W Oberaigner1, W Stühlinger. 1. Cancer Registry of Tyrol, TILAK GmbH, Anichstrasse 35, 6020 Innsbruck, Austria. willi.oberaigner@iet.at
Abstract
OBJECTIVE: Record linkage of patient data originating from various data sources and record linkage for checking uniqueness of patient registration are common tasks for every cancer registry. In Austria, there is no unique person identifier in use in the medical system. Hence, it was necessary and the goal of this work to develop an efficient means of record linkage for use in cancer registries in Austria. METHODS: We adapted the method of probabilistic record linkage to the situation of cancer registries in Austria. In addition to the customary components of this method, we also took into consideration typing errors commonly occurring in names and dates of birth. The method was implemented in a program written in DELPHI(TM) with interfaces optimised for cancer registries. RESULTS: Applying our record linkage method to 130,509 linkages results in 105,272 (80.7%) identical pairs. For these identical pairs, 88.9% of decisions were performed automatically and 11.1% semi-automatically. For results decided automatically, 6.9% did not have simultaneous identity of last name, first name and date of birth. For results decided semi-automatically, 48.4% did not have an identical last name, 25.6% did not have an identical date of birth and 83.1% did not have simultaneous identity of last name and date of birth and first name. CONCLUSIONS: The method implemented in our cancer registry solves all record linkage problems in Austria with sufficient precision.
OBJECTIVE: Record linkage of patient data originating from various data sources and record linkage for checking uniqueness of patient registration are common tasks for every cancer registry. In Austria, there is no unique person identifier in use in the medical system. Hence, it was necessary and the goal of this work to develop an efficient means of record linkage for use in cancer registries in Austria. METHODS: We adapted the method of probabilistic record linkage to the situation of cancer registries in Austria. In addition to the customary components of this method, we also took into consideration typing errors commonly occurring in names and dates of birth. The method was implemented in a program written in DELPHI(TM) with interfaces optimised for cancer registries. RESULTS: Applying our record linkage method to 130,509 linkages results in 105,272 (80.7%) identical pairs. For these identical pairs, 88.9% of decisions were performed automatically and 11.1% semi-automatically. For results decided automatically, 6.9% did not have simultaneous identity of last name, first name and date of birth. For results decided semi-automatically, 48.4% did not have an identical last name, 25.6% did not have an identical date of birth and 83.1% did not have simultaneous identity of last name and date of birth and first name. CONCLUSIONS: The method implemented in our cancer registry solves all record linkage problems in Austria with sufficient precision.
Authors: Oliver Preyer; Nicole Concin; Andreas Obermair; Hans Concin; Hanno Ulmer; Willi Oberaigner Journal: BMC Cancer Date: 2017-10-24 Impact factor: 4.430