To protect Scotland’s health and social care future, we must take big, bold steps forward right now.
That means strengthening and developing technologies and techniques into our NHS that can prevent or detect disease before it develops, accelerate diagnosis and treatment times, aid clinical decision-making, and supplement an incredible workforce.
There is arguably no greater opportunity than in transformative artificial intelligence (AI) and Scotland’s ecosystem is truly pulsating with potential. From remote monitoring and predictive technologies, to breast cancer screening and wellbeing apps, AI offers opportunities to improve patient experience, while supplementing and extending human expertise, not to mention providing the most effective intervention for reducing waiting lists – a significant post-pandemic challenge.
Medical innovation is in Scotland’s DNA – and there is so much more to come. Back in 1958, Glasgow produced the first practical ultrasound scanners, and in 1980 the world’s first clinical service for MRI launched in Aberdeen. With long-standing collaborative relationships between NHS, industry, and universities, a strong track record of academic-based AI excellence, an NHS recovery plan supporting acceleration of new technologies, not to mention a well joined-up community with the same collective, progressive aims, it is not hyperbole to say that we can build an AI powerhouse here in Scotland, shaped by our vision of trustworthy, ethical and inclusive AI, and ushering in a new era of healthcare innovation.
One key area of consensus as we work to recover from the Covid-19 pandemic is that human resource is no longer sufficient in isolation. If the pandemic can be said to have had any kind of positive legacy, then its acceleration of wider collaborative change in healthcare has been a significant beneficiary. Covid-19 has essentially necessitated the rapid development and adoption of new solutions to improve operational and clinical outcomes.
AI offers an opportunity to radically change health and social care, and whilst the tech is in its infancy, it is also rapidly maturing. Scotland is already realising the potential by developing infrastructure to ensure AI is viable, with a longer-term aim of being properly embedded into clinical practice. Overall, it can make the NHS better at what it does and undoubtedly lies at the heart of key NHS aims going forward, supporting transformation and innovation.
Through the work of the Scottish Health Industry Partnership – an initiative hosted by the Chief Scientist Office and the Enterprise and Innovation Division of Scottish Government – technical, clinical, and commercial expertise comes together to drive an ambitious programme of work aimed at strengthening Scotland’s innovation activities in health and social care. It has led to the planned establishment of an AI hub that will provide a single place where people can access advice, infrastructure for AI development, standards, and investment.
The AI hub has multiple aims including supporting development of a growing, well-funded health and care AI ecosystem for Scotland; supporting alignment between health and care organisations and innovators; offering a national, full-lifecycle health and care AI advisory and support service; and establishing national pathfinder projects using AI to deliver against priorities.
Of course, for AI to be truly inclusive and benefit everyone, trust in the technology must be secured and its role in society crystallised.
It is important that we invest in the whole innovation lifecycle, including research and development, skills development, business growth and support, and robust evaluation within the clinical environment. It is not enough for technology to be interesting – it must be viable, safe, and properly embedded into clinical practice. Driving this work forward and supporting investment in Scotland’s rich AI innovation ecosystem will generate national economic prosperity and improve the health and wellbeing of the nation.
But it’s not just a future vision. In early diagnostic heart failure, a study by NHS Greater Glasgow and Clyde, University of Glasgow, and industry partners has seen the potential for treatment waiting times to be reduced from one year to two weeks by introducing digital and AI techniques.
In breast cancer screening, a study by NHS Grampian and The Industrial Centre for Artificial Intelligence Research in Digital Diagnostics, used AI to detect cancer in 80,000 mammograms to prove AI can successfully be deployed as a ‘second pair of eyes.’ This could help address recruitment challenges in radiology, accelerate the turnaround time for results, and enable clinicians to spend more time with patients.
AI software is being trialled at hospital sites across the north of Scotland to help faster decision-making in lung cancer. The AI technology can scan X-rays for more than 100 potential issues, flagging things so small they could be missed by the human and acting as an automatic triage system.
In North Lanarkshire, a pilot project using AI to help clinicians more rapidly identify abnormal cells in digital images of human tissue, increased service capacity by around 25 per cent. AI holds great promise in accelerating the detection of disease within digital pathology.
The detection of very early cancers is impressive, but AI is also proving effective in identifying changes to some cancers’ DNA and where exactly in the body they are developing. Known as the Galleri test, it is thought to be capable of picking up signs of more than 50 types of cancer. The technology is being piloted in NHS England with the next stages of the study being considered for Scotland.
Whilst we can’t stop people getting cancer, if we can use AI to pick it up earlier, it offers more options, more hope, and better survival than it presenting later at a more advanced stage. It can help the NHS prioritise and focus timely patient care on those with the greatest need.
We know a large amount of clinician time is spent on tests where no cancer is detected. AI excels at this type of task, doesn’t experience fatigue like humans do amid mass screening, and bases its analysis on rigorous, comprehensive data and pattern recognition.
As a result, more effort can be focused on the positive cases, and clinicians can process more of them, including cancers that are rare or difficult to diagnose. Ultimately, patients benefit through faster diagnosis and treatment and the NHS benefits through greater efficiency.
AI undoubtedly lies at the heart of key NHS aims going forward – including encouraging new ways of working as part of a wider innovation ecosystem. Fundamentally, Scotland is well positioned to support that AI evolution, ultimately improving patient experience, outcomes and of course saving lives.
James Blackwood is Artificial Intelligence (AI) lead at the Scottish Health and Industry Partnership (SHIL)
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