药物警戒
医学
数据收集
药物流行病学
观察研究
数据科学
数据质量
计算机科学
药理学
不利影响
工程类
病理
运营管理
公制(单位)
统计
数学
药方
作者
Jonathan L. Richardson,Alan Moore,Rebecca Bromley,Michael Stellfeld,Yvonne Geissbühler,Matthew Bluett-Duncan,Ursula Winterfeld,Guillaume Favre,Amalia Alexe,Alison Oliver,Yrea R.J. van Rijt-Weetink,Kenneth Hodson,Bita Rezaallah,Eugène van Puijenbroek,Donna Lewis,Laura Yates
出处
期刊:Drug Safety
[Springer Nature]
日期:2023-03-28
卷期号:46 (5): 479-491
被引量:7
标识
DOI:10.1007/s40264-023-01291-7
摘要
The risks and benefits of medication use in pregnancy are typically established through post-marketing observational studies. As there is currently no standardised or systematic approach to the post-marketing assessment of medication safety in pregnancy, data generated through pregnancy pharmacovigilance (PregPV) research can be heterogenous and difficult to interpret. The aim of this article is to describe the development of a reference framework of core data elements (CDEs) for collection in primary source PregPV studies that can be used to standardise data collection procedures and, thereby, improve data harmonisation and evidence synthesis capabilities.This CDE reference framework was developed within the Innovative Medicines Initiative (IMI) ConcePTION project by experts in pharmacovigilance, pharmacoepidemiology, medical statistics, risk-benefit communication, clinical teratology, reproductive toxicology, genetics, obstetrics, paediatrics, and child psychology. The framework was produced through a scoping review of data collection systems used by established PregPV datasets, followed by extensive discussion and debate around the value, definition, and derivation of each data item identified from these systems.The finalised listing of CDEs comprises 98 individual data elements, arranged into 14 tables of related fields. These data elements are openly available on the European Network of Teratology Information Services (ENTIS) website ( http://www.entis-org.eu/cde ).With this set of recommendations, we aim to standardise PregPV primary source data collection processes to improve the speed at which high-quality evidence-based statements can be provided about the safety of medication use in pregnancy.
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