New research fellowship

Invention for Innovation - AI in MSK highlight notice

Introduction

Orthopaedic Research UK is seeking to co-fund research applications in the April 2023 Product Development Award call 26 and Challenge call 15 of the NIHR Invention for Innovation (i4i) programme with the aim of transforming Musculoskeletal (MSK) health outcomes through the application of Artificial Intelligence (AI).

Background

Over 20 million people in the UK (around a third of the population) live with a MSK condition such as arthritis and low back pain. Not surprisingly MSK conditions account for one in seven of GP consultations and 7.3% of hospital admissions (1.26 million finished admission episodes) in England. There is also a significant impact on the workplace with MSK conditions accounting for 15% of ‘working days lost’ in 2020.

The size of waiting lists for all hospital procedures has been exacerbated by the COVID-19 pandemic. According to the British Orthopaedic Association, patients awaiting elective Trauma and Orthopaedic (T&O) surgery, including knee and hip replacements, instability and arthritis, fractures and dislocations, account for the largest proportion of people on hospital waiting lists in England; over 700,000 people were waiting for T&O surgery at the end of 2021, the largest total for over a decade. Over 60,000 people had been waiting for over a year – the equivalent figure for January 2020 was only 436.

It is widely recognised that the use of AI, especially when harnessing the vast amount of available patient data, can play an important role in improving clinical performance and patient outcomes. There are many examples of how AI is transforming the prevention, diagnosis, treatment and management of people with poor MSK health. It is delivering better patient outcomes and enhancing the performance and effectiveness of clinical teams. It is improving the accuracy of radiographic image analysis. It is creating 3D orthopaedic templates to provide orthopaedic surgeons with a more detailed view of anatomical structures, enabling them to be more precise in the selection of replacement joints and prosthetics. Healthcare teams armed with AI enabled data, including images sourced from motion capture, are making better decisions about the scheduling and planning of procedures and identifying patients likely to require higher levels of post operative care and those most at risk of artificial joint failure. Data from wearable technology is being used to monitor patient rehabilitation.

To make a significant contribution to the health of the majority of patients demanding support, and reduce the costs to the NHS, the application of AI technology must be broadened and accelerated and access to data improved. Scepticism about the use of AI to inform decision making in healthcare among both healthcare professionals and patients must also be countered. In Orthopaedic Research UK’s our survey of the MSK community, 86% agreed that further work is required to counter scepticism among healthcare professionals about the use of AI to inform decision making in healthcare and 80% agreed that further work is required to counter patient scepticism or concern.

Aim of the focus in AI and musculoskeletal health

This highlight notice is intended to support the research and development of advanced AI solutions to
improve operational efficiencies and clinical outcomes in people with poor musculoskeletal health.

The areas of focus should fall into any of the following areas:

  • Diagnosis
  • Self-management
  • Treatment optimisation
  • Monitoring
  • Risk stratification
  • Health economics

Applicants need to demonstrate:

  • The novelty of the AI solution?
  • What the unmet need is that the proposed AI solution addresses?
  • How project outcomes will lead to improved musculoskeletal care and offer significant added
    value over current or alternative solutions?
  • How will they ensure the acceptability of the technology to people with musculoskeletal
    conditions, their families, healthcare professionals and providers?
  • How the proposed AI solution could impact or integrate into patients’ daily lives and NHS care
    pathways
  • Consideration of potential commercialisation routes for the AI solution which will inform the
    clinical and health economic evidence that needs to be generated.

How to apply