Establishment of a pharmacoepidemiological database in Germany: methodological potential, scientific value and practical limitations

Pharmacoepidemiol Drug Saf. 2008 Mar;17(3):215-23. doi: 10.1002/pds.1545.


Purpose: We present a new population-based pharmacoepidemiological (PE) database obtained from statutory health insurances (SHIs) that is able to generate signals, to monitor prescribed drugs and to describe drug utilisation. We discuss methodological features of the database and we assess to which degree this database reflects basic demographic characteristics and hospitalisation rates of the general population.

Methods: Files of three SHIs were linked with drug dispensation data from a pharmacies' electronic data processing centre on an individual basis using the unique subject identification number (ID) at a trusted third party centre. Plausibility checks and descriptive analyses were carried out.

Results: The database covers 3.6 million SHI-members, provides drug utilisation data and data on hospitalisations. SHI membership is fairly stable over time. Our data indicate marked differences in socio-demographic characteristics between SHIs. Hospital admission rates standardised for age vary between 0.164 and 0.229 per person year, which is in good agreement with official statistics (0.20). The age distribution shows good agreement for men and some underrepresentation for women above the age of 60 as compared to the general population.

Conclusions: Confounder information on medical conditions, concomitant medications and socio-demographic variables can be obtained from the database, while the assessment of confounders related to lifestyle requires supplementary data collection. The database allows for a population-based approach and reflects daily practice including off-label use of drugs. Independent recording of exposure and outcome data prevents reporting bias on medication or outcome. Legal conditions that allow continuous updating of the database need to be settled.

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Aged
  • Databases, Factual*
  • Drug Utilization / statistics & numerical data*
  • Female
  • Germany
  • Hospitalization / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • Pharmacoepidemiology / methods*
  • Sex Factors