Digital health during COVID-19: lessons from operationalising new models of care in ophthalmology

Development, Feasibility, and Acceptability of the Electronic Patient Benefit Index for Psoriasis in Clinical Practice: Mixed Methods Study

BACKGROUND

Patient-reported outcomes are relevant in clinical practice showing patient benefits, supporting clinicians' decision-making, and contributing to the delivery of high standards of care. Digital monitoring of patient-reported outcomes is still rare. The Patient Benefit Index (PBI) measures benefits and goals from patients' views and may be relevant for regular documentation and shared decision-making.

OBJECTIVE

This study aimed to develop electronic versions of the PBI to examine their feasibility and acceptability in clinical practice for patients with psoriasis.

METHODS

We developed an app and a web version of the existing, valid PBI using focus groups and cognitive debriefings with patients before conducting a quantitative survey on its feasibility and acceptability. Conduction took part in an outpatient dermatology care unit in Germany. Descriptive and subgroup analyses were conducted.

RESULTS

A total of 139 patients completed the electronic PBIs (ePBIs) and took part in the survey. The ePBI was understandable (n=129-137, 92.8%-98.6%) and feasible, for example, easy to read (n=135, 97.1%) and simple to handle (n=137, 98.5%). Acceptability was also high, for example, patients can imagine using and discussing the ePBI data in practice (n=91, 65.5%) and documenting it regularly (n=88, 63.3%). They believe it could support treatment decisions (n=118, 84.9%) and improve communication with their physician (n=112, 81.3%). They can imagine filling in electronic questionnaires regularly (n=118, 84.9%), even preferring electronic over paper versions (n=113, 81.2%). Older and less educated people show less feasibility, but the latter expected the relationship with their physician to improve and would be more willing to invest time or effort.

CONCLUSIONS

The app and web version of the PBI are usable and acceptable for patients offering comprehensive documentation and patient participation in practice. An implementation strategy should consider patients' needs, barriers, and facilitators but also physicians' attitudes and requirements from the health care system.

Exploring the uses of digital health in palliative care in Southeast Asia

BACKGROUND

This integrative review explores the use of digital health technologies in palliative care within Southeast Asia. Despite extensive documentation of digital health in palliative care in Western nations, its application in Southeast Asia remains underdeveloped.

METHOD

The review includes a total of four papers meeting the eligibility criteria.

FINDINGS

The findings reveal limited studies of digital health adoption in palliative care. Key technologies include mobile health applications, electronic health records and telemedicine platforms. Challenges, such as health inequities, data security and the need for technology validation were identified. The review underscores the necessity for region-specific research to address these challenges and improve the integration of digital health in palliative care.

CONCLUSION

This study highlights the potential of digital health to enhance palliative care delivery and patient outcomes in Southeast Asia, advocating for increased adoption and tailored implementation strategies.

eHealth Literacy and the Use of NHS 111 Online Urgent Care Service in England: Cross-Sectional Survey

BACKGROUND

Many health care systems have used digital technologies to support care delivery, a trend amplified by the COVID-19 pandemic. "Digital first" may exacerbate health inequalities due to variations in eHealth literacy. The relationship between eHealth literacy and web-based urgent care service use is unknown.

OBJECTIVE

This study aims to measure the association between eHealth literacy and the use of NHS (National Health Service) 111 online urgent care service.

METHODS

A cross-sectional sequential convenience sample survey was conducted with 2754 adults (October 2020-July 2021) from primary, urgent, or emergency care; third sector organizations; and the NHS 111 online website. The survey included the eHealth Literacy Questionnaire (eHLQ), questions about use, preferences for using NHS 111 online, and sociodemographic characteristics.

RESULTS

Across almost all dimensions of the eHLQ, NHS 111 online users had higher mean digital literacy scores than nonusers (P<.001). Four eHLQ dimensions were significant predictors of use, and the most highly significant dimensions were eHLQ1 (using technology to process health information) and eHLQ3 (ability to actively engage with digital services), with odds ratios (ORs) of 1.86 (95% CI 1.46-2.38) and 1.51 (95% CI 1.22-1.88), respectively. Respondents reporting a long-term health condition had lower eHLQ scores. People younger than 25 years (OR 3.24, 95% CI 1.87-5.62) and those with formal qualifications (OR 0.74, 95% CI 0.55-0.99) were more likely to use NHS 111 online. Users and nonusers were likely to use NHS 111 online for a range of symptoms, including chest pain symptoms (n=1743, 70.4%) or for illness in children (n=1117, 79%). The users of NHS 111 online were more likely to have also used other health services, particularly the 111 telephone service (χ12=138.57; P<.001).

CONCLUSIONS

These differences in eHealth literacy scores amplify perennial concerns about digital exclusion and access to care for those impacted by intersecting forms of disadvantage, including long-term illness. Although many appear willing to use NHS 111 online for a range of health scenarios, indicating broad acceptability, not all are able or likely to do this. Despite a policy ambition for NHS 111 online to substitute for other services, it appears to be used alongside other urgent care services and thus may not reduce demand.

The next generation of healthcare ecosystem in the metaverse

The Metaverse has gained wide attention for being the application interface for the next generation of Internet. The potential of the Metaverse is growing, as Web 3·0 development and adoption continues to advance medicine and healthcare. We define the next generation of interoperable healthcare ecosystem in the Metaverse. We examine the existing literature regarding the Metaverse, explain the technology framework to deliver an immersive experience, along with a technical comparison of legacy and novel Metaverse platforms that are publicly released and in active use. The potential applications of different features of the Metaverse, including avatar-based meetings, immersive simulations, and social interactions are examined with different roles from patients to healthcare providers and healthcare organizations. Present challenges in the development of the Metaverse healthcare ecosystem are discussed, along with potential solutions including capabilities requiring technological innovation, use cases requiring regulatory supervision, and sound governance. This proposed concept and framework of the Metaverse could potentially redefine the traditional healthcare system and enhance digital transformation in healthcare. Similar to AI technology at the beginning of this decade, real-world development and implementation of these capabilities are relatively nascent. Further pragmatic research is needed for the development of an interoperable healthcare ecosystem in the Metaverse.

Bridging the Divide: Unintended Consequences of the Shift to Home-Based Telemedicine

OBJECTIVE

To evaluate the impact on health care access of the change in telemedicine delivery from a clinic-based model, in which patients connect with their healthcare provider from local telemedicine clinics, to a home-based model, in which patients independently connect from their homes.

STUDY DESIGN

In this retrospective analysis, we compared relative uptake in telemedicine services in Period 1 (01/01/2019 to 03/15/2020, prepandemic, clinic-based model) vs Period 2 (03/16/2020 to 06/30/2022, home-based model) within a tertiary pediatric hospital system. Using multivariable logistic regression, we investigated the influence of telemedicine delivery model on patient sociodemographic characteristics of completed telemedicine visits.

RESULTS

We analyzed 400 539 patients with 1 406 961 completed outpatient encounters (52% White, 35% Black), of which 62 920 (4.5%) were telemedicine. In the clinic-based model (Period 1), underserved populations had greater likelihoods of accessing telemedicine: Hispanic ethnicity (OR = 1.41, P = .028) vs reference group non-Hispanic, Medicaid (OR = 2.62, P < .001) vs private insurance, and low-income neighborhood (OR = 3.40, P < .001) vs medium-income. In aggregate, telemedicine utilization rapidly increased from Period 1 (1.5 encounters/day) to Period 2 (107.9 encounters/day). However, underserved populations saw less relative increase (Medicaid [OR = 0.28, P < .001], Hispanic [OR = 0.53, P < .001], low-income [OR = 0.23, P < .001]).

CONCLUSIONS

We observe that the clinic-based model offers more equitable access, while the home-based model offers more absolute access, suggesting that a hybrid model that offers both home-based and clinic-based services may result in more absolute and equitable access to telemedicine.

Telehealth Utilization and Associations in the United States During the Third Year of the COVID-19 Pandemic: Population-Based Survey Study in 2022

BACKGROUND

The COVID-19 pandemic rapidly changed the landscape of clinical practice in the United States; telehealth became an essential mode of health care delivery, yet many components of telehealth use remain unknown years after the disease's emergence.

OBJECTIVE

We aim to comprehensively assess telehealth use and its associated factors in the United States.

METHODS

This cross-sectional study used a nationally representative survey (Health Information National Trends Survey) administered to US adults (≥18 years) from March 2022 through November 2022. To assess telehealth adoption, perceptions of telehealth, satisfaction with telehealth, and the telehealth care purpose, we conducted weighted descriptive analyses. To identify the subpopulations with low adoption of telehealth, we developed a weighted multivariable logistic regression model.

RESULTS

Among a total of 6252 survey participants, 39.3% (2517/6252) reported telehealth use in the past 12 months (video: 1110/6252, 17.8%; audio: 876/6252, 11.6%). The most prominent reason for not using telehealth was due to telehealth providers failing to offer this option (2200/3529, 63%). The most common reason for respondents not using offered telehealth services was a preference for in-person care (527/578, 84.4%). Primary motivations to use telehealth were providers' recommendations (1716/2517, 72.7%) and convenience (1516/2517, 65.6%), mainly for acute minor illness (600/2397, 29.7%) and chronic condition management (583/2397, 21.4%), yet care purposes differed by age, race/ethnicity, and income. The satisfaction rate was predominately high, with no technical problems (1829/2517, 80.5%), comparable care quality to that of in-person care (1779/2517, 75%), and no privacy concerns (1958/2517, 83.7%). Younger individuals (odd ratios [ORs] 1.48-2.23; 18-64 years vs ≥75 years), women (OR 1.33, 95% CI 1.09-1.61), Hispanic individuals (OR 1.37, 95% CI 1.05-1.80; vs non-Hispanic White), those with more education (OR 1.72, 95% CI 1.03-2.87; at least a college graduate vs less than high school), unemployed individuals (OR 1.25, 95% CI 1.02-1.54), insured individuals (OR 1.83, 95% CI 1.25-2.69), or those with poor general health status (OR 1.66, 95% CI 1.30-2.13) had higher odds of using telehealth.

CONCLUSIONS

To our best knowledge, this is among the first studies to examine patient factors around telehealth use, including motivations to use, perceptions of, satisfaction with, and care purpose of telehealth, as well as sociodemographic factors associated with telehealth adoption using a nationally representative survey. The wide array of descriptive findings and identified associations will help providers and health systems understand the factors that drive patients toward or away from telehealth visits as the technology becomes more routinely available across the United States, providing future directions for telehealth use and telehealth research.

Improving Access to Eye Care in Rural Communities: PocDoc's Web-Based Visual Acuity Screening Tool

Objective: Visual acuity (VA) testing is crucial for early intervention in cases of visual impairment, especially in rural health care. This study aimed to determine the potential of a web-based VA test (PocDoc) in addressing the unique health care needs of rural areas through the comparison in its effectiveness against the conventional VA test in identifying visual impairment among an Indian rural population. Methods: Prospective comparative study conducted in December 2022 at a tertiary referral eye care center in central India. We evaluated all patients with the PocDoc VA tests using three device types, and the conventional VA test. Bland-Altman plot (BAP) compared PocDoc and conventional VA tests. Fisher's exact tests evaluated associations between categorical parameters. Kruskal-Wallis tests followed by post hoc Dunn's tests identified association between categorical parameters and numerical parameters. Results: We evaluated 428 patients (792 measurements of VA) with mean age 36.7 (±23.3) years. PocDoc resulted in slightly worse VA scores (mean logMAR: 0.345) than conventional (mean logMAR: 0.315). Correlation coefficient between the conventional and PocDoc logMAR VA values was rho = 0.845 and rho2 = 0.7133 (p = 6.617 × 10-215; adjusted p = 2.205 × 10-214). Most data points fell within the interchangeable range of ±0.32 on BAP. Difference between the two methods increased with higher logMAR values, indicating poorer agreement for worse VA scores. Conclusions: Identifying and addressing the unique health care needs of rural populations is critical, including access to appropriate and effective VA testing methods. Validating and improving VA testing methods can ensure early intervention and improve the quality of life for individuals with visual impairment.

Advances and Opportunities of Mobile Health in the Postpandemic Era: Smartphonization of Wearable Devices and Wearable Deviceization of Smartphones

Mobile health (mHealth) with continuous real-time monitoring is leading the era of digital medical convergence. Wearable devices and smartphones optimized as personalized health management platforms enable disease prediction, prevention, diagnosis, and even treatment. Ubiquitous and accessible medical services offered through mHealth strengthen universal health coverage to facilitate service use without discrimination. This viewpoint investigates the latest trends in mHealth technology, which are comprehensive in terms of form factors and detection targets according to body attachment location and type. Insights and breakthroughs from the perspective of mHealth sensing through a new form factor and sensor-integrated display overcome the problems of existing mHealth by proposing a solution of smartphonization of wearable devices and the wearable deviceization of smartphones. This approach maximizes the infinite potential of stagnant mHealth technology and will present a new milestone leading to the popularization of mHealth. In the postpandemic era, innovative mHealth solutions through the smartphonization of wearable devices and the wearable deviceization of smartphones could become the standard for a new paradigm in the field of digital medicine.

Artificial intelligence, ChatGPT, and other large language models for social determinants of health: Current state and future directions

This perspective highlights the importance of addressing social determinants of health (SDOH) in patient health outcomes and health inequity, a global problem exacerbated by the COVID-19 pandemic. We provide a broad discussion on current developments in digital health and artificial intelligence (AI), including large language models (LLMs), as transformative tools in addressing SDOH factors, offering new capabilities for disease surveillance and patient care. Simultaneously, we bring attention to challenges, such as data standardization, infrastructure limitations, digital literacy, and algorithmic bias, that could hinder equitable access to AI benefits. For LLMs, we highlight potential unique challenges and risks including environmental impact, unfair labor practices, inadvertent disinformation or "hallucinations," proliferation of bias, and infringement of copyrights. We propose the need for a multitiered approach to digital inclusion as an SDOH and the development of ethical and responsible AI practice frameworks globally and provide suggestions on bridging the gap from development to implementation of equitable AI technologies.

Teleophthalmology and retina: a review of current tools, pathways and services

Telemedicine, the use of telecommunication and information technology to deliver healthcare remotely, has evolved beyond recognition since its inception in the 1970s. Advances in telecommunication infrastructure, the advent of the Internet, exponential growth in computing power and associated computer-aided diagnosis, and medical imaging developments have created an environment where telemedicine is more accessible and capable than ever before, particularly in the field of ophthalmology. Ever-increasing global demand for ophthalmic services due to population growth and ageing together with insufficient supply of ophthalmologists requires new models of healthcare provision integrating telemedicine to meet present day challenges, with the recent COVID-19 pandemic providing the catalyst for the widespread adoption and acceptance of teleophthalmology. In this review we discuss the history, present and future application of telemedicine within the field of ophthalmology, and specifically retinal disease. We consider the strengths and limitations of teleophthalmology, its role in screening, community and hospital management of retinal disease, patient and clinician attitudes, and barriers to its adoption.

Large language models and their impact in ophthalmology

The advent of generative artificial intelligence and large language models has ushered in transformative applications within medicine. Specifically in ophthalmology, large language models offer unique opportunities to revolutionise digital eye care, address clinical workflow inefficiencies, and enhance patient experiences across diverse global eye care landscapes. Yet alongside these prospects lie tangible and ethical challenges, encompassing data privacy, security, and the intricacies of embedding large language models into clinical routines. This Viewpoint highlights the promising applications of large language models in ophthalmology, while weighing up the practical and ethical barriers towards their real-world implementation. This Viewpoint seeks to stimulate broader discourse on the potential of large language models in ophthalmology and to galvanise both clinicians and researchers into tackling the prevailing challenges and optimising the benefits of large language models while curtailing the associated risks.

Medication management of COVID-19 patients during transition to virtual models of care: a qualitative study

INTRODUCTION

Expansion of hospital service models was one of the strategies implemented to manage the COVID-19 pandemic through virtual models of care. COVID-19 patients were hospital inpatients transferred to virtual wards and managed outside the hospital. Pharmacists had to provide distance medication management and support services. Virtual care patient support incorporated telehealth consultations by doctors, pharmacists and nurses. This study explored hospital clinicians' experiences and perspectives on medication management and safety issues of the COVID-19 patients transferred from inpatient units (IPUs) to virtual models of care at the time of transfer.

METHODS

Semi-structured qualitative interviews were conducted with purposively selected doctors, pharmacists and nurses involved in the management of COVID-19 patients in a virtual model of care (home or hotel). Clinicians were interviewed face-to-face or via MS Teams between March and May 2022. An interview schedule included 13 questions and prompts to explore perceptions of medication management and safety aspects.

RESULTS

Twenty clinicians were interviewed: six doctors, seven pharmacists, and seven nurses. The average interview time was 26 min (SD: 4.7; range 21-39). Four major medication management and safety themes emerged from the data: (1) complexities involved in efficient handover between IPU and virtual models of care; (2) lack of clarity on roles and responsibilities between hospital and primary care clinicians; (3) communication challenges when pharmacists work remotely; and (4) proactive management of specific medication safety risks. A common thread throughout the themes was concerns for potential impact on patient safety.

CONCLUSION

Overall, clinicians were supportive of the virtual models although patient safety issues were raised that need to be addressed in the development of future services. The results from this study may inform improvements in medication safety implementation of future virtual models of care.

Remote Perimetry in a Virtual Reality Metaverse Environment for Out-of-Hospital Functional Eye Screening Compared Against the Gold Standard Humphrey Visual Fields Perimeter: Proof-of-Concept Pilot Study

BACKGROUND

The growing global burden of visual impairment necessitates better population eye screening for early detection of eye diseases. However, accessibility to testing is often limited and centralized at in-hospital settings. Furthermore, many eye screening programs were disrupted by the COVID-19 pandemic, presenting an urgent need for out-of-hospital solutions.

OBJECTIVE

This study investigates the performance of a novel remote perimetry application designed in a virtual reality metaverse environment to enable functional testing in community-based and primary care settings.

METHODS

This was a prospective observational study investigating the performance of a novel remote perimetry solution in comparison with the gold standard Humphrey visual field (HVF) perimeter. Subjects received a comprehensive ophthalmologic assessment, HVF perimetry, and remote perimetry testing. The primary outcome measure was the agreement in the classification of overall perimetry result normality by the HVF (Swedish interactive threshold algorithm-fast) and testing with the novel algorithm. Secondary outcome measures included concordance of individual testing points and perimetry topographic maps.

RESULTS

We recruited 10 subjects with an average age of 59.6 (range 28-81) years. Of these, 7 (70%) were male and 3 (30%) were female. The agreement in the classification of overall perimetry results was high (9/10, 90%). The pointwise concordance in the automated classification of individual test points was 83.3% (8.2%; range 75%-100%). In addition, there was good perimetry topographic concordance with the HVF in all subjects.

CONCLUSIONS

Remote perimetry in a metaverse environment had good concordance with gold standard perimetry using the HVF and could potentially avail functional eye screening in out-of-hospital settings.

COVID-19 Patients' Medication Management during Transition of Care from Hospital to Virtual Care: A Cross-Sectional Survey and Audit

BACKGROUND

Virtual models of care were implemented to ease hospital bed pressure during COVID-19. We evaluated the medication management of COVID-19 patients transferred to virtual models of care.

METHOD

A retrospective audit of COVID-19 patients transferred from inpatient units to virtual care during January 2022 and surveys from patients transferred during December 2021-February 2022 was carried out.

RESULTS

One hundred patients were randomly selected: mean age 59 years (SD: 19.8), mean number of medicines at admission 4.3 (SD: 4.03), mean length of virtual ward stay 4.4 days (SD: 2.1). Pharmacists reviewed 43% (43/100) of patients' medications during their hospital stay and provided 29% (29/100) with discharge medicine lists at transfer. Ninety-two (92%) patients were prescribed at least one new high-risk medicine whilst in hospital, but this was not a factor considered to receive a pharmacist medication review. Forty patients (40%) were discharged on newly commenced high-risk medicines, and this was also not a factor in receiving a pharmacist discharge medication list. In total, 25% of patient surveys (96/378) were returned: 70% (66/96) reported adequate medicine information at transfer and 55% (52/96) during the virtual model period.

CONCLUSION

Patient survey data show overall positive experiences of medication management and support. Audit data highlight gaps in medication management during the transfer to a virtual model, highlighting the need for patient prioritisation.

Awareness and attitudes of elderly Southeast Asian adults towards telehealth during the COVID-19 pandemic: a qualitative study

Introduction

We aimed to understand the awareness and attitudes of elderly Southeast Asians towards telehealth services during the coronavirus disease 2019 (COVID-19) pandemic in this study.

Methods

In this qualitative study, 78 individuals from Singapore (51.3% female, mean age 73.0 ± 7.6 years) were interviewed via telephone between 13 May 2020 and 9 June 2020 during Singapore's first COVID-19 'circuit breaker'. Participants were asked to describe their understanding of telehealth, their experience of and willingness to utilise these services, and the barriers and facilitators underlying their decision. Transcripts were analysed using thematic analysis, guided by the United Theory of Acceptance Use of Technology framework.

Results

Of the 78 participants, 24 (30.8%) were able to describe the range of telehealth services available and 15 (19.2%) had previously utilised these services. Conversely, 14 (17.9%) participants thought that telehealth comprised solely home medication delivery and 50 (51.3%) participants did not know about telehealth. Despite the advantages offered by telehealth services, participants preferred in-person consultations due to a perceived lack of human interaction and accuracy of diagnoses, poor digital literacy and a lack of access to telehealth-capable devices.

Conclusion

Our results showed poor overall awareness of the range of telehealth services available among elderly Asian individuals, with many harbouring erroneous views regarding their use. These data suggest that public health education campaigns are needed to improve awareness of and correct negative perceptions towards telehealth services in elderly Asians.

Planning an artificial intelligence diabetic retinopathy screening program: a human-centered design approach

Diabetic retinopathy (DR) is a leading cause of vision loss in the United States and throughout the world. With early detection and treatment, sight-threatening sequelae from DR can be prevented. Although artificial intelligence (AI) based DR screening programs have been proven to be effective in identifying patients at high risk of vision loss, adoption of AI in clinical practice has been slow. We adapted the United Kingdom Design Council's Double-Diamond model to design a strategy for care delivery which integrates an AI-based screening program for DR into a primary care setting. Methods from human-centered design were used to develop a strategy for implementation informed by context-specific barriers and facilitators. The purpose of this community case study is to present findings from this work in progress, including a system of protocols, educational documents and workflows created using key stakeholder input.

India's Opportunity to Address Human Resource Challenges in Healthcare

India's health indicators have improved in recent times but continue to lag behind those of its peer nations. The country with a population of 1.3 billion, has an estimated active health workers density of doctors and nurses/midwives of 5.0 and 6.0 respectively, for 10,000 persons, which is much lower than the WHO threshold of 44.5 doctors, nurses, and midwives per 10,000 population. The issue is compounded by the skewed inter-state, urban-rural, and public-private sector divide. Calls to urgently augment the skilled health workforce reinforce the central role human resources have in healthcare, which has evolved into a complex multifactorial issue. The paucity of skilled personnel must be addressed if India is to accelerate its progress toward achieving universal health coverage and its sustainable development goals (SDGs). The recent increase in the federal health budget offers an unprecedented opportunity to do this. This article utilizes the ready materials, extract and analyze data, distill findings (READ) approach to adding to the authors' experiential learning to analyze the health system in India. The growing divide between the public and the burgeoning private health sector systems, with the latter's booming medical tourism industry and medical schools, are analyzed along with the newly minted National Medical Council, to recommend policies that would help India achieve its SDGs.

Trialling a Large Language Model (ChatGPT) in General Practice With the Applied Knowledge Test: Observational Study Demonstrating Opportunities and Limitations in Primary Care

BACKGROUND

Large language models exhibiting human-level performance in specialized tasks are emerging; examples include Generative Pretrained Transformer 3.5, which underlies the processing of ChatGPT. Rigorous trials are required to understand the capabilities of emerging technology, so that innovation can be directed to benefit patients and practitioners.

OBJECTIVE

Here, we evaluated the strengths and weaknesses of ChatGPT in primary care using the Membership of the Royal College of General Practitioners Applied Knowledge Test (AKT) as a medium.

METHODS

AKT questions were sourced from a web-based question bank and 2 AKT practice papers. In total, 674 unique AKT questions were inputted to ChatGPT, with the model's answers recorded and compared to correct answers provided by the Royal College of General Practitioners. Each question was inputted twice in separate ChatGPT sessions, with answers on repeated trials compared to gauge consistency. Subject difficulty was gauged by referring to examiners' reports from 2018 to 2022. Novel explanations from ChatGPT-defined as information provided that was not inputted within the question or multiple answer choices-were recorded. Performance was analyzed with respect to subject, difficulty, question source, and novel model outputs to explore ChatGPT's strengths and weaknesses.

RESULTS

Average overall performance of ChatGPT was 60.17%, which is below the mean passing mark in the last 2 years (70.42%). Accuracy differed between sources (P=.04 and .06). ChatGPT's performance varied with subject category (P=.02 and .02), but variation did not correlate with difficulty (Spearman ρ=-0.241 and -0.238; P=.19 and .20). The proclivity of ChatGPT to provide novel explanations did not affect accuracy (P>.99 and .23).

CONCLUSIONS

Large language models are approaching human expert-level performance, although further development is required to match the performance of qualified primary care physicians in the AKT. Validated high-performance models may serve as assistants or autonomous clinical tools to ameliorate the general practice workforce crisis.

Impact of the COVID-19 Pandemic on Cancer Patient Educators

Patient education (PE) is vital in reducing anxiety, increasing satisfaction with treatment, helping with self-management, and creating a sense of control for cancer patients. Patients access much of their material from health care providers through in-person visits, patient libraries, and in-person classes. Due to reductions in in-person visits throughout the pandemic, we sought to understand how PE programs responded under varying levels of COVID-19 restrictions to meet the information needs of patients and families. A cross-sectional survey was distributed to members of the Cancer Patient Education Network (CPEN) and the Health Care Education Association (HCEA) via the respective listservs. The survey consisted of five sections that included closed and opened questions. Participants were asked questions to describe their PE programs and how their duties were affected during the pandemic. Forty-two CPEN members completed the survey (N = 42, 66%) with a 35% response rate and a 55% completion rate, and 19 HCEA members completed the survey (N = 19, 30%) with a 5% response rate and 16% completion rate. The majority of staff surveyed were not furloughed (N = 57/64, 89%). Just under half reported a change in daily PE program activities (N = 23/52, 44%) and most reported a change in developing PE materials (e.g., pamphlets) (N = 10/26, 63%), finding information for patients/families (N = 11/19, 58%), and delivering classes (N = 12/21, 57%). COVID-19 has ushered in a new era in the delivery of PE with the rapid deployment of digital cancer patient education. Results can inform future directions for the delivery of PE post-pandemic.

Development and testing of a multi-lingual Natural Language Processing-based deep learning system in 10 languages for COVID-19 pandemic crisis: A multi-center study

Purpose

The COVID-19 pandemic has drastically disrupted global healthcare systems. With the higher demand for healthcare and misinformation related to COVID-19, there is a need to explore alternative models to improve communication. Artificial Intelligence (AI) and Natural Language Processing (NLP) have emerged as promising solutions to improve healthcare delivery. Chatbots could fill a pivotal role in the dissemination and easy accessibility of accurate information in a pandemic. In this study, we developed a multi-lingual NLP-based AI chatbot, DR-COVID, which responds accurately to open-ended, COVID-19 related questions. This was used to facilitate pandemic education and healthcare delivery.

Methods

First, we developed DR-COVID with an ensemble NLP model on the Telegram platform (https://t.me/drcovid_nlp_chatbot). Second, we evaluated various performance metrics. Third, we evaluated multi-lingual text-to-text translation to Chinese, Malay, Tamil, Filipino, Thai, Japanese, French, Spanish, and Portuguese. We utilized 2,728 training questions and 821 test questions in English. Primary outcome measurements were (A) overall and top 3 accuracies; (B) Area Under the Curve (AUC), precision, recall, and F1 score. Overall accuracy referred to a correct response for the top answer, whereas top 3 accuracy referred to an appropriate response for any one answer amongst the top 3 answers. AUC and its relevant matrices were obtained from the Receiver Operation Characteristics (ROC) curve. Secondary outcomes were (A) multi-lingual accuracy; (B) comparison to enterprise-grade chatbot systems. The sharing of training and testing datasets on an open-source platform will also contribute to existing data.

Results

Our NLP model, utilizing the ensemble architecture, achieved overall and top 3 accuracies of 0.838 [95% confidence interval (CI): 0.826-0.851] and 0.922 [95% CI: 0.913-0.932] respectively. For overall and top 3 results, AUC scores of 0.917 [95% CI: 0.911-0.925] and 0.960 [95% CI: 0.955-0.964] were achieved respectively. We achieved multi-linguicism with nine non-English languages, with Portuguese performing the best overall at 0.900. Lastly, DR-COVID generated answers more accurately and quickly than other chatbots, within 1.12-2.15 s across three devices tested.

Conclusion

DR-COVID is a clinically effective NLP-based conversational AI chatbot, and a promising solution for healthcare delivery in the pandemic era.

Assessing the Acceptability of Home Blood Monitoring for Patients With Cancer Who Are Receiving Systemic Anticancer Therapy From a Patient, Caregiver, and Clinician Perspective: Focus Group and Interview Study

BACKGROUND

Regular blood testing is an integral part of systemic anticancer therapy delivery. Blood tests are required before every administration of treatment to ensure that a patient is sufficiently well to receive it. Blood testing is burdensome for patients as they require either an extra visit within 48 hours of planned administration of treatment or a significantly long visit if performed on the day of treatment. The additional time for appointments can have a significant impact on the quality of life of someone who is living with cancer. In the United Kingdom, the COVID-19 pandemic created unprecedented disruption to the delivery of cancer care. Face-to-face hospital visits were reduced, resulting in the need to develop more innovative ways of working to minimize treatment interruptions. This led to significant uptake of digital technologies, with new models of care rapidly deployed across the UK health service to meet these challenges.

OBJECTIVE

This study aimed to explore the acceptability of a point-of-care home blood monitoring device for people with cancer who are receiving systemic anticancer therapy, which is being developed in response to the increased need for remote care for patients with cancer.

METHODS

Qualitative focus groups and semistructured interviews were conducted with patients (23/47, 49%), caregivers (6/47, 13%), and health care professionals (18/47, 38%) over a 19-month time frame from May 2019 to December 2020. Data were analyzed using framework analysis guided by the Unified Theory of Acceptance and Use of Technology model.

RESULTS

Analysis identified 4 overarching themes: performance expectancy, effort expectancy, social influence, and facilitating conditions.

CONCLUSIONS

This study found that patients with cancer, their caregivers, and health care professionals had positive perceptions about home blood monitoring. Although they are often considered synonymously, self-testing and self-management are not mutually exclusive, and this study illustrated some disparity in opinions regarding patient self-management. Home blood monitoring has the potential to provide patients with cancer with a convenient option for blood monitoring. It would minimize hospital attendances, decrease late treatment deferrals, and provide prompt recognition of cancer treatment toxicities, thus enhancing the existing nurse-led protocols and clinical pathways. Home blood monitoring would create a long-term sustainable transformation for the delivery of cancer care, using digital health to act as a facilitator to address a pertinent issue regarding improving the efficiency of hospital resources and increasing the delivery of personalized patient care. Further studies are needed to determine how and where home blood monitoring would fit within clinical pathways, in a way that is robust and equitable.

Surfing the COVID-19 Tsunami with Teleophthalmology: the Advent of New Models of Eye Care

Purpose of Review

In this article, we reviewed the impact resulting from the COVID-19 pandemic on the traditional model of care in ophthalmology.

Recent Findings

Though virtual eye care has been present for more than 20 years, the COVID-19 pandemic has established a precedent to seriously consider its role in the evolving paradigm of vision and eye care. New hybrid models of care have enhanced or replaced traditional synchronous and asynchronous visits. The increased use of smart phoneography and mobile applications enhanced the remote examination of patients. Use of e-learning became a mainstream tool to continue accessing education and training.

Summary

Teleophthalmology has demonstrated its value for screening, examining, diagnosing, monitoring treatment, and increasing access to education. However, much of the progress made following the COVID-19 pandemic is at risk of being lost as society pushes to reestablish normalcy. Further studies during the new norm are required to prove a more permanent role for virtual eye care.

Patient-facing digital tools for delivering genetic services: a systematic review

This study systematically reviewed the literature on the impact of digital genetics tools on patient care and system efficiencies. MEDLINE and Embase were searched for articles published between January 2010 and March 2021. Studies evaluating the use of patient-facing digital tools in the context of genetic service delivery were included. Two reviewers screened and extracted patient-reported and system-focused outcomes from each study. Data were synthesised using a descriptive approach. Of 3226 unique studies identified, 87 were included. A total of 70 unique digital tools were identified. As a result of using digital tools, 84% of studies reported a positive outcome in at least one of the following patient outcomes: knowledge, psychosocial well-being, behavioural/management changes, family communication, decision-making or level of engagement. Digital tools improved workflow and efficiency for providers and reduced the amount of time they needed to spend with patients. However, we identified a misalignment between study purpose and patient-reported outcomes measured and a lack of tools that encompass the entire genetic counselling and testing trajectory. Given increased demand for genetic services and the shift towards virtual care, this review provides evidence that digital tools can be used to efficiently deliver patient-centred care. Future research should prioritise development, evaluation and implementation of digital tools that can support the entire patient trajectory across a range of clinical settings. PROSPERO registration numberCRD42020202862.

Finding the sweet spot: a qualitative study exploring patients' acceptability of chatbots in genetic service delivery

Chatbots, web-based artificial intelligence tools that simulate human conversation, are increasingly in use to support many areas of genomic medicine. However, patient preferences towards using chatbots across the range of clinical settings are unknown. We conducted a qualitative study with individuals who underwent genetic testing for themselves or their child. Participants were asked about their preferences for using a chatbot within the genetic testing journey. Thematic analysis employing interpretive description was used. We interviewed 30 participants (67% female, 50% 50 + years). Participants considered chatbots to be inefficient for very simple tasks (e.g., answering FAQs) or very complex tasks (e.g., explaining results). Chatbots were acceptable for moderately complex tasks where participants perceived a favorable return on their investment of time and energy. In addition to achieving this "sweet spot," participants anticipated that their comfort with chatbots would increase if the chatbot was used as a complement to but not a replacement for usual care. Participants wanted a "safety net" (i.e., access to a clinician) for needs not addressed by the chatbot. This study provides timely insights into patients' comfort with and perceived limitations of chatbots for genomic medicine and can inform their implementation in practice.

Developments in respiratory self-management interventions over the last two decades

This paper describes developments in the fields of asthma and COPD self-management interventions (SMIs) over the last two decades and discusses future directions. Evidence around SMIs has exponentially grown. Efficacy on group level is convincing and both asthma and COPD SMIs are currently recommended by respiratory guidelines. Core components of asthma SMIs are defined as education, action plans, and regular review, with some discussion about self-monitoring. Exacerbation action plans are defined as an integral part of COPD management. Patient's adherence to SMI's is however inadequate and significantly reducing the intervention's impact. Adherence could be improved by tailoring of SMIs to patients' needs, health beliefs, and capabilities; the use of shared decision making; and optimising the communication between patients and health care providers. Due to the COVID-19 pandemic, digital health innovations have rapidly been introduced and expanded. Digital technology use may increase efficiency, flexibility, and efficacy of SMIs. Furthermore, artificial intelligence can be used to e.g., predict exacerbations in action plans. Research around digital health innovations to ensure evidence-based practice is of utmost importance. Current implementation of respiratory SMIs is not satisfactory. Implementation research should be used to generate further insights, with cost-effectiveness, policy (makers), and funding being significant determinants.

Hospitality and COVID-19: a willingness to choose e-consultation owing to unemployment and home isolation

Purpose

Coronavirus disease (COVID-19) was declared as a pandemic since COVID-19's widespread outbreak and the hospitality industry has been the hardest hit due to lockdown. Consequently, hospitality workers are suffering from the negative aspects of mental health. In the event of such a crisis, this study aims to explore the link between unemployment and home isolation to the willingness to choose electronic consultation (e-consultation) by exploiting psychological ill-being and behavioural intention (BI) with marital status as a moderator.

Design/methodology/approach

A quantitative methodology is applied to primary data collected from 310 workers from the hospitality industry through an online survey.

Findings

Findings of this study suggest that the usage of the e-consultation service can be adopted using three levels. There are valid reasons to conclude unemployment and home isolation are linked to higher rates of psychological health behaviours, which can result in stigma, loss of self-worth and increased mortality. The adverse effect is higher for single individuals than for married people.

Originality/value

The study focussed on e-consultation, BI coupled with the Fishbein scale and a classification model for the prediction of willingness to choose e-consultation with the extension of Theory of Planned Behaviour (TPB).

Digital innovations for retinal care in diabetic retinopathy

AIM

The purpose of this review is to examine the applications of novel digital technology domains for the screening and management of patients with diabetic retinopathy (DR).

METHODS

A PubMed engine search was performed, using the terms "Telemedicine", "Digital health", "Telehealth", "Telescreening", "Artificial intelligence", "Deep learning", "Smartphone", "Triage", "Screening", "Home-based", "Monitoring", "Ophthalmology", "Diabetes", "Diabetic Retinopathy", "Retinal imaging". Full-text English language studies from January 1, 2010, to February 1, 2022, and reference lists were considered for the conceptual framework of this review.

RESULTS

Diabetes mellitus and its eye complications, including DR, are particularly well suited to digital technologies, providing an ideal model for telehealth initiatives and real-world applications. The current development in the adoption of telemedicine, artificial intelligence and remote monitoring as an alternative to or in addition to traditional forms of care will be discussed.

CONCLUSIONS

Advances in digital health have created an ecosystem ripe for telemedicine in the field of DR to thrive. Stakeholders and policymakers should adopt a participatory approach to ensure sustained implementation of these technologies after the COVID-19 pandemic. This article belongs to the Topical Collection "Diabetic Eye Disease", managed by Giuseppe Querques.

Implementation science: A critical but undervalued part of the healthcare innovation ecosystem

Healthcare systems face many competing demands and insufficient resources. Service innovations to improve efficiency are important to address this challenge. Innovations can range from new pharmaceuticals, alternate models of care, novel devices, and the use other technologies. Suboptimal implementation can mean lost benefits. This review article aims to highlight the role of implementation science, summarize how settings have leveraged this methodology to promote translation of innovation into practice, and describe our own experience of embedding implementation science into an academic medical center in Singapore. Implementation science offers a range of methods to promote systematic uptake of research findings about innovations and is gaining recognition worldwide as an important discipline for health services researchers. Health systems around the world have tried to promote implementation research in their settings by establishing (1) dedicated centers/programs, (2) offering funding, and (3) building knowledge and capacity among staff. Implementation science is a critical piece in the translational pathway of "evidence to innovation." The three efforts we describe should be strengthened to integrate implementation science into the innovation ecosystem around the world.

Adherence to Urgent Eye Visits during the COVID-19 Pandemic: A Population Characteristics Study

PURPOSE

To explore individual and community factors associated with adherence to physician recommended urgent eye visits via a tele-triage system during the COVID-19 pandemic.

METHOD

We retrospectively reviewed acute visit requests and medical exam data between April 6, 2020 and June 6, 2020. Patient demographics and adherence to visit were examined. Census tract level community characteristics from the U.S. Census Bureau and zip code level COVID-19 related death data from the Cook County Medical Examiner's Office were appended to each geocoded patient address. Descriptive statistics, t-tests, and logistic regression analyses were performed to explore the effects of individual and community variables on adherence to visit.

RESULTS

Of 229 patients recommended an urgent visit, 216 had matching criteria on chart review, and 192 (88.9%) adhered to their visit. No difference in adherence was found based on individual characteristics including: age (p = .24), gender (p = .94), race (p = .56), insurance (p = .28), nor new versus established patient status (p = .20). However, individuals who did not adhere were more likely to reside in neighborhoods with a greater proportion of Blacks (59.4% vs. 33.4%; p = .03), greater unemployment rates (17.5% vs. 10.7%; p < .01), and greater cumulative deaths from COVID-19 (56 vs. 31; p = .01). Unemployment rate continued to be statistically significant after controlling for race and cumulative deaths from COVID-19 (p = .04).

CONCLUSION

We found that as community unemployment rate increases, adherence to urgent eye visits decreases, after controlling for relevant neighborhood characteristics. Unemployment rates were highest in predominantly Black neighborhoods early in the pandemic, which may have contributed to existing racial disparities in eye care.

Beyond tingles: An exploratory qualitative study of the Autonomous Sensory Meridian Response (ASMR)

This qualitative exploratory study investigated the embodied experiences and the meanings of Autonomous Sensory Meridian Response (ASMR) from the viewer's perspective. ASMR research has been sparse and largely quantitative, assuming it to be a predominantly fixed physiological response of "tingles", despite the acronym being rooted in pseudoscience. A qualitative research design was adopted to facilitate the exploratory nature of the study in this under-researched area. In contrast to the mostly survey-based research on ASMR, this study employed semi-structured interviews as a means to understand the lived experience of ASMR and to promote participant agency. Six self-identifying ASMR consumers were recruited using a mixture of snowball and opportunity sampling. Semi-structured interviews were conducted both in person and using Skype to facilitate transnational data collection. Interview transcripts were analysed using an inductive, data-driven approach to thematic analysis. The analysis suggests that ASMR is felt to provide a social environment of comfort rather than a solely physiological-based experience. Three key themes emerged: who and what defines ASMR? (reflecting the variety of what was classed as ASMR and what content was consumed to produce the response); "real" intimacy tailored to me (reflecting the idiosyncratic perception of intimacy made possible through ASMR); and emotional relief on my terms (reflecting the role of ASMR in self-soothing). The present data reflect a rich, complex experience of the ASMR consumer, pointing to potential wider applications and informing further research.

Monitoring Australian parents' shifting receptiveness to digital mental health interventions during the COVID-19 pandemic

BACKGROUND

Nascent evidence indicates that the mental health of parents and children has markedly declined during the COVID-19 pandemic. Considering disruptions to traditional face-to-face mental health services resultant from stay-at-home orders, the potential value of digital mental health interventions has become extremely apparent. Despite this, uptake of digital interventions remains poor, indicating that a better understanding is needed of factors that determine a willingness to use digital platforms.

METHOD

The present multi-wave, longitudinal study of 2365 Australian parents explored between-person and within-person predictors of intentions to use digital interventions during the pandemic.

RESULTS

More than one-third of parents reported likely use of a self-guided and therapist-guided digital intervention, with the most endorsed reason for use being to support their child's mental health. Between-person baseline predictors of higher intention ratings were parent's prior mental illness, not living with a partner and recent environmental stressors. Within-person predictors of higher intention ratings were endorsement of mindful parenting strategies, child access to the Internet, better perceived management of child's education, lower social support and financial hardship.

CONCLUSION

Findings demonstrate that willingness to engage in digital interventions fluctuates in response to changing circumstances. Identifying novel ways to increase acceptance and uptake of digital interventions based on modifiable predictors established here is needed to realize the full potential of these modes of care in times of need.

Lessons learnt for enhancing hospital resilience to pandemics: A qualitative analysis from Italy

The COVID-19 pandemic has outlined the need to strengthen the resilience of healthcare systems. It has cost millions of human lives and has had indirect health impacts too. Hospital buildings have undergone extensive modifications and adaptations to ensure infection control and prevention measures, and, as it is happened following past epidemics, the COVID-19 experience might change the design of hospital buildings in the future. This paper aims to capitalise on the knowledge developed by the stakeholders directly involved with the hospital response during the pandemic to generate new evidence that will enhance resilience of hospital buildings to pandemics. The research adopted qualitative research methods, namely literature review and interviews with Italian experts including doctors and facility managers to collect data which were analysed through a thematic analysis. The findings include the identification of new needs for hospital buildings and the related actions to be taken or already performed at hospital building and service level which are viable for long term implementation and are aimed at improving hospital resilience to pandemics. The results specify how to improve resilience by means of structural modifications (e.g. placing filter zones among different wards, ensuring the presence of airborne infection isolation rooms at least in the emergency departments), technological changes (e.g. oversizing capacity such as medical gases, information technology improvement for delivering healthcare services remotely), and operational measures (e.g. assessing the risk of infection before admission, dividing acute-care from low-care assets). The needs discussed in this paper substantiate the urge to renovate the Italian healthcare infrastructures and they can be considered useful elements of knowledge for enhancing hospital resilience to pandemics in the extended and in the post-COVID-19 era.

Person-centred support programme (RESPECT intervention) for women with breast cancer treated with endocrine therapy: a feasibility study

OBJECTIVE

The peRson-cEntred Support Programme EndoCrine Therapy intervention is a complex intervention encompassing a person-centred support programme for patients with breast cancer being treated with endocrine therapy (ET). The aim of this study was to explore the feasibility of the trial design and patient acceptability of the intervention and outcome measures and to provide data to estimate the parameters required to design the final intervention.

DESIGN

A controlled before-and-after design following the Consolidated Standards of Reporting Trials 2010 statement for feasibility trials.

SETTING

A surgical outpatient clinic in Sweden.

PARTICIPANTS

Forty-one patients (aged 47-85) with breast cancer who were treated with ET.

INTERVENTIONS

Eligible patients were assigned to the control group or intervention group, which included individual education material, an individualised learning plan and a personalised reminder letter using a person-centred approach. The intervention could be delivered as a telephone or digital follow-up during a 12-week follow-up.

OUTCOME MEASURES

The aims were to determine the recruitment rate, assess the rate of retention, explore whether the intervention was delivered according to the protocol, assess the preferred form of educational support, rate of education sessions, length per education session and length between each education session, determine the distribution of education materials and assess completion rates of patient-reported instruments, including the General Self-efficacy Scale, the Quality of Care from the Patient's Perspective Questionnaire and the Memorial Symptom Assessment Scale.

RESULTS

Eighty-six per cent of the patients in the intervention group completed the intervention and questionnaires 3 months after their inclusion. The call attendance was 90%. During the intervention, the contact nurse complied with the intervention protocol. For self-efficacy, symptoms and quality of care, there were no differences in effect size between the control and intervention groups.

CONCLUSIONS

This intervention seems to be feasible and acceptable among patients.

Digital Advancements in Retinal Models of Care in the Post-COVID-19 Lockdown Era

The coronavirus disease-2019 (COVID-19) pandemic introduced unique barriers to retinal care including limited access to imaging modalities, ophthalmic clinicians, and direct medical interventions. These unprecedented barriers were met with the robust implementation of digital advances to aid in monitoring and efficiency of retinal care while taking into the account of public safety. Many of these innovations have been successful in maintaining efficiency and patient satisfaction and are likely to stay to help preserve vision in the future. In this article we highlight these advances implemented during the pandemic including telescreening triage, virtual retinal imaging clinics, at-home optical coherence tomography, mobile phone self-monitoring, and virtual reality monitoring technology. We also discuss advancing innovations including Internet of Things and Blockchain technology that will be critical for further implementation and security of these digital advancements.

Machine learning models using mobile game play accurately classify children with autism

Digitally-delivered healthcare is well suited to address current inequities in the delivery of care due to barriers of access to healthcare facilities. As the COVID-19 pandemic phases out, we have a unique opportunity to capitalize on the current familiarity with telemedicine approaches and continue to advocate for mainstream adoption of remote care delivery. In this paper, we specifically focus on the ability of GuessWhat? a smartphone-based charades-style gamified therapeutic intervention for autism spectrum disorder (ASD) to generate a signal that distinguishes children with ASD from neurotypical (NT) children. We demonstrate the feasibility of using "in-the-wild", naturalistic gameplay data to distinguish between ASD and NT by children by training a random forest classifier to discern the two classes (AU-ROC = 0.745, recall = 0.769). This performance demonstrates the potential for GuessWhat? to facilitate screening for ASD in historically difficult-to-reach communities. To further examine this potential, future work should expand the size of the training sample and interrogate differences in predictive ability by demographic.

Ophthalmologic emergency room visits during COVID-19 lockdown–Characterization from Haifa, Israel

Purpose

To characterize quantitative differences among ophthalmologic emergency room (OER) encounters at Rambam Health Care Campus during a 6-week complete lockdown at the peak of the first COVID-19 wave as compared to a corresponding uneventful period a year earlier.

Methods

A retrospective chart analysis of all OER encounters during the lockdown and non-lockdown period was conducted. Patients were stratified into primary ophthalmological conditions (OER visits) and cases in which ophthalmologic consultations were requested by a non-ophthalmologist (OER consultations). The following parameters were compared: total number of cases, age, gender, chief complaint/diagnosis categorized into major entities, and discharge vs. hospitalization. For continuous variables a t-test was used and for categorical variables a chi-squared or Fisher’s exact test was used. A 2-sided p value <0.05 was considered statistically significant.

Results

The total number of patients in the lockdown and non-lockdown groups was 486 and 992, respectively, showing a 51% decrease in visits during lockdown. In the non-lockdown and lockdown groups 56% and 61% of patients were male (p = 0.07), with an average age of 42 (range 0–97, SD 23) and 43 (range 0–90, SD 22) years, respectively (p = 0.44). No statistically significant proportional increase was found for any diagnostic category between the OER visits (p = 0.07) and OER consultation groups (p = 0.77). Nevertheless, analysis revealed a non-significant increase in the proportion of eye trauma from 14.8% to 21.2%, and reduction in eyelid conditions from 10.7% to 5.8%. The total number of OER visits demanding urgent intervention on admission was 43 (non-lockdown) and 24 (lockdown), while hospitalization ratio (hospitalizations/visits) was 8.8% and 10.6%, respectively (p = 0.44).

Conclusions

During the COVID-19 lockdown the guideline for patients in Israel was to avoid unnecessary hospital visits. Since patients tended to avoid the OER rather uniformly regardless of their specific eye condition, determining the risk-benefit of such recommendations and identifying high-risk sub-populations are critical public health issues.

A qualitative study of hospital and community providers’ experiences with digitalization to facilitate hospital-to-home transitions during the COVID-19 pandemic

Background

The COVID-19 pandemic has triggered substantial changes to the healthcare context, including the rapid adoption of digital health to facilitate hospital-to-home transitions. This study aimed to: i) explore the experiences of hospital and community providers with delivering transitional care during the COVID-19 pandemic; ii) understand how rapid digitalization in healthcare has helped or hindered hospital-to-home transitions during the COVID-19 pandemic; and, iii) explore expectations of which elements of technology use may be sustained post-pandemic.

Methods

Using a pragmatic qualitative descriptive approach, remote interviews with healthcare providers involved in hospital-to-home transitions in Ontario, Canada, were conducted. Interviews were analyzed using a team-based rapid qualitative analysis approach to generate timely results. Visual summary maps displaying key concepts/ideas were created for each interview and revised based on input from multiple team members. Maps that displayed similar concepts were then combined to create a final map, forming the themes and subthemes.

Results

Sixteen healthcare providers participated, of which 11 worked in a hospital, and five worked in a community setting. COVID-19 was reported to have profoundly impacted healthcare providers, patients, and their caregivers and influenced the communication processes. There were several noted opportunities for technology to support transitions.

Interpretation

Several challenges with technology use were highlighted, which could impact post-pandemic sustainability. However, the perceived opportunities for technology in supporting transitions indicate the need to investigate the optimal role of technology in the transition workflow.

Investigation of optical solitons to the nonlinear complex Kundu-Eckhaus and Zakharov-Kuznetsov-Benjamin-Bona-Mahony equations in conformable

This research manuscript focuses on the extraction of dark-bright solitons and periodic wave distributions of two models, namely, the Zakharov-Kuznetsov-Benjamin-Bona-Mahony equation and complex Kundu-Eckhaus equation with conformable derivative. To reach these important properties, the generalized exponential rational function method is considered. To observe wave distributions in periodic and singular sense, dynamical behaviour modulus of solutions are also archived. Strain conditions for validity of results obtained in this paper are also reported.

A Systematic Literature Review and Bibliometric Analysis of Ophthalmology and COVID-19 Research

This review is proposed to summarize the updates on COVID-19 and ophthalmology along with the bibliometric features of articles that have been published since the beginning of the COVID-19 outbreak. The databases, including PubMed, Scopus, and Web of Science, were searched using "Coronavirus," "COVID-19," "SARS-CoV-2," "pandemic," "ophthalmology," "ophthalmic," and "eye" keywords. All published articles except commentaries, errata, and corrigenda up to April 2021 were included. Titles and abstracts were screened, and ophthalmology-focused articles were collected. The bibliographic information of the articles, such as the name and country of the first author, type of study, date of publication, language, and journal name, were extracted. Included studies were assessed using the Joanna Briggs Institute (JBI) critical appraisal checklist. After systematic searching, 2,669 distinct articles were screened by title/abstract, and 1,174 ophthalmology-focused articles were selected to be reviewed. Ophthalmology-focused publications accounted for less than 0.5 percent of the total COVID-19-related articles. Most of the articles were published in the Indian Journal of Ophthalmology, and the main publication type was "original article." Almost 88% of the publications were in English. There was a decline in the publication rate during the initial months of 2021 compared with the middle and last months of 2020. Most of the publications were affiliated with the United States of America. However, Singapore and the United Kingdom were the countries with the highest number of publications after population adjustment. Furthermore, a comprehensive review on major topics including SARS-CoV-2 ocular tropism, ophthalmic manifestations, ocular complications due to COVID-19 treatment strategies, the pandemic effect on ophthalmology care and operations, myopia progression during the pandemic, and telemedicine was conducted.

Physician perceptions of surveillance: Wearables, Apps, and Chatbots for COVID-19

Background and Purpose

To characterize the global physician community's opinions on the use of digital tools for COVID-19 public health surveillance and self-surveillance.

Materials and Methods

Cross-sectional, random, stratified survey done on Sermo, a physician networking platform, between September 9 and 15, 2020. We aimed to sample 1000 physicians divided among the USA, EU, and rest of the world. The survey questioned physicians on the risk-benefit ratio of digital tools, as well as matters of data privacy and trust.

Statistical Analysis Used

Descriptive statistics examined physicians' characteristics and opinions by age group, gender, frontline status, and geographic region. ANOVA, t-test, and Chi-square tests with P < 0.05 were viewed as qualitatively different. As this was an exploratory study, we did not adjust for small cell sizes or multiplicity. We used JMP Pro 15 (SAS), as well as Protobi.

Results

The survey was completed by 1004 physicians with a mean (standard deviation) age of 49.14 (12) years. Enthusiasm was highest for self-monitoring smartwatches (66%) and contact tracing apps (66%) and slightly lower (48-56%) for other tools. Trust was highest for health providers (68%) and lowest for technology companies (30%). Most respondents (69.8%) felt that loosening privacy standards to fight the pandemic would lead to misuse of privacy in the future.

Conclusion

The survey provides foundational insights into how physicians think of surveillance.

The psychological mechanism of internet information processing for post-treatment evaluation

Digital healthcare has been greatly benefiting the public health system, especially during the COVID-19 pandemic. In digital healthcare, information communication through the Internet is crucial. The current study explores how patients' accessibility and trust in Internet information influence their decisions and ex-post assessment of healthcare providers by employing the Bayesian Mindsponge Framework (BMF) on a dataset of 1,459 Vietnamese patients. We find that patients’ accessibility to Internet information positively affects the perceived sufficiency of information for choosing a healthcare provider, and their trust in the information intensifies this effect. Internet information accessibility is negatively associated with post-treatment assessment of healthcare providers, and trust also moderates this effect. Moreover, patients considering professional reputation important while making a decision are more likely to regard their choices as optimal, whereas patients considering services important have contradicting tendencies. Based on these findings, a concern about the risk of eroding trust toward Internet sources about healthcare information is raised. Thus, quality control and public trust-building measures need to be taken to improve the effectiveness of healthcare-related communication through the Internet and facilitate the implementation of digital healthcare.

Metaverse and Virtual Health Care in Ophthalmology: Opportunities and Challenges

ABSTRACT

The outbreak of the coronavirus disease 2019 has further increased the urgent need for digital transformation within the health care settings, with the use of artificial intelligence/deep learning, internet of things, telecommunication network/virtual platform, and blockchain. The recent advent of metaverse, an interconnected online universe, with the synergistic combination of augmented, virtual, and mixed reality described several years ago, presents a new era of immersive and real-time experiences to enhance human-to-human social interaction and connection. In health care and ophthalmology, the creation of virtual environment with three-dimensional (3D) space and avatar, could be particularly useful in patient-fronting platforms (eg, telemedicine platforms), operational uses (eg, meeting organization), digital education (eg, simulated medical and surgical education), diagnostics, and therapeutics. On the other hand, the implementation and adoption of these emerging virtual health care technologies will require multipronged approaches to ensure interoperability with real-world virtual clinical settings, user-friendliness of the technologies and clinical efficiencies while complying to the clinical, health economics, regulatory, and cybersecurity standards. To serve the urgent need, it is important for the eye community to continue to innovate, invent, adapt, and harness the unique abilities of virtual health care technology to provide better eye care worldwide.

Evaluating the impact of a digital leadership programme on national digital priorities: a mixed methods study

OBJECTIVES

This study aimed to determine the impact of the United Kingdom's National Health Service Digital Academy (NHSDA) Digital Health Leadership course on high-level recommendations in digital preparedness and the development of a proficient leadership to oversee digital transformation, which has been a longstanding priority within the NHS.

DESIGN

A mixed methods study incorporating an online questionnaire, in-depth interviews and focus groups that were then analysed through a thematic analysis, underpinned by a constructivist approach.

SETTINGS

An online mixed methods study of a defined cohort of participants who had completed the NHSDA course.

PARTICIPANTS

26 participants were recruited to the study, of whom 50% were clinicians, 26.9% in management and 19.2% in data science. All had completed the 2-year NHSDA programme in Digital Health Leadership more than 6 months prior.

RESULTS

Interviews and focus groups elicited two key areas of impact of the course: loco-regional digitisation and the development of a network of change agents. The dissertation project had direct effects on local digital transformation efforts. Most of these projects focused on clinician (11.7%) or service user (10.3%) engagement, as oppose to de novo digital processes (9.4%). The development of a network of digital leaders has facilitated communication between organisations and improved the efficiency of the national digital infrastructure.

CONCLUSIONS

A bespoke course incorporating a dissertation of practice model for digital health leaders can have broader impact for the attainment of digital priorities. This includes helping trusts to successfully adopt digital solutions, as well as fostering shared organisational learning. These influences, however, are mediated by resource and cultural barriers, which continue to hinder transformation efforts.

The road to successful people-centric research in rare diseases: the web-based case study of the Immunology and Congenital Disorders of Glycosylation questionnaire (ImmunoCDGQ)

Background

Congenital Disorders of Glycosylation (CDG) are a complex family of rare metabolic diseases. Robust clinical data collection faces many hurdles, preventing full CDG biological and clinical comprehension. Web-based platforms offer privileged opportunities for biomedical data gathering, and participant recruitment, particularly in rare diseases. The immunology and CDG electronic (e-) questionnaire (ImmunoCDGQ) explores this paradigm, proposing a people-centric framework to advance health research and participant empowerment.

Objective

The objectives of this study were to: (1) Describe and characterize the ImmunoCDGQ development, engagement, recruitment, participation, and result dissemination strategies; (2) To critically compare this framework with published literature and making recommendations.

Methods

An international, multistakeholder people-centric approach was initiated to develop and distribute the ImmunoCDGQ, a multi-lingual e-questionnaire able to collect immune-related data directly from patients and family caregivers. An adapted version was produced and distributed among the general “healthy” population (ImmunoHealthyQ), serving as the control group. Literature screening was performed to identify and analyze comparable studies.

Results

The ImmunoCDGQ attained high participation and inclusion rates (94.6%, 209 out of 221). Comparatively to the control, CDG participants also showed higher and more variable questionnaire completion times as well as increased English version representativeness. Additionally, 20% of the CDG group (42 out of 209) chose not to complete the entire questionnaire in one go. Conditional logic structuring guided participant data provision and accurate data analysis assignment. Multi-channel recruitment created sustained engagement with Facebook emerging as the most followed social media outlet. Still, most included ImmunoCDGQ questionnaires (50.7%, 106 out of 209) were submitted within the first month of the project’s launch. Literature search and analysis showed that most e-questionnaire-based studies in rare diseases are author-built (56.8%, 25 out of 44), simultaneously addressing medical and health-related quality of life (HRQoL) and/or information needs (79.5%, 35 out of 44). Also, over 68% of the studies adopt multi-platform recruitment (30 out of 44) actively supported by patient organizations (52.3%, 23 out of 44).

Conclusions

The ImmunoCDGQ, its methodology and the CDG Community served as models for health research, hence paving a successful and reproducible road to people-centricity in biomedical research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-022-02286-w.

Future challenges in rheumatology – is telemedicine the solution?

The COVID-19 pandemic has become an unprecedented facilitator of rapid telehealth expansion within rheumatology. Due to demographic shifts and workforce shortages in the future, new models of rheumatology care will be expected to emerge, with a growing footprint of telehealth interventions. Telehealth is already being used to monitor patients with rheumatic diseases and initial studies show good results in terms of safety and disease progression. It is being used as a tool for appointment prioritization and triage, and there is good evidence for using telehealth in rehabilitation, patient education and self-management interventions. Electronic patient-reported outcomes (ePROs) offer a number of long-term benefits and opportunities, and a routine collection of ePROs also facilitates epidemiological research that can inform future healthcare delivery. Telehealth solutions should be developed in close collaboration with all stakeholders, and the option of a telehealth visit must not deprive patients of the possibility to make use of a conventional ‘face-to-face’ visit. Future studies should especially focus on optimal models for rheumatology healthcare delivery to patients living in remote areas who are unable to use or access computer technology, and other patient groups at risk for disparity due to technical inequity and lack of knowledge.

Real-world evaluation of rapid and laboratory-free COVID-19 triage for emergency care: external validation and pilot deployment of artificial intelligence driven screening

Background

Uncertainty in patients' COVID-19 status contributes to treatment delays, nosocomial transmission, and operational pressures in hospitals. However, the typical turnaround time for laboratory PCR remains 12–24 h and lateral flow devices (LFDs) have limited sensitivity. Previously, we have shown that artificial intelligence-driven triage (CURIAL-1.0) can provide rapid COVID-19 screening using clinical data routinely available within 1 h of arrival to hospital. Here, we aimed to improve the time from arrival to the emergency department to the availability of a result, do external and prospective validation, and deploy a novel laboratory-free screening tool in a UK emergency department.

Methods

We optimised our previous model, removing less informative predictors to improve generalisability and speed, developing the CURIAL-Lab model with vital signs and readily available blood tests (full blood count [FBC]; urea, creatinine, and electrolytes; liver function tests; and C-reactive protein) and the CURIAL-Rapide model with vital signs and FBC alone. Models were validated externally for emergency admissions to University Hospitals Birmingham, Bedfordshire Hospitals, and Portsmouth Hospitals University National Health Service (NHS) trusts, and prospectively at Oxford University Hospitals, by comparison with PCR testing. Next, we compared model performance directly against LFDs and evaluated a combined pathway that triaged patients who had either a positive CURIAL model result or a positive LFD to a COVID-19-suspected clinical area. Lastly, we deployed CURIAL-Rapide alongside an approved point-of-care FBC analyser to provide laboratory-free COVID-19 screening at the John Radcliffe Hospital (Oxford, UK). Our primary improvement outcome was time-to-result, and our performance measures were sensitivity, specificity, positive and negative predictive values, and area under receiver operating characteristic curve (AUROC).

Findings

72 223 patients met eligibility criteria across the four validating hospital groups, in a total validation period spanning Dec 1, 2019, to March 31, 2021. CURIAL-Lab and CURIAL-Rapide performed consistently across trusts (AUROC range 0·858–0·881, 95% CI 0·838–0·912, for CURIAL-Lab and 0·836–0·854, 0·814–0·889, for CURIAL-Rapide), achieving highest sensitivity at Portsmouth Hospitals (84·1%, Wilson's 95% CI 82·5–85·7, for CURIAL-Lab and 83·5%, 81·8–85·1, for CURIAL-Rapide) at specificities of 71·3% (70·9–71·8) for CURIAL-Lab and 63·6% (63·1–64·1) for CURIAL-Rapide. When combined with LFDs, model predictions improved triage sensitivity from 56·9% (51·7–62·0) for LFDs alone to 85·6% with CURIAL-Lab (81·6–88·9; AUROC 0·925) and 88·2% with CURIAL-Rapide (84·4–91·1; AUROC 0·919), thereby reducing missed COVID-19 cases by 65% with CURIAL-Lab and 72% with CURIAL-Rapide. For the prospective deployment of CURIAL-Rapide, 520 patients were enrolled for point-of-care FBC analysis between Feb 18 and May 10, 2021, of whom 436 received confirmatory PCR testing and ten (2·3%) tested positive. Median time from arrival to a CURIAL-Rapide result was 45 min (IQR 32–64), 16 min (26·3%) sooner than with LFDs (61 min, 37–99; log-rank p<0·0001), and 6 h 52 min (90·2%) sooner than with PCR (7 h 37 min, 6 h 5 min to 15 h 39 min; p<0·0001). Classification performance was high, with sensitivity of 87·5% (95% CI 52·9–97·8), specificity of 85·4% (81·3–88·7), and negative predictive value of 99·7% (98·2–99·9). CURIAL-Rapide correctly excluded infection for 31 (58·5%) of 53 patients who were triaged by a physician to a COVID-19-suspected area but went on to test negative by PCR.

Interpretation

Our findings show the generalisability, performance, and real-world operational benefits of artificial intelligence-driven screening for COVID-19 over standard-of-care in emergency departments. CURIAL-Rapide provided rapid, laboratory-free screening when used with near-patient FBC analysis, and was able to reduce the number of patients who tested negative for COVID-19 but were triaged to COVID-19-suspected areas.

Funding

The Wellcome Trust, University of Oxford Medical and Life Sciences Translational Fund.

Telemedicine monitoring in the follow-up of kidney transplant recipients: consensus indications from an Italian panel of surgeons and nephrologists after the COVID-19 experience

The quality of follow-up has clearly emerged as a key factor for long-term kidney graft survival. Currently, many clinics are facing difficulties in delivering optimal surveillance because of the increased number and complexity of kidney transplant recipients, and because of the COVID-19 pandemic. Additional ways of performing follow-up visits are needed and telemedicine has emerged as a tool to strengthen patient care intensity. Six Italian transplant surgeons and nephrologists convened via teleconference to develop a consensual model of video visits for the follow-up of kidney transplant recipients. Issues discussed were: profile of eligible patients; assessments that can be carried out; video visit organization and medical professionals involved; supporting tools and implementation. The video visit was consensually recognized as the most relevant for the follow-up of kidney transplant recipients. Eligible patients should have basic electronic devices and the skills to correctly use them and be in clinically stable condition. With the exception of physical and instrumental examination, and kidney biopsy, all other assessments are feasible during a video visit and can be implemented by specific training and use of supporting tools. The video visit model is simple and adaptable to most transplant patients. It is not intended to replace face-to-face examinations, but is an additional tool for improving the intensity of follow-up of kidney transplant recipients, which can be integrated into current monitoring protocols.

A Natural Language Processing Pipeline to Identify COVID-19 Outbreaks from Contact Tracing Interview Forms for Public Health Departments

BACKGROUND

In Wisconsin, COVID-19 case interview forms contain free text fields that need to be mined to identify potential outbreaks for targeted policy making. We developed an automated pipeline to ingest the free text into a pre-trained neural language model to identify businesses and facilities as outbreaks.

OBJECTIVE

We aimed to examine the precision and recall of our natural language processing pipeline against existing outbreaks and potentially new clusters.

METHODS

Data on cases of COVID-19 were extracted from the Wisconsin Electronic Disease Surveillance System (WEDSS) for Dane County between July 1, 2020, and June 30, 2021. Features from the case interview forms were fed into a Bidirectional Encoder Representations from Transformers (BERT) model that was fine-tuned for named entity recognition (NER). We also developed a novel location mapping tool to provide addresses for relevant NERs. Precision and recall were measured against manually verified outbreaks and valid addresses in WEDSS.

RESULTS

There were 46,798 cases of COVID-19 with 4,183,273 total BERT tokens and 15,051 unique tokens. The recall and precision of the NER tool were 0.67 (95 % CI 0.66-0.68) and 0.55 (95 % CI: 0.54-0.57), respectively. For the location mapping tool, the recall and precision were 0.93 (95% CI: 0.92-0.95) and 0.93 (95% CI: 0.92-0.95), respectively. Across monthly intervals, the NER tool identified more potential clusters than were verified in the WEDSS system.

CONCLUSIONS

We developed a novel pipeline of tools that identified existing outbreaks and novel clusters with associated addresses. Our pipeline ingests data from a statewide database and may be deployed to assist local health departments for targeted interventions.

The impact and applications of social media platforms for public health responses before and during COVID-19

Background

 Social media platforms have numerous potential benefits and drawbacks on public health, which have been described in the literature. The COVID-19 pandemic has exposed our limited knowledge regarding the potential health impact of these platforms, which have been detrimental to public health responses in many regions.

Objective

This review aims to highlight a brief history of social media in health care and report its potential negative and positive public health impacts, which have been characterized in the literature.

Methods

 We searched electronic bibliographic databases including PubMed, including Medline and Institute of Electrical and Electronics Engineers Xplore, from December 10, 2015, to December 10, 2020. We screened the title and abstracts and selected relevant reports for review of full text and reference lists. These were analyzed thematically and consolidated into applications of social media platforms for public health.

Results

 The positive and negative impact of social media platforms on public health are catalogued on the basis of recent research in this report. These findings are discussed in the context of improving future public health responses and incorporating other emerging digital technology domains such as artificial intelligence. However, there is a need for more research with pragmatic methodology that evaluates the impact of specific digital interventions to inform future health policy.

Conclusions

 Recent research has highlighted the potential negative impact of social media platforms on population health, as well as potentially useful applications for public health communication, monitoring, and predictions. More research is needed to objectively investigate measures to mitigate against its negative impact while harnessing effective applications for the benefit of public health.