24-25 - DIGITAL NHS: Smart asks

With its famous adage of free healthcare from cradle to grave, the NHS was once hailed as “a great and novel undertaking” by its pioneering architects.

Fast-forward to the present day, and a tsunami of crippling staff shortages has eroded this noble vision – not to mention stories of widespread burnout, funding shortfalls and mismanaged tech.

Last month, a devastating report from the government’s health and social care select committee shed light on ‘the greatest workforce crisis’ in NHS history, with long waiting lists and overstretched personnel posing ‘a serious threat’ to patient safety. Small wonder that three-quarters of NHS employees are thinking about leaving the service.

While there are no easy answers to impermeable problems such as an ageing population or huge COVID backlogs, the provision of smarter infrastructure could be an anchor in this pressure-cooker climate. Take the issue of HIT (health information technology) systems, many of which are disjointed and cumbersome to manage.

For example, a single sign-on technology project at Alder Hey Hospital in Liverpool reduced HIT login times from 1 minute 45 seconds to 10 seconds. That may not sound like a lot of time to most of us, but an unprecedented rise in HIT-related burnout is adding to what are already exhausting and stressful working conditions.

If similar efficiencies could be introduced across a full range of NHS clinical systems – leveraging developments in biometrics, AI, automation and more – tech could significantly relieve overworked staff. But, crucially, it needs to be rolled out in synchrony with real human needs. Here’s how:

The use of real-time interactive mapping data came into its own during the pandemic. For example, public health bodies used Google’s anonymised community mobility reports to help make critical policy decisions. Similarly real-time data in the UK’s adult social care system was used to shape emergency responses particularly around understanding emerging risks.

Using a technology like blockchain, the NHS now has the option to augment this approach. For example, real-time data on wait time could take the strain off overstretched hospitals – perhaps directing patients to less crowded health centres nearby. Real-time information could make a huge difference internally throughout the NHS, especially in clinical trials and medical supply chains.

It could help oil the wheels of automation efforts, too. In a case study presented in Outpatients, a three-week deployment to automate patient cancellations freed up 13,000 appointments and saved £2.1m. With the ability to impact nearly 36% of healthcare processes, automated projects like these are front and centre in the battle to free up highly skilled individuals – allowing them to focus on care priorities rather than time-consuming admin. And they all rely on robust real-time data.

Singapore’s ‘Digital Health Passport’ scheme, launched during COVID, allowed citizens to access personal medical documents in a secure digital wallet – with blockchain technology providing a security wrapper, enabling easy access and verification.

A similar model could help the NHS streamline healthcare professionals’ workflow with a decentralised, transparent and incorruptible data log. With this structure in place, staff across the NHS’s disparate local and national systems could share information such as test results quickly and safely. Blockchain’s complex codes are also an effective solution for protecting the sensitivity of medical data amid growing concerns around patient confidentiality.

The impact of smart devices in healthcare is excellent on an individual level, but it also carries enormous implications for preventive medicine and medicinal effectiveness. For example, in America, Adherium’s Smart Inhaler has increased adherence to preventive medication by 180% in children and 59% in adults – which, in turn, is easing the pressure brought about by asthma-related A&E visits and hospitalisations.

Meanwhile, we have the emergence of smart insulin patches to measure the glucose levels of diabetic patients, delivering the appropriate dose, and smart knee implants that monitor a patient’s postoperative gait metrics to track their recovery more accurately.

These innovations hold significant knock-on benefits in their ability to give more accurate medication dosage and effectiveness measures (both measures are currently based on averages from lengthy and expensive clinical trials). But, equally, they could also be used to catch infections early and improve the lifespan of transplants, especially if smart tech is expanded to hips and shoulders.

With large healthcare organisations routinely juggling information between 800 and 1,000 applications across various disparate IT systems, it’s clear that the NHS could benefit from simpler, more accessible infrastructure. And while some of the technology solutions discussed so far – for example, blockchain-enabled wallets – could help, they’re also costly to install and require specialist personnel.

Low-code platforms offer a third way in this picture, with fast, cost-effective and integrated solutions that can bridge the gap between technologists and the issues on the ground that they are aiming to solve. With 65% of application development activity predicted to be low-code by 2024, this is an avenue that offers huge potential for innovation and improvement in healthcare provision, e.g. in the capacity to analyse cross-department performance.

Another advantage of low-code platforms is that they allow those without a traditional coding background (e.g. doctors and nurses) to work in unison with designers, creating an iterative tool that directly addresses day-to-day problems. A good example is the Christie NHS Foundation Trust, Europe’s largest single-site cancer centre, which recently partnered with a low-code development platform to unify its cancer data into one patient-centric record in support of better direct care.

While disorganised data is a roadblock, NLP – via its sophisticated understanding of human speech and meaning – could extract and manage valuable information from NHS data archives in a way that helps to drive speedy and intelligent decision-making. Front-end speech recognition could also ease the frustration of administrative tasks that everyday healthcare workers face, whilst back-end technology can detect and correct any errors in transcriptions before passing it on for human proofing.

NLP can also aid doctors by providing decision support at the point of need: for example, by analysing a patient’s background to help early diagnosis or to predict post-surgical complications.

In its current and chaotic state, the NHS is teetering on a precipice. Hospital doctors, nurses and other frontline staff report feeling “totally unvalued and taken advantage of”, with family GPs also grappling with demand in a system brought to its knees.

Tech is no silver bullet for this complex situation. But – used in the right way – it could drive powerful efficiencies, with a domino effect that cuts to the crux of the issues causing staff burnout and disengagement.

With universal, intuitive data access, the best kind of tech will target the crossover between organisational and human needs that embody most major NHS challenges. This, in turn, can bring direct, rapid and lasting change to the areas that require it most.