AI can cut surgical waiting lists

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AI can cut surgical waiting lists

Artificial Intelligence (AI) designed to identify patients suitable for joint replacement surgery has the potential to significantly cut waiting times and improve surgical efficiency according to new research from the University of Aberdeen.

The study found that using the Aberdeen-led AI could help to ‘rapidly’ and ‘accurately’ identify patients that are suitable for hip replacement surgery, cut waiting lists and help to ensure that the right person is seen by the right clinician at the right time.     

Dr Luke Farrow, Clinical Research Fellow, from the University of Aberdeen who led the study said: “We identified that the radiologist’s summary of x-ray findings can be successfully used to help predict which patients referred for consideration of hip replacement will go on to have surgery.  

“This is the first comprehensive study to confirm the potential of Artificial Intelligence in this field.” 

While this is an exciting development with potential for radically improving patient care, Dr Farrow and the team found that the AI still needs to be trained according to the specific characteristics of the healthcare setting it is to be used in.   

He said: “The effectiveness of the developed AI algorithm deteriorated significantly when faced with radiology reports from a different healthcare setting, indicating a need for further training on a wider, more diverse population. 

“Further development is needed to ensure that the algorithm works better when applied to new healthcare settings, such as different NHS trusts. With any AI algorithm it is important to ensure that it functions effectively in the real world.”  

However, with waiting lists for joint replacement surgery currently at an all-time high, this new technology has the potential to transform a highly saturated system: “Using this AI tool in clinical practice would allow for rapid automated review of many patients which would likely significantly improve efficiency and reduce associated costs – this could change the lives of thousands of patients who have been waiting for years to reach the top of surgical lists.” added Dr Farrow.  

Steven Lewis, 52, from Aberdeenshire, began to notice pain in his hip while following his passion for trail running. What started as reduction in mobility and ‘niggling pain’, developed into a continual limp, chronic pain and discomfort. Steven went from running the hills of Aberdeenshire to being unable to even sit or sleep without pain in a period of a few months.  

Unable to register with a GP since moving from England more than a year ago, Steven was conscious that he would have a long wait to get his hip replaced.  

“I moved to Scotland more than a year ago and have yet to find a GP that will take me.  

“I have seen the reports of people having to wait years for hip replacements and I knew I couldn’t wait that long.  

“The pain was having a huge impact on my life - I missed running of course, but more than that – I couldn’t get any relief from it – even when I was trying to sleep.”  

Steven is able to access private healthcare through his employer and is now considering hip replacement surgery from a private healthcare provider. 

Using AI to streamline the process can only be a good thing in Steven’s opinion: “Data enabled decision making to support humans is now at the forefront of technology and has huge potential across many industries.  

“I have heard horror stories of people waiting years for hip replacements so if it can be used to help patients receive a swifter diagnosis and remedial surgery where required it can only be seen as a positive.” 

It is hoped that with ongoing further development of the technology it will be available within the NHS in the next few years. 

  

ENDS 

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