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General Data Protection Regulation (GDPR) of the European Union (EU) was passed to protect data privacy. Though the GDPR intended to address issues related to data privacy in the EU, it created an extra-territorial effect through Articles 3, 45 and 46. Extra-territorial effect refers to the application or the effect of local laws and regulations in another country. Lawmakers around the globe passed or intensified their efforts to pass laws to have personal data privacy covered so that they meet the adequacy requirement under Articles 45–46 of GDPR while providing comprehensive legislation locally. This study aims to analyze the Malaysian and Saudi Arabian legislation on health data privacy and their adequacy in meeting GDPR data privacy protection requirements.

The research used a systematic literature review, legal content analysis and comparative analysis to critically analyze the health data protection in Malaysia and Saudi Arabia in comparison with GDPR and to see the adequacy of health data protection that could meet the requirement of EU data transfer requirement.

The finding suggested that the private sector is better regulated in Malaysia than the public sector. Saudi Arabia has some general laws to cover health data privacy in both public and private sector organizations until the newly passed data protection law is implemented in 2024. The finding also suggested that the Personal Data Protection Act 2010 of Malaysia and the Personal Data Protection Law 2022 of Saudi Arabia could be considered “adequate” under GDPR.

The research would be able to identify the key principles that could identify the adequacy of the laws about health data in Malaysia and Saudi Arabia as there is a dearth of literature in this area. This will help to propose suggestions to improve the laws concerning health data protection so that various stakeholders can benefit from it.

This study aims to analyze a conspicuous corpus of literature related to the field of technology-based intensive care research and to develop an architecture model of the future smart intensive care unit (ICU).

Papers related to the topics of electronic health record (EHR), big data, data flow and clinical decision support in ICUs were investigated. These concepts have been analyzed in combination with secondary use of data, prediction models, data standardization and interoperability challenges. Based on the findings, an architecture model evaluated using MIMIC III is proposed.

Research identified issues regarding implementation of systems, data sources, interoperability, management of big data and free text produced in ICUs and lack of accuracy of prediction models. ICU should be treated as part of a greater system, able to intercommunicate with other entities.

The research examines the current needs of ICUs in interoperability and data management. As environment changes dynamically, continuous assessment and evaluation of the model with other ICU databases is required.

The proposed model improves ICUs interoperability in national health system, ICU staff intercommunication, remote access and decision support. Its modular approach ensures that ICUs can have their own particularities and specialisms while ICU functions provide ongoing expertise and training to upgrade its staff.

Along with technology-based ecosystems, healthcare start-ups are expanding multi-fold. On the other hand, underlying uncertainties pose several challenges for these health-tech enterprises at macro-meso-micro level, influencing their business circumstances and profitability. The current study aims to comprehend the macro-, meso- and micro-level barriers that make it difficult for enterprises to set up healthcare technology start-ups. The study also observed the perceived effect of these challenges on firms' performance and cost structure over time. Using the theory of behaviour under uncertainty, the study revealed multiple systemic, sector-related, human and implementation barriers that hinder business growth and lead to uncertainties for health-tech start-ups.

Using a grounded theory approach, the study collected the views of 51 health tech start-ups in the UK using an online participants pool. The data was collected using qualitative data techniques in the form of open-ended essays, and a content analysis using thematic coding process was conducted. The questions centered around the different institutional uncertainties or barriers while setting up or running a healthcare start-up.

The study revealed several macro-, meso- and micro-level barriers these technology-based enterprises perceive in the healthcare industry. These are recognised as systemic barriers, such as lack of funding and procedural issues; sector-related barriers, such as market-related impediments; human barriers, including psychological barriers and resistance to new technology; and implementation barriers, such as operational and personnel issues.

The study used qualitative, open-ended essay techniques to collect the data. Future studies may use a mixed-methods approach to provide holistic insights. The study is conducted in a single developed country, the UK. Future work may expand these findings by comparing developed market challenges with those of emerging markets and by assessing the viewpoints of healthcare start-ups.

This research will assist the healthcare sector and government understand health tech start-up hurdles and uncertainty. Policymakers must assist start-ups and encourage entrepreneurial innovation. Regulating and enabling policies will help. The paper examines start-ups' macro, meso and micro uncertainties. Policymakers promoting sector entrepreneurship must consider these barriers while designing policy guidelines.

The study contributes to the existing literature on technology start-ups, particularly in the healthcare industry, and identifies significant barriers these start-ups face. The study synthesizes research on health-tech start-up uncertainty and bridges the gap between theory and practice by applying empirical findings.

The purpose of this review paper was identifying barriers to the use of telemedicine systems in primary health-care individual level among professionals.

This study used Scopus and PubMed databases for scientific records identification. A systematic review of the literature structured by PRISMA guidelines was conducted on 37 included papers published between 2009 and 2019. A qualitative approach was used to synthesize insights into using telemedicine by primary care professionals.

Three barriers were identified and classified: system quality, data quality and service quality barriers. System complexity in terms of usability, system unreliability, security and privacy concerns, lack of integration and inflexibility of systems-in-use are related to system quality. Data quality barriers are data inaccuracy, data timeliness issues, data conciseness concerns and lack of data uniqueness. Finally, service reliability concerns, lack of technical support and lack of user training have been categorized as service quality barriers.

This review identified and mapped emerging themes of barriers to the use of telemedicine systems. This paper also through a new conceptualization of telemedicine use from perspectives of the primary care professionals contributes to informatics literature and system usage practices.

The main aim of this paper is to describe the potential benefits of enterprise building information models (EBIMs) for health-care institutions. The main research question addressed is how data from EBIM could be leveraged to create value for hospitals beyond design, construction and traditional facility management.

Three different prototypes, which use different technologies in combination with EBIM, are described to illustrate different uses of EBIM within the context of a hospital and health-care operations. The case study approach has been used to present the prototypes.

EBIM data, in combination with other data sources, increases the potential benefits of the data with respect to many health-care-related processes, during the operation of a health-care institution. The benefits of EBIM span beyond the design and construction life cycle phases of a hospital and provide value to a variety of stakeholders in multiple health-care-related processes.

The main limitation of this work is the limited sources of data and information such as the specific methods that were used in the design and development of each of the prototypes and a deeper insight into the design rationale and decisions. Another limitation of this paper is that the findings have not been validated.

This study demonstrates the value of convergence of a number of technologies such as EBIM, data and different types of technologies, throughout the life cycle of a building. This study also highlights the value of building information models (BIMs) data for supporting the design of novel educational and other types of application areas. The practical implications include the value for multiple stakeholders, such as resources planning, fleet and equipment management and contract negotiation. Benefits identified for resource planning can have strategic and financial implications at the management level. For patients, visitors and health-care personnel, there may be reduced infections, cleaner and pleasant facilities as well as a reduction of time to find relevant resources.

Social implications" could be replaced by "For patients, visitors and health-care personnel, there may be cleaner and pleasant facilities and easy navigation support through the hospital. Furthermore, enhanced access to knowledge and information about the artefact and assets in the hospital can enhance learning and knowledge sharing.

This study identifies the lack of research in using BIM with other data for value-added services for multiple stakeholders in the operations phase of a hospital and addresses that research gap.

Deployment of health and safety standards in extremely hazardous work environments such as oil and gas sector, is essential to minimise accidents leaving employees permanently or temporarily incapacitated. The purpose of this research, is to understand why there are frequent accidents in case country's oil and gas sector, with a view to recommend solutions to mitigate problems.

Research methodology involved extensive review of the literature to appreciate background, and current research on typical accidents and safety measures taken at oil and gas construction sites to minimise accidents in a middle east country. Interviews, questionnaires and case stidies were deployed to acquire data which highlighted major reasons for accidents occurrence at oil and gas construction sites, and safety tools and techniques that could reduce accident rate if adopted by companies.

Findings, showed that oil and gas construction projects in case country were prone to health and safety related risks, challenges and accidents due to failure to comply with standards and legislation. Construction site teams and shop floor staff were rarely involved in development of safety policies, and some had no understanding of requirements and procedures underpinning safety during operations. Research recommended rapid application/adoption of international standards underpinned by ISO 45000 series and staff training at all levels. Deployment of robots and use of machine learning technology were suggested to implement risky tasks in the sector.

Research was based on rampant accidents occurring in hazardous oil and gas sector in country studied. Enforcement of health and safety standards, and use of modern tools and techniques were recommended to minimise accident rate.

Despite technological advancements to enhance patient health, the risks of not discovering the correct interactions and trends in digital health are high. Hence, a careful policy is required for health coverage tailored to needs and capacity. Therefore, this study aims to explore the adoption of a cognitive computing decision support system (CCDSS) in the assessment of health-care policymaking and validates it by extending the unified theory of acceptance and use of technology model.

A survey was conducted to collect data from different stakeholders, referred to as the 4Ps, namely, patients, providers, payors and policymakers. Structural equation modelling and one-way ANOVA were used to analyse the data.

The result reveals that the behavioural insight of policymakers towards the assessment of health-care policymaking is based on automatic and reflective systems. Investments in CCDSS for policymaking assessment have the potential to produce rational outcomes. CCDSS, built with quality procedures, can validate whether breastfeeding-supporting policies are mother-friendly.

Health-care policies are used by lawmakers to safeguard and improve public health, but it has always been a challenge. With the adoption of CCDSS, the overall goal of health-care policymaking can achieve better quality standards and improve the design of policymaking.

This study drew attention to how CCDSS as a technology enabler can drive health-care policymaking assessment for each stage and how the technology enabler can help the 4Ps of health-care gain insight into the benefits and potential value of CCDSS by demonstrating the breastfeeding supporting policy.

The purpose of this study is to examine the management perceptions towards calculative practices behind the reconstruction of a mandatory hospital accreditation (HA) system that transforms multiple facets of health-care quality into a single performance index.

This study contributes to the sociology of quantification mobilising the concept of commensuration as a social process to reflect on contemporary changes in managing HA systems. Data are collected adopting a case study of a Spanish public hospital drawing on semi-structured interviews, observation and documentary review.

Findings emphasise a shift from standards’ compliance to a more comprehensive view encouraging continuous quality improvement. Accreditation acts as a tin opener to facilitate external inspection removing contextual differences amongst hospitals and reducing organisational practices into controllable objects. It also reveals underlying ethical concerns as the system was built as a care quality measure that promptly developed into an attainment goal.

The valuable role of HA to enhance quality standards and the limitations resulting from its commensuration practices will be of interest to policymakers, organisational managers and researchers.

Despite a growing emphasis on audit and valuation practices in health care, accounting studies examining the capacity of public hospitals to manage quality improvement are scarce. This study inspires further research on accreditation to overcome commensuration flaws regarding external transparency, evaluation ambiguity and extra incentives.

This paper introduces a new set of equity and rights-based principles for health data governance (HDG) and makes the case for their adoption into global, regional and national policy and practice.

This paper discusses the need for a unified approach to HDG that maximises the value of data for whole populations. It describes the unique process employed to develop a set of HDG principles. The paper highlights lessons learned from the principle development process and proposes steps to incorporate them into data governance policies and practice.

More than 200 individuals from 130 organisations contributed to the development of the HDG principles, which are clustered around three interconnected objectives of protecting people, promoting health value and prioritising equity. The principles build on existing norms and guidelines by bringing a human rights and equity lens to HDG.

The principles offer a strong vision for HDG that reaps the public good benefits of health data whilst safeguarding individual rights. They can be used by governments and other actors as a guide for the equitable collection and use of health data. The inclusive model used to develop the principles can be replicated to strengthen future data governance approaches.

The article describes the first bottom-up effort to develop a set of principles for HDG.