Digital Solutions to Alleviate the Burden on Health Systems During a Public Health Care Crisis: COVID-19 as an Opportunity

Co-Designing a Conversational Agent With Older Adults With Chronic Obstructive Pulmonary Disease Who Age in Place: Qualitative Study

BACKGROUND

As a reaction to the global demographic increase in older adults (aged 60+ years), policy makers call for initiatives to enable healthy aging. This includes a focus on person-centered care and access to long-term care for older adults, such as developing different services and digital health technologies. This can enable patients to engage in their health and reduce the burden on the health care systems and health care professionals. The European Union project Smart Inclusive Living Environments (SMILE) focuses on well-being and aging in place using new digital health technologies. The novelty of the SMILE project is the use of a cocreational approach focused on the needs and preferences of older adults with chronic obstructive pulmonary disease (COPD) in technology development, to enhance access, adaptation, and usability and to reduce stigma.

OBJECTIVE

The study aimed to describe the perspective, needs, and preferences of older adults living with COPD in the context of the design and development of a conversational agent.

METHODS

This study carried out a data-driven thematic analysis of interview data from 11 cocreation workshops with 33 older adults living with COPD.

RESULTS

The three particular features that the workshop participants wanted to implement in a new technology were (1) a "my health" function, to use technology to manage and learn more about their condition; (2) a "daily activities" function, including an overview and information about social and physical activities in their local area; and (3) a "sleep" function, to manage circadian rhythm and enhance sleep quality, for example, through online video guides. In total, 2 overarching themes were identified for the 3 functions: measurements, which were actively discussed and received mixed interest among the participants, and health literacy, due to an overall interest in learning more about their condition in relation to everyday life.

CONCLUSIONS

The future design of digital health technology must embrace the complexities of the everyday life of an older adult living with COPD and cater to their needs and preferences. Measurements should be optional and personalized, and digital solutions should be used as a supplement to health care professionals, not as substitute.

Mobile Diagnostic Clinics

This article reviews the revolutionary impact of emerging technologies and artificial intelligence (AI) in reshaping modern healthcare systems, with a particular focus on the implementation of mobile diagnostic clinics. It presents an insightful analysis of the current healthcare challenges, including the shortage of healthcare workers, financial constraints, and the limitations of traditional clinics in continual patient monitoring. The concept of "Mobile Diagnostic Clinics" is introduced as a transformative approach where healthcare delivery is made accessible through the incorporation of advanced technologies. This approach is a response to the impending shortfall of medical professionals and the financial and operational burdens conventional clinics face. The proposed mobile diagnostic clinics utilize digital health tools and AI to provide a wide range of services, from everyday screenings to diagnosis and continual monitoring, facilitating remote and personalized care. The article delves into the potential of nanotechnology in diagnostics, AI's role in enhancing predictive analytics, diagnostic accuracy, and the customization of care. Furthermore, the article discusses the importance of continual, noninvasive monitoring technologies for early disease detection and the role of clinical decision support systems (CDSSs) in personalizing treatment guidance. It also addresses the challenges and ethical concerns of implementing these advanced technologies, including data privacy, integration with existing healthcare infrastructure, and the need for transparent and bias-free AI systems.

Digital Phenotyping of Geriatric Depression Using a Community-Based Digital Mental Health Monitoring Platform for Socially Vulnerable Older Adults and Their Community Caregivers: 6-Week Living Lab Single-Arm Pilot Study

BACKGROUND

Despite the increasing need for digital services to support geriatric mental health, the development and implementation of digital mental health care systems for older adults have been hindered by a lack of studies involving socially vulnerable older adult users and their caregivers in natural living environments.

OBJECTIVE

This study aims to determine whether digital sensing data on heart rate variability, sleep quality, and physical activity can predict same-day or next-day depressive symptoms among socially vulnerable older adults in their everyday living environments. In addition, this study tested the feasibility of a digital mental health monitoring platform designed to inform older adult users and their community caregivers about day-to-day changes in the health status of older adults.

METHODS

A single-arm, nonrandomized living lab pilot study was conducted with socially vulnerable older adults (n=25), their community caregivers (n=16), and a managerial social worker over a 6-week period during and after the COVID-19 pandemic. Depressive symptoms were assessed daily using the 9-item Patient Health Questionnaire via scripted verbal conversations with a mobile chatbot. Digital biomarkers for depression, including heart rate variability, sleep, and physical activity, were measured using a wearable sensor (Fitbit Sense) that was worn continuously, except during charging times. Daily individualized feedback, using traffic signal signs, on the health status of older adult users regarding stress, sleep, physical activity, and health emergency status was displayed on a mobile app for the users and on a web application for their community caregivers. Multilevel modeling was used to examine whether the digital biomarkers predicted same-day or next-day depressive symptoms. Study staff conducted pre- and postsurveys in person at the homes of older adult users to monitor changes in depressive symptoms, sleep quality, and system usability.

RESULTS

Among the 31 older adult participants, 25 provided data for the living lab and 24 provided data for the pre-post test analysis. The multilevel modeling results showed that increases in daily sleep fragmentation (P=.003) and sleep efficiency (P=.001) compared with one's average were associated with an increased risk of daily depressive symptoms in older adults. The pre-post test results indicated improvements in depressive symptoms (P=.048) and sleep quality (P=.02), but not in the system usability (P=.18).

CONCLUSIONS

The findings suggest that wearable sensors assessing sleep quality may be utilized to predict daily fluctuations in depressive symptoms among socially vulnerable older adults. The results also imply that receiving individualized health feedback and sharing it with community caregivers may help improve the mental health of older adults. However, additional in-person training may be necessary to enhance usability.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06270121; https://clinicaltrials.gov/study/NCT06270121.

Recommendations for Improving Chronic Care in Times of a Pandemic Based on Patient Experiences

OBJECTIVES

The COVID-19 pandemic had a profound and pervasive impact on the health of chronic care patients and disrupted care systems worldwide. Our research aimed to assess the impact of the pandemic on chronic care provision and provide recommendations for improving care provision, based on patient experiences.

DESIGN

Qualitative semi-structured interviews were held among patients with chronic obstructive pulmonary disease (COPD) or heart failure.

SETTING AND PARTICIPANTS

Using stratified sampling, 23 patients with COPD, heart failure, or both were recruited to participate in semi-structured interviews. In the summer of 2021, online interviews were conducted.

METHODS

An iterative process was adopted to analyze the data. Going back and forth through the data and our analytical structure, we first coded the data, and subsequently developed categories, themes, and aggregate dimensions. The data were synthesized in a data structure and a data table, which were analyzed using an interpretative approach.

RESULTS

We found 3 dimensions through which care might be improved: (1) proactive and adaptive health care organization and use of innovative technologies, (2) assistance in maintaining patient resilience and coping strategies, and (3) health care built on outreaching and person-centered care enabling identification of individual patient needs. Experiences of impaired accessibility to care, altered and unmet care demands and patient needs, and the negative impact of national containment strategies on patient resilience support the need for improvement in these dimensions.

CONCLUSIONS AND IMPLICATIONS

The in-depth insight gained on the impact of the pandemic on chronic care provision was used to propose recommendations for improving care, supported by not only the what and how but also the why developments require additional efforts made by policymakers and change agents, augmented by structural use and development of innovations. Health care organizations should be enabled to rapidly respond to changing internal and external environments, develop and implement innovations, and match care to patient needs.

Specialized nurses' role in ensuring patient safety within the context of telehealth in home care: A scoping review

Objectives

Specialized nurses are uniquely positioned to implement innovative telehealth solutions to improve the quality and safety of home care, and this has become a focal point of contemporary healthcare research. This review aimed to identify the nature and scope of specialized nurses' roles in ensuring patient safety within the context of telehealth in home care.

Methods

A scoping review of the international literature was carried out from January 1, 2013, to August 29, 2024. The review employed Levac et al.'s framework to delineate the research phenomenon and consolidate existing empirical research findings. Through a comparative analysis, the review integrated findings from selected studies, highlighting both similarities and differences related to this phenomenon, which led to the development of distinct categories.

Results

The search yielded 1127 articles, from which 23 studies met the inclusion criteria for research synthesis and subsequent reporting of results. These studies spanned specialized nurses' roles in telehealth and various fields in which specialized nurses utilized telehealth to deliver high-quality and safe home care. The findings highlighted key outcomes linked to the improvement of patient safety in home care encompassing continuity of care, confidence in care, monitoring and early intervention, medication safety, engagement and adherence, and healthcare costs.

Conclusions

The review revealed the crucial role played by specialized nurses in harnessing telehealth in healthcare to meet the highest care standards, creating an environment that prioritizes the well-being and patient safety in home care.

Healthcare workers' acceptance of the integrated tuberculosis-COVID-19 screening in central Java Private Hospitals, Indonesia

Objective

COVID-19 pandemic has negatively impacted the diagnosis and management of tuberculosis (TB) cases, and TB-COVID-19 integrated screening was introduced as a strategy to overcome these problems. This study determined the acceptability of the TB-COVID-19 integrated screening by healthcare workers (HCWs) and its impact on achievement of the TB program.

Methods

This was a mixed-method study with an embedded design. Data on hospital TB program coverage from the national TB information system for all Muhammadiyah and Aisyiyah Hospitals (MAHs) in Central Java were compared before and after the implementation of TB-COVID-19 integrated screening. The informants consisted of HCWs from 21 MAHs in Central Java. Focus group discussions (FGDs) were carried out with 7 hospital TB, 19 emergency room, 10 outpatient, 6 inpatient, and 4 managerial staff. In-depth interview (IDIs) were also performed with the Technical Officer TB Recovery Head of the Muhammadiyah Center. All IDIs and FGDs were recorded, transcribed verbatim, and subjected to thematic analysis guided by the theoretical framework of acceptability (TFA).

Result

Implementation of the TB-COVID-19 integrated screening program led to an increase in the number of new TB case diagnoses at the Central Java Hospitals. Moreover, the program was acceptable based on seven indicators from TFA. Despite the obstacles faced by HCWs during the implementation process, the program still managed to meet the standards.

Conclusion

Acceptance by HCWs is a critical factor in the successful implementation of programs, including the TB-COVID-19 integrated screening. Furthermore, a multifaceted and cross-sectoral approach is required to address the constraints associated with the process.

Digital Health Programs to Reduce Readmissions in Coronary Artery Disease: A Systematic Review and Meta-Analysis

Background

The use of mobile health (mHealth, wireless communication devices, and/or software technologies) in health care delivery has increased rapidly in recent years. Their integration into disease management programs (DMPs) has tremendous potential to improve outcomes for patients with coronary artery disease (CAD), yet a more robust evaluation of the evidence is required.

Objectives

The purpose of this study was to undertake a systematic review and meta-analysis of mHealth-enabled DMPs to determine their effectiveness in reducing readmissions and mortality in patients with CAD.

Methods

We systematically searched English language studies from January 1, 2007, to August 3, 2021, in multiple databases. Studies comparing mHealth-enabled DMPs with standard DMPs without mHealth were included if they had a minimum 30-day follow-up for at least one of all-cause or cardiovascular-related mortality, readmissions, or major adverse cardiovascular events.

Results

Of the 3,411 references from our search, 155 full-text studies were assessed for eligibility, and data were extracted from 18 publications. Pooled findings for all-cause readmissions (10 studies, n = 1,514) and cardiac-related readmissions (9 studies, n = 1,009) indicated that mHealth-enabled DMPs reduced all-cause (RR: 0.68; 95% CI: 0.50-0.91) and cardiac-related hospitalizations (RR: 0.55; 95% CI: 0.44-0.68) and emergency department visits (RR: 0.37; 95% CI: 0.26-0.54) compared to DMPs without mHealth. There was no significant reduction for mortality outcomes (RR: 1.72; 95% CI: 0.64-4.64) or major adverse cardiovascular events (RR: 0.68; 95% CI: 0.40-1.15).

Conclusions

DMPs integrated with mHealth should be considered an effective intervention for better outcomes in patients with CAD.

Right Information, Right Patient, Right Time: Utilizing the MyCareCompass Platform to Deliver Patient Education in the Oncology Setting

Patient education is an important part of cancer care as it increases patient activation and informed decision-making, reduces anxiety, and improves outcomes. However, challenges to providing appropriate education to patients exist on both the health provider and patient side of the equation, e.g., time constraints and health literacy issues. Digital health education is a fast-growing field of interest that has been shown to improve health outcomes, increase effectiveness of medical treatments and education, lower medical costs, and enhance both clinical diagnosis and research opportunities by streamlining data collection, sharing, and analysis. In 2019, Fox Chase Cancer Center was selected by ARCHES, an established patient education software company, to pilot its award-winning digital patient engagement system MyCareCompass. During the pilot, patients scheduled for port insertions were sent electronic messages inviting them to review various online educational materials related to their procedure and subsequent concerns. The invitations and resources were seamlessly integrated into the scheduling system and timed to arrive when patients would most need them. There was high usage of the port-related materials and patients reported a high level of satisfaction with the delivery system and the information. This automated process of delivering high-quality and relevant patient education was able to be implemented smoothly with IT involvement, had a positive impact on patients without adding any extra burden to the care team, and highlighted opportunities to integrate these types of interventions into routine care.

An artificially intelligent, natural language processing chatbot designed to promote COVID-19 vaccination: A proof-of-concept pilot study

Objective

Our goal is to establish the feasibility of using an artificially intelligent chatbot in diverse healthcare settings to promote COVID-19 vaccination.

Methods

We designed an artificially intelligent chatbot deployed via short message services and web-based platforms. Guided by communication theories, we developed persuasive messages to respond to users' COVID-19-related questions and encourage vaccination. We implemented the system in healthcare settings in the U.S. between April 2021 and March 2022 and logged the number of users, topics discussed, and information on system accuracy in matching responses to user intents. We regularly reviewed queries and reclassified responses to better match responses to query intents as COVID-19 events evolved.

Results

A total of 2479 users engaged with the system, exchanging 3994 COVID-19 relevant messages. The most popular queries to the system were about boosters and where to get a vaccine. The system's accuracy rate in matching responses to user queries ranged from 54% to 91.1%. Accuracy lagged when new information related to COVID emerged, such as that related to the Delta variant. Accuracy increased when we added new content to the system.

Conclusions

It is feasible and potentially valuable to create chatbot systems using AI to facilitate access to current, accurate, complete, and persuasive information on infectious diseases. Such a system can be adapted to use with patients and populations needing detailed information and motivation to act in support of their health.

Promoting University Students' Mental Health through an Online Multicomponent Intervention during the COVID-19 Pandemic

The mental health of university students is a serious public health issue. The alarming trend of high levels of untreated psychological distress observed during the COVID-19 pandemic highlights the need for prevention programs. Digital tools are a promising means of delivering such programs. Web-based programs are acceptable and effective at improving mental health problems and general mental well-being. However, the usefulness of such digital prevention approaches to address the multiple issues raised by the COVID-19 pandemic needs to be tested. The current study assessed the effectiveness of an 8-week online intervention, integrating a variety of evidence-based strategies for improving French university students' mental health. Students were assigned to: (1) the online self-help program ETUCARE (n = 53), or (2) the control condition (n = 50). All the participants completed pre- and post-intervention questionnaires that assessed mental health problems and psychological well-being. The findings revealed that, compared to the control group, participation in the online program was associated with higher levels of psychological well-being post-test and fewer clinical symptoms of psychological distress, anxiety, and alcohol consumption. These preliminary findings suggest that the ETUCARE program is a promising multicomponent intervention to buffer the mental health consequences of the COVID-19 pandemic in French university students.

Testing the Differential Impact of an Internet-Based Mental Health Intervention on Outcomes of Well-being and Psychological Distress During COVID-19: Uncontrolled Intervention Study

BACKGROUND

During COVID-19, the psychological distress and well-being of the general population has been precarious, increasing the need to determine the impact of complementary internet-based psychological interventions on both positive mental health as well as distress states. Psychological distress and mental well-being represent distinct dimensions of our mental health, and congruent changes in outcomes of distress and well-being do not necessarily co-occur within individuals. When testing intervention impact, it is therefore important to assess change in both outcomes at the individual level, rather than solely testing group differences in average scores at the group level.

OBJECTIVE

This study set out to investigate the differential impact of an internet-based group mental health intervention on outcomes of positive mental health (ie, well-being, life satisfaction, resilience) and indicators of psychological distress (ie, depression, anxiety, stress).

METHODS

A 5-week mental health intervention was delivered to 89 participants using the Zoom platform during 2020. Impact on outcomes of distress, well-being, and resilience was assessed at the start and end of the program with multiple analysis of variance (MANOVA) and reliable change indices (RCIs) being used to determine program impact at the group and individual levels, respectively.

RESULTS

The intervention significantly improved all mental health outcomes measured, (F6,83=5.60, P<.001; Wilks Λ=.71; partial η2=.29) showing small to moderate effect sizes on individual outcomes. The largest effect sizes were observed for life satisfaction and overall well-being (η2=.22 and η2=.2, respectively). Larger effect sizes were noted for those with problematic mental health scores at baseline. A total of 92% (82/89) of participants demonstrated reliable change in at least one mental health outcome. Differential response patterns using RCI revealed that more than one-half of the participants showed improvement in both mental well-being and psychological distress, over one-quarter in outcomes of well-being only, and almost one-fifth in distress only.

CONCLUSIONS

The results provide evidence for the significant impact of an internet-based mental health intervention during COVID-19 and indicate the importance of assessing dimensions of both well-being and distress when determining mental health intervention effectiveness.