Related Experiment Video
Updated: Aug 11, 2026
09:30
Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform
Published on: August 17, 2022
Identifying Pregnancies in Population-Based Data Sources: Development and Application of the ConcePTION Pregnancy
Giorgio Limoncella1,2,3, Anna Girardi3, Claudia Bartolini3
1Department of Statistics, Informatics and Applications "Giuseppe Parenti", University of Florence, Florence, Italy.
Pharmacoepidemiology and Drug Safety
|August 9, 2026
Summary
The ConcePTION Pregnancy Algorithm (PA) successfully identified ~2.7 million pregnancies across 10 European data sources. This open-source tool aids in monitoring medication safety during pregnancy and breastfeeding.
Area of Science:
- Pharmacovigilance
- Reproductive Health
- Data Science
Background:
- Monitoring medication safety in pregnancy is crucial for maternal and infant health.
- Existing data sources often lack standardized methods for identifying pregnancies and their duration.
- The ConcePTION project aimed to improve pregnancy and breastfeeding medication safety monitoring.
Purpose of the Study:
- To describe the development and application of the ConcePTION Pregnancy Algorithm (PA).
- To identify pregnancies and estimate their duration in diverse European electronic healthcare data.
- To support multinational studies on medication safety in pregnancy.
Main Methods:
- Mapping 10 European data sources to the ConcePTION Common Data Model.
- Retrieving and reconciling pregnancy-related records into distinct pregnancy episodes.
- Utilizing a random forest model to estimate gestational age for incomplete records.
- Evaluating model performance using cross-validated Root Mean Squared Error (RMSE).
Main Results:
- The PA identified approximately 2.7 million pregnancies across over 2.2 million individuals.
- Pregnancy outcomes included live births (50%-83%), elective terminations (1%-15%), and spontaneous abortions (4%-10%).
- Gestational age was predicted for 6%-89% of records, with RMSE ranging from 17-50 days.
Conclusions:
- An open-source algorithm was developed to identify and date pregnancies, including early stages and those with unknown outcomes.
- The algorithm facilitates multinational research on the use and safety of medications during pregnancy.
- This tool enhances the generation of timely real-world evidence for pregnancy pharmacovigilance.
Related Concept Videos
01:24Testing a Claim about Population Proportion
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
01:12Statistical Software for Data Analysis and Clinical Trials
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...