A strategy for statistical Master Person Index linking.

A linking program used by Connecticut Healthcare Information Management and Exchange to maintain the Master Person Index for its large, state-wide patient data repository is being stretched beyond its limits by the growing size and complexity of the database. This paper presents the early work into developing a second-generation linking program. Like the original program, the new linker will use a unique multi-step process to allow effective linking of data from a large number of dissimilar data sources. The new linker will use parallel multi-processing to allow improved performance and scalability. These changes will also make possible more sophisticated statistical methods of defining link confidence. The system is implemented using a scalable collection of inexpensive, PC based systems running the Linux operating system, a freely available database engine, and the Java programming language.