Readiness for Telemedical Services in Patients With Cardiovascular Diseases: Cross-sectional Study

BACKGROUND

Telemedicine solutions, especially in the face of epidemiological emergencies such as the COVID-19 pandemic, played an important role in the remote communication between patients and medical providers. However, the implementation of modern technologies should rely on patients' readiness toward new services to enable effective cooperation with the physician. Thus, successful application of patient-centric telehealth services requires an in-depth analysis of users' expectations.

OBJECTIVE

This study aimed to evaluate factors determining readiness for using telehealth solutions among patients with cardiovascular diseases.

METHODS

We conducted a cross-sectional study based on an investigator-designed, validated questionnaire that included 19 items (demographics, health status, medical history, previous health care experience, expected telehealth functionalities, and preferred remote communication methods). Multivariate logistic regression was applied to assess the relationship between readiness and their determinants.

RESULTS

Of the 249 respondents, 83.9% (n=209) consented to the use of telemedicine to contact a cardiologist. The nonacceptance of using telemedicine was 2 times more frequent in rural dwellers (odds ratio [OR] 2.411, 95% CI 1.003-5.796) and patients without access to the internet (OR 2.432, 95% CI 1.022-5.786). In comparison to participants living in rural areas, city dwellers demonstrated a higher willingness to use telemedicine, including following solutions: issuing e-prescriptions (19/31, 61.3% vs 141/177, 79.7%; P=.02); alarming at the deterioration of health (18/31, 58.1% vs 135/177, 76.3%; P=.03); and arranging or canceling medical visits (16/31, 51.6% vs 126/176, 71.6%; P=.03). Contact by mobile phone was preferred by younger patients (OR 2.256, 95% CI 1.058-4.814), whereas older patients and individuals who had no previous difficulties in accessing physicians preferred landline phone communication.

CONCLUSIONS

During a nonpandemic state, 83.9% of patients with cardiovascular diseases declared readiness to use telemedicine solutions.

Promoting Healthcare Workers' Adoption Intention of Artificial-Intelligence-Assisted Diagnosis and Treatment: The Chain Mediation of Social Influence and Human-Computer Trust

Artificial intelligence (AI)-assisted diagnosis and treatment could expand the medical scenarios and augment work efficiency and accuracy. However, factors influencing healthcare workers' adoption intention of AI-assisted diagnosis and treatment are not well-understood. This study conducted a cross-sectional study of 343 dental healthcare workers from tertiary hospitals and secondary hospitals in Anhui Province. The obtained data were analyzed using structural equation modeling. The results showed that performance expectancy and effort expectancy were both positively related to healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Social influence and human-computer trust, respectively, mediated the relationship between expectancy (performance expectancy and effort expectancy) and healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Furthermore, social influence and human-computer trust played a chain mediation role between expectancy and healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Our study provided novel insights into the path mechanism of healthcare workers' adoption intention of AI-assisted diagnosis and treatment.

Recommendations for the Design and Delivery of Transitions-Focused Digital Health Interventions: Rapid Review

Background

Older adults experience a high risk of adverse events during hospital-to-home transitions. Implementation barriers have prevented widespread clinical uptake of the various digital health technologies that aim to support hospital-to-home transitions.

Objective

To guide the development of a digital health intervention to support transitions from hospital to home (the Digital Bridge intervention), the specific objectives of this review were to describe the various roles and functions of health care providers supporting hospital-to-home transitions for older adults, allowing future technologies to be more targeted to support their work; describe the types of digital health interventions used to facilitate the transition from hospital to home for older adults and elucidate how these interventions support the roles and functions of providers; describe the lessons learned from the design and implementation of these interventions; and identify opportunities to improve the fit between technology and provider functions within the Digital Bridge intervention and other transition-focused digital health interventions.

Methods

This 2-phase rapid review involved a selective review of providers’ roles and their functions during hospital-to-home transitions (phase 1) and a structured literature review on digital health interventions used to support older adults’ hospital-to-home transitions (phase 2). During the analysis, the technology functions identified in phase 2 were linked to the provider roles and functions identified in phase 1.

Results

In phase 1, various provider roles were identified that facilitated hospital-to-home transitions, including navigation-specific roles and the roles of nurses and physicians. The key transition functions performed by providers were related to the 3 categories of continuity of care (ie, informational, management, and relational continuity). Phase 2, included articles (n=142) that reported digital health interventions targeting various medical conditions or groups. Most digital health interventions supported management continuity (eg, follow-up, assessment, and monitoring of patients’ status after hospital discharge), whereas informational and relational continuity were the least supported. The lessons learned from the interventions were categorized into technology- and research-related challenges and opportunities and informed several recommendations to guide the design of transition-focused digital health interventions.

Conclusions

This review highlights the need for Digital Bridge and other digital health interventions to align the design and delivery of digital health interventions with provider functions, design and test interventions with older adults, and examine multilevel outcomes.

International Registered Report Identifier (IRRID)

RR2-10.1136/bmjopen-2020-045596

Patients' and Clinicians' Perceived Trust in Internet-of-Things Systems to Support Asthma Self-management: Qualitative Interview Study

Background

Asthma affects 235 million people worldwide. Supported self-management, including an action plan agreed with clinicians, improves asthma outcomes. Internet-of-things (IoT) systems with artificial intelligence (AI) can provide customized support for a range of self-management functions, but trust is vital to encourage patients’ adoption of such systems. Many models for understanding trust exist, some explicitly designed for eHealth, but no studies have used these models to explore trust in the context of using IoT systems to support asthma self-management.

Objective

In this study, we aim to use the McKnight model to explore the functionality, helpfulness, and reliability domains of patients’ and clinicians’ trust in IoT systems to deliver the 14 components of self-management support defined by the PRISMS (Practical Reviews in Self-Management Support) taxonomy.

Methods

We used think-aloud techniques in semistructured interviews to explore the views of patients and clinicians. Patients were recruited from research registers and social media and purposively sampled to include a range of ages, genders, action plan ownership, asthma duration, hospital admissions, and experience with mobile apps. Clinicians (primary, secondary, and community-based) were recruited from professional networks. Interviews were transcribed verbatim, and thematic analysis was used to explore perceptions of the functionality, helpfulness, and reliability of IoT features to support components of supported self-management.

Results

A total of 12 patients and 12 clinicians were interviewed. Regarding perceived functionality, most patients considered that an IoT system had functionality that could support a broad range of self-management tasks. They wanted a system to provide customized advice involving AI. With regard to perceived helpfulness, they considered that IoT systems could usefully provide integrated support for a number of recognized components of self-management support. In terms of perceived reliability, they believed they could rely on the system to log their asthma condition and provide preset action plan advice triggered by their logs. However, they were less confident that the system could operate continuously and without errors in providing advice. They were not confident that AI could generate new advice or reach diagnostic conclusions without the interpretation of their trusted clinicians. Clinicians wanted clinical evidence before trusting the system.

Conclusions

IoT systems including AI were regarded as offering potentially helpful functionality in mediating the action plans developed with a trusted clinician, although our technologically adept participants were not yet ready to trust AI to generate novel advice. Research is needed to ensure that technological capability does not outstrip the trust of individuals using it.

Readiness for Voice Technology in Patients With Cardiovascular Diseases: Cross-Sectional Study

Background

The clinical application of voice technology provides novel opportunities in the field of telehealth. However, patients’ readiness for this solution has not been investigated among patients with cardiovascular diseases (CVD).

Objective

This paper aims to evaluate patients’ anticipated experiences regarding telemedicine, including voice conversational agents combined with provider-driven support delivered by phone.

Methods

A cross-sectional study enrolled patients with chronic CVD who were surveyed using a validated investigator-designed questionnaire combining 19 questions (eg, demographic data, medical history, preferences for using telehealth services). Prior to the survey, respondents were educated on the telemedicine services presented in the questionnaire while being assisted by a medical doctor. Responses were then collected and analyzed, and multivariate logistic regression was used to identify predictors of willingness to use voice technology.

Results

In total, 249 patients (mean age 65.3, SD 13.8 years; 158 [63.5%] men) completed the questionnaire, which showed good repeatability in the validation procedure. Of the 249 total participants, 209 (83.9%) reported high readiness to receive services allowing for remote contact with a cardiologist (176/249, 70.7%) and telemonitoring of vital signs (168/249, 67.5%). The voice conversational agents combined with provider-driven support delivered by phone were shown to be highly anticipated by patients with CVD. The readiness to use telehealth was statistically higher in people with previous difficulties accessing health care (OR 2.920, 95% CI 1.377-6.192) and was most frequent in city residents and individuals reporting a higher education level. The age and sex of the respondents did not impact the intention to use voice technology (P=.20 and P=.50, respectively).

Conclusions

Patients with cardiovascular diseases, including both younger and older individuals, declared high readiness for voice technology.