Zandesh Zahra
Information Technology and Statistics Department, Tehran University of Medical Sciences, Tehran, Iran.
JMIR Form Res. 2024 Feb 12;8:e38372. doi: 10.2196/38372.
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.
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.
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.
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.
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.
在我们的数字世界中,隐私是一个非常复杂的话题,尤其是当云计算技术成果与其多维度背景相结合时。在这里,隐私是一个扩展概念,有时被称为法律、哲学甚至技术层面的概念。因此,有必要将其与医疗保健的其他方面进行协调,以提供一个新的生态系统。这个新的生态系统可能会导致范式转变,涉及到对一些最重要和基本的要求进行重构和重新设计,如隐私概念、法律问题和安全服务。随着嵌入式应用数量的不断增加,健康领域的云计算对移动健康、健康物联网和无线体域网等其他技术做出了显著贡献。其他依赖应用,如社交网络等通常用于健康业务的应用,或一些新引入的应用,在隐私透明度边界和隐私保护原则方面存在问题,这使得该领域的政策制定变得困难。
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一系列选择在概念上更加清晰。本研究旨在构建一个全面的健康云隐私分类法,该分类法还为相关技术中的隐私提供了一个前瞻性的框架。
在包括科学引文索引、电气和电子工程师协会数字图书馆、谷歌学术、Scopus和PubMed在内的数据库中搜索相关的已发表英文论文。根据预定义的关键词和搜索字符串,共有2042篇论文与健康云隐私概念相关。分类法设计采用演绎法。
该分类法有3个层次。第一层有4个主要维度,包括云、数据、设备和法律。第二层有15个组成部分,最后一层有相关子类别(n = 57)。该分类法涵盖了一些相关概念,如隐私、安全、保密和法律问题,这里对它们进行了分类,并根据其扩展和独特边界进行了定义。该分类法的主要优点是能够为不同场景澄清隐私术语,并表明电子健康中隐私的多学科客观化。
该分类法通过其如健康数据和场景等规范能够涵盖健康行业的要求,而这些被认为是商业和行业中最复杂的。因此,该分类法的使用可以推广并定制到其他复杂性较低的领域和业务中。此外,该分类法有不同的利益相关者,包括人员、组织和系统。如果分类法前期的工作得到验证,主题专家可以通过验证、评估和修订该分类法来提高健康云中隐私的程度。