Balancing health privacy, health information exchange, and research in the context of the COVID-19 pandemic

Social determinants of health predict readmission following COVID-19 hospitalization: a health information exchange-based retrospective cohort study

Introduction

Since February 2020, over 104 million people in the United States have been diagnosed with SARS-CoV-2 infection, or COVID-19, with over 8.5 million reported in the state of Texas. This study analyzed social determinants of health as predictors for readmission among COVID-19 patients in Southeast Texas, United States.

Methods

A retrospective cohort study was conducted investigating demographic and clinical risk factors for 30, 60, and 90-day readmission outcomes among adult patients with a COVID-19-associated inpatient hospitalization encounter within a regional health information exchange between February 1, 2020, to December 1, 2022.

Results and discussion

In this cohort of 91,007 adult patients with a COVID-19-associated hospitalization, over 21% were readmitted to the hospital within 90  days (n = 19,679), and 13% were readmitted within 30  days (n = 11,912). In logistic regression analyses, Hispanic and non-Hispanic Asian patients were less likely to be readmitted within 90  days (adjusted odds ratio [aOR]: 0.8, 95% confidence interval [CI]: 0.7-0.9, and aOR: 0.8, 95% CI: 0.8-0.8), while non-Hispanic Black patients were more likely to be readmitted (aOR: 1.1, 95% CI: 1.0-1.1, p = 0.002), compared to non-Hispanic White patients. Area deprivation index displayed a clear dose-response relationship to readmission: patients living in the most disadvantaged neighborhoods were more likely to be readmitted within 30 (aOR: 1.1, 95% CI: 1.0-1.2), 60 (aOR: 1.1, 95% CI: 1.2-1.2), and 90  days (aOR: 1.2, 95% CI: 1.1-1.2), compared to patients from the least disadvantaged neighborhoods. Our findings demonstrate the lasting impact of COVID-19, especially among members of marginalized communities, and the increasing burden of COVID-19 morbidity on the healthcare system.

Measuring the willingness to share personal health information: a systematic review

Background

In the age of digitalization and big data, personal health information is a key resource for health care and clinical research. This study aimed to analyze the determinants and describe the measurement of the willingness to disclose personal health information.

Methods

The study conducted a systematic review of articles assessing willingness to share personal health information as a primary or secondary outcome. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis protocol. English and Italian peer-reviewed research articles were included with no restrictions for publication years. Findings were narratively synthesized.

Results

The search strategy found 1,087 papers, 89 of which passed the screening for title and abstract and the full-text assessment.

Conclusion

No validated measurement tool has been developed for willingness to share personal health information. The reviewed papers measured it through surveys, interviews, and questionnaires, which were mutually incomparable. The secondary use of data was the most important determinant of willingness to share, whereas clinical and socioeconomic variables had a slight effect. The main concern discouraging data sharing was privacy, although good data anonymization and the high perceived benefits of sharing may overcome this issue.

Data-Driven Collaboration between Hospitals and Other Healthcare Organisations in Europe During the COVID-19 Pandemic: An Explanatory Sequential Mixed-Methods Study among Mid-Level Hospital Managers

Introduction

Data and digital infrastructure drive collaboration and help develop integrated healthcare systems and services. COVID-19 induced changes to collaboration between healthcare organisations, which previously often happened in fragmented and competitive ways. New collaborative practices relied on data and were crucial in managing coordinated responses to the pandemic. In this study, we explored data-driven collaboration between European hospitals and other healthcare organisations in 2021 by identifying common themes, lessons learned and implications going forward.

Methods

Study participants were recruited from an existing Europe-wide community of mid-level hospital managers. For data collection, we ran an online survey, conducted multi-case study interviews and organised webinars. Data were analysed using descriptive statistics, thematic analysis and cross-case synthesis.

Results

Mid-level hospital managers from 18 European countries reported an increase in data exchange between healthcare organisations during the COVID-19 pandemic. Data-driven collaborative practices were goal-oriented and focused on the optimisation of hospitals' governance functions, innovation in organisational models and improvements to data infrastructure. This was often made possible by temporarily overcoming system complexities, which would otherwise hinder collaboration and innovation. Sustainability of these developments remains a challenge.

Discussion

Mid-level hospital managers form a huge potential of reacting and collaborating when needed, including rapidly setting up novel partnerships and redefining established processes. Major post-COVID unmet medical needs are linked to hospital care provision, including diagnostic and therapeutic backlogs. Tackling these will require rethinking of the position of hospitals within healthcare systems, including their role in care integration.

Conclusion

Learning from COVID-19-induced developments in data-driven collaboration between hospitals and other healthcare organisations is important to address systemic barriers, sustain resilience and further build transformative capacity to help build better integrated healthcare systems.

Impact of the COVID-19 Pandemic on Mental Health and Lifestyle in Thai Occupational Therapy Students: A Mixed Method Study

The impacts of the COVID-19 pandemic have led to global reports of hazards to mental health. However, reports regarding lifestyle changes due to the COVID-19 pandemic are lacking. Using a convergent mixed methods design, we conducted individual interviews with twelve occupational therapy students and interpreted the results by content analysis. We completed a survey of Thai Sensory Patterns Assessment (TSPA) concerning perspectives from occupational therapy students (n = 99). They identified two major themes: (i) adaptive responses were consistent with areas of occupation during the COVID-19 pandemic; (ii) multidimensional challenges were related to sensory patterns of purposeful and meaningful activities. The participants reported both positive and negative impacts of the COVID-19 pandemic on their lives. It had both positive and negative effects on the lifestyle of students affected by the COVID-19 pandemic. The positive effect was that most students learned better ways to protect and care for themselves. During the COVID-19 pandemic, occupational therapy students were most concerned about their online learning activities, economic problems, isolation from society, and lifestyle. The negative effects of this include stress, anxiety, loneliness, frustration, boredom, and exhaustion for occupational therapy students. As an impact of the COVID-19 pandemic, occupational therapy students adapted to new lifestyles and experienced mental health issues related to their studies, families, friends, economics, social climate, and future job opportunities. Educators may use the findings of this study to prevent negative impacts on mental health and promote academic achievement in the future, as well as general well-being, efficacy, and empowerment of students in the new normal post-COVID-19 pandemic era.

Blockchain Framework for Secure COVID-19 Pandemic Data Handling and Protection

COVID-19 pandemic caused global epidemic infections, which is one of the most severe infections in human medical history. In the absence of proper medications and vaccines, handling the pandemic has been challenging for governments and major health facilities. Additionally, tracing COVID-19 cases and handling data generated from the pandemic are also extremely challenging. Data privacy access and collection are also a challenge when handling COVID-19 data. Blockchain technology provides various features such as decentralization, anonymity, cryptographic security, smart contracts, and a distributed framework that allows users and entities to handle COVID-19 data better. Since the outbreak has made the moral crisis in the clinical and administrative centers worse than any other that has resulted in the decline in the supply of the exact information, however, it is vital to provide fast and accurate insight into the situation. As a result of all these concerns, this study emphasizes the need for COVID-19 data processing to acquire aspects such as data security, data integrity, real-time data handling, and data management to provide patients with all benefits from which they had been denied owing to misinformation. Hence, the management of COVID-19 data through the use of the blockchain framework is crucial. Therefore, this paper illustrates how blockchain technology can be implemented in the COVID-19 data handling process. The paper also proposes a framework with three main layers: data collection layer; data access and privacy layer; and data storage layer.

Transforming Health Data to Actionable Information: Recent Progress and Future Opportunities in Health Information Exchange

OBJECTIVES

Provide a systematic review of literature pertaining to health information exchange (HIE) since 2018. Summarize HIE-associated literature for most frequently occurring topics, as well as within the context of the COVID-19 pandemic and health equity. Finally, provide recommendations for how HIE can advance the vision of a digital healthcare ecosystem.

METHODS

A computer program was developed to mediate a literature search of primary literature indexed in MEDLINE that was: (1) indexed with "Health Information Exchange" MeSH descriptor as a major topic; and (2) published between January 2018 and December 2021. Frequency of MeSH descriptors was then used to identify and to rank topics associated with the retrieved literature. COVID-19 literature was identified using the general COVID-19 PubMed Clinical Query filter. Health equity literature was identified using additional MeSH descriptor-based searches. The retrieved literature was then reviewed and summarized.

RESULTS

A total of 256 articles were retrieved and reviewed for this survey. The major thematic areas summarized were: (1) Information Dissemination; (2) Delivery of Health Care; (3) Hospitals; (4) Hospital Emergency Service; (5) COVID-19; (6) Health Disparities; and (7) Computer Security and Confidentiality. A common theme across all areas examined for this survey was the maturity of HIE to support data-driven healthcare delivery. Recommendations were developed based on opportunities identified across the reviewed literature.

CONCLUSIONS

HIE is an essential advance in next generation healthcare delivery. The review of the recent literature (2018-2021) indicates that successful HIE improves healthcare delivery, often resulting in improved health outcomes. There remain major opportunities for expanded use of HIE, including the active engagement of clinical and patient stakeholders. The maturity of HIE reflects the maturity of the biomedical informatics and health data science fields.

Standardizing, Harmonizing, and Protecting Data Collection to Broaden the Impact of COVID-19 Research: The Rapid Acceleration of Diagnostics-Underserved Populations (RADx-up) Initiative

Objective

The Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) program is a consortium of community-engaged research projects with the goal of increasing access to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) tests in underserved populations. To accelerate clinical research, common data elements (CDEs) were selected and refined to standardize data collection and enhance cross-consortium analysis.

Materials and Methods

The RADx-UP consortium began with more than 700 CDEs from the National Institutes of Health (NIH) CDE Repository, Disaster Research Response (DR2) guidelines, and the PHENotypes and eXposures (PhenX) Toolkit. Following a review of initial CDEs, we made selections and further refinements through an iterative process that included live forums, consultations, and surveys completed by the first 69 RADx-UP projects.

Results

Following a multistep CDE development process, we decreased the number of CDEs, modified the question types, and changed the CDE wording. Most research projects were willing to collect and share demographic NIH Tier 1 CDEs, with the top exception reason being a lack of CDE applicability to the project. The NIH RADx-UP Tier 1 CDE with the lowest frequency of collection and sharing was sexual orientation.

Discussion

We engaged a wide range of projects and solicited bidirectional input to create CDEs. These RADx-UP CDEs could serve as the foundation for a patient-centered informatics architecture allowing the integration of disease-specific databases to support hypothesis-driven clinical research in underserved populations.

Conclusion

A community-engaged approach using bidirectional feedback can lead to the better development and implementation of CDEs in underserved populations during public health emergencies.

Responding to COVID-19 Through Interhospital Resource Coordination: A Mixed-Methods Evaluation

OBJECTIVES

The COVID-19 pandemic stressed hospital operations, requiring rapid innovations to address rise in demand and specialized COVID-19 services while maintaining access to hospital-based care and facilitating expertise. We aimed to describe a novel hospital system approach to managing the COVID-19 pandemic, including multihospital coordination capability and transfer of COVID-19 patients to a single, dedicated hospital.

METHODS

We included patients who tested positive for SARS-CoV-2 by polymerase chain reaction admitted to a 12-hospital network including a dedicated COVID-19 hospital. Our primary outcome was adherence to local guidelines, including admission risk stratification, anticoagulation, and dexamethasone treatment assessed by differences-in-differences analysis after guideline dissemination. We evaluated outcomes and health care worker satisfaction. Finally, we assessed barriers to safe transfer including transfer across different electronic health record systems.

RESULTS

During the study, the system admitted a total of 1209 patients. Of these, 56.3% underwent transfer, supported by a physician-led System Operations Center. Patients who were transferred were older (P = 0.001) and had similar risk-adjusted mortality rates. Guideline adherence after dissemination was higher among patients who underwent transfer: admission risk stratification (P < 0.001), anticoagulation (P < 0.001), and dexamethasone administration (P = 0.003). Transfer across electronic health record systems was a perceived barrier to safety and reduced quality. Providers positively viewed our transfer approach.

CONCLUSIONS

With standardized communication, interhospital transfers can be a safe and effective method of cohorting COVID-19 patients, are well received by health care providers, and have the potential to improve care quality.

A Comprehensive Review of Artificial Intelligence in Prevention and Treatment of COVID-19 Pandemic

The unprecedented outbreak of the Corona Virus Disease 2019 (COVID-19) pandemic has seriously affected numerous countries in the world from various aspects such as education, economy, social security, public health, etc. Most governments have made great efforts to control the spread of COVID-19, e.g., locking down hard-hit cities and advocating masks for the population. However, some countries and regions have relatively poor medical conditions in terms of insufficient medical equipment, hospital capacity overload, personnel shortage, and other problems, resulting in the large-scale spread of the epidemic. With the unique advantages of Artificial Intelligence (AI), it plays an extremely important role in medical imaging, clinical data, drug development, epidemic prediction, and telemedicine. Therefore, AI is a powerful tool that can help humans solve complex problems, especially in the fight against COVID-19. This study aims to analyze past research results and interpret the role of Artificial Intelligence in the prevention and treatment of COVID-19 from five aspects. In this paper, we also discuss the future development directions in different fields and prove the validity of the models through experiments, which will help researchers develop more efficient models to control the spread of COVID-19.

The Rapid Development of Virtual Care Tools in Response to COVID-19: Case Studies in Three Australian Health Services

BACKGROUND

News of the impact of COVID-19 around the world delivered a brief opportunity for Australian health services to plan new ways of delivering care to large numbers of people while maintaining staff safety through greater physical separation. The rapid pivot to telemedicine and virtual care provided immediate and longer term benefits; however, such rapid-cycle development also created risks.

OBJECTIVE

The aim of this study was to understand the sociotechnical aspects of the rapid-cycle development of seven different COVID-19 virtual care tools, and to identify enablers, barriers, and risks at three health services in Victoria, Australia.

METHODS

A qualitative, embedded, multiple case study design was adopted. Researchers from three health services collaborated with university researchers who were independent from those health services to gather and analyze structured interview data from key people involved in either clinical or technical aspects of designing and deploying seven different virtual care tools.

RESULTS

The overall objectives of each health service reflected the international requirements for managing large numbers of patients safely but remotely and for protecting staff. However, the governance, digital maturity, and specific use cases at each institution shaped the methodology and specific outcomes required. Dependence on key individuals and their domain knowledge within an existing governance framework generally enabled rapid deployment, but sometimes posed barriers. Existing relationships with technical service developers enabled strong solutions, which in some cases were highly scalable. Conventional project methodologies such as steering committees, scope, budget control, tight functional specification, consumer engagement and codesign, universal accessibility, and postimplementation evaluation were ignored almost universally in this environment.

CONCLUSIONS

These three health services took a variety of approaches to the rapid-cycle development of virtual care tools to meet their urgent needs for triaging and remote monitoring during the first year of the COVID-19 pandemic. Their experiences provided insights into many social and technical barriers and enablers to the development of virtual care tools. If these are addressed proactively, they will improve clinical governance and technical management of future virtual care. Some changes can be made within individual health services, while others entail health system policy reforms. Enhancing the environment for virtual care tool design and implementation now will yield returns not only during future health emergencies but also in many more routine care settings.

Jordanian views regarding sharing of medical data for research: A cross-sectional study during COVID-19 pandemic

PURPOSE

In the current study, the views of Jordanian regarding sharing medical reports for research purposes were investigated during the COVID-19 pandemic. In addition, motivators and barriers regarding sharing of medical records were examined.

METHODS

This observational survey-based cross-sectional study was conducted using an electronic questionnaire during the COVID-19 pandemic (second half of 2020). The questionnaire link was disseminated through two social media platforms (WhatsApp and Facebook), targeting Jordanian adults (age >18 years).

RESULTS

In this study, 1,194 participants agreed to complete the study survey. Results showed that 58.3% of them (n = 696) reported to be willing to share their medical data. while 17.6% of the participants (n = 210) showed hesitancy to share their medical information. The most important motivators as perceived by the study participants were helping other patients who have similar health conditions (n = 995, 83.3%). Moreover, fearing from stigma (n = 753, 63.1%), and the lack of confidence in data security and privacy (n = 728, 61.0%) were among the main barriers preventing participants from sharing their information. Finally, results showed that participants with higher educational level (bachelor or higher) (OR = 0.299, P<0.001), or those living in center of Jordan (OR = 0.270, P<0.001) showed a lower tendency to share their medical data. While participants those who have shared data before showed a higher tendency to share their medical data (OR = 2.524, P<0.001).

CONCLUSION

In this study, many of the participants had a positive attitude towards sharing biomedical data for scientific research during the COVID-19 pandemic, many had doubts in the control over their data. Thus, policymakers and data users should address the concerns and values of patients and understand their preferences in favor of an ethically scrupulous use of data in research.

Telehealth: Opportunities to Improve Access, Quality, and Cost in Pediatric Care

The use of telehealth technology to connect with patients has expanded significantly over the past several years, particularly in response to the global coronavirus disease 2019 pandemic. This technical report describes the present state of telehealth and its current and potential applications. Telehealth has the potential to transform the way care is delivered to pediatric patients, expanding access to pediatric care across geographic distances, leveraging the pediatric workforce for care delivery, and improving disparities in access to care. However, implementation will require significant efforts to address the digital divide to ensure that telehealth does not inadvertently exacerbate inequities in care. The medical home model will continue to evolve to use telehealth to provide high-quality care for children, particularly for children and youth with special health care needs, in accordance with current and evolving quality standards. Research and metric development are critical for the development of evidence-based best practices and policies in these new models of care. Finally, as pediatric care transitions from traditional fee-for-service payment to alternative payment methods, telehealth offers unique opportunities to establish value-based population health models that are financed in a sustainable manner.

Unsupervised characterization of Major Depressive Disorder medication treatment pathways

Learning health systems have the ability to systematically evaluate treatments and treatment pathways. Characterization of treatment pathways can enhance a health system's ability to perform systematic evaluation to improve care quality. In this study we use a Long-Short Term Memory (LSTM) autoencoder model to systematically characterize treatment pathways in a prevalent phenotype-Major Depressive Disorder (MDD). LSTM autoencoder models generate representations of medication treatment pathways that account for temporality and complex interactions. Patients with similar pathways are grouped with K-means clustering. Clusters are characterized by analysis of medication utilization sequences and trends, as well as clinical features, such as demographics, outcomes and comorbidities. Cluster characterization identifies endotypes of MDD including acute MDD, moderate-chronic MDD and severe-chronic, but managed MDD.

Achieving data privacy for decision support systems in times of massive data sharing

The world is suffering from a new pandemic of Covid-19 that is affecting human lives. The collection of records for Covid-19 patients is necessary to tackle that situation. The decision support systems (DSS) are used to gather that records. The researchers access the patient's data through DSS and perform predictions on the severity and effect of the Covid-19 disease; in contrast, unauthorized users can also access the data for malicious purposes. For that reason, it is a challenging task to protect Covid-19 patient data. In this paper, we proposed a new technique for protecting Covid-19 patients' data. The proposed model consists of two folds. Firstly, Blowfish encryption uses to encrypt the identity attributes. Secondly, it uses Pseudonymization to mask identity and quasi-attributes, then all the data links with one another, such as the encrypted, masked, sensitive, and non-sensitive attributes. In this way, the data becomes more secure from unauthorized access.

AND-rPPG: A novel denoising-rPPG network for improving remote heart rate estimation

Heart rate (HR) estimation is an essential physiological parameter in the field of biomedical imaging. Remote Photoplethysmography (r-PPG) is a pathbreaking development in this field wherein the PPG signal is extracted from non-contact face videos. In the COVID-19 pandemic, rPPG plays a vital role for doctors and patients to perform telehealthcare. Existing rPPG methods provide incorrect HR estimation when face video contains facial deformations induced by facial expression. These methods process the entire face and utilize the same knowledge to mitigate different noises. It limits the performance of these methods because different facial expressions induce different noise characteristics depending on the facial region. Another limitation is that these methods neglect the facial expression for denoising even though it is the prominent noise source in temporal signals. These issues are mitigated in this paper by proposing a novel HR estimation method AND-rPPG, that is, A Novel Denoising-rPPG. We initiate the utilization of Action Units (AUs) for denoising temporal signals. Our denoising network models the temporal signals better than sequential architectures and mitigate the AUs-based (or face expression-based) noises effectively. The experiments performed on publicly available datasets reveal that our proposed method outperforms state-of-the-art HR estimation methods, and our denoising model can be easily integrated with existing methods to improve their HR estimation.

Shared Access to Patient Portals for Older Adults: Implications for Privacy and Digital Health Equity (Preprint)

Growing reliance on the patient portal as a mainstream modality in health system interactions necessitates prioritizing digital health equity through systems-level strategies that acknowledge and support all persons. Older adults with physical, cognitive, sensory, and socioeconomic vulnerabilities often rely on the involvement of family and friends in managing their health, but the role of these care partners in health information technology is largely undefined and poorly understood. This viewpoint article discusses challenges and opportunities of systematic engagement of care partners through shared access to the patient portal that have been amplified in the context of the COVID-19 outbreak and recent implementation of federal information blocking rules to promote information transparency alongside broader shifts toward care delivery innovation and population aging. We describe implementation considerations and the promise of granular, role-based privacy controls in addressing the nuanced and dynamic nature of individual information sharing preferences and fostering person- and family-centered care delivery.

Pediatric Telehealth in the COVID-19 Pandemic Era and Beyond

The coronavirus disease 2019 (COVID-19) pandemic led to an unprecedented demand for health care at a distance, and telehealth (the delivery of patient care using telecommunications technology) became more widespread. Since our 2018 state-of-the-art review assessing the pediatric telehealth landscape, there have been many changes in technology, policy, payment, and physician and patient acceptance of this care model. Clinical best practices in telehealth, on the other hand, have remained unchanged during this time, with the primary difference being the need to implement them at scale.Because of the pandemic, underlying health system weaknesses that have previously challenged telehealth adoption (including inequitable access to care, unsustainable costs in a fee-for-service system, and a lack of quality metrics for novel care delivery modalities) were simultaneously exacerbated. Higher volume use has provided a new appreciation of how patients from underrepresented backgrounds can benefit from or be disadvantaged by the shift toward virtual care. Moving forward, it will be critical to assess which COVID-19 telehealth changes should remain in place or be developed further to ensure children have equitable access to high-quality care.With this review, we aim to (1) depict today's pediatric telehealth practice in an era of digital disruption; (2) describe the people, training, processes, and tools needed for its successful implementation and sustainability; (3) examine health equity implications; and (4) critically review current telehealth policy as well as future policy needs. The American Academy of Pediatrics (AAP) is continuing to develop policy, specific practice tips, training modules, checklists, and other detailed resources, which will be available later in 2021.

Interorganizational Knowledge Sharing to Establish Digital Health Learning Ecosystems: Qualitative Evaluation of a National Digital Health Transformation Program in England

Background

The English Global Digital Exemplar (GDE) program is one of the first concerted efforts to create a digital health learning ecosystem across a national health service.

Objective

This study aims to explore mechanisms that support or inhibit the exchange of interorganizational digital transformation knowledge.

Methods

We conducted a formative qualitative evaluation of the GDE program. We used semistructured interviews with clinical, technical, and managerial staff; national program managers and network leaders; nonparticipant observations of knowledge transfer activities through attending meetings, workshops, and conferences; and documentary analysis of policy documents. The data were thematically analyzed by drawing on a theory-informed sociotechnical coding framework. We used a mixture of deductive and inductive methods, supported by NVivo software, to facilitate coding.

Results

We conducted 341 one-on-one and 116 group interviews, observed 86 meetings, and analyzed 245 documents from 36 participating provider organizations. We also conducted 51 high-level interviews with policy makers and vendors; performed 77 observations of national meetings, workshops, and conferences; and analyzed 80 national documents. Formal processes put in place by the GDE program to initiate and reinforce knowledge transfer and learning have accelerated the growth of informal knowledge networking and helped establish the foundations of a learning ecosystem. However, formal networks were most effective when supported by informal networking. The benefits of networking were enhanced (and costs reduced) by geographical proximity, shared culture and context, common technological functionality, regional and strategic alignments, and professional agendas.

Conclusions

Knowledge exchange is most effective when sustained through informal networking driven by the mutual benefits of sharing knowledge and convergence between group members in their organizational and technological setting and goals. Policy interventions need to enhance incentives and reduce barriers to sharing across the ecosystem, be flexible in tailoring formal interventions to emerging needs, and promote informal knowledge sharing.

The Clinical Information Systems Response to the COVID-19 Pandemic

OBJECTIVE

The year 2020 was predominated by the coronavirus disease 2019 (COVID-19) pandemic. The objective of this article is to review the areas in which clinical information systems (CIS) can be and have been utilized to support and enhance the response of healthcare systems to pandemics, focusing on COVID-19.

METHODS

PubMed/MEDLINE, Google Scholar, the tables of contents of major informatics journals, and the bibliographies of articles were searched for studies pertaining to CIS, pandemics, and COVID-19 through October 2020. The most informative and detailed studies were highlighted, while many others were referenced.

RESULTS

CIS were heavily relied upon by health systems and governmental agencies worldwide in response to COVID-19. Technology-based screening tools were developed to assist rapid case identification and appropriate triaging. Clinical care was supported by utilizing the electronic health record (EHR) to onboard frontline providers to new protocols, offer clinical decision support, and improve systems for diagnostic testing. Telehealth became the most rapidly adopted medical trend in recent history and an essential strategy for allowing safe and effective access to medical care. Artificial intelligence and machine learning algorithms were developed to enhance screening, diagnostic imaging, and predictive analytics - though evidence of improved outcomes remains limited. Geographic information systems and big data enabled real-time dashboards vital for epidemic monitoring, hospital preparedness strategies, and health policy decision making. Digital contact tracing systems were implemented to assist a labor-intensive task with the aim of curbing transmission. Large scale data sharing, effective health information exchange, and interoperability of EHRs remain challenges for the informatics community with immense clinical and academic potential. CIS must be used in combination with engaged stakeholders and operational change management in order to meaningfully improve patient outcomes.

CONCLUSION

Managing a pandemic requires widespread, timely, and effective distribution of reliable information. In the past year, CIS and informaticists made prominent and influential contributions in the global response to the COVID-19 pandemic.

Privacy-Oriented Technique for COVID-19 Contact Tracing (PROTECT) Using Homomorphic Encryption: Design and Development Study

BACKGROUND

Various techniques are used to support contact tracing, which has been shown to be highly effective against the COVID-19 pandemic. To apply the technology, either quarantine authorities should provide the location history of patients with COVID-19, or all users should provide their own location history. This inevitably exposes either the patient's location history or the personal location history of other users. Thus, a privacy issue arises where the public good (via information release) comes in conflict with privacy exposure risks.

OBJECTIVE

The objective of this study is to develop an effective contact tracing system that does not expose the location information of the patient with COVID-19 to other users of the system, or the location information of the users to the quarantine authorities.

METHODS

We propose a new protocol called PRivacy Oriented Technique for Epidemic Contact Tracing (PROTECT) that securely shares location information of patients with users by using the Brakerski/Fan-Vercauteren homomorphic encryption scheme, along with a new, secure proximity computation method.

RESULTS

We developed a mobile app for the end-user and a web service for the quarantine authorities by applying the proposed method, and we verified their effectiveness. The proposed app and web service compute the existence of intersections between the encrypted location history of patients with COVID-19 released by the quarantine authorities and that of the user saved on the user's local device. We also found that this contact tracing smartphone app can identify whether the user has been in contact with such patients within a reasonable time.

CONCLUSIONS

This newly developed method for contact tracing shares location information by using homomorphic encryption, without exposing the location information of patients with COVID-19 and other users. Homomorphic encryption is challenging to apply to practical issues despite its high security value. In this study, however, we have designed a system using the Brakerski/Fan-Vercauteren scheme that is applicable to a reasonable size and developed it to an operable format. The developed app and web service can help contact tracing for not only the COVID-19 pandemic but also other epidemics.

Overcoming gaps: regional collaborative to optimize capacity management and predict length of stay of patients admitted with COVID-19

Objective

Ensuring an efficient response to COVID-19 requires a degree of inter-system coordination and capacity management coupled with an accurate assessment of hospital utilization including length of stay (LOS). We aimed to establish optimal practices in inter-system data sharing and LOS modeling to support patient care and regional hospital operations.

Materials and Methods

We completed a retrospective observational study of patients admitted with COVID-19 followed by 12-week prospective validation, involving 36 hospitals covering the upper Midwest. We developed a method for sharing de-identified patient data across systems for analysis. From this, we compared 3 approaches, generalized linear model (GLM) and random forest (RF), and aggregated system level averages to identify features associated with LOS. We compared model performance by area under the ROC curve (AUROC).

Results

A total of 2068 patients were included and used for model derivation and 597 patients for validation. LOS overall had a median of 5.0 days and mean of 8.2 days. Consistent predictors of LOS included age, critical illness, oxygen requirement, weight loss, and nursing home admission. In the validation cohort, the RF model (AUROC 0.890) and GLM model (AUROC 0.864) achieved good to excellent prediction of LOS, but only marginally better than system averages in practice.

Conclusion

Regional sharing of patient data allowed for effective prediction of LOS across systems; however, this only provided marginal improvement over hospital averages at the aggregate level. A federated approach of sharing aggregated system capacity and average LOS will likely allow for effective capacity management at the regional level.

Using Electronic Health Records to Mitigate Workplace Burnout Among Clinicians During the COVID-19 Pandemic: Field Study in Iran

Background

The COVID-19 pandemic spread worldwide in 2020. Notably, in the countries dealing with massive casualties, clinicians have worked in new conditions characterized by a heavy workload and a high risk of being infected. The issue of clinician burnout during the pandemic has attracted considerable attention in health care research. Electronic health records (EHRs) provide health care workers with several features to meet a health system’s clinical needs.

Objective

We aim to examine how the use of EHR features affects the burnout of clinicians working in hospitals that have special wards for confirmed COVID-19 cases.

Methods

Using an online survey, we collected data from 368 physicians, physician assistants, and nurses working in six hospitals that have implemented EHRs in the city of Tehran in Iran. We used logistic regression to assess the association between burnout and awareness of EHR features, EHR system usability, concerns about COVID-19, technology solutions, hospital technology interventions, hospital preparedness, and professional efficacy adjusted for demographic and practice characteristics.

Results

The primary outcome of our study was self-reported burnout during the COVID-19 pandemic. Of the 368 respondents, 36% (n=134) reported having at least one symptom of burnout. Participants indicated that the leading cause of EHR-related stress is inadequate training for using technology (n=159, 43%), followed by having less face-to-face time with patients (n=140, 38%). Positive perceptions about the EHR’s ease of use were associated with lower odds of burnout symptoms. More interventions, such as clear communication of regulations; transparency in policies, expectations, and goals regarding the use of technology in the clinical workflow; and hospital preparedness to cope with the challenges of the pandemic, were associated with lower odds of burnout.

Conclusions

The use of EHR applications, hospital pandemic preparation programs, and transparent technology-related policies and procedures throughout the epidemic can be substantial mitigators of technology-based stress and clinician burnout. Hospitals will then be better positioned to devise or modify technology-related policies and procedures to support physicians’ and nurses’ well-being during the COVID-19 pandemic. Training programs, transparency in communications of regulations, and developing a clear channel for informing clinicians of changes in policies may help reduce burnout symptoms among physicians and nurses during a pandemic. Providing easily accessible mentorship through teleconsultation and 24-hour available information technology support may also help to mitigate the odds of burnout.

Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality

Understanding sociodemographic, behavioral, clinical, and laboratory risk factors in patients diagnosed with COVID-19 is critically important, and requires building large and diverse COVID-19 cohorts with both retrospective information and prospective follow-up. A large Health Information Exchange (HIE) in Southeast Texas, which assembles and shares electronic health information among providers to facilitate patient care, was leveraged to identify COVID-19 patients, create a cohort, and identify risk factors for both favorable and unfavorable outcomes. The initial sample consists of 8,874 COVID-19 patients ascertained from the pandemic's onset to June 12th, 2020 and was created for the analyses shown here. We gathered demographic, lifestyle, laboratory, and clinical data from patient's encounters across the healthcare system. Tobacco use history was examined as a potential risk factor for COVID-19 fatality along with age, gender, race/ethnicity, body mass index (BMI), and number of comorbidities. Of the 8,874 patients included in the cohort, 475 died from COVID-19. Of the 5,356 patients who had information on history of tobacco use, over 26% were current or former tobacco users. Multivariable logistic regression showed that the odds of COVID-19 fatality increased among those who were older (odds ratio = 1.07, 95% CI 1.06, 1.08), male (1.91, 95% CI 1.58, 2.31), and had a history of tobacco use (2.45, 95% CI 1.93, 3.11). History of tobacco use remained significantly associated (1.65, 95% CI 1.27, 2.13) with COVID-19 fatality after adjusting for age, gender, and race/ethnicity. This effort demonstrates the impact of having an HIE to rapidly identify a cohort, aggregate sociodemographic, behavioral, clinical and laboratory data across disparate healthcare providers electronic health record (HER) systems, and follow the cohort over time. These HIE capabilities enable clinical specialists and epidemiologists to conduct outcomes analyses during the current COVID-19 pandemic and beyond. Tobacco use appears to be an important risk factor for COVID-19 related death.

The applicability of blockchain technology in healthcare contexts to contain COVID-19 challenges

Purpose

Blockchain technology, a key feature of the fourth industrial revolution, is receiving widespread attention and exploration around the world. Taking the coronavirus pandemic as an example, the purpose of this study to examine the application of blockchain technology from the perspective of epidemic prevention and control.

Design/methodology/approach

Exploring multiple case studies in the Chinese context at various stages of deployment, this study documents a framework about how some of the major challenges associated with COVID-19 can be alleviated by leveraging blockchain technology.

Findings

The case studies and framework presented herein show that utilization of blockchain acts as an enabler to facilitate the containment of several COVID-19 challenges. These challenges include the following: complications associated with medical data sharing; breaches of patients' data privacy; absence of real-time monitoring tools; counterfeit medical products and non-credible suppliers; fallacious insurance claims; overly long insurance claim processes; misappropriations of funds; and misinformation, rumors and fake news.

Originality/value

Blockchain is ushering in a new era of innovation that will lay the foundation for a new paradigm in health care. As there are currently insufficient studies pertaining to real-life case studies of blockchain and COVID-19 interaction, this study adds to the literature on the role of blockchain technology in epidemic control and prevention.

Identifying Barriers to and Opportunities for Telehealth Implementation Amidst the COVID-19 Pandemic by Using a Human Factors Approach: A Leap Into the Future of Health Care Delivery?

The extensive uptake of telehealth has considerably transformed health care delivery since the beginning of the COVID-19 pandemic and has imposed tremendous challenges to its large-scale implementation and adaptation. Given the shift in paradigm from telehealth as an alternative mechanism of care delivery to telehealth as an integral part of the health system, it is imperative to take a systematic approach to identifying barriers to, opportunities for, and the overall impact of telehealth implementation amidst the current pandemic. In this work, we apply a human factors framework, the Systems Engineering Initiative for Patient Safety model, to guide our holistic analysis and discussion of telehealth implementation, encompassing the health care work system, care processes, and outcomes.

Utilizing a health information exchange to facilitate COVID-19 VA primary care follow-up for Veterans diagnosed in the community

The use of alerts from the Bronx RHIO, a health information exchange (HIE) to identify James J. Peters VAMC patients diagnosed with COVID-19 in the community was described to facilitate COVID-19 VA primary care follow-up. COVID-19 hospitalization and testing alerts were delivered on a Bronx RHIO facility report. VA COVID-19 follow-up care by telephone and video was guided by local COVID-19 clinical pathways, electronic health record (EHR) templates, and tracking through a database. VA received 180 RHIO alerts for 111 unique patients, and 88 had positive non-VA testing from March to June 2020. 41% of the 88 had non-VA admissions and 23% died. 63% received VA primary care follow-up of COVID-19 symptoms documented by custom EHR templates. The HIE identified 11% of the facility COVID-19 patients. HIE alerts can be used to identify facility COVID-19 patients diagnosed in the community and facilitate follow-up by their VA primary care teams.

What the Coronavirus Disease 2019 (COVID-19) Pandemic Has Reinforced: The Need for Accurate Data

The COVID-19 pandemic has challenged the United States’ existing national public health informatics infrastructure. This report details the factors that have contributed to COVID-19 data inaccuracies and reporting delays and their effect on the modeling and monitoring of the COVID-19 pandemic.

Health Information System's Responses to COVID-19 Pandemic in China: A National Cross-sectional Study

OBJECTIVE

After the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, Chinese hospitals and health information technology (HIT) vendors collaborated to provide comprehensive information technology support for pandemic prevention and control. This study aims to describe the responses from the health information systems (HIS) to the COVID-19 pandemic and provide empirical evidence in the application of emerging health technologies in China.

METHODS

This observational descriptive study utilized a nationally representative, cross-sectional survey of hospitals in China (N = 1,014) from 30 provincial administrative regions across the country. Participants include hospital managers, hospital information workers, and health care providers.

RESULTS

Among all the responses, the most popular interventions and applications include expert question-and-answer sessions and science popularization (61.74%) in online medical consultation, online appointment registration (58.97%) in online medical service, and remote consultation (75.15%) in telehealth service. A total of 63.71% of the participating hospitals expanded their fever clinics during the pandemic, 15.38% hospitals used new or upgraded mobile ward rounds systems, and 44.68% hospitals applied online self-service systems. Challenges and barriers include protecting network information security (57.00%) since some hospitals experienced cybersecurity incidents. 71.79% participants hope to shorten wait time and optimize the treatment process. Health care workers experienced increased amount of work during the pandemic, while hospital information departments did not experience significant changes in their workload.

CONCLUSION

In the process of fighting against the COVID-19, hospitals have widely used traditional and emerging novel HITs. These technologies have strengthened the capacity of prevention and control of the pandemic and provided comprehensive information technology support while also improving accessibility and efficiency of health care delivery.

Use of electronic health records to support a public health response to the COVID-19 pandemic in the United States: a perspective from 15 academic medical centers

Our goal is to summarize the collective experience of 15 organizations in dealing with uncoordinated efforts that result in unnecessary delays in understanding, predicting, preparing for, containing, and mitigating the COVID-19 pandemic in the US. Response efforts involve the collection and analysis of data corresponding to healthcare organizations, public health departments, socioeconomic indicators, as well as additional signals collected directly from individuals and communities. We focused on electronic health record (EHR) data, since EHRs can be leveraged and scaled to improve clinical care, research, and to inform public health decision-making. We outline the current challenges in the data ecosystem and the technology infrastructure that are relevant to COVID-19, as witnessed in our 15 institutions. The infrastructure includes registries and clinical data networks to support population-level analyses. We propose a specific set of strategic next steps to increase interoperability, overall organization, and efficiencies.

Ethics and informatics in the age of COVID-19: challenges and recommendations for public health organization and public policy

The COVID-19 pandemic response in the United States has exposed significant gaps in information systems and processes that prevent timely clinical and public health decision-making. Specifically, the use of informatics to mitigate the spread of SARS-CoV-2, support COVID-19 care delivery, and accelerate knowledge discovery bring to the forefront issues of privacy, surveillance, limits of state powers, and interoperability between public health and clinical information systems. Using a consensus-building process, we critically analyze informatics-related ethical issues in light of the pandemic across 3 themes: (1) public health reporting and data sharing, (2) contact tracing and tracking, and (3) clinical scoring tools for critical care. We provide context and rationale for ethical considerations and recommendations that are actionable during the pandemic and conclude with recommendations calling for longer-term, broader change (beyond the pandemic) for public health organization and policy reform.

Information Seeking on Covid-19 Pandemic: Care Providers' Experience at the University of Gondar Teaching Hospital, Northwest of Ethiopia

Background

During the pandemic, information is inevitable and important, and having knowledge on pertinent information is very crucial for health-care professionals in order to deliver sustainable and quality health services to their clients, and to combat the virus. Therefore, the aim of this study was to assess the health-care providers' information seeking behavior on COVID-19 pandemic.

Methods

A descriptive cross-sectional study had conducted among 291 respondents. The participant’s characteristics were presented using frequency and percentage. The association between the independent and dependent variables was explained using chi-squared test.

Results

Out of the 291 respondents, 207 (71.1%) of them had sought information on COVID-19 pandemic. The association between the gender and educational status with the outcome variable was found insignificant. Age (χ²=10.6, P=0.011), respondent’s working unit (χ²=33.7, P<0.001), profession (χ²=12.7, P=0.013), taking computer training (χ²=17.44, P=0.000), computer access at work place (χ²=7.28, P=0.007), internet access at work place (χ²=22.2, P<0.001), and frequency of internet use (χ²=17.63, P<0.001) were found significant with COVID-19 information seeking.

Conclusion

Information seeking behavior was positively associated with computer access, computer training, internet access and frequency of use. Therefore, comprehensive package is required to build the capacity of care providers on computer-related skills. Besides, institutions need to have internet and computer access.

Compositional cyber-physical epidemiology of COVID-19

The COVID-19 pandemic has posed significant challenges globally. Countries have adopted different strategies with varying degrees of success. Epidemiologists are studying the impact of government actions using scenario analysis. However, the interactions between the government policy and the disease dynamics are not formally captured. We, for the first time, formally study the interaction between the disease dynamics, which is modelled as a physical process, and the government policy, which is modelled as the adjoining controller. Our approach enables compositionality, where either the plant or the controller could be replaced by an alternative model. Our work is inspired by the engineering approach for the design of Cyber-Physical Systems. Consequently, we term the new framework Compositional Cyber-Physical Epidemiology. We created different classes of controllers and applied these to control the disease in New Zealand and Italy. Our controllers closely follow government decisions based on their published data. We not only reproduce the pandemic progression faithfully in New Zealand and Italy but also show the tradeoffs produced by differing control actions.

A novel extended approach under hesitant fuzzy sets to design a framework for assessing the key challenges of digital health interventions adoption during the COVID-19 outbreak

In recent years, Digital Technologies (DTs) are becoming an inseparable part of human lives. Thus, many scholars have conducted research to develop new tools and applications. Processing information, usually in the form of binary code, is the main task in DTs, which is happening through many devices, including computers, smartphones, robots, and applications. Surprisingly, the role of DTs has been highlighted in people's life due to the COVID-19 pandemic. There are several different challenges to implement and intervene in DTs during the COVID-19 outbreak; therefore, the present study extended a new fuzzy approach under Hesitant Fuzzy Set (HFS) approach using Stepwise Weight Assessment Ratio Analysis (SWARA) and Weighted Aggregated Sum Product Assessment (WASPAS) method to evaluate and rank the critical challenges of DTs intervention to control the COVID-19 outbreak. In this regard, a comprehensive survey using literature and in-depth interviews have been carried out to identify the challenges under the SWOT (Strengths, Weaknesses, Opportunities, Threats) framework. Moreover, the SWARA procedure is applied to analyze and assess the challenges to DTs intervention during the COVID-19 outbreak, and the WASPAS approach is utilized to rank the DTs under hesitant fuzzy sets. Further, to demonstrate the efficacy and practicability of the developed framework, an illustrative case study has been analyzed. The results of this study found that Health Information Systems (HIS) was ranked as the first factor among other factors followed by a lack of digital knowledge, digital stratification, economic interventions, lack of reliable data, and cost inefficiency In conclusion, to confirm the steadiness and strength of the proposed framework, the obtained outputs are compared with other methods.

COVID-19 Contact-Tracing Technology: Acceptability and Ethical Issues of Use

BACKGROUND

The contact-tracing COVID-19 technology allows for tracing people that come in contact to individuals with COVID-19 wherever they are located. The number of tracing COVID-19 infection technology and devices is rapidly increasing. This has prompted many researchers to study the acceptability and ethical issues related to the implementation of such technology.

AIM

The purpose of this study was to determine the acceptability of COVID-19 contact-tracing technology and ethical issues of use.

METHODS

A cross-sectional questionnaire-based study was used. The target population was Jordanian adults (>18 years). The survey was distributed to a convenience sample of 2000 general public in Jordan.

RESULTS

The results found that the number of people who accept to use COVID-19 contact-tracing technology was 71.6%. However, the percentage of people who were using this technology was 37.8. The main ethical concerns for many of participants were privacy, voluntariness, and beneficence of the data. Only income and living area were predictors for acceptability and use of tracing technology (p≤ 0.01).

CONCLUSION

The majority of Jordanians accept the implementation of contact-tracing technology for COVID-19 infection. Among ethical concerns of the implementation of such technology were privacy, beneficence and voluntariness.

IMPLICATIONS

The results of this study would help in improving the state of science regarding acceptability to use contact-tracing technology for health purposes. Moreover, the present findings provide evidence of predictors of acceptance and ethical concerns among Jordanian population about COVID-19 contact-tracing technology.

Digital advantage in the COVID-19 response: perspective from Canada's largest integrated digitalized healthcare system

The SARS-CoV-2 pandemic has challenged healthcare systems worldwide. Uncertainty of transmission, limitations of physical healthcare system infrastructure and supplies as well as workforce shortages require dynamic adaption of resource deployment to manage rapidly evolving care demands, ideally based on real time data for the entire population. Moreover, shut down of traditional face-to-face care infrastructure requires rapid deployment of virtual health care options to avoid collapse of health organizations. The Alberta Electronic Health Record Information System is one of the largest population based comprehensive electronic medical record (EMR) installations. Alberta's long standing solid telehealth hardware-, training-, provider remuneration- and legislation infrastructure has enabled quick transition to virtual healthcare. Virtual health services including asynchronous secure clinical communications, real-time virtual care via messaging, telephony or video conferencing (telehealth) and ancillary functions like triage, scheduling, documentation and reporting, the previously established virtual hospital program with home monitoring, virtual health assessments, medication review, education and support for patients and families and coordination between family doctors, specialists and other health team members help to control viral transmission, protect healthcare personnel and save supplies. Moreover, rapid launch of online screening and triage tools to guide testing and isolation, online result sharing, infected patient and contact tracing including a smartphone exposure tracking application (ABTraceTogether), electronic best practice alerts and decision support tools, test and treatment order sets for standardized COVID-19 management, continuous access to population level real-time data to inform healthcare provider, public health and government decisions have become key factors in the management of a global crisis in Alberta.

COVID-19 & an NGO and university developed interactive portal: a perspective from Iran

On 19 February 2020, Iran reported the initial cases of novel coronavirus (2019-nCoV). As of 21 March 2020, Iran had reported 175,927 COVID-19 cases, including 8425 deaths. One of the best approaches for responding to COVID-19 is rapid detection, early isolation, and quick treatment of the disease. Studies have stated that information technology (IT) is a powerful tool for detecting, tracking, and responding to pandemic diseases. Despite the importance of IT, a lack of efficient use of information technology capacity was observed after the emergence of the new cases of COVID-19 in Iran. A web-portal can integrate different services and technologies and can support interaction between non-governmental organizations (NGO) and universities. NGOs can provide services for public health utilizing technology and its advancements. One of the important duties of these organizations is to inform and provide integrated services to the general public. An interactive portal is one of the advanced technologies that these organizations can use for health management. Medical sciences of universities play a vital surveillance role for enhancing the performance quality of NGOs. A web-portal can be a collaboration tool between health-related NGOs and medical sciences of universities. In this study, an interactive portal was developed by NGOs and a university. NGOs under the supervision and participation of Tabriz University of Medical Sciences’ Center for Social Factors Research in COVID-19 management division of this portal separated classified information into two sections, informatics and services. This portal is accessible to the general public, patients, service providers, and, importantly, policymakers and presents educational and medical research information to all users. For patients and the general public in high-risk environments, increasing information security, reducing confusion regarding finding needed information, and facilitating communication are only part of the portal’s benefit. It seems that web-portal capacity is needed to control COVID-19 in the digital age. The collaboration of academic and university bodies in the context of health portals can play key roles for coverage of the COVID-19 pandemic.

Telemedicine, COVID-19, and disparities: Policy implications

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COVID-19 has resulted in a dramatic increase in the use of telemedicine but this could worsen disparities.

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We review recent telemedicine policy changes and their implications regarding disparities.

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We also discuss what systems can do to improve access to telemedicine and to best meet the needs of underserved patients.

While the rapid expansion of telemedicine in response to the COVID-19 pandemic highlights the impressive ability of health systems to adapt quickly to new complexities, it also raises important concerns about how to implement these novel modalities equitably. As the healthcare system becomes increasingly virtual, it risks widening disparities among marginalized populations who have worse health outcomes at baseline and limited access to the resources necessary for the effective use of telemedicine. In this article, we review recent policy changes and outline important recommendations that governments and health care systems can adopt to improve access to telemedicine and to tailor the use of these technologies to best meet the needs of underserved patients. We suggest that by making health equity integral to the implementation of telemedicine now, it will help to ensure that all can benefit from its use going forward and that this will be increasingly integral to care delivery.

Belief in a COVID-19 Conspiracy Theory as a Predictor of Mental Health and Well-Being of Health Care Workers in Ecuador: Cross-Sectional Survey Study

BACKGROUND

During the coronavirus disease (COVID-19) pandemic, social media platforms have become active sites for the dissemination of conspiracy theories that provide alternative explanations of the cause of the pandemic, such as secret plots by powerful and malicious groups. However, the association of individuals' beliefs in conspiracy theories about COVID-19 with mental health and well-being issues has not been investigated. This association creates an assessable channel to identify and provide assistance to people with mental health and well-being issues during the pandemic.

OBJECTIVE

Our aim was to provide the first evidence that belief in conspiracy theories regarding the COVID-19 pandemic is a predictor of the mental health and well-being of health care workers.

METHODS

We conducted a survey of 252 health care workers in Ecuador from April 10 to May 2, 2020. We analyzed the data regarding distress and anxiety caseness with logistic regression and the data regarding life and job satisfaction with linear regression.

RESULTS

Among the 252 sampled health care workers in Ecuador, 61 (24.2%) believed that the virus was developed intentionally in a lab; 82 (32.5%) experienced psychological distress, and 71 (28.2%) had anxiety disorder. Compared to health care workers who were not sure where the virus originated, those who believed the virus was developed intentionally in a lab were more likely to report psychological distress and anxiety disorder and to have lower levels of job satisfaction and life satisfaction.

CONCLUSIONS

This paper identifies belief in COVID-19 conspiracy theories as an important predictor of distress, anxiety, and job and life satisfaction among health care workers. This finding will enable mental health services to better target and provide help to mentally vulnerable health care workers during the ongoing COVID-19 pandemic.

Belief in a COVID-19 Conspiracy Theory as a Predictor of Mental Health and Well-Being of Health Care Workers in Ecuador: Cross-Sectional Survey Study

Background

During the coronavirus disease (COVID-19) pandemic, social media platforms have become active sites for the dissemination of conspiracy theories that provide alternative explanations of the cause of the pandemic, such as secret plots by powerful and malicious groups. However, the association of individuals’ beliefs in conspiracy theories about COVID-19 with mental health and well-being issues has not been investigated. This association creates an assessable channel to identify and provide assistance to people with mental health and well-being issues during the pandemic.

Objective

Our aim was to provide the first evidence that belief in conspiracy theories regarding the COVID-19 pandemic is a predictor of the mental health and well-being of health care workers.

Methods

We conducted a survey of 252 health care workers in Ecuador from April 10 to May 2, 2020. We analyzed the data regarding distress and anxiety caseness with logistic regression and the data regarding life and job satisfaction with linear regression.

Results

Among the 252 sampled health care workers in Ecuador, 61 (24.2%) believed that the virus was developed intentionally in a lab; 82 (32.5%) experienced psychological distress, and 71 (28.2%) had anxiety disorder. Compared to health care workers who were not sure where the virus originated, those who believed the virus was developed intentionally in a lab were more likely to report psychological distress and anxiety disorder and to have lower levels of job satisfaction and life satisfaction.

Conclusions

This paper identifies belief in COVID-19 conspiracy theories as an important predictor of distress, anxiety, and job and life satisfaction among health care workers. This finding will enable mental health services to better target and provide help to mentally vulnerable health care workers during the ongoing COVID-19 pandemic.

Transmission dynamics: Data sharing in the COVID-19 era

Problem

The current coronavirus disease 2019 (COVID‐19) pandemic underscores the need for building and sustaining public health data infrastructure to support a rapid local, regional, national, and international response. Despite a historical context of public health crises, data sharing agreements and transactional standards do not uniformly exist between institutions which hamper a foundational infrastructure to meet data sharing and integration needs for the advancement of public health.

Approach

There is a growing need to apply population health knowledge with technological solutions to data transfer, integration, and reasoning, to improve health in a broader learning health system ecosystem. To achieve this, data must be combined from healthcare provider organizations, public health departments, and other settings. Public health entities are in a unique position to consume these data, however, most do not yet have the infrastructure required to integrate data sources and apply computable knowledge to combat this pandemic.

Outcomes

Herein, we describe lessons learned and a framework to address these needs, which focus on: (a) identifying and filling technology “gaps”; (b) pursuing collaborative design of data sharing requirements and transmission mechanisms; (c) facilitating cross‐domain discussions involving legal and research compliance; and (d) establishing or participating in multi‐institutional convening or coordinating activities.

Next steps

While by no means a comprehensive evaluation of such issues, we envision that many of our experiences are universal. We hope those elucidated can serve as the catalyst for a robust community‐wide dialogue on what steps can and should be taken to ensure that our regional and national health care systems can truly learn, in a rapid manner, so as to respond to this and future emergent public health crises.

Telehealth Solutions for In-hospital Communication with Patients Under Isolation During COVID-19

The coronavirus disease 2019 (COVID-19) pandemic is a public health crisis that has quickly overwhelmed our healthcare system. It has led to significant shortages in personal protective equipment (PPE), ventilators, and intensive care unit beds across the nation. As the initial entry point for patients with suspected COVID illness, emergency departments (ED) have had to adapt quickly to prioritize the safety of patients and providers while still delivering optimal, timely patient care. COVID-19 has presented many challenges for the ED that also extend to all inpatient services. Some of these key challenges are the fundamental tasks of communicating with patients in respiratory isolation while minimizing PPE usage and enabling all patients who have been affected by hospitals' visitor restrictions to connect with their families. We discuss the design principles behind implementing a robust in-hospital telehealth system for patient-provider and patient-family communication, provide a review of the strengths and weaknesses of potential videoconferencing options, and deliver concise, step-by-step guides for setting up a secure, low-cost, user-friendly solution that can be rapidly deployed.

Using Information Technology to Manage the COVID-19 Pandemic: Development of a Technical Framework Based on Practical Experience in China

BACKGROUND

The coronavirus disease (COVID-19) epidemic poses an enormous challenge to the global health system, and governments have taken active preventive and control measures. The health informatics community in China has actively taken action to leverage health information technologies for epidemic monitoring, detection, early warning, prevention and control, and other tasks.

OBJECTIVE

The aim of this study was to develop a technical framework to respond to the COVID-19 epidemic from a health informatics perspective.

METHODS

In this study, we collected health information technology-related information to understand the actions taken by the health informatics community in China during the COVID-19 outbreak and developed a health information technology framework for epidemic response based on health information technology-related measures and methods.

RESULTS

Based on the framework, we review specific health information technology practices for managing the outbreak in China, describe the highlights of their application in detail, and discuss critical issues to consider when using health information technology. Technologies employed include mobile and web-based services such as Internet hospitals and Wechat, big data analyses (including digital contact tracing through QR codes or epidemic prediction), cloud computing, Internet of things, Artificial Intelligence (including the use of drones, robots, and intelligent diagnoses), 5G telemedicine, and clinical information systems to facilitate clinical management for COVID-19.

CONCLUSIONS

Practical experience in China shows that health information technologies play a pivotal role in responding to the COVID-19 epidemic.

Repurposing current therapeutics for treating COVID-19: A vital role of prescription records data mining

Since its outbreak in late 2019, the SARS‐Cov‐2 pandemic already infected over 3.7 million people and claimed more than 250,000 lives globally. At least 1 year may take for an approved vaccine to be in place, and meanwhile millions more could be infected, some with fatal outcome. Over thousand clinical trials with COVID‐19 patients are already listed in ClinicalTrials.com, some of them for assessing the utility of therapeutics approved for other conditions. However, clinical trials take many months, and are typically done with small cohorts. A much faster and by far more efficient method for rapidly identifying approved therapeutics that can be repurposed for treating COVID‐19 patients is data mining their past and current electronic health and prescription records for identifying drugs that may protect infected individuals from severe COVID‐19 symptoms. Examples are discussed for applying health and prescription records for assessing the potential repurposing (repositioning) of angiotensin receptor blockers, estradiol, or antiandrogens for reducing COVID‐19 morbidity and fatalities. Data mining of prescription records of COVID‐19 patients will not cancel the need for conducting controlled clinical trials, but could substantially assist in trial design, drug choice, inclusion and exclusion criteria, and prioritization. This approach requires a strong commitment of health provides for open collaboration with the biomedical research community, as health provides are typically the sole owners of retrospective drug prescription records.