On 19 October 2026, the Eastern England Secure Data Environment (SDE) hosted a webinar exploring how artificial intelligence (AI) and secure access to NHS data could support the prediction of hospital-acquired pressure ulcers.
The webinar showcased a pioneering research project led by Imperial College London, which is using de-identified patient data within the Eastern England Secure Data Environment to externally validate a machine learning model designed to predict hospital-acquired pressure ulcers.
During the session, attendees heard about the journey from research to implementation, including how the algorithm is being validated using patient data within the SDE and why external validation is such an important step before AI tools can be adopted in clinical practice. The discussion also highlighted the role of secure data environments in enabling health research while maintaining high standards of patient privacy and security.
The webinar provided practical insights for researchers, innovators and healthcare professionals interested in accessing de-identified NHS data for research. Attendees learned more about routes to data access, available datasets and the experiences of researchers working within the Eastern England Secure Data Environment.
Watch the webinar recording
If you were unable to attend, or would like to revisit the discussion, you can watch the webinar recording below:
The recording explores:
- The development and validation of a machine learning model for predicting hospital-acquired pressure ulcers
- The importance of external validation before clinical adoption of AI tools
- How secure data environments support health research while protecting patient privacy
- The process of accessing de-identified NHS data for research
- Lessons learned from conducting research within the Eastern England SDE
To learn more about the project featured in the webinar, visit the project page here
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