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Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study.

Oskar GauffinJudith S BrandSara Hedfors VidlinDaniele SartoriSuvi AsikainenMartí CatalàEtir ChalabiDaniel DedmanAna DanilovicTalita Duarte-SallesMaria Teresa García MoralesSaara HiltunenAnnika M JödickeMilan LazarevicMiguel A MayerJelena MiladinovicJoseph MitchellAndrea PistilloJuan Manuel Ramírez-AnguitaCarlen ReyesAnnette RudolphLovisa SandbergRuth SavageMartijn SchuemieDimitrije SpasicNhung T H TrinhNevena VeljkovicAnkica VujovicMarcel de WildeAlem ZekariasPeter RijnbeekPatrick RyanDaniel Prieto-AlhambraG Niklas Norén
Published in: Drug safety (2023)
Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost-benefit of integrating these analyses at this stage of signal management requires further research.
Keyphrases
  • healthcare
  • public health
  • decision making
  • electronic health record
  • mental health
  • big data
  • health information
  • clinical practice
  • machine learning
  • human health
  • drug induced
  • artificial intelligence
  • deep learning