背景:在我们的数字世界中,隐私是一个非常复杂的话题,尤其是在满足云计算技术成就的多维背景时。这里,隐私是一个扩展的概念,有时被称为法律,哲学,甚至技术。因此,有必要将其与医疗保健的其他方面协调起来,以提供新的生态系统。这个新的生态系统可能导致范式转变,包括重建和重新设计一些最重要和最基本的要求,如隐私概念,法律问题,和安全服务。健康领域的云计算对其他技术有显著的贡献,比如移动医疗,健康的物联网,和无线体域网,随着越来越多的嵌入式应用程序。其他依赖应用程序,通常用于健康企业,如社交网络,或者一些新推出的应用程序有关于隐私透明度边界和隐私保护原则的问题,这使得该领域的政策制定变得困难。
目的:克服这一挑战的一种方法是开发一种分类法来识别所有相关因素。分类法有助于使面对面医疗服务中的替代方案在概念上清晰。本研究旨在构建健康云中隐私的综合分类法,这也为相关技术中的隐私提供了一个前瞻性的景观。
方法:在数据库中搜索相关已发表的英文论文,包括WebofScience,IEEE数字图书馆,谷歌学者,Scopus,和PubMed。根据预定义的关键字和搜索字符串,共有2042篇论文与健康云隐私概念相关。使用演绎方法进行分类学设计。
结果:这个分类有3层。第一层有4个主要维度,包括云,数据,装置,和法律。第二层有15种成分,最后一层具有相关的子类别(n=57)。这个分类法涵盖了一些相关的概念,比如隐私,安全,保密性,和法律问题,它们在这里被分类,并由它们的扩展和独特的边界来定义。这种分类法的主要优点是它能够澄清不同场景的隐私术语,并在eHealth中表示隐私多学科对象化。
结论:这种分类可以涵盖健康行业的要求,包括健康数据和方案等规范,这被认为是企业和行业中最复杂的。因此,这种分类法的使用可以推广和定制到其他复杂情况较少的领域和企业。此外,这个分类法有不同的股东,包括人,组织,和系统。如果分类法中的先行努力得到证明,主题专家可以通过验证来增强健康云中的隐私程度,评估,并修改这个分类法。
BACKGROUND: Privacy in our digital world is a very complicated topic, especially when meeting cloud computing technological achievements with its multidimensional context. Here, privacy is an extended concept that is sometimes referred to as legal, philosophical, or even technical. Consequently, there is a need to harmonize it with other aspects in health care in order to provide a new ecosystem. This new ecosystem can lead to a paradigm shift involving the reconstruction and redesign of some of the most important and essential requirements like privacy concepts, legal issues, and security services. Cloud computing in the health domain has markedly contributed to other technologies, such as mobile health, health Internet of Things, and wireless body area networks, with their increasing numbers of embedded applications. Other dependent applications, which are usually used in health businesses like social networks, or some newly introduced applications have issues regarding privacy transparency boundaries and privacy-preserving principles, which have made policy making difficult in the field.
OBJECTIVE: One way to overcome this challenge is to develop a taxonomy to identify all relevant factors. A taxonomy serves to bring conceptual clarity to the set of alternatives in in-person health care delivery. This study aimed to construct a comprehensive taxonomy for privacy in the health cloud, which also provides a prospective landscape for privacy in related technologies.
METHODS: A search was performed for relevant published English papers in databases, including Web of Science, IEEE Digital Library, Google Scholar, Scopus, and PubMed. A total of 2042 papers were related to the health cloud privacy concept according to predefined keywords and search strings. Taxonomy designing was performed using the deductive methodology.
RESULTS: This taxonomy has 3 layers. The first layer has 4 main dimensions, including cloud, data, device, and legal. The second layer has 15 components, and the final layer has related subcategories (n=57). This taxonomy covers some related concepts, such as privacy, security, confidentiality, and legal issues, which are categorized here and defined by their expansion and distinctive boundaries. The main merits of this taxonomy are its ability to clarify privacy terms for different scenarios and signalize the privacy multidisciplinary objectification in eHealth.
CONCLUSIONS: This taxonomy can cover health industry requirements with its specifications like health data and scenarios, which are considered as the most complicated among businesses and industries. Therefore, the use of this taxonomy could be generalized and customized to other domains and businesses that have less complications. Moreover, this taxonomy has different stockholders, including people, organizations, and systems. If the antecedent effort in the taxonomy is proven, subject matter experts could enhance the extent of privacy in the health cloud by verifying, evaluating, and revising this taxonomy.