Current implementation of PPSPM Software (http://dmm.anu.edu.au/PPSPM/) handles similar patient matching (SPM) based on Bloom filter based masking and matching techniques of numerical attributes (such as age, blood pressure, BMI, and date of birth), categorical attributes (such as gender and marital status) and string attributes (such as names and addresses) (Vatsalan et al. 2016). Aim of this R&D project is to extend the functionality of PPSPM software to increase the accuracy and probability of Similar Patient Matching by identifying and incorporating advanced techniques (while preserving privacy) to include other complex patient medical data (such as scan image, textual data, medical reports, and geographical data) in record linkage.

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2016