Timely Transfers, Safer Care: A Collaborative Approach for Analytics-Driven Improvement of Inter-Site Hospital Patient Transfers
Aneurin Bevan University Health Board
Introduction:
This project aimed to align inter-site ambulance capacity with real-world demand across Aneurin Bevan University Health Board (ABUHB), targeting 80% transfer compliance by December 2024. Rising complexity in patient transfers since the Grange University Hospital’s opening exposed mismatches between demand and existing ambulance schedules, leading to clinical delays, inefficient resource use, and inequitable care access.
Methods:
Using the IHI Model for Improvement and a QMS approach, the project was delivered in two PDSA cycles. A multidisciplinary team - including modellers, clinicians, operational leaders, and Cardiff University academics - analysed over 15,000 transfer records. Mathematical modelling and optimisation techniques were applied to test new ambulance schedules, removing inefficiencies while ensuring contract compliance and clinical safety. “Off-mission” transfers were excluded to preserve capacity for critical hospital-to-hospital movement. Extensive stakeholder engagement ensured clinical relevance and practical feasibility.
Outcomes:
By May 2024, average transfer wait times significantly reduced, and over 80% of transfers met the 1- and 4-hour targets. The system became more reliable and person-centred, particularly benefiting patients needing timely step-up care. Staff reported improved job satisfaction due to more predictable, proactive planning. Operational efficiency improved, enabling a reduction in peak-time ambulances and delivering a contract saving of approximately £800,000 without compromising performance. SPC charts demonstrated sustained improvement.
Learnings:
Technical modelling alone isn’t enough - success required co-production, iterative testing, and strong clinical-operational collaboration. PDSA cycles helped phase change safely. Earlier investment in user-friendly tools and clearer governance structures would have accelerated adoption. Embedding quality improvement methods fostered trust and sustained learning.
What Next?
The team will refine model assumptions, reassess transfer targets, and embed QI learning across services. Broader scaling across NHS Wales is underway, with plans to share this analytics-driven, co-produced approach nationally. The project provides a blueprint for smarter, safer, and more sustainable inter-site transport planning.
