As the costs of healthcare services rise and healthcare professionals are becoming scarce and hard to find, it is imminent that healthcare organizations consider adopting health information technology (HIT) systems. HIT allows health organizations to streamline many of their processes and provide services in a more efficient and cost-effective manner. The latest technological trends such as Cloud Computing (CC) provide a strong infrastructure and offer a true enabler for HIT services over the Internet. This can be achieved on a pay-as-you-use model of the “e-Health Cloud” to help the healthcare industry cope with current and future demands yet keeping their costs to a minimum. Despite its great potential, HIT as a CC model has not been addressed extensively in the literature. There are no apparent frameworks which clearly encompass all viable schemes and interrelationships between HIT and CC. Therefore, analyzing and comparing the effectiveness of such schemes is important. In this paper we introduce the concept of “e-Health Cloud” highlighting many of its constituents and proposing building an e-health environment and elucidating many of the challenges confronting the success of the e-Health Cloud. We will also discuss different possible solutions to address challenges such as security and privacy

Health 4.0 establishes a new promising vision for the healthcare industry. It creatively integrates and employ innovative technologies such as the Internet of Health Things (IoHT), medical Cyber-Physical Systems (medical CPS), health cloud, health fog, big data analytics, machine learning, blockchain, and smart algorithms. The goal is to deliver improved, value-added and cost-effective healthcare services to patients and enhance the effectiveness and efficiency or the healthcare industry. Health 4.0 (adapted from the Industry 4.0 principles) changes the healthcare business model to enhance the interactions across the healthcare clients (the patients), stakeholders, infrastructure, and value chain. This effectively will improve the quality, flexibility, productivity, cost-effectiveness, and reliability of healthcare services in addition to increasing patients’ satisfaction. However, building and utilizing healthcare applications that follow the Health 4.0 concept is a non-trivial and complex endeavor. In addition, advanced potential applications based on Health 4.0 capabilities are not yet being investigated. In this paper we define the main objectives of Health 4.0 and discuss advanced potential Health 4.0 applications. To have a clear understanding of these applications, we categorize them in 4 groups based on the primary beneficiary of these applications. Thus we have patient targeted applications, applications supporting healthcare professionals, resource management applications and high-level healthcare systems management applications. In addition, as we studied the different applications, we realized that these is a certain collection of services that these most of them need regardless of their goals or business context. Services supporting data collection and transfer, security and privacy, reliable operations are some examples. As a result we propose creating a service-oriented middleware framework to offers the common services to the applications developers and facilitate the integration of different services to build applications under the Health 4.0 umbrella.

Recently, most healthcare organizations focus their attention on reducing the cost of their supply chain management (SCM) by improving the decision making pertaining processes' efficiencies. The availability of products through healthcare SCM is often a matter of life or death to the patient; therefore, trial and error approaches are not an option in this environment. Simulation and modeling (SM) has been presented as an alternative approach for supply chain managers in healthcare organizations to test solutions and to support decision making processes associated with various SCM problems. This paper presents and analyzes past SM efforts to support decision making in healthcare SCM and identifies the key challenges associated with healthcare SCM modeling. We also present and discuss emerging technologies to meet these challenges.

Th metaverse presents a new opportunity to construct personalized learning paths and to promote practices that scale the development of future skills and collective intelligence. The attitudes, knowledge and skills that are necessary to face the challenges of the 21st century should be developed through iterative cycles of continuous learning, where learners are enabled to experience, reflect, and produce new ideas while participating in a collective creativity process. In this paper, we propose an architecture to develop a metaverse-intensive learning experience (MiLEx) platform with an illustrative scenario that reinforces the development of 21st century career practices and collective intelligence. The learning ecosystem of MiLEx integrates four key elements: (1) key players that define the main actors and their roles in the learning process; (2) a learning context that defines the learning space and the networks of expected interactions among human and non-human objects; (3) experiential learning instances that deliver education via a real-life–virtual merge; and (4) technology support for building practice communities online, developing experiential cycles and transforming knowledge between human and non-human objects within the community. The proposed MiLEx architecture incorporates sets of technological and data components to (1) discover/profile learners and design learner-centric, theoretically grounded and immersive learning experiences; (2) create elements and experiential learning scenarios; (3) analyze learner’s interactive and behavioral patterns; (4) support the emergence of collective intelligence; (5) assess learning outcomes and monitor the learner’s maturity process; and (6) evaluate experienced learning and recommend future experiences. We also present the MiLEx continuum as a cyclic flow of information to promote immersive learning. Finally, we discuss some open issues to increase the learning value and propose some future work suggestions to further shape the transformative potential of metaverse-based learning environments.

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