Paper short abstract:

We highlight the complex and changing contexts in which sensitive health data live, focusing on disclosure control methods that seek to create data, or to create specific contexts for data, that allow it to be considered low-risk, anonymous, and useful.

Paper long abstract:

Sharing of health data is crucial in order to reduce waste and inefficiency as well as to maximise the scientific potential of data. However, there is a well-recognised need to protect the confidentiality of participant's and their data. Consequently calls for increasing openness of of health data have been accompanied by new norms and techniques to evaluate and control disclosure risk.

This presentation will address the themes of the track by highlighting the complex and changing contexts in which sensitive health data live; focusing on how and why disclosure control methods seek to create data, or to create specific contexts for data, that allow it to be considered low-risk, anonymous, and useful. We review some of the central concepts deployed in the literature about disclosure control. For example, the construction of risk in terms of the internal statistical properties of data, and in terms of the external context, or 'data environments' (Elliot et al, 2010), which data inhabit and move through. Finally we provide some suggestions for areas where STS scholarship may usefully engage with the field of Statistical Disclosure Control.