Overview

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This session contains two 40 minute panels.

Artificial intelligence (AI) and machine learning (ML) enabled methods have been shown to be feasible for automating the analysis of reports about patient safety incidents which continue to grow. However, the benefits of AI and ML cannot be realized unless tools are translated into real-world clinical settings. This panel will review the state-of-the-art in applying AI and ML to improve the management of patient safety incidents. It will firstly examine methods for identifying incidents by type and severity level, then cover approaches to extract structured data, hybrid models, and approaches for translating tools into routine use by patient safety managers. The panel aims to: 1) improve understanding about application of current and future AI/ML methods in patient safety; 2) share learnings about approaches for assessing model transportability and integrating tools into real-world settings, and 3) identify gaps and areas for further work

The lifesaving implementation of Covid-19 vaccines was the result of unprecedented collaboration between government, science, international funding bodies, industry and regulatory bodies to speed up the development of vaccines from bench to licensure from 8-15 years to just over 1 year. They were introduced in the face of enormous global need and licensed using provisional license or emergency use authorization. Predominately using novel technology, clinical trials showed efficacy in healthy trial populations and demonstrated reactogenicity, common and some uncommon adverse events. Rarer adverse events following immunisation (AEFI) are detected for vaccines and medicines after implementation, as are duration of protection and performance against new emergent strains. The introduction also occurred in the context of dynamic vaccine confidence and varying acceptance of governmental recommendations regarding both Covid-19 measures and Covid-19 vaccination. The need to rapidly understand real world vaccine effectiveness, safety and social attitudes and concerns regarding Covid-19 vaccines allowed wide-ranging informatics driven innovations in surveillance of safety, effectiveness, understanding dynamic community and cultural attitudes, and how to respond to these.

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