Open AccessA common data model for harmonization in the Nordic Pregnancy Drug Safety Studies (NorPreSS)
Author(s) -
Jacqueline M. Cohen,
Carolyn E. Cesta,
Lars Jøran Kjerpeseth,
Maarit K. Lein,
Óskar Hálfdánarson,
Øystein Karlstad,
Pär Karlsson,
Morten Andersen,
Kari Furu,
Vidar Hjellvik
Publication year - 2021
Publication title -
norsk epidemiologi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.134
H-Index - 19
eISSN - 1891-5477
pISSN - 0803-2491
DOI - 10.5324/nje.v29i1-2.4053
Subject(s) - harmonization , raw data , observational study , computer science , pharmacovigilance , safer , data science , medicine , risk analysis (engineering) , data mining , drug , pharmacology , computer security , physics , pathology , acoustics , programming language
It is necessary to carry out large observational studies to generate robust evidence about the safety of drugs used during pregnancy. In the Nordic countries, nationwide population-based health registers that document all births and dispensed prescribed drugs are valuable resources for such studies. A common data model (CDM) is a data harmonization and structuring tool that enables a unified and streamlined analytic approach for studies including data from multiple countries or databases. We describe a CDM developed for the Nordic Pregnancy Drug Safety Studies (NorPreSS), including details on data sources and structure of the data tables. We also provide an overview of the advantages and disadvantages of the approach (e.g. sharing of data analysis programs versus extra initial work to create CDM datasets from raw data).