Pressure ulcers, also known as bedsores, are one of the top ten harms in the NHS, affecting up to 10% of hospital patients and costing the health service an estimated £3.8 million every day. A new white paper released by Tunley Environmental and Bassetlaw Teaching Hospitals NHS Foundation Trust demonstrates how artificial intelligence (AI) could transform prevention and management, creating benefits for patients, healthcare budgets and the environment.
The white paper, Pressure Ulcer Prevention with AI: Improving Outcomes and Sustainability, introduces the Pressure Ulcer Clinical Pathway Aid (PU-CPA). Developed through the SBRI Healthcare programme, the tool combines predictive machine learning with clinical knowledge to recommend personalised, evidence-based pathways that reduce risks and improve patient care.
Co-authored by sustainability scientists Dr Aaron Yeardley, Dr Nathan Wood and Dr William Beer from Tunley Environmental, alongside Dr Jane Fearnside and Kelly Phillips from Bassetlaw Teaching Hospitals NHS Foundation Trust, the white paper highlights the enormous clinical, financial and environmental challenges posed by pressure ulcers. Current management strategies, such as repositioning and pressure-redistributing devices, are often limited by difficulties in determining the most effective patient-specific care.
Dr Aaron Yeardley
Dr Aaron Yeardley, Science Co-Lead at Tunley Environmental, said, “Our PU-CPA tool uses AI algorithms on real data to recommend personalised care paths that improve healing, cut costs, and lower carbon emissions for the NHS. Reaching proof-of-concept is thrilling and it proves this works and sets us up to scale it across the NHS.”
The white paper also outlines the environmental case for innovation. With wound care estimated to cost the NHS £8.3 billion annually and generating high levels of medical waste, tools such as the PU-CPA could contribute to sustainable healthcare practices aligned with Net Zero ambitions.
The full paper is now available to download via Tunley Environmental here.
