A Patient Self-Checkup App for COVID-19: Development and Usage Pattern Analysis

A Digital First Healthcare Approach to Managing Pandemics: A Scoping Review of Pandemic Self-Triage Tools

BACKGROUND

During the COVID-19 pandemic, many patient-facing digital self-triage tools were designed and deployed to alleviate demand for pandemic virus triage in hospitals and doctors' offices by providing a way for people to self-assess health status and get advice on whether to seek care. These tools, provided via websites, apps, or patient portals allow people to answer questions, e.g., about symptoms and contact history, and receive guidance to appropriate care, which might be self-care.

OBJECTIVE

The purpose of this scoping review was to explore the state of literature on digital self-triage tools that direct or advise care for adults during a pandemic, and to explore what has been learned about intended purpose, use, and quality of guidance, tool usability, impact on providers, and ability to forecast health outcomes or care demand.

METHODS

A literature search was conducted in July 2021 using MEDLINE, Embase, Scopus, PsycINFO, CINAHL and Cochrane databases. Using Covidence, 1227 titles and abstracts were screened by two researchers, with 83 reviewed via full text screening. 22 articles met inclusion criteria: they allowed adults to self-assess for pandemic virus and directed to care. Using Microsoft Excel, we extracted and charted the following data: authors, publication year and country, country the tool was used in, whether the tool was integrated into a healthcare system, research question/purpose, direction of care provided, and key findings.

RESULTS

All but two studies reported on tools developed since early 2020 during the COVID-19 pandemic. Studies reported on tools were developed in 17 countries. Direction of care advice included directing to an ER, seek urgent care, contact/see a doctor, be tested, or to stay at home/self-isolate. Only two studies evaluated tool usability. One used 52 use-cases to evaluate quality of advice by tools in four countries, finding advice varied, e.g., tools in the US and UK often advising staying home when clinical assessment was warranted, while tools in Japan and Singapore advised seeking care. No study demonstrated that the tools reduce demand on the health care system, although at least one suggests data can predict demand for care and data allows monitoring public health.

CONCLUSIONS

While self-triage tools developed and used around the world have similarities in directing to care (ER, physician, self-care), they also differ in important ways. Some collect data to predict healthcare demand. Some are for use when concerned about health status; others are intended to be used repeatedly by users to monitor public health. Quality of triage may vary. The high use of such tools during the COVID-19 pandemic suggests research is needed to assess and ensure quality of advice given by self-triage tools, and to assess intended or unintended consequences on public health and health care systems.

CLINICALTRIAL

www.coronabambini.ch: Development and usage of an online decision support tool for paediatric COVID-19-testing in Switzerland: a cross-sectional analysis

OBJECTIVES

To describe the development and usage of www.coronabambini.ch as an example of a paediatric electronic public health application and to explore its potential and limitations in providing information on disease epidemiology and public health policy implementation.

DESIGN

We developed and maintained a non-commercial online decision support tool, www.coronabambini.ch, to translate the Swiss Federal Office of Public Health (FOPH) paediatric (age 0-18 years) COVID-19 guidelines around testing and school/daycare attendance for caregivers, teachers and healthcare personnel. We analysed the online decision tool as well as a voluntary follow-up survey from October 2020 to September 2021 to explore its potential as a surveillance tool for public health policy and epidemiology.

PARTICIPANTS

68 269 users accessed and 52 726 filled out the complete online decision tool. 3% (1399/52 726) filled out a voluntary follow-up. 92% (18 797/20 330) of users were parents.

RESULTS

Certain dynamics of the pandemic and changes in testing strategies were reflected in the data captured by www.coronabambini.ch, for example, in terms of disease epidemiology, gastrointestinal symptoms were reported more frequently in younger age groups (13% (3308/26 180) in children 0-5 years vs 9% (3934/42 089) in children ≥6 years, χ²=184, p≤0.001). As a reflection of public health policy, the proportion of users consulting the tool for a positive contact without symptoms in children 6-12 years increased from 4% (1415/32 215) to 6% (636/9872) after the FOPH loosened testing criteria in this age group, χ²=69, p≤0.001. Adherence to the recommendation was generally high (84% (1131/1352)) but differed by the type of recommendation: 89% (344/385) for 'stay at home and observe', 75% (232/310) for 'school attendance'.

CONCLUSIONS

Usage of www.coronabambini.ch was generally high in areas where it was developed and promoted. Certain patterns in epidemiology and adherence to public health policy could be depicted but selection bias was difficult to measure showing the potential and challenges of digital decision support as public health tools.

Self-care for coronavirus disease through electronic health technologies: A scoping review

Background and Aims

Considering the rapid spread and transmission of COVID-19 and its high mortality rate, self-care practices are of special importance during this pandemic to prevent and control the spread of the virus. In this regard, electronic health systems can play a major role in improving self-care practices related to coronavirus disease. This study aimed to review the electronic health technologies used in each of the constituent elements of the self-care (self-care maintenance, self-care monitoring, and self-care management) during the COVID-19 pandemic.

Methods

This scoping review was conducted based on Arksey and O'Malley's framework. In this study, the specific keywords related to "electronic health," "self-care," and "COVID-19" were searched on PubMed, Web of Science, Scopus, and Google.

Results

Of the 47 articles reviewed, most articles (27 articles) were about self-care monitoring and aimed to monitor the vital signs of patients. The results showed that the use of electronic health tools mainly focuses on training in the control and prevention of coronavirus disease during this pandemic, in the field of self-care maintenance, and medication management, communication, and consultation with healthcare providers, in the field of self-care management. Moreover, the most commonly used electronic health technologies were mobile web applications, smart vital signs monitoring devices, and social networks, respectively.

Conclusion

The study findings suggested that the use of electronic health technologies, such as mobile web applications and social networks, can effectively improve self-care practices for coronavirus disease. In addition, such technologies can be applied by health policymakers and disease control and prevention centers to better manage the COVID-19 pandemic.

The medical and societal impact of big data analytics and artificial intelligence applications in combating pandemics: A review focused on Covid-19

With Covid-19 impacting communities in different ways, research has increasingly turned to big data analytics (BDA) and artificial intelligence (AI) tools to track and monitor the virus's spread and its effect on humanity and the global economy. The purpose of this study is to conduct an in-depth literature review to identify how BDA and AI were involved in the management of Covid-19 (while considering diversity, equity, and inclusion (DEI)). The rigorous search resulted in a portfolio of 607 articles, retrieved from the Web of Science database, where content analysis has been conducted. This study identifies the BDA and AI applications developed to deal with the initial Covid-19 outbreak and the containment of the pandemic, along with their benefits for the social good. Moreover, this study reveals the DEI challenges related to these applications, ways to mitigate the concerns, and how to develop viable techniques to deal with similar crises in the future. The article pool recognized the high presence of machine learning (ML) and the role of mobile technology, social media and telemedicine in the use of BDA and AI during Covid-19. This study offers a collective insight into many of the key issues and underlying complexities affecting public health and society from Covid-19, and the solutions offered from information systems and technological perspectives.

Validation of Machine Learning Models to Predict Adverse Outcomes in Patients with COVID-19: A Prospective Pilot Study

PURPOSE

We previously developed learning models for predicting the need for intensive care and oxygen among patients with coronavirus disease (COVID-19). Here, we aimed to prospectively validate the accuracy of these models.

MATERIALS AND METHODS

Probabilities of the need for intensive care [intensive care unit (ICU) score] and oxygen (oxygen score) were calculated from information provided by hospitalized COVID-19 patients (n=44) via a web-based application. The performance of baseline scores to predict 30-day outcomes was assessed.

RESULTS

Among 44 patients, 5 and 15 patients needed intensive care and oxygen, respectively. The area under the curve of ICU score and oxygen score to predict 30-day outcomes were 0.774 [95% confidence interval (CI): 0.614-0.934] and 0.728 (95% CI: 0.559-0.898), respectively. The ICU scores of patients needing intensive care increased daily by 0.71 points (95% CI: 0.20-1.22) after hospitalization and by 0.85 points (95% CI: 0.36-1.35) after symptom onset, which were significantly different from those in individuals not needing intensive care (p=0.002 and <0.001, respectively). Trends in daily oxygen scores overall were not markedly different; however, when the scores were evaluated within <7 days after symptom onset, the patients needing oxygen showed a higher daily increase in oxygen scores [1.81 (95% CI: 0.48-3.14) vs. -0.28 (95% CI: 1.00-0.43), p=0.007].

CONCLUSION

Our machine learning models showed good performance for predicting the outcomes of COVID-19 patients and could thus be useful for patient triage and monitoring.

Innovative Use of a Mobile Web Application to Remotely Monitor Nonhospitalized Patients with COVID-19

Introduction: Most patients with COVID-19 do not require hospitalization but may need close monitoring, which can strain primary care practices. Our objective was to describe the implementation of a mobile web application to monitor COVID-19 signs and symptoms among nonhospitalized primary care patients and to assess the feasibility and acceptability of the application. Study Design: Retrospective analysis of (1) mobile web application data from March through December 2020 and (2) cross-sectional surveys administered in June 2020. Materials and Methods: We enrolled nonhospitalized patients and staff from nine New England primary care practices across 29 sites. Outcomes included feasibility and acceptability of the application as measured by the proportion of texts that resulted in a response, proportion of patients who agreed using the application was easy, and proportion of practice staff who agreed the application reduced outreach burden and that they would recommend use. Results: Five thousand five hundred thirty-two patients used the mobile web application, with 26,466 total responses. Overall, 78% of the daily texts resulted in a response from patients. Most patients agreed that responding to texts was easy (95%) and that they would be willing to participate in other texting programs (78%). Most staff agreed that the program reduced burden of outreach (94%) and that they would recommend use to other practices (100%). Conclusions: Use of a COVID-19 symptom tracking application was feasible and acceptable to patients and primary care practice staff. Outpatient practices should consider use of mobile web applications to monitor nonhospitalized patients with other acute illnesses.

Telehealth-Based Services During the COVID-19 Pandemic: A Systematic Review of Features and Challenges

Background: As an ever-growing popular service, telehealth catered for better access to high-quality healthcare services. It is more valuable and cost-effective, particularly in the middle of the current COVID-19 pandemic. Accordingly, this study aimed to systematically review the features and challenges of telehealth-based services developed to support COVID-19 patients and healthcare providers. Methods: A comprehensive search was done for the English language and peer-reviewed articles published until November 2020 using PubMed and Scopus electronic databases. In this review paper, only studies focusing on the telehealth-based service to support COVID-19 patients and healthcare providers were included. The first author's name, publication year, country of the research, study objectives, outcomes, function type including screening, triage, prevention, diagnosis, treatment or follow-up, target population, media, communication type, guideline-based design, main findings, and challenges were extracted, classified, and tabulated. Results: Of the 5,005 studies identified initially, 64 met the eligibility criteria. The studies came from 18 countries. Most of them were conducted in the United States and China. Phone calls, mobile applications, videoconferencing or video calls, emails, websites, text messages, mixed-reality, and teleradiology software were used as the media for communication. The majority of studies used a synchronous communication. The articles addressed the prevention, screening, triage, diagnosis, treatment, and follow-up aspects of COVID-19 which the most common purpose was the patients' follow-up (34/64, 53%). Thirteen group barriers were identified in the literature, which technology acceptance and user adoption, concerns about the adequacy and accuracy of subjective patient assessment, and technical issues were the most frequent ones. Conclusion: This review revealed the usefulness of telehealth-based services during the COVID-19 outbreak and beyond. The features and challenges identified through the literature can be helpful for a better understanding of current telehealth approaches and pointed out the need for clear guidelines, scientific evidence, and innovative policies to implement successful telehealth projects.