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PubMed · 10566482

A strategy for statistical Master Person Index linking.

M K Martin·I P Shevchenko·L L Reed-Fourquet·J T Lynch
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Abstract

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.

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Abstracting and IndexingConnecticutDatabases as TopicHumansMedical Record LinkageMedical Records Systems, ComputerizedJournal ArticleResearch Support, U.S. Gov't, Non-P.H.S.

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M K Martin, I P Shevchenko, L L Reed-Fourquet, J T Lynch. 1999. A strategy for statistical Master Person Index linking.. https://pubmed.ncbi.nlm.nih.gov/10566482/

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