Public institutions gather and process data for a wide variety of purposes. In many cases, it is useful for them to process personal data, i.e., data connected to identifiable individuals. However, large-scale processing of personal data allows data-bases to be combined through shared identifiers. This would significantly enhance the identity knowledge capacity of governments; particularly given the sensitive nature of medical data, serious privacy risks are associated with this type of data collection and processing.
For certain types of purposes, such as statistical analysis of official data in the health sector, it is not always necessary to process raw personal data. Anonymization of data is an important tool to mitigate the privacy risks of large-scale data processing. In this chapter, we describe how anonymization can be implemented in a particular public sector without threatening the purposes of the data processing. For this, we have chosen two case studies in the health sector.