The National Health Service (NHS) is one of the busiest healthcare providers in the world, with an astounding 2.3 million interactions with patients every 36 hours. But as the demands on the NHS grow, so do the challenges it faces.
To ensure patient care isn’t put at risk, the NHS must embrace innovation, and its recent announcement to pledge £21 million to NHS Trusts and Networks seeking out AI for diagnostics is one of the prominent efforts in doing so. So, why is now the perfect time for the NHS to embrace AI and what benefits can they expect to see, particularly in the field of medical imaging?
If the recent strike action, news of staff shortages and reports of stretched budgets have highlighted anything, it’s that there needs to be a radical intervention to maintain healthcare standards in the UK, and it isn’t going to be a miraculous influx of additional personnel.
There is particular concern in medical imaging, with the Royal College of Radiologists declaring in its most recent census that the UK now has a 29% shortfall in clinical radiologists, which will rise to 40% in five years without action. This will inevitably impact the quality of care for patients, with only 24% of clinical directors believing they have sufficient radiologists to deliver safe and effective care.
The workforce crisis has an inevitable impact on already stretched budgets, with 99% of imaging departments unable to manage reporting demand. It is estimated that across the UK last year, health systems spent £223 million on managing excess reporting, equivalent to 2,309 full-time consultant positions.
Last winter, the NHS faced one of the toughest periods in its history with most hospitals full to bursting, ED throughput stalling, ambulances stacking up outside hospitals waiting to offload patients and, in December 2022, waits of over 1.5 hours on average for category 2 calls for conditions such as strokes and heart attacks. For every 67 patients who wait between 8-12 hours in ED, one will come to avoidable harm. A report by the Royal College of Emergency Medicine has found that this equates to at least 4,519 patients dying in England in 2020-2021 as a result of this overcrowding.
The answer to the healthcare challenges will be complex, but there is a bright light at the end of the tunnel. The infusion of £21 million from the UK government serves as a resounding vote of confidence in AI’s potential, signalling an era where cutting-edge technology becomes an integral part of healthcare delivery.
Amongst others, imaging departments stand to benefit immensely from AI assistance. AI can analyse medical images, automatically prioritising urgent cases and flagging suspected positive findings. Not only does this facilitate early disease detection by clinicians, but it also expedites diagnosis, allowing for timely intervention and ultimately better and more efficient patient care in a challenging environment. There is already an undeniable positive impact, with recent studies demonstrating how AI decreased screen reading workload by 44% in breast cancer and reduced wait time and turnaround time for incidental pulmonary embolism (iPE) patients, saving over 800 days of unnecessary diagnosis delays per year. Through advanced integrations with multiple healthcare IT systems, such as Electronic Patient Records, AI can also play a role in ensuring patients don’t fall through the cracks and get their recommended follow-ups.
These benefits can only be realised when solutions are seamlessly integrated into the workflow and challenges around AI adoption at scale are overcome given the limited resources of IT departments and lengthy information governance (IG) processes. Consideration must also be given to the long-term orchestration of these solutions and monitoring them for phenomena such as ‘AI drift’, which can result in decreased accuracy over time, if not properly accounted for.
In conclusion, the NHS stands on the brink of a transformative journey, powered by the integration of AI technologies. The convergence of technological advancements, the start of governmental support, and the pressing need for innovative solutions positions AI as a formidable ally in navigating the NHS through the current storm. By embracing AI in medical imaging, the NHS has the potential to amplify its diagnostic accuracy, expedite patient care, and pave the way for a more resilient and efficient healthcare system.
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