title: Linkage of mother-baby pairs in the German Pharmacoepidemiological Research Database.
abstract: OBJECTIVE
  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.
authors.affiliation: Bremen Institute for Prevention Research and Social Medicine, University of Bremen, Germany. garbe@uni-bremen.de
authors.forename: Edeltraut
authors.initials: E
authors.lastname: Garbe
authors.forename: Marc
authors.initials: M
authors.lastname: Suling
authors.forename: Sebastian
authors.initials: S
authors.lastname: Kloss
authors.forename: Christina
authors.initials: C
authors.lastname: Lindemann
authors.forename: Ulrike
authors.initials: U
authors.lastname: Schmid
mesh_terms: D016208:Databases, Factual / Q000706:statistics & numerical data; D004363:Drug Utilization / Q000706:statistics & numerical data; D064420:Drug-Related Side Effects and Adverse Reactions; D005260:Female; D005858:Germany; D006302:Health Services Research / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D007231:Infant, Newborn; D008498:Medical Record Linkage / Q000379:methods*; D009313:National Health Programs / Q000706:statistics & numerical data; D017891:Pharmacoepidemiology / Q000379:methods* / Q000706:statistics & numerical data; D011247:Pregnancy