From Analogue to Digital and Beyond - From Analogue to Digital and Beyond - The Potential Impact of AI on the UK’s Healthcare Services

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From Analogue to Digital and Beyond

The Potential Impact of AI on the UK’s Healthcare Services

With several ‘big shifts’ for the NHS proposed by the UK Healthcare Secretary, how can AI and automation help transform the delivery of healthcare services and optimise patient outcomes across the UK?Contents

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From Analogue to Digital and Beyond

From Analogue to Digital and Beyond

The Potential Impact of AI on the UK’s Healthcare Services

On the morning of 12^th September 2024, the UK Health Secretary, Wes Streeting, pinpointed three 'big shifts' that would be required to transform the NHS:

From hospital to community care
From analogue to digital
From treating sickness to preventing it

While the transition to community care lies outside the scope of this piece, there is much to consider around the second two shifts, and a wide range of opportunities to optimise patient care that, in certain cases, are already in motion...

While the transition to community care lies outside the scope of this piece, there is much to consider around the second two shifts, and a wide range of opportunities to optimise patient care that, in certain cases, are already in motion...

As regular readers of this blog will know, the digital transformation of UK healthcare has been very much an ongoing journey for some time now. While there's no doubt that there have been considerable strides made in recent years, there is still much work to be done, as Lord Darzi's report shows. Let's consider a few key statistics:

19% of healthcare professionals are expected to retire within the next five years.
There are more staff over 55 in specialist fields like neuropathology (45%) and histopathology (29%), but fewer up-and-coming professionals are focusing on these areas, with vacancy rates for histopathology consultants alone currently standing at 10%.
The NHS has set a target of 85% of patients receiving a diagnosis and beginning treatment within two months of an urgent referral. At the time of writing, this stands at 62.8%.

What do you believe is the most significant barrier to achieving the NHS's target of 85% of patients receiving a diagnosis and beginning treatment within two months of an urgent referral?

Shortage of specialist healthcare professionals
Inefficient analogue processes
Lack of funding for digital technologies
Resistance to change within the healthcare sector

If we are to achieve an optimal time-to-diagnosis for as many patients as possible, then we need to enable healthcare professionals to work more efficiently and effectively, but with a shrinking number of specialists, we are experiencing an increasingly tight bottleneck in this regard. However, I would argue that if we approach the shift from analogue to digital in the right way, we will be well-placed to not only meet the NHS's targets around time-to-diagnosis, but also begin driving the third 'big shift' and change our focus from treatment to prevention, wherever possible.

As I have argued before, AI has a key role to play here, allowing for the strategic automation of pathology processes and thus enabling high-speed, highly accurate analysis that would not be possible with human eyes alone, recognising specific biomarkers within the highest volumes of data - more specifically, digitalised slides from across multiple healthcare sites.

Let me be clear, these technologies are not intended to replace the experience and expertise of a specialist consultant, and they never will be. As with any digital transformation initiative within healthcare, the focus should always remain on the patients, and so the final diagnosis will always be the pathologist's responsibility.

However, freeing our pathologists of the need to manually analyse the rapidly growing volumes of healthcare data generated each day in order to arrive at their final diagnosis will prove transformative for patient care, enabling accurate diagnoses to be delivered at speeds that would previously have been impossible.

This, in turn, will support the cutting-edge research that will eventually allow for a preventative approach to treating the most complex conditions.

We're already seeing this new breed of digital pathology in action within the NHS, but establishing the technology and processes across the wider UK healthcare sector will require ongoing collaboration between the NHS and its technology partners. This means not only training the algorithms, but also ensuring the platforms support the sector's well-honed workflows and that the integrity of patient data will be maintained at all times.

There's no doubt the journey will be a long one, but based on the successes of current digital pathology initiatives and the conversations myself and my colleagues are having with healthcare professionals across the country, I am confident that we have already taken the first steps.

So, don't hesitate to contact us if you'd like to explore any of this, or any other aspect of how digital transformation can support better patient outcomes, in greater depth!

Which area of digital pathology do you believe will benefit the most from AI advancements in the next 5 years?

Cancer diagnosis and prognosis
Infectious disease diagnosis
Drug discovery and development
Personalised medicine
Other