Literature DB >> 21351307

Linkage of mother-baby pairs in the German Pharmacoepidemiological Research Database.

Edeltraut Garbe1, Marc Suling, Sebastian Kloss, Christina Lindemann, Ulrike Schmid.   

Abstract

PURPOSE: Administrative healthcare databases are increasingly being used to investigate potential drug risks in pregnancy. Our study aimed to develop an algorithm for linkage of mother-baby pairs (MBPs) in the German Pharmacoepidemiological Research Database (GePaRD) as a prerequisite for such studies.
METHODS: GePaRD contains sociodemographic data, drug dispensations, ambulatory, and hospital information on more than 14 million insurants from four German statutory health insurances (SHIs) covering all regions in Germany. Linkage was based on co-insurance information of the newborn with the potential mother (direct linkage) or of both potential mother and newborn with the potential father (indirect linkage). Linkage is not possible if the baby is co-insured with the father and the mother is self-insured. Further information on birth or childbed was used to validate the potential mother as true mother in MBP. Descriptive comparisons between linked and unlinked mothers were conducted.
RESULTS: Of 323,993 newborns identified between 2004 and 2006, 250,355 (77.3%) could be linked in MBP. Of those, 189,702 (75.8%) MBP were based on direct linkage. Mean age was similar in linked (31.1 years, standard deviation (SD = 5.4) and unlinked (31.8 years, SD = 5.5) mothers as was the proportion of caesarean sections in both groups (28.9% vs. 29.3%).
CONCLUSIONS: The developed algorithm permits linkage of a great number of newborns with their mothers and creates a potential data source for investigation of drug risks in pregnancy. Further validation studies are needed also including information on pregnancies not resulting in live births.
Copyright © 2010 John Wiley & Sons, Ltd.

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Year:  2010        PMID: 21351307     DOI: 10.1002/pds.2038

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  13 in total

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