Connected Mental Health: Systematic Mapping Study

BACKGROUND

Although mental health issues constitute an increasing global burden affecting a large number of people, the mental health care industry is still facing several care delivery barriers such as stigma, education, and cost. Connected mental health (CMH), which refers to the use of information and communication technologies in mental health care, can assist in overcoming these barriers.

OBJECTIVE

The aim of this systematic mapping study is to provide an overview and a structured understanding of CMH literature available in the Scopus database.

METHODS

A total of 289 selected publications were analyzed based on 8 classification criteria: publication year, publication source, research type, contribution type, empirical type, mental health issues, targeted cohort groups, and countries where the empirically evaluated studies were conducted.

RESULTS

The results showed that there was an increasing interest in CMH publications; journals were the main publication channels of the selected papers; exploratory research was the dominant research type; advantages and challenges of the use of technology for mental health care were the most investigated subjects; most of the selected studies had not been evaluated empirically; depression and anxiety were the most addressed mental disorders; young people were the most targeted cohort groups in the selected publications; and Australia, followed by the United States, was the country where most empirically evaluated studies were conducted.

CONCLUSIONS

CMH is a promising research field to present novel approaches to assist in the management, treatment, and diagnosis of mental health issues that can help overcome existing mental health care delivery barriers. Future research should be shifted toward providing evidence-based studies to examine the effectiveness of CMH solutions and identify related issues.

Machine Learning Model Based on Transthoracic Bioimpedance and Heart Rate Variability for Lung Fluid Accumulation Detection: Prospective Clinical Study

Background

Accumulation of excess body fluid and autonomic dysregulation are clinically important characteristics of acute decompensated heart failure. We hypothesized that transthoracic bioimpedance, a noninvasive, simple method for measuring fluid retention in lungs, and heart rate variability, an assessment of autonomic function, can be used for detection of fluid accumulation in patients with acute decompensated heart failure.

Objective

We aimed to evaluate the performance of transthoracic bioimpedance and heart rate variability parameters obtained using a fluid accumulation vest with carbon black–polydimethylsiloxane dry electrodes in a prospective clinical study (System for Heart Failure Identification Using an External Lung Fluid Device; SHIELD).

Methods

We computed 15 parameters: 8 were calculated from the model to fit Cole-Cole plots from transthoracic bioimpedance measurements (extracellular, intracellular, intracellular-extracellular difference, and intracellular-extracellular parallel circuit resistances as well as fitting error, resonance frequency, tissue heterogeneity, and cellular membrane capacitance), and 7 were based on linear (mean heart rate, low-frequency components of heart rate variability, high-frequency components of heart rate variability, normalized low-frequency components of heart rate variability, normalized high-frequency components of heart rate variability) and nonlinear (principal dynamic mode index of sympathetic function, and principal dynamic mode index of parasympathetic function) analysis of heart rate variability. We compared the values of these parameters between 3 participant data sets: control (n=32, patients who did not have heart failure), baseline (n=23, patients with acute decompensated heart failure taken at the time of admittance to the hospital), and discharge (n=17, patients with acute decompensated heart failure taken at the time of discharge from hospital). We used several machine learning approaches to classify participants with fluid accumulation (baseline) and without fluid accumulation (control and discharge), termed with fluid and without fluid groups, respectively.

Results

Among the 15 parameters, 3 transthoracic bioimpedance (extracellular resistance, R₀; difference in extracellular-intracellular resistance, R₀ – R_∞, and tissue heterogeneity, α) and 3 heart rate variability (high-frequency, normalized low-frequency, and normalized high-frequency components) parameters were found to be the most discriminatory between groups (patients with and patients without heart failure). R₀ and R₀ – R_∞ had significantly lower values for patients with heart failure than for those without heart failure (R₀: P=.006; R₀ – R_∞: P=.001), indicating that a higher volume of fluids accumulated in the lungs of patients with heart failure. A cubic support vector machine model using the 5 parameters achieved an accuracy of 92% for with fluid and without fluid group classification. The transthoracic bioimpedance parameters were related to intra- and extracellular fluid, whereas the heart rate variability parameters were mostly related to sympathetic activation.

Conclusions

This is useful, for instance, for an in-home diagnostic wearable to detect fluid accumulation. Results suggest that fluid accumulation, and subsequently acute decompensated heart failure detection, could be performed using transthoracic bioimpedance and heart rate variability measurements acquired with a wearable vest.

Developing a Mobile App (iGAM) to Promote Gingival Health by Professional Monitoring of Dental Selfies: User-Centered Design Approach

BACKGROUND

Dental visits are unpleasant; sometimes, patients only seek treatment when they are in intolerable pain. Recently, the novel coronavirus (COVID-19) pandemic has highlighted the need for remote communication when patients and dentists cannot meet in person. Gingivitis is very common and characterized by red, swollen, bleeding gums. Gingivitis heals within 10 days of professional care and with daily, thorough oral hygiene practices. If left untreated, however, its progress may lead to teeth becoming mobile or lost. Of the many medical apps currently available, none monitor gingivitis.

OBJECTIVE

This study aimed to present a characterization and development model of a mobile health (mHealth) app called iGAM, which focuses on periodontal health and improves the information flow between dentists and patients.

METHODS

A focus group discussed the potential of an app to monitor gingivitis, and 3 semistructured in-depth interviews were conducted on the use of apps for monitoring gum infections. We used a qualitative design process based on the Agile approach, which incorporated the following 5 steps: (1) user story, (2) use cases, (3) functional requirements, (4) nonfunctional requirements, and (5) Agile software development cycles. In a pilot study with 18 participants aged 18-45 years and with different levels of health literacy, participants were given a toothbrush, toothpaste, mouthwash, toothpicks, and dental floss. After installing iGAM, they were asked to photograph their gums weekly for 4 weeks.

RESULTS

All participants in the focus group believed in the potential of a mobile app to monitor gingivitis and reduce its severity. Concerns about security and privacy issues were discussed. From the interviews, 2 themes were derived: (1) "what's in it for me?" and (2) the need for a take-home message. The 5 cycles of development highlighted the importance of communication between dentists, app developers, and the pilot group. Qualitative analysis of the data from the pilot study showed difficulty with: (1) the camera, which was alleviated with the provision of mouth openers, and (2) the operation of the phone, which was alleviated by changing the app to be fully automated, with a weekly reminder and an instructions document. Final interviews showed satisfaction.

CONCLUSIONS

iGAM is the first mHealth app for monitoring gingivitis using self-photography. iGAM facilitates the information flow between dentists and patients between checkups and may be useful when face-to-face consultations are not possible (such as during the COVID-19 pandemic).

Prediction of heart failure hospitalizations based on the direct measurement of intrathoracic impedance

Aims

OptiVol fluid index was developed as a transthoracic impedance‐based indicator of short‐term risk for heart failure hospitalization (HFH). OptiVol is calculated as the accumulating difference between daily impedance (measured impedance) and long‐term average impedance (reference impedance). Measured impedance alone was thought to have limited prognostic utility; however, measured impedance has the advantage of being simple, direct, and possibly additive to OptiVol fluid index in establishing long‐term HFH risk. We tested the hypothesis that directly measured impedance has independent prognostic value in predicting long‐term HFH risk and that changes in measured impedance result in a change in predicted long‐term HFH risk.

Methods and results

A retrospective analysis of 1719 patients studied in PARTNERS‐HF, FAST, and RAFT studies was performed. Baseline measured impedance was determined using daily values averaged over 1 month, from Month 6 to 7 post implant; change in measured impedance was determined from values averaged over 1 month, from Month 7 to 8 post implant compared with baseline. The predictive value of baseline measured impedance for HFHs was assessed beginning 7 months post implant. The predictive value of a change in measured impedance for a change in HFHs was assessed beginning 8 months post implant. Baseline measured impedance successfully predicted HFHs. For example, 3 year HFH rate for low baseline impedance < 70 Ω was 23%; for high baseline impedance ≥ 70 Ω was 15% (P < 0.001). Changes in measured impedance resulted in changes in predicted HFHs. For example, when a baseline impedance of ≥70 fell during follow‐up to <70 Ω, the subsequent HFHs were 15% compared with 4% in patients with measured impedance that remained >70 Ω (P = 0.004). In addition, when baseline measured impedance fell during follow‐up by >1%, 2%, or 3%, subsequent HFHs increased to 13%, 17%, or 18%, respectively. Finally, the prognostic value of measured impedance was additive to the prognostic value of the OptiVol fluid index.

Conclusions

Direct measurements of intrathoracic impedance using an implanted device can be used to stratify patients at varying risk of long‐term HFH. These direct measurements of impedance have practical clinical appeal because they are simple, continuous, and ambulatory.

Effects of an Innovative Telerehabilitation Intervention for People With Parkinson's Disease on Quality of Life, Motor, and Non-motor Abilities

Parkinson's disease (PD) often leads to multifactorial motor and non-motor disabilities with resultant social restrictions. Continuity of care in this pathology, including a tailored home rehabilitation, is crucial to improve or maintain the quality of life for patients. The aim of this multicenter study was to test in a pilot sample of PD patients the efficiency and efficacy of the Human Empowerment Aging and Disability (HEAD) program. The virtual reality HEAD program was administered in two consecutive phases: (1) in clinic (ClinicHEAD, 12 45-minutes sessions, 3 sessions/week); (2) at home (HomeHEAD, 60 45-minutes sessions, 5 sessions/week). Thirty-one PD outpatients were enrolled [mean age (SD) = 66.84 (9.13)]. All patients performed ClinicHEAD, and after allocation (ratio 1:2) were assigned to the HomeHEAD or the Usual Care (UC) group. Motor, cognitive and behavioral outcome measures were assessed at enrollment (T0), at hospital discharge (T1), at 4 (T2) and 7 (T3) months after baseline. After ClinicHEAD (T1 vs. T0 comparison) a significant (p < 0.05) improvement in functional mobility, balance, upper limb mobility, global cognitive function, memory, quality of life and psychological well-being was observed. After the HomeHEAD intervention there was an additional enhancement for upper limb mobility. At T3 follow-up, the UC group that did not continue the HEAD program at home showed a worsening with respect to the HomeHEAD group in balance and functional mobility. Furthermore, in the HomeHEAD group, a positive association was observed between adherence, mental and physical health (SF-12). A trend was also registered between adherence and positive affect. The digital health patient-tailored rehabilitation program resulted in improving motor and non-motor abilities and quality of life in clinical setting, enhancing the motor function in telerehabilitation at home, and maintaining the non-motor abilities and quality of life at follow-up. In the near future, people with PD can be supported also at home with individualized rehabilitation strategies for a better quality of life and wellbeing along with lower costs for society.

[Cardiac rhythm monitoring : New tools on the horizon]

Cardiac rhythm monitoring plays an integral role in the diagnosis and treatment of various conditions. Technological developments of recent years have partly increased the ease of use and the availability of cardiac rhythm monitoring. Yet, the multitude of options has also added confusion. Various manufacturers offer devices for pulse wave and electrocardiogram analysis. Their use plays an important role in clinical routine, both for diagnostic purposes and for the need to interpret opportunistic findings. This article is intended to provide an overview of existing technologies and to highlight their advantages and disadvantages. It also is intended to introduce future technologies. In any case it is important to emphasize that numerous clinical trials will be required to evaluate the benefit of modern cardiac rhythm monitoring and foster its medical use.

The Role of Wearables in Heart Failure

PURPOSE OF REVIEW

This review discusses how wearable devices-sensors externally applied to the body to measure a physiological signal-can be used in heart failure (HF) care.

RECENT FINDINGS

Most wearables are marketed to consumers and can measure movement, heart rate, and blood pressure; detect and monitor arrhythmia; and support exercise training and rehabilitation. Wearable devices targeted at healthcare professionals include ECG patch recorders and vests, patches, and textiles with in-built sensors for improved prognostication and the early detection of acute decompensation. Integrating data from wearables into clinical decision-making has been slow due to clinical inertia and concerns regarding data security and validity, lack of evidence of meaningful impact, interoperability, regulatory and reimbursement issues, and legal liability. Although few studies have assessed how best to integrate wearable technologies into clinical practice, their use is rapidly expanding and may support improved decision-making by patients and healthcare professionals along the whole patient pathway.

Mildly symptomatic heart failure with reduced ejection fraction: diagnostic and therapeutic considerations

AIMS

Whereas up to about half of patients with heart failure with reduced ejection fraction (HFrEF) report no or only mild symptoms and are considered as clinically stable, the progressive nature of HFrEF, often silent, renders clinical stability a misleading situation, especially if disease progression is unrecognized. We highlight the challenges in the definition of clinical stability and mild symptomatic status in HFrEF, outline clinical characteristics and available diagnostic tools, and discuss evidence and gaps in the current guidelines for the management of these patients.

METHODS AND RESULTS

This is a state-of-the-art review that focuses on clinical, diagnostic, and therapeutic aspects in mildly symptomatic HFrEF patients; summarizes the challenges; and proposes directions for future research in this group of patients. The New York Heart Association classification has been widely used as a measure of prognosis in HFrEF, but it lacks objectivity and reproducibility in terms of symptoms assessment. The definition of clinical stability as described in current guidelines is vague and may often lead to underdiagnosis of disease progression in patients who appear to be 'stable' but in fact are at an increased risk of clinical worsening, hospitalization, or death. Although an increasing number of clinical trials proved that the efficacy of HFrEF therapies was unrelated to the symptomatic status of patients and led to their implementation early in the course of the disease, clinical inertia in terms of under-prescription or underdosing of guideline-recommended medications in mildly symptomatic HFrEF patients is still a challenging issue to deal with.

CONCLUSIONS

Mildly symptomatic status in a patient with HFrEF is very frequent; it should not be ignored and should not be regarded as an index of disease stability. The application of risk scores designed to predict mortality and mode of death should be engaged among mildly symptomatic patients, not only to identify the most suitable HF candidates for cardioverter defibrillator implantation, but also to identify patients who might benefit from early intensification of medical treatment before the implementation of more interventional approaches.

Promotion of Preconception Care Among Adolescents and Young Adults by Conversational Agent

PURPOSE

Preconception care is important for all women to improve infant and maternal health outcomes and may be especially important for adolescents and young adults. This study assesses the acceptance, usability, and use of an automated intervention to screen women on 108 preconception care risks and address them over the course of a year via a Web-based virtual animated health counselor and compares these measures for the adolescent and young adult users aged 18-25 years with those of users aged 26-34 years. We hypothesize that the younger cohort will have significantly greater use of and satisfaction with the online intervention.

METHODS

A randomized controlled trial involving a national sample of 528 women was conducted. We present a secondary data analysis on the system use and self-reported usability and satisfaction of the 79 women aged 18-25 years randomized to the intervention group, compared with the 183 women aged 26-34 years in the intervention group. Participants were required to self-identify as female, black or African American, aged 18-34 years, not pregnant, and English-speaking and were recruited through a variety of advertisements and outreach activities.

RESULTS

Of the adolescent and young adult participants (aged 18-25 years) enrolled and randomized to the intervention, 20.25% of participants accessed the system 0 times; 29.11%, 1-3 times; and 50.63%, >3 times over the course of a year. At the end of the year, almost all (96.4%) indicated they had either acted on recommendations made by the agent or planned to. Most (75.0%) said they would recommend the system to someone they knew. There were no significant differences between the two age groups on intervention use or satisfaction.

CONCLUSIONS

Web-based conversational agents are a viable medium for delivering longitudinal preconception care counseling to adolescents and young adults.

Rapid implementation of a COVID-19 remote patient monitoring program

OBJECTIVE

The study sought to evaluate early lessons from a remote patient monitoring engagement and education technology solution for patients with coronavirus disease 2019 (COVID-19) symptoms.

MATERIALS AND METHODS

A COVID-19-specific remote patient monitoring solution (GetWell Loop) was offered to patients with COVID-19 symptoms. The program engaged patients and provided educational materials and the opportunity to share concerns. Alerts were resolved through a virtual care workforce of providers and medical students.

RESULTS

Between March 18 and April 20, 2020, 2255 of 3701 (60.93%) patients with COVID-19 symptoms enrolled, resulting in over 2303 alerts, 4613 messages, 13 hospital admissions, and 91 emergency room visits. A satisfaction survey was given to 300 patient respondents, 74% of whom would be extremely likely to recommend their doctor.

DISCUSSION

This program provided a safe and satisfying experience for patients while minimizing COVID-19 exposure and in-person healthcare utilization.

CONCLUSIONS

Remote patient monitoring appears to be an effective approach for managing COVID-19 symptoms at home.

Rapid implementation of a COVID-19 remote patient monitoring program

OBJECTIVE

The study sought to evaluate early lessons from a remote patient monitoring engagement and education technology solution for patients with coronavirus disease 2019 (COVID-19) symptoms.

MATERIALS AND METHODS

A COVID-19-specific remote patient monitoring solution (GetWell Loop) was offered to patients with COVID-19 symptoms. The program engaged patients and provided educational materials and the opportunity to share concerns. Alerts were resolved through a virtual care workforce of providers and medical students.

RESULTS

Between March 18 and April 20, 2020, 2255 of 3701 (60.93%) patients with COVID-19 symptoms enrolled, resulting in over 2303 alerts, 4613 messages, 13 hospital admissions, and 91 emergency room visits. A satisfaction survey was given to 300 patient respondents, 74% of whom would be extremely likely to recommend their doctor.

DISCUSSION

This program provided a safe and satisfying experience for patients while minimizing COVID-19 exposure and in-person healthcare utilization.

CONCLUSIONS

Remote patient monitoring appears to be an effective approach for managing COVID-19 symptoms at home.

Computer-Controlled Virtual Humans in Patient-Facing Systems: Systematic Review and Meta-Analysis

BACKGROUND

Virtual humans (VH) are computer-generated characters that appear humanlike and simulate face-to-face conversations using verbal and nonverbal cues. Unlike formless conversational agents, like smart speakers or chatbots, VH bring together the capabilities of both a conversational agent and an interactive avatar (computer-represented digital characters). Although their use in patient-facing systems has garnered substantial interest, it is unknown to what extent VH are effective in health applications.

OBJECTIVE

The purpose of this review was to examine the effectiveness of VH in patient-facing systems. The design and implementation characteristics of these systems were also examined.

METHODS

Electronic bibliographic databases were searched for peer-reviewed articles with relevant key terms. Studies were included in the systematic review if they designed or evaluated VH in patient-facing systems. Of the included studies, studies that used a randomized controlled trial to evaluate VH were included in the meta-analysis; they were then summarized using the PICOTS framework (population, intervention, comparison group, outcomes, time frame, setting). Summary effect sizes, using random-effects models, were calculated, and the risk of bias was assessed.

RESULTS

Among the 8,125 unique records identified, 53 articles describing 33 unique systems, were qualitatively, systematically reviewed. Two distinct design categories emerged - simple VH and VH augmented with health sensors and trackers. Of the 53 articles, 16 (26 studies) with 44 primary and 22 secondary outcomes were included in the meta-analysis. Meta-analysis of the 44 primary outcome measures revealed a significant difference between intervention and control conditions, favoring the VH intervention (SMD = .166, 95% CI .039-.292, P=.012), but with evidence of some heterogeneity, I2=49.3%. There were more cross-sectional (k=15) than longitudinal studies (k=11). The intervention was delivered using a personal computer in most studies (k=18), followed by a tablet (k=4), mobile kiosk (k=2), head-mounted display (k=1), and a desktop computer in a community center (k=1).

CONCLUSIONS

We offer evidence for the efficacy of VH in patient-facing systems. Considering that studies included different population and outcome types, more focused analysis is needed in the future. Future studies also need to identify what features of virtual human interventions contribute toward their effectiveness.

Lived Experiences and Technological Literacy of Heart Failure Patients and Clinicians at a Cardiac Care Centre in Uganda

Background

Digital health could serve as a low-cost means of enabling better self-care in patients living with heart failure (HF) in resource-limited settings such as Uganda. However, digital health interventions previously deployed in such settings have been unsuccessful due to a lack of local patient and clinician engagement in the design process.

Objective

To engage Ugandan HF patients and clinicians regarding their experiences with HF management and technology, so as to inform the future design of a digital health intervention for HF patients in Uganda.

Methods

The study employed a convergent parallel mixed-methods design. Data collection was completed at the Uganda Heart Institute in Kampala, Uganda. Data were ascertained through a patient survey and semi-structured interviews completed with HF patients, caregivers, physicians, and nurses. A conventional content analysis approach was used to qualitatively examine interview transcripts.

Findings

Survey data were collected from 101 HF patients (62 female/39 male, aged 54.2 ± 17.5 years). Nearly half (48%) disagreed that they knew what to do in response to changes in their HF symptoms. Almost all patients (98%) had access to a mobile device. Many patients (63%) identified as comfortable in using mobile money - a local set of services that use Unstructured Supplementary Service Data (USSD). Interviews were completed with 19 HF patients, three caregivers, seven physicians, and three nurses. Qualitative analysis revealed four clusters of themes: overdependence of patients on the clinic, inconvenience associated with attending the clinic, inconsistent patient self-care behaviours at home, and technological abilities that favoured USSD-based services.

Conclusions

Ugandan HF patients possess unmet information needs that leave them ill-equipped to care for themselves. Future digital health interventions for this population should empower patients with HF-specific information and reassurance in their self-care abilities. Based on patient preferences, such systems should harness USSD technology with which most patients are already comfortable.

The detrimental effect of COVID-19 nationwide quarantine on accelerometer-assessed physical activity of heart failure patients

AIMS

A reduction of habitual physical activity due to prolonged COVID-19 quarantine can have serious consequences for patients with cardiovascular diseases, such as heart failure. This study aimed to explore the effect of COVID-19 nationwide quarantine on accelerometer-assessed physical activity of heart failure patients.

METHODS AND RESULTS

We analysed the daily number of steps in 26 heart failure patients during a 6-week period that included 3 weeks immediately preceding the onset of the quarantine and the first 3 weeks of the quarantine. The daily number of steps was assessed using a wrist-worn accelerometer worn by the patients as part of an ongoing randomized controlled trial. Multilevel modelling was used to explore the effect of the quarantine on the daily step count adjusted for weather conditions. As compared with the 3 weeks before the onset of the quarantine, the step count was significantly lower during each of the first 3 weeks of the quarantine (P < 0.05). When the daily step count was averaged across the 3 weeks before and during the quarantine, the decrease amounted to 1134 (SE 189) steps per day (P < 0.001), which translated to a 16.2% decrease.

CONCLUSIONS

The introduction of the nationwide quarantine due to COVID-19 had a detrimental effect on the level of habitual physical activity in heart failure patients, leading to an abrupt decrease of daily step count that lasted for at least the 3-week study period. Staying active and maintaining sufficient levels of physical activity during the COVID-19 pandemic are essential despite the unfavourable circumstances of quarantine.

Patients' needs and perspectives for using mobile phone interventions to improve heart failure self-care: A qualitative study

AIMS

To explore heart failure patients' needs and perspectives for using mobile health technology at home before developing a mobile phone-based heart failure self-care intervention.

DESIGN

A qualitative interview study.

METHODS

Purposive sampling was used to conduct semi-structured individual interviews with patients diagnosed with chronic heart failure (N = 20). Data were collected from November 2018 - May 2019. All interviews were audio-recorded and transcribed verbatim and data were analysed using qualitative content analysis.

RESULTS

The four themes that emerged from the interviews were as follows: 'The demand for reliable and customized health information', 'Valuable features of mobile phone applications', 'Barriers to adopting mobile health service', and 'Expected benefits of using mobile health technology'. Participants in this study required personalized health-related information and reminders for improving their self-care behaviours. However, while difficulties in using mobile phone applications posed the main obstacle, users expected mobile health services to improve their overall quality of life.

CONCLUSION

Despite mobile phone technology's potential benefits for effective self-care strategies at home, there were some obstacles such as security issues, application costs, and the need for user friendly designs and reliable information for patients' optimal use.

IMPACT

This study highlights that healthcare professionals should consider patients' needs and preferences to promote the acceptability of mobile health technology. This study's findings can guide the future design and implementation of mobile health interventions for improving self-care among patients with heart failure.

A Specific Mobile Health Application for Older HIV-Infected Patients: Usability and Patient's Satisfaction

Background: HIV infection is an increasingly complex chronic disease associated with numerous medical, psychological, and social problems. The life expectancy of affected patients has increased considerably. Medical apps could also play a role in prevention and management of comorbid conditions in the HIV-infected population. Objectives: To determine the usefulness of an app designed specifically for HIV-infected patients aged 60 years or older and to assess changes in patient satisfaction, adherence to treatment, and quality of health care. Methods: A randomized clinical trial was conducted, including 100 patients (50 per group): (1) an experimental group comprising patients using the app + routine medical care (app group) and (2) with routine medical care (control group). The usability of the app and patient satisfaction were evaluated in the app group at week 48. Quality of life, adherence to treatment, and clinical parameters were compared between both groups at 48 weeks, as well as the number of face-to-face visits. Results: We found that 52.2% and 73.8% of patients in the app group used the app at weeks 24 and 48, respectively. Patients used the app for a mean of 23.7 (±2.84) days over the 48 weeks. The most visited screens were health counseling and medical records (24.8% and 22.2%, respectively). At week 48, 85.2% of patients thought that the app was useful and 91.4% would recommend the app to friends or relatives. The app was well valued by participants (4.79 [±0.21] of 5.00) and 64.6% thought that the app improved their health care.

Towards personalized fluid monitoring in haemodialysis patients: thoracic bioimpedance signal shows strong correlation with fluid changes, a cohort study

Background

Haemodialysis (HD) patients are burdened by frequent fluid shifts which amplify their comorbidities. Bioimpedance (bioZ) is a promising technique to monitor changes in fluid status. The aim of this study is to investigate if the thoracic bioZ signal can track fluid changes during a HD session.

Methods

Prevalent patients from a single centre HD unit were monitored during one to six consecutive HD sessions using a wearable multi-frequency thoracic bioZ device. Ultrafiltration volume (UFV) was determined based on the interdialytic weight gain and target dry weight set by clinicians. The correlation between the bioZ signal and UFV was analysed on population level. Additionally regression models were built and validated per dialysis session.

Results

66 patients were included, resulting in a total of 133 HD sessions. Spearman correlation between the thoracic bioZ and UFV showed a significant strong correlation of 0.755 (p < 0.01) on population level. Regression analysis per session revealed a strong relation between the bioZ value and the UFV (R² = 0.982). The fluid extraction prediction error of the leave-one-out cross validation was very small (56.2 ml [− 121.1–194.1 ml]) across all sessions at all frequencies.

Conclusions

This study demonstrated that thoracic bioZ is strongly correlated with fluid shifts during HD over a large range of UFVs. Furthermore, leave-one-out cross validation is a step towards personalized fluid monitoring during HD and could contribute to the creation of autonomous dialysis.

The Role of Electrocardiography in Occupational Medicine, from Einthoven's Invention to the Digital Era of Wearable Devices

Clinical-instrumental investigations, such as electrocardiography (ECG), represent a corollary of a procedures that, nowadays, is called upon as part of the principles of precision medicine. However when carrying out the professional routine examinations, most tend to ignore how a “simple” instrument can offer indispensable support in clinical practice, even in occupational medicine. The advent of the digital age, made of silicon and printed circuit boards, has allowed the miniaturization of the electronic components of these electro-medical devices. Finally, the adoption of patient wearables in medicine has been rapidly expanding worldwide for a number of years. This has been driven mainly by consumers’ demand to monitor their own health. With the ongoing research and development of new features capable of assessing and transmitting real-time biometric data, the impact of wearables on cardiovascular management has become inevitable. Despite the potential offered by this technology, as evident from the scientific literature, the application of these devices in the field of health and safety in the workplace is still limited. This may also be due to the lack of targeted scientific research. While offering great potential, it is very important to consider and evaluate ethical aspects related to the use of these smart devices, such as the management of the collected data relating to the physiological parameters and the location of the worker. This technology is to be considered as being aimed at monitoring the subject’s physiological parameters, and not at the diagnosis of any pathological condition, which should always be on charge of the medical specialist We conducted a review of the evolution of the role that electrophysiology plays as part of occupational health and safety management and on its possible future use, thanks to ongoing technological innovation.

Advances in accelerometry for cardiovascular patients: a systematic review with practical recommendations

Aims

Accelerometers are becoming increasingly commonplace for assessing physical activity; however, their use in patients with cardiovascular diseases is relatively substandard. We aimed to systematically review the methods used for collecting and processing accelerometer data in cardiology, using the example of heart failure, and to provide practical recommendations on how to improve objective physical activity assessment in patients with cardiovascular diseases by using accelerometers.

Methods and results

Four electronic databases were searched up to September 2019 for observational, interventional, and validation studies using accelerometers to assess physical activity in patients with heart failure. Study and population characteristics, details of accelerometry data collection and processing, and description of physical activity metrics were extracted from the eligible studies and synthesized. To assess the quality and completeness of accelerometer reporting, the studies were scored using 12 items on data collection and processing, such as the placement of accelerometer, days of data collected, and criteria for non‐wear of the accelerometer. In 60 eligible studies with 3500 patients (of those, 536 were heart failure with preserved ejection fraction patients), a wide variety of accelerometer brands (n = 27) and models (n = 46) were used, with Actigraph being the most frequent (n = 12), followed by Fitbit (n = 5). The accelerometer was usually worn on the hip (n = 32), and the most prevalent wear period was 7 days (n = 22). The median wear time required for a valid day was 600 min, and between two and five valid days was required for a patient to be included in the analysis. The most common measures of physical activity were steps (n = 20), activity counts (n = 15), and time spent in moderate‐to‐vigorous physical activity (n = 14). Only three studies validated accelerometers in a heart failure population, showing that their accuracy deteriorates at slower speeds. Studies failed to report between one and six (median 4) of the 12 scored items, with non‐wear time criteria and valid day definition being the most underreported items.

Conclusions

The use of accelerometers in cardiology lacks consistency and reporting on data collection, and processing methods need to be improved. Furthermore, calculating metrics based on raw acceleration and machine learning techniques is lacking, opening the opportunity for future exploration. Therefore, we encourage researchers and clinicians to improve the quality and transparency of data collection and processing by following our proposed practical recommendations for using accelerometers in patients with cardiovascular diseases, which are outlined in the article.

Feature rearrangement based deep learning system for predicting heart failure mortality

BACKGROUND AND OBJECTIVE

Heart Failure is a clinical syndrome commonly caused by any structural or functional impairment. Fast and accurate mortality prediction for Heart Failure is essential to improve the health care of patients and prevent them from death. However, due to the imbalance problem and poor feature representation in Heart Failure data, mortality prediction of Heart Failure is difficult with some simple models. To handle these problems, this study is focused on proposing a fast and accurate Heart Failure mortality prediction framework.

METHODS

This paper proposes a feature rearrangement based deep learning system for heart failure mortality prediction. The proposed framework improves the performance of predicting heart failure mortality by handling imbalance problem and achieving better feature representation. This paper also proposes a method named Feature rearrangement based convolutional layer, which demonstrates that the order of the input features is essential for the convolutional network.

RESULTS

The proposed system is experimentally evaluated on real-world Heart Failure data collected from the EHR system of Shanghai Shuguang Hospital, where 10,198 in-patients records are extracted between March 2009 and April 2016. Internal comparison results illustrate that the proposed framework achieves the best performance for Heart Failure mortality prediction. Extensive experimental results compared with other machine learning methods demonstrate that the proposed method has the highest average accuracy and area under the curve while predicting the three goals of in-hospital mortality, 30-day mortality, and 1-year mortality. Finally, top 12 essential clinical features are mined with their chi-square scores, which can help to assist clinicians in the treatment and research of heart failure.

CONCLUSIONS

The proposed method successfully predict different target in three observation windows. Feature rearrangement based convolutional layer and Focal loss are employed into the proposed framework, which helps promote the prediction accuracy of Heart Failure death. The proposed method is fast and accurate for predicting heart failure mortality, especially for imbalance situation. This paper also provide a reasonable pipeline to model EHRs data and handle imbalance problem in medical data.

Wearable Monitoring and Interpretable Machine Learning Can Objectively Track Progression in Patients during Cardiac Rehabilitation

Cardiovascular diseases (CVD) are often characterized by their multifactorial complexity. This makes remote monitoring and ambulatory cardiac rehabilitation (CR) therapy challenging. Current wearable multimodal devices enable remote monitoring. Machine learning (ML) and artificial intelligence (AI) can help in tackling multifaceted datasets. However, for clinical acceptance, easy interpretability of the AI models is crucial. The goal of the present study was to investigate whether a multi-parameter sensor could be used during a standardized activity test to interpret functional capacity in the longitudinal follow-up of CR patients. A total of 129 patients were followed for 3 months during CR using 6-min walking tests (6MWT) equipped with a wearable ECG and accelerometer device. Functional capacity was assessed based on 6MWT distance (6MWD). Linear and nonlinear interpretable models were explored to predict 6MWD. The t-distributed stochastic neighboring embedding (t-SNE) technique was exploited to embed and visualize high dimensional data. The performance of support vector machine (SVM) models, combining different features and using different kernel types, to predict functional capacity was evaluated. The SVM model, using chronotropic response and effort as input features, showed a mean absolute error of 42.8 m (±36.8 m). The 3D-maps derived using the t-SNE technique visualized the relationship between sensor-derived biomarkers and functional capacity, which enables tracking of the evolution of patients throughout the CR program. The current study showed that wearable monitoring combined with interpretable ML can objectively track clinical progression in a CR population. These results pave the road towards ambulatory CR.

Conducting clinical trials in heart failure during (and after) the COVID-19 pandemic: an Expert Consensus Position Paper from the Heart Failure Association (HFA) of the European Society of Cardiology (ESC)

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has important implications for the safety of participants in clinical trials and the research staff caring for them and, consequently, for the trials themselves. Patients with heart failure may be at greater risk of infection with COVID-19 and the consequences might also be more serious, but they are also at risk of adverse outcomes if their clinical care is compromised. As physicians and clinical trialists, it is our responsibility to ensure safe and effective care is delivered to trial participants without affecting the integrity of the trial. The social contract with our patients demands no less. Many regulatory authorities from different world regions have issued guidance statements regarding the conduct of clinical trials during this COVID-19 crisis. However, international trials may benefit from expert guidance from a global panel of experts to supplement local advice and regulations, thereby enhancing the safety of participants and the integrity of the trial. Accordingly, the Heart Failure Association of the European Society of Cardiology on 21 and 22 March 2020 conducted web-based meetings with expert clinical trialists in Europe, North America, South America, Australia, and Asia. The main objectives of this Expert Position Paper are to highlight the challenges that this pandemic poses for the conduct of clinical trials in heart failure and to offer advice on how they might be overcome, with some practical examples. While this panel of experts are focused on heart failure clinical trials, these discussions and recommendations may apply to clinical trials in other therapeutic areas.

Emerging Technologies for Identifying Atrial Fibrillation

Atrial fibrillation (AF) is a major cause of morbidity and mortality globally, and much of this is driven by challenges in its timely diagnosis and treatment. Existing and emerging mobile technologies have been used to successfully identify AF in a variety of clinical and community settings, and while these technologies offer great promise for revolutionizing AF detection and screening, several major barriers may impede their effectiveness. The unclear clinical significance of device-detected AF, potential challenges in integrating patient-generated data into existing healthcare systems and clinical workflows, harm resulting from potential false positives, and identifying the appropriate scope of population-based screening efforts are all potential concerns that warrant further investigation. It is crucial for stakeholders such as healthcare providers, researchers, funding agencies, insurers, and engineers to actively work together in fulfilling the tremendous potential of mobile technologies to improve AF identification and management on a population level.

Effects of self-management interventions on heart failure: Systematic review and meta-analysis of randomized controlled trials

BACKGROUND

Self-management intervention is an important component of disease management in patients with heart failure. It can improve heart failure knowledge, quality of life, and heart failure-related hospitalizations of heart failure patients. However, studies on the effect of two self-management interventions tasks have reported conflicting results.

OBJECTIVE

This study conducted an up-to-date systematic review of the literature to evaluate the effects of self-management interventions on heart failure knowledge, quality of life, and heart failure-related hospitalizations in patients with heart failure.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

We searched PubMed, Embase, Web of Science, Cochrane Library, and the references of articles in 14th December 2019.

METHODS

The study characteristics included: authors, year, country, sample size, mean age of patients with heart failure, duration of intervention, recruitment and intervention delivery, interventions based on self-efficacy theory, cognitive behavioral therapy, disease management, self-care education. The risk of bias for each study was assessed independently by two investigators based on the Cochrane Handbook. This study used Revman to analyze different research outcomes. The fixed-effect model was used in the absence of significant heterogeneity or low heterogeneity, and if the heterogeneity was high, the random effect model was used.

RESULTS

A total of 4977 publications were retrieved in this study. After eliminating duplicates and screening for titles and abstracts, 209 articles were retrieved for full-text evaluation. Finally, a total sample size analyzed across 15 randomized controlled trials was 2630 participants. This study showed that self-management interventions significantly improved heart failure knowledge (0.61, 95% confidence interval (CI) 0.27-0.95, p = 0.0004), quality of life (0.20, 95% CI 0.02-0.38, p = 0.03), and heart failure-related hospitalization (OR 0.40, 95% CI 0.29 to 0.55, p<0.00001) in patients with heart failure.

CONCLUSIONS

This study reveals the beneficial effects of self-management interventions on heart failure knowledge, quality of life, and heart failure-related hospitalization in patients with heart failure. Therefore, high quality randomized controlled designs are needed to explore the optimal self-management interventions for patients with heart failure. Tweetable abstract: This study reveals self-management interventions can improve heart failure knowledge, quality of life, and reduced heart failure-related hospitalization.

Utilising digital health to improve medication-related quality of care for hypertensive patients: An integrative literature review

BACKGROUND

Hypertension or high blood pressure is considered as a significant contributor and risk factor to many serious conditions, approximately 1.13 billion people have hypertension globally. However, the integrated technologies can upscale health provisions and improve the effectiveness of the healthcare system. WHO has recommended that the digital health interventions (DHIs) and the Health System Challenges should be used in tandem in addressing health.

AIM

To summarise the outcomes from a range of research which investigated the use of DHI to improve the medication-related quality of care (MRQOC) for hypertensive patients.

METHODS

An integrative literature review was undertaken in October 2019 using the Medline, Cumulative Index of Nursing and Allied Health Literature, and Scopus databases for publications in English with no date limit.

RESULTS

In total, 18433 participants were included in this review from 28 studies meeting the eligibility criteria. There were 19 DHI identified within eight countries: Australia, Canada, India, South Korea, Lebanon, Pakistan, the United Kingdom, and the United States of America. The DHI were provided as community-based, clinical-based and home-based program through mobile phone, mobile health system, short message service, and telehealth, digital medicine, and online healthcare (web-based). The mean age of participants was 59 ranging from 42 to 81 years with an average mean systolic blood pressure of 143.3 mmHg at baseline, ranging from 129.0 mmHg to 159.0 mmHg. The proportion of male participants ranged from 13.9% to 92.0%. Eighteen interventions showed evidence of reduction in blood pressure and improvement of self-management in relation to medication adherence and blood pressure control. The reduction of systolic blood pressure ranged between 1.9 mmHg and 26.0 mmHg, with a mean of 10.8 mmHg. The digital health was found positively associated with the MRQOC for hypertensive patients such as improvement in medication adherence and medication management; better blood pressure control; maintaining follow-ups appointment and self-management; increasing access to healthcare particularly among patients living in rural area; and reducing adverse events. However, some interventions found no significant effect on hypertensive care. The follow up duration varied between 2 mo and 18 mo with an average attrition rate of 10.1%, ranging from 0.0% to 17.4%.

CONCLUSION

Utilising digital health innovation for hypertensive care in different settings with tailored interventions positively impacted on MRQOC leading to an improvement of patient outcomes and their quality of life. Nevertheless, inconclusive findings were found in some interventions, and inconsistent outcomes between DHI were noted. A future research and evidence-based DHI for hypertension or chronic diseases should be developed through the evidence-to-decision framework and guidelines.

Technical Metrics Used to Evaluate Health Care Chatbots: Scoping Review

BACKGROUND

Dialog agents (chatbots) have a long history of application in health care, where they have been used for tasks such as supporting patient self-management and providing counseling. Their use is expected to grow with increasing demands on health systems and improving artificial intelligence (AI) capability. Approaches to the evaluation of health care chatbots, however, appear to be diverse and haphazard, resulting in a potential barrier to the advancement of the field.

OBJECTIVE

This study aims to identify the technical (nonclinical) metrics used by previous studies to evaluate health care chatbots.

METHODS

Studies were identified by searching 7 bibliographic databases (eg, MEDLINE and PsycINFO) in addition to conducting backward and forward reference list checking of the included studies and relevant reviews. The studies were independently selected by two reviewers who then extracted data from the included studies. Extracted data were synthesized narratively by grouping the identified metrics into categories based on the aspect of chatbots that the metrics evaluated.

RESULTS

Of the 1498 citations retrieved, 65 studies were included in this review. Chatbots were evaluated using 27 technical metrics, which were related to chatbots as a whole (eg, usability, classifier performance, speed), response generation (eg, comprehensibility, realism, repetitiveness), response understanding (eg, chatbot understanding as assessed by users, word error rate, concept error rate), and esthetics (eg, appearance of the virtual agent, background color, and content).

CONCLUSIONS

The technical metrics of health chatbot studies were diverse, with survey designs and global usability metrics dominating. The lack of standardization and paucity of objective measures make it difficult to compare the performance of health chatbots and could inhibit advancement of the field. We suggest that researchers more frequently include metrics computed from conversation logs. In addition, we recommend the development of a framework of technical metrics with recommendations for specific circumstances for their inclusion in chatbot studies.

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

Selection of private or public hospital care: examining the care-seeking behaviour of patients with private health insurance

Background

This study aimed to examine the healthcare-seeking (hospital, primary and preventive care) and healthcare utilisation behaviour of patients with private health insurance (PHI) in Australia. It also aimed to examine the socioeconomic, demographic and lifestyle factors that influence the choice of hospital care in Australia.

Method

A logistic regression model with repeated measure t-test and Pearson’s Chi-square test were used to identify the factors that affect the choice of care. Data from waves 9 (2009) and 13 (2013) of the nationally-representative Household, Income and Labour Dynamics in Australia (HILDA) survey were used in the analysis.

Results

Patients with PHI had a higher number of hospital nights’ stay despite having a lower number of hospital admissions than those without private cover. Significant disparities were identified in preventive and specialist care use between patients with cover and without cover. No significant variations were observed in healthcare utilisation for PHI patients before and after dropping PHI. One in four patients chose to use public hospitals despite holding PHI cover. Moreover, those insured and from lower socioeconomic backgrounds and those who were younger and without long-term health conditions showed a higher probability of selecting public rather than private care.

Conclusions

It is evident that PHI cover encourages people to use private care. However, a considerable number of PHI patients are using public care, even though eligible for private care may indicate consumer information asymmetry.

Infodemiology and Infoveillance: Scoping Review

BACKGROUND

Web-based sources are increasingly employed in the analysis, detection, and forecasting of diseases and epidemics, and in predicting human behavior toward several health topics. This use of the internet has come to be known as infodemiology, a concept introduced by Gunther Eysenbach. Infodemiology and infoveillance studies use web-based data and have become an integral part of health informatics research over the past decade.

OBJECTIVE

The aim of this paper is to provide a scoping review of the state-of-the-art in infodemiology along with the background and history of the concept, to identify sources and health categories and topics, to elaborate on the validity of the employed methods, and to discuss the gaps identified in current research.

METHODS

The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed to extract the publications that fall under the umbrella of infodemiology and infoveillance from the JMIR, PubMed, and Scopus databases. A total of 338 documents were extracted for assessment.

RESULTS

Of the 338 studies, the vast majority (n=282, 83.4%) were published with JMIR Publications. The Journal of Medical Internet Research features almost half of the publications (n=168, 49.7%), and JMIR Public Health and Surveillance has more than one-fifth of the examined studies (n=74, 21.9%). The interest in the subject has been increasing every year, with 2018 featuring more than one-fourth of the total publications (n=89, 26.3%), and the publications in 2017 and 2018 combined accounted for more than half (n=171, 50.6%) of the total number of publications in the last decade. The most popular source was Twitter with 45.0% (n=152), followed by Google with 24.6% (n=83), websites and platforms with 13.9% (n=47), blogs and forums with 10.1% (n=34), Facebook with 8.9% (n=30), and other search engines with 5.6% (n=19). As for the subjects examined, conditions and diseases with 17.2% (n=58) and epidemics and outbreaks with 15.7% (n=53) were the most popular categories identified in this review, followed by health care (n=39, 11.5%), drugs (n=40, 10.4%), and smoking and alcohol (n=29, 8.6%).

CONCLUSIONS

The field of infodemiology is becoming increasingly popular, employing innovative methods and approaches for health assessment. The use of web-based sources, which provide us with information that would not be accessible otherwise and tackles the issues arising from the time-consuming traditional methods, shows that infodemiology plays an important role in health informatics research.

Review of mobile applications for the detection and management of atrial fibrillation

BACKGROUND

Free mobile applications (apps) that use photoplethysmography (PPG) waveforms may extend atrial fibrillation (AF) detection to underserved populations, but they have not been rigorously evaluated.

OBJECTIVE

The purpose of this study was to systematically review and evaluate the quality, functionality, and adherence to self-management behaviors of existing mobile apps for AF.

METHODS

We systematically searched 3 app stores for apps that were free, available in English, and intended for use by patients to detect and manage AF. A minimum of 2 reviewers evaluated (1) app quality, using the Mobile Application Rating Scale (MARS); (2) functionality using published criteria; and (3) features that support 4 self-management behaviors (including PPG waveform monitoring) identified using evidence-based guidelines. Interrater reliability between the reviewers was calculated.

RESULTS

Of 12 included apps, 5 (42%) scored above average for quality (MARS score ≥3.0). App quality was highest for their ease of use, navigation, layout, and visual appeal (eg, functionality and aesthetics) and lowest for their behavioral change support and subjective impressions of quality. The most common app functionalities were capturing and graphically displaying user-entered data (n = 9 [75%]). Nearly all apps (n = 11 [92%]) supported PPG waveform monitoring, but only 2 (17%) supported all 4 self-management behaviors. Interrater reliability was high (0.75-0.83).

CONCLUSION

The reviewed apps had wide variability in quality, functionality, and adherence to self-management behaviors. Given the accessibility of these apps to underserved populations and the tremendous potential they hold for improving AF detection and management, high priority should be given to improving app quality and functionality.

Proposal for the User-Centered Design Approach for Health Apps Based on Successful Experiences: Integrative Review

Background

Different strategies encompassed within mHealth have shown themselves to be effective for maintaining good health or controlling certain diseases. However, there is usually a very high rate of abandonment of health apps. Therefore, it would seem obvious that there is a need for involving the end users (whether they are health professionals, patients, or both) in the design process from the early stages in order to enable their needs and characteristics to be identified. In this sense, it is common knowledge that focusing on the user permits the consideration of valuable details aimed at making the correct adjustment between the patient, the technology, and the organization of attention.

Objective

The goal of the research was to propose a methodology based on the review of previous successful user experiences in setting up health apps by using qualitative techniques (focus groups and discussion groups) that includes the participation of information technology and health professionals and the patients themselves.

Methods

An integrative review was made of studies in which a qualitative methodology was employed mainly through focus and/or discussion groups for the design and development of health apps, consulting diverse databases (PubMed, Scopus, and Proquest) with the following search strategy: “mHealth AND apps AND focus group OR discussion group.” A total of 69 papers were included in the review.

Results

A proposal structured in 4 sessions of variable duration was made in which information technology and health professionals and patients take part: composing, preparing, and organizing contents (session 1); testing structure and usability (session 2); does the app fit the needs of end users? (session 3); and last testing—keep on improving (session 4). Throughout the sessions, we propose studying aspects like previous user experiences in mHealth, barriers to the adoption of mHealth, interface contents, management and browsability, usability, perceived quality, security and privacy, capacity to self-manage disease with the app, ergonomics, and glanceability, etc. Specific tools that have proved useful in previous research for measuring these aspects are presented.

Conclusions

These work sessions would be based on predominantly qualitative methodologies although, as they evolve, validated questionnaires permitting the assessment of the objectivity of certain technical aspects could be incorporated. With this proposal, a project centered on end users could be effected, responding to their needs. However, this requires validation that will be made via implementation in the development of health apps, with the subsequent measurement of results in terms of adherence and improvement in the clinical variables of the end users.

Recent advances of biosensors for hypertension and nephrology

PURPOSE OF REVIEW

Hypertension (HTN) and chronic kidney disease (CKD) are significant problems. With recent advances in technologies, biosensors have shown a great potential to provide better home monitoring in hypertension (HTN), medication compliance, diagnostic device for kidney disease, CKD/end-stage renal disease (ESRD) care, and post kidney transplant management.

RECENT FINDINGS

Multiple devices/biosensors have been developed related to HTN, kidney function including real-time glomerular filtration rate, CKD/end-stage renal disease, and transplant care. In recent advances in wearable biosensors, point of care monitoring system could provide more integrated care to the patients via telenephrology.

SUMMARY

This review focuses on the recent advances in biosensors which may be useful for HTN and nephrology. We will discuss future potential clinical implication of these biosensors.

Enhancing the Robustness of Smartphone Photoplethysmography: A Signal Quality Index Approach

Heart rate variability (HRV) provides essential health information such as the risks of heart attacks and mental disorders. However, inconvenience related to the accurate detection of HRV limits its potential applications. The ubiquitous use of smartphones makes them an excellent choice for regular and portable health monitoring. Following this trend, smartphone photoplethysmography (PPG) has recently garnered prominence; however, the lack of robustness has prevented both researchers and practitioners from embracing this technology. This study aimed to bridge the gap in the literature by developing a novel smartphone PPG quality index (SPQI) that can filter corrupted data. A total of 226 participants joined the study, and results from 1343 samples were used to validate the proposed sinusoidal function-based model. In both the correlation coefficient and Bland–Altman analyses, the agreement between HRV measurements generated by both the smartphone PPG and the reference electrocardiogram improved when data were filtered through the SPQI. Our results support not only the proposed approach but also the general value of using smartphone PPG in HRV analysis.

Health workers' perceptions and experiences of using mHealth technologies to deliver primary healthcare services: a qualitative evidence synthesis

BACKGROUND

Mobile health (mHealth), refers to healthcare practices supported by mobile devices, such as mobile phones and tablets. Within primary care, health workers often use mobile devices to register clients, track their health, and make decisions about care, as well as to communicate with clients and other health workers. An understanding of how health workers relate to, and experience mHealth, can help in its implementation.

OBJECTIVES

To synthesise qualitative research evidence on health workers' perceptions and experiences of using mHealth technologies to deliver primary healthcare services, and to develop hypotheses about why some technologies are more effective than others.

SEARCH METHODS

We searched MEDLINE, Embase, CINAHL, Science Citation Index and Social Sciences Citation Index in January 2018. We searched Global Health in December 2015. We screened the reference lists of included studies and key references and searched seven sources for grey literature (16 February to 5 March 2018). We re-ran the search strategies in February 2020. We screened these records and any studies that we identified as potentially relevant are awaiting classification.

SELECTION CRITERIA

We included studies that used qualitative data collection and analysis methods. We included studies of mHealth programmes that were part of primary healthcare services. These services could be implemented in public or private primary healthcare facilities, community and workplace, or the homes of clients. We included all categories of health workers, as well as those persons who supported the delivery and management of the mHealth programmes. We excluded participants identified as technical staff who developed and maintained the mHealth technology, without otherwise being involved in the programme delivery. We included studies conducted in any country.

DATA COLLECTION AND ANALYSIS

We assessed abstracts, titles and full-text papers according to the inclusion criteria. We found 53 studies that met the inclusion criteria and sampled 43 of these for our analysis. For the 43 sampled studies, we extracted information, such as country, health worker category, and the mHealth technology. We used a thematic analysis process. We used GRADE-CERQual to assess our confidence in the findings.

MAIN RESULTS

Most of the 43 included sample studies were from low- or middle-income countries. In many of the studies, the mobile devices had decision support software loaded onto them, which showed the steps the health workers had to follow when they provided health care. Other uses included in-person and/or text message communication, and recording clients' health information. Almost half of the studies looked at health workers' use of mobile devices for mother, child, and newborn health. We have moderate or high confidence in the following findings. mHealth changed how health workers worked with each other: health workers appreciated being more connected to colleagues, and thought that this improved co-ordination and quality of care. However, some described problems when senior colleagues did not respond or responded in anger. Some preferred face-to-face connection with colleagues. Some believed that mHealth improved their reporting, while others compared it to "big brother watching". mHealth changed how health workers delivered care: health workers appreciated how mHealth let them take on new tasks, work flexibly, and reach clients in difficult-to-reach areas. They appreciated mHealth when it improved feedback, speed and workflow, but not when it was slow or time consuming. Some health workers found decision support software useful; others thought it threatened their clinical skills. Most health workers saw mHealth as better than paper, but some preferred paper. Some health workers saw mHealth as creating more work. mHealth led to new forms of engagement and relationships with clients and communities: health workers felt that communicating with clients by mobile phone improved care and their relationships with clients, but felt that some clients needed face-to-face contact. Health workers were aware of the importance of protecting confidential client information when using mobile devices. Some health workers did not mind being contacted by clients outside working hours, while others wanted boundaries. Health workers described how some community members trusted health workers that used mHealth while others were sceptical. Health workers pointed to problems when clients needed to own their own phones. Health workers' use and perceptions of mHealth could be influenced by factors tied to costs, the health worker, the technology, the health system and society, poor network access, and poor access to electricity: some health workers did not mind covering extra costs. Others complained that phone credit was not delivered on time. Health workers who were accustomed to using mobile phones were sometimes more positive towards mHealth. Others with less experience, were sometimes embarrassed about making mistakes in front of clients or worried about job security. Health workers wanted training, technical support, user-friendly devices, and systems that were integrated into existing electronic health systems. The main challenges health workers experienced were poor network connections, access to electricity, and the cost of recharging phones. Other problems included damaged phones. Factors outside the health system also influenced how health workers experienced mHealth, including language, gender, and poverty issues. Health workers felt that their commitment to clients helped them cope with these challenges.

AUTHORS' CONCLUSIONS

Our findings propose a nuanced view about mHealth programmes. The complexities of healthcare delivery and human interactions defy simplistic conclusions on how health workers will perceive and experience their use of mHealth. Perceptions reflect the interplay between the technology, contexts, and human attributes. Detailed descriptions of the programme, implementation processes and contexts, alongside effectiveness studies, will help to unravel this interplay to formulate hypotheses regarding the effectiveness of mHealth.

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.

Happiness at Your Fingertips: Assessing Mental Health with Smartphone Photoplethysmogram-Based Heart Rate Variability Analysis

Background: Heart rate variability (HRV) provides essential mental health information for clinical diagnosis, telemedicine, preventive medicine, and public health; however, the lack of a convenient detection method limits its potential. Objective: This study aims to investigate the feasibility and credibility of smartphone photoplethysmogram (PPG)-based HRV analysis for mental well-being and health assessment. Methods: Data were collected from 93 students and university employees in Shenzhen, China. Forty-six percent were male, and the average age was 23.71 years (σ = 4.33). An app recorded a 4-min video of their fingertips and converted the frames into five HRV measures, including the root mean square of successive differences (rMSSD), standard deviation of the normal-to-normal (NN) intervals (SDNN), percentage of successive NN intervals differing by ≥50 ms (pNN50), log high-frequency (HF) HRV, and log low-frequency (LF) HRV. Results: The data verify the positive relationship between mental well-being and HRV measures. Participants with higher Satisfaction With Life Scale (SWLS) scores have a higher rMSSD (p = 0.047), SDNN (p = 0.009), log HF (p = 0.02), and log LF (p = 0.003). Participants who suffer from depression have lower log HF (p = 0.048) and log LF (p = 0.02). Participants in the high-anxiety group have lower pNN50 (p = 0.04) and log HF (p = 0.03). Conclusions: The results of this study validate the feasibility of using the smartphone PPG by demonstrating similar results to previous findings. Our data also support the theorized positive link between mental health and HRV.

Technical Metrics Used to Evaluate Health Care Chatbots: Scoping Review (Preprint).. [DOI: 10.2196/preprints.18301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

BACKGROUND

Dialog agents (chatbots) have a long history of application in health care, where they have been used for tasks such as supporting patient self-management and providing counseling. Their use is expected to grow with increasing demands on health systems and improving artificial intelligence (AI) capability. Approaches to the evaluation of health care chatbots, however, appear to be diverse and haphazard, resulting in a potential barrier to the advancement of the field.

OBJECTIVE

This study aims to identify the technical (nonclinical) metrics used by previous studies to evaluate health care chatbots.

METHODS

Studies were identified by searching 7 bibliographic databases (eg, MEDLINE and PsycINFO) in addition to conducting backward and forward reference list checking of the included studies and relevant reviews. The studies were independently selected by two reviewers who then extracted data from the included studies. Extracted data were synthesized narratively by grouping the identified metrics into categories based on the aspect of chatbots that the metrics evaluated.

RESULTS

Of the 1498 citations retrieved, 65 studies were included in this review. Chatbots were evaluated using 27 technical metrics, which were related to chatbots as a whole (eg, usability, classifier performance, speed), response generation (eg, comprehensibility, realism, repetitiveness), response understanding (eg, chatbot understanding as assessed by users, word error rate, concept error rate), and esthetics (eg, appearance of the virtual agent, background color, and content).

CONCLUSIONS

The technical metrics of health chatbot studies were diverse, with survey designs and global usability metrics dominating. The lack of standardization and paucity of objective measures make it difficult to compare the performance of health chatbots and could inhibit advancement of the field. We suggest that researchers more frequently include metrics computed from conversation logs. In addition, we recommend the development of a framework of technical metrics with recommendations for specific circumstances for their inclusion in chatbot studies.

Heart failure disease management programs in Austria 2019 : A systematic survey of the Heart Failure Working Group and the Working Group for Cardiological Assistance and Care Personnel of the Austrian Society of Cardiology

Heart failure (HF) is common and is associated with high morbidity, mortality and high health expenditure. A multidisciplinary disease management plan (DMP) can reduce morbidity and mortality, save costs and improve the quality of life. In Austria, three HF-specific DMPs are currently in a project phase and four established DMPs are active. Although programs are widely heterogeneous with respect to their intervention type, they pursue the same interventional goal by supporting seamless care between inpatient and community care settings with a multidisciplinary team. This survey presents a systematic survey of the HF-specific DMPs in Austria. Disparities between programs are highlighted and discussed. The nationwide establishment of HF-specific DMPs that integrate primary care and cardiology services including a regulation of the remuneration of stakeholders and program infrastructure is needed to decrease the burden of HF for both the individual and society.

Outcomes of a Heart Failure Telemonitoring Program Implemented as the Standard of Care in an Outpatient Heart Function Clinic: Pretest-Posttest Pragmatic Study

Background

Telemonitoring (TM) can improve heart failure (HF) outcomes by facilitating patient self-care and clinical decisions. The Medly program enables patients to use a mobile phone to record daily HF readings and receive personalized self-care messages generated by a clinically validated algorithm. The TM system also generates alerts, which are immediately acted upon by the patients’ existing care team. This program has been operating for 3 years as part of the standard of care in an outpatient heart function clinic in Toronto, Canada.

Objective

This study aimed to evaluate the 6-month impact of this TM program on health service utilization, clinical outcomes, quality of life (QoL), and patient self-care.

Methods

This pragmatic quality improvement study employed a pretest-posttest design to compare 6-month outcome measures with those at program enrollment. The primary outcome was the number of HF-related hospitalizations. Secondary outcomes included all-cause hospitalizations, emergency department visits (HF related and all cause), length of stay (HF related and all cause), and visits to the outpatient clinic. Clinical outcomes included bloodwork (B-type natriuretic peptide [BNP], creatinine, and sodium), left ventricular ejection fraction, and predicted survival score using the Seattle Heart Failure Model. QoL was measured using the Minnesota Living with Heart Failure Questionnaire (MLHFQ) and the 5-level EuroQol 5-dimensional questionnaire. Self-care was measured using the Self-Care of Heart Failure Index (SCHFI). The difference in outcome scores was analyzed using negative binomial distribution and Poisson regressions for the health service utilization outcomes and linear regressions for all other outcomes to control for key demographic and clinical variables.

Results

Available data for 315 patients enrolled in the TM program between August 2016 and January 2019 were analyzed. A 50% decrease in HF-related hospitalizations (incidence rate ratio [IRR]=0.50; P<.001) and a 24% decrease in the number of all-cause hospitalizations (IRR=0.76; P=.02) were found when comparing the number of events 6 months after program enrollment with the number of events 6 months before enrollment. With regard to clinical outcomes at 6 months, a 59% decrease in BNP values was found after adjusting for control variables. Moreover, 6-month MLHFQ total scores were 9.8 points lower than baseline scores (P<.001), representing a clinically meaningful improvement in HF-related QoL. Similarly, the MLHFQ physical and emotional subscales showed a decrease of 5.4 points (P<.001) and 1.5 points (P=.04), respectively. Finally, patient self-care after 6 months improved as demonstrated by a 7.8-point (P<.001) and 8.5-point (P=.01) increase in the SCHFI maintenance and management scores, respectively. No significant changes were observed in the remaining secondary outcomes.

Conclusions

This study suggests that an HF TM program, which provides patients with self-care support and active monitoring by their existing care team, can reduce health service utilization and improve clinical, QoL, and patient self-care outcomes.

A Mobile Phone-Based Telemonitoring Program for Heart Failure Patients After an Incidence of Acute Decompensation (Medly-AID): Protocol for a Randomized Controlled Trial

BACKGROUND

Patients with heart failure (HF) are at the highest risk for hospital readmissions during the first few weeks after discharge when patients are transitioning from hospital to home. Telemonitoring (TM) for HF management has been found to reduce mortality risk and hospital readmissions if implemented appropriately; however, the impact of TM targeted for patients recently discharged from hospital, for whom TM might have the biggest benefit, is still unknown. Medly, a mobile phone-based TM system that is currently being used as a standard of care for HF at a large Canadian hospital, may be an effective tool for the management of HF in patients recently discharged from hospital.

OBJECTIVE

The objective of the Medly-After an Incidence of acute Decompensation (Medly-AID) trial is to determine the effect of Medly on the self-care and quality of life of patients with HF who have been recently discharged from hospital after an HF-related decompensation.

METHODS

A multisite multimethod randomized controlled trial (RCT) will be conducted at 2 academic hospitals and at least one community hospital to evaluate the impact of Medly-enabled HF management on the outcomes of patients with HF who had been hospitalized for HF-related decompensation and discharged during the 2 weeks before recruitment. The trial will include 144 participants with HF (74 in each control and intervention groups). Control patients will receive standard of care, whereas patients in the intervention group will receive standard of care and Medly. Specifically, patients in the intervention group will record daily weight, blood pressure, and heart rate and answer symptom-related questions via the Medly app. Medly will generate automated patient self-care messages such as to adjust diuretic medications, based on the rules-based algorithm personalized to the individual patient, and send real-time alerts to their health care providers as necessary. All patients will be followed for 3 months. Primary outcome measures are self-care and quality of life as measured through the validated questionnaires Self-Care of Heart Failure Index, EQ-5D-5L, and the Kansas City Cardiomyopathy Questionnaire-12. Secondary outcome measures for this study include cost of health care services used and health outcomes.

RESULTS

Patient recruitment began in November 2018 at the Sunnybrook Health Sciences Centre, with a total of 35 participants recruited by July 30, 2019 (17 in the intervention group and 18 in the control group). The final analysis is expected to occur in the fall of 2020.

CONCLUSIONS

This RCT will be the first to assess the effectiveness of the Medly TM system for use following discharge from hospital after a HF-related decompensation.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03358303; https://clinicaltrials.gov/ct2/show/NCT03358303.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/15753.

Prognostic value of point-of-care ultrasound during cardiac arrest: a systematic review

BACKGROUND

Despite significant improvements in cardiopulmonary resuscitation, sudden cardiac arrest is one of the leading causes of mortality in the United States. Ultrasound is a widely available tool that can be used to evaluate the presence of cardiac wall motion during cardiac arrest. Several clinical studies have evaluated the use of ultrasound to visualize cardiac motion as a predictor of mortality in cardiac arrest patients. However, there are limited data summarizing the prognostic value of point of care ultrasound evaluation during resuscitation. We performed a systematic literature review of the existing evidence examining the clinical utility of point-of-care ultrasound evaluation of cardiac wall motion as a predictor of cardiac resuscitation outcomes.

METHODS/RESULTS

We performed a systematic PubMed search of clinical studies up to July 23, 2019 evaluating point-of-care sonographic cardiac motion as a predictor of mortality following cardiac resuscitation. We included studies written in English that reviewed short-term outcomes and included adult populations. Fifteen clinical studies met inclusion criteria for assessing cardiac wall motion with point-of-care ultrasound and outcomes following cardiac resuscitation. Fourteen of the fifteen studies showed a statistically significant correlation between the presence of cardiac motion on ultrasound and short-term survival. This was most evident in patients with ventricular fibrillation or ventricular tachycardia as a presenting rhythm. Absence of cardiac motion non-survival. The data were pooled and the overall pooled odds ratio for return of spontaneous circulation in the presence of cardiac motion during CPR was 12.4 +/1 2.7 (p <  0.001).

CONCLUSION

Evaluation of cardiac motion on transthoracic echocardiogram is a valuable tool in the prediction of short-term cardiac resuscitation outcomes. Given the safety and availability of ultrasound in the emergency department, it is reasonable to apply point-of-care ultrasound to cardiopulmonary resuscitation as long as its use does not interrupt resuscitation.

Post-Arthroscopic Rotator Cuff Repair Rehabilitation Booklet: A Patient-Based Evaluation

BACKGROUND

Lack of physical therapists has led to increment of self-managed rehabilitations in post-arthroscopic rotator cuff repair (ARCR) in the forms of booklets or leaflets.

PURPOSE

The aim of study is to investigate 1) the acceptance of post-ARCR patients towards an education booklet, and 2) whether it could be a timesaving and laborsaving tool to physical therapists.

METHODS

An education booklet was established through a systematic review. Patients who underwent ARCR in our hospital were included and randomly assigned to the intervention or control group (27 women, 21 men, mean age=57.06 years old). Patients in the intervention group received educational booklets, and an evaluation was also obtained after they finished reading. Patients' understanding of the booklet was determined by asking patients to re-enact training presented in the booklet. Then, a therapist blinded to allocations would personally demonstrate training to patients until patients fully understood the protocol. For the control group, the same therapist coached patients until the whole protocol was clearly understood. The coaching time for patients in both groups was recorded.

RESULTS

Out of 48 patients, 24 (50%) were randomly assigned to the intervention group, and 21 (87.50%) completed their questionnaire. Out of these 21 patients, 20 (95.24%) rated the booklet as "excellent and easy to read", and 17 (80.95%) felt that the booklet was helpful. The re-enaction accuracy was for strengthening training and specific training (71.43% and 61.90%, respectively). As compared to the control group, the time of coaching for the patients to fully master the protocol in the intervention group was significantly less (P<0.01).

CONCLUSION

Patients highly applauded this booklet, and they cherished the information and support it contained. Nevertheless, the re-enaction accuracy was not high, suggesting that the high level of acceptance does not guarantee full understanding of information sent to patients.

Strategies for the Successful Implementation of a Novel iPhone Loaner System (iShare) in mHealth Interventions: Prospective Study

Background

As smartphone ownership continues to rise, health care systems and technology companies are driven to develop mobile health (mHealth) interventions as both diagnostic and therapeutic tools. An important consideration during mHealth intervention development is how to achieve health equity despite demographic differences in smartphone ownership. One solution is through the recirculation of loaner smartphones; however, best practices for implementing such programs to optimize security, privacy, scalability, and convenience for participants are not well defined.

Objective

In this tutorial, we describe how we implemented our novel Corrie iShare program, a 30-day loaner iPhone and smartwatch recirculation program, as part of a multi-center mHealth intervention to improve recovery and access to guideline-directed therapy following acute myocardial infarction.

Methods

We conducted a prospective study utilizing a smartphone app and leveraged iOS enterprise features as well as cellular data service to automate recirculation.

Results

Our configuration protocol was shortened from 1 hour to 10 minutes. Of 200 participants, 92 (46.0%) did not own an iPhone and would have been excluded from the study without iShare. Among iShare participants, 72% (66/92) returned their loaned smartphones.

Conclusions

The Corrie iShare program demonstrates the potential for a sustainable and scalable mHealth loaner program, enabling broader population reach while optimizing user experience. Implementation may face institutional constraints and software limitations. Consideration should be given to optimizing loaner returns.

Characteristics Associated With Facebook Use and Interest in Digital Disease Support Among Older Adults With Atrial Fibrillation: Cross-Sectional Analysis of Baseline Data From the Systematic Assessment of Geriatric Elements in Atrial Fibrillation (SAGE-AF) Cohort

BACKGROUND

Online support groups for atrial fibrillation (AF) and apps to detect and manage AF exist, but the scientific literature does not describe which patients are interested in digital disease support.

OBJECTIVE

The objective of this study was to describe characteristics associated with Facebook use and interest in digital disease support among older patients with AF who used the internet.

METHODS

We used baseline data from the Systematic Assessment of Geriatric Elements in Atrial Fibrillation (SAGE-AF), a prospective cohort of older adults (≥65 years) with AF at high stroke risk. Participants self-reported demographics, clinical characteristics, and Facebook and technology use. Online patients (internet use in the past 4 weeks) were asked whether they would be interested in participating in an online support AF community. Mobile users (owns smartphone and/or tablet) were asked about interest in communicating with their health care team about their AF-related health using a secure app. Logistic regression models identified crude and multivariable predictors of Facebook use and interest in digital disease support.

RESULTS

Online patients (N=816) were aged 74.2 (SD 6.6) years, 47.8% (390/816) were female, and 91.1% (743/816) were non-Hispanic white. Roughly half (52.5%; 428/816) used Facebook. Facebook use was more common among women (adjusted odds ratio [aOR] 2.21, 95% CI 1.66-2.95) and patients with mild to severe depressive symptoms (aOR 1.50, 95% CI 1.08-2.10) and less common among patients aged ≥85 years (aOR 0.27, 95% CI 0.15-0.48). Forty percent (40.4%; 330/816) reported interest in an online AF patient community. Interest in an online AF patient community was more common among online patients with some college/trade school or Bachelors/graduate school (aOR 1.70, 95% CI 1.10-2.61 and aOR 1.82, 95% CI 1.13-2.92, respectively), obesity (aOR 1.65, 95% CI 1.08-2.52), online health information seeking at most weekly or multiple times per week (aOR 1.84, 95% CI 1.32-2.56 and aOR 2.78, 95% CI 1.86-4.16, respectively), and daily Facebook use (aOR 1.76, 95% CI 1.26-2.46). Among mobile users, 51.8% (324/626) reported interest in communicating with their health care team via a mobile app. Interest in app-mediated communication was less likely among women (aOR 0.48, 95% CI 0.34-0.68) and more common among online patients who had completed trade school/some college versus high school/General Educational Development (aOR 1.95, 95% CI 1.17-3.22), sought online health information at most weekly or multiple times per week (aOR 1.86, 95% CI 1.27-2.74 and aOR 2.24, 95% CI 1.39-3.62, respectively), and had health-related apps (aOR 3.92, 95% CI 2.62-5.86).

CONCLUSIONS

Among older adults with AF who use the internet, technology use and demographics are associated with interest in digital disease support. Clinics and health care providers may wish to encourage patients to join an existing online support community for AF and explore opportunities for app-mediated patient-provider communication.