Abstract

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).

Highlights

  • Studies of drug safety in pregnancy typically involve both rare exposures and outcomes

  • We describe the common data model (CDM) approach to data harmonization that the Nordic Pregnancy Drug Safety Studies (NorPreSS) consortium, which started in 2017, carried out to facilitate studies based on data from five Nordic countries

  • In part III we describe how the NorPreSS CDM is designed and populated, by giving the structure of the various data tables

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Summary

Introduction

Studies of drug safety in pregnancy typically involve both rare exposures and outcomes. This necessitates conducting very large studies to generate robust evidence. International or multi-database studies that aim to have a single protocol and analytic approach must account for source data heterogeneity. We describe the common data model (CDM) approach to data harmonization that the Nordic Pregnancy Drug Safety Studies (NorPreSS) consortium, which started in 2017, carried out to facilitate studies based on data from five Nordic countries. In part II we describe the data sources used in NorPreSS. In part III we describe how the NorPreSS CDM is designed and populated, by giving the structure of the various data tables. In part IV we sum up with pros and cons of the CDM approach

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