Remote Patient Monitoring Program for COVID-19 Patients Following Hospital Discharge: A Cross-Sectional Study

A national survey of rheumatology telephone advice line support in the United Kingdom: frontline perspectives

Objectives

Telephone advice lines are a key component of rheumatology services. A national survey of telephone advice line providers was undertaken to explore how this service is currently delivered and the impact on those delivering it to inform providers, policymakers and patients.

Methods

We conducted an online survey between March and September 2023 collecting data on demographics, how advice lines function, governance and the impact on nurses' well-being. Data were analysed using descriptive statistics.

Results

A total of 123 health professionals completed the survey. The majority were rheumatology nurses [n = 118 (96%)], >45 years of age [n = 112 (91%)], band ≥7 [n = 92 (76%)], with 77 (65%) reporting >10 years of experience within rheumatology. Most advice lines operated weekdays only [n = 93 (79%)], with most calls returned within 2 days [n = 81 (66%)], although some callers waited >7 days [n = 19 (15%)]. The number of calls received monthly ranged from 100 to >800, with 46 (37%) responders reporting >500 calls/month. The most common reasons for contacting advice lines were disease activity, pain and medication concerns. For most responders, governance arrangements were unclear [n = 72 (61%)]. Providing advice lines impacted on the well-being of nurses providing the service: 89 (72%) felt anxious 'sometimes to mostly' and 79 (64%) found it 'mostly-always' stressful. A total of 85 (69%) nurses had not received any training to manage advice lines.

Conclusion

Although telephone advice lines are provided by experienced rheumatology nurses, high demand is impacting on well-being. Having designated training could equip nurses with additional skills to manage increased capacity and monitor their own well-being.

An Era of Digital Healthcare-A Comprehensive Review of Sensor Technologies and Telehealth Advancements in Chronic Heart Failure Management

Heart failure (HF) is a multi-faceted, complex clinical syndrome characterized by significant morbidity, high mortality rate, reduced quality of life, and rapidly increasing healthcare costs. A larger proportion of these costs comprise both ambulatory and emergency department visits, as well as hospital admissions. Despite the methods used by telehealth (TH) to improve self-care and quality of life, patient outcomes remain poor. HF management is associated with numerous challenges, such as conflicting evidence from clinical trials, heterogeneity of TH devices, variability in patient inclusion and exclusion criteria, and discrepancies between healthcare systems. A growing body of evidence suggests there is an unmet need for increased individualization of in-hospital management, continuous remote monitoring of patients pre and post-hospital admission, and continuation of treatment post-discharge in order to reduce re-hospitalizations and improve long-term outcomes. This review summarizes the current state-of-the-art for HF and associated novel technologies and advancements in the most frequently used types of TH (implantable sensors), categorizing devices in their preclinical and clinical stage, bench-to-bedside implementation challenges, and future perspectives on remote HF management to improve long-term outcomes of HF patients. The Review also highlights recent advancements in non-invasive remote monitoring technologies demonstrated by a few pilot observational prospective cohort studies.

Transformative Frontiers: A Comprehensive Review of Emerging Technologies in Modern Healthcare

The rapid evolution of emerging technologies in healthcare is reshaping the field of medical practices and patient outcomes, ushering in an era of unprecedented innovation. This narrative review touches upon the transformative impacts of various technologies, including virtual reality (VR), augmented reality (AR), the internet of medical things (IoMT), remote patient monitoring (RPM), financial technology (fintech) integration, cloud migration, and the pivotal role of machine learning (ML). It emphasizes the collaborative impact of these technologies, which is reshaping the healthcare landscape. Virtual reality and AR revolutionize medical training, IoMT extends healthcare boundaries, RPM facilitates proactive care, and fintech integration enhances financial processes. Cloud migration ensures scalable and efficient data management, while ML harnesses algorithms for diagnostic precision and personalized treatment.

The paradoxes of telehealth platforms: what did we learn from the use of telehealth platforms?

This article is an overview and reflection of the findings of an evaluative study conducted on a program called "Techno-Covid Partnership" (TCP) implemented in April 2020 at the Centre Hospitalier de l'Université de Montréal (CHUM) in Montreal, Canada. In the context of the COVID-19 pandemic, the CHUM decided in April 2020 to implement telehealth, virtual care, and telemonitoring platforms and technologies to maintain access to care and reduce the risks of contamination and spread of COVID-19 as well as to protect users of health services and health professionals. Three technological platforms for telehealth and remote care and monitoring have been developed, implemented, and evaluated in real-time within the framework of the TCP program. A cross-sectional study was carried out in which a questionnaire was used and administered to users of telehealth platforms including patients and healthcare professionals. The methods and results of the study have been published previously published. In the completion of the two articles published in this context, in this paper, we briefly recall the context of the study and the method performed. The main focus of the paper is on presenting a critical overview and reflection on the major findings of our evaluation of the use of telehealth platforms from the point of view of patients and health professionals and discuss certain paradoxes i.e., the advantages, challenges, recommendations, and other perspectives that emerged in this study.

Evaluating an Advanced Practice Provider-Managed Coronavirus Disease 2019 Deterioration Program

Background

COVID-19 changed how healthcare systems could provide quality healthcare to patients, safely. An urban healthcare system created an advanced practice provider (APP)-managed continuous remote patient monitoring (cRPM) program.

Methods

A mixed-method study design focusing on the usable and feasible nature of the cRPM program. Both APP-guided interviews and online questionnaires were analyzed.

Results

There was overwhelmingly positive APP feedback utilizing the remote monitoring solution including providing quality healthcare, detecting early clinical deterioration, and desiring to adapt the solution to other acute or chronic diseases.

Implications

Understanding the clinical users' feedback on usability and feasibility of cRPM highlights the significance of rapid clinical assessment, urgent care escalation and provider accessibility.

A systematic review and knowledge mapping on ICT-based remote and automatic COVID-19 patient monitoring and care

BACKGROUND

e-Health has played a crucial role during the COVID-19 pandemic in primary health care. e-Health is the cost-effective and secure use of Information and Communication Technologies (ICTs) to support health and health-related fields. Various stakeholders worldwide use ICTs, including individuals, non-profit organizations, health practitioners, and governments. As a result of the COVID-19 pandemic, ICT has improved the quality of healthcare, the exchange of information, training of healthcare professionals and patients, and facilitated the relationship between patients and healthcare providers. This study systematically reviews the literature on ICT-based automatic and remote monitoring methods, as well as different ICT techniques used in the care of COVID-19-infected patients.

OBJECTIVE

The purpose of this systematic literature review is to identify the e-Health methods, associated ICTs, method implementation strategies, information collection techniques, advantages, and disadvantages of remote and automatic patient monitoring and care in COVID-19 pandemic.

METHODS

The search included primary studies that were published between January 2020 and June 2022 in scientific and electronic databases, such as EBSCOhost, Scopus, ACM, Nature, SpringerLink, IEEE Xplore, MEDLINE, Google Scholar, JMIR, Web of Science, Science Direct, and PubMed. In this review, the findings from the included publications are presented and elaborated according to the identified research questions. Evidence-based systematic reviews and meta-analyses were conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Additionally, we improved the review process using the Rayyan tool and the Scale for the Assessment of Narrative Review Articles (SANRA). Among the eligibility criteria were methodological rigor, conceptual clarity, and useful implementation of ICTs in e-Health for remote and automatic monitoring of COVID-19 patients.

RESULTS

Our initial search identified 664 potential studies; 102 were assessed for eligibility in the pre-final stage and 65 articles were used in the final review with the inclusion and exclusion criteria. The review identified the following eHealth methods-Telemedicine, Mobile Health (mHealth), and Telehealth. The associated ICTs are Wearable Body Sensors, Artificial Intelligence (AI) algorithms, Internet-of-Things, or Internet-of-Medical-Things (IoT or IoMT), Biometric Monitoring Technologies (BioMeTs), and Bluetooth-enabled (BLE) home health monitoring devices. Spatial or positional data, personal and individual health, and wellness data, including vital signs, symptoms, biomedical images and signals, and lifestyle data are examples of information that is managed by ICTs. Different AI and IoT methods have opened new possibilities for automatic and remote patient monitoring with associated advantages and weaknesses. Our findings were represented in a structured manner using a semantic knowledge graph (e.g., ontology model).

CONCLUSIONS

Various e-Health methods, related remote monitoring technologies, different approaches, information categories, the adoption of ICT tools for an automatic remote patient monitoring (RPM), advantages and limitations of RMTs in the COVID-19 case are discussed in this review. The use of e-Health during the COVID-19 pandemic illustrates the constraints and possibilities of using ICTs. ICTs are not merely an external tool to achieve definite remote and automatic health monitoring goals; instead, they are embedded in contexts. Therefore, the importance of the mutual design process between ICT and society during the global health crisis has been observed from a social informatics perspective. A global health crisis can be observed as an information crisis (e.g., insufficient information, unreliable information, and inaccessible information); however, this review shows the influence of ICTs on COVID-19 patients' health monitoring and related information collection techniques.

Home monitoring of coronavirus disease 2019 patients in different phases of disease

PURPOSE OF REVIEW

Various home monitoring programs have emerged through the COVID-19 pandemic in different phases of COVID-19 disease.

RECENT FINDINGS

The prehospital monitoring of COVID-19-positive patients detects early deterioration. Hospital care at home provides early discharge with oxygen to empty hospital beds for other patients. Home monitoring during recovery can be used for rehabilitation and detection of potential relapses. General goals of home monitoring in COVID-19 are early detection of deterioration and prompt escalation of care such as emergency department presentation, medical advice, medication prescription and mental support. Due to the innovations of vaccination and treatment changes, such as dexamethasone and tocilizumab, the challenge for the healthcare system has shifted from large numbers of admitted COVID-19 patients to lower numbers of admitted patients with specific risk profiles (such as immunocompromised). This also changes the field of home monitoring in COVID-19. Efficacy and cost-effectiveness of home monitoring interventions depend on the costs of the intervention (use of devices, apps and medical staff) and the proposed patient group (depending on risk factors and disease severity).

SUMMARY

Patient satisfaction of COVID-19 home monitoring programs was mostly high. Home monitoring programs for COVID-19 should be ready to be re-escalated in case of a new global pandemic.

A Review of the Role of Artificial Intelligence in Healthcare

Artificial intelligence (AI) applications have transformed healthcare. This study is based on a general literature review uncovering the role of AI in healthcare and focuses on the following key aspects: (i) medical imaging and diagnostics, (ii) virtual patient care, (iii) medical research and drug discovery, (iv) patient engagement and compliance, (v) rehabilitation, and (vi) other administrative applications. The impact of AI is observed in detecting clinical conditions in medical imaging and diagnostic services, controlling the outbreak of coronavirus disease 2019 (COVID-19) with early diagnosis, providing virtual patient care using AI-powered tools, managing electronic health records, augmenting patient engagement and compliance with the treatment plan, reducing the administrative workload of healthcare professionals (HCPs), discovering new drugs and vaccines, spotting medical prescription errors, extensive data storage and analysis, and technology-assisted rehabilitation. Nevertheless, this science pitch meets several technical, ethical, and social challenges, including privacy, safety, the right to decide and try, costs, information and consent, access, and efficacy, while integrating AI into healthcare. The governance of AI applications is crucial for patient safety and accountability and for raising HCPs' belief in enhancing acceptance and boosting significant health consequences. Effective governance is a prerequisite to precisely address regulatory, ethical, and trust issues while advancing the acceptance and implementation of AI. Since COVID-19 hit the global health system, the concept of AI has created a revolution in healthcare, and such an uprising could be another step forward to meet future healthcare needs.

Long-COVID-19 in Asymptomatic, Non-Hospitalized, and Hospitalized Populations: A Cross-Sectional Study

A substantial proportion of coronavirus disease 2019 (COVID-19) survivors continue to suffer from long-COVID-19 (LC) symptoms. Our study aimed to determine the risk factors for LC by using a patient population from Northern Cyprus. Subjects who were diagnosed with severe acute respiratory syndrome-2 (SARS-CoV-2) infection in our university hospital were invited and asked to fill in an online questionnaire. Data from 296 survivors who had recovered from COVID-19 infection at least 28 days prior the study was used in the statistical analysis. For determination of risk factors for “ongoing symptomatic COVID-19 (OSC)” and “Post-COVID-19 (PSC)” syndromes, the patient population was further divided into group 1 (Gr1) and group 2 (Gr2), that included survivors who were diagnosed with COVID-19 within 4-12 weeks and at least three months prior the study, respectively. The number of people with post-vaccination SARS-CoV-2 infection was 266 (89.9%). B.1.617.2 (Delta) (41.9%) was the most common SARS-CoV-2 variant responsible for the infections, followed by BA.1 (Omicron) (34.8%), B.1.1.7 (Alpha) (15.5%), and wild-type SARS-CoV-2 (7.8%). One-hundred-and-nineteen volunteers (40.2%) stated an increased frequency of COVID-19-related symptoms and experienced the symptoms in the week prior to the study. Of those, 81 (38.8%) and 38 (43.7%) were from Gr1 and Gr2 groups, respectively. Female gender, chronic illness, and symptomatic status at PCR testing were identified as risk factors for developing OSC syndrome, while only the latter showed a similar association with PSC symptoms. Our results also suggested that ongoing and persistent COVID-19-related symptoms are not influenced by the initial viral cycle threshold (Ct) values of the SARS-CoV-2, SARS-CoV-2 variant as well as vaccination status and type prior to COVID-19. Therefore, strategies other than vaccination are needed to combat the long-term effect of COVID-19, especially after symptomatic SARS-CoV-2 infection, and their possible economic burden on healthcare settings.

Characteristics and outcomes of COVID-19 home monitoring in Saudi Arabia during the second and third waves

Introduction

As severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) spread around the world, patient care was shifted to outpatient care and home monitoring. This paper describes the characteristics and outcomes of patients with coronavirus disease 2019 (COVID-19) treated at home during the second and third waves in Saudi Arabia.

Materials and methods

Descriptive evaluation of the characteristics and outcome of COVID-19-positive cases enrolled in the home monitoring programme.

Results

This study included 14,970 SARS-CoV-2-positive patients (52.6% male). The mean age was 30.8 [standard deviation (SD) 19.9] years. Among the confirmed cases, 14,234 had documented vaccination status; of these, 3943 (27.7%) had not received any doses of COVID-19 vaccine, 1452 (10.2%) had received one dose, 4882 (34.3%) had received two doses, and 3957 (27.8%) had received three doses. The mean number of days in the home monitoring programme was 8.3 (SD 3.5) days. The mean interval from the last vaccine dose until SARS-CoV-2 infection was 116.6 (SD 75.5) days in 7975 patients. The presence of comorbidities was as follows: chronic kidney disease, 340 (2.3%); hypertension, 2569 (17.2%); chronic pulmonary disease, 2539 (17%); smoking, 1711 (11.4%) of 9269 with documented smoking histroy; coronary artery disease, 854 (5.7%); and diabetes mellitus, 1531 (10.3%). The hospitalization rate was 1.8%, and the case fatality rate was 5% of admitted patients, accounting for 0.11% of all cases. The mean age of patients who died was 76.6 (SD 17.7) years, which was higher compared with the mean age of those who survived [30.8 (SD 19.9) years] (P<0.001).

Conclusion

Utilization of a home monitoring programme was effective and safe for patients with COVID-19 who were either asymptomatic or had mild symptoms.

Artificial intelligence technologies and compassion in healthcare: A systematic scoping review

Background

Advances in artificial intelligence (AI) technologies, together with the availability of big data in society, creates uncertainties about how these developments will affect healthcare systems worldwide. Compassion is essential for high-quality healthcare and research shows how prosocial caring behaviors benefit human health and societies. However, the possible association between AI technologies and compassion is under conceptualized and underexplored.

Objectives

The aim of this scoping review is to provide a comprehensive depth and a balanced perspective of the emerging topic of AI technologies and compassion, to inform future research and practice. The review questions were: How is compassion discussed in relation to AI technologies in healthcare? How are AI technologies being used to enhance compassion in healthcare? What are the gaps in current knowledge and unexplored potential? What are the key areas where AI technologies could support compassion in healthcare?

Materials and methods

A systematic scoping review following five steps of Joanna Briggs Institute methodology. Presentation of the scoping review conforms with PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews). Eligibility criteria were defined according to 3 concept constructs (AI technologies, compassion, healthcare) developed from the literature and informed by medical subject headings (MeSH) and key words for the electronic searches. Sources of evidence were Web of Science and PubMed databases, articles published in English language 2011-2022. Articles were screened by title/abstract using inclusion/exclusion criteria. Data extracted (author, date of publication, type of article, aim/context of healthcare, key relevant findings, country) was charted using data tables. Thematic analysis used an inductive-deductive approach to generate code categories from the review questions and the data. A multidisciplinary team assessed themes for resonance and relevance to research and practice.

Results

Searches identified 3,124 articles. A total of 197 were included after screening. The number of articles has increased over 10 years (2011, n = 1 to 2021, n = 47 and from Jan-Aug 2022 n = 35 articles). Overarching themes related to the review questions were: (1) Developments and debates (7 themes) Concerns about AI ethics, healthcare jobs, and loss of empathy; Human-centered design of AI technologies for healthcare; Optimistic speculation AI technologies will address care gaps; Interrogation of what it means to be human and to care; Recognition of future potential for patient monitoring, virtual proximity, and access to healthcare; Calls for curricula development and healthcare professional education; Implementation of AI applications to enhance health and wellbeing of the healthcare workforce. (2) How AI technologies enhance compassion (10 themes) Empathetic awareness; Empathetic response and relational behavior; Communication skills; Health coaching; Therapeutic interventions; Moral development learning; Clinical knowledge and clinical assessment; Healthcare quality assessment; Therapeutic bond and therapeutic alliance; Providing health information and advice. (3) Gaps in knowledge (4 themes) Educational effectiveness of AI-assisted learning; Patient diversity and AI technologies; Implementation of AI technologies in education and practice settings; Safety and clinical effectiveness of AI technologies. (4) Key areas for development (3 themes) Enriching education, learning and clinical practice; Extending healing spaces; Enhancing healing relationships.

Conclusion

There is an association between AI technologies and compassion in healthcare and interest in this association has grown internationally over the last decade. In a range of healthcare contexts, AI technologies are being used to enhance empathetic awareness; empathetic response and relational behavior; communication skills; health coaching; therapeutic interventions; moral development learning; clinical knowledge and clinical assessment; healthcare quality assessment; therapeutic bond and therapeutic alliance; and to provide health information and advice. The findings inform a reconceptualization of compassion as a human-AI system of intelligent caring comprising six elements: (1) Awareness of suffering (e.g., pain, distress, risk, disadvantage); (2) Understanding the suffering (significance, context, rights, responsibilities etc.); (3) Connecting with the suffering (e.g., verbal, physical, signs and symbols); (4) Making a judgment about the suffering (the need to act); (5) Responding with an intention to alleviate the suffering; (6) Attention to the effect and outcomes of the response. These elements can operate at an individual (human or machine) and collective systems level (healthcare organizations or systems) as a cyclical system to alleviate different types of suffering. New and novel approaches to human-AI intelligent caring could enrich education, learning, and clinical practice; extend healing spaces; and enhance healing relationships.

Implications

In a complex adaptive system such as healthcare, human-AI intelligent caring will need to be implemented, not as an ideology, but through strategic choices, incentives, regulation, professional education, and training, as well as through joined up thinking about human-AI intelligent caring. Research funders can encourage research and development into the topic of AI technologies and compassion as a system of human-AI intelligent caring. Educators, technologists, and health professionals can inform themselves about the system of human-AI intelligent caring.

The "Lazio ADVICE" telemedicine platform: First results of general practitioners' usage, facilitators and barriers in the Local Health Authority Roma 1

Background

Telemedical approaches represent a valuable tool for the management of coronavirus disease 2019 patients, allowing daily clinical assessment, monitoring of vital parameters, remote visits, and prescription of treatment or hospitalization in case of clinical worsening. This cross-sectional study aims to evaluate the use, barriers and facilitators of the "Lazio ADVICE" telemedical platform, a regional system for remote assistance for coronavirus disease 2019 patients at home, according to General Practitioners and Family Pediatricians of the Local Health Authority Roma 1, during the coronavirus disease 2019 pandemic.

Methods

An interview-based survey was performed between December 2020 and January 2021. The survey investigated the demographic information of General Practitioner and Family Pediatricians, the knowledge of the platform, frequency of utilization, usefulness, strengths and weaknesses, and hypothesis of future implementation proposed.

Results

We interviewed 214 physicians and 89 (41.6%) were classified as users and 125 (58.4%) as non-users. Older age and working in District 1, 14 and 15 (vs. District 13) significantly reduced the probability of using the platform physician. Among the 89 users, 19 (21.3%) used the platform every day or even several times a day, 40 (44.9%) several times a week but less than one access per day, 30 (33.7%) used the platform several times a month up to one entry per week. Most of them (92.3%) consider the platform useful. Barriers were poor integration with software and work routine (76.4%), and usability issues (53.9%). Among the 125 non-users, 14 (11.2%) didn't know the existence of the platform, 60 (48.0%) never tried it and 51 (40.8%) tried to use it. Reported reasons for the interruption of use were not very user-friendly (45.1%), perceived useless (37.3%), non-optimal functioning (23.5%), and lack of time (19.6%).

Conclusion

The pandemic accelerated the implementation of telemedicine services around Lazio Region, starting a positive and continuous exchange of experiences, activities and best practices among physicians.

Telehealth and COVID-19 Pandemic: An Overview of the Telehealth Use, Advantages, Challenges, and Opportunities during COVID-19 Pandemic

The use of telehealth and digital health platforms has increased during the COVID-19 pandemic due to the implementation of physical distancing measures and restrictions. To address the pandemic threat, telehealth was promptly and extensively developed, implemented, and used to maintain continuity of care offered through multi-purpose technology platforms considered as virtual healthcare facilities. The aim of this paper is to define telehealth and discuss some aspects of its utilization, role, and impact, but also opportunities and future implications particularly during the COVID-19 pandemic. In order to support our reflection and consolidate our viewpoints, numerous bibliographical sources and relevant literature were identified through an electronic keyword search of four databases (PubMed, Web of Science, Google Scholar, and ResearchGate). In this paper, we consider that telehealth to be a very interesting approach which can be effective and affordable for health systems aiming to facilitate access to care, maintain quality and safety of care, and engage patients and health professionals and users of health services. However, we also believe that telehealth faces many challenges, such as the issue of lack of human contact in care, confidentiality, and data security, also accessibility and training in the use of platforms for telehealth. Despite the many challenges it faces, we believe telehealth has enormous potential for strengthening and improving healthcare services. In this paper, we also call for and encourage further studies to build a solid and broad understanding of telehealth challenges with its short-term and long-term clinical, organizational, socio-economic, and ethical impacts.

Recommendations for Successful Implementation of the Use of Vocal Biomarkers for Remote Monitoring of COVID-19 and Long COVID in Clinical Practice and Research

The COVID-19 pandemic accelerated the use of remote patient monitoring in clinical practice or research for safety and emergency reasons, justifying the need for innovative digital health solutions to monitor key parameters or symptoms related to COVID-19 or Long COVID. The use of voice-based technologies, and in particular vocal biomarkers, is a promising approach, voice being a rich, easy-to-collect medium with numerous potential applications for health care, from diagnosis to monitoring. In this viewpoint, we provide an overview of the potential benefits and limitations of using voice to monitor COVID-19, Long COVID, and related symptoms. We then describe an optimal pipeline to bring a vocal biomarker candidate from research to clinical practice and discuss recommendations to achieve such a clinical implementation successfully.

Effect of COVID-19 inpatients with cognitive decline on discharge after the quarantine period: A retrospective cohort study

Background

A new SARS-CoV-2 variant, Omicron, was reported on November 14, 2021, and it altered the COVID-19 epidemic with a different peak timing by region in Japan. Residents in the Hiroshima prefecture, especially the vulnerable elderly, were threatened by this wave in advance of many other prefectures. We evaluated the effect of cognitive decline on discharge extension after the quarantine period.

Methods

Participants of this retrospective cohort study were patients who were admitted to the care unit for COVID-19 treatment at Hiroshima University Hospital between January 1, 2022, and March 1, 2022 (60 days). Our primary outcome was the extended length of stay (LOS) in the hospital after the quarantine period (10 days after onset). A negative binomial regression analysis was performed to assess the extended LOS of patients with cognitive decline, adjusting for age classification, gender, and severity of COVID-19.

Results

The total number of participants was 74. Per the level of cognitive function, there were 56 independent participants, 5 mild declines, and 13 severe declines. For the negative binomial regression analysis, the exponentiated coefficient of mild cognitive decline was 3.05 (95% confidential interval [CI]: 1.43-6.49) and that of severe cognitive decline was 1.95 (95% CI: 1.09-3.53).

Conclusions

Mild cognitive decline and severe cognitive decline elevated the risk of extended LOS after COVID-19 patients finished the quarantine period.

Reconnecting health through innovation

Learning health systems identify appropriate data to improve their performance and population health. The pandemic has shown that a proper response depends on using data from patients' needs, scientific research, hospital capacity, digital innovations, and stakeholder knowledge. Academic health centres play a role in data collection, information synthesis, and decision making supported by digital innovations. The results obtained by an academic centre and network in Quebec have demonstrated the value of integrating these elements during the pandemic and beyond.

Innovating in a Crisis: A Qualitative Evaluation of a Hospital and Google Partnership to Implement a COVID-19 Inpatient Video Monitoring Program

Objective

To describe adaptations necessary for effective use of direct-to-consumer (DTC) cameras in an inpatient setting, from the perspective of health care workers.

Methods

Our qualitative study included semi-structured interviews and focus groups with clinicians, information technology (IT) personnel, and health system leaders affiliated with the Mount Sinai Health System. All participants either worked in a coronavirus disease 2019 (COVID-19) unit with DTC cameras or participated in the camera implementation. Three researchers coded the transcripts independently and met weekly to discuss and resolve discrepancies. Abiding by inductive thematic analysis, coders revised the codebook until they reached saturation. All transcripts were coded in Dedoose using the final codebook.

Results

Frontline clinical staff, IT personnel, and health system leaders (N = 39) participated in individual interviews and focus groups in November 2020–April 2021. Our analysis identified 5 areas for effective DTC camera use: technology, patient monitoring, workflows, interpersonal relationships, and infrastructure. Participants described adaptations created to optimize camera use and opportunities for improvement necessary for sustained use. Non-COVID-19 patients tended to decline participation.

Discussion

Deploying DTC cameras on inpatient units required adaptations in many routine processes. Addressing consent, 2-way communication issues, patient privacy, and messaging about video monitoring could help facilitate a nimble rollout. Implementation and dissemination of inpatient video monitoring using DTC cameras requires input from patients and frontline staff.

Conclusions

Given the resources and time it takes to implement a usable camera solution, other health systems might benefit from creating task forces to investigate their use before the next crisis.

Participant and Research Team Perspectives on the Conduct of a Remote Therapeutic COVID-19 Clinical Trial: A Mixed Methods Approach

Background:

Responding to the need to investigate potential treatments of COVID-19, a research team employed a telehealth platform to determine whether niclosamide, an oral anthelmintic drug that had shown antiviral activity, reduced SARS-CoV-2 shedding and duration of symptoms in patients with mild-to-moderate symptoms of COVID-19. To encourage compliance with patient self-quarantine, this randomized placebo-controlled clinical trial was conducted utilizing a remote telehealth design to complete all study visits, monitor symptoms, and coordinate participant self-collected specimens.

Methods:

A mixed methods approach employing surveys and interviews of trial participants and interviews of research team members was used to collect their experiences with and perspectives on the acceptability of the remote clinical trial design and delivery.

Results:

Of the 67 eligible trial participants invited to take part in a study to evaluate the telehealth platform, 46% (n = 31) completed a post-participation survey. While 97% (n = 30) of respondents had not previously participated in a clinical trial, 77% (n = 24) reported they would consider taking part in a future remote research study. The majority of respondents were moderately or very comfortable (93%) with using the technology.

Conclusions:

The COVID-19 crisis was a call to action to expand understanding of the conduct of remote clinical trials, including the experiences of research participants. Our findings showed that this approach can be both effective for the conduct of research and positive for participants. Further research on the use of telehealth research platforms seems warranted in rural, underserved populations, and remote trials of prevention, screening, and treatment.