SOEMPI: A Secure Open Enterprise Master Patient Index Software Toolkit for Private Record Linkage

To mitigate bias in multi-institutional research studies, healthcare organizations need to integrate patient records. However, this process must be accomplished without disclosing the identities of the corresponding patients. Various private record linkage (PRL) techniques have been proposed, but there is a lack of translation into practice because no software suite supports the entire PRL lifecycle. This paper addresses this issue with the introduction of the Secure Open Enterprise Master Patient Index (SOEMPI). We show how SOEMPI covers the PRL lifecycle, illustrate the implementation of several PRL protocols, and provide a runtime analysis for the integration of two datasets consisting of 10,000 records. While the PRL process is slower than a non-secure setting, our analysis shows the majority of processes in a PRL protocol require several seconds or less and that SOEMPI completes the process in approximately two minutes, which is a practical amount of time for integration.