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数字表型与敏感健康数据:对数据治理的影响。

Digital phenotyping and sensitive health data: Implications for data governance.

机构信息

MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.

The Alan Turing Institute, London, United Kingdom.

出版信息

J Am Med Inform Assoc. 2021 Aug 13;28(9):2002-2008. doi: 10.1093/jamia/ocab012.

Abstract

In this perspective we want to highlight the rise of what we call "digital phenotyping" or inferring insights about peopleãs health and behavior from their digital devices and data, and the challenges this introduces. Indeed, the collection, processing, and storage of data comes with significant ethical, security and data governance considerations. The COVID-19 pandemic has laid bare the importance of scientific data and modeling, both to understand the nature and spread of the disease, and to develop treatment. But digital devices have also played a (controversial) role, with track and trace systems and increasingly "vaccine passports" being rolled out to help societies open back up. These systems epitomize a wider and longer-standing trend towards seeing almost any form of personal data as potentially health data, especially with the rise of consumer health trackers and other gadgets. Here, we offer an overview of the risks this introduces, drawing on the earlier revolution in genomic sequencing, and propose guidelines to help protect privacy whilst utilizing personal data to help get society back up to speed.

摘要

在这个视角下,我们想强调一下所谓“数字表型”的兴起,即从人们的数字设备和数据中推断出他们的健康和行为洞察,以及这带来的挑战。实际上,数据的收集、处理和存储带来了重大的伦理、安全和数据治理方面的考量。新冠疫情凸显了科学数据和建模的重要性,既有助于理解疾病的性质和传播,也有助于开发治疗方法。但是,数字设备也发挥了(有争议的)作用,追踪和溯源系统以及越来越多的“疫苗护照”被推出,以帮助社会重新开放。这些系统体现了一个更广泛和更长期的趋势,即将几乎任何形式的个人数据都视为潜在的健康数据,尤其是随着消费者健康追踪器和其他小工具的兴起。在这里,我们借鉴基因组测序的早期革命,概述了这带来的风险,并提出了一些指导方针,以帮助在利用个人数据帮助社会恢复正常的同时保护隐私。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2eb4/8363798/a01ccecf7515/ocab012f1.jpg

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