Collaborative eHealth Meets Security: Privacy-Enhancing Patient Profile Management
| Autor: | Patricia Arias Cabarcos, Florina Almenarez Mendoza, Rosa Sanchez-Guerrero, Andrés Marín López, Daniel Diaz-Sanchez |
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| Rok vydání: | 2017 |
| Předmět: |
media_common.quotation_subject
Internet privacy 0211 other engineering and technologies MEDLINE 02 engineering and technology Merkle tree Computer security computer.software_genre Health Information Management Health care 0202 electrical engineering electronic engineering information engineering eHealth Electronic Health Records Humans Medicine Computer Simulation Confidentiality Quality (business) Electrical and Electronic Engineering Computer Security media_common 021110 strategic defence & security studies business.industry 020206 networking & telecommunications Models Theoretical Credential Telemedicine Computer Science Applications Information sensitivity business computer Biotechnology |
| Zdroj: | IEEE Journal of Biomedical and Health Informatics. 21:1741-1749 |
| ISSN: | 2168-2208 2168-2194 |
| DOI: | 10.1109/jbhi.2017.2655419 |
| Popis: | Collaborative healthcare environments offer potential benefits, including enhancing the healthcare quality delivered to patients and reducing costs. As a direct consequence, sharing of electronic health records (EHRs) among healthcare providers has experienced a noteworthy growth in the last years, since it enables physicians to remotely monitor patients' health and enables individuals to manage their own health data more easily. However, these scenarios face significant challenges regarding security and privacy of the extremely sensitive information contained in EHRs. Thus, a flexible, efficient, and standards-based solution is indispensable to guarantee selective identity information disclosure and preserve patient's privacy. We propose a privacy-aware profile management approach that empowers the patient role, enabling him to bring together various healthcare providers as well as user-generated claims into an unique credential. User profiles are represented through an adaptive Merkle Tree, for which we formalize the underlying mathematical model. Furthermore, performance of the proposed solution is empirically validated through simulation experiments. |
| Databáze: | OpenAIRE |
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