Integrated Care System Partnership Programme
The University of Hertfordshire is working in partnership with the Central East Integrated Care System (CEICS) to bring together health, care and education. By working with organisations across the region and beyond, particularly within health and social care, the partnership supports collaboration on innovation, research and service development.
Innovation, integration, impact
We are committed to using our academic expertise, research capabilities, and advanced facilities to support this partnership. Together, we address key challenges, drive impactful innovation, and maximise knowledge exchange to create real, lasting change.
Through this programme, we aim to:
- strengthen system credibility and innovation;
- address complex challenges through collective action;
- build capacity and develop talent across organisations;
- leverage knowledge exchange and research;
- facilitate shared funding and resource allocation.
The three central hubs
To ensure a long-term positive impact aligned with CEICS's strategic direction, the programme operates through three dedicated hubs.
Key headline projects
The partnership is delivering a range of projects that address key challenges across the health and care system.
Our social value
Our Social Value is an online platform that helps voluntary, community, faith and social enterprise (VCFSE) organisations measure and communicate the wider impact of their work beyond financial outcomes. Developed in partnership with the sector, it supports organisations in recording activities, measuring outcomes and demonstrating community value.
Health and care organisations are increasingly asked to demonstrate the difference they make beyond financial outcomes. For the VCFSE, capturing this wider impact can be challenging.
Our Social Value is an online tool designed to help organisations measure and communicate their impact in a clear and practical way. Led by Professor Eren Demir (Hertfordshire Business School) and Hannah Morgan‑Gray (VCFSE Alliance), and developed in partnership with CEICS and VCFSE organisations, the tool reflects the real‑world needs of the sector. It focuses on outcomes such as wellbeing, prevention and community value, rather than financial return alone.
It allows users to record activities, measure outcomes and generate reports that support funding applications and service improvement. A key feature of the platform is its ability to reflect the local context. By incorporating deprivation data, it recognises that the same intervention can have different levels of impact depending on the community it serves.
Since its launch in October 2025, the tool has seen strong uptake both locally and nationally. Organisations using it span a wide range of services, including community support, housing, youth services and health and wellbeing initiatives.
Elective care web-based Decision Support Tool
The Decision Support Tool (DST) is a simulation-based platform developed to help healthcare organisations model and compare different service scenarios before changes are introduced. It supports more informed, evidence-based decision-making by exploring how changes to patient pathways, staffing and capacity may affect performance and resource use.
Health systems are under pressure to manage growing demand while improving efficiency and reducing waiting times. Planning services effectively requires tools that can test changes before they are introduced.
The DST has been developed to support this need. It is a simulation-based platform, led by Professor Eren Demir (Hertfordshire Business School) and Richard Hammond (Hertfordshire and West Essex Integrated Care Board (HWEICB)), that helps healthcare leaders model and compare different service scenarios.
The DST allows users to explore how changes to patient pathways, staffing levels or clinic capacity may affect performance. By comparing current and proposed scenarios, it supports more informed and confident decision-making. Initially focused on cardiology services, the tool helps identify opportunities to reduce waiting times, improve patient flow and make better use of resources such as staff, beds and theatre capacity.
By combining simulation modelling with data-driven insights, the DST enables organisations to move from reactive planning to a more proactive, evidence-based approach. Its outputs are already being used to support business planning and service redesign across the system.
Immersive technology in healthcare
This project explores how extended reality (XR) can support healthcare training by providing immersive clinical learning experiences in a safe and accessible environment. Designed to be affordable and scalable, it helps healthcare organisations enhance workforce development, build in-house training capability and improve access to restricted clinical settings.
Training and workforce development are critical to the future of health and care services. However, access to real clinical environments can be limited, particularly in high-demand settings such as operating theatres.
This project explores how XR can provide immersive, practical learning experiences in a safe and accessible way. Using XR technology, students and professionals can experience realistic clinical scenarios without needing to be physically present, helping to build confidence, develop skills and improve understanding of complex environments.
A key focus is creating a solution that is both affordable and scalable. Unlike many existing XR initiatives, which rely on costly or specialist platforms, this approach is designed to be flexible and sustainable for long-term use.
The project also enables healthcare organisations to develop and adapt their own training content, reducing reliance on external providers and supporting in-house capability.
Led by Professor Salvatore Livatino (School of Physics, Engineering and Computer Science), Sasha Irons (HWEICB) and Professor Nikhil Vasdev (Robotic Surgery, Lister Hospital), the initiative demonstrates how XR can open access to restricted clinical settings, supporting recruitment, enhancing training and strengthening the future workforce.
Al-driven modelling for future system needs
This project uses AI-enabled modelling tools to help healthcare organisations forecast future demand across health and care services. By analysing demographic and service data, it supports evidence-based planning, helping systems assess capacity needs, test service scenarios and make more informed decisions.
Health and care services are under increasing pressure as demand continues to rise and populations grow and age. In Hertfordshire and West Essex, this challenge is particularly significant, with a marked increase in the number of people aged over 85 expected in the coming years. Understanding future demand, and the system’s capacity to respond, is essential for protecting services and ensuring high-quality care for the most vulnerable.
In response, the CEICS has agreed a transformation programme aligned to its strategic priorities for improving population health. A key part of this work is the development of a strengthened system intelligence function, using data and analytics to support effective, evidence-based decision‑making.
The University’s School of Physics, Engineering, and Computer Science, led by Professor Iosif Mporas (School of Physics, Engineering and Computer Science) and Charlotte Mullins (HWEICВ), is supporting this ambition through the development of AI-enabled modelling tools. These tools forecast demand across health and care services by analysing demographic trends and service data to simulate patient behaviour and predict admission risk and emergency attendance. By accounting for population growth, particularly among those aged over 85, they help the system identify future capacity requirements and potential pressure points.
The AI‑driven models will be integrated into a decision‑support framework, enabling healthcare organisations to test scenarios, assess the potential impact of service changes, and align workforce, capacity and financial planning. This approach supports more proactive, informed decision-making while helping to build and retain analytical capability across the system.
For more information about the programme and projects, and to explore how you can get involved, please get in touch.