The relation between big data and informational privacy in the context of the healthcare
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Abstract
Big data is a broad term that is related to the collection, storage and analysis of large volumes of data. The term big data is often associated with the popular 3V’s model, which defined that data is growing significantly in the characteristics volume, variety and velocity. In this research we defined big data as: the collection, storage and transformation of structured and unstructured data from multiple sources into useful information (or knowledge) to improve decision-making within organizations. The significant growth of data is also occurring in the health care sector. A lot of these scattered data sources, possessing large volumes of personal health data of patients, are present in the health care. Big data have shown potential to support health care, by combining and transforming health data. Big data can be used to support medical and healthcare functions, including among others clinical decision support, disease surveillance, and population health (Raghupathi & Raghupathi, 2014). The increasing availability of large data sets from various sources in combination with the development of more advanced analytical tools for big data makes it more and more difficult to ensure privacy. Big data in its current form is still relatively new, and the knowledge on the implications on the security and privacy issues that it brings is still limited. This study explores the relation between big data and privacy in the health care. The research objective of this study is to gather knowledge on how big data affects privacy in the health care. In order to reach this objective, semi-structured interviews have been conducted with eight experts in either big data, health care or privacy in the Netherlands. In this research, a conceptual model of privacy has been created based on existing theories of privacy (e.g. nonintrusion theory, seclusion theory, control theory and restricted access theory). The conceptual model of privacy defines privacy in the elements: natural privacy, normative privacy, control aspect of privacy and the condition of privacy and has been used as a structure to analyze the relation between big data and privacy.