Health Research with Big Data: Time for Systemic Oversight
Health Research with Big Data: Time for Systemic Oversight
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DOI：
10.1177/1073110518766026
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发表时间：
2018-03-01
影响因子：
2.1
通讯作者：
Blasimme, Alessandro
中科院分区：
文献类型：
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作者：
Vayena, Effy;Blasimme, Alessandro
为了解决大数据健康研究中的伦理挑战，我们提出了系统监督的概念。这种方法基于六个定义特征（适应性、灵活性、监控性、响应性、反身性和包容性），旨在在生物医学大数据研究的监督管道中建立一个共同点。当前提高知情同意的粒度和明确法律条款以解决数据驱动的健康研究中的信息隐私和歧视问题的趋势值得称赞。然而，除非不同利益相关者的监督活动获得共同的实质性方向，否则这些解决方案本身无法产生预期的影响。
To address the ethical challenges in big data health research we propose the concept of systemic oversight. This approach is based on six defining features (adaptivity, flexibility, monitoring, responsiveness, reflexivity, and inclusiveness) and aims at creating a common ground across the oversight pipeline of biomedical big data research. Current trends towards enhancing granularity of informed consent and specifying legal provisions to address informational privacy and discrimination concerns in data-driven health research are laudable. However, these solutions alone cannot have the desired impact unless oversight activities by different stakeholders acquire a common substantive orientation.