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Blockchain technology enhances information management in healthcare supply chains by securing healthcare information and providing medical resource traceability. However, there is no decision framework to support blockchain implementation for managing information, especially in emerging economies’ healthcare supply chains. This paper develops a hierarchical decision model for implementing blockchain technology for information management in emerging economies’ healthcare supply chains.

This study uses 20 health supply chain experts in Ghana to rank 17 decision criteria for implementing blockchain for healthcare information management using the best-worst method (BWM) multi-criteria decision technique.

The results show that “security” and “privacy,” “infrastructural facility” and “presence of training facilities” are the top three critical factors impacting blockchain adoption in the health supply chain for healthcare information management. Other sub-factors are prioritized.

To implement blockchain effectively to enhance information management in the healthcare supply chain, health institutions, blockchain technology providers and state authorities should concentrate on the highly critical factors extracted from the study.

This is the first study that develops a hierarchical decision model for implementing blockchain technology in emerging economies' health supply chains.

The purpose of this study is to examine the role of artificial intelligence (AI) in transforming the healthcare sector, with a focus on how AI contributes to entrepreneurship and value creation. This study also aims to explore the potential of combining AI with other technologies, such as cloud computing, blockchain, IoMT, additive manufacturing and 5G, in the healthcare industry.

Exploratory qualitative methodology was chosen to analyze 22 case studies from the USA, EU, Asia and South America. The data source was public and specialized podcast platforms.

The findings show that combining technologies can create a competitive advantage for technology entrepreneurs and bring about transitions from simple consumer devices to actionable healthcare applications. The results of this research identified three main entrepreneurship areas: 1. Analytics, including staff reduction, patient prediction and decision support; 2. Security, including protection against cyberattacks and detection of atypical cases; 3. Performance optimization, which, in addition to reducing the time and costs of medical procedures, includes staff training, reducing capital costs and working with new markets.

This study demonstrates how AI can be used with other technologies to cocreate value in the healthcare industry. This study provides a conceptual framework, “AI facilitators – AI achievers,” based on the findings and offer several theoretical contributions to academic literature in technology entrepreneurship and technology management and industry recommendations for practical implication.

Quantifying the performance level of surgeons with digital virtual reality (VR) simulators can help ensure that quality requirements in healthcare are met. In order to better understand integration amongst quality principles, practices and technologies in the adoption and diffusion of VR simulators, the authors applied a technological innovation system (TIS) framework. The purpose of this study is to understand how the adoption and diffusion of VR surgical simulators in a Swedish healthcare context is influenced by various system factors.

In this study, single-case holistic design based on innovation system theory was used to analyse the adoption of digital quality technologies related to surgical performance in Swedish hospitals. The case employs a mixed methods approach triangulating data longitudinally from published documents and expert interviews.

Adoption of digital technologies regarding surgical performance is restricted by system factors relating to inconsistent normative and regulatory requirements for quantified performance criteria to judge surgical expertise. Addressing these systems' weaknesses with evidence-based training programmes can have a significant impact on the further development of the innovation system and can ultimately affect healthcare reliability and quality.

This paper explores quality management (QM) challenges in the context of digital transformation in healthcare. The paper attempts to fill the gap for TIS studies in a healthcare context and highlight the role of innovation function strength along the value chain and in relation to technology cycles to increase the understanding of adoption of digital technologies relating to surgical performance.

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.

Diabetes is regarded as a global epidemic with 382 million people globally suffering from diabetes. It also has major implications on patients’ quality of life. There are also high cost of treatment associated with diabetes for both patient and healthcare provider. Telemonitoring represents an excellent technology opportunity to redefine health care delivery. Using technology for home-based care promises the ability to deliver more cost effective care whilst also enhancing quality of care and patient satisfaction. The paper aims to discuss these issues.

The current research aims to contribute to the methodological design of action research projects in their use to implementation health technologies such as telemonitoring. In particular, it seeks create a model which can be used to demonstrate the efficacy of the use of the action research method as a viable alternative to the traditional randomised control trials methodology currently employed in healthcare.

The paper contributes towards the methodological design to investigate the area of practice making use of the telemonitoring programme within a Victorian Health Services Network using action research.

It intends to address the research problem of the low utilisation of telemonitoring within Monash Health as a whole, and more specifically within the diabetes unit. In this context the research intends to utilise the benefits of telemonitoring to improve clinical outcomes of patients by increasing insulin stabilisation. It is also intended the research organisation benefits by increased efficiency by decreasing clinical workforce time spent on managing patient insulin data.

The purpose of this paper is to better understand how and why adoption and implementation of healthcare IT innovations occur. The authors examine two IT applications, computerised physician order entry (CPOE) and picture archiving and communication systems (PACS) at the meso and micro levels, within the context of the National Programme for IT in the English National Health Service (NHS).

To analyse these multi-level dynamics, the authors blend Rogers’ diffusion of innovations theory (DoIT) with Webster’s sociological critique of technological innovation in medicine and healthcare systems to illuminate a wider range of interacting factors. Qualitative data collected between 2004 and 2006 uses semi-structured, in-depth interviews with 72 stakeholders across four English NHS hospital trusts.

Overall, PACS was more successfully implemented (fully or partially in three out of four trusts) than CPOE (implemented in one trust only). Factors such as perceived benefit to users and attributes of the application – in particular speed, ease of use, reliability and flexibility and levels of readiness – were highly relevant but their influence was modulated through interaction with complex structural and relational issues.

Results reveal that combining contextual system level theories with DoIT increases understanding of real-life processes underpinning implementation of IT innovations within healthcare. They also highlight important drivers affecting success of implementation, including socio-political factors, the social body of practice and degree of “co-construction” between designers and end-users.

The originality of the study partly rests on its methodological innovativeness and its value on critical insights afforded into understanding complex IT implementation programmes.

Advanced Electronic Medical Records (EMR) provide many potential benefits to hospitals. However, because of their broad scope, many stakeholders deal with the EMR and a continuous effort has to be made to keep up with internal and external change. Therefore, hospitals need to deliberately shape their organizational competencies considering the pursuit of alignment, i.e. making sure that the EMR remains optimally aligned with strategies, goals and needs of the hospital and its stakeholders. This paper aims to investigate the evolutionary paths of these alignment competencies and their drivers, from a theoretical perspective of co-evolutionary information systems alignment (COISA).

This paper reports on a longitudinal multiple case study of three Dutch hospitals which each recently implemented an advanced EMR system. The authors conducted 35 in-depth interviews in 2 phases (before and after go-live of the EMR), and studied documentation related to the EMR implementations.

The findings show that each hospital's COISA capability shows a different evolutionary path. However, two of the three case hospitals ended up coordinating part of their COISA capability to an ecosystem level, i.e. they incorporated other hospitals using the same EMR system to coordinate their alignment efforts, either from an operational perspective, or in terms of orchestration and strategy. The found evolutionary paths' key drivers include “stakeholder initiative”, “accumulating experience”, “driving events” and “emerging issues”.

The findings help healthcare practitioners to deliberately shape their organization's COISA capability in pursuit of EMR alignment. Furthermore, the authors add to the knowledge base on co-evolutionary approaches to alignment through the longitudinal approach.

This study aims to provide a picture of the current state of art in the use of big data for decision-making processes for the management of health-care organizations.

A systematic literature review was carried out. The research uses two analyses: descriptive analysis, describing the evolution of citations; keywords; and the ten most influential papers, and bibliometric analysis, for content evaluation, for which a cluster analysis was performed.

A total of 48 articles were selected for bibliographic coupling out of an initial sample of more than 5,000 papers. Of the 48 articles, 29 are linked on the basis of their bibliography. Clustering the 29 articles on the basis of actual content, four research areas emerged: quality of care, quality of service, crisis management and data management.

Health-care organizations believe strongly that big data can become the most effective tool for correctly influencing the decision-making processes. Thus, more and more organizations continue to invest in big data analytics, and the literature on this topic has expanded rapidly. This study seeks to provide a comprehensive picture of the different streams of literature existing, together with gaps in research and future perspectives. The literature is mature enough for an analysis to be made and provide managers with useful insights on opportunities, criticisms and perspectives on the use of big data for health-care organizations. However, to date, there is no comprehensive literature review on the big data analysis in health care. Furthermore, as big data is a “sexy catchphrase,” more clarity on its usage may be needed. It represents an important tool to be investigated and its great potential is often yet to be discovered. This study thus sheds light on emerging issues and suggests further research that may be needed.