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 model-derived 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.