Developing AI prediction models for arthroplasty PROMs
Research type
Research Study
Full title
The development and validation of artificial intelligence algorithms for predicting clinically important changes in Patient Reported Outcome Measures following hip and knee arthroplasty
IRAS ID
337618
Contact name
David Sochart
Contact email
Sponsor organisation
Epsom and St Helier University Hospitals NHS Trust
Duration of Study in the UK
0 years, 6 months, 1 days
Research summary
This research project aims to improve how doctors predict patient outcomes after knee and hip replacement surgeries. When patients undergo these surgeries, their improvement is often measured using scores that reflect their views on pain and function. However, it can be challenging for doctors to anticipate who will benefit the most from surgery. This project will use a computer-based approach, known as machine learning, to predict these outcomes more accurately.
A computer can learn to recognise patterns within large amounts of data that humans might not easily see. In this case, we will review past medical records of patients who have had knee or hip replacement surgery, focusing on their recovery scores. By doing so, we hope to develop a tool that can predict how much a patient's condition might improve after their surgery.
We'll be using data that has already been collected in the past and will take strict steps to ensure patient data remains anonymous. The database used is from 2004-2022 and consists of 17000 knee replacements, and 15000 hip replacements with 1 year follow up data.
The potential benefits of this research are significant. If successful, doctors could have a better way of predicting patient recovery, leading to more personalised and effective treatment plans. It is a step towards more tailored healthcare, ensuring patients have realistic expectations and doctors can offer the best possible advice and care.
In summary, our study is about using advanced computer methods to help improve the quality of life for people undergoing knee and hip replacement surgeries by providing doctors and patients with a tool to better predict patient outcomes.
REC name
East of Scotland Research Ethics Service REC 2
REC reference
24/ES/0054
Date of REC Opinion
11 Jul 2024
REC opinion
Further Information Favourable Opinion