Privacy in the age of medical big data image

Nature Medicine, January 7, 2019
by W. Nicholson Price (Academic Fellow Alumnus) and I. Glenn Cohen (Faculty Director)

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Big data has come to medicine. Its advocates promise increased accountability, quality, efficiency, and innovation. Most recently, the rapid development of machine-learning techniques and artificial intelligence (AI) has promised to bring forth even more useful applications from big data, from resource allocation to complex disease diagnosis1 . But with big data comes big risks and challenges, among them significant questions about patient privacy. In this article, we examine the host of ethical concerns and legal responses raised. Nevertheless, attempts to reduce privacy risks also bring their own costs that must be considered, both for current patients and for the system as a whole. We begin by discussing the benefits big data may bring to health science and practice and then turn to the concerns big data raises in these contexts. We focus on a prominent (but not the only) worry: privacy violations. We present a basic theory of health privacy and examine how privacy concerns play out in two phases of the life cycle of big data’s application to health care: data collection and data use. We ground these concerns in a discussion of relevant US law, a key feature of the health data world faced by innovators in this space, and make some regulatory recommendations. We argue, counter to the current zeitgeist, that while too little privacy raises concerns, it is also true that too much privacy in this area can pose problems.

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big data bioethics biotechnology i. glenn cohen w. nicholson price ii