State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences (ICMS), University of Macau, Macau, China.
Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau, China.
Int J Biol Sci. 2018 May 22;14(8):907-919. doi: 10.7150/ijbs.24617. eCollection 2018.
This paper takes up the problem of medical resource sharing through MicroService architecture without compromising patient privacy. To achieve this goal, we suggest refactoring the legacy EHR systems into autonomous MicroServices communicating by the unified techniques such as RESTFul web service. This lets us handle clinical data queries directly and far more efficiently for both internal and external queries. The novelty of the proposed approach lies in avoiding the data process often used as a means of preserving patient privacy. The implemented toolkit combines software engineering technologies such as Java EE, RESTful web services, JSON Web Tokens to allow exchanging medical data in an unidentifiable XML and JSON format as well as restricting users to the principle. Our technique also inhibits retrospective processing of data such as attacks by an adversary on a medical dataset using advanced computational methods to reveal Protected Health Information (PHI). The approach is validated on an endoscopic reporting application based on openEHR and MST standards. From the usability perspective, the approach can be used to query datasets by clinical researchers, governmental or non-governmental organizations in monitoring health care and medical record services to improve quality of care and treatment.
本文提出了一种通过微服务架构来实现医疗资源共享,同时又不损害患者隐私的方法。为了实现这一目标,我们建议将传统的 EHR 系统重构为自主的微服务,通过统一的技术(如 RESTful Web 服务)进行通信。这使得我们能够更直接、更高效地处理临床数据查询,无论是内部查询还是外部查询。所提出方法的新颖之处在于避免了数据处理通常被用作保护患者隐私的手段。实现的工具包结合了软件工程技术,如 Java EE、RESTful Web 服务、JSON Web 令牌,以允许以不可识别的 XML 和 JSON 格式交换医疗数据,并限制用户遵守原则。我们的技术还可以抑制数据的回溯处理,例如攻击者使用先进的计算方法对医疗数据集进行攻击,以揭示受保护的健康信息 (PHI)。该方法在基于 openEHR 和 MST 标准的内镜报告应用程序上得到了验证。从可用性的角度来看,该方法可用于临床研究人员、政府或非政府组织查询数据集,以监测医疗保健和医疗记录服务,从而提高护理和治疗质量。