This task aims to work towards a national and international European collaborative platform to exchange data and knowledge with the potential to grow towards synoptic real-time sharing of clinical data. We will start out with a minimal viable product that is a shared workspace for healthcare workers at ICUs, including physicians, nurses, and associated professionals.
The workspace will allow the individual user to deposit anonymised data and create visualisations, such as time series across multi-dimensional and multi-modal data, to support interactive synchronous and a-synchronous case reviews and consultations, a best teaching practise in medicine known as Grand Rounds. The long-term objective of the workspace is to increase skills of healthcare workers, reduce gaps in education, and shorten the time from scientific evidence generation to clinical practice implementation.
This task includes the following subtasks:
T6.6.1
Deploy an interactive workspace accessible to healthcare workers and students that enables review of anonymised multi-modal data.
T6.6.2
Develop virtual patient simulations based on realistic clinical cases where users can practise scenarios, a so-called skills lab within the Grand Rounds Workspace.
T6.6.3
Implement personalised learning experience by leveraging machine learning algorithms to personalise education content based on user’s performance in simulations to give feedback and recommendations.
T6.6.4
Implement aggregated performance analytics from data gathered during healthcare worker’s interactions with the workspace, such as response times and learning results to prioritise the continued development of the Grand Rounds Workspace and compare performance across regions.
Use case leader
