Version: v1, Published online: 2021
Retrieved February 22, 2024, from https://www.rep.routledge.com/articles/thematic/big-data-in-healthcare/v-1
The current era of ‘big data’ in healthcare is a direct result of the gradual culmination across decades of accumulation of large volumes of data, along with substantial advances in tools capable of analysing that data. Potential applications cut across almost all aspects of healthcare, including improving the efficiency of health systems, evaluating the efficacy of treatments using volumes of real-world data, and tailoring treatments to individual patient profiles through ‘precision medicine’. These prospects must be tempered, however, not only against the practical reality of what is possible through big data, but also how big data can be responsibly and ethically managed.
Preserving privacy, one of the central values in data ethics, has become increasingly complex in the big data era. Privacy can be understood in at least two distinct senses – either in terms of control over information about ourselves, or in terms of limitations on the access others have to that information. Traditionally, anonymisation and consent have been deployed to protect these aspects of privacy. Consent puts control over data in the hands of the data subject, while anonymisation limits the extent to which those using data can discern meaningful information about particular, identifiable individuals.
The paradigms of consent and anonymisation, however, are somewhat limited when it comes to big data. The massive scope of potential big data applications makes obtaining consent for particular uses, or even categories of uses, oftentimes impracticable. Anonymisation, meanwhile, is more difficult to guarantee as big data contains ever more fine-grained bits of information that could potentially be used to re-identify individuals.
Robust governance, then, takes on an outsize role for big data. Three key aspects of good data governance include: accountability, transparency, and engagement. These governance characteristics promote both the inherent legitimacy of big data uses, as well as the possibility of achieving a social license for big data uses – that is to say, the degree to which the public finds a particular use of big data acceptable. Conversely, failure to obtain a social licence (informal though it may be) can scuttle even well-intentioned, socially valuable big data applications.
Data ethics is of necessity an evolving and adaptive field. Attention to these complications for the application of big data analytics into the healthcare sector is needed in order to ensure responsible and publicly defensible use of that data.
Schaefer, G. Owen. Big data in healthcare, 2021, doi:10.4324/9780415249126-L170-1. Routledge Encyclopedia of Philosophy, Taylor and Francis, https://www.rep.routledge.com/articles/thematic/big-data-in-healthcare/v-1.
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