Privacy Protection and Secondary Use of Health Data: Strategies and Methods

Abstract

Health big data has already been the most important big data for its serious privacy disclosure concerns and huge potential value of secondary use. Measurements must be taken to balance and compromise both the two serious challenges. One holistic solution or strategy is regarded as the preferred direction, by which the risk of reidentification from records should be kept as low as possible and data be shared with the principle of minimum necessary. In this article, we present a comprehensive review about privacy protection of health data from four aspects: health data, related regulations, three strategies for data sharing, and three types of methods with progressive levels. Finally, we summarize this review and identify future research directions.

The Social Acceptance of Smart Health Services in Japan

“…These are not longitudinal or experimental data; accordingly, it is difficult to conclude that our model is the most appropriate. The findings of this study are consistent with the results of previous studies [15,[23][24][25][26][27][28][29][30][31][32][33][34] and the empirical findings related to the technology acceptance model, which deals with the social acceptance of scientific technology in general [51,52]. However, for a survey such as the one conducted in this study, the inability to sufficiently evaluate causal relationships is a significant and universal problem.…”

“…In addition, perceived risk scores in this study were remarkably higher than those in the previous study [25], which was recently conducted in Japan and dealt with the social acceptance of various smart city projects. This suggests that the risk of leakage of highly private data, especially those collected in s-Health services, is likely to be strongly perceived [31,32]. In contrast, concerns about interventions for individuals did not have a significant relationship with social acceptance (Figure 2).…”

“…In a previous study conducted recently in Japan which summarized people's expectations and concerns about health-related initiatives in smart cities [30], many concerns were expressed about the direct instructions for the individual's health behavior based on personal health and medical data, namely, "concern about interventions for individuals," such as "Being presented with risks related to one's health and diseases increases anxiety" [30]. It has been noted that personal health and medical information is one of the most private types of data [31,32]. There are also likely to be many people who feel that s-Health services are provided in a surveillance society [33,34].…”

“…In particular, there was a significant relationship between perceived benefit and social acceptance, which can be attributed to the s-Health service depicted in our vignette being more closely associated with the individuals' lives than other kinds of smart city projects and being directly related to their health behaviors. In addition, personal health and medical information collected in s-Health services are highly private data [31,32]. Since people tend to make more elaborate decisions about the targets closely related to themselves [40,41], the participants were believed to make more elaborate information processing about the extent of future benefits from the service depicted in the vignette.…”

“…Referring to the research on persuasion in social psychology, trust in the other person is a peripheral cue, and deciding on the target based on trust alone is regarded as information processing through peripheral routes [42][43][44]. As mentioned above, compared to other kinds of smart city projects, s-Health services are more closely related to the lives of general citizens and the issue of privacy protection [31,32]. Hence, in this study, elaborate information processing regarding future benefits seemed to be more active than information processing regarding trust in the city government, the peripheral cue.…”