Ruotsalainen Pekka, Blobel Bernd, Pohjolainen Seppo
Faculty of Information Technology and Communication Sciences (ITC), Tampere University, 33100 Tampere, Finland.
Medical Faculty, University of Regensburg, 93953 Regensburg, Germany.
J Pers Med. 2022 Apr 19;12(5):657. doi: 10.3390/jpm12050657.
The use of eHealth and healthcare services are becoming increasingly common across networks and ecosystems. Identifying the quality and health impact of these services is a big problem that in many cases it is difficult determine. Health ecosystems are seldom designed with privacy and trust in mind, and the service user has almost no way of knowing how much trust to place in the service provider and other stakeholders using his or her personal health information (PHI). In addition, the service user cannot rely on privacy laws, and the ecosystem is not a trustworthy system. This demonstrates that, in real life, the user does not have significant privacy. Therefore, before starting to use eHealth services and subsequently disclosing personal health information (PHI), the user would benefit from tools to measure the level of privacy and trust the ecosystem can offer. For this purpose, the authors developed a solution that enables the service user to calculate a Merit of Service (Fuzzy attractiveness rating (FAR)) for the service provider and for the network where PHI is processed. A conceptual model for an eHealth ecosystem was developed. With the help of heuristic methods and system and literature analysis, a novel proposal to identify trust and privacy attributes focused on eHealth was developed. The FAR value is a combination of the service network's privacy and trust features, and the expected health impact of the service. The computational Fuzzy linguistic method was used to calculate the FAR. For user friendliness, the Fuzzy value of Merit was transformed into a linguistic Fuzzy label. Finally, an illustrative example of FAR calculation is presented.
电子健康和医疗服务在网络和生态系统中的使用正变得越来越普遍。识别这些服务的质量和对健康的影响是一个大问题，在很多情况下很难确定。健康生态系统在设计时很少考虑隐私和信任，服务用户几乎无法知道该在多大程度上信任使用其个人健康信息（PHI）的服务提供商和其他利益相关者。此外，服务用户无法依赖隐私法，而且该生态系统也不是一个值得信赖的系统。这表明，在现实生活中，用户没有显著的隐私。因此，在开始使用电子健康服务并随后披露个人健康信息（PHI）之前，用户将受益于用于衡量生态系统所能提供的隐私和信任水平的工具。为此，作者开发了一种解决方案，使服务用户能够为服务提供商以及处理PHI的网络计算服务价值（模糊吸引力评级（FAR））。开发了一个电子健康生态系统的概念模型。借助启发式方法以及系统和文献分析，提出了一种专注于电子健康的识别信任和隐私属性的新颖方案。FAR值是服务网络的隐私和信任特征与服务预期的健康影响的组合。使用计算模糊语言方法来计算FAR。为了便于用户使用，将价值的模糊值转换为语言模糊标签。最后，给出了一个FAR计算的示例。
