An Integrated Cloud-based Healthcare Infrastructure

Ekonomou, Elias; Lü, Fan; Buchanan, William J.; Thüemmler, Christoph

doi:10.1109/cloudcom.2011.80

Cited by 38 publications

(17 citation statements)

References 8 publications

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“…With respect to healthcare cloud computing ecosystems, [16] mention the works by [18], [19], [20], [21], [22] as being related. The analysis of the literature shows enabling data access permissions across different cloud services and LBAC policies in some healthcare cloud computing ecosystem has been out of the scope so far.…”

Section: B Related Workmentioning

confidence: 99%

Enabling location-based policies in a healthcare cloud computing environment

Zickau

Thatmann

Ermakova

et al. 2014

2014 IEEE 3rd International Conference on Cloud Networking (CloudNet)

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In a multi-stakeholder cloud computing environment, data access control is of essential importance. Nowadays, it is usually handled in and deployed by every single cloud service on its own which makes the configuration of fine-grained access privileges cumbersome and economically expensive. In this paper, we introduce a novel cloud ecosystem architecture featuring an overall lightweight data access control model. This model is enabling data access policies based on location information of service consumer devices. We apply our architecture in the sensitive healthcare domain, which itself comprises multiple parties with complex data access privileges. Here, we define high-level requirements driven from current data protection regulations and guidelines as well as practice requirements in this area, which we address in the design of our architecture. We implement and test the main components. The results demonstrate the feasibility of our architecture and the applicability of our approach even in the healthcare application domain.

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Section: B Related Workmentioning

confidence: 99%

Enabling location-based policies in a healthcare cloud computing environment

Zickau

Thatmann

Ermakova

et al. 2014

2014 IEEE 3rd International Conference on Cloud Networking (CloudNet)

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“…The works are differentiated by: context-aware platforms for supporting continuous care [24], activity monitoring [50], [30], cloud-based healthcare [21], [51] and personalized care [17]. The context-aware systems that are developed using rule-mining and data mining only solve some specific diseases [33], [52].…”

Section: Related Workmentioning

confidence: 99%

BDCaM: Big Data for Context-Aware Monitoring—A Personalized Knowledge Discovery Framework for Assisted Healthcare

Forkan

Khalil

Ibaida

et al. 2017

IEEE Trans. Cloud Comput.

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Context-aware monitoring is an emerging technology that provides real-time personalised health-care services and a rich area of big data application. In this paper, we propose a knowledge discovery-based approach that allows the context-aware system to adapt its behaviour in runtime by analysing large amounts of data generated in ambient assisted living (AAL) systems and stored in cloud repositories. The proposed BDCaM model facilitates analysis of big data inside a cloud environment. It first mines the trends and patterns in the data of an individual patient with associated probabilities and utilizes that knowledge to learn proper abnormal conditions. The outcomes of this learning method are then applied in context-aware decision-making processes for the patient. A use case is implemented to illustrate the applicability of the framework that discovers the knowledge of classification to identify the true abnormal conditions of patients having variations in blood pressure (BP) and heart rate (HR). The evaluation shows a much better estimate of detecting proper anomalous situations for different types of patients. The accuracy and efficiency obtained for the implemented case study demonstrate the effectiveness of the proposed model.

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“…An integration system is proposed in [40]. The main goal was to integrate a formal EHR care system developed at an Edinburgh Napier University (ENU, in UK) denominated DACAR with an informal care system MS HealthVault [28].…”

Section: System Integration and Standardsmentioning

confidence: 99%

Integrated, Reliable and Cloud-Based Personal Health Record : A Scoping Review

Romero¹,

López²,

Noguera³

et al. 2016

HIIJ

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Personal Health Records (PHR) emerge as an alternative to integrate patient's health information to give a global view of patients' status. However, integration is not a trivial feature when dealing with a variety electronic health systems from healthcare centers. Access to PHR sensitive information must comply with privacy policies defined by the patient. Architecture PHR design should be in accordance to these, and take advantage of nowadays technology. Cloud computing is a current technology that provides scalability, ubiquity, and elasticity features. This paper presents a scoping review related to PHR systems that achieve three characteristics: integrated, reliable and cloud-based. We found 101 articles that addressed thosecharacteristics. We identified four main research topics: proposal/developed systems, PHR recommendations for development, system integration and standards, and security and privacy. Integration is tackled with HL7 CDA standard. Information reliability is based in ABE security-privacy mechanism. Cloud-based technology access is achieved via SOA.

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An Integrated Cloud-based Healthcare Infrastructure

Cited by 38 publications

References 8 publications

Enabling location-based policies in a healthcare cloud computing environment

Enabling location-based policies in a healthcare cloud computing environment

BDCaM: Big Data for Context-Aware Monitoring—A Personalized Knowledge Discovery Framework for Assisted Healthcare

Integrated, Reliable and Cloud-Based Personal Health Record : A Scoping Review

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