AI have a dream

10 ways AI is transforming healthcare across the NHS

Sometimes we seem to talk of little else at the ‘innovation’ end of healthcare.

For some years now, AI has been seen as the biggest lever the NHS can pull to address its biggest challenges: demand; diagnosis backlogs; getting to the patients most in need fastest; and allowing them access, better communication, and even enhanced outcomes.

My recent articles for this publication have looked at the ‘three shifts’ proposed by Health Secretary Wes Streeting. We’ve had treatment to prevention. There’s hospital to community. And the third one is analogue to digital. And when there’s a digital element being discussed as transformative in the NHS – the chances are it’ll be an AI tool.

AI is rapidly reshaping the landscape of healthcare within the NHS. From diagnostics to administrative efficiency, AI tech is being placed front and centre.

But surveying it all can be overwhelming. So many projects and types of process now have an AI element, it’s difficult to have a comprehensive overview of all the major trends.

At my company HSJ Information, we have a unique window on the NHS cutting edge when it comes to AI. Our digital summit brings together the principal CTOs and digital leaders.

Our Advisory team helps both tech companies themselves and Pharma gain market access through building AI tech into their value proposition. And our digital awards showcase some of the most groundbreaking AI out there.

In this article we’ll explore ten pivotal ways AI is currently being used across the NHS.

Faster, more accurate cancer detection provided by AI could have a huge impact on demand and outcomes.

For example, the NHS is trialling the miONCO-Dx blood test, developed by the University of Southampton and start-up Xgenera, which uses AI to detect 12 common cancers from a small blood sample. Early trials involving 20,000 patients indicated 99% accuracy, potentially reducing reliance on invasive procedures like colonoscopies.

AI technology is being rolled out to all radiography departments in England, backed by £15.5 million in government funding.

This AI can locate cancer cells 2.5 times quicker than doctors alone, helping to reduce cancer waiting times by assisting doctors in distinguishing between cancerous cells and healthy organs during radiation treatment.

NICE has now approved the use of robotic surgery systems for 11 types of operations across NHS specialist centres in England. These systems enhance surgical precision, reduce recovery times and can alleviate the burden on overextended surgical teams.

AI software is being integrated into the National Optimal Stroke Imaging Pathway (NOSIP) to support rapid interpretation of CT and MRI scans.

This technology reduces decision-making time for treatments like thrombolysis and thrombectomy, increasing the number of patients eligible for these interventions and improving outcomes.

AI tools are aiding in the early detection of heart diseases. For instance, smart stethoscopes using AI have demonstrated 90% accuracy in identifying heart failure, allowing for earlier diagnosis and treatment.

Additionally, AI algorithms can assess whether patients in A&E have experienced a heart attack, improving triage and care.

AI-enabled remote patient monitoring (RPM) systems are transforming healthcare by allowing doctors to monitor patients with chronic or acute illnesses remotely.

These systems use wearable devices and sensors to collect data, which AI algorithms analyse to detect early signs of deterioration, personalise monitoring and learn patient behaviour patterns.

Not something the NHS necessarily planned, but something it will have to deal with, is the phenomenon of AI in counselling.

With long NHS mental health treatment waiting lists, many young people in the UK are turning to AI tools like ChatGPT for emotional support. These AI chatbots offer instant availability, providing a non-judgmental space for users to articulate thoughts and manage feelings of anxiety and overwhelm.

It’s likely programmes such as these will be rolled out via the NHS app as smartphones become a key mental health pathway entrance point.

AI algorithms are being used to predict patient health risks. For example, Cera Care’s AI products can forecast more than 80% of health risks in advance, reducing hospitalisations by up to 70%. Its Falls Prevention AI predicts 83% of falls in advance, reducing patient falls by 20%.

AI is streamlining administrative processes within the NHS. For instance, AI can capture doctor-patient dialogues and translate them into structured patient records.

Additionally, AI platforms can predict which appointments may be missed and suggest optimal time slots, reducing missed appointments by 30% in pilot programmes.

The NHS Long Term Plan sees AI as a key element in digital transformation. In general practice, AI can automate service efficiency through voice recognition software that transcribes consultations, freeing up staff time. It also supports diagnostic decision-making by applying guidelines to consultation data, suggesting diagnoses or management plans.

The integration of AI into the NHS is revolutionising patient care by enhancing diagnostic accuracy, improving treatment outcomes, and streamlining admin. As these technologies continue to evolve, they hold the promise of a more efficient and responsive healthcare system.

More and more clients are coming to HSJ Information wanting to build AI tools and processes into their value proposition. How does it align with yours?

Oli Hudson is content director at HSJ Information.
Go to hsjmarketintelligence.co.uk