Information Extraction, Matching and Reporting for Medical Devices Vigilance

Abstract

Medical devices play a vital role in the delivery of high quality healthcare with their numbers increasing exponentially during the past fifty years. Although recent technological advancements have led to much more reliable and safer Medical Devices (MDs), potential risks of failure and the associated adverse incidents cannot be ignored. To create a safer environment for the patient in terms of technology, it is necessary to provide rapid and accurate information on adverse events, in order to avoid their repetition. The traditional approach of MD Vigilance based only on official user reports of adverse incidents has been proven inadequate today. A modern approach, also used in this work, to the problem is based on the introduction of additional means, such as data mining, extraction, standardization and codification of the information, from different direct and indirect sources worldwide, and its systematic classification and archiving in dedicated databases. The aim is to timely extract information on potentially hazardous MDs and to make it available where appropriate.