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Time to create the dream: AI in the NHS



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Daniel Pitchford, Co-founder of  AI Business, urges the NHS to stop stalling and get to grips with AI if there’s any chance of us hitting the targets set for 2030  

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Earlier this year, a US study found that when diagnosing lung cancer, AI was more accurate than specialist pulmonologists. This announcement is one of many that demonstrates the potential AI has – and will continue to have – in healthcare sectors around the world.

In the UK, the NHS is just waking up to the benefits of the technology. There are concerns that data processing systems and AI algorithms will take away jobs from staff and doctors. A recent report examining AI implementation within the NHS found that people are worried about the type of data this technology will use. As patients and the public remain suspicious, the rollout of technologically advanced features has slowed.

The NHS has a responsibility to promote and effectively communicate how this technology could improve and save patients’ lives. AI implementation will mean shorter wait times, a better understanding of illnesses and speedier diagnoses which will allow the NHS to become the future-facing healthcare system. Understanding the impact AI is already having within the NHS, as well as the factors that are slowing down its implementation, and where the technology is heading, is vital in order to keep up with global developments in digital health.

Medtech for all? How AI is already being used in the NHS

The NHS’s ambitions around how AI will be used in the NHS are well publicised – the organisation announced its Long-Term Plan in January this year with a major focus on technology. The government said it wants AI and NHS data to ‘transform the prevention, early diagnosis and treatment of chronic diseases by 2030’. Despite these grand claims, there is currently no centralised plan to roll out the technology.

The health secretary Matt Hancock recently stated that the NHS must adopt new technology in order to survive. Even though there are huge ambitions, there is no pressure on NHS trusts to invest in AI programs or products that can be used to help patients. As there is no clarity or specific targets for each trust to invest in AI technology, uptake with AI in NHS trusts is not on track.

There are a few great examples where the technology is being used, with significant effects. HeartFlow’s AI creates personalised 3D models of patients’ hearts so doctors can see where blockages may be occurring, while the C the Signs’ app, which helps GPs identify patients most at risk of developing cancer, is being piloted in South London. It’s clear there is an appetite to implement AI technology within certain NHS trusts.

There’s a financial incentive too: a recent report by the TaxPayers’ Alliance found that up to one-tenth of the NHS’s budget could be saved by the introduction of automation, as it will increase productivity and more effective uses of its vast database of patient data. The main obstacle is that there is no priority on investing in new technology – and it remains a daunting task.

Another area prime for disruption is communication itself – every day, doctors and nurses waste hours trying to contact each other using out-dated technology such as pagers, landlines and fax machines. As more and more workflow is handled through messaging platforms, the need for a secure, encrypted service which safely stores sensitive data grows.

Forward Health, an exciting healthtech start-up, was set up in 2017 to solve this problem. NHS junior doctors Lydia Yarlott and Barney Gilbert joined forces with technology entrepreneur Philip Mundy to create Forward, a secure messaging app that allows clinical teams to communicate securely and quickly.

Aiming to solve the problems that waste most time, the app incorporates secure messaging and photo capture, a hospital directory of staff, and workflow management tools to collaborate with colleagues on the go. Relatively simple technology, but with revolutionary potential in the world of healthcare; a world where a patient’s route through the hospital is typically tracked by paper, pen and frequent verbal handovers of information.

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The prospect of using AI in the app becomes increasingly exciting, aiding diagnosis from imaging is an expanding area in medicine. Real-time insights into staffing, workflow and pressure points in healthcare systems are another aspect with huge potential, particularly if predictive algorithms can anticipate surges in demand.

Public perception is a stumbling block

The idea that a machine could help in diagnosing someone is a scary and alien concept for the general public. The NHS holds some incredibly sensitive data, and many are concerned and focused on the question of whose hands will this data end up in? Transparency and an understanding of how and where the data is being used are vital if AI’s potential is to be realised within UK healthcare.

In February, the organisation updated its code of conduct in relation to AI, championing data privacy and the importance of security. The Department for Health and Social Care expects technology companies to meet and follow these ten rules accordingly.

The onus shouldn’t just be on the companies developing innovative AI healthtech; the NHS needs to make the public aware of the positives this technology will bring and assuage (understandable) privacy fears. In order for the NHS to achieve its goal of becoming a leader in world-class healthcare, it must understand the right products to invest in and simultaneously work on improving the public’s confidence around how this technology is being used to create positive change.

The opportunity of AI in healthcare

The potential benefits this technology could have on the healthcare system is vast. Every week, there are headlines around companies’ efforts in creating new AI systems that will help the full gamut of health concerns. Recently, The Institute of Cancer Research announced an investment of £75m to develop drugs to combat cancer cells that have become resistant to drugs. AI will be used to predict the moves of cancerous cells – mutating into a stronger, more resistant form of the disease, while also helping in understanding how the cells would respond to new treatments. These drugs will take around a decade to create, but there is no doubt that the technology is offering the possibility of a transformational change the healthcare industry has yet to see or achieve.

A more immediate use of this technology can be found with a recent AI system developed at University College London, which is set to be piloted in the NHS. It will help in flagging up ‘at risk’ patients of major illnesses, with the system hoping to save thousands of lives. With a growing ageing population, pressure within the NHS is only going to increase – it is therefore important that these AI systems are invested in for the NHS to modernise and future-proof itself.

The most obvious and immediate application of AI is its potential to transform the NHS’ vast database – smart systems could help automate the diagnostic and predictive process, relieving pressure from skilled employees and tasks that require a human element. However, without a centralised and organised plan for investment, the NHS will fail to take advantage of the infinite possibilities that AI brings.

There are continuous projects, reports and announcements around how AI can improve the healthcare system. We are yet to see AI’s full impact within healthcare. If the public and healthcare professionals are to understand and benefit from the changes this technology can bring, the NHS must act now – or the 2030 dream will never be met.

Dan Pitchford

About the author

With well over 100 years experience between us, we've been around the editorial and medical blocks a few times. But we're still as keen as any young pup to root out what's new and inspiring.

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