Patient-Facing Mobile Apps to Treat High-Need, High-Cost Populations: A Scoping Review

Usability of the BigO system in pediatric obesity treatment: A mixed-methods evaluation of clinical end-users

Objective

To assess technical usability of the BigO app and clinical portal among diverse participants and explore the overall user experiences of both.

Methods

Methods included technical usability testing by measuring the relative user efficiency score (RUS) for the app and measuring Relative User Efficiency (RUE) using the 'think aloud' method with the clinical portal. Qualitative approaches involved focus groups with adolescent app users and semi-structured one-to-one interviews with clinician participants. Thematic analysis was applied to analyze qualitative data.

Participants

Clinical participants consisted of adolescents seeking treatment for severe obesity and were invited via telephone/face to face to attend technical usability testing and a focus group. Healthcare professionals (HCPs) and researchers using the BigO clinical portal interface were invited to participate in usability testing and semi-structured interviews.

Results

From 14 families invited to attend, seven consented to join the study and four adolescents (mean age=13.8 (SD 0.8) years) participated. Additionally, six HCPs and one pediatric obesity researcher took part. RUS for adolescents indicated that the tasks required of them via myBigO app were feasible, and technically efficient. No user-related errors were observed during tasks. Technical barriers reported by adolescents included notifications of battery optimization, misunderstanding image annotation language, and compatibility challenges with certain phone models. RUS for the HCPs and researcher indicated that basic technical skills are a potential barrier for clinical portal use and qualitative findings revealed that clinical users wanted a logging option for monitoring goals and providing feedback on the portal.

Conclusion

Our study provided valuable formative findings from clinical end-users in Ireland indicating that adolescents being treated for obesity rated myBigO app as usable, acceptable and that it may assist other key stakeholders to understand food marketing and to monitor dietary and physical activity behaviors. Several key suggestions for future iterations of the clinical portal were provided to enhance its value in pediatric obesity treatment.

A blockchain-based healthcare data marketplace: prototype and demonstration

Objectives

This study aimed to develop healthcare data marketplace using blockchain-based B2C model that ensures the transaction of healthcare data among individuals, companies, and marketplaces.

Materials and methods

We designed an architecture for the healthcare data marketplace using blockchain. A healthcare data marketplace was developed using Panacea, MySQL 8.0, JavaScript library, and Node.js. We evaluated the performance of the data marketplace system in 3 scenarios.

Results

We developed mobile and web applications for healthcare data marketplace. The transaction data queries were executed fully within about 1-2 s, and approximately 9.5 healthcare data queries were processed per minute in each demonstration scenario.

Discussion

Blockchain-based healthcare data marketplaces have shown compliance performance in the process of data collection and will provide a meaningful role in analyzing healthcare data.

Conclusion

The healthcare data marketplace developed in this project can iron out time and place limitations and create a framework for gathering and analyzing fragmented healthcare data.

Outcome After Self-Triage App Referral in Urgent Direct-to-Consumer Telemedicine Encounter

Background: The quantification of self-triage effectiveness, guided by mobile applications, in urgent direct-to-consumer telemedicine (TM) encounters requires further investigation. The objective of this study was to evaluate the outcomes of referral guidance provided by a symptom-based self-management mobile application decision algorithm in the context of remote urgent care assessments. Methods: An observational retrospective single-center study was conducted from May 2022 to December 2023. The inclusion criteria encompassed individuals aged >18 years old, and those spontaneously seeking virtual emergency care through the EINSTEIN CONECTA application. Patients experiencing connectivity issues, preventing completion of the encounter, were excluded. The primary outcomes included the rate of patient concurrence with the algorithm's recommendation for seeking in-person emergency care and the referral rate to face-to-face assessment among cases evaluated through TM. The application's algorithm employs scientific evidence based on symptoms to recommend referrals to emergency departments (EDs). Results: Out of 88,834 patients connected to the TM Center, self-triage obviated the need for virtual physician assessment in 53,302 (60%) encounters. A total of 35,532 patients were remotely evaluated by 316 on-duty physicians, resulting in 1,125 ICD-coded diagnoses. Among these, 21,722 (61.1%) were initially advised by self-triage to visit the ED, with subsequent medical assessment leading to in-person referrals in 6,354 (29.3%) of the evaluations. Of the 13,810 patients recommended to continue with virtual care post-self-triage, 157 (1.1%) were referred for in-person assessment. Conclusions: Self-triage effectively reduced the need for physician encounters in approximately three-fifths of TM consultations. Despite being based on scientific evidence, symptom-based referral algorithms demonstrated high sensitivity but poor correlation with physician decision-making.

Quality of Care in Hospitals and the Use of Mobile-Based Personal Health Record Applications: An Exploratory Study Using National Hospital Evaluation Data

The use of mobile-based personal health record (m-PHR) applications at the hospital level has been minimally studied. This study aimed to investigate the relationship between m-PHR use and quality of care. A cross-sectional study design was employed, analyzing data from 99 hospitals. Two data sources were utilized: a previous m-PHR investigation conducted from 26 May to 30 June 2022 and a hospital evaluation dataset on quality of care. The use of m-PHR applications was measured by the number of m-PHR application downloads. Three independent variables were assessed: quality of care in the use of antibiotic drugs, injection drugs, and polypharmacy with ≥6 drugs. A generalized linear model was used for the analysis. The hospitals providing high-quality care, as evaluated based on the rate of antibiotic prescription (relative risk [RR], 3.328; 95% confidence interval [CI], 1.840 to 6.020; p < 0.001) and polypharmacy (RR, 2.092; 95% CI, 1.027 to 4.261; p = 0.042), showed an increased number of m-PHR downloads. Among the hospital covariates, public foundation status and being part of multi-hospital systems were associated with the number of m-PHR downloads (p < 0.05). This exploratory study found a positive relationship between quality of care and m-PHR use. Hospitals providing high-quality care may also excel in various activities, including m-PHR application use.

Caring for high-need patients

OBJECTIVE

We aimed to explore the construct of "high need" and identify common need domains among high-need patients, their care professionals, and healthcare organizations; and to describe the interventions that health care systems use to address these needs, including exploring the potential unintended consequences of interventions.

METHODS

We conducted a modified Delphi panel informed by an environmental scan. Expert stakeholders included patients, interdisciplinary healthcare practitioners (physicians, social workers, peer navigators), implementation scientists, and policy makers. The environmental scan used a rapid literature review and semi-structured interviews with key informants who provide healthcare for high-need patients. We convened a day-long virtual panel meeting, preceded and followed by online surveys to establish consensus.

RESULTS

The environmental scan identified 46 systematic reviews on high-need patients, 19 empirical studies documenting needs, 14 intervention taxonomies, and 9 studies providing construct validity for the concept "high need." Panelists explored the construct and terminology and established that individual patients' needs are unique, but areas of commonality exist across all high-need patients. Panelists agreed on 11 domains describing patient (e.g., social circumstances), 5 care professional (e.g., communication), and 8 organizational (e.g., staffing arrangements) needs. Panelists developed a taxonomy of interventions with 15 categories (e.g., care navigation, care coordination, identification and monitoring) directed at patients, care professionals, or the organization. The project identified potentially unintended consequences of interventions for high-need patients, including high costs incurred for patients, increased time and effort for care professionals, and identification of needs without resources to respond appropriately.

CONCLUSIONS

Care for high-need patients requires a thoughtful approach; differentiating need domains provides multiple entry points for interventions directed at patients, care professionals, and organizations. Implementation efforts should consider outlined intended and unintended downstream effects on patients, care professionals, and organizations.

A nurse-led mHealth intervention to alleviate depressive symptoms in older adults living alone in the community: A quasi-experimental study

BACKGROUND

The prevalence of geriatric depression has increased worldwide, becoming a major contributor to the burden of health care costs. Geriatric depression is difficult to detect in daily life because of its atypical presentation for each person. Therefore, there is an emerging need to develop personalised mHealth interventions for older adults with depression based on data from an ecological momentary assessment.

OBJECTIVE

To develop and evaluate the effect of a nurse-led mHealth intervention of geriatric depression in older adults living alone.

DESIGN

A quasi-experimental research design was used, and the study followed the transparent reporting of evaluations with a nonrandomised design statement.

SETTING

The nurse-led mHealth intervention was developed and evaluated in a community senior centre in Seoul, Korea.

PARTICIPANTS

Sixty-four older adults living alone with depressive symptoms were recruited between 1 October 2018 and 1 October 2019.

METHODS

Study participants were randomly assigned to the intervention or control groups by drawing lots. In the intervention group, nurses repeatedly assessed older adults' depressive symptoms using an ecological momentary assessment via a mobile tablet. The intervention consisted of weekly sessions, which included (1) standardised mHealth device training, (2) a nurse-led mHealth programme, and (3) art activities. The control group received care as usual. Intra- and inter-group differences were evaluated using paired t-tests and analysis of covariance was used to assess subjective depression symptoms. A linear mixed-model was used to analyse the relationship between groups and momentary scores over time.

RESULTS

The average age of the final sample was 76.2 years (SD = 6.06), 63.6 % (28/44) of whom were female. Compared with the control group (n = 23), the intervention group (n = 21) showed a decreased depression score (t = 4.041, p = .027). There was no statistical difference between the intervention and control groups based on traditional scales and the ecological momentary assessment. However, our data from the ecological momentary assessment captures clear fluctuating patterns across the days during the study, which traditional scales could not measure.

CONCLUSIONS

Most of the older adults successfully participated in a nurse-led mHealth intervention that included multiple components of a non-pharmacological approach to address depression. Mental health nurses should perform critical roles to personalise mHealth activities considering the older adult's autonomy and supportive decision-making, specifically when using high-technological intervention. Future research should maximise the methodological and clinical advantage of an ecological momentary assessment of geriatric depression.

REGISTRATION

Clinical Research Information Service number KCT0005073.

Evaluation of a Web-Based Simulation Tool for Self-Management Support in Type 1 Diabetes: A Pilot Study

OBJECTIVE

To develop and evaluate a novel Web-based Simulation Tool (WST) that brings simulation technologies to people with Type 1 Diabetes (T1D), enabling unique patient-data interactions seamlessly on a daily basis.

METHODS

A pilot clinical trial was conducted to assess system usability. The study consisted of one week of observation (Phase 1) and four weeks of interaction with WST (Phase 2). Responses to Technology Acceptance (TA) and Diabetes Distress Scale (DDS) questionnaires were collected, and follow-up interviews were conducted after Phase 2.

RESULTS

Fifteen participants with T1D using Control-IQ technology (age: 36 ± 13 years, HbA1c: 6.5% ± 0.7%) completed all study procedures. Generated simulation models achieved a median Mean Absolute Relative Difference (MARD) of 6.8% [interquartile range, IQR: 5.1%, 9.1%]. A decrease in expected benefits (likely explained by issues with the third-party data collection system) and an increase in expected burdens were observed. On a 1-5 scale, ease of use, trust, and usefulness scores were 3 [3,4], 4 [3,4], and 4 [3,4], respectively. Time below 70 mg/dL decreased between Phases 1 and 2 (1.6% [0.7%,3.7%] vs 0.8% [0.5%,3.0%]). A reduction in mean emotional burden was also observed (2.5 ± 1.1 vs 2.1 ± 0.8).

CONCLUSIONS

Results indicate that there was a learning curve to WST, but also that most participants trusted the system and found it useful in their diabetes care.

SIGNIFICANCE

Simulation technologies like WST could be used by educators and patients to facilitate diabetes self-management, leading to better diabetes literacy and reducing associated distress.

An overview of and recommendations for more accessible digital mental health services

Mental health concerns are common, and various evidence-based interventions for mental health conditions have been developed. However, many people have difficulty accessing appropriate mental health care and this has been exacerbated by the COVID-19 pandemic. Digital mental health services, such as those delivered by mobile phone or web-based platforms, offer the possibility of expanding the reach and accessibility of mental health care. To achieve this goal, digital mental health interventions and plans for their implementation must be designed with the end users in mind. In this Review, we describe the evidence base for digital mental health interventions across various diagnoses and treatment targets. Then, we explain the different formats for digital mental health intervention delivery, and offer considerations for their use across key age groups. We discuss the role that the COVID-19 pandemic has played in emphasizing the value of these interventions, and offer considerations for ensuring equity in access to digital mental health interventions among diverse populations. As healthcare providers continue to embrace the role that technology can play in broadening access to care, the design and implementation of digital mental healthcare solutions must be carefully considered to maximize their effectiveness and accessibility.

Use of technology for self-care in surgical wound infection surveillance: integrative review

ABSTRACT Objectives: to synthesize knowledge about technology for self-care in surgical wound infection surveillance. Methods: integrative review conducted in CINAHL, Embase, LILACS, PubMed, Scopus and Web of Science databases with the descriptors “surgical wound infection” and “self-care”, in addition to manual search in the references of the included studies. The selection and evaluation of the methodological quality of the studies and data collection were performed by two independent reviewers; conflicts were resolved by a third reviewer. Results: nine primary studies were included, published between 2011 and 2019. Six are cross-sectional, two are randomized clinical trials, and one is a case report. Mobile, text messaging, and imaging applications, computer software, assessments, and data storage capacity stand out. Conclusions: the technologies identified for self-care in surgical wound infection surveillance were the creation and use of mHealth and the use of health apps on mobile devices. Effective technologies in surveillance of surgical wound infection that enable rapprochement with the healthcare team, encourage a greater number of surgical wound assessments, enhance self-care actions, and decrease patient anxiety. Technology is also a monitored and recorded form of patient care, one of the main axes of infection surveillance.

Effects of Patient-Generated Health Data: Comparison of Two Versions of Long-Term Mobile Personal Health Record Usage Logs

Patient-generated health data (PGHD) can be managed easily by a mobile personal health record (mPHR) and can increase patient engagement. This study investigated the effect of PGHD functions on mPHR usage. We collected usage log data from an mPHR app, My Chart in My Hand (MCMH), for seven years. We analyzed the number of accesses and trends for each menu by age and sex according to the version-up. Generalized estimating equation (GEE) analysis was used to determine the likelihood of continuous app usage according to the menus and version-up. The total number of users of each version were 15,357 and 51,553, respectively. Adult females under 50 years were the most prevalent user group (30.0%). The “My Chart” menu was the most accessed menu, and the total access count increased by ~10 times after the version-up. The “Health Management” menu designed for PGHD showed the largest degree of increase in its likelihood of continuous usage after the version-up (1.245; p < 0.0001) across menus (range: 0.925–1.050). Notably, improvement of PGHD management in adult females over 50 years is needed.

Co-designing an Adaption of a Mobile App to Enhance Communication, Safety, and Well-being Among People Living at Home With Early-Stage Dementia: Protocol for an Exploratory Multiple Case Study

Background

There is a growing interest in using mobile apps to support communication, safety, and well-being. Evidence directly from people with dementia regarding the usability, usefulness, and relevance of mobile apps is limited.

Objective

This paper describes the protocol of a study that will evaluate an app designed for supporting communication, safety, and well-being among people living with dementia. The study aims to understand if the app can enhance safety through improved communication among users.

Methods

The study will use participatory qualitative methods over 3 cycles of evaluation with co-designers (service users, their families, and care practitioners). The study will be developed in partnership with a specialist home care service in England. Purposive case selection will be performed to ensure that the cases exemplify differences in experiences. The app will be evaluated in a walk-through workshop by people living with early-stage dementia and then trialed at home by up to 12 families in a try-out cycle. An amended version will be evaluated in a final walk-through workshop during cycle 3. Data will be collected from at least 4 data sources during the try-out phase and analyzed thematically. An explanatory multiple case study design will be used to synthesize and present the evidence from the three cycles, drawing on the Normalization Process Theory to support the interpretation of the findings.

Results

The study is ready to be implemented, but it was paused to protect vulnerable individuals during the COVID-19 pandemic in 2020. The findings will be particularly relevant for understanding how to support vulnerable people living in the community during social distancing and the period following the pandemic as well as for providing insight into the challenges of social isolation that arise from living with dementia.

Conclusions

Evaluating a mobile app for enhancing communication, safety, and well-being among people living with dementia contributes to the key ambitions enshrined in policy and practice—championing the use of digital technology and supporting people with dementia to live safely in their own homes. The study will involve co-designers living with dementia, so that the voices of service users can be used to highlight the benefits and challenges of assistive technology and shape the future development of apps that enhance safety by improving communication.

International Registered Report Identifier (IRRID)

PRR1-10.2196/19543

Feasibility of a Mobile Health App for Routine Outcome Monitoring and Feedback in SMART Recovery Mutual Support Groups: Stage 1 Mixed Methods Pilot Study

Background

Mutual support groups are an important source of long-term help for people impacted by addictive behaviors. Routine outcome monitoring (ROM) and feedback are yet to be implemented in these settings. SMART Recovery mutual support groups focus on self-empowerment and use evidence-based techniques (eg, motivational and behavioral strategies). Trained facilitators lead all SMART Recovery groups, providing an opportunity to implement ROM.

Objective

The aim of this stage 1 pilot study is to explore the feasibility, acceptability, and preliminary outcomes of a novel, purpose-built mobile health ROM and feedback app (SMART Track) in mutual support groups coordinated by SMART Recovery Australia (SRAU) over 8 weeks.

Methods

SMART Track was developed during phase 1 of this study using participatory design methods and an iterative development process. During phase 2, 72 SRAU group participants were recruited to a nonrandomized, prospective, single-arm trial of the SMART Track app. Four modes of data collection were used: ROM data directly entered by participants into the app; app data analytics captured by Amplitude Analytics (number of visits, number of unique users, visit duration, time of visit, and user retention); baseline, 2-, and 8-week follow-up assessments conducted through telephone; and qualitative telephone interviews with a convenience sample of study participants (20/72, 28%) and facilitators (n=8).

Results

Of the 72 study participants, 68 (94%) created a SMART Track account, 64 (88%) used SMART Track at least once, and 42 (58%) used the app for more than 5 weeks. During week 1, 83% (60/72) of participants entered ROM data for one or more outcomes, decreasing to 31% (22/72) by the end of 8 weeks. The two main screens designed to provide personal feedback data (Urges screen and Overall Progress screen) were the most frequently visited sections of the app. Qualitative feedback from participants and facilitators supported the acceptability of SMART Track and the need for improved integration into the SRAU groups. Participants reported significant reductions between the baseline and 8- week scores on the Severity of Dependence Scale (mean difference 1.93, SD 3.02; 95% CI 1.12-2.73) and the Kessler Psychological Distress Scale-10 (mean difference 3.96, SD 8.31; 95% CI 1.75-6.17), but no change on the Substance Use Recovery Evaluator (mean difference 0.11, SD 7.97; 95% CI –2.02 to 2.24) was reported.

Conclusions

Findings support the feasibility, acceptability, and utility of SMART Track. Given that sustained engagement with mobile health apps is notoriously difficult to achieve, our findings are promising. SMART Track offers a potential solution for ROM and personal feedback, particularly for people with substance use disorders who attend mutual support groups.

Trial Registration

Australian New Zealand Clinical Trials Registry ACTRN12619000686101; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377336

International Registered Report Identifier (IRRID)

RR2-10.2196/15113

Landscape Analysis of Oncology Mobile Health Applications

PURPOSE

More than 325,000 mobile health (mhealth) applications (apps) have been developed. We sought to describe the state of oncology-specific apps and to highlight areas of strength and opportunities for future development.

METHODS

We searched for oncology apps in the Apple iOS and Google Play app stores in January 2020. Apps were classified by English language support, date of last update, downloads, intended audience, intended purpose, and developer type.

RESULTS

We identified 794 oncology-specific, English language applications; only 257 (32%) met basic recency standards and were considered evaluable. Of evaluable apps, almost half (47%) were found in the Medical Store Category and the majority were free (88%). The most common intended audience was health care professionals (45%), with 28% being geared toward the general public and 27% being intended for patients. The intended function was education for 36%, clinical decision support for 19.5%, and patient support for 18%. Only 23% of education apps and 40% of clinical decision support apps reported any formal app content review process. Web developers created 61.5% of apps, scientific societies created 10%, and hospitals or health care organizations created just 6%. Of 54 studies that used mobile apps in oncology identified by a recent meta-analysis, only two could be matched to commercially available apps from our study, suggesting a substantial divide between investigation and product dissemination.

CONCLUSION

Relatively few oncology-related apps exist in the commercial marketplace, up-to-date apps are uncommon, and there is a notable absence of key oncology stakeholders in app development. Meaningful development opportunities exist.

The Doctor Will "Friend" You Now: A Qualitative Study on Adolescents' Preferences for Weight Management App Features

OBJECTIVES

Primary care providers report a lack of resources as a barrier to managing adolescent obesity. Mobile health applications (apps) may be helpful in weight management; however, adolescents' preferences for weight management app features are unknown. Our objectives were to provide insight into adolescents' preferred weight management app features and elicit facilitators and barriers to app use.

METHODS

Using the qualitative content analysis method, 14 interviews with adolescents with overweight/obesity were conducted in rural and urban pediatric offices in South Carolina. Eligibility criteria included being 13 to 17 years old, having a body mass index at or above the 85th percentile for age and sex, and having access to a smartphone or tablet. Semistructured key informant interviews were conducted from May to October 2017. Participants were presented with three popular mobile health apps and asked to complete tasks and comment on their various features and usability. Summative content analysis coding was performed on interview transcripts, and interviews were conducted until thematic saturation was reached.

RESULTS

Seventy-one percent of participants were from a rural practice, 64% were White, and 86% had a body mass index higher than the 95th percentile. Familiarity with similar apps and accessibility of apps on their smartphones promoted app use. The need for wireless Internet, operating difficulties, or privacy concerns were barriers. Nutritional education, physical activity tracking, and social connection were desirable app features.

CONCLUSIONS

Adolescents have expressed preferred app features to help them manage weight; however, further work is needed to see whether these features are effective.

A Mobile App for Self-Triage for Pediatric Emergency Patients in Japan: 4 Year Descriptive Epidemiological Study

BACKGROUND

When children suffer sudden illness or injury, many parents wonder whether they should go to the hospital immediately or call an ambulance. In 2015, we developed a mobile app that allows parents or guardians to determine the urgency of their child's condition or call an ambulance and that indicates available hospitals and clinics when their child is suddenly sick or injured by simple selection of the child's chief complaints and symptoms. However, the effectiveness of medical apps used by the general public has not been well evaluated.

OBJECTIVE

The purpose of this study was to clarify the use profile of this mobile app based on data usage in the app.

METHODS

This study was a descriptive epidemiological study with a 4-year study period running from January 2016 to December 2019. We included cases in which the app was used either by the children themselves or by their parents and other guardians. Cases in which the app was downloaded but never actually used were excluded from this study. Continuous variables are presented as median and IQR, and categorical variables are presented as actual number and percentages.

RESULTS

The app was used during the study period for 59,375 children whose median age was 1 year (IQR 0-3 years). The app was used for 33,874 (57.05%) infants, 16,228 (27.33%) toddlers, 8102 (13.65%) elementary school students, and 1117 (1.88%) junior high school students, with 54 (0.09%) having an unknown status. Furthermore, 31,519 (53.08%) were male and 27,329 (46.03%) were female, with sex being unknown for 527 (0.89%) children. "Sickness" was chosen for 49,101 (78.51%) patients, and "injury, poisoning, foreign, substances and others" was chosen for 13,441 (21.49%). For "sickness," "fever" was the most commonly selected option (22,773, 36.41%), followed by "cough" (4054, 6.48%), and "nausea/vomiting" (3528, 5.64%), whereas for "injury, poisoning, foreign substances and others," "head and neck injury" was the most commonly selected option (3887, 6.22%), followed by "face and extremities injury" (1493, 2.39%) and "injury and foreign substances in eyes" (1255, 2.01%).

CONCLUSIONS

This study clarified the profile of use of a self-triage app for pediatric emergency patients in Japan.

Developing a mHealth Routine Outcome Monitoring and Feedback App ("SMART Track") to Support Self-Management of Addictive Behaviours

Background: Routine outcome monitoring (ROM) has been implemented across a range of addiction treatment services, settings and organisations. Mutual support groups are a notable exception. Innovative solutions are needed. SMART Track is a purpose built smartphone app designed to capture ROM data and provide tailored feedback to adults attending Australian SMART Recovery groups for addictive behaviour(s). Objective: Details regarding the formative stage of app development is essential, but often neglected. Improved consideration of the end-user is vital for curtailing app attrition and enhancing engagement. This paper provides a pragmatic example of how principles embedded in published frameworks can be operationalised to address these priorities during the design and development of the SMART Track app. Methods: Three published frameworks for creating digital health technologies ("Person-Based Approach," "BIT" Model and IDEAS framework) were integrated and applied across two stages of research to inform the development, design and content of SMART Track. These frameworks were chosen to ensure that SMART Track was informed by the needs and preferences of the end-user ("Person-Based"); best practise recommendations for mHealth development ("BIT" Model) and a collaborative, iterative development process between the multi-disciplinary research team, app developers and end-users (IDEAS framework). Results: Stage one of the research process generated in-depth knowledge to inform app development, including a comprehensive set of aims (clinical, research/organisation, and usage); clear articulation of the target behaviour (self-monitoring of recovery related behaviours and experiences); relevant theory (self-determination and social control); appropriate behavioural strategies (e.g., behaviour change taxonomy and process motivators) and key factors that may influence engagement (e.g., transparency, relevance and trust). These findings were synthesised into guiding principles that were applied during stage two in an iterative approach to app design, content and development. Conclusions: This paper contributes new knowledge on important person-centred and theoretical considerations that underpin a novel ROM and feedback app for people with addictive behaviour(s). Although person-centred design and best-practise recommendations were employed, further research is needed to determine whether this leads to improved usage outcomes. Clinical Trial Registration: Pilot Trial: http://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377336.

Person-Generated Health Data in Women's Health: Protocol for a Scoping Review

Background

Due to their ability to collect person-generated health data, digital tools and connected health devices may hold great utility in disease prevention, chronic disease self-monitoring and self-tracking, as well as in tailoring information and educational content to fit individual needs. Facilitators and barriers to the use of digital health technologies vary across demographics, including sex. The “femtech” market is growing rapidly, and women are some of the largest adopters of digital health technologies.

Objective

This paper aims to provide the background and methods for conducting a scoping review on the use of person-generated health data from connected devices in women’s health. The objectives of the scoping review are to identify the various contexts of digital technologies in women’s health and to consolidate women’s views on the usability and acceptability of the devices.

Methods

Searches were conducted in the following databases: Medline, Embase, APA PsycInfo, CINAHL Complete, and Web of Science Core Collection. We included articles from January 2015 to February 2020. Screening of articles was done independently by at least two authors in two stages. Data charting is being conducted in duplicate. Results will be reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) checklist.

Results

Our search identified 9102 articles after deduplication. As of November 2020, the full-text screening stage is almost complete and data charting is in progress. The scoping review is expected to be completed by Fall 2021.

Conclusions

This scoping review will broadly map the literature regarding the contexts and acceptability of digital health tools for women. The results from this review will be useful in guiding future digital health and women’s health research.

International Registered Report Identifier (IRRID)

DERR1-10.2196/26110

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.

Actionable health app evaluation: translating expert frameworks into objective metrics

As use and availability of mobile health apps have increased, so too has the need for a thorough, accessible framework for app evaluation. The American Psychiatric Association's app evaluation model has emerged as a way to critically assess an app by considering accessibility, privacy and security, clinical foundation, engagement, and interoperability; however, there is no centralized database where users can view how various health apps perform when assessed via the APA model. In this perspective, we propose and outline our effort to translate the APA's model for the evaluation of health apps into a set of objective metrics that can be published online, making the framework actionable and accessible to a broad audience. The questions from the APA model were operationalized into 105 objective questions that are either binary or numeric. These questions serve as the foundation of an online database, where app evaluation consists of answering these 105 questions and can be crowdsourced. While the database has yet to be published and crowdsourced, initial internal testing demonstrated excellent interrater reliability. The database proposed here introduces a public and interactive approach to data collection that is guided by the APA model. The published product enables users to sort through the many mobile health apps and filter them according to individual preferences and priorities, making the ever-growing health app market more navigable.

Acceptability and Usability of the Mobile Digital Health App NoObesity for Families and Health Care Professionals: Protocol for a Feasibility Study

Background

Almost a quarter or more than a fifth of children in the United Kingdom are overweight or obese by the time they start school. The UK Department of Health and Social Care’s national policy for combating childhood obesity has critical outcomes centered on sugar and caloric consumption reduction. Health Education England has developed two digital apps for families with children up to 15 years and for their associated health care professionals to provide a digital learning resource and tool aimed at encouraging healthy lifestyles to prevent obesity.

Objective

This feasibility study assesses the usability and acceptability of Health Education England’s NoObesity app for undertaking activities to improve families’ diet and physical activity. The purpose of the study is to evaluate the app’s influence on self-efficacy and goal setting and to determine what can be learnt to improve its design for future studies, if there is evidence of adoption and sustainability.

Methods

The study population will include 20 to 40 families and their linked health care professionals. Considering issues related to digital access associated with socioeconomic status and the impact on information technology use, study recruitment will be regionally focused in a low socioeconomic status area. The study will last for 9 months (3-month intervention period and 6-month follow-up). The evaluations of feasibility, acceptability, and usability will be conducted using the following scales and theoretical frameworks: (1) system usability scale; (2) Reach Effectiveness Adoption Implementation Maintenance framework; (3) Bandura model of health promotion; and (4) Nonadoption, Abandonment, and Challenges to the Scale-up, Spread, and Suitability framework. App use will be captured and quantitatively analyzed for net use patterns (eg, number of screens viewed, number of logins, cumulative minutes using the app, number of plans made, and number of times goals met) and to triangulate qualitative feedback from study participants.

Results

This study was funded in March 2019 by Health Education England and received University of Oxford Medical Sciences Interdivisional Research Ethics Committee approval on January 31, 2020 (R62092/RE001). At manuscript submission, study recruitment is pending, and expected results will be published in 2021.

Conclusions

This study will provide evidence on the NoObesity app’s influence on self-efficacy and goal-setting and determine what can be learnt to improve its design for future studies, if there is evidence of adoption and sustainability.

International Registered Report Identifier (IRRID)

PRR1-10.2196/18068

Design and testing of a mobile health application rating tool

Mobile health applications ("apps") have rapidly proliferated, yet their ability to improve outcomes for patients remains unclear. A validated tool that addresses apps' potentially important dimensions has not been available to patients and clinicians. The objective of this study was to develop and preliminarily assess a usable, valid, and open-source rating tool to objectively measure the risks and benefits of health apps. We accomplished this by using a Delphi process, where we constructed an app rating tool called THESIS that could promote informed app selection. We used a systematic process to select chronic disease apps with ≥4 stars and <4-stars and then rated them with THESIS to examine the tool's interrater reliability and internal consistency. We rated 211 apps, finding they performed fair overall (3.02 out of 5 [95% CI, 2.96-3.09]), but especially poorly for privacy/security (2.21 out of 5 [95% CI, 2.11-2.32]), interoperability (1.75 [95% CI, 1.59-1.91]), and availability in multiple languages (1.43 out of 5 [95% CI, 1.30-1.56]). Ratings using THESIS had fair interrater reliability (κ = 0.3-0.6) and excellent scale reliability (ɑ = 0.85). Correlation with traditional star ratings was low (r = 0.24), suggesting THESIS captures issues beyond general user acceptance. Preliminary testing of THESIS suggests apps that serve patients with chronic disease could perform much better, particularly in privacy/security and interoperability. THESIS warrants further testing and may guide software and policymakers to further improve app performance, so apps can more consistently improve patient outcomes.

Use of a Smartphone-Based Mobile App for Weight Management in Obese Minority Stroke Survivors: Pilot Randomized Controlled Trial With Open Blinded End Point

Background

Minorities have an increased incidence of early-onset, obesity-related cerebrovascular disease. Unfortunately, effective weight management in this vulnerable population has significant barriers.

Objective

Our objective was to determine the feasibility and preliminary treatment effects of a smartphone-based weight loss intervention versus food journals to monitor dietary patterns in minority stroke patients.

Methods

Swipe out Stroke was a pilot prospective randomized controlled trial with open blinded end point. Minority stroke patients and their caregivers were screened for participation using cluster enrollment. We used adaptive randomization for assignment to a behavior intervention with (1) smartphone-based self-monitoring or (2) food journal self-monitoring. The smartphone group used Lose it! to record meals and communicate with us. Reminder messages (first 30 days), weekly summaries plus reminder messages on missed days (days 31-90), and weekly summaries only (days 91-180) were sent via push notifications. The food journal group used paper diaries. Both groups received 4 in-person visits (baseline and 30, 90, and 180 days), culturally competent counseling, and educational materials. The primary outcome was reduced total body weight.

Results

We enrolled 36 stroke patients (n=23, 64% African American; n=13, 36% Hispanic), 17 in the smartphone group, and 19 in the food journal group. Mean age was 54 (SD 9) years; mean body mass index was 35.7 (SD 5.7) kg/m2; education, employment status, and family history of stroke or obesity did not differ between the groups. Baseline rates of depression (Patient Health Questionnaire-9 [PHQ-9] score median 5.5, IQR 3.0-9.5), cognitive impairment (Montreal Cognitive Assessment score median 23.5, IQR 21-26), and inability to ambulate (5/36, 14% with modified Rankin Scale score 3) were similar. In total, 25 (69%) stroke survivors completed Swipe out Stroke (13/17 in the smartphone group, 12/19 in the food journal group); 1 participant in the smartphone group died. Median weight change at 180 days was 5.7 lb (IQR –2.4 to 8.0) in the smartphone group versus 6.4 lb (IQR –2.2 to 12.5; P=.77) in the food journal group. Depression was significantly lower at 30 days in the smartphone group than in the food journal group (PHQ-9 score 2 vs 8; P=.03). Clinically relevant depression rates remained in the zero to minimal range for the smartphone group compared with mild to moderate range in the food journal group at day 90 (PHQ-9 score 3.5 vs 4.5; P=.39) and day 180 (PHQ-9 score 3 vs 6; P=.12).

Conclusions

In a population of obese minority stroke survivors, the use of a smartphone did not lead to a significant difference in weight change compared with keeping a food journal. The presence of baseline depression (19/36, 53%) was a confounding variable, which improved with app engagement. Future studies that include treatment of poststroke depression may positively influence intervention efficacy.

Trial Registration

ClinicalTrials.gov NCT02531074; https://www.clinicaltrials.gov/ct2/show/NCT02531074

Mobile Health Divide Between Clinicians and Patients in Cancer Care: Results From a Cross-Sectional International Survey

Background

Mobile technologies are increasingly being used to manage chronic diseases, including cancer, with the promise of improving the efficiency and effectiveness of care. Among the myriad of mobile technologies in health care, we have seen an explosion of mobile apps. The rapid increase in digital health apps is not paralleled by a similar trend in usage statistics by clinicians and patients. Little is known about how much and in what ways mobile health (mHealth) apps are used by clinicians and patients for cancer care, what variables affect their use of mHealth, and what patients’ and clinicians’ expectations of mHealth apps are.

Objective

This study aimed to describe the patient and clinician population that uses mHealth in cancer care and to provide recommendations to app developers and regulators to generally increase the use and efficacy of mHealth apps.

Methods

Through a cross-sectional Web-based survey, we explored the current utilization rates of mHealth in cancer care and factors that explain the differences in utilization by patients and clinicians across the United States and 5 different countries in Europe. In addition, we conducted an international workshop with more than 100 stakeholders and a roundtable with key representatives of international organizations of clinicians and patients to solicit feedback on the survey results and develop insights into mHealth app development practices.

Results

A total of 1033 patients and 1116 clinicians participated in the survey. The proportion of cancer patients using mHealth (294/1033, 28.46%) was far lower than that of clinicians (859/1116, 76.97%). Accounting for age and salary level, the marginal probabilities of use at means are still significantly different between the 2 groups and were 69.8% for clinicians and 38.7% for patients using the propensity score–based regression adjustment with weighting technique. Moreover, our analysis identified a gap between basic and advanced users, with a prevalent use for activities related to the automation of processes and the interaction with other individuals and a limited adoption for side-effect management and compliance monitoring in both groups.

Conclusions

mHealth apps can provide access to clinical and economic data that are low cost, easy to access, and personalized. The benefits can go as far as increasing patients’ chances of overall survival. However, despite its potential, evidence on the actual use of mobile technologies in cancer care is not promising. If the promise of mHealth is to be fulfilled, clinician and patient usage rates will need to converge. Ideally, cancer apps should be designed in ways that strengthen the patient-physician relationship, ease physicians’ workload, be tested for validity and effectiveness, and fit the criteria for reimbursement.

Using Human-Centered Design to Build a Digital Health Advisor for Patients With Complex Needs: Persona and Prototype Development

Background

Twenty years ago, a “Guardian Angel” or comprehensive digital health advisor was proposed to empower patients to better manage their own health. This is now technically feasible, but most digital applications have narrow functions and target the relatively healthy, with few designed for those with the greatest needs.

Objective

The goal of the research was to identify unmet needs and key features of a general digital health advisor for frail elderly and people with multiple chronic conditions and their caregivers.

Methods

In-depth interviews were used to develop personas and use cases, and iterative feedback from participants informed the creation of a low-fidelity prototype of a digital health advisor. Results were shared with developers, investors, regulators, and health system leaders for suggestions on how this could be developed and disseminated.

Results

Patients highlighted the following goals: “live my life,” “love my life,” “manage my health,” and “feel understood.” Patients and caregivers reported interest in four functions to address these goals: tracking and insights, advice and information, providing a holistic picture of the patient, and coordination and communication. Experts and system stakeholders felt the prototype was technically feasible, and that while health care delivery organizations could help disseminate such a tool, it should be done in partnership with consumer-focused organizations.

Conclusions

This study describes the key features of a comprehensive digital health advisor, but to spur its development, we need to clarify the business case and address the policy, organizational, and cultural barriers to creating tools that put patients and their goals at the center of the health system.

Patients' and Nephrologists' Evaluation of Patient-Facing Smartphone Apps for CKD

BACKGROUND AND OBJECTIVES

Many aspects of CKD management rely heavily on patient self-care, including medication and dietary adherence, self-monitoring of BP, and daily physical activity. Growing evidence suggests that incorporating smartphone-based applications can support self-care in CKD and chronic disease more generally.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

We identified applications targeting patients with CKD by conducting a search of the US Apple App Store (iOS) and Google Play Store (Android) using the following four phrases: "kidney disease," "renal," "dialysis," and "kidney transplant." We considered the first 50 applications for each search term on each application store. We adapted a previously described framework for assessment of mobile health applications to account for kidney disease-specific content areas and evaluated applications on their types of patient engagement, quality, usability, and safety. Engagement and quality were assessed by both a patient and a nephrologist, usability was assessed by a patient, and safety was assessed by a nephrologist. Overall, two patients with CKD and three nephrologists performed the evaluations. We examined pairwise correlations between patient, nephrologist, and consumer ratings of application quality.

RESULTS

Our search strategy identified 174 unique applications on Android and 165 unique applications on iOS. After excluding applications that were not related to kidney disease, were not patient facing, or were last updated before 2014, 12 Android-only applications, 11 iOS-only applications, and five dual-platform applications remained. Patient and nephrologist application quality ratings, assessed by the net promoter score, were not correlated (r=0.36; P=0.06). Consumer ratings on the application stores did not correlate with patient ratings of application quality (r=0.34; P=0.18).

CONCLUSIONS

Only a small subset of CKD applications was highly rated by both patients and nephrologists. Patients' impressions of application quality are not directly linked to consumer application ratings or nephrologist impressions.

Is Blockchain Technology Suitable for Managing Personal Health Records? Mixed-Methods Study to Test Feasibility

Background

There are many perspectives on the advantages of introducing blockchain in the medical field, but there are no published feasibility studies regarding the storage, propagation, and management of personal health records (PHRs) using blockchain technology.

Objective

The purpose of this study was to investigate the usefulness of blockchains in the medical field in relation to transactions with and propagation of PHRs in a private blockchain.

Methods

We constructed a private blockchain network using Ethereum version 1.8.4 and conducted verification using the de-identified PHRs of 300 patients. The private blockchain network consisted of one hospital node and 300 patient nodes. In order to verify the effectiveness of blockchain-based PHR management, PHRs at a time were loaded in a transaction between the hospital and patient nodes and propagated to the whole network. We obtained and analyzed the time and gas required for data transaction and propagation on the blockchain network. For reproducibility, these processes were repeated 100 times.

Results

Of 300 patient records, 74 (24.7%) were not loaded in the private blockchain due to the data block size of the transaction block. The remaining 226 individual health records were classified into groups A (80 patients with outpatient visit data less than 1 year old), B (84 patients with outpatient data from between 1 and 3 years before data collection), and C (62 patients with outpatient data 3 to 5 years old). With respect to mean transaction time in the blockchain, C (128.7 seconds) had the shortest time, followed by A (132.2 seconds) and then B (159.0 seconds). The mean propagation times for groups A, B, and C were 1494.2 seconds, 2138.9 seconds, and 4111.4 seconds, respectively; mean file sizes were 5.6 KB, 18.6 KB, and 45.38 KB, respectively. The mean gas consumption values were 1,900,767; 4,224,341; and 4,112,784 for groups A, B, and C, respectively.

Conclusions

This study confirms that it is possible to exchange PHR data in a private blockchain network. However, to develop a blockchain-based PHR platform that can be used in practice, many improvements are required, including reductions in data size, improved personal information protection, and reduced operating costs.

Continuous Glucose Monitoring and Insulin Informed Advisory System with Automated Titration and Dosing of Insulin Reduces Glucose Variability in Type 1 Diabetes Mellitus

BACKGROUND

Glucose variability (GV) remains a key limiting factor in the success of diabetes management. While new technologies, for example, accurate continuous glucose monitoring (CGM) and connected insulin delivery devices, are now available, current treatment standards fail to leverage the wealth of information generated. Expert systems, from automated insulin delivery to advisory systems, are a key missing element to richer, more personalized, glucose management in diabetes.

METHODS

Twenty four subjects with type 1 diabetes mellitus (T1DM), 15 women, 37 ± 11 years of age, hemoglobin A1c 7.2% ± 1%, total daily insulin (TDI) 46.7 ± 22.3 U, using either an insulin pump or multiple daily injections with carbohydrate counting, completed two randomized crossover 48-h visits at the University of Virginia, wearing Dexcom G4 CGM, and using either usual care or the UVA decision support system (DSS). DSS consisted of a combination of automated insulin titration, bolus calculation, and CHO treatment advice. During each admission, participants were exposed to a variety of meal sizes and contents and two 45-min bouts of exercise. GV and glucose control were assessed using CGM.

RESULTS

The use of DSS significantly reduced GV (coefficient of variation: 0.36 ± 08. vs. 0.33 ± 0.06, P = 0.045) while maintaining glycemic control (average CGM: 155.2 ± 27.1 mg/dL vs. 155.2 ± 23.2 mg/dL), by reducing hypoglycemia exposure (%<70 mg/dL: 3.8% ± 4.6% vs. 1.8% ± 2%, P = 0.018), with nonsignificant trends toward reduction of significant hyperglycemia overnight (%>250 mg/dL: 5.3% ± 9.5% vs. 1.9% ± 4.6%) and at mealtime (11.3% ± 14.8% vs. 5.8% ± 9.1%).

CONCLUSIONS

A CGM/insulin informed advisory system proved to be safe and feasible in a cohort of 24 T1DM subjects. Use of the system may result in reduced GV and improved protection against hypoglycemia.

Self-Management of Chronic Diseases Among Older Korean Adults: An mHealth Training, Protocol, and Feasibility Study

Background

Most training programs for self-management of chronic diseases in Korea currently involve face-to-face interactions primarily in a health care setting. Therefore, older Koreans living in the community continue to seek other training opportunities for the management of chronic diseases. This has led to the development of new training methods, such as mobile health (mHealth) care, which are valuable in community centers and homes.

Objective

This feasibility study (1) developed an mHealth training protocol to empower community-dwelling elderly individuals to manage their chronic diseases; (2) examined the feasibility of delivering this mHealth training protocol to elderly individuals through mobile tablets and applications (apps); and (3) discussed the contextual and methodological challenges associated with the development of this protocol.

Methods

The mHealth training protocol was developed based on the eHealth Enhanced Chronic Care Model and comprised of four phases. Phase 1 included standardized technology (mobile tablets) training using guidebooks, demonstrations, and guided practice. Phase 2 included provision of standardized information about disease management that was obtained from governmental and professional health care organizations. Phase 3 included provision of training on the use of high-quality mHealth apps that were selected based on individual diagnoses. Phase 4 included encouraging the patients to practice using self-selected mHealth apps based on their individual needs. Quantitative descriptive statistics and qualitative content analyses of user evaluations were used to assess the feasibility and user acceptance of this protocol.

Results

Of the 27 older adults included in this study, 25 completed all 4 weeks of the mHealth training. The attrition rate was 7% (2/27), and the reasons included time conflicts, emotional distress, and/or family discouragement. The men required little or no training for Phase 1, and in comparison with men, women seemed to depend more on the mHealth trainers in Phase 3. Gender, level of education, and previous experience of using smartphones were associated with the speed of learning, level of confidence, and overall competence.

Conclusions

A tailored and personalized approach is required to develop mHealth training protocols for older adults. Self-management of chronic diseases via mHealth training requires careful consideration of the complex nature of human behavior, emotional responses, and familial influences. Therefore, integration of a theoretical, clinical, and technical approach is necessary for the successful development and implementation of an mHealth training program that targets older adults with chronic diseases in a community setting.

The Spanish Availability and Readability of Diabetes Apps

BACKGROUND

There is growing evidence supporting the use of mobile health apps for the management of diabetes. Given the disproportionate impact of diabetes on Latinos, especially those with limited English proficiency (LEP) and low literacy, diabetes apps have the potential to address existing health disparities. Our study aimed to understand the current accessibility of diabetes apps for these populations.

METHODS

We searched the Android and iOS stores for the term "diabetes" to identify patient-facing diabetes apps. We reviewed the app store descriptions and user interfaces for Spanish availability. We assessed the readability of the descriptions in English and Spanish using the Lexile Analyzer and the Flesch-Kincaid Reading Grade Level.

RESULTS

Overall, in reviewing both app stores, 30% (28/92) of apps had descriptions available in Spanish, of which 41% (18/44) of Android apps were available in Spanish and 21% (10/48) iOS apps were available in Spanish. In addition, the readability of 94% (90/96) for the app store descriptions was above the recommended reading level for patient education material in English and Spanish. The overall kappa coefficient for app translation quality assessment was .72, reflecting moderate interrater agreement.

CONCLUSIONS

Despite the evidence supporting the use of diabetes apps, they do not cater to the language needs of LEP Latino patients.

A Novel Mobile App and Population Management System to Manage Rheumatoid Arthritis Flares: Protocol for a Randomized Controlled Trial

Background

Rheumatoid arthritis flares have a profound effect on patients, causing pain and disability. However, flares often occur between regularly scheduled health care provider visits and are, therefore, difficult to monitor and manage. We sought to develop a mobile phone app combined with a population management system to help track RA flares between visits.

Objective

The objective of this study is to implement the mobile app plus the population management system to monitor rheumatoid arthritis disease activity between scheduled health care provider visits over a period of 6 months.

Methods

This is a randomized controlled trial that lasts for 6 months for each participant. We aim to recruit 190 patients, randomized 50:50 to the intervention group versus the control group. The intervention group will be assigned the mobile app and be prompted to answer daily questionnaires sent to their mobile devices. Both groups will be assigned a population manager, who will communicate with the participants via telephone at 6 weeks and 18 weeks. The population manager will also communicate with the participants in the intervention group if their responses indicate a sustained increase in rheumatoid arthritis disease activity. To assess patient satisfaction, the primary outcomes will be scores on the Treatment Satisfaction Questionnaire for Medication as well as the Perceived Efficacy in Patient-Physician Interactions questionnaire at 6 months. To determine the effect of the mobile app on rheumatoid arthritis disease activity, the primary outcome will be the Clinical Disease Activity Index at 6 months.

Results

The trial started in November 2016, and an estimated 2.5 years will be necessary to complete the study. Study results are expected to be published by the end of 2019.

Conclusions

The completion of this study will provide important data regarding the following: (1) the assessment of validated outcome measures to assess rheumatoid arthritis disease activity with a mobile app between routinely scheduled health care provider visits, (2) patient engagement in monitoring their condition, and (3) communication between patients and health care providers through the population management system.

Trial Registration

ClinicalTrials.gov NCT02822521, http://clinicaltrials.gov/ct2/show/NCT02822521 (Archived by WebCite at http://www.webcitation.org/6xed3kGPd)

Managing Patient-Generated Health Data Through Mobile Personal Health Records: Analysis of Usage Data

Background

Personal health records (PHRs) and mHealth apps are considered essential tools for patient engagement. Mobile PHRs (mPHRs) can be a platform to integrate patient-generated health data (PGHD) and patients’ medical information. However, in previous studies, actual usage data and PGHD from mPHRs have not been able to adequately represent patient engagement.

Objective

By analyzing 5 years’ PGHD from an mPHR system developed by a tertiary hospital in South Korea, we aimed to evaluate how PGHD were managed and identify issues in PGHD management based on actual usage data. Additionally, we analyzed how to improve patient engagement with mPHRs by analyzing the actively used services and long-term usage patterns.

Methods

We gathered 5 years (December 2010 to December 2015) of log data from both hospital patients and general users of the app. We gathered data from users who entered PGHD on body weight, blood pressure (BP), blood glucose levels, 10-year cardiovascular disease (CVD) risk, metabolic syndrome risk, medication schedule, insulin, and allergy. We classified users according to whether they were patients or general users based on factors related to continuous use (≥28 days for weight, BP, and blood glucose, and ≥180 days for CVD and metabolic syndrome), and analyzed the patients’ characteristics. We compared PGHD entry counts and the proportion of continuous users for each PGHD by user type.

Results

The total number of mPHR users was 18,265 (patients: n=16,729, 91.59%) with 3620 users having entered weight, followed by BP (n=1625), blood glucose (n=1374), CVD (n=764), metabolic syndrome (n=685), medication (n=252), insulin (n=72), and allergy (n=61). Of those 18,256 users, 3812 users had at least one PGHD measurement, of whom 175 used the PGHD functions continuously (patients: n=142, 81.14%); less than 1% of the users had used it for more than 4 years. Except for weight, BP, blood glucose, CVD, and metabolic syndrome, the number of PGHD records declined. General users’ continuous use of PGHD was significantly higher than that of patients in the blood glucose (P<.001) and BP (P=.03) functions. Continuous use of PGHD in health management (BP, blood glucose, and weight) was significantly greater among older users (P<.001) and men (P<.001). In health management (BP, weight, and blood glucose), overall chronic disease and continuous use of PGHD were not statistically related (P=.08), but diabetes (P<.001) and cerebrovascular diseases (P=.03) were significant.

Conclusions

Although a small portion of users managed PGHD continuously, PGHD has the potential to be useful in monitoring patient health. To realize the potential, specific groups of continuous users must be identified, and the PGHD service must target them. Further evaluations for the clinical application of PGHD, feedback regarding user interfaces, and connections with wearable devices are needed.