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Prioritising where technology can realistically help the NHS

By Iain O’Neil, Managing Partner, Healthcare, TPXimpact



While the entire UK public sector is facing unprecedented funding challenges, most would agree that the NHS is facing the most pressure.

From the ongoing recovery from the impact of the COVID-19 pandemic, the current crisis in emergency medicine, the return of flu season and the resurgence of Covid, to staff shortages and strike action over pay, the latest health secretary Steve Barclay faces a large number of challenges.

The government argues that money is being invested and additional funding won’t be forthcoming to relieve this pressure – so what can technology do to help the NHS get itself out from the current crisis

It’s easy to forget when the headlines describe a backlog of circa five million referrals for treatment waiting to be actioned that these are real people with real problems, concerns and dependants.

The NHS is rightly making tackling the backlog its top priority.

Waiting list management, triage, sharing the correct patient information at the right time, booking the right people and equipment into the right location – these are all things technology has proven itself to be effective at supporting and that the NHS can use to relieve some of the current pressures it is facing.

Electronic patient records

Currently the NHS is undertaking a massive transformation programme, funded partly from the national budget in the NHS England Transformation Directorate (ex-NHSx) and partly match-funded locally, to roll out or extend the use of electronic patient records.

It is hard to argue with increasing the use of electronic patient records, most people agree – and what evidence there is, seems to show – the quality of care that you get from a hospital that has digitally transformed with easily accessible data can be noticeably different from a paper based hospital.

However, the critical elements of the above are ‘digitally transformed’ and ‘access to data’ – it is possible to implement an electronic patient record in a way where information is still siloed and staff working practices are made more burdensome.

While electronic patient records can improve efficiency, digitisation isn’t a ‘cure all.’

EPR systems in acute trusts will help most as part of an integrated system and it is important this large amount of public money going to a relatively small number of EPR suppliers is used as an opportunity to move that market to a more open, standardised data-sharing model.

One of the big challenges facing the NHS is its connectivity to social care – with a recent article stating the NHS is considering buying care beds in order to make it easier to move patients out of hospitals.

It could use the EPR programme to connect better to social care and to help ease that problem.

Understanding through data

The other sizeable procurement in the NHS technology landscape is the Federated Data Platform.

The NHS is constantly collecting data about patients but wants to be able to use that data in a more strategic way, to enable a better understanding of care needs and to share information better around the system – as well as giving ‘the centre’ the view it needs.

From a diabetic patient attending a routine check up, to a parent rushing to A&E in the early hours of the morning, every hospital visit provides valuable information that tells an important story of their health over time and indicates what further care may be required.

However, despite information being captured at each interaction between a patient and a healthcare provider, too often this information isn’t joined up.

This means specialists have to often request information from patients that they have already provided or some details may not be recovered.

The Federated Data Platform and move to EPRs will – it is hoped – help solve this.

The NHS should be encouraged to continue their work joining up datasets and unlocking the benefits of the data it already possesses as this will create the most value without prohibitive costs.

This can then enable better collaboration across the entire healthcare system, as well as social care systems, and increase their effectiveness by making it easier for patients to receive the most accurate diagnosis and effective onward care.

While the government has taken some steps towards making this possible, through the local health and care record exemplar programme for example, and the move to empower Integrated Care Boards, there is still room for these efforts to go further and faster.

The right mindset for Artificial Intelligence

If we are able to get the fundamentals of data sharing right, if we are able to win the conversation with the public that data sharing is good, then we could move into a very interesting future where technology really could help keep the NHS financially sustainable and we could make another giant leap in the quality of care.

AI has the potential to make a significant difference in health and care by providing patients with more effective care, earlier intervention, faster and potentially cheaper by reducing the flow of patients needing expensive treatment by acting sooner with mitigation.

There are already some great examples of impactful AI in clinical care, as well as examples of AI in health logistics.

Perhaps one of the most interesting use cases of AI in healthcare is in the diagnosis and treatment of specific diseases like Alzheimer’s, or enabling more accurate methods of rapidly detecting cancer earlier.

                               Iain O’Neil

A study by the American Cancer Society shows that a high proportion of mammograms yield false results, leading to 1 in 2 healthy women being wrongly diagnosed with cancer.

The study suggests that through the use of AI, there is now a better level of review and translation of mammograms at a rate that is 30 times faster, and with 99 per cent accuracy, reducing the need for a reliance on unnecessary biopsies.

The use of artificial intelligence in healthcare has potential to assist healthcare providers with certain processes and increase the overall efficiency of the NHS.

However, AI models are currently good at doing one specific thing very well and we are some way away from the technology being used in a general fashion across different services and departments.

It’s also important to note that for staff to work alongside AI effectively they may need significant training and support, something which requires further investment in time and resources.

While we have seen some positive development in the future of healthcare through the increased use of electronic patient records, machine learning, and data driven outcomes, it is unlikely that these technologies will be able to solve all of the challenges the NHS is facing simultaneously.

In the middle of a funding crisis, we also must make the most of the tools and data available to us today.

Technology works best when it enables professionals to do what they do more effectively, which in turn can deliver better outcomes for the people who rely on their services the most.

So it is imperative that the NHS takes a ‘user first, technology second’ approach and targets its investment to ensure maximum return – otherwise there is every danger the current crisis becomes the new normal.

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