Health information exchange across multiple organizations requires a method or algorithm to optimally link records of the same individuals using demographic data. Selecting the best record linkage algorithm requires an evaluation to determine its sensitivity and specificity. This evaluation is facilitated by a large database test bed that closely reflects a real world population and takes into account the potential data entry errors that unfortunately occur in real-world databases. This study investigated the synthesis of such a database.
A conference poster presented at the American Medical Informatics Association (AMIA)'s 2008 Annual Symposium
Agency for Healthcare Research and Quality (AHRQ) grant number UC1 HS16155
Theera-Ampornpunt, Nawanan; Kijsanayotin, Boonchai; Speedie, Stuart M..
Creating a Large Database Test Bed with Typographical Errors for Record Linkage Evaluation.
Retrieved from the University of Minnesota Digital Conservancy,
Content distributed via the University of Minnesota's Digital
Conservancy may be subject to additional license and use
restrictions applied by the depositor.