen in the immediate group before the delayed group began the intervention.

CONCLUSION

The study highlights the effectiveness of interrupting sedentary behavior with light- or greater intensity activities in managing depressive symptoms among HF patients. The home-based intervention, facilitated by mobile technology, provides a feasible and accessible approach to improving mental well-being.

CLINICAL RELEVANCE

The findings support the broader implementation of home-based interventions addressing sedentary time reduction as a valuable strategy for enhancing the mental health of HF patients, particularly those facing challenges with traditional rehabilitation programs or intense exercise.

The paradox of convenience: how information overload in mHealth apps leads to medical service overuse

Background

Mobile health applications (mHealth) have become an indispensable tool in the healthcare industry to provide users with efficient and convenient health services. However, information overload has led to significant information overload problems in mHealth applications, which may further lead to overuse of medical services.

Methods

The purpose of this study was to explore the relationship between information overload and overuse of medical services in mHealth applications through health belief model (HBM). Data were collected from 1,494 respondents who were sampled through a simple random approach. A structured questionnaire was used as the instrument for data collection from mobile APP users in Guangdong Province between February 4, 2024, and February 20, 2024. Structural equation modeling (SEM) was used to analyze the data to investigate the effects of information overload on users' perceived severity, susceptibility, treatment benefits, barriers, self-efficacy, and action cues, which further influence the overuse of health care services.

Results

The study found that information overload significantly affected users' perceived severity, susceptibility, treatment benefits, barriers, self-efficacy, and action cues, and subsequently affected overuse of health care services. These results provide valuable insights for mHealth application developers, healthcare providers, and policy makers.

Conclusion

This study highlights the importance of effectively managing information delivery in mHealth applications to reduce the risk of overuse of healthcare services. The study not only highlights the dark side of information overload in mHealth applications, but also provides a framework to understand and address the challenges associated with information overload and service overuse in the mHealth context.

Quality assessment of mHealth apps: a scoping review

Introduction

The number of mHealth apps has increased rapidly during recent years. Literature suggests a number of problems and barriers to the adoption of mHealth apps, including issues such as validity, usability, as well as data privacy and security. Continuous quality assessment and assurance systems might help to overcome these barriers. Aim of this scoping review was to collate literature on quality assessment tools and quality assurance systems for mHealth apps, compile the components of the tools, and derive overarching quality dimensions, which are potentially relevant for the continuous quality assessment of mHealth apps.

Methods

Literature searches were performed in Medline, EMBASE and PsycInfo. Articles in English or German language were included if they contained information on development, application, or validation of generic concepts of quality assessment or quality assurance of mHealth apps. Screening and extraction were carried out by two researchers independently. Identified quality criteria and aspects were extracted and clustered into quality dimensions.

Results

A total of 70 publications met inclusion criteria. Included publications contain information on five quality assurance systems and further 24 quality assessment tools for mHealth apps. Of these 29 systems/tools, 8 were developed for the assessment of mHealth apps for specific diseases, 16 for assessing mHealth apps for all fields of health and another five are not restricted to health apps. Identified quality criteria and aspects were extracted and grouped into a total of 14 quality dimensions, namely "information and transparency", "validity and (added) value", "(medical) safety", "interoperability and compatibility", "actuality", "engagement", "data privacy and data security", "usability and design", "technology", "organizational aspects", "social aspects", "legal aspects", "equity and equality", and "cost(-effectiveness)".

Discussion

This scoping review provides a broad overview of existing quality assessment and assurance systems. Many of the tools included cover only a few dimensions and aspects and therefore do not allow for a comprehensive quality assessment or quality assurance. Our findings can contribute to the development of continuous quality assessment and assurance systems for mHealth apps.

Systematic Review Registration

https://www.researchprotocols.org/2022/7/e36974/, International Registered Report Identifier, IRRID (DERR1-10.2196/36974).

Artificial Intelligence and Its Role in Diagnosing Heart Failure: A Narrative Review

Heart failure (HF) is prevalent globally. It is a dynamic disease with varying definitions and classifications due to multiple pathophysiologies and etiologies. The diagnosis, clinical staging, and treatment of HF become complex and subjective, impacting patient prognosis and mortality. Technological advancements, like artificial intelligence (AI), have been significant roleplays in medicine and are increasingly used in cardiovascular medicine to transform drug discovery, clinical care, risk prediction, diagnosis, and treatment. Medical and surgical interventions specific to HF patients rely significantly on early identification of HF. Hospitalization and treatment costs for HF are high, with readmissions increasing the burden. AI can help improve diagnostic accuracy by recognizing patterns and using them in multiple areas of HF management. AI has shown promise in offering early detection and precise diagnoses with the help of ECG analysis, advanced cardiac imaging, leveraging biomarkers, and cardiopulmonary stress testing. However, its challenges include data access, model interpretability, ethical concerns, and generalizability across diverse populations. Despite these ongoing efforts to refine AI models, it suggests a promising future for HF diagnosis. After applying exclusion and inclusion criteria, we searched for data available on PubMed, Google Scholar, and the Cochrane Library and found 150 relevant papers. This review focuses on AI's significant contribution to HF diagnosis in recent years, drastically altering HF treatment and outcomes.

Digital Literacy and Associated Factors in Older Adults Living in Urban South Korea: A Qualitative Study

This study aimed to explore digital literacy among community-dwelling older adults in urban South Korea. A semistructured interview guide was developed using the Digital Competence ( 2.0 framework, which emphasizes the competencies for full digital participation in five categories: information and data literacy, communication and collaboration, content creation, safety, and problem-solving. The data were analyzed using combined inductive and deductive content analysis. Inductive analysis identified three main categories: perceived ability to use digital technology, responses to digital technology, and contextual factors. In the results of deductive analysis, participants reported varying abilities in using digital technologies for information and data literacy, communication or collaboration, and problem-solving. However, their abilities were limited in handling the safety or security of digital technology and lacked in creating digital content. Responses to digital technology contain subcategories of perception (positive or negative) and behavior (trying or avoidance). Regarding contextual factors, aging-related physical and cognitive changes were identified as barriers to digital literacy. The influence of families or peers was viewed as both a facilitator and a barrier. Our participants recognized the importance of using digital devices to keep up with the trend of digitalization, but their digital literacy was mostly limited to relatively simple levels.

Effectiveness of support from community health workers on the sustained use of a wearable monitoring device among community-dwelling older adults: A randomized trial protocol

BACKGROUND

Wearable monitoring devices, such as smartwatches and fitness bands, are health technologies for enhancing self-care management among community-dwelling older adults. While the evidence suggests that these devices can promote health, older adults often struggle to use them over the long term. Community health workers can effectively motivate older adults to change their health behaviors. This study proposes an intervention involving community health workers as peer supporters to promote sustained daily use of wearable monitoring devices among community-dwelling older adults.

METHODS

The intervention group in this randomized controlled trial will receive the Live with Wearable Monitoring Device program from trained community health workers with the support of a nurse and social workers through a one-time home visit and regular phone calls. The control group will receive only the wearable monitoring device. Data will be collected at baseline, 1 month, 3 months, and 6 months.

DISCUSSION

Merely providing older adults with wearable monitoring devices may not lead to the realization of the potential health benefits of these devices, as long-term usage can be challenging. The results of this trial can provide evidence for a new approach to enhancing self-management and community healthcare among community-dwelling older adults, ultimately improving their health outcomes.

IMPACT

Wearable monitoring devices not only enable real-time monitoring of vital signs, but can also support tailored messaging and facilitate virtual communication between users and healthcare professionals. Despite considerable health benefits, there is evidence showing that older adults largely stop using them after a few months. This study is the first to use a peer support approach to help older adults incorporate a wearable monitoring device in their daily routines in conjunction with goal setting and regular reminders. This will boost the self-care ability of the older adults, allowing them to continue physically functioning in the community.

TRIAL REGISTRATION

This study was prospectively registered at clinicaltrials.gov (identifier: NCT05269303). Registration date: 24/2/2022.

A Web-Based Patient Empowerment to Medication Adherence Program for Patients With Rheumatoid Arthritis: Feasibility Randomized Controlled Trial

BACKGROUND

Living with a chronic illness such as rheumatoid arthritis (RA) requires medications and therapies, as well as long-term follow-up with multidisciplinary clinical teams. Patient involvement in the shared decision-making process on medication regimens is an important element in promoting medication adherence. Literature review and needs assessment showed the viability of technology-based interventions to equip patients with knowledge about chronic illness and competencies to improve their adherence to medications. Thus, a web-based intervention was developed to empower patients living with RA to adhere to their disease-modifying antirheumatic drugs (DMARDs) medication regimen.

OBJECTIVE

This study aims to discuss the intervention mapping process in the design of a web-based intervention that supports patient empowerment to medication adherence and to evaluate its feasibility among patients living with RA.

METHODS

The theory-based Patient Empowerment to Medication Adherence Programme (PE2MAP) for patients with RA was built upon the Zimmerman Psychological Empowerment framework, a web-based program launched through the Udemy website. PE2MAP was developed using a 6-step intervention mapping process: (1) needs assessment, (2) program objectives, (3) conceptual framework to guide the intervention, (4) program plan, (5) adoption, and (6) evaluation involving multidisciplinary health care professionals (HCPs) and a multimedia team. PE2MAP is designed as a 4-week web-based intervention program with a complementary RA handbook. A feasibility randomized controlled trial was completed on 30 participants from the intervention group who are actively taking DMARD medication for RA to test the acceptability and feasibility of the PE2MAP.

RESULTS

The mean age and disease duration of the 30 participants were 52.63 and 8.50 years, respectively. The feasibility data showed 87% (n=26) completed the 4-week web-based PE2MAP intervention, 57% (n=17) completed all 100% of the contents, and 27% (n=8) completed 96% to 74% of the contents, indicating the overall feasibility of the intervention. As a whole, 96% (n=24) of the participants found the information on managing the side effects of medications, keeping fit, managing flare-ups, and monitoring joint swelling/pain/stiffness as the most useful contents of the intervention. In addition, 88% (n=23) and 92% (n=24) agreed that the intervention improved their adherence to medications and management of their side effects, including confidence in communicating with their health care team, respectively. The dos and do nots of traditional Chinese medicine were found by 96% (n=25) to be useful. Goal setting was rated as the least useful skill by 6 (23.1%) of the participants.

CONCLUSIONS

The web-based PE2MAP intervention was found to be acceptable, feasible, and effective as a web-based tool to empower patients with RA to manage and adhere to their DMARD medications. Further well-designed randomized controlled trials are warranted to explore the effectiveness of this intervention in the management of patients with RA.

Effect of a Home-Based Mobile Health App Intervention on Physical Activity Levels in Patients With Heart Failure: A Randomized Controlled Trial

BACKGROUND

The use of mobile health applications (apps) is an effective strategy in supporting patients' self-management of heart failure (HF) in home settings, but it remains unclear whether they can be used to reduce sedentary behaviors and increase overall physical activity levels.

AIM

The aims of this study were to determine the effect of an 8-week home-based mobile health app intervention on physical activity levels and to assess its effects on symptom burden and health-related quality of life.

METHOD

In this study, we collected repeated-measures data from 132 participants with HF (60.8 ± 10.47 years) randomized into a usual care group (n = 67) or an 8-week home-based mobile health app intervention group (n = 65). The intervention was tailored to decrease the time spent in sedentary behavior and to increase the time spent in physical activities performed at light or greater intensity levels. Physical activity levels were monitored for 2 weeks before the intervention and during the 8-week intervention using the Samsung mobile health app. Heart failure symptom burden and health-related quality of life were assessed at baseline, 2 weeks from baseline assessment, and immediately post intervention.

RESULTS

At week 8, all participants in the intervention group demonstrated an increase in the average daily step counts above the preintervention counts (range of increase: 2351-7925 steps/d). Only 29 participants (45%) achieved an average daily step count of 10 000 or higher by week 6 and maintained their achievement to week 8 of the intervention. Repeated-measures analysis of variance showed a significant group-by-time interaction, indicating that the intervention group had a greater improvement in physical activity levels, symptom burden, and health-related quality of life than the usual care group.

CONCLUSION

Home-based mobile health app-based interventions can increase physical activity levels and can play an important role in promoting better HF outcomes.

Patient perspectives on the use of mobile apps to support heart failure management: A qualitative descriptive study

BACKGROUND

Adherence to diet and medical therapies are key to improving heart failure (HF) outcomes; however, nonadherence is common. While mobile apps may be a promising way to support patients with adherence via education and monitoring, HF patient perspectives regarding the use of apps for HF management in unknown. This data is critical for these tools to be successfully developed, implemented, and adopted to optimize adherence and improve HF outcomes.

OBJECTIVE

To determine patients' needs, motivations, and challenges on the use of mobile apps to support HF management.

METHODS

A qualitative descriptive study using focus groups (n = 4,60 minutes) was conducted among HF patients from outpatient HF clinics in Toronto, Canada. The Diffusion of Innovation theory informed a ten-question interview guide. Interview transcripts were independently coded by two researchers and analyzed using content analysis.

RESULTS

Nineteen HF patients (65 ± 10 yrs, 12 men) identified a total of four key themes related to the use of mobile apps. The theme 'Factors impacting technology use by patients' identified motivations and challenges to app use, including access to credible information, easy and accessible user-interface. Three themes described patients' needs on the use of mobile apps to support HF management: 1) 'Providing patient support through access to information and self-monitoring', apps could provide education on HF-related content (e.g., diet, medication, symptoms); 2) 'Facilitating connection and communication', through information sharing with healthcare providers and connecting with other patients; 3) 'Patient preferences', app features such as reminders for medication, and visuals to show changes in HF symptoms were favoured.

CONCLUSIONS

HF patients perceive several benefits and challenges to app use for HF self-management. Capitalizing on the benefits and addressing the challenges during the app development process may maximize adoption of such tools in this patient population.

Characteristics of Smart Health Ecosystems That Support Self-care Among People With Heart Failure: Scoping Review

BACKGROUND

The management of heart failure is complex. Innovative solutions are required to support health care providers and people with heart failure with decision-making and self-care behaviors. In recent years, more sophisticated technologies have enabled new health care models, such as smart health ecosystems. Smart health ecosystems use data collection, intelligent data processing, and communication to support the diagnosis, management, and primary and secondary prevention of chronic conditions. Currently, there is little information on the characteristics of smart health ecosystems for people with heart failure.

OBJECTIVE

We aimed to identify and describe the characteristics of smart health ecosystems that support heart failure self-care.

METHODS

We conducted a scoping review using the Joanna Briggs Institute methodology. The MEDLINE, Embase, CINAHL, PsycINFO, IEEE Xplore, and ACM Digital Library databases were searched from January 2008 to September 2021. The search strategy focused on identifying articles describing smart health ecosystems that support heart failure self-care. A total of 2 reviewers screened the articles and extracted relevant data from the included full texts.

RESULTS

After removing duplicates, 1543 articles were screened, and 34 articles representing 13 interventions were included in this review. To support self-care, the interventions used sensors and questionnaires to collect data and used tailoring methods to provide personalized support. The interventions used a total of 34 behavior change techniques, which were facilitated by a combination of 8 features for people with heart failure: automated feedback, monitoring (integrated and manual input), presentation of data, education, reminders, communication with a health care provider, and psychological support. Furthermore, features to support health care providers included data presentation, alarms, alerts, communication tools, remote care plan modification, and health record integration.

CONCLUSIONS

This scoping review identified that there are few reports of smart health ecosystems that support heart failure self-care, and those that have been reported do not provide comprehensive support across all domains of self-care. This review describes the technical and behavioral components of the identified interventions, providing information that can be used as a starting point for designing and testing future smart health ecosystems.

The Determinants of User Acceptance of Mobile Medical Platforms: An Investigation Integrating the TPB, TAM, and Patient-Centered Factors

Mobile medical platforms (MMPs) can make medical services more accessible and effective. However, the patient-centered factors that influence patients' acceptance of MMPs are not well understood. Our study examined the factors affecting patients' acceptance of MMPs by integrating the theory of planned behavior (TPB), the technology acceptance model (TAM), and three patient-centered factors (i.e., perceived convenience, perceived credibility, and perceived privacy risk). Three hundred and eighty-nine Chinese respondents were recruited in this study and completed a self-administered online questionnaire that included items adapted from validated measurement scales. The partial least squares structural equation modeling results revealed that perceived privacy risk, perceived credibility, and perceived ease of use directly determined the perceived usefulness of an MMP. Perceived convenience, perceived credibility, and perceived usefulness significantly affected the patients' attitudes toward MMPs. Perceived usefulness, attitude, perceived privacy risk, and perceived behavioral control were important determinants of the patients' behavioral intentions to use MMPs. Behavioral intention and perceived behavioral control significantly influenced perceived effective use. Perceived credibility and perceived ease of use significantly affected perceived convenience. However, social influence had no significant effect on attitude and behavioral intention. The study provides important theoretical and practical implications, which could help practitioners enhance the patients' use of MMPs for their healthcare activities.

Usability and feasibility assessment of a smartphone application (Suhriday) for heart failure self-care remote monitoring in an Indian tertiary health care setting: a pilot mixed-methods study

BACKGROUND/OBJECTIVES

Remote monitoring as a component of chronic heart failure (CHF) management programmes has demonstrated utility in reducing the risk of rehospitalisation and mortality. There is little evidence on mobile health app facilitated remote monitoring in India. We conducted a pilot usability and feasibility assessment of a smartphone-based application (Suhriday) to remotely monitor patients with CHF.

METHODS

We used a mixed-methods design. Usability testing consisted of the think-aloud approach followed by semistructured in-depth interviews (SSIs) and a satisfaction questionnaire. Feasibility testing was done using acceptability and user satisfaction questionnaires in addition to SSIs. We trained five purposively sampled patients with CHF (based on health literacy and gender) and their caregivers (n=10) in self-care monitoring and app use. Usability was assessed using metrics such as task completion, time required for task completion and user satisfaction using Brooke's System Usability Scale (SUS). Content analysis of the transcripts with deductive coding was performed for both usability and feasibility interviews. The number and types of medical alerts transmitted through the app were captured and escalated to the treating team.

RESULTS

Critical tasks involving (1) opening the app and identifying task list, (2) reporting blood pressure, weight, heart rate and fluid intake and (3) reporting symptoms were completed within 60 s by four patients. Median (IQR) SUS score was 85 (75-92.5) indicating high level of usability. There were 62 alerts from four patients over 4 weeks, with 36 (58.1%) excess fluid intake alerts and 16 (25.8%) blood pressure variations being the most frequent. One participant had challenges using the app and was monitored through active phone calls.

CONCLUSION

Overall usability and satisfaction with Suhriday were good and we were able to remotely manage patients. However, patients with limited health literacy and those facing technological challenges required active structured telephone support.

mHealth Apps for Self-Management of Cardiovascular Diseases: A Scoping Review

The use of mHealth apps for the self-management of cardiovascular diseases (CVDs) is an increasing trend in patient-centered care. In this research, we conduct a scoping review of mHealth apps for CVD self-management within the period 2014 to 2021. Our review revolves around six main aspects of the current status of mHealth apps for CVD self-management: main CVDs managed, main app functionalities, disease stages managed, common approaches used for data extraction, analysis, management, common wearables used for CVD detection, monitoring and/or identification, and major challenges to overcome and future work remarks. Our review is based on Arksey and O'Malley's methodological framework for conducting studies. Similarly, we adopted the PRISMA model for reporting systematic reviews and meta-analyses. Of the 442 works initially retrieved, the review comprised 38 primary studies. According to our results, the most common CVDs include arrhythmia (34%), heart failure (32%), and coronary heart disease (18%). Additionally, we found that the majority mHealth apps for CVD self-management can provide medical recommendations, medical appointments, reminders, and notifications for CVD monitoring. Main challenges in the use of mHealth apps for CVD self-management include overcoming patient reluctance to use the technology and achieving the interoperability of mHealth applications with other systems.

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.

Toward the Value Sensitive Design of eHealth Technologies to Support Self-management of Cardiovascular Diseases: Content Analysis

BACKGROUND

eHealth can revolutionize the way self-management support is offered to chronically ill individuals such as those with a cardiovascular disease (CVD). However, patients' fluctuating motivation to actually perform self-management is an important factor for which to account. Tailoring and personalizing eHealth to fit with the values of individuals promises to be an effective motivational strategy. Nevertheless, how specific eHealth technologies and design features could potentially contribute to values of individuals with a CVD has not been explicitly studied before.

OBJECTIVE

This study sought to connect a set of empirically validated, health-related values of individuals with a CVD with existing eHealth technologies and their design features. The study searched for potential connections between design features and values with the goal to advance knowledge about how eHealth technologies can actually be more meaningful and motivating for end users.

METHODS

Undertaking a technical investigation that fits with the value sensitive design framework, a content analysis of existing eHealth technologies was conducted. We matched 11 empirically validated values of CVD patients with 70 design features from 10 eHealth technologies that were previously identified in a systematic review. The analysis consisted mainly of a deductive coding stage performed independently by 3 members of the study team. In addition, researchers and developers of 6 of the 10 reviewed technologies provided input about potential feature-value connections.

RESULTS

In total, 98 connections were made between eHealth design features and patient values. This meant that some design features could contribute to multiple values. Importantly, some values were more often addressed than others. CVD patients' values most often addressed were related to (1) having or maintaining a healthy lifestyle, (2) having an overview of personal health data, (3) having reliable information and advice, (4) having extrinsic motivators to accomplish goals or health-related activities, and (5) receiving personalized care. In contrast, values less often addressed concerned (6) perceiving low thresholds to access health care, (7) receiving social support, (8) preserving a sense of autonomy over life, and (9) not feeling fear, anxiety, or insecurity about health. Last, 2 largely unaddressed values were related to (10) having confidence and self-efficacy in the treatment or ability to achieve goals and (11) desiring to be seen as a person rather than a patient.

CONCLUSIONS

Positively, existing eHealth technologies could be connected with CVD patients' values, largely through design features that relate to educational support, self-monitoring support, behavior change support, feedback, and motivational incentives. Other design features such as reminders, prompts or cues, peer-based or expert-based human support, and general system personalization were also connected with values but in narrower ways. In future studies, the inferred feature-value connections must be validated with empirical data from individuals with a CVD or similar chronic conditions.

Use of mobile applications in heart failure self-management: a qualitative study exploring the patient and primary care clinician perspective (Preprint)

Background

Mobile apps have the potential to support patients with heart failure and facilitate disease self-management, but this area of research is recent and rapidly evolving, with inconsistent results for efficacy. So far, most of the published studies evaluated the feasibility of a specific app or assessed the quality of apps available in app stores. Research is needed to explore patients’ and clinicians’ perspectives to guide app development, evaluation, and implementation into models of care.

Objective

This study aims to explore the patient and primary care clinician perspective on the facilitators and barriers to using mobile apps, as well as desired features, to support heart failure self-management.

Methods

This is a qualitative phenomenological study involving face-to-face semistructured interviews. Interviews were conducted in a general practice clinic in Sydney, Australia. Eligible participants were adult patients with heart failure and health care professionals who provided care to these patients at the clinic. Patients did not need to have previous experience using heart failure mobile apps to be eligible for this study. The interviews were audio-recorded, transcribed, and analyzed using inductive thematic data analysis in NVivo 12.

Results

A total of 12 participants were interviewed: 6 patients (mean age 69 [SD 7.9] years) and 6 clinicians. The interviews lasted from 25 to 45 minutes. The main facilitators to the use of apps to support heart failure self-management were communication ability, personalized feedback and education, and automated self-monitoring. Patients mentioned that chat-like features and ability to share audio-visual information can be helpful for getting support outside of clinical appointments. Clinicians considered helpful to send motivational messages to patients and ask them about signs and symptoms of heart failure decompensation. Overall, participants highlighted the importance of personalization, particularly in terms of feedback and educational content. Automated self-monitoring with wireless devices was seen to alleviate the burden of tracking measures such as weight and blood pressure. Other desired features included tools to monitor patient-reported outcomes and support patients’ mental health and well-being. The main barriers identified were the patients’ unwillingness to engage in a new strategy to manage their condition using an app, particularly in the case of low digital literacy. However, clinicians mentioned this barrier could potentially be overcome by introducing the app soon after an exacerbation, when patients might be more willing to improve their self-management and avoid rehospitalization.

Conclusions

The use of mobile apps to support heart failure self-management may be facilitated by features that increase the usefulness and utility of the app, such as communication ability in-between consultations and personalized feedback. Also important is facilitating ease of use by supporting automated self-monitoring through integration with wireless devices. Future research should consider these features in the co-design and testing of heart failure mobile apps with patients and clinicians.

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.

A pilot randomized clinical trial of a teamwork intervention for heart failure care dyads

BACKGROUND

Dyadic heart failure (HF) management can improve outcomes for patients and caregivers and can be enhanced through eHealth interventions.

OBJECTIVE

To evaluate the feasibility, acceptability, and preliminary efficacy of an eHealth dyadic teamwork intervention, compared to an attention control condition.

METHODS

We recruited 29 HF patient-caregiver dyads from inpatient units and randomized dyads to an intervention or a control group. We calculated enrollment and retention rates, described acceptability using interview and questionnaire data, and computed intervention effect sizes.

RESULTS

37% of eligible dyads agreed to participate and 93% of randomized participants completed follow-up questionnaires. Participants found both study conditions to be acceptable. Between-group effect sizes suggested that the intervention led to improvements in relationship quality, self-efficacy, and quality of life for patients and caregivers.

CONCLUSIONS

Dyadic recruitment from acute care settings is challenging. Findings provide initial evidence that our intervention can contribute to better health outcomes for HF dyads.

Smart Wearables for Cardiac Monitoring-Real-World Use beyond Atrial Fibrillation

The possibilities and implementation of wearable cardiac monitoring beyond atrial fibrillation are increasing continuously. This review focuses on the real-world use and evolution of these devices for other arrhythmias, cardiovascular diseases and some of their risk factors beyond atrial fibrillation. The management of nonatrial fibrillation arrhythmias represents a broad field of wearable technologies in cardiology using Holter, event recorder, electrocardiogram (ECG) patches, wristbands and textiles. Implementation in other patient cohorts, such as ST-elevation myocardial infarction (STEMI), heart failure or sleep apnea, is feasible and expanding. In addition to appropriate accuracy, clinical studies must address the validation of clinical pathways including the appropriate device and clinical decisions resulting from the surrogate assessed.

A Personal Health System for Self-Management of Congestive Heart Failure (HeartMan): Development, Technical Evaluation, and Proof-of-Concept Randomized Controlled Trial

BACKGROUND

Congestive heart failure (CHF) is a disease that requires complex management involving multiple medications, exercise, and lifestyle changes. It mainly affects older patients with depression and anxiety, who commonly find management difficult. Existing mobile apps supporting the self-management of CHF have limited features and are inadequately validated.

OBJECTIVE

The HeartMan project aims to develop a personal health system that would comprehensively address CHF self-management by using sensing devices and artificial intelligence methods. This paper presents the design of the system and reports on the accuracy of its patient-monitoring methods, overall effectiveness, and patient perceptions.

METHODS

A mobile app was developed as the core of the HeartMan system, and the app was connected to a custom wristband and cloud services. The system features machine learning methods for patient monitoring: continuous blood pressure (BP) estimation, physical activity monitoring, and psychological profile recognition. These methods feed a decision support system that provides recommendations on physical health and psychological support. The system was designed using a human-centered methodology involving the patients throughout development. It was evaluated in a proof-of-concept trial with 56 patients.

RESULTS

Fairly high accuracy of the patient-monitoring methods was observed. The mean absolute error of BP estimation was 9.0 mm Hg for systolic BP and 7.0 mm Hg for diastolic BP. The accuracy of psychological profile detection was 88.6%. The F-measure for physical activity recognition was 71%. The proof-of-concept clinical trial in 56 patients showed that the HeartMan system significantly improved self-care behavior (P=.02), whereas depression and anxiety rates were significantly reduced (P<.001), as were perceived sexual problems (P=.01). According to the Unified Theory of Acceptance and Use of Technology questionnaire, a positive attitude toward HeartMan was seen among end users, resulting in increased awareness, self-monitoring, and empowerment.

CONCLUSIONS

The HeartMan project combined a range of advanced technologies with human-centered design to develop a complex system that was shown to help patients with CHF. More psychological than physical benefits were observed.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03497871; https://clinicaltrials.gov/ct2/history/NCT03497871.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1186/s12872-018-0921-2.

Remote Patient Monitoring in Heart Failure: Factors for Clinical Efficacy

Despite clinical advances in its treatment, heart failure (HF) is associated with significant adverse clinical outcomes and is among the greatest drivers of healthcare utilization. Outpatient management of HF remains suboptimal, with gaps in the provision of evidence-based therapies, and difficulties in predicting and managing clinical decompensation. Remote patient monitoring (RPM) has the potential to address these issues, and thus has been of increasing interest to HF clinicians and health systems. Economic incentives, including increasing RPM reimbursement and HF readmission penalties, are also spurring increased interest in RPM. This review establishes a framework for evaluating RPM based on its various components: 1) patient data collection, 2) data transmission, analysis, and presentation, and 3) care team review and clinical action. The existing evidence regarding RPM in HF management is also reviewed. Based on the data, we identify RPM features associated with clinical efficacy and describe emerging digital tools that have the promise of addressing current needs.

The Future of Wearables in Heart Failure Patients

The adoption of mobile health (mHealth) devices is creating a unique opportunity to improve heart failure (HF) care. The rise of mHealth is driven by multiple factors including consumerism, policy changes in health care, and innovations in technology. Wearable health devices are one aspect of mHealth that may improve the delivery of HF care by allowing for medical data collection outside of a clinician's office or hospital. Wearable devices are externally applied and capture functional or physiological data in order to monitor and improve patients' health. Most wearable sensors capture data continuously and may be incorporated into accessories (e.g., a watch or clothing) or may be applied as a cutaneous patch. Wearable devices are often paired with another device, such as a smartphone, to collect, interpret, or transmit data. This study assessed the potential applications of wearable devices in HF care, summarizes available data for wearables, and discusses the future of wearables for improving the health of patients with HF.

Leveraging Walking Performance to Understand Work Fatigue Among Young Adults: Mixed-Methods Study

Background

Work fatigue negatively impacts personal health in the long term. Prior research has indicated the possibility of leveraging both walking parameters and perceptual measures to assess a person’s fatigue status. However, an effective and ubiquitous approach to assessing work fatigue in young adults remains unexplored.

Objective

The goals of this paper were to (1) explore how walking rhythms and multiple streams of data, including reaction time, self-reports, and an activity diary, reflect work-induced fatigue in the lab setting; (2) identify the relationship between objective performance and subjective perception in indicating fatigue status and fatigability; and (3) propose a mobile-based assessment for work-induced fatigue that uses multiple measurements.

Methods

We conducted a 2-day in-lab study to measure participants’ fatigue status using multiple measurements, including the stair climb test (SCT), the 6-minute walk test (6MWT), and the reaction time test. Both the SCT and the 6MWT were conducted at different points in time and under 2 conditions (measurement time, including prior to and after work, and pace, including normal and fast). Participants reported their fatigue perception through questionnaires completed before conducting walking tests and in an activity diary recorded over a week. Walking performance data were collected by a smartphone with a built-in 3-axis accelerometer. To examine the effect of fatigability on walking performance, we first clustered participants into 2 groups based on their reported mental fatigue level in the entry surveys and then compared their walking performance using a generalized linear model (GLM). The reaction time was examined using a 2-way repeated-measures GLM. We conducted semistructured interviews to understand participants’ fatigue perception after each day’s walking tests.

Results

All participants (N=26; mean age 24.68 years) were divided into 2 groups—the fatigue-sensitive group (11/26, 42%) and the fatigue-nonsensitive group (15/26, 58%)—based on their mental subscores from 3 entry surveys: Fatigue Scale-14, Three-Dimensional Work Fatigue Inventory, and Fatigue Self-Assessment Scale (FSAS). The fatigue-sensitive group reported a significantly higher FSAS score in the before-work setting (t₅₀=–3.361; P=.001). The fatigue-sensitive group covered fewer steps than the fatigue-nonsensitive group (β₁=–0.099; SE 0.019; t₁=–5.323; P<.001) and had a higher step-to-step time variability in the 6MWT (β₁=9.61 × 10^–4; t₁=2.329; P=.02). No strong correlation between subjective and objective measurements was observed in the study.

Conclusions

Walking parameters, including step counts and step-to-step time variability, and some selected scales (eg, FSAS) were found to reflect participants’ work-induced fatigue. Overall, our work suggests the opportunity of employing mobile-based walking measurements to indicate work fatigue among young adults.

Developing a Heart Transplantation Self-Management Support Mobile Health App in Taiwan: Qualitative Study

BACKGROUND

Heart transplantation (HTx) is the most effective treatment for end-stage heart failure patients. After transplantation, patients face physiological, psychological, social, and other health care problems. Mobile health (mHealth) apps can change the delivery of conventional health care to ubiquitous care and improve health care quality. However, a dearth of mHealth apps exists for patients with HTx worldwide, including in Taiwan.

OBJECTIVE

The aim of this study was to investigate the information needed and to develop a preliminary framework for an mHealth app for post-HTx patients.

METHODS

A qualitative approach with individual in-depth interviews was conducted at a heart center in the regional hospital of northern Taiwan from June to November 2017. Patients that had undergone HTx and their health professionals were recruited for purposeful sampling. A semistructured interview guideline was used for individual interviews and transcribed. Thematic analysis was used for data analysis.

RESULTS

A total of 21 subjects, including 17 patients and 4 health professionals, were recruited for the study. The following five major themes were identified: reminding, querying, experience sharing, diet, and expert consulting. Minor themes included a desire to use the app with artificial intelligence and integration with professional management.

CONCLUSIONS

An intelligent mHealth app that addresses the five main themes and integrates the processes of using a mobile app could facilitate HTx self-management for Taiwanese patients.

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.

Supporting Self-Management of Cardiovascular Diseases Through Remote Monitoring Technologies: Metaethnography Review of Frameworks, Models, and Theories Used in Research and Development

Background

Electronic health (eHealth) is a rapidly evolving field informed by multiple scientific disciplines. Because of this, the use of different terms and concepts to explain the same phenomena and lack of standardization in reporting interventions often leaves a gap that hinders knowledge accumulation. Interventions focused on self-management support of cardiovascular diseases through the use of remote monitoring technologies are a cross-disciplinary area potentially affected by this gap. A review of the underlying frameworks, models, and theories that have informed projects at this crossroad could advance future research and development efforts.

Objective

This research aimed to identify and compare underlying approaches that have informed interventions focused on self-management support of cardiovascular diseases through the use of remote monitoring technologies. The objective was to achieve an understanding of the distinct approaches by highlighting common or conflicting principles, guidelines, and methods.

Methods

The metaethnography approach was used to review and synthesize researchers’ reports on how they applied frameworks, models, and theories in their projects. Literature was systematically searched in 7 databases: Scopus, Web of Science, EMBASE, CINAHL, PsycINFO, Association for Computing Machinery Digital Library, and Cochrane Library. Included studies were thoroughly read and coded to extract data for the synthesis. Studies were mainly related by the key ingredients of the underlying approaches they applied. The key ingredients were finally translated across studies and synthesized into thematic clusters.

Results

Of 1224 initial results, 17 articles were included. The articles described research and development of 10 different projects. Frameworks, models, and theories (n=43) applied by the projects were identified. Key ingredients (n=293) of the included articles were mapped to the following themes of eHealth development: (1) it is a participatory process; (2) it creates new infrastructures for improving health care, health, and well-being; (3) it is intertwined with implementation; (4) it integrates theory, evidence, and participatory approaches for persuasive design; (5) it requires continuous evaluation cycles; (6) it targets behavior change; (7) it targets technology adoption; and (8) it targets health-related outcomes.

Conclusions

The findings of this review support and exemplify the numerous possibilities in the use of frameworks, models, and theories to guide research and development of eHealth. Participatory, user-centered design, and integration with empirical evidence and theoretical modeling were widely identified principles in the literature. On the contrary, less attention has been given to the integration of implementation in the development process and supporting novel eHealth-based health care infrastructures. To better integrate theory and evidence, holistic approaches can combine patient-centered studies with consolidated knowledge from expert-based approaches.

Trial Registration

PROSPERO CRD42018104397; https://tinyurl.com/y8ajyajt

International Registered Report Identifier (IRRID)

RR2-10.2196/13334

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.

Effectiveness of Mobile Phone-Based Interventions for Improving Health Outcomes in Patients with Chronic Heart Failure: A Systematic Review and Meta-Analysis

Mobile phone-based interventions are increasingly used to prevent adverse health outcomes in heart failure patients. However, the effects of mobile phone-based interventions on the health outcomes of heart failure patients remain unclear. Our review aims to synthesize the randomized controlled trials (RCT) of mobile phone-based interventions for heart failure patients and identify the intervention features that are most effective. Electronic searches of RCTs published from January 2000 to July 2019 were conducted. Primary outcomes included all-cause mortality, readmission, emergency department visits, length of hospital stays, and quality of life. Secondary outcomes were self-care behaviors, including medication adherence and other clinical outcomes. A total of eight studies with varying methodological quality met the inclusion criteria and were analyzed. Voice call intervention was more frequently used compared with telemonitoring and short message services. Our meta-analysis showed that voice call interventions had significant effects on the length of hospital stays. However, no significant effects on all-cause mortality, readmission, emergency department visits, or quality of life were found. Compared to other mobile phone-based interventions, voice calls were more effective in reducing the length of hospital stay. Future studies are needed to identify which features of mobile phone-based intervention most effectively improve health outcomes.

Symptom perception in heart failure: a scoping review on definition, factors and instruments

BACKGROUND

Symptom perception in heart failure has been identified as crucial for effective self-care that is a modifiable factor related to decreased hospital readmission and improved survival.

AIMS

To review systematically the heart failure symptom perception literature and synthesise knowledge on definition, description, factors and instruments.

METHODS

We conducted a scoping review including studies reporting patient-reported symptom perception in adults with heart failure. Structured searches were conducted in Medline, PubMed, Embase, CINAHL, PsychINFO, Web of Science, Cochrane, JBI and grey literature. Two authors independently reviewed references for eligibility. Data were charted in tables and results narratively summarised.

RESULTS

The search yielded 3057 references, of which 106 were included. The definition of heart failure symptom perception comprised body listening, monitoring signs, recognising, interpreting and labelling symptoms, and furthermore awareness of and assigning meaning to the change. Symptom monitoring, recognition and interpretation were identified as challenging. Symptom perception facilitators include prior heart failure hospitalisation, heart failure self-care maintenance, symptom perception confidence, illness uncertainty and social support. Barriers include knowledge deficits, symptom clusters and lack of tools/materials. Factors with inconsistent impact on symptom perception include age, sex, education, experiences of living with heart failure, comorbidities, cognitive impairment, depression and symptom progression. One instrument measuring all dimensions of heart failure symptom perception was identified.

CONCLUSION

Heart failure symptom perception definition and description have been elucidated. Several factors facilitating or hampering symptom perception are known. Further research is needed to determine a risk profile for poor symptom perception - which can then be taken into consideration when supporting heart failure self-care.

Technology anxiety and resistance to change behavioral study of a wearable cardiac warming system using an extended TAM for older adults

With advances in technology, wireless and sensor technologies represent a method for continuously recording people’s biomedical signals, which may enhance the diagnosis and treatment of users’ everyday health conditions. These technologies mostly target older adults. In this study, we examine a smart clothing system targeting clinically high-risk patients, including older adults with cardiovascular disease (31 outpatients) and older adults in general (81 participants), to obtain an understanding of the patients’ perception of using wearable healthcare technologies. Given that technology anxiety has been shown to affect users’ resistance to using new technology and that perceived ubiquity is considered a characteristic of wearable devices and other mobile wireless technologies, we included three external variables: i.e., technology anxiety, perceived ubiquity, and resistance to change, in addition to the traditional components of the technology acceptance model (TAM). The results of the hypothesized model showed that among older adults in general, technology anxiety had a negative effect on the perceived ease of use and perceived ubiquity. The perceived ubiquity construct affects both user groups’ perceived ease of use and perceived usefulness of wearing smart clothes. Most relationships among the original constructs of the TAM were validated in older adults in general. Interestingly, we found that perceived usefulness had an indirect effect on behavioral intention through attitude. These results further confirm the validity of the extended TAM in determining older users’ technology acceptance behavior.

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.

The rise of artificial intelligence in healthcare applications

Big data and machine learning are having an impact on most aspects of modern life, from entertainment, commerce, and healthcare. Netflix knows which films and series people prefer to watch, Amazon knows which items people like to buy when and where, and Google knows which symptoms and conditions people are searching for. All this data can be used for very detailed personal profiling, which may be of great value for behavioral understanding and targeting but also has potential for predicting healthcare trends. There is great optimism that the application of artificial intelligence (AI) can provide substantial improvements in all areas of healthcare from diagnostics to treatment. It is generally believed that AI tools will facilitate and enhance human work and not replace the work of physicians and other healthcare staff as such. AI is ready to support healthcare personnel with a variety of tasks from administrative workflow to clinical documentation and patient outreach as well as specialized support such as in image analysis, medical device automation, and patient monitoring. In this chapter, some of the major applications of AI in healthcare will be discussed covering both the applications that are directly associated with healthcare and those in the healthcare value chain such as drug development and ambient assisted living.

Applying M-Health to Palliative Care: A Systematic Review on the Use of M-Health in Monitoring Patients With Chronic Diseases and its Transposition in Palliative Care

BACKGROUND

The major growth of mobile technologies in the recent years has led to the development of medical-monitoring applications, particularly on smartphones.

AIM

The aim of this study was to review the use of m-health in the monitoring of patients with chronic pathologies in order to consider what could be adapted for palliative care patients at home.

DESIGN

A systematic review of the English and French literature was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria.

DATE SOURCES

The review screened the following databases: PUBMED, SCOPUS, COCHRANE, SCIENCE DIRECT, SUDOC, and EM-Premium, screening studies published between 2008 and 2018. The selection of articles was done by the main investigator. All studies concerning the use of m-Health apps for patients with chronic diseases were included.

RESULTS

From the 337 selected publications, 8 systematic reviews and 14 original studies were included. The main uses of m-Health apps were biological and clinical monitoring (particularly concerning the symptoms) in 75% of the applications, disease self-management in 64% of the applications, and therapeutic patient education in 50% of the applications, with remote monitoring.

CONCLUSIONS

The development of an m-Health application could become a complementary monitoring tool during palliative care. However, it seems important to question the impact of technique in the professional-patient relationship and avoid the pitfalls of standardizing palliative care and reducing the patient to a "sick" health technician. A future step would then be to define which health-care professional would be in charge of this "m-monitoring."

Impact on Readmission Reduction Among Heart Failure Patients Using Digital Health Monitoring: Feasibility and Adoptability Study

Background

Heart failure (HF) is a condition that affects approximately 6.2 million people in the United States and has a 5-year mortality rate of approximately 42%. With the prevalence expected to exceed 8 million cases by 2030, projections estimate that total annual HF costs will increase to nearly US $70 billion. Recently, the advent of remote monitoring technology has significantly broadened the scope of the physician’s reach in chronic disease management.

Objective

The goal of our program, named the Heart Health Program, was to examine the feasibility of using digital health monitoring in real-world home settings, ascertain patient adoption, and evaluate impact on 30-day readmission rate.

Methods

A digital medicine software platform developed at Mount Sinai Health System, called RxUniverse, was used to prescribe a digital care pathway including the HealthPROMISE digital therapeutic and iHealth mobile apps to patients’ personal smartphones. Vital sign data, including blood pressure (BP) and weight, were collected through an ambulatory remote monitoring system that comprised a mobile app and complementary consumer-grade Bluetooth-connected smart devices (BP cuff and digital scale) that send data to the provider care teams. Care teams were alerted via a Web-based dashboard of abnormal patient BP and weight change readings, and further action was taken at the clinicians’ discretion. We used statistical analyses to determine risk factors associated with 30-day all-cause readmission.

Results

Overall, the Heart Health Program included 58 patients admitted to the Mount Sinai Hospital for HF. The 30-day hospital readmission rate was 10% (6/58), compared with the national readmission rates of approximately 25% and the Mount Sinai Hospital’s average of approximately 23%. Single marital status (P=.06) and history of percutaneous coronary intervention (P=.08) were associated with readmission. Readmitted patients were also less likely to have been previously prescribed angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (P=.02). Notably, readmitted patients utilized the BP and weight monitors less than nonreadmitted patients, and patients aged younger than 70 years used the monitors more frequently on average than those aged over 70 years, though these trends did not reach statistical significance. The percentage of the 58 patients using the monitors at least once dropped from 83% (42/58) in the first week after discharge to 46% (23/58) in the fourth week.

Conclusions

Given the increasing burden of HF, there is a need for an effective and sustainable remote monitoring system for HF patients following hospital discharge. We identified clinical and social factors as well as remote monitoring usage trends that identify targetable patient populations that could benefit most from integration of daily remote monitoring. In addition, we demonstrated that interventions driven by real-time vital sign data may greatly aid in reducing hospital readmissions and costs while improving patient outcomes.

The influence of mobile health applications on patient - healthcare provider relationships: A systematic, narrative review

OBJECTIVE

To explore the influence of mobile health applications on various dimensions of patient and healthcare provider relationships.

METHODS

A systematic, narrative review of English literature reporting experiences and outcomes of using mobile health applications was performed, evaluating communication and relationships between patients and healthcare professionals. Findings were framed thematically within the four dimensions of relationship-centred care. The methodological quality of included articles was appraised.

RESULTS

Thirty-seven articles were included, all of them meeting tenets of relationship-centred care. After adopting mobile health applications patients perceived an overall positive impact on their relationship with healthcare providers, indicating they are ready to transition from traditional clinical ecounters to a different modality. Use of the applications supported patients in assuming active roles in the management of their health in collaboration with health professionals. Reluctance of providers to using mobile health needs to be acknowledged and addressed when encouraging wider use of applications in clinical practice.

CONCLUSION

The use of mobile health applications can influence communication and relationships between patients and providers positively, facilitating relationship-centered healthcare.

PRACTICE IMPLICATION

Implementation of mobile health can support patients' self-efficacy, improve access to healthcare services and improve relationships between patients and providers in ambulatory and hospital settings.

A Patient-Centered Mobile Phone App (iHeartU) With a Virtual Human Assistant for Self-Management of Heart Failure: Protocol for a Usability Assessment Study

Background

Heart failure (HF) causes significant economic and humanistic burden for patients and their families, especially those with a low income, partly due to high hospital readmission rates. Optimal self-care is considered an important nonpharmacological aspect of HF management that can improve health outcomes. Emerging evidence suggests that self-management assisted by smartphone apps may reduce rehospitalization rates and improve the quality of life of patients. We developed a virtual human–assisted, patient-centered mobile health app (iHeartU) for patients with HF to enhance their engagement in self-management and improve their communication with health care providers and family caregivers. iHeartU may help patients with HF in self-management to reduce the technical knowledge and usability barrier while maintaining a low cost and natural, effective social interaction with the user.

Objective

With a standardized systematic usability assessment, this study had two objectives: (1) to determine the obstacles to effective and efficient use of iHeartU in patients with HF and (2) to evaluate of HF patients’ adoption, satisfaction, and engagement with regard to the of iHeartU app.

Methods

The basic methodology to develop iHeartU systems consists of a user-centric design, development, and mixed methods formative evaluation. The iterative design and evaluation are based on the guidelines of the American College of Cardiology Foundation and American Heart Association for the management of heart failure and the validated “Information, Motivation, and Behavioral skills” behavior change model. Our hypothesis is that this method of a user-centric design will generate a more usable, useful, and easy-to-use mobile health system for patients, caregivers, and practitioners.

Results

The prototype of iHeartU has been developed. It is currently undergoing usability testing. As of September 2018, the first round of usability testing data have been collected. The final data collection and analysis are expected to be completed by the end of 2019.

Conclusions

The main contribution of this project is the development of a patient-centered self-management system, which may support HF patients’ self-care at home and aid in the communication between patients and their health care providers in a more effective and efficient way. Widely available mobile phones serve as care coordination and “no-cost” continuum of care. For low-income patients with HF, a mobile self-management tool will expand their accessibility to care and reduce the cost incurred due to emergency visits or readmissions. The user-centered design will improve the level of engagement of patients and ultimately lead to better health outcomes. Developing and testing a novel mobile system for patients with HF that incorporates chronic disease management is critical for advancing research and clinical practice of care for them. This research fills in the gap in user-centric design and lays the groundwork for a large-scale population study in the next phase.

International Registered Report Identifier (IRRID)

DERR1-10.2196/13502

Designing meaningful outcome parameters using mobile technology: a new mobile application for telemonitoring of patients with heart failure

Aims

Health data captured by commercially available smart devices may represent meaningful patient‐reported outcome measures (PROMs) in heart failure (HF) patients. The purpose of this study was to test this hypothesis by evaluating the feasibility of a new telemonitoring concept for patients following initial HF hospitalization.

Methods and results

We designed a cardio patient monitoring platform (CPMP) that comprised mobile iOS‐based applications for patients' smartphone/smartwatch and the equivalent application on a physicians' tablet. It allowed for safe and continuous data transmission of self‐measured physiological parameters, activity data, and patient‐reported symptoms. In a prospective feasibility trial with 692 patient days from 10 patients hospitalized for newly diagnosed HF with reduced ejection fraction (mean left ventricular ejection fraction (LVEF) 26.5 ± 9.8%), we examined the CPMP during the first 2 months following discharge (69 ± 15 observation days per patient). The mean daily step count recorded by the mobile devices emerged as a promising new PROM. Its 14 day average increased over the study period (3612 ± 3311 steps/day at study inclusion and 7069 ± 5006 steps/day at end of study; P < 0.0001). It is unique for continuously reflecting real‐life activity and correlated significantly with traditional surrogate parameters of cardiac performance including LVEF (r = 0.44; 95% CI 0.07–0.71; P = 0.0232), 6 min walk test (r = 0.67; 95% CI 0.38–0.84; P = 0.0002), and scores in health‐related quality of life questionnaires.

Conclusions

We provide the first patient monitoring platform for HF patients that relies on commercially available iOS/watchOS‐based devices. Our study suggests it is ready for implementation as a tool for recording meaningful PROMs in future HF trials and telemonitoring.

Heuristic-based user interface evaluation of the mobile centralized doctor appointment system

Purpose

This study aims to evaluate the interface of the mobile Centralized Doctor Appointment System (CDAS), the largest mobile e-government health application developed in Turkey to allow citizens to make medical appointments at public hospitals.

Design/methodology/approach

A total of 40 information systems engineers took part in the study. The evaluation process was mainly based on Nielsen’s heuristics. The data obtained in the evaluation process were enriched using system usability scale to conduct a more detailed analysis.

Findings

Based on the findings, problems related to the usability of the evaluated mobile health application were identified. The most violated heuristic items were found to be “error prevention” and “user control and freedom”, whereas the least violated heuristic item was “consistency and standards”. The participants generally categorized the usability problems they identified as “minor” or “major” according to their severity.

Originality/value

As a developing country, Turkey has made considerable investment in mobile e-government applications in recent years. It is equally important that mobile e-government services provided by public institutions have features that make these applications effective, efficient and satisfying for citizens. Therefore, the usability of mobile health applications in government services needs to be researched to improve their effectiveness and guide authorities, practitioners and designers.

HF app to support self-care among community dwelling adults with HF: A feasibility study

BACKGROUND

The prevalence of Heart Failure (HF) is expected to increase by 46% from 2012 to 2030, which will result in over 8 million adults with HF. The development and testing of interventions that can support HF self-care behaviors is critical.

AIM

Determine the: 1) feasibility of using the HF App in middle to older adult community dwelling patients with HF; and 2) acceptability of using the HF App mobile health application.

METHODS

A convenience sample of community dwelling HF participants daily used the HF App to enter physiologic data, answer questions about symptoms, reviewed HF education within the application and received reminders over a two-week period. Feasibility and acceptability measures were assessed using data extracted from the principal investigator's qualitative diary. In addition, two acceptability questionnaires were utilized.

RESULTS

All participants enrolled (N = 10) completed the two-week period. Participant mean age was 64.5 years. The mean scores on the acceptability of the HF App 19 (SD 2.87) indicated increased perceived benefit of using the app while the mean scores of acceptability of the education offered in the app 12.4 (SD 2.84) indicated that participants positively benefited from viewing the education. Qualitative results indicated that participants were more aware of their symptoms and the need to self-monitor.

CONCLUSIONS

This feasibility study points to the incorporation of mobile applications to support self-care as promising research that can be useful to aid middle to older individuals in performing effective HF self-care but further studies with a larger randomized sample is needed.

Usability Testing of a Smartphone Application for Delivering Qigong Training

A Qigong App was designed to promote a more flexible mode of delivering qigong training than face-to-face, with which individuals can access to this mind-body aerobic exercise more readily. The objective of the study was to examine the usability and acceptance of the App. Target participants were Cantonese- or Putonghua-speaking adults and owned a smartphone. First we conducted a pilot trial with 14 participants to examine the navigation feature of the App, followed by a main test. In the main test, another 100 participants reviewed the Qigong App and filled in a questionnaire on usability (System Usability Scale) and user acceptance (i.e., attitude, perceived ease of use, perceived usefulness, intention to use, and satisfaction), of which 89 completed the same questionnaire in a two-week interval. Qualitative feedback yielded from the pilot trial was summarized, and descriptive statistics, t-tests, and linear regressions were used in quantitative data analysis of the main test. The mean composite usability score in the main test was satisfactory (77.62 out of 100). Descriptive analyses showed that the majority of users found the Qigong App pleasant, user friendly, and useful for learning qigong. Participants indicated positive ratings for the items assessing usability and acceptance of the App. Regression results showed that certain characteristics predicted the ratings for some items, e.g., age as a predictor of scores of usability and perceived ease of use. The study provided researchers and practitioners with evidence of the usability and acceptance of an alternative qigong training mode that can enhance participants' access and motivation to practice qigong.

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.

Aging barriers influencing mobile health usability for older adults: A literature based framework (MOLD-US)

BACKGROUND

With the growing population of older adults as a potential user group of mHealth, the need increases for mHealth interventions to address specific aging characteristics of older adults. The existence of aging barriers to computer use is widely acknowledged. Yet, usability studies show that mHealth still fails to be appropriately designed for older adults and their expectations. To enhance designs of mHealth aimed at older adult populations, it is essential to gain insight into aging barriers that impact the usability of mHealth as experienced by these adults.

OBJECTIVES

This study aims to synthesize literature on aging barriers to digital (health) computer use, and explain, map and visualize these barriers in relation to the usability of mHealth by means of a framework.

METHODS

We performed a scoping review to synthesize and summarize reported physical and functional age barriers in relation to digital (mobile) health applications use. Aging barriers reported in the literature were mapped onto usability aspects categorized by Nielsen to explain their influence on user experience of mHealth. A framework (MOLD-US) was developed summarizing the evidence on the influence of aging barriers on mHealth use experienced by older adults.

RESULTS

Four key categories of aging barriers influencing usability of mHealth were identified: cognition, motivation, physical ability and perception. Effective and satisfactory use of mHealth by older adults is complicated by cognition and motivation barriers. Physical ability and perceptual barriers further increase the risk of user errors and fail to notice important interaction tasks. Complexities of medical conditions, such as diminished eye sight related to diabetes or deteriorated motor skills as a result of rheumatism, can cause errors in user interaction.

CONCLUSIONS

This research provides a novel framework for the exploration of aging barriers and their causes influencing mHealth usability in older adults. This framework allows for further systematic empirical testing and analysis of mHealth usability issues, as it enables results to be classified and interpreted based on impediments intrinsic to usability issues experienced by older adults. Importantly, the paper identifies a key need for future research on motivational barriers impeding mhealth use of older adults. More insights are needed in particular to disaggregating normal age related functional changes from specific medical conditions that influence experienced usefulness of mHealth by these adults.

"Mobile technology to improve heart failure outcomes: A proof of concept paper"

BACKGROUND

Heart failure (HF) causes significant symptom burden and human suffering with considerable economic burden due to hospital readmissions. Targeted interventions to encourage and support self-management behavior is warranted.

AIM

To test the proof of concept of a mobile application (HeartMapp) in improving self-care management of patients with heart failure.

METHOD

An exploratory inquiry used a field study strategy with purposeful sampling and constant comparative analysis to test the proof of concept of HeartMapp using The Business Model Canvas framework.

RESULTS

A total of 125 individuals, who were identified as potential candidates to use the HeartMapp completed the interview over a seven-week period in 2016. Constant comparative analysis indicated themes that Skilled Nursing Facilities had increased readmissions. Participants from Skilled Nursing Facilities reported concern on lack of staffing, star rating, and malpractice claims. Two types of patients were identified as early adapters of technology and those in denial. Health care facilities reported challenges on transitional care, nurses struggle with engagement of patients on self-care management. To avoid readmission penalty, hospitals task home care agencies to keep the patients home for 30-days. While home care agencies rely on remote telemonitoring reported that current telemonitoring devices are costly to maintain, thus exploring novel technology.

CONCLUSION

The Business Model Canvas provided directions for future testing of HeartMapp for its usability as an adjunct device in home health setting to improve self-management and enhance communication with providers, and ultimately reduce readmissions.

Primary Prevention of Asymptomatic Cardiovascular Disease Using Physiological Sensors Connected to an iOS App

Cardiovascular disease is the first cause of death and disease and one of the leading causes of disability in developed countries. The prevalence of this disease is expected to increase in coming years although the death rate may be lower due to better treatment. To present the design and development of a technology solution for primary prevention of cardiovascular disease in asymptomatic patients. The system aims to raise the population's awareness of the importance of adopting healthy heart habits by using self-feedback techniques. A series of sensors which makes it possible to detect cardiovascular risk factors in asymptomatic patients were used. These sensors enable evaluation of heart rate, blood pressure, SpO₂ -oxygen saturation in blood- and body temperature. This work has developed a modular solution centred on four parts: iOS app, sensors, server and web. The CoreBluetooth library, which carries out Bluetooth 4.0 communication, was used for the connection between the app and the sensors. The data files are stored on the iPad and the server by using CoreData and SQL mechanisms. The system was validated with 20 healthy volunteers and 10 patients with established structural heart disease. Once the samples had been obtained, a comparison of all the significant data was run, in addition to a statistical analysis. The result of this calculation was a total of 32 cases of first level significance correlations (p < 0.01), for example, the inverse relationship between the daily step count and high blood pressure (p = 0.008) and 24 s level cases (p < 0.05) such as the significant correlation between risk and age (p = 0.013). The system designed in this paper has made it possible to create an application capable of collecting data on cardiovascular risk factors through a sensor system that measures physiological variables and records physical activity and diet.

A Mobile Health Intervention to Improve Self-Care in Patients With Heart Failure: Pilot Randomized Control Trial

BACKGROUND

Heart failure (HF) is a progressive chronic disease affecting 6.5 million Americans and over 15 million individuals globally. Patients with HF are required to engage in complex self-care behaviors. Although the advancements in medicine have enabled people with HF to live longer, they often have poor health-related quality of life and experience severe and frequent symptoms that limit several aspects of their lives. Mobile phone apps have not only created new and interactive ways of communication between patients and health care providers but also provide a platform to enhance adherence to self-care management.

OBJECTIVE

The aim of this pilot study was to test the feasibility of a newly developed mobile app (HeartMapp) in improving self-care behaviors and quality of life of patients with HF and to calculate effect sizes for sample size calculation for a larger study.

METHODS

This was a pilot feasibility randomized controlled trial. Participants were enrolled in the hospital before discharge and followed at home for 30 days. The intervention group used HeartMapp (n=9), whereas the control group (n=9) received HF education. These apps were downloaded onto their mobile phones for daily use.

RESULTS

A total of 72% (13/18) participants completed the study; the mean age of the participants was 53 (SD 4.02) years, 56% (10/18) were females, 61% (11/18) lived alone, 33% (6/18) were African Americans, and 61% (11/18) used mobile phone to get health information. The mean engagement with HeartMapp was 78%. Results were promising with a trend that participants in the HeartMapp group had a significant mean score change on self-care management (8.7 vs 2.3; t3.38=11, P=.01), self-care confidence (6.7 vs 1.8; t2.53=11, P=.28), and HF knowledge (3 vs -0.66; t2.37=11, P=.04. Depression improved among both groups, more so in the control group (-1.14 vs -5.17; t1.97=11, P=.07). Quality of life declined among both groups, more so in the control group (2.14 vs 9.0; t-1.43=11, P=.18).

CONCLUSIONS

The trends demonstrated in this pilot feasibility study warrant further exploration on the use of HeartMapp to improve HF outcomes.

TRIAL REGISTRATION

Pilot study, no funding from National agencies, hence not registered.