Mobile learning for delivering health professional education (protocol)

© 2015 The Cochrane Collaboration.This is the protocol for a review and there is no abstract. The objectives are as follows: The objective of this review is to evaluate the effectiveness of mLearning educational interventions for delivering pre-registration and post-registration healthcare professional education. We will primarily assess the impact of these interventions on students knowledge, skills, professional attitudes and satisfaction

How 5G wireless (and concomitant technologies) will revolutionize healthcare?

The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution

“What if There's Something Wrong with Her?”‐How Biomedical Technologies Contribute to Epistemic Injustice in Healthcare

While there is a steadily growing literature on epistemic injustice in healthcare, there are few discussions of the role that biomedical technologies play in harming patients in their capacity as knowers. Through an analysis of newborn and pediatric genetic and genomic sequencing technologies (GSTs), I argue that biomedical technologies can lead to epistemic injustice through two primary pathways: epistemic capture and value partitioning. I close by discussing the larger ethical and political context of critical analyses of GSTs and their broader implications for just and equitable healthcare delivery

Radical Technological Innovation and Perception: A Non-Physician Practitioners’ Perspective

Radical technological innovations, such as chatbots, fundamentally alter many aspects of healthcare organizations. For example, they transform how clinicians care for their patients. Despite the potential benefits, they cannot be integrated into practice without the support of the clinicians whose jobs are affected. While previous research shed important light on physicians’ perceptions, little is known on nonphysician practitioners view said innovations. This paper reports on a qualitative study, involving 10 nonphysician clinicians from Ontario, Canada, conducted to determine the perceptions and cognitions of clinicians regarding radical innovation and their previous experiences with technological change. Results indicate that clinicians as semi-autonomous agents can interpret and act upon their environment with regard to determining how innovations such as chatbots are implemented

A systematic literature review of cloud computing in eHealth

Cloud computing in eHealth is an emerging area for only few years. There needs to identify the state of the art and pinpoint challenges and possible directions for researchers and applications developers. Based on this need, we have conducted a systematic review of cloud computing in eHealth. We searched ACM Digital Library, IEEE Xplore, Inspec, ISI Web of Science and Springer as well as relevant open-access journals for relevant articles. A total of 237 studies were first searched, of which 44 papers met the Include Criteria. The studies identified three types of studied areas about cloud computing in eHealth, namely (1) cloud-based eHealth framework design (n=13); (2) applications of cloud computing (n=17); and (3) security or privacy control mechanisms of healthcare data in the cloud (n=14). Most of the studies in the review were about designs and concept-proof. Only very few studies have evaluated their research in the real world, which may indicate that the application of cloud computing in eHealth is still very immature. However, our presented review could pinpoint that a hybrid cloud platform with mixed access control and security protection mechanisms will be a main research area for developing citizen centred home-based healthcare applications

Co-innovation: the future of telemedicine in developing countries

Telemedicine which has been widely adopted in developed countries to reach all its citizens irrespective of their location is only being used for education purposes or disaster relief in developing countries. Since developing countries already suffer inadequate healthcare provision especially in remote areas, it would be essential to implement telemedicine practices for daily clinical uses rather than education use. This research argues that to understand the future of telemedicine in developing countries, both well-established technology innovations adoption factors as well as co-innovation factors should be addressed. In the context of healthcare provision, we propose a conceptual framework that integrates the healthcare resources and the organisational affiliations in co-innovation

Enhancing reuse of data and biological material in medical research : from FAIR to FAIR-Health

The known challenge of underutilization of data and biological material from biorepositories as potential resources formedical research has been the focus of discussion for over a decade. Recently developed guidelines for improved data availability and reusability—entitled FAIR Principles (Findability, Accessibility, Interoperability, and Reusability)—are likely to address only parts of the problem. In this article,we argue that biologicalmaterial and data should be viewed as a unified resource. This approach would facilitate access to complete provenance information, which is a prerequisite for reproducibility and meaningful integration of the data. A unified view also allows for optimization of long-term storage strategies, as demonstrated in the case of biobanks.Wepropose an extension of the FAIR Principles to include the following additional components: (1) quality aspects related to research reproducibility and meaningful reuse of the data, (2) incentives to stimulate effective enrichment of data sets and biological material collections and its reuse on all levels, and (3) privacy-respecting approaches for working with the human material and data. These FAIR-Health principles should then be applied to both the biological material and data. We also propose the development of common guidelines for cloud architectures, due to the unprecedented growth of volume and breadth of medical data generation, as well as the associated need to process the data efficiently.peer-reviewe

Contextual barriers to mobile health technology in African countries: a perspective piece

On a global scale, healthcare practitioners are now beginning to move from traditional desktop-based computer technologies towards mobile computing environments[1]. Consequently, such environments have received immense attention from both academia and industry, in order to explore these promising opportunities, apparent limitations, and implications for both theory and practice[2]. The application of mobile IT within a medical context, referred to as mobile health or mHealth, has revolutionised the delivery of healthcare services as mobile technologies offer the potential of retrieving, modifying and entering patient-related data/information at the point-of-care. As a component of the larger health informatics domain mHealth may be referred as all portable computing devices (e.g. mobile phones, mobile clinical assistants and medical sensors) used in a healthcare context to support the delivery of healthcare services