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https://doi.org/10.1109/cloud....
Article . 2011 . Peer-reviewed
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DACAR Platform for eHealth Services Cloud

Authors: Lu Fan; William J. Buchanan; Christoph Thümmler; Owen Lo; Abou Sofyane Khedim; Omair Uthmani; Alistair Lawson; +1 Authors

DACAR Platform for eHealth Services Cloud

Abstract

The use of digital technologies in providing health care services is collectively known as eHealth. Considerable progress has been made in the development of eHealth services, but concerns over service integration, large scale deployment, and security, integrity and confidentiality of sensitive medical data still need to be addressed. This paper presents a solution proposed by the Data Capture and Auto Identification Reference (DACAR) project to overcoming these challenges. The key contributions of this paper include a Single Point of Contact (SPoC), a novel rule based information sharing policy syntax, and Data Buckets hosted by a scalable and cost-effective Cloud infrastructure. These key components and other system services constitute DACAR's eHealth platform, which allows the secure capture, storage and consumption of sensitive health care data. Currently, a prototype of the DACAR platform has been implemented. To assess the viability and performance of the platform, a demonstration application, namely the Early Warning Score (EWS), has been developed and deployed within a private Cloud infrastructure at Edinburgh Napier University. Simulated experimental results show that the end-to-end communication latency of 97.8% of application messages were below 100ms. Hence, the DACAR platform is efficient enough to support the development and integration of time critical eHealth services. A more comprehensive evaluation of the DACAR platform in a real life clinical environment is under development at Chelsea & Westminster Hospital in London.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
42
Top 10%
Top 10%
Top 10%