Integrating electronic health records with other data sources for postmarket drug safety signal identification: a review

Electronic health records (EHRs) have emerged as resources for both the identification of adverse drug events (ADEs) and general population health surveillance, however questions remain around how best to utilize EHR data for drug safety signal identification. While the majority of signal identifica...

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Main Authors: Julie V. Kim (Author), Sharon E. Davis (Author), Michael E. Matheny (Author), Joshua C. Smith (Author)
Format: Book
Published: Frontiers Media S.A., 2024-11-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Julie V. Kim  |e author 
700 1 0 |a Julie V. Kim  |e author 
700 1 0 |a Sharon E. Davis  |e author 
700 1 0 |a Michael E. Matheny  |e author 
700 1 0 |a Michael E. Matheny  |e author 
700 1 0 |a Joshua C. Smith  |e author 
245 0 0 |a Integrating electronic health records with other data sources for postmarket drug safety signal identification: a review 
260 |b Frontiers Media S.A.,   |c 2024-11-01T00:00:00Z. 
500 |a 2674-0869 
500 |a 10.3389/fdsfr.2024.1428831 
520 |a Electronic health records (EHRs) have emerged as resources for both the identification of adverse drug events (ADEs) and general population health surveillance, however questions remain around how best to utilize EHR data for drug safety signal identification. While the majority of signal identification research has utilized spontaneous reports and health insurance claims, these data also have limitations. Pharmacovigilance approaches combining EHR data with other data sources have the potential to address many of the shortcomings of individual sources. This mini-review seeks to provide an overview of some of the recent research leveraging EHR data in combination with spontaneous reports, claims data, and other pharmacovigilance data sources for drug safety signal identification. Studies have shown that combining EHR data with these and other sources is often beneficial compared to the use of a single source alone, however the synergism or friction introduced is insufficiently explored in current literature. Our review explores how EHR data benefits signal identification when used in combination with other sources, what methods have been applied, and what considerations have previously been noted. Finally, we identify gaps in current research and highlight important considerations for future work using multiple real world data sources for drug safety surveillance. 
546 |a EN 
690 |a pharmacovigilance 
690 |a safety signal identification 
690 |a electronic health records 
690 |a spontaneous reporting systems 
690 |a adverse drug events 
690 |a Therapeutics. Pharmacology 
690 |a RM1-950 
655 7 |a article  |2 local 
786 0 |n Frontiers in Drug Safety and Regulation, Vol 4 (2024) 
787 0 |n https://www.frontiersin.org/articles/10.3389/fdsfr.2024.1428831/full 
787 0 |n https://doaj.org/toc/2674-0869 
856 4 1 |u https://doaj.org/article/8b86ed7aeb82437fba2d0273e12a669d  |z Connect to this object online.