A logic for uncertain probabilities
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Disseminating Trust Information in Wearable Communities
Personal and Ubiquitous Computing
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
A reputation-based trust model for peer-to-peer ecommerce communities [Extended Abstract]
Proceedings of the 4th ACM conference on Electronic commerce
PeerTrust: Supporting Reputation-Based Trust for Peer-to-Peer Electronic Communities
IEEE Transactions on Knowledge and Data Engineering
Semantic constraints for trust transitivity
APCCM '05 Proceedings of the 2nd Asia-Pacific conference on Conceptual modelling - Volume 43
TRAVOS: Trust and Reputation in the Context of Inaccurate Information Sources
Autonomous Agents and Multi-Agent Systems
ARES '07 Proceedings of the The Second International Conference on Availability, Reliability and Security
Probabilistic logic under uncertainty
CATS '07 Proceedings of the thirteenth Australasian symposium on Theory of computing - Volume 65
Hedaquin: A Reputation-based Health Data Quality Indicator
Electronic Notes in Theoretical Computer Science (ENTCS)
Bayesian network based trust management
ATC'06 Proceedings of the Third international conference on Autonomic and Trusted Computing
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There is currently a strong focus worldwide on the potential of large-scale Electronic Health Record (EHR) systems to cut costs and improve patient outcomes through increased efficiency. This is accomplished by aggregating medical data from isolated Electronic Medical Record databases maintained by different healthcare providers. Concerns about the privacy and reliability of Electronic Health Records are crucial to healthcare service consumers. Traditional security mechanisms are designed to satisfy confidentiality, integrity, and availability requirements, but they fail to provide a measurement tool for data reliability from a data entry perspective. In this paper, we introduce a Medical Data Reliability Assessment (MDRA) service model to assess the reliability of medical data by evaluating the trustworthiness of its sources, usually the healthcare provider which created the data and the medical practitioner who diagnosed the patient and authorised entry of this data into the patient's medical record. The result is then expressed by manipulating health record metadata to alert medical practitioners relying on the information to possible reliability problems.