Turning a Data-Rich NHS into a Research-Ready System
The UK has abundant relevant data from the NHS and a range of other sources, but providing access to the right people at the right time in the right way is an incredibly complex task.
The team at Oxford University Hospitals NHS Foundation Trust understood that researchers and analysts need rapid access to real-world data. This includes images such as X-rays and MRI scans, detailed analysis from lab tests and the millions of notes and data points captured as part of day-to-day care in hundreds of electronic patient record and specialist systems. OUH also understood that this must be achieved safely and securely, with public trust at the core.
Traditional approaches to accessing health data for purposes beyond direct care can be cumbersome, slow and ineffective. It can take years to access data from across organisations, only to find that it is incomplete or lacks the granular context required for developing new medicines and training AI models. To achieve OUH’s ambition, they had a number of key hurdles to overcome included:
- Fragmented infrastructure: The trust operated a traditional on-premises data warehouse that was siloed across departments and partner organisations, limiting scalability and making it difficult to support growing data volumes or advanced analytics.
- Restricted research capabilities: Biomedical research was hindered by slow data access, inconsistent formats, and limited interoperability with external partners. There was no unified environment to support Trusted Research Environment (TRE) standards or secure multi-party collaboration.
- Security and governance gaps: Security monitoring and incident response were not centralised or automated, and there was no integrated SIEM/SOAR capability for the Azure environment.
- Administrative burden: Clinicians were spending excessive time on IT and administrative tasks due to disjointed systems and lack of self-service tools.
Oxford University Hospitals NHS Foundation Trust needed a solution that could unify data across care settings, enable secure research collaboration, and reduce the operational burden on clinical and IT teams