7,807 research outputs found

    A systematic literature review of cloud computing in eHealth

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    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

    Managing the Ethical Dimensions of Brain-Computer Interfaces in eHealth: An SDLC-based Approach

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    A growing range of brain-computer interface (BCI) technologies is being employed for purposes of therapy and human augmentation. While much thought has been given to the ethical implications of such technologies at the ‘macro’ level of social policy and ‘micro’ level of individual users, little attention has been given to the unique ethical issues that arise during the process of incorporating BCIs into eHealth ecosystems. In this text a conceptual framework is developed that enables the operators of eHealth ecosystems to manage the ethical components of such processes in a more comprehensive and systematic way than has previously been possible. The framework’s first axis defines five ethical dimensions that must be successfully addressed by eHealth ecosystems: 1) beneficence; 2) consent; 3) privacy; 4) equity; and 5) liability. The second axis describes five stages of the systems development life cycle (SDLC) process whereby new technology is incorporated into an eHealth ecosystem: 1) analysis and planning; 2) design, development, and acquisition; 3) integration and activation; 4) operation and maintenance; and 5) disposal. Known ethical issues relating to the deployment of BCIs are mapped onto this matrix in order to demonstrate how it can be employed by the managers of eHealth ecosystems as a tool for fulfilling ethical requirements established by regulatory standards or stakeholders’ expectations. Beyond its immediate application in the case of BCIs, we suggest that this framework may also be utilized beneficially when incorporating other innovative forms of information and communications technology (ICT) into eHealth ecosystems

    Managing the Ethical Dimensions of Brain-Computer Interfaces in eHealth: An SDLC-based Approach

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    A growing range of brain-computer interface (BCI) technologies is being employed for purposes of therapy and human augmentation. While much thought has been given to the ethical implications of such technologies at the ‘macro’ level of social policy and ‘micro’ level of individual users, little attention has been given to the unique ethical issues that arise during the process of incorporating BCIs into eHealth ecosystems. In this text a conceptual framework is developed that enables the operators of eHealth ecosystems to manage the ethical components of such processes in a more comprehensive and systematic way than has previously been possible. The framework’s first axis defines five ethical dimensions that must be successfully addressed by eHealth ecosystems: 1) beneficence; 2) consent; 3) privacy; 4) equity; and 5) liability. The second axis describes five stages of the systems development life cycle (SDLC) process whereby new technology is incorporated into an eHealth ecosystem: 1) analysis and planning; 2) design, development, and acquisition; 3) integration and activation; 4) operation and maintenance; and 5) disposal. Known ethical issues relating to the deployment of BCIs are mapped onto this matrix in order to demonstrate how it can be employed by the managers of eHealth ecosystems as a tool for fulfilling ethical requirements established by regulatory standards or stakeholders’ expectations. Beyond its immediate application in the case of BCIs, we suggest that this framework may also be utilized beneficially when incorporating other innovative forms of information and communications technology (ICT) into eHealth ecosystems

    Mechatronics & the cloud

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    Conventionally, the engineering design process has assumed that the design team is able to exercise control over all elements of the design, either directly or indirectly in the case of sub-systems through their specifications. The introduction of Cyber-Physical Systems (CPS) and the Internet of Things (IoT) means that a design team’s ability to have control over all elements of a system is no longer the case, particularly as the actual system configuration may well be being dynamically reconfigured in real-time according to user (and vendor) context and need. Additionally, the integration of the Internet of Things with elements of Big Data means that information becomes a commodity to be autonomously traded by and between systems, again according to context and need, all of which has implications for the privacy of system users. The paper therefore considers the relationship between mechatronics and cloud-basedtechnologies in relation to issues such as the distribution of functionality and user privacy

    SERIES: eHealth in primary care. Part 5: a critical appraisal of five widely used eHealth applications for primary care - opportunities and challenges

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    Background Given the pressure on modern healthcare systems, eHealth can offer valuable opportunities. However, understanding the potential and challenges of eHealth in daily practice can be challenging for many general practitioners (GPs) and their staff. Objectives To critically appraise five widely used eHealth applications, in relation to safe, evidence-based and high-quality eHealth. Using these applications as examples, we aim to increase understanding of eHealth among GPs and highlight the opportunities and challenges presented by eHealth. Discussion eHealth applications can support patients while increasing efficiency for GPs. A three-way division (inform, monitor, track; interaction; data utilisation) characterises many eHealth applications, with an increasing degree of complexity depending on the domain. All applications provide information and some have extra functionalities that promote interaction, while data analysis and artificial intelligence may be applied to support or (fully) automate care processes. Applications in the inform domain are relatively easy to use and implement but their impact on clinical outcomes may be limited. More demanding applications, in terms of privacy and ethical aspects, are found in the data utilisation domain and may potentially have a more significant impact on care processes and patient outcomes. When selecting and implementing eHealth applications, we recommend that GPs remain critical regarding preconditions on safe, evidence-based and high-quality eHealth, particularly in the case of more complex applications in the data utilisation domain.Prevention, Population and Disease management (PrePoD)Public Health and primary car

    MOSAIC roadmap for mobile collaborative work related to health and wellbeing.

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    The objective of the MOSAIC project is to accelerate innovation in Mobile Worker Support Environments. For that purpose MOSAIC develops visions and illustrative scenarios for future collaborative workspaces involving mobile and location-aware working. Analysis of the scenarios is input to the process of road mapping with the purpose of developing strategies for R&D leading to deployment of innovative mobile work technologies and applications across different domains. One of the application domains where MOSAIC is active is health and wellbeing. This paper builds on another paper submitted to this same conference, which presents and discusses health care and wellbeing specific scenarios. The aim is to present an early form of a roadmap for validation

    The European Institute for Innovation through Health Data

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    The European Institute for Innovation through Health Data (i~HD, www.i-hd.eu) has been formed as one of the key sustainable entities arising from the Electronic Health Records for Clinical Research (IMI-JU-115189) and SemanticHealthNet (FP7-288408) projects, in collaboration with several other European projects and initiatives supported by the European Commission. i~HD is a European not-for-profit body, registered in Belgium through Royal Assent. i~HD has been established to tackle areas of challenge in the successful scaling up of innovations that critically rely on high-quality and interoperable health data. It will specifically address obstacles and opportunities to using health data by collating, developing, and promoting best practices in information governance and in semantic interoperability. It will help to sustain and propagate the results of health information and communication technology (ICT) research that enables better use of health data, assessing and optimizing their novel value wherever possible. i~HD has been formed after wide consultation and engagement of many stakeholders to develop methods, solutions, and services that can help to maximize the value obtained by all stakeholders from health data. It will support innovations in health maintenance, health care delivery, and knowledge discovery while ensuring compliance with all legal prerequisites, especially regarding the insurance of patient's privacy protection. It is bringing multiple stakeholder groups together so as to ensure that future solutions serve their collective needs and can be readily adopted affordably and at scale

    Commercialisation of eHealth Innovations in the Market of UK Healthcare Sector: A Framework for Sustainable Business Model.

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    This is the peer reviewed version of the following article: Festus Oluseyi Oderanti, and Feng Li, ‘Commercialization of eHealth innovations in the market of the UK healthcare sector: A framework for a sustainable business model’, Psychology & Marketing, Vol. 35 (2): 120-137, February 2018, which has been published in final form at https://doi.org/10.1002/mar.21074. Under embargo until 10 January 2020. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Demographic trends with extended life expectancy are placing increasing pressures on the UK state-funded healthcare budgets. eHealth innovations are expected to facilitate new avenues for cost-effective and safe methods of care, for enabling elderly people to live independently at their own homes and for assisting governments to cope with the demographic challenges. However, despite heavy investment in these innovations, large-scale deployment of eHealth continues to face significant obstacles, and lack of sustainable business models (BMs) is widely regarded as part of the greatest barriers. Through various empirical methods that include facilitated workshops, case studies of relevant organizations, and user groups, this paper investigates the reasons the private market of eHealth innovations has proved difficult to establish, and therefore it develops a framework for sustainable BMs that could elimiesnate barriers of eHealth innovation commercialization. Results of the study suggest that to achieve sustainable commercialization, BM frameworks and innovation diffusion characteristics should be considered complements but not substitutes.Peer reviewe

    Protecting Patient Privacy: Strategies for Regulating Electronic Health Records Exchange

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    The report offers policymakers 10 recommendations to protect patient privacy as New York state develops a centralized system for sharing electronic medical records. Those recommendations include:Require that the electronic systems employed by HIEs have the capability to sort and segregate medical information in order to comply with guaranteed privacy protections of New York and federal law. Presently, they do not.Offer patients the right to opt-out of the system altogether. Currently, people's records can be uploaded to the system without their consent.Require that patient consent forms offer clear information-sharing options. The forms should give patients three options: to opt-in and allow providers access to their electronic medical records, to opt-out except in the event of a medical emergency, or to opt-out altogether.Prohibit and sanction the misuse of medical information. New York must protect patients from potential bad actors--that small minority of providers who may abuse information out of fear, prejudice or malice.Prohibit the health information-sharing networks from selling data. The State Legislature should pass legislation prohibiting the networks from selling patients' private health information
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