Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.
Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.
Int J Med Inform. 2019 Sep;129:242-247. doi: 10.1016/j.ijmedinf.2019.06.015. Epub 2019 Jun 22.
Passive data refers to data generated without the active participation of the subject. This includes data from global positioning systems and accelerometers or metadata on phone call and text activity. Although the potential healthcare applications are far-reaching, passive data raises numerous ethical challenges.
We performed a systematic review to identify all ethical concerns, normative standpoints, and underlying arguments related to the use of passive data in healthcare.
Among the various challenges discussed in the ethical literature, informational privacy, informed consent, and data security were the primary focus of the current debate. Other topics of discussion were the evaluation and regulation of products, equity in access, vulnerable patient groups, ownership, and secondary use.
No clear ethical framework has been established that stimulates passive data-driven innovation while protecting patient integrity. The consensus in the ethical literature, as well as the parallels with similar concerns and solutions in other fields, can lay a foundation for the construction of an ethical framework. The future debate should focus on conflicts between two or more ethical, technical, or clinical values to ensure a safe and effective implementation of passive data in healthcare.
被动数据是指在主体没有主动参与的情况下生成的数据。这包括来自全球定位系统和加速度计的数据,或有关电话和短信活动的元数据。尽管被动数据在医疗保健方面具有广泛的应用潜力,但它也引发了众多伦理挑战。
我们进行了系统综述,以确定与在医疗保健中使用被动数据相关的所有伦理问题、规范立场和潜在论点。
在伦理文献中讨论的各种挑战中,信息隐私、知情同意和数据安全是当前争论的主要焦点。其他讨论的议题包括产品的评估和监管、公平获取、弱势患者群体、所有权和二次使用。
目前还没有建立明确的伦理框架,既能激发被动数据驱动的创新,又能保护患者的完整性。伦理文献中的共识,以及与其他领域类似问题和解决方案的相似之处,可以为构建伦理框架奠定基础。未来的辩论应该集中在两个或更多伦理、技术或临床价值之间的冲突上,以确保在医疗保健中安全有效地实施被动数据。