Improving NHS productivity through digital technology

“Productivity isn’t everything, but in the long run it is almost everything.” Nobel prize-winning economist Paul Krugman’s comment in his 1990 book The Age of Diminished Expectations is still significant today, especially in the UK.

 

Poor productivity in the UK’s public sector is having a major damaging effect on growth. Public sector productivity rose between 2010 and 2019, having stagnated and declined slightly during the previous 15 years. Unsurprisingly though, it fell massively during the Covid crisis.

 

However, a year since the UN declared an end to the emergency, public sector productivity in the UK is still languishing at 85 per cent of the pre-pandemic figure, with the UK government struggling to get civil servants back to full office-based productivity. The National Health Service (NHS) is no exception to this drop in productivity. And, as public health is by far the largest area of public spending in the UK, this is a matter for concern.

 

There are of course many reasons for low productivity in the NHS. There is a major skills shortage, although there were fewer vacancies for doctors and nurses in Q3 of 2023/24 than there were in Q3 of 2017/18. Management is weak, with a preference for blame rather than learning from mistakes, a culture that promotes reputation over patient benefits, and an over-reliance on commercial management practices. There are undoubtedly problems with infrastructure too: buildings are badly maintained, and IT systems operate in silos – when they are not being hacked, that is.

 

Technology cannot solve all these problems. But the wise use of appropriate digital technology will have a significant impact on efficiency, leading in turn to greater patient satisfaction.

 

Funding constraints

 

Many people argue that the fundamental problem with the NHS is a lack of money: limited financial resources affect the quality and availability of healthcare services. While a growing and aging population mean that there is certainly a case for additional funding, budgets will always be tightly controlled.

 

Extra money need not be the only solution to limited budgets. Technology can help by ensuring the efficient allocation of resources. AI and data analytics can be implemented to ensure funds are used effectively and that areas – geographical and medical – with the greatest need receive appropriate support.

 

Staff shortages

 

There are over 100,000 vacancies in the NHS. Insufficient numbers of healthcare professionals lead to overworked staff and compromised patient care. According to the Kings Fund, the reasons for this shortage include difficulties in workforce forecasting, the insufficiently strategic use of international recruitment and a tendency to train too few staff.

 

Technology has a role to play here, even though it cannot overcome the political and professional constraints on training. AI can be used to forecast where and what type of human resources are needed. And automated processes supported by AI can be used to streamline international, as well as local, recruitment.

 

In addition, technology used to increase NHS operational efficiency will reduce the need for extra staff in some areas. This is perhaps where the most exciting opportunities lie. Few people expect AI systems to replace doctors.

 

But they can undoubtedly make doctors more efficient (so that fewer will be needed), for example by enabling scarce medical specialists to work remotely, including during remote operating theatre procedures, meaning their skills can be used outside their physical location. In addition, professionals, including international teams of healthcare professionals, can be given access to the most relevant information in real time, including translations where necessary.

 

One area that is often mentioned is the use of AI to automate the analysis of scans, leaving doctors to examine only those identified as high risk. For instance, one study showed that a single radiologist working with AI detected 20 per cent more cancers among mammograms than two radiologists working without the technology. It should be said that using doctors in this way is not because they are better than AI at spotting anomalies. Rather they act as a sense check, enabling AI systems to constantly improve. In addition, rightly or wrongly, they increase patient confidence in diagnoses.

 

Administrative problems

 

AI is already being used to improve operational efficiencies in NHS back-office roles. Machine-learning tools rapidly analyse complex information, find patterns and suggest optimal solutions to human decision makers. As well as optimising management and planning, such tools can improve scheduling. Patients often face long waits for consultations, diagnostic tests and treatments, waits that affect both health outcomes and satisfaction. AI can streamline patient pathways, reducing bottlenecks and inefficiencies, and maximising the number of patients that can be seen in any one period.

 

Routine hospital management can also be improved. In one NHS hospital, the maintenance and cleaning teams have their duties prioritised by an AI tool. This tool uses indoor location sensors to track staff and assign urgent tasks to individuals or teams based on their location. In a similar way, AI can help with bed blocking by facilitating real-time medical decision-making, automating routine but important administration prior to patient discharge, and extending care co-ordination to home settings.

 

One major administrative problem that the NHS must deal with is the number of patients who do not attend scheduled appointments. This clearly wastes scarce healthcare professional time. AI software has been trialled that predicts likely missed appointments, identifying whether someone may not attend an appointment using a range of external insights, including the weather and traffic. Back-up bookings that are more convenient (for example at weekends for people in nine-to-five jobs) can then be offered, while a degree of over-booking also becomes possible. This system led to a 30 per cent fall in non-attendances when trialled at the Mid and South Essex NHS Foundation Trust, and enabled an additional 1,910 patients to be seen over the six-month trial.

 

Poor practice

 

“It is estimated that 5 per cent of the 8.5 million patients admitted to hospitals in England and Wales each year experience preventable adverse events, leading to an additional three million bed days,” said Hemant Patel, Past-president of the Royal Pharmaceutical Society of Great Britain, in evidence submitted to parliament. “More than one million hospital admittances each year in the UK are because of medical errors, incompetence or the side-effects of treatment. Much of the damage is caused by careless or inappropriate prescribing, or overprescribing. This means the clinicians rate alongside cancer and heart disease as a major cause of serious illness and death.”

 

Healthcare workers are not infallible of course. Mistakes are made in hospitals for a number of reasons, including tiredness, stress, poor access to data and even poor training. Ensuring high standards of patient safety will always be challenging amid resource constraints and high demand.

 

However, technology can be used to ensure that standardised protocols and best practices are followed. Procedural anomalies can be called out by a combination of sensors and AI. Additional information can be delivered to healthcare professionals during patient interactions through augmented reality and “smart glasses”. Using digital tools in this way can reduce the large amount of iatrogenic harm experienced in the NHS.

 

Training can also be enhanced using technology. AI can be used to deliver tailored training plans for individual professionals based on their current role and past experience. Virtual reality can be used to overcome training bottlenecks or to give professionals the opportunity to practice complex procedures on a virtual dummy rather than a real patient.

 

A multifaceted approach

 

Addressing the challenge of poor productivity in the NHS requires a multifaceted approach that combines increased funding, workforce development and process improvements. Technology can play a central part here, helping the NHS enhance its efficiency, improve patient outcomes and ensure sustainable healthcare delivery.

 

Thankfully, the organisation is well aware of the opportunities that technology offers, as the activities of the NHS AI lab indicate. The responsible and human-centred application of AI within the UK’s healthcare sector is set to transform outcomes for patients across the country over the medium term.