Applying Differential Privacy to Medical Questionnaires

Currently, the medical sector sees a lot of digitization efforts. Besides the already available and growing amount of data there is still a need to receive data from patients. A special form of data donation are medical questionnaires. They come with a fixed set of questions regarding medical conditions and can be performed regularly or once. Such data donations show promising potential for research but come with open questions regarding privacy. There are many examples that show that re-identification is even possible with anonymized data. To mitigate such risks privacy enhancing technologies like Differential Privacy (DP) can be used. This paper presents a procedure for privacy preserving questionnaires using an implementation of DP called RAPPOR. Through its Randomized Response mechanism RAPPOR is well suited to be used with questionnaires. To proof feasibility of this procedure various experiments are conducted that show that this approach can improve privacy while still retaining a good level of utility.