title: A naturalistic patient matching algorithm: Derivation and validation.
abstract: With the vast amount of medical data being generated on an electronic basis, to ensure that individual patient information is properly linked across multiple sources, efficient patient matching algorithms are critical. We describe a novel naturalistic approach that is a hybrid of both deterministic (exact) and probabilistic ("close") systems that allows for manual adjudication of cases where necessary, but whose basis stems from the thought processes that a rational individual would follow in the comparison of medical records. A validation of this algorithm using large databases from two disparate sources demonstrates that the naturalistic approach can largely eliminate false positives (false matches) and false negatives (false mismatches).
authors.affiliation: UCLA, USA martin.l.lee@att.net.
authors.forename: Martin Laurence
authors.initials: ML
authors.lastname: Lee
authors.affiliation: UCLA, USA.|Atlas Development Corporation, USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Clymer
authors.affiliation: UCLA, USA.|Atlas Development Corporation, USA.
authors.forename: Kate
authors.initials: K
authors.lastname: Peters
mesh_terms: D000465:Algorithms; D066264:Datasets as Topic / Q000639:trends*; D006801:Humans; D008498:Medical Record Linkage / Q000379:methods; D010355:Patient Identification Systems / Q000379:methods*; D018579:Patient Selection
keywords: exact versus probabilistic matching; medical record keeping; naturalistic algorithm; patient matching algorithms; record linkage; validation