Gesundheitswesen
Volume 68, Issue 10, 2006, Pages 643-649

Name-based identification of cases of Turkish origin in the childhood cancer registry in Mainz [Namensbasierte identifizierung von fällen mit Türkischer herkunft im kinderkrebsregister Mainz] (Article)

Spallek J.* , Kaatsch P. , Spix C. , Ulusoy N. , Zeeb H. , Razum O.
  • a AG 3 - Epidemiologie and International Public Health, Fakultät für Gesundheitswissenschaften, Universität Bielefeld, Mainz, Germany, AG3: Epidemiologie and International Public Health, Fakultät für Gesundheitswissenschaften, Universität Bielefeld, Postfach 10 01 31, 33501 Bielefeld, Germany
  • b Deutsches Kinderkrebsregister am IMBEI, Institut für Medizinische Biometrie, Epidemiologie und Informatik, Mainz, Germany
  • c Deutsches Kinderkrebsregister am IMBEI, Institut für Medizinische Biometrie, Epidemiologie und Informatik, Mainz, Germany
  • d AG 3 - Epidemiologie and International Public Health, Fakultät für Gesundheitswissenschaften, Universität Bielefeld, Mainz, Germany
  • e AG 3 - Epidemiologie and International Public Health, Fakultät für Gesundheitswissenschaften, Universität Bielefeld, Mainz, Germany, World Health Organization, Genf, Switzerland
  • f AG 3 - Epidemiologie and International Public Health, Fakultät für Gesundheitswissenschaften, Universität Bielefeld, Mainz, Germany

Abstract

Until now few analyses of routine data relating to the health of migrants have been conducted in Germany. A major obstacle is that most data sources do not provide reliable information on the origin of migrants. While some sources contain the nationality of persons registered, this information does not allow one to identify migrants who have taken up German citizenship, i.e., a substantial part of second-generation migrants. In this paper we demonstrate how a computer-aided, name-based algorithm can be used to identify persons of Turkish origin in the German Childhood Cancer Registry in Mainz, Germany. The performance of the algorithm, as assessed against the gold standard of assessing names manually, was very good (sensitivity and specificity ≥0.975). In total, we identified 1774 of the 37 259 cases in the registry as being of Turkish origin. The name algorithm proved to be a useful tool to identify Turkish migrants in routine data sources, thus avoiding potential bias due to changes in citizenship. This approach aims at improving migrant-sensitive health reporting and research in Germany. In future, additional information on migrant status should be obtained already during primary data collection so that health data for all migrant groups can be provided. © Georg Thieme Verlag KG Stuttgart.

Author Keywords

Transients and migrants cancer Turkish children cancer registry

Index Keywords

Germany childhood cancer Registries Neoplasms human Names medical research controlled study Turkey (republic) algorithm Algorithms artificial intelligence Humans cancer registry sensitivity and specificity Article major clinical study migration Turkey Emigration and Immigration Natural Language Processing computer aided design citizenship Child
Link
https://www.scopus.com/inward/record.uri?eid=2-s2.0-33845257338&doi=10.1055%2fs-2006-927166&partnerID=40&md5=e93d17f1af09ac0b187527ec4627305c
DOI: 10.1055/s-2006-927166
ISSN: 09413790
Cited by: 23
Original Language: German