DIAGNOSTICS
Diagnostics and AI vital to NHS recovery
Early and targeted diagnosis will be crucial as the UK recovers from the pandemic. Geoff Twist argues that diagnostics, along with artificial intelligence, could have a key role in helping to ease the NHS backlog.
The diagnostic testing which has been so critical during the pandemic can and should play a similarly significant role in the next set of challenges now facing the NHS. Although we are moving beyond lockdown, the pandemic is far from over, and the next phase of our response will need to be mindful and measured so that, as restrictions ease, the NHS can move into a period of sustained recovery. We know there are backlogs to address, most notably in cancer and cardiac services, and that these pressures exacerbate challenges the NHS was facing well before the pandemic struck. For example, only around a third of doctors who have successfully completed the foundation training programme now choose to go straight into specialty training1
and, of
particular concern, the rate at which training posts were filled in England dropped to 72% in histopathology, from almost 100% in the previous two years.2
At the same time,
demand for pathology services in the NHS continues to escalate year on year, a trend that is matched by the increasing complexity of the workload faced by pathologists. These existing problems are now compounded by the fallout from the COVID-19 pandemic. There has been a significant impact on cancer screening programmes, some of which were paused for a period of time in 2020, as well as long waiting times for further diagnostic tests and treatment. Around three million fewer people were screened between March and September 2020, and nearly 44,000 fewer patients started treatment for cancer between April 2020 and January 2021, compared to the same time period in the previous year, according to analysis by Cancer Research UK.3 There is a clear impact across the whole patient pathway: fewer patients being diagnosed, or being diagnosed later, means a delay in accessing appropriate treatment, which can have a disastrous impact on outcomes. Diagnostics have always played
a crucial role, but the benefits of early and targeted diagnosis will be even more crucial as the UK recovers from this pandemic and there is a clear need to work together to tackle the backlog of patients with significant or long-term health conditions. Our current situation is a case of unintended consequences. In focusing attention and effort on this vicious virus – which has been entirely necessary in order to safeguard the NHS and prevent it from being overwhelmed – the NHS now has another mountain to climb in order to return to normal service. Over the next few months, alongside the continued rollout of the vaccine, the role of diagnostic testing will enter a new, important phase as one of the cornerstones of the NHS recovery. COVID-19 testing will continue to play an ongoing role for the foreseeable future but there is a need for integration here, to make sure we are also diagnosing and expediting the right treatment decisions for other diseases. The Government Integration and Innovation White Paper sets out how closer working between primary care, secondary care and tertiary care can help NHS
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efficiency. Industry can help enable this greater interconnection across the patient pathway by providing solutions to support healthcare professionals at each stage. Quick and efficient diagnostic testing can help get patients into treatment more quickly, and it can also help to prevent or unblock bottlenecks and relieve pressure on acute NHS services.
Tackling the cancer backlog Efficiency and agility are key in building capacity and enabling the NHS to tackle the backlog of cancer patients which has built up during the pandemic. In this instance, the application of digital pathology and artificial intelligence (AI) has exciting potential. The traditional approach to cancer diagnosis involves pathologists examining tissue samples under a microscope. Digital pathology takes this a step further by making it possible to scan and create digital images of tissue samples, enabling quick and efficient analysis on a computer screen, and the ability to share among experts more easily. The application of AI to the highly complex visual information within
AUGUST 2021
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