Evaluating Patient-Centered Mobile Health Technologies: Definitions, Methodologies, and Outcomes

Investigating patient engagement associations between a postdischarge texting programme and patient experience, readmission and revisit rates outcomes

OBJECTIVES

This study aimed (1) to examine the association between patient engagement with a bidirectional, semiautomated postdischarge texting programme and Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey outcomes, readmissions and revisit rates in a large health system and (2) to describe operational and clinical flow considerations for implementing a postdischarge texting programme.

SETTING

The study involved 1 main academic hospital (beds: 2500+) and 6 community hospitals (beds: 190-400, averaging 300 beds per hospital) in Houston, Texas.

METHODS

Retrospective, observational cohort study between non-engaged patients (responded with 0-2 incoming text messages) and engaged patients (responded with 3+ incoming, patient-initiated text messages) between December 2022 and May 2023. We used the two-tailed t-test for continuous variables and χ2 test for categorical variables to compare the baseline characteristics between the two cohorts. For the binary outcomes, such as the revisit (1=yes, vs 0=no) and readmissions (1=yes vs 0=no), we constructed mixed effect logistic regression models with the random effects to account for repeated measurements from the hospitals. For the continuous outcome, such as the case mix index (CMI), a generalised linear quantile mixed effect model was built. All tests for significance were two tailed, using an alpha level of 0.05, and 95% CIs were provided. Significance tests were performed to evaluate the CMI and readmissions and revisit rates.

RESULTS

From 78 883 patients who were contacted over the course of this pilot implementation, 49 222 (62.4%) responded, with 39 442 (50%) responded with 3+ incoming text messages. The engaged cohort had higher HCAHPS scores in all domains compared with the non-engaged cohort. The engaged cohort used significantly fewer 30-day acute care resources, experiencing 29% fewer overall readmissions and 20% fewer revisit rates (23% less likely to revisit) and were 27% less likely to be readmitted. The results were statistically significant for all but two hospitals.

CONCLUSIONS

This study builds on the few postdischarge texting studies, and also builds on the patient engagement literature, finding that patient engagement with postdischarge texting can be associated with fewer acute care resources. To our knowledge, this is the only study that documented an association between a text-based postdischarge programme and HCAHPS scores, perhaps owing to the bidirectionality and ease with which patients could interact with nurses. Future research should explore the texting paradigms to evaluate their associated outcomes in a variety of postdischarge applications.

Comprehensiveness, Accuracy, and Readability of Exercise Recommendations Provided by an AI-Based Chatbot: Mixed Methods Study

BACKGROUND

Regular physical activity is critical for health and disease prevention. Yet, health care providers and patients face barriers to implement evidence-based lifestyle recommendations. The potential to augment care with the increased availability of artificial intelligence (AI) technologies is limitless; however, the suitability of AI-generated exercise recommendations has yet to be explored.

OBJECTIVE

The purpose of this study was to assess the comprehensiveness, accuracy, and readability of individualized exercise recommendations generated by a novel AI chatbot.

METHODS

A coding scheme was developed to score AI-generated exercise recommendations across ten categories informed by gold-standard exercise recommendations, including (1) health condition-specific benefits of exercise, (2) exercise preparticipation health screening, (3) frequency, (4) intensity, (5) time, (6) type, (7) volume, (8) progression, (9) special considerations, and (10) references to the primary literature. The AI chatbot was prompted to provide individualized exercise recommendations for 26 clinical populations using an open-source application programming interface. Two independent reviewers coded AI-generated content for each category and calculated comprehensiveness (%) and factual accuracy (%) on a scale of 0%-100%. Readability was assessed using the Flesch-Kincaid formula. Qualitative analysis identified and categorized themes from AI-generated output.

RESULTS

AI-generated exercise recommendations were 41.2% (107/260) comprehensive and 90.7% (146/161) accurate, with the majority (8/15, 53%) of inaccuracy related to the need for exercise preparticipation medical clearance. Average readability level of AI-generated exercise recommendations was at the college level (mean 13.7, SD 1.7), with an average Flesch reading ease score of 31.1 (SD 7.7). Several recurring themes and observations of AI-generated output included concern for liability and safety, preference for aerobic exercise, and potential bias and direct discrimination against certain age-based populations and individuals with disabilities.

CONCLUSIONS

There were notable gaps in the comprehensiveness, accuracy, and readability of AI-generated exercise recommendations. Exercise and health care professionals should be aware of these limitations when using and endorsing AI-based technologies as a tool to support lifestyle change involving exercise.

Informing Patient-Provider Engagement for Shared Decision Making Through Mobile Health Applications

Objective

The study utilized a cross-sectional dataset to identify demographic and health factors associated with patient utilization of mHealth applications for engaging with healthcare providers. The focus was on adults with chronic health conditions as the primary app user group. The goal was to reveal specific barriers and facilitators to app adoption among smartphone users, with the aim of highlighting opportunities for upgrades that promote patient empowerment as a prerequisite for shared decision-making (SDM).

Methods

Data from the Health Information National Trends Survey (HINTS 5, Cycle 4, 2020) with 3865 respondents (≥18 years old) stratified analyses and weighted logistic regression were used.

Results

The study found that individuals having a wellness app on a smartphone increased the likelihood (OR 2.68, CI: 2.02-3.56, p-value < 0.0001) of discussing health conditions with providers. Furthermore, individuals with multiple chronic health conditions were more likely (OR 1.93, CI 1.26-2.95, p-value < 0.01) to use apps to use mobile health applications to engage with healthcare providers. Other significant variables affecting app usage such as race, marital status, and educational level.

Conclusion

Due to difficulties obtaining in-person healthcare, the COVID-19 epidemic forced a swift deployment of mHealth technologies. Even in the absence of a crisis, mobile health applications continue to be crucial for improving patient-provider engagement and developing novel approaches to healthcare delivery. During the pandemic, people with numerous chronic diseases used apps to stay in touch with doctors and maintain their reliance on these platforms. Nonetheless, different smartphone users continue to use mHealth application in different ways. The findings revealing barriers in mHealth app adoption among certain patient subgroups suggest opportunities for developers, in collaboration with users and providers, to enhance inclusion and acceptability when upgrading mHealth application platforms.

Rigorous and rapid evidence assessment in digital health with the evidence DEFINED framework

Dozens of frameworks have been proposed to assess evidence for digital health interventions (DHIs), but existing frameworks may not facilitate DHI evidence reviews that meet the needs of stakeholder organizations including payers, health systems, trade organizations, and others. These organizations may benefit from a DHI assessment framework that is both rigorous and rapid. Here we propose a framework to assess Evidence in Digital health for EFfectiveness of INterventions with Evaluative Depth (Evidence DEFINED). Designed for real-world use, the Evidence DEFINED Quick Start Guide may help streamline DHI assessment. A checklist is provided summarizing high-priority evidence considerations in digital health. Evidence-to-recommendation guidelines are proposed, specifying degrees of adoption that may be appropriate for a range of evidence quality levels. Evidence DEFINED differs from prior frameworks in its inclusion of unique elements designed for rigor and speed. Rigor is increased by addressing three gaps in prior frameworks. First, prior frameworks are not adapted adequately to address evidence considerations that are unique to digital health. Second, prior frameworks do not specify evidence quality criteria requiring increased vigilance for DHIs in the current regulatory context. Third, extant frameworks rarely leverage established, robust methodologies that were developed for non-digital interventions. Speed is achieved in the Evidence DEFINED Framework through screening optimization and deprioritization of steps that may have limited value. The primary goals of Evidence DEFINED are to a) facilitate standardized, rapid, rigorous DHI evidence assessment in organizations and b) guide digital health solutions providers who wish to generate evidence that drives DHI adoption.

Living Ambivalently with Chronic Illness

Mobile health smartphone applications (mHealth apps) enable patients to monitor how chronic illness interconnects with their everyday life. I explore, through focus group discussions, how such monitoring makes sense to pediatric and young patients and parents in Denmark. These groups explicate how they live both with and without chronic illness by distinguishing between when to focus on which aspects of it. I argue that this relationship with chronic illness produces parent's, children's, and young people's ambivalent attitudes toward mHealth apps that promote illness monitoring "anywhere" and at "any time."

Mobile Health Apps for Patient-Centered Care: Review of United States Rheumatoid Arthritis Apps for Engagement and Activation

BACKGROUND

Rheumatoid arthritis (RA) is a highly dynamic and individualized disease in terms of its patterns of symptomatic flare-ups and periods of remission. Patient-centered care (PCC) aligns patients' lifestyle goals with their preferences for managing symptoms and side effects through the selection of therapies appropriate for disease management. Mobile health (mHealth) apps have the potential to engage and activate patients in PCC. mHealth apps can provide features that increase disease knowledge, collect patient-generated health indicators and behavioral metrics, and highlight goals for disease management. However, little evidence-based guidance exists as to which apps contain functionality essential for supporting the delivery of PCC.

OBJECTIVE

The objective of this study was to evaluate the patient-centeredness of United States-based rheumatoid arthritis mobile apps in terms of patient engagement and activation.

METHODS

A search of mobile apps on 2 major United States app stores (Apple App Store and Google Play) was conducted from June 2020 to July 2021 to identify apps designed for use by patients with RA by adapting the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines for mobile health app screening based on the literature. Reviewers conducted a content analysis of mobile app features to evaluate their functionality for patient engagement and activation. Engagement and activation were assessed using the Mobile Application Rating Scale (MARS) and social cognitive theory, respectively. Apps were ranked by their ability to facilitate PCC care along 2 dimensions: engagement and activation.

RESULTS

A total of 202 mobile apps were initially identified, and 20 remained after screening. Two apps emerged with the greatest ability to facilitate PCC. Both apps were scored as having acceptable or good patient engagement according to the MARS. These 2 apps also had high patient activation according to social cognitive theory, with many features within those apps representing theoretical constructs such as knowledge, perceived self-efficacy, and expectations about outcomes that support behavioral management of RA.

CONCLUSIONS

We found very few mobile apps available within the United States that have functionality that both engages and activates the patient to facilitate PCC. As the prevalence of mobile apps expands, the design of mobile apps needs to integrate patients to ensure that their functionality promotes engagement and activation. More research is needed to understand how mobile app use impacts patient engagement and activation, and ultimately, treatment decisions and disease trajectory.

Exploring the Black Box of an mHealth Intervention (LIFE4YOUth): A Qualitative Process and Outcome Evaluation of End-User Engagement

The effectiveness of mHealth interventions rely on whether the content successfully activate mechanisms necessary for behavior change. These mechanisms may be affected by end-users' experience of the intervention content. The aim of this study was to explore how the content of a novel mHealth intervention (LIFE4YOUth) was understood, interpreted, and applied by high school students, and the consequences of engaging with the content. Qualitative content analysis was used inductively and deductively to analyze interview data (n = 16) based on think-aloud techniques with Swedish high school students aged 16-19 years. Theoretical constructs from social cognitive theory framed the deductive analysis. The analysis resulted in four categories which describe central activities of intervention engagement among end-users: defining, considering, centralizing, and personalizing. End-users engaged in these activities to different degrees as illustrated by four typologies: Literal, Vague, Rigid, and Creative engagement. Most informants knew about the risks and benefits of health behaviors, but engagement with intervention content generally increased informants' awareness. In conclusion, this study provides in-depth knowledge on the cognitive process when engaging with mHealth content and suggests that deliberate and flexible engagement most likely deepens end-users' understanding of why and how health behavior change can be managed.

ProHealth eCoach: user-centered design and development of an eCoach app to promote healthy lifestyle with personalized activity recommendations

Background

Regular physical activity (PA), healthy habits, and an appropriate diet are recommended guidelines to maintain a healthy lifestyle. A healthy lifestyle can help to avoid chronic diseases and long-term illnesses. A monitoring and automatic personalized lifestyle recommendation system (i.e., automatic electronic coach or eCoach) with considering clinical and ethical guidelines, individual health status, condition, and preferences may successfully help participants to follow recommendations to maintain a healthy lifestyle. As a prerequisite for the prototype design of such a helpful eCoach system, it is essential to involve the end-users and subject-matter experts throughout the iterative design process.

Methods

We used an iterative user-centered design (UCD) approach to understend context of use and to collect qualitative data to develop a roadmap for self-management with eCoaching. We involved researchers, non-technical and technical, health professionals, subject-matter experts, and potential end-users in design process. We designed and developed the eCoach prototype in two stages, adopting different phases of the iterative design process. In design workshop 1, we focused on identifying end-users, understanding the user’s context, specifying user requirements, designing and developing an initial low-fidelity eCoach prototype. In design workshop 2, we focused on maturing the low-fidelity solution design and development for the visualization of continuous and discrete data, artificial intelligence (AI)-based interval forecasting, personalized recommendations, and activity goals.

Results

The iterative design process helped to develop a working prototype of eCoach system that meets end-user’s requirements and expectations towards an effective recommendation visualization, considering diversity in culture, quality of life, and human values. The design provides an early version of the solution, consisting of wearable technology, a mobile app following the “Google Material Design” guidelines, and web content for self-monitoring, goal setting, and lifestyle recommendations in an engaging manner between the eCoach app and end-users.

Conclusions

The adopted iterative design process brings in a design focus on the user and their needs at each phase. Throughout the design process, users have been involved at the heart of the design to create a working research prototype to improve the fit between technology, end-user, and researchers. Furthermore, we performed a technological readiness study of ProHealth eCoach against standard levels set by European Union (EU).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08441-0.

Waiting Time and Patient Satisfaction in a Subspecialty Eye Hospital Using a Mobile Data Collection Kit: Pre-Post Quality Improvement Intervention

BACKGROUND

Waiting time can considerably increase the cost to both the clinic and the patient and be a major predictor of the satisfaction of eye care users. Efficient management of waiting time remains as a challenge in hospitals. Waiting time management will become even more crucial in the postpandemic era. A key consideration when improving waiting time is the involvement of eye care users. This study aimed at improving patient waiting time and satisfaction through the use of Plan-Do-Study-Act (PDSA) quality improvement cycles.

OBJECTIVE

The objectives of this study were to determine the waiting time and patient satisfaction, measure the association between waiting time and patient satisfaction, and determine the effectiveness of the PDSA model in improving waiting time and satisfaction.

METHODS

This was a pre-post quality improvement study among patients aged 19 to 80 years, who are consulting with the Magrabi International Council of Ophthalmology Cameroon Eye Institute. We used PDSA cycles to conduct improvement audits of waiting time and satisfaction over 6 weeks. A data collection app known as Open Data Kit (Get ODK Inc) was used for real-time tracking of waiting, service, and idling times at each service point. Participants were also asked whether they were satisfied with the waiting time at the point of exit. Data from 51% (25/49) preintervention participants and 49% (24/49) postintervention participants were analyzed using Stata 14 at .05 significance level. An unpaired 2-tailed t test was used to assess the statistical significance of the observed differences in times before and after the intervention. Logistic regression was used to examine the association between satisfaction and waiting time.

RESULTS

In total, 49 participants were recruited with mean age of 49 (SD 15.7) years. The preintervention mean waiting, service, and idling times were 450 (SD 96.6), 112 (SD 47), and 338 (SD 98.1) minutes, respectively. There was no significant association between patient waiting time and satisfaction (odds ratio 1, 95% CI 0.99-1; P=.37; χ23=0.4). The use of PDSA led to 15% (66 minutes/450 minutes) improvement in waiting time (t47=2; P=.05) and nonsignificant increase in patient satisfaction from 32% (8/25) to 33% (8/24; z=0.1; P=.92).

CONCLUSIONS

Use of PDSA led to a borderline statistically significant reduction of 66 minutes in waiting time over 6 weeks and an insignificant improvement in satisfaction, suggesting that quality improvement efforts at the clinic have to be made over a considerable period to be able to produce significant changes. The study provides a good basis for standardizing the cycle (consultation) time at the clinic. We recommend shortening the patient pathway and implementing other measures including a phasic appointment system, automated patient time monitoring, robust ticketing, patient pathway supervision, standard triaging, task shifting, physician consultation planning, patient education, and additional registration staff.

Interaction Empowerment in Mobile Health: Concepts, Challenges, and Perspectives

In its most trending interpretation, empowerment in health care is implemented as a patient-centered approach. In the same sense, many mobile health (mHealth) apps are being developed with a primary focus on the individual user. The integration of mHealth apps into the health care system has the potential to counteract existing challenges, including incomplete or nonstandardized medical data and lack of communication, especially in the intersectional context (eg, patients, medical forces). However, concerns about data security and privacy, regional differences in regulations, lack of accessibility, and nontransparent apps hinder the successful integration of mHealth into the health care system. One approach to address this is to rethink the interpretation of empowerment. On that basis, we here examine existing approaches of individual empowerment and subsequently analyze a different view of empowerment in digital health, namely interaction empowerment. Such a change of perspective could positively influence intersectoral communication and facilitate secure data and knowledge sharing. We discuss this novel viewpoint on empowerment, focusing on more efficient integration and development of mHealth approaches. A renewed interpretation of empowerment could thus buffer current limitations of individual empowerment while also advancing digitization of the health system.

Rapid Deployment of Technology: Patient and Staff Empowerment at Houston Methodist

SUMMARY

Digital innovations are arriving in healthcare at an increasing rate. Electronic medical records provided the foundation for this growth, and now thousands of technology companies are servicing every aspect of healthcare. Since 2018, Houston Methodist has been cultivating digital disruption, working to speed up the development of new initiatives. As our digital innovation has grown exponentially over the past few years, we have kept the patient at the center of all activities. We hold the philosophy that patient empowerment should be a process whereby patients understand their role and have access to knowledge that enables them to engage with their providers in a bidirectional relationship. Patient empowerment in the patient room, in care pathways, and in opioid reduction demonstrate the success of our approach with strongly positive outcomes. Importantly, the efforts are not only appreciated by our patients, but also widely embraced by our clinicians.

Usability Testing of a Patient-Centered Mobile Health App for Supporting and Guiding the Pediatric Emergency Department Patient Journey: Mixed Methods Study

BACKGROUND

Patient experience in emergency departments (EDs) remains often suboptimal and can be a source of stress, particularly in pediatric settings. In an attempt to support patients and their families before, during, and after their visit to a pediatric ED, a mobile health (mHealth) app was developed by a multidisciplinary team based on patient-centered care principles.

OBJECTIVE

This study aims to evaluate the usability (effectiveness, efficiency, and satisfaction) of a new mHealth app, InfoKids, by potential end users through usability testing.

METHODS

The app was assessed through an in-laboratory, video-recorded evaluation in which participants had to execute 9 goal-oriented tasks, ranging from account creation to the reception of a diagnostic sheet at the end of the emergency care episode. Effectiveness was measured based on the task completion rate, efficiency on time on task, and user satisfaction according to answers to the System Usability Scale questionnaire. Think-aloud usability sessions were also transcribed and analyzed. Usability problems were rated for their severity and categorized according to ergonomic criteria.

RESULTS

A total of 17 parents participated in the study. The overall completion rate was 97.4% (149/153). Overall, they reported good effectiveness, with the task successfully completed in 88.2% (135/153) of cases (95% CI 83%-93%). Each task, with the exception of the first, created difficulties for some participants but did not prevent their completion by most participants. Users reported an overall good to excellent perceived usability of the app. However, ergonomic evaluation identified 14 usability problems occurring 81 time. Among these, 50% (7/14) were serious as their severity was rated as either major or catastrophic and indicated areas of improvements for the app. Following the suggested usability improvements by participants, mitigation measures were listed to further improve the app and avoid barriers to its adoption.

CONCLUSIONS

Usability of the InfoKids app was evaluated as good to excellent by users. Areas of improvement were identified, and mitigation measures were proposed to inform its development toward a universal app for all ED patients visiting a digitalized institution. Its contribution could also be useful in paving the way for further research on mobile apps aimed at supporting and accompanying patients in their care episodes, as research in this area is scarce.

Enhancing Patient-Centered Surgical Care With Mobile Health Technology

From smartphones or wearables to portable physiologic sensors and apps, healthcare is witnessing an exponential growth in mHealth-digital health tools used to support medical and surgical care, as well as public health. In surgery, there is interest in harnessing the capabilities of mHealth to improve the quality of patient-centered care delivery. Digitally delivered surveys have enhanced patient-reported outcome measurement and patient engagement throughout care. Wearable devices and sensors have allowed for the assessment of physical fitness before surgery and during recovery. Smartphone-based digital phenotyping has introduced novel methods of integrating multiple data streams (accelerometer, global positioning system, call and text logs) to create multidimensional digital health footprints for patients following surgery. Yet, with all the technological sophistication and 'big data' mHealth provides, widespread implementation has been elusive. Do clinicians and patients find these data valuable or clinically actionable? How can mHealth become integrated into the day-to-day workflows of surgical systems? Do these data represent opportunities to address disparities of care or worsen them? In this review, we discuss experiences and future opportunities to use mHealth to enhance patient-centered surgical care.

Effectiveness of Digital Counseling Environments on Anxiety, Depression, and Adherence to Treatment Among Patients Who Are Chronically Ill: Systematic Review

Background

Patients who are chronically ill need novel patient counseling methods to support their self-care at different stages of the disease. At present, knowledge of how effective digital counseling is at managing patients’ anxiety, depression, and adherence to treatment seems to be fragmented, and the development of digital counseling will require a more comprehensive view of this subset of interventions.

Objective

This study aims to identify and synthesize the best available evidence on the effectiveness of digital counseling environments at improving anxiety, depression, and adherence to treatment among patients who are chronically ill.

Methods

Systematic searches of the EBSCO (CINAHL), PubMed, Scopus, and Web of Science databases were conducted in May 2019 and complemented in October 2020. The review considered studies that included adult patients aged ≥18 years with chronic diseases; interventions evaluating digital (mobile, web-based, and ubiquitous) counseling interventions; and anxiety, depression, and adherence to treatment, including clinical indicators related to adherence to treatment, as outcomes. Methodological quality was assessed using the standardized Joanna Briggs Institute critical appraisal tool for randomized controlled trials or quasi-experimental studies. As a meta-analysis could not be conducted because of considerable heterogeneity in the reported outcomes, narrative synthesis was used to synthesize the results.

Results

Of the 2056 records screened, 20 (0.97%) randomized controlled trials, 4 (0.19%) pilot randomized controlled trials, and 2 (0.09%) quasi-experimental studies were included. Among the 26 included studies, 10 (38%) digital, web-based interventions yielded significantly positive effects on anxiety, depression, adherence to treatment, and the clinical indicators related to adherence to treatment, and another 18 (69%) studies reported positive, albeit statistically nonsignificant, changes among patients who were chronically ill. The results indicate that an effective digital counseling environment comprises high-quality educational materials that are enriched with multimedia elements and activities that engage the participant in self-care. Because of the methodological heterogeneity of the included studies, it is impossible to determine which type of digital intervention is the most effective for managing anxiety, depression, and adherence to treatment.

Conclusions

This study provides compelling evidence that digital, web-based counseling environments for patients who are chronically ill are more effective than, or at least comparable to, standard counseling methods; this suggests that digital environments could complement standard counseling.