The ethics of shared Covid-19 risks: an epistemological framework for ethical health technology assessment of risk in vaccine supply chain infrastructures

An innovative technological infrastructure for managing SARS-CoV-2 data across different cohorts in compliance with General Data Protection Regulation

Background

The ORCHESTRA project, funded by the European Commission, aims to create a pan-European cohort built on existing and new large-scale population cohorts to help rapidly advance the knowledge related to the prevention of the SARS-CoV-2 infection and the management of COVID-19 and its long-term sequelae. The integration and analysis of the very heterogeneous health data pose the challenge of building an innovative technological infrastructure as the foundation of a dedicated framework for data management that should address the regulatory requirements such as the General Data Protection Regulation (GDPR).

Methods

The three participating Supercomputing European Centres (CINECA - Italy, CINES - France and HLRS - Germany) designed and deployed a dedicated infrastructure to fulfil the functional requirements for data management to ensure sensitive biomedical data confidentiality/privacy, integrity, and security. Besides the technological issues, many methodological aspects have been considered: Berlin Institute of Health (BIH), Charité provided its expertise both for data protection, information security, and data harmonisation/standardisation.

Results

The resulting infrastructure is based on a multi-layer approach that integrates several security measures to ensure data protection. A centralised Data Collection Platform has been established in the Italian National Hub while, for the use cases in which data sharing is not possible due to privacy restrictions, a distributed approach for Federated Analysis has been considered. A Data Portal is available as a centralised point of access for non-sensitive data and results, according to findability, accessibility, interoperability, and reusability (FAIR) data principles. This technological infrastructure has been used to support significative data exchange between population cohorts and to publish important scientific results related to SARS-CoV-2.

Conclusions

Considering the increasing demand for data usage in accordance with the requirements of the GDPR regulations, the experience gained in the project and the infrastructure released for the ORCHESTRA project can act as a model to manage future public health threats. Other projects could benefit from the results achieved by ORCHESTRA by building upon the available standardisation of variables, design of the architecture, and process used for GDPR compliance.

Biosecurity in the workplace and a QMS during the COVID-19 pandemic: a survey for Peruvian goods companies

Objectives. This study analyzes the differences between goods companies with a Standard No. ISO 9001:2015 quality management system (QMS) and those without, in terms of implementation of biosecurity measures during the COVID-19 pandemic. The study shows whether having a QMS helped companies to implement the biosecurity measures required to continue operating during a pandemic. Methods. The sample was composed of 145 Peruvian goods companies. The empirical data were collected through a questionnaire sent to company presidents, general managers and department heads. The questionnaire focused on four biosecurity dimensions in the workplace: protocols, preventive actions, biosecurity processes and risk management. Results. The study found that companies with a QMS (Standard No. ISO 9001:2015) significantly differed from companies without in the implementation of three of the four biosecurity dimensions. Conclusions. This study is useful for academia and companies because it identifies the main differences between certified and non-certified companies, in terms of adoption of biosecurity measures. This study highlights the importance of a QMS to respond to hazardous situations like a global health crisis, but also provides useful information for the strategic decision-making process of companies.

Revolutionizing healthcare: the role of artificial intelligence in clinical practice

INTRODUCTION

Healthcare systems are complex and challenging for all stakeholders, but artificial intelligence (AI) has transformed various fields, including healthcare, with the potential to improve patient care and quality of life. Rapid AI advancements can revolutionize healthcare by integrating it into clinical practice. Reporting AI's role in clinical practice is crucial for successful implementation by equipping healthcare providers with essential knowledge and tools.

RESEARCH SIGNIFICANCE

This review article provides a comprehensive and up-to-date overview of the current state of AI in clinical practice, including its potential applications in disease diagnosis, treatment recommendations, and patient engagement. It also discusses the associated challenges, covering ethical and legal considerations and the need for human expertise. By doing so, it enhances understanding of AI's significance in healthcare and supports healthcare organizations in effectively adopting AI technologies.

MATERIALS AND METHODS

The current investigation analyzed the use of AI in the healthcare system with a comprehensive review of relevant indexed literature, such as PubMed/Medline, Scopus, and EMBASE, with no time constraints but limited to articles published in English. The focused question explores the impact of applying AI in healthcare settings and the potential outcomes of this application.

RESULTS

Integrating AI into healthcare holds excellent potential for improving disease diagnosis, treatment selection, and clinical laboratory testing. AI tools can leverage large datasets and identify patterns to surpass human performance in several healthcare aspects. AI offers increased accuracy, reduced costs, and time savings while minimizing human errors. It can revolutionize personalized medicine, optimize medication dosages, enhance population health management, establish guidelines, provide virtual health assistants, support mental health care, improve patient education, and influence patient-physician trust.

CONCLUSION

AI can be used to diagnose diseases, develop personalized treatment plans, and assist clinicians with decision-making. Rather than simply automating tasks, AI is about developing technologies that can enhance patient care across healthcare settings. However, challenges related to data privacy, bias, and the need for human expertise must be addressed for the responsible and effective implementation of AI in healthcare.

The Effects of COVID-19 Pandemic on Adults Living in Turkey and Ways of Coping

This study investigated the experiences and views of adult people living in Turkey about the changes in their usual life during the pandemic, the effects of these changes, difficulties they had, and ways of coping with these difficulties. The study adopted a qualitative design within the scope of the phenomenological approach. The study sample consisted of 449 adults. The findings showed that the changes due to the pandemic were divided into eight categories that included social life, work-life, daily routines, emotions, school life, economy, and cognitive and physiological changes. The participants reported both positive and negative effects of these changes in terms of emotions, cognition, work and school life, physiology, and social life. In the pandemic process, the participants were found to have difficulties in emotions, social life, work-life and economy, physiology, and daily routines. To cope with these difficulties, the participants were found to demonstrate various emotion-focused, problem-focused, and appraisal-focused behaviors.

Challenges and recommendations for wearable devices in digital health: Data quality, interoperability, health equity, fairness

Wearable devices are increasingly present in the health context, as tools for biomedical research and clinical care. In this context, wearables are considered key tools for a more digital, personalised, preventive medicine. At the same time, wearables have also been associated with issues and risks, such as those connected to privacy and data sharing. Yet, discussions in the literature have mostly focused on either technical or ethical considerations, framing these as largely separate areas of discussion, and the contribution of wearables to the collection, development, application of biomedical knowledge has only partially been discussed. To fill in these gaps, in this article we provide an epistemic (knowledge-related) overview of the main functions of wearable technology for health: monitoring, screening, detection, and prediction. On this basis, we identify 4 areas of concern in the application of wearables for these functions: data quality, balanced estimations, health equity, and fairness. To move the field forward in an effective and beneficial direction, we present recommendations for the 4 areas: local standards of quality, interoperability, access, and representativity.

Current state of ethical challenges reported in Saudi Arabia: a systematic review & bibliometric analysis from 2010 to 2021

Background

Over the past few years, five domains of importance about the current state of bioethics in Saudi Arabia have shaped the perspective of most research: doctor-patient relationship, informed consent, do-not-resuscitate, organ donation, and transplantation, medical students’ knowledge and attitudes about medical ethics curriculum. This systematic review aimed to systematically identify, compile, describe and discuss ethical arguments and concepts in the best-studied domains of bioethics in Saudi Arabia and to present cultural, social, educational, and humane perspectives.

Methods

Six databases were searched using Boolean operators (PubMed, Embase, Web of Science, Scopus, CINAHL, Google Scholar) from December 2020–June 2021. The search and report process followed the statement and flowchart of preferred reporting items for systematic reviews and meta-analyses (PRISMA).

Resutls

The search resulted in 1651 articles, of which 82 studies were selected for a final review and assessment. There is a gradual increase in research, whereby a substantial increase was observed from 2017. Most of the published articles focused on ‘Organ Donation & Transplantation’ with 33 articles, followed by ‘Doctor-Patient Relations’ with 18 publications. Most of the published articles were from Central Province (33), followed by Western Province (16). The authorship pattern showed a collaborative approach among researchers. The thematic analysis of keywords analysis showed that ‘Saudi Arabia,’ ‘attitude PHC,’ ‘organ donation,’ ‘knowledge and education,’ and ‘donation’ have been used the most commonly.

Conclusion

This systematic quantitative synthesis is expected to guide researchers, stakeholders, and policymakers about the strengths and gaps in knowledge and attitudes regarding medical ethics in Saudi Arabia, both among the general public and health professionals.

The Influence of the Development of the Internet of Things Industry on the Optimization of the High- and New-Tech Industry Structure under the Wireless Mobile Network

At present, the pressure on China's economic development is increasing day by day due to the profound changes in the internal and external environment. The global economic pattern is undergoing significant changes in terms of the external environment. Adjusting and optimizing the industrial structure will aid in achieving the goal of facilitating transformation through steady growth in the short term. Meanwhile, it will also accelerate sustainable economic development. In this study, the relevant theories of industrial structure optimization are described based on the impact of wireless mobile networks and the Internet of things (IoT) industry. Based on the gray correlation degree, the high- and new-tech industries under the development of the IoT industry are analyzed and the impact of optimization of the high- and new-tech industry structure is investigated. The results show that the development of the IoT industry has driven the development of the high- and new-tech industry. The gray correlation between the development of the IoT industry and the high- and new-tech industry obtained is 0.64, indicating a strong correlation. The average output share of the electronic computer and office equipment manufacturing industries is 47.09%. The average output ratio of the industrial structure optimization of the electronics and communication manufacturing industry is 42.55%. Moreover, the proportion of the output of medical manufacturing and medical equipment and instrument manufacturing industrial structure optimization is small, 15.63% and 10.54%, respectively. The results have significant value in the research on the impact of the development of the IoT industry on the high- and new-tech industry under the wireless mobile network and the effect of its industrial structure optimization.

Evaluating the Potential and Challenges of IoT in Education and Other Sectors during the COVID-19 Pandemic: The Case of Bangladesh

The Internet of Things (IoT) adoption affects different sectors immensely, especially during Covid-19. This study mainly examines the benefits and challenges experienced in Bangladesh's education, and corporate and service sectors while using IoT services during COVID-19. Data collection was performed using a convenient random sampling method and distributing questions online. Two hundred sixty completed responses were analyzed, where 40% of responses were from the education sector, and 60% were from the corporate and service sector. The research method was quantitative and empirical. The study reveals that people find saving time the most potential in education sector, whereas, in the corporate and service sector, the topmost benefit of using IoT services is that it helps strictly maintain physical distance. Conversely, the most significant challenges people face in both sectors are that the IoT increases social distance and reduces individual communication. Nevertheless, people in both sectors have a positive attitude towards using IoT in the future. The findings have practical implications for business professionals, academic scholars, and other associated parties keen to identify IoT impact during the pandemic.

Vaccine Development in the Time of COVID-19: The Relevance of the Risklick AI to Assist in Risk Assessment and Optimize Performance

The 2019 coronavirus (COVID-19) pandemic revealed the urgent need for the acceleration of vaccine development worldwide. Rapid vaccine development poses numerous risks for each category of vaccine technology. By using the Risklick artificial intelligence (AI), we estimated the risks associated with all types of COVID-19 vaccine during the early phase of vaccine development. We then performed a postmortem analysis of the probability and the impact matrix calculations by comparing the 2020 prognosis to the contemporary situation. We used the Risklick AI to evaluate the risks and their incidence associated with vaccine development in the early stage of the COVID-19 pandemic. Our analysis revealed the diversity of risks among vaccine technologies currently used by pharmaceutical companies providing vaccines. This analysis highlighted the current and future potential pitfalls connected to vaccine production during the COVID-19 pandemic. Hence, the Risklick AI appears as an essential tool in vaccine development for the treatment of COVID-19 in order to formally anticipate the risks, and increases the overall performance from the production to the distribution of the vaccines. The Risklick AI could, therefore, be extended to other fields of research and development and represent a novel opportunity in the calculation of production-associated risks.

Epistemological and Bibliometric Analysis of Ethics and Shared Responsibility—Health Policy and IoT Systems

The focus in this paper is placed on shared responsibility and ethics in health policy, specific to Internet of Things (IoT) devices in healthcare systems. The article assesses how the introduction of IoT brings risks to the security of medical systems. The justification for this research emerges from the opportunities emerging from digital technologies for medical services, but also creating a range of new cyber risks in the shared healthcare infrastructure. Such concerns are often not visible to individual departments in an integrated healthcare system. In addition, many healthcare organisations do not possess cyber skills and are faced with barriers to the adoption of smart manufacturing technologies, e.g., cost. These barriers trigger ethical concerns related to responsibility of cyber risks in shared healthcare systems.