Challenges Associated with the Safety Signal Detection Process for Medical Devices

Abstract

Background: Previous safety issues involving medical devices have stressed the need for better safety signal detection. Various European Union (EU) national competent authorities have started to focus on strengthening the analysis of vigilance data. Consequently, article 90 of the new EU regulation states that the European Commission shall put in place systems and processes to actively monitor medical device safety signals. Methods: A systematic literature review was conducted to synthesize the current state of knowledge and investigate the present tools used for medical device safety signal detection. An electronic literature search was performed in Embase, Medline, Cochrane, Web of science, and Google scholar from inception until January 2017. Articles that included terms related to medical devices and terms associated with safety were selected. A further selection was based on the abstract review. A full review of the remaining articles was conducted to decide on which articles finally to consider relevant for this review. Completeness was assessed based on the content of the articles. Results: Our search resulted in a total of 20,819 articles, of which 24 met the inclusion criteria and were subject to data extraction and completeness scoring. A wide range of data sources, especially spontaneous reporting systems and registries, used for the detection and assessment of product problems and patient harms associated with the use of medical devices, were studied. Coding is remarkably heterogeneous, no agreement on the preferred methods for signal detection exists, and no gold standard for signal detection has been established thus far. Conclusion: Data source harmonization, the development of gold standard signal detection methodologies and the standardization of coding dictionaries are amongst the recommendations to support the implementation of a new proactive approach to signal detection. The new safety surveillance system will be able to use real-world evidence to support regulatory decision-making across all jurisdictions.