Tech and AI will play a vital part in making the NHS fit for future generations to come, and that’s why it has been positive to see more invested into automation and digital transformation across the NHS.
If we reflect on the past few years, we’ve seen increased commitment from the government to invest a share of its £32m AI funding in the NHS. But most encouraging of all is the shift in public sentiment around the technology – with most people (according to data from the health foundation) being willing to share health data to develop AI in the NHS, providing the human touch is not lost.
Like with anything, change can be scary, and it can take time to adopt. If we think back to the early days of telehealth, it was initially met with a lot of scepticism around the quality of care and the effectiveness of remote consultations, but now we’ve identified the best use cases for it, it has become a critical component of healthcare delivery. The same will inevitably happen with AI. It’ll become increasingly adopted across the NHS. But it’ll still be important to maintain those important touch-points in person with healthcare teams.
We’re already seeing this happen. AI is being used in the NHS to support staff in areas such as clinical decision making, analysing test results and in scheduling and managing the appointment process. According to the Health Foundation, 76% of NHS staff cited that they support the use of AI to help with patient care, with 81% also in favour of its use for administrative tasks.
However, if we’re to see the continued roll out of AI across NHS trusts, quickly, we need to be realistic about the use cases – and consider and evidence how AI products work in practice.
Some of the biggest benefits we’re seeing at the moment are from applying AI to improve operational efficiencies and to help make healthcare teams workflows more effective. This helps to build familiarity and trust around embedding AI in health care team’s workflows and lays the foundation for expanding to more complex and higher risk clinical use cases later down the line.
As the investment in AI continues, how can we be smart about where it’s applied to truly transform operational efficiencies for the NHS in 2025?
Automating NHS workflows with AI
One of the biggest challenges the NHS is facing is keeping its processes as efficient as possible in the face of a workforce shortage, reduced resources and waitlists which have been teetering close to 8 million since the pandemic.
AI cannot immediately solve these issues, but it can be a game-changer in how we work effectively.
The best AI solutions start with real problems that AI is the most effective to solve and leverage other technology too. The biggest impact for a hospital might not always be in groundbreaking diagnostic solutions, but in reducing repetitive and low value tasks that are stunting healthcare teams’ workflows.
For example, by using our AI model to predict people unlikely to attend appointments, we implement a simple automated workflow to send a series of automated reminders to the patients identified. This simple solution helped to save five staff over 18 hours of time a week – time that they were able to put back into patient care.
When we improve operational efficiencies across a Trust or specialty, this saves time, money and makes team outputs much more effective. We then have the buy in and trust to keep experimenting with AI and driving more impact.
We can improve care just by reducing missed appointments.
One area where we urgently need to move from analogue to digital is in dealing with missed hospital appointments. In 2021-2022, nearly 7.5 million outpatient appointments were missed – this is nearly equivalent to today’s 7.6 million person waitlist.
This means that millions of patients are missing out on potentially critical care.
This is one of the NHS’s most expensive problems – costing the NHS £960 million per year. And yet, out of 5,003 UK adults surveyed who have missed at least one NHS hospital appointment in the last two years, nearly half (46%) are likely to go on to miss more. These patients are marked as “Did Not Attend”, or DNAs.
This points to a systematic problem. A third (33%) of DNA patients do not make it from the point of referral to their first hospital appointment, in spite of 93% admitting they did want to attend their appointment. The reasons for missing varied – 42% of respondents chalked it up to pre-appointment anxiety. Exactly half of respondents said they had faced travel-related challenges, where their referral was located too far away or they couldn’t afford the transportation fair. Workplace commitments and the fear of a loss of income were also cited by 27% of respondents as to why they couldn’t.
Why is this significant? Because had these patients been able to reschedule their appointment to a time that worked for them, they wouldn’t have to miss out on the care.
And if patients are able to reschedule or cancel, their appointment slots could be filled by one of the millions of other deserving patients waiting on the list for their appointment slot.
AI can help here. AI can help tailor solution to meet the patient’s own individual drivers of DNAs. With long wait times and paper notifications, it’s often easy to forget an appointment. Automated notifications can help patients remember their hospital commitments in advance. And if integrated into the hospital’s own appointment system, patients can rearrange appointments when needed.
We can also use AI to predict which patients are most likely to miss an appointment, based on patient behaviours and care pathways, so we can send patients tailored interventions and potentially reduce the no-show rate by 30%.
We can also optimise how appointment slots are filled. One hospital was able to see additional 8.9K patients within three months of trialling this technology.
I’m feeling hopeful that we’re seeing more hospitals and NHS Trusts roll out AI tools in the right places, moving beyond pilots and starting to drive larger scale adoption of products that work. Once we start investing in these tools across the board, we can make care more personalised and interconnected – helping to change the tide of care from treatment to prevention.
What to expect for 2025?
We will continue to see AI tools adopted across hospitals in the UK to streamline complex processes and personalise care. We need to continue to invest in the data infrastructure and evidencing of these tools, to enable further investment into scaling what is having a real impact.
We need a combined effort; the NHS needs more investment in hybrid healthcare efforts, so that digital tools can be integrated across systems. ICS boards need to create teams dedicated to connecting siloed datasets and integrating and implementing AI and other advanced technologies that can help solve long-term issues. And private sector companies need to be working with each other more effectively – to create end-to-end patient experiences that connects all stops on the patient pathway.
The new government has brought a wave of hope back into the healthcare system. We’re seeing promise in Wes Streeting’s language, and we’re eager to see what the 10-Year Health Plan will mean for a strong future of the NHS.
In 2025, once we begin addressing these issues at system-level, we’ll be in a good position to start scaling AI and feeling its benefits – both in lower waiting times and in quick, strong patient care.
About the Author
Brigitte West is Executive Director of Product at DrDoctor. At DrDoctor we’re building the future of outpatient care. DrDoctor is a patient engagement platform that helps the NHS activate patients in their care and increase capacity through waitlist validation and remote management. Our mission is to improve efficiency in healthcare, and ultimately enable the NHS to break the enormous backlog of patients needing care. How do we do this? We are innovators. Our cloud-based patient management tools automate and virtualise processes and care, so that Doctors can focus on their patients, and that patients can engage as true partners in their care.
