An Efficient Validation Method of Probabilistic Record Linkage Including Readmissions and Twins

Abstract

Summary Objective: To describe an efficient, generalizable approach to validate probabilistic record linkage results, in particular by a model-guided detection of linking errors, and to apply this approach to validate linkage of admissions of newborns. Methods: Our double-blind validation procedure consisted of three steps: sample selection, data collection and data analysis. The linked Dutch national newborn admission registry contained 30,082 records for 2001 including readmissions (7.4%) and twins (9.7%). A highly informative sample was selected from the linked file by oversampling uncertain links based on modelderived linking weight. Four hundred and eight fax forms with minimal registry information (admissions of 191 children) were sent out to different pediatric units. The pediatricians were asked to create a short detailed patient history from independent sources. The linkage status and additional record data was validated against this external information. Results: Response rate was 97% (395/408 faxes). Accuracy of the linkage of singleton admissions was high: except for some expected errors in the uncertain area (0.02% of record pairs), linkage was error-free. Validation of multiple birth readmissions showed 37% linkage errors due to low data quality of the multiple birth variables. The quality of the linked registry file was still high; only 1.7% of the children were from a multiple birth with multiple admissions, resulting in less than 1% linking error. Conclusions: Our external validation procedure of record linkage was feasible, efficient, and informative about identifying the source of the errors.