(054) Supporting pharmacovigilance signal validation and prioritisation with analyses of routinely collected health data – lessons learned from an EHDEN network study

Publication Number: 1050

Background: 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 prioritisation of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in epidemiological studies to assess communicated signals.

Objectives: To examine the feasibility and utility of analysing routinely collected health data from a multinational distributed network to support signal validation and prioritisation.

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 was 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, out 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 (out of which 15-60 minutes for execution) and informed decisions for 6 out of 8 signals. The impact of insights from 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, of which two were supported by insights from these data.

Conclusions: Analyses of multi-source routine health data to support signal validation and prioritisation are feasible and can inform decision-making. The cost-benefit of integrating these data at this stage of signal management requires further research.