Ensuring privacy when integrating patient-based datasets: New methods and developments in record linkage

Abstract

© 2017 Brown, Ferrante, Randall, Boyd and Semmens. In an era where the volume of structured and unstructured digital data has exploded, there has been an enormous growth in the creation of data about individuals that can be used for understanding and treating disease. Joining these records together at an individual level provides a complete picture of a patient's interaction with health services and allows better assessment of patient outcomes and effectiveness of treatment and services. Record linkage techniques provide an efficient and cost-effective method to bring individual records together as patient profiles. These linkage procedures bring their own challenges, especially relating to the protection of privacy. The development and implementation of record linkage systems that do not require the release of personal information can reduce the risks associated with record linkage and overcome legal barriers to data sharing. Current conceptual and experimental privacy-preserving record linkage (PPRL) models show promise in addressing data integration challenges. Enhancing and operationalizing PPRL protocols can help address the dilemma faced by some custodians between using data to improve quality of life and dealing with the ethical, legal, and administrative issues associated with protecting an individual's privacy. These methods can reduce the risk to privacy, as they do not require personally identifying information to be shared. PPRL methods can improve the delivery of record linkage services to the health and broader research community.