£1.2 million grant fuels development of AI platform for early arthritis detection

Henley Business School has secured a significant grant of £1.2 million to develop an innovative machine learning system aimed at improving the early detection and referral of rheumatic and musculoskeletal diseases (RMDs). The project, known as RMD-Health, seeks to transform the way these conditions are identified and managed, offering a pathway to quicker diagnoses and more effective treatment options for individuals living with these conditions.

The initial pilot of RMD-Health is scheduled for 2026-2027, with trials planned at both the Royal Berkshire NHS Foundation Trust and Oxford University Hospitals NHS Foundation Trust. This pilot phase is critical for refining the AI system and moving it toward regulatory approval and subsequent commercialisation, ensuring that it meets the stringent requirements necessary for integration into the broader healthcare system.

The funding for this initiative is provided through a collaboration between the National Institute for Health and Care Research (NIHR), the Engineering and Physical Sciences Research Council, the Health Innovation Partnership, and Henley Business School. This financial support underscores the importance of addressing the pressing challenges associated with RMDs.

RMDs, which encompass conditions like inflammatory arthritis, affect up to one-third of the UK population and represent a leading cause of disability. These conditions place a considerable burden on both individuals and the healthcare system, often resulting in chronic pain, mobility issues, and substantial impacts on daily life.

Professor Weizi (Vicky) Li, who leads the project and serves as a professor of informatics and digital health at Henley Business School, highlighted the economic and healthcare challenges posed by RMDs. She noted, “With an estimated annual cost of £1.8 billion in sick leave and work-related disability for rheumatoid arthritis alone, the current RMD referral system faces huge challenges.”

Professor Li explained how RMD-Health aims to revolutionise the referral process, saying, “Our machine-learning system presents a new approach to RMD referrals. Unlike existing solutions, which often rely on the advice and guidance from already stretched rheumatology specialists, we’re introducing a machine learning-based decision support system enabling doctors to refer patients more accurately and promptly, ultimately leading to quicker and more effective treatment.”

One of the major issues with the current referral process is the delay in accessing specialised care for RMDs, which often results in individuals having to attend multiple GP appointments before receiving the appropriate care. Between 2019 and 2021, GPs accurately identified early inflammatory arthritis in only 40% of cases, leading to an increased workload for secondary care clinicians who must review a large volume of unnecessary referrals.

Dr. Antoni Chan, the project’s co-lead and a consultant rheumatologist at Royal Berkshire NHS Foundation Trust, emphasised the potential impact of the RMD-Health system. He stated, “This exciting and innovative project represents a major step forward in the early detection and referral of RMD, promising improved patient outcomes, reduced healthcare costs and increased efficiency across our healthcare system.” Dr. Chan also noted that during experimental trials at the trust, the AI tool demonstrated “significantly higher accuracy” than traditional clinical criteria and clinicians’ assessments.

Looking ahead, Dr. Chan expressed optimism about the project’s timeline, stating, “With this grant, we fully expect to be on track for regulatory approval at the end of three years.” The goal is to ensure that the system is ready for widespread use, offering tangible improvements in the early detection and management of RMDs.

The development of RMD-Health involves a collaborative effort that brings together AI experts, secondary care specialists, GPs, industry stakeholders, and patient representatives. This partnership aims to create a comprehensive software prototype that will lay the foundation for the future integration of RMD-Health into the NHS, ensuring that the system is both effective and practical for everyday use in clinical settings.

The project is led by Henley Business School, part of the University of Reading, in partnership with several key organisations, including the Royal Berkshire NHS Foundation Trust, the RBFT Health Data Institute, Oxford University Hospitals NHS Foundation Trust, Health Innovation Oxford and Thames Valley, Buckinghamshire, Oxfordshire and Berkshire West Integrated Care Board, and patient leaders. This consortium aims to ensure that the needs of patients remain at the forefront of the system’s development, making it as user-centred as possible.

In a related development, Flok Health, an AI-driven physiotherapy clinic tailored for people experiencing musculoskeletal issues, is set to be implemented within the NHS by autumn 2024. This initiative, announced in June 2024, aims to address the backlog in physiotherapy services and reduce waiting times for those seeking treatment. The deployment of Flok Health, alongside projects like RMD-Health, highlights the growing role of AI in transforming the delivery of healthcare for musculoskeletal conditions across the UK.

With the backing of this £1.2 million grant, the RMD-Health project is poised to make a significant difference in the early detection and referral process for RMDs, ultimately improving the quality of life for those affected and alleviating the pressure on an already strained healthcare system.