Empowering Patients and Transforming Healthcare in the Post-COVID-19 Era: The Role of Digital and Wearable Technologies.

The COVID-19 pandemic has dramatically impacted the global healthcare system, revealing critical gaps in our capacity to provide efficient and effective care to patients, particularly those with chronic diseases [...].

The Accuracy of Wearable Photoplethysmography Sensors for Telehealth Monitoring: A Scoping Review.

Background and Objectives: Photoplethysmography (PPG) sensors have been increasingly used for remote patient monitoring, especially during the COVID-19 pandemic, for the management of chronic diseases and neurological disorders. There is an urgent need to evaluate the accuracy of these devices. This scoping review considers the latest applications of wearable PPG sensors with a focus on studies that used wearable PPG sensors to monitor various health parameters. The primary objective is to report the accuracy of the PPG sensors in both real-world and clinical settings. Methods: This scoping review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). Studies were identified by querying the Medline, Embase, IEEE, and CINAHL databases. The goal was to capture eligible studies that used PPG sensors to monitor various health parameters for populations with a minimum of 30 participants, with at least some of the population having relevant health issues. A total of 2,996 articles were screened and 28 are included in this review. Results: The health parameters and disorders identified and investigated in this study include heart rate and heart rate variability, atrial fibrillation, blood pressure (BP), obstructive sleep apnea, blood glucose, heart failure, and respiratory rate. An overview of the algorithms used, and their limitations is provided. Conclusion: Some of the barriers identified in evaluating the accuracy of multiple types of wearable devices include the absence of reporting standard accuracy metrics and a general paucity of studies with large subject size in real-world settings, especially for parameters such as BP.

Accelerating digital health literacy for the treatment of growth disorders: The impact of a massive open online course.

Background: Growth hormone deficiency (GHD) is a rare disorder characterized by inadequate secretion of growth hormone (GH) from the anterior pituitary gland. One of the challenges in optimizing GH therapy is improving adherence. Using digital interventions may overcome barriers to optimum treatment delivery. Massive open online courses (MOOCs), first introduced in 2008, are courses made available over the internet without charge to a large number of people. Here, we describe a MOOC aiming to improve digital health literacy among healthcare professionals managing patients with GHD. Based on pre- and post-course assessments, we evaluate the improvement in participants' knowledge upon completion of the MOOC. Methods: The MOOC entitled 'Telemedicine: Tools to Support Growth Disorders in a Post-COVID Era' was launched in 2021. It was designed to cover 4 weeks of online learning with an expected commitment of 2 h per week, and with two courses running per year. Learners' knowledge was assessed using pre- and post-course surveys via the FutureLearn platform. Results: Out of 219 learners enrolled in the MOOC, 31 completed both the pre- and post-course assessments. Of the evaluated learners, 74% showed improved scores in the post-course assessment, resulting in a mean score increase of 21.3%. No learner achieved 100% in the pre-course assessment, compared with 12 learners (40%) who achieved 100% in the post-course assessment. The highest score increase comparing the pre- and the post-course assessments was 40%, observed in 16% of learners. There was a statistically significant improvement in post-course assessment scores from 58.1 ± 18.9% to 72.6 ± 22.4% reflecting an improvement of 14.5% (p < 0.0005) compared to the pre-course assessment. Conclusion: This "first-of-its-kind" MOOC can improve digital health literacy in the management of growth disorders. This is a crucial step toward improving the digital capability and confidence of healthcare providers and users, and to prepare them for the technological innovations in the field of growth disorders and growth hormone therapy, with the aim of improving patient care and experience. MOOCs provide an innovative, scalable and ubiquitous solution to train large numbers of healthcare professionals in limited resource settings.

A scoping review to assess the effects of virtual reality in medical education and clinical care

Due to the challenges and restrictions posed by COVID-19 pandemic, technology and digital solutions played an important role in the rendering of necessary healthcare services, notably in medical education and clinical care. The aim of this scoping review was to analyze and sum up the most recent developments in Virtual Reality (VR) use for therapeutic care and medical education, with a focus on training medical students and patients. We identified 3743 studies, of which 28 were ultimately selected for the review. The search strategy followed the most recent Preferred Reporting Items for Systematic Reviews and Meta-Analysis for scoping review (PRISMA-ScR) guidelines. 11 studies (39.3%) in the field of medical education assessed different domains, such as knowledge, skills, attitudes, confidence, self-efficacy, and empathy. 17 studies (60.7%) focused on clinical care, particularly in the areas of mental health, and rehabilitation. Among these, 13 studies also investigated user experiences and feasibility in addition to clinical outcomes. Overall, the findings of our review reported considerable improvements in terms of medical education and clinical care. VR systems were also found to be safe, engaging, and beneficial by the studies' participants. There were huge variations in studies with respect to the study designs, VR contents, devices, evaluation methods, and treatment periods. In the future, studies may focus on creating definitive guidelines that can help in improving patient care further. Hence, there is an urgent need for researchers to collaborate with the VR industry and healthcare professionals to foster a better understanding of contents and simulation development.

Measuring the Burden of Infodemics: Summary of the Methods and Results of the Fifth WHO Infodemic Management Conference.

Background: An infodemic is excess information, including false or misleading information, that spreads in digital and physical environments during a public health emergency. The COVID-19 pandemic has been accompanied by an unprecedented global infodemic that has led to confusion about the benefits of medical and public health interventions, with substantial impact on risk-taking and health-seeking behaviors, eroding trust in health authorities and compromising the effectiveness of public health responses and policies. Standardized measures are needed to quantify the harmful impacts of the infodemic in a systematic and methodologically robust manner, as well as harmonizing highly divergent approaches currently explored for this purpose. This can serve as a foundation for a systematic, evidence-based approach to monitoring, identifying, and mitigating future infodemic harms in emergency preparedness and prevention. Objective: In this paper, we summarize the Fifth World Health Organization (WHO) Infodemic Management Conference structure, proceedings, outcomes, and proposed actions seeking to identify the interdisciplinary approaches and frameworks needed to enable the measurement of the burden of infodemics. Methods: An iterative human-centered design (HCD) approach and concept mapping were used to facilitate focused discussions and allow for the generation of actionable outcomes and recommendations. The discussions included 86 participants representing diverse scientific disciplines and health authorities from 28 countries across all WHO regions, along with observers from civil society and global public health-implementing partners. A thematic map capturing the concepts matching the key contributing factors to the public health burden of infodemics was used throughout the conference to frame and contextualize discussions. Five key areas for immediate action were identified. Results: The 5 key areas for the development of metrics to assess the burden of infodemics and associated interventions included (1) developing standardized definitions and ensuring the adoption thereof; (2) improving the map of concepts influencing the burden of infodemics; (3) conducting a review of evidence, tools, and data sources; (4) setting up a technical working group; and (5) addressing immediate priorities for postpandemic recovery and resilience building. The summary report consolidated group input toward a common vocabulary with standardized terms, concepts, study designs, measures, and tools to estimate the burden of infodemics and the effectiveness of infodemic management interventions. Conclusions: Standardizing measurement is the basis for documenting the burden of infodemics on health systems and population health during emergencies. Investment is needed into the development of practical, affordable, evidence-based, and systematic methods that are legally and ethically balanced for monitoring infodemics; generating diagnostics, infodemic insights, and recommendations; and developing interventions, action-oriented guidance, policies, support options, mechanisms, and tools for infodemic managers and emergency program managers.

A scoping review to assess the effects of virtual reality in medical education and clinical care.

Due to the challenges and restrictions posed by COVID-19 pandemic, technology and digital solutions played an important role in the rendering of necessary healthcare services, notably in medical education and clinical care. The aim of this scoping review was to analyze and sum up the most recent developments in Virtual Reality (VR) use for therapeutic care and medical education, with a focus on training medical students and patients. We identified 3743 studies, of which 28 were ultimately selected for the review. The search strategy followed the most recent Preferred Reporting Items for Systematic Reviews and Meta-Analysis for scoping review (PRISMA-ScR) guidelines. 11 studies (39.3%) in the field of medical education assessed different domains, such as knowledge, skills, attitudes, confidence, self-efficacy, and empathy. 17 studies (60.7%) focused on clinical care, particularly in the areas of mental health, and rehabilitation. Among these, 13 studies also investigated user experiences and feasibility in addition to clinical outcomes. Overall, the findings of our review reported considerable improvements in terms of medical education and clinical care. VR systems were also found to be safe, engaging, and beneficial by the studies' participants. There were huge variations in studies with respect to the study designs, VR contents, devices, evaluation methods, and treatment periods. In the future, studies may focus on creating definitive guidelines that can help in improving patient care further. Hence, there is an urgent need for researchers to collaborate with the VR industry and healthcare professionals to foster a better understanding of contents and simulation development.

A Scoping Review and a Taxonomy to Assess the Impact of Mobile Apps on Cancer Care Management.

Mobile Health (mHealth) has a great potential to enhance the self-management of cancer patients and survivors. Our study aimed to perform a scoping review to evaluate the impact and trends of mobile application-based interventions on adherence and their effects on health outcomes among the cancer population. In addition, we aimed to develop a taxonomy of mobile-app-based interventions to assist app developers and healthcare researchers in creating future mHealth cancer care solutions. Relevant articles were screened from the online databases PubMed, EMBASE, and Scopus, spanning the time period from 1 January 2016 to 31 December 2022. Of the 4135 articles initially identified, 55 were finally selected for the review. In the selected studies, breast cancer was the focus of 20 studies (36%), while mixed cancers were the subject of 23 studies (42%). The studies revealed that the usage rate of mHealth was over 80% in 41 of the 55 studies, with factors such as guided supervision, personalized suggestions, theoretical intervention foundations, and wearable technology enhancing adherence and efficacy. However, cancer progression, technical challenges, and unfamiliarity with devices were common factors that led to dropouts. We also proposed a taxonomy based on diverse theoretical foundations of mHealth interventions, delivery methods, psycho-educational programs, and social platforms. We suggest that future research should investigate, improve, and verify this taxonomy classification to enhance the design and efficacy of mHealth interventions.

Virtual reality enhancing medical education and practice: Brief communication.

The COVID-19 pandemic has become a major cause of rapid globalization and digitization of educational institutions, including medical education. The adaptation to digital technologies is the purpose of best education and training practices in the development of the academic medical curriculum. Virtual reality (VR) is embraced by the 3D environment and network resources which allow the expansion of VR from the entertainment industry to the education industry. This brief communication explains our understanding and the challenges in adopting VR technologies for medical training at an academic medical center. Advancement in VR technology assists medical institutes to strategize for the further development of medical training and education. There is a timely need for persistence to make the VR content accessible widely and open source. There is an urgent need for collaboration of medical institutes and technology industries on the development of education-related VR content and simulations.

A Scoping Review to Assess Adherence to and Clinical Outcomes of Wearable Devices in the Cancer Population.

The use of wearable devices (WDs) in healthcare monitoring and management has attracted increasing attention. A major problem is patients' adherence and acceptance of WDs given that they are already experiencing a disease burden and treatment side effects. This scoping review explored the use of wrist-worn devices in the cancer population, with a special focus on adherence and clinical outcomes. Relevant articles focusing on the use of WDs in cancer care management were retrieved from PubMed, Scopus, and Embase from 1 January 2017 to 3 March 2022. Studies were independently screened and relevant information was extracted. We identified 752 studies, of which 38 met our inclusion criteria. Studies focused on mixed, breast, colorectal, lung, gastric, urothelial, skin, liver, and blood cancers. Adherence to WDs varied from 60% to 100%. The highest adherence was reported in the 12-week studies. Most studies focused on physical activity, sleep analysis, and heart vital signs. Of the 10 studies that described patient-reported outcomes using questionnaires and personal interviews, 8 indicated a positive correlation between the patient-reported and wearable outcomes. The definitions of the outcome measures and adherence varied across the studies. A better understanding of the intervention standards in terms of the clinical outcomes could improve adherence to wearables.

Deep-Learning Approach to Predict Survival Outcomes Using Wearable Actigraphy Device Among End-Stage Cancer Patients.

Survival prediction is highly valued in end-of-life care clinical practice, and patient performance status evaluation stands as a predominant component in survival prognostication. While current performance status evaluation tools are limited to their subjective nature, the advent of wearable technology enables continual recordings of patients' activity and has the potential to measure performance status objectively. We hypothesize that wristband actigraphy monitoring devices can predict in-hospital death of end-stage cancer patients during the time of their hospital admissions. The objective of this study was to train and validate a long short-term memory (LSTM) deep-learning prediction model based on activity data of wearable actigraphy devices. The study recruited 60 end-stage cancer patients in a hospice care unit, with 28 deaths and 32 discharged in stable condition at the end of their hospital stay. The standard Karnofsky Performance Status score had an overall prognostic accuracy of 0.83. The LSTM prediction model based on patients' continual actigraphy monitoring had an overall prognostic accuracy of 0.83. Furthermore, the model performance improved with longer input data length up to 48 h. In conclusion, our research suggests the potential feasibility of wristband actigraphy to predict end-of-life admission outcomes in palliative care for end-stage cancer patients. Clinical Trial Registration: The study protocol was registered on ClinicalTrials.gov (ID: NCT04883879).

COVID-19 infodemic and digital health literacy in vulnerable populations: A scoping review.

BACKGROUND: People from lower and middle socioeconomic classes and vulnerable populations are among the worst affected by the COVID-19 pandemic, thus exacerbating disparities and the digital divide. OBJECTIVE: To draw a portrait of e-services as a digital approach to support digital health literacy in vulnerable populations amid the COVID-19 infodemic, and identify the barriers and facilitators for their implementation. METHODS: A scoping review was performed to gather published literature with a broad range of study designs and grey literature without exclusions based on country of publication. A search was created in Medline (Ovid) in March 2021 and translated to Medline, PsycINFO, Scopus and CINAHL with Full Text (EBSCOhost). The combined literature search generated 819 manuscripts. To be included, manuscripts had to be written in English, and present information on digital intervention(s) (e.g. social media) used to enable or increase digital health literacy among vulnerable populations during the COVID-19 pandemic (e.g. older adults, Indigenous people living on reserve). RESULTS: Five articles were included in the study. Various digital health literacy-enabling e-services have been implemented in different vulnerable populations. Identified e-services aimed to increase disease knowledge, digital health literacy and social media usage, help in coping with changes in routines and practices, decrease fear and anxiety, increase digital knowledge and skills, decrease health literacy barriers and increase technology acceptance in specific groups. Many facilitators of digital health literacy-enabling e-services implementation were identified in expectant mothers and their families, older adults and people with low-income. Barriers such as low literacy limited to no knowledge about the viruses, medium of contamination, treatment options played an important role in distracting and believing in misinformation and disinformation. Poor health literacy was the only barrier found, which may hinder the understanding of individual health needs, illness processes and treatments for people with HIV/AIDS. CONCLUSIONS: The literature on the topic is scarce, sparse and immature. We did not find any literature on digital health literacy in Indigenous people, though we targeted this vulnerable population. Although only a few papers were included, two types of health conditions were covered by the literature on digital health literacy-enabling e-services, namely chronic conditions and conditions that are new to the patients. Digital health literacy can help improve prevention and adherence to a healthy lifestyle, improve capacity building and enable users to take the best advantage of the options available, thus strengthening the patient's involvement in health decisions and empowerment, and finally improving health outcomes. Therefore, there is an urgent need to pursue research on digital health literacy and develop digital platforms to help solve current and future COVID-19-related health needs.

Information Flow and Data Gaps in COVID-19 Recording and Reporting at National and Provincial Levels in Indonesia.

Epidemiological surveillance is an essential component of public health practice especially during infectious disease outbreaks. It is critical to offer transparent epidemiological information in a rigorous manner at different regional levels in countries for managing the outbreak situations. The objectives of this research are to better understand the information flow of COVID-19 health monitoring systems and to determine the data gaps of COVID-19 incidence at the national and provincial levels in Indonesia. COVID-19 information flow was researched using government websites at the national and various provincial levels. To find the disparities, we assessed the number of cases reported at both levels at the same time and displayed the absolute and relative differences. The findings revealed that out of a total of 34 provinces in Indonesia, data differences were seen in 25 (73.52%) provinces in terms of positive cases, 31 (91.18%) provinces in terms of cured cases, and 28 (82.35%) provinces of the number of deaths. Our results showed a pressing need for high-quality, transparent, and timely information. The integration of COVID-19 data in Indonesia has not been optimal, implying that the reported COVID-19 incidence rate may be biased or delayed. COVID-19 incidents must be better monitored to disrupt the disease's transmission chain.

Using artificial intelligence-based models to predict the risk of mucormycosis among COVID-19 survivors: An experience from a public hospital in India.

INTRODUCTION: India reported a severe public health challenge not only due to the COVID-19 outbreak but also the increasing number of associated mucormycosis cases since 2021.This study aimed at developing artificial intelligence based models to predict the risk of mucormycosis among the patients at the time of discharge from hospital. METHODS: The dataset included of 1229 COVID-19 positive patients, and additional 214 inpatients, COVID-19 positive as well as infected with mucormycosis. We used logistic regression, decision tree and random forest and the extreme gradient boosting algorithm. All our models were evaluated with 5-fold validation to derive a reliable estimate of the model error. RESULTS: The logistic regression, XGBoost and random forest performed equally well with AUROC 95.0, 94.0, and 94.0 respectively. The best accuracy and precision (PPV) were 0.91 ± 0.026 and 0.67 ± 0.0526, respectively achieved by XGBoost, followed by logistic regression. This study also determined top five variables namely obesity, anosmia, de novo diabetes, myalgia, and nasal discharge, which showed positive impact towards the risk of mucormycosis. CONCLUSION: The developed model has the potential to predict the patients at high risk and thus, consequently initiating preventive care or aiding in early detection of mucormycosis infection. Thus, this study, holds potential for early treatment and better management of patients suffering from COVID-19 associated mucormycosis.

Telemedicine in Your Pocket: An Alternative Teleconsultation Tool in a Pandemic and in Resource-Poor Settings.

Introduction: Owing to the coronavirus disease 2019 (COVID-19) pandemic, digitalization is booming in all sectors, including health care. This study provides evidence of using a social networking mobile app as a telemedicine tool during the pandemic in India. Methods: The data include telemedicine conversations of 318 COVID-19 patients who were consulted over WhatsApp during the period March 31 to April 16, 2021, and monitored during a quarantine period of 17 days. Results: In total, 2,089 consultations were made by these patients during the study period. Diagnostic reports and recommendations were suggested through WhatsApp 74 times, and 30 patients were advised to admit themselves to the hospital due to increasing symptom severity. Conclusions: WhatsApp efficiently helped remotely manage hundreds of patients, thereby avoiding unnecessary travel to hospitals. Future study implies the need to acquire information on patient satisfaction during the teleconsultations and further encourage applications of commonly used social networking apps as alternative tools for consultations during a pandemic situation.

The Pandemic, Infodemic, and People's Resilience in India: Viewpoint.

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused widespread fear and stress. The pandemic has affected everyone, everywhere, and created systemic inequities, leaving no one behind. In India alone, more than 34,094,373 confirmed COVID-19 cases and 452,454 related deaths have been reported as of October 19, 2021. Around May 2021, the daily number of new COVID-19 cases crossed the 400,000 mark, seriously hampering the health care system. Despite the devastating situation, the public response was seen through their efforts to come forward with innovative ideas for potential ways to combat the pandemic, for instance, dealing with the shortage of oxygen cylinders and hospital bed availability. With increasing COVID-19 vaccination rates since September 2021, along with the diminishing number of daily new cases, the country is conducting preventive and preparatory measures for the third wave. In this article, we propose the pivotal role of public participation and digital solutions to re-establish our society and describe how Sustainable Development Goals (SDGs) can support eHealth initiatives and mitigate infodemics to tackle a postpandemic situation. This viewpoint reflects that the COVID-19 pandemic has featured a need to bring together research findings across disciplines, build greater coherence within the field, and be a driving force for multi-sectoral, cross-disciplinary collaboration. The article also highlights the various needs to develop digital solutions that can be applied to pandemic situations and be reprocessed to focus on other SDGs. Promoting the use of digital health care solutions to implement preventive measures can be enhanced by public empowerment and engagement. Wearable technologies can be efficiently used for remote monitoring or home-based care for patients with chronic conditions. Furthermore, the development and implementation of informational tools can aid the improvement of well-being and dissolve panic-ridden behaviors contributing toward infodemics. Thus, a call to action for an observatory of digital health initiatives on COVID-19 is required to share the main conclusions and lessons learned in terms of resilience, crisis mitigation, and preparedness.

Predicting severe outcomes in Covid-19 related illness using only patient demographics, comorbidities and symptoms.

OBJECTIVE: Development of a risk-stratification model to predict severe Covid-19 related illness, using only presenting symptoms, comorbidities and demographic data. MATERIALS AND METHODS: We performed a case-control study with cases being those with severe disease, defined as ICU admission, mechanical ventilation, death or discharge to hospice, and controls being those with non-severe disease. Predictor variables included patient demographics, symptoms and past medical history. Participants were 556 patients with laboratory confirmed Covid-19 and were included consecutively after presenting to the emergency department at a tertiary care center from March 1, 2020 to April 21, 2020 RESULTS: Most common symptoms included cough (82%), dyspnea (75%), and fever/chills (77%), with 96% reporting at least one of these. Multivariable logistic regression analysis found that increasing age (adjusted odds ratio [OR], 1.05; 95% confidence interval [CI], 1.03-1.06), dyspnea (OR, 2.56; 95% CI: 1.51-4.33), male sex (OR, 1.70; 95% CI: 1.10-2.64), immunocompromised status (OR, 2.22; 95% CI: 1.17-4.16) and CKD (OR, 1.76; 95% CI: 1.01-3.06) were significant predictors of severe Covid-19 infection. Hyperlipidemia was found to be negatively associated with severe disease (OR, 0.54; 95% CI: 0.33-0.90). A predictive equation based on these variables demonstrated fair ability to discriminate severe vs non-severe outcomes using only this historical information (AUC: 0.76). CONCLUSIONS: Severe Covid-19 illness can be predicted using data that could be obtained from a remote screening. With validation, this model could possibly be used for remote triage to prioritize evaluation based on susceptibility to severe disease while avoiding unnecessary waiting room exposure.

COVID-19 preventive measures showing an unintended decline in infectious diseases in Taiwan.

Most of the communicable diseases have contact, airborne and/or droplet mode of transsmission. Following the outbreak of COVID-19, the Taiwan government implemented the use of masks and sanitizer, as well as other preventive measures like social distancing for prevention. This public response likely contributed significantly to the decline in the outbreak of other infectious diseases.