How data is analysed and the associated benefits to population health care will be presented to delegates attending the Digital Health Rewired conference taking place in London (15-16 March).
I-Lin Hall, NECS Head of Data and Digital Applications (pictured above) along with Mark Walsh, Portfolio Manager from the Academic Health Science Network North East, and North Cumbria (AHSN NENC) will set out how they are improving how data is linked and analysed for the purposes of service improvement, new innovations, and research.
Representatives from Axym and the Trusted Research and Evaluation Environment Programmes (or TREE as it is referred) will speak on the first day of the event on the Artificial Intelligence (AI) and Data Workstream stage at the annual Digital Health conference.
Axym builds upon the existing ICS-wide data infrastructure and provides a robust environment for local areas and organisations to collaborate. Axym supports partnership working across health and care and organisations including universities, public and third sector. It aligns with national support offers and direction, minimising duplication and supporting local requirements.
TREE builds on Axym’s work by providing a safe and secure environment for researchers and analysts to collaborate using common and linked datasets to evaluate healthcare challenges.
The shared infrastructure that TREE brings means that it can be accessed by approved professionals from across the region to analyse linked data from multiple sources and apply complex analysis in a safe environment. Access to TREE will be strictly governed in line with regional, legal and ethical processes around the use of data.
Both programmes are enabling our region to take huge steps in terms of cross-sector collaborations and how we analyse, interpret, and derive insights from the data collected. We will be able to link together data from across the system in ways we haven’t been able to before – which will help us as a region improve decision making and research capabilities based on evidence collected locally.