- Run by Leeds Teaching Hospitals NHS Trust, in partnership with the University of Leeds and Yorkshire and Humber Care Record.
- Aiming to embed data science into clinical care and hospital management.
- Will build on an existing web application to provide health care professionals and hospital managers with interactive analytics for cancer outcomes and waiting time data.
Most data collected by hospitals as part of routine care is not utilised for analytics or organisational intelligence. Although hospitals are required to produce datasets that are shared and analysed by organisations such as NHS Digital or National Cancer Registry and Analytics Service, the outputs of these national bodies are not designed to provide detailed information at a local or regional level.
Skill shortages, insufficient resources, limited data access and interoperability issues are barriers to embedding data science into clinical care and hospital management. This project aims overcome these by combining routinely collected cancer data with open-source analytics tools in a web application.
The app will provide health care professionals and hospital managers with easy to use, interactive analytics for cancer outcomes and waiting time data. Results will be easily exportable to create reports for use in patient records or for managerial oversight.
This project will build on an existing prototype app, AuguR, and will be deployed within a secure regional cloud environment, The Yorkshire Data Arc, so that hospital staff across the region can easily analyse their own cancer data. Hospitals can also have automatically generated data analytics reports emailed straight to key decision makers.
A clinical user group and managerial user group will ensure that the software meets the needs of end users.
The project team aims to showcase how this software could be scaled up to harness the power of cancer data and enable efficiency, generate insight and ultimately improve patient care nationally.
For further information about this project, please contact:
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