Manual Evaluation of Record Linkage Algorithm Performance in Four Real-World Datasets.

ABSTRACT:

Objectives

 Patient data are fragmented across multiple repositories, yielding suboptimal and costly care. Record linkage algorithms are widely accepted solutions for improving completeness of patient records. However, studies often fail to fully describe their linkage techniques. Further, while many frameworks evaluate record linkage methods, few focus on producing gold standard datasets. This highlights a need to assess these frameworks and their real-world performance. We use real-world datasets and expand upon previous frameworks to evaluate a consistent approach to the manual review of gold standard datasets and measure its impact on algorithm performance.

Methods

 We applied the framework, which includes elements for data description, reviewer training and adjudication

SUBMITTER: Gupta AK 

PROVIDER: S-EPMC11290950 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature