Overcoming the Impasse 1: Reporting on Recent Australian Experiences in The Use of Privacy-Preserving Record Linkage Methods Using Bloom Filters

IntroductionNotwithstanding the growth in the number and type of datasets that are being included in data linkage projects, some datasets remain ‘hard to include’ in operational linkage systems. Legal or regulatory constraints often restrict the release of personally identifying information from some datasets; alternatively, it may be privacy or reputational risks that prevent data release. Advances in privacy-preserving record linkage (PPRL) methods have made it possible to overcome this impasse. Objectives and ApproachWe present and describe a number of recent Australian ‘use cases’ where the PPRL-Bloom method has been used. For each, we report and reflect on the following: a) The nature of problem or ‘impasse’ being solvedb) The linkage model adoptedc) Quality, performance, privacy and automationd) Challenges, insights and opportunities for improvement ResultsAustralian projects utilising privacy preserving linkage (PPRL-Bloom) include several linking state-based datasets to Commonwealth datasets, some linking primary care data to state-based hospital and other health collections, and others linking state-based non-health datasets such as education, police and justice datasets. Conclusion / ImplicationsPPRL is a useful and innovative methodology for providing access to some ‘hard to get’ datasets. It has already enabled a number of research projects that for regulatory or other privacy related reasons would not have occurred. The use of PPRL in Australia appears likely to grow.