The Impact of Name Transformation on Match Rates Within a Large Consumer Database.

Accurate record linkage depends on the availability and quality of features such as first name and last name. Privacy preserving record linkage methods using tokenization is sensitive to perturbations in the patient features used as inputs. In this study we evaluated the impact of name transformations on the accuracy of patient matching using a large commercial dataset.