Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study
Oskar Gauffin,
Judith S. Brand (),
Sara Hedfors Vidlin,
Daniele Sartori,
Suvi Asikainen,
Martí Català,
Etir Chalabi,
Daniel Dedman,
Ana Danilovic,
Talita Duarte-Salles,
Maria Teresa García Morales,
Saara Hiltunen,
Annika M. Jödicke,
Milan Lazarevic,
Miguel A. Mayer,
Jelena Miladinovic,
Joseph Mitchell,
Andrea Pistillo,
Juan Manuel Ramírez-Anguita,
Carlen Reyes,
Annette Rudolph,
Lovisa Sandberg,
Ruth Savage,
Martijn Schuemie,
Dimitrije Spasic,
Nhung T. H. Trinh,
Nevena Veljkovic,
Ankica Vujovic,
Marcel Wilde,
Alem Zekarias,
Peter Rijnbeek,
Patrick Ryan,
Daniel Prieto-Alhambra and
G. Niklas Norén
Additional contact information
Oskar Gauffin: Uppsala Monitoring Centre
Judith S. Brand: Uppsala Monitoring Centre
Sara Hedfors Vidlin: Uppsala Monitoring Centre
Daniele Sartori: Uppsala Monitoring Centre
Suvi Asikainen: BCB Medical Ltd
Martí Català: University of Oxford
Etir Chalabi: Heliant Ltd
Daniel Dedman: The Medicines and Healthcare Products Regulatory Agency
Ana Danilovic: CHC Zvezdara
Talita Duarte-Salles: Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol)
Maria Teresa García Morales: Universidad Complutense de Madrid
Saara Hiltunen: BCB Medical Ltd
Annika M. Jödicke: University of Oxford
Milan Lazarevic: University Clinical Center Nis
Miguel A. Mayer: Hospital del Mar Medical Research Institute, Parc de Salut Mar
Jelena Miladinovic: University Clinical Center Nis, University Clinical Center Nis
Joseph Mitchell: Uppsala Monitoring Centre
Andrea Pistillo: Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol)
Juan Manuel Ramírez-Anguita: Hospital del Mar Medical Research Institute, Parc de Salut Mar
Carlen Reyes: Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol)
Annette Rudolph: Uppsala Monitoring Centre
Lovisa Sandberg: Uppsala Monitoring Centre
Ruth Savage: Uppsala Monitoring Centre
Martijn Schuemie: Johnson & Johnson
Dimitrije Spasic: University Clinical Center Nis
Nhung T. H. Trinh: University of Oslo
Nevena Veljkovic: Heliant Ltd
Ankica Vujovic: University of Belgrade
Marcel Wilde: Erasmus University Medical Center
Alem Zekarias: Uppsala Monitoring Centre
Peter Rijnbeek: Erasmus University Medical Center
Patrick Ryan: Johnson & Johnson
Daniel Prieto-Alhambra: University of Oxford
G. Niklas Norén: Uppsala Monitoring Centre
Drug Safety, 2023, vol. 46, issue 12, No 6, 1335-1352
Abstract:
Abstract Introduction Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals. Objective The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process. Methods Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals. Results Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15–60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development. Conclusions 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.
Date: 2023
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DOI: 10.1007/s40264-023-01353-w
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