Developing and testing a protocol using a common data model for federated collection and analysis of national perinatal health indicators in Europe

Abstract

Context: International comparisons of the health of mothers and babies provide essential benchmarks for guiding health practice and policy, but statistics are not routinely compiled in a comparable way. These data are especially critical during health emergencies, such as the coronavirus disease (COVID-19) pandemic. The Population Health Information Research Infrastructure (PHIRI) project aimed to promote the exchange of population data in Europe and included a Use Case on perinatal health. Objective: To develop and test a protocol for federated analysis of population birth data in Europe. Methods: The Euro-Peristat network with participants from 31 countries developed a Common Data Model (CDM) and R scripts to exchange and analyse aggregated data on perinatal indicators. Building on recommended Euro-Peristat indicators, complemented by a three-round consensus process, the network specified variables for a CDM and common outputs. The protocol was tested using routine birth data for 2015 to 2020; a survey was conducted assessing data provider experiences and opinions. Results: The CDM included 17 core data items for the testing phase and 18 for a future expanded phase. 28 countries and the four UK nations created individual person-level databases and ran R scripts to produce anonymous aggregate tables. Seven had all core items, 17 had 13-16, while eight had ≤12. Limitations were not having all items in the same database, required for this protocol. Infant death and mode of birth were most frequently missing. Countries took from under a day to several weeks to set up the CDM, after which the protocol was easy and quick to use. Conclusion: This open-source protocol enables rapid production and analysis of perinatal indicators and constitutes a roadmap for a sustainable European information system. It also provides minimum standards for improving national data systems and can be used in other countries to facilitate comparison of perinatal indicators.

Trends in caesarean section rates in Europe from 2015 to 2019 using Robson's Ten Group Classification System: A Euro‐Peristat study

“…Using a federated model, individual-level data maintained by representatives from each country (data sources included in Table S1) were formatted into a common data model and transformed by implementing R scripts developed by INSERM/Euro-Peristat to anonymised, aggregated data, and then transferred to the Euro-Peristat coordination team. 11 The common data model is available from https://zenodo.org/recor d/7639001 and the R scripts are available from https://zenodo.org/recor d/6936870. Data outputs were reviewed and verified by representatives from each country and the Euro-Peristat coordination team to ensure the completeness and accuracy of the data.…”

“…Compared with the TGCS analysis conducted using only 2015 data, 2 several countries could not provide the data necessary to analyse births according to the TGCS used in this study (France, due to previous data provided from a routine survey carried out every 5 years; the Netherlands, due to temporary changes to data; Switzerland, due to delivery mode not linked in data hub). 11 Additionally, as discussed extensively in a previous Euro-Peristat article, 2 the use of routine data sources may lead to misclassification, particularly for fetal presentation (as observed based on results for group 9), labour onset and prior CS. Countries differ in classifications for prelabour/intrapartum/emergency CS and for labour induction/augmentation, which implies some heterogeneity of the corresponding TGCS groups between countries.…”

Socioeconomic disparities in changes to preterm birth and stillbirth rates during the first year of the COVID-19 pandemic: a study of 21 European countries

“…As part of the PHIRI project, a new data collection protocol using a federated framework was implemented, involving the definition of a common data model and R-scripts that produce aggregate data tables or analytic results. 31 Each data provider constructed a database following the specifications of the common data model and ran R programmes on their local server to generate results that were transferred to the central coordinating office (see Supplementary appendix A for contributing partners). Only anonymous data aggregated at the country level are used.…”

“…Data items were selected based on the Euro-Peristat core indicators augmented by items identified in a Delphi consensus process with the network members. 31 The consistent international definitions and format of the selected data items were based on previous Euro-Peristat work. Inclusion criteria for the study were all live births and stillbirths ≥22 +0 weeks of gestation or where gestational age (GA) was missing, with a birthweight ≥500 g. Data were collected on births from 2015 to 2020 to allow modelling of time trends in the period before the COVID-19 pandemic.…”

Data reduction when aggregating information about harms associated with medical interventions

“…For the very same reason, it is essential to rely on a lingua franca of research on medical interventions when referring to aggregate data on harms. 9 Additionally, uniformity on characterisation and format of safety data would translate into dataset harmonisation across studies, countries and sponsors, introducing several benefits 10 : federated analyses would bypass data sharing agreement while preserving individual patient’s privacy, increasing access to data and maximising transparency 11 ; linking harmonised data to pharmacovigilance repositories would be facilitated, allowing real-time contribution of multiple data sources into a synchronous environment.…”