Waiting list to recovery: AI in the patient journey

Every point in the patient journey is under pressure. From lengthy waiting lists to strained discharge processes, the NHS is being asked to do more with less — while still maintaining safe, high-quality care. The urgency for change has never been greater.

The NHS’s 10 Year Plan, now in its implementation phase, set out a vision for care that is more personalised, preventative and digitally enabled. Central to that vision is the use of technology to improve patient flow — ensuring people are seen faster, supported more effectively, and discharged safely.

AI and low-code automation aren’t futuristic concepts in this context — they are practical tools that help deliver on the commitments outlined in the plan. When embedded properly, they offer staff better insight, streamline routine tasks, and ensure patients experience smoother transitions throughout their care.

Digital transformation doesn’t need to start with
a major system overhaul. Some of the biggest 
improvements are being driven by low-code platforms and AI tools embedded into the existing NHS infrastructure. What makes the difference is where and how they’re used.

Smarter access and booking

The journey begins before a patient steps through the door. Appointment access is often the first test of a system’s efficiency — and its empathy.

At the Rotherham NHS Foundation Trust, the implementation of a digital patient portal via an AI-driven low-code platform means that patients are engaged in the way they prefer — from the moment of referral, through their waiting period, to booking appointments, including diagnostics tests. The system nudges them with prompts if they get stuck, helping reduce failed attempts and missed appointments. This isn’t just a win for admin teams — it removes anxiety for patients, and ensures better use of diagnostic capacity. The results are clear. Since implementation, call wait times for diagnostics have been cut by 70 per cent and Did Not Attend (DNA) rates have been reduced from 8% to 2%.

Similarly, Hampshire Hospitals NHS Foundation Trust used an online patient engagement portal to tackle appointment communication head-on by reducing its reliance on appointment letters, streamlining over 8,000 letter templates into just a handful. Combined with SMS and email alerts, this dramatically improved patient clarity and responsiveness, while freeing up time for frontline staff. This resulted in a 79% patient uptake and a 39% reduction in DNAs.

These are real, scalable examples of how AI and automation can enhance access, simplify admin, and improve experience — right from the beginning.

Optimising patient flow

Once a patient enters the system, triage determines how quickly and effectively they are seen. AI tools are now helping to speed up this process.

In urgent care settings, AI-powered triage solutions can prioritise patients based on clinical risk, directing them to the right service faster. These systems aren’t replacing clinicians — they’re giving them faster, richer insight so they can focus on care.

At Imperial College Healthcare NHS Trust, intelligent contact centre features now handle more than 11,000 daily interactions, with 95% of calls now answered within one minute. Meanwhile, real-time call-back options and prioritisation tools ensure patients get the support they need without long waits.

Smart triage is also playing a growing role in community and outpatient care. Whether it’s through automated questionnaires or data-driven referral checks, AI helps surface the right information faster.

Automated validation and coordination

Once a patient is in the system, the challenge becomes flow — making sure their journey continues without unnecessary delays. One of the simplest, most effective ways to do this is to validate whether patients still need appointments.

NHS Highland used AI-supported tools to contact patients on outpatient waiting lists, asking whether their referral was still needed. With an 80%+ response rate and 9-15% discharge rate, the Trust significantly reduced unnecessary appointments and prioritised those in real need.

These types of validation exercises — simple in principle, powerful in practice — highlight how automation can unlock capacity without additional clinical input.

Coordination is another key win. AI tools can automatically link appointment types, schedule follow-ups, and flag missing tests or information. This reduces admin time, shortens pathways, and improves safety.

Managing the patient journey

Discharge isn’t the end of the journey — it’s a handover. Unless that handover is clear, timely and supported, patients fall through the cracks.

AI has real potential to speed up safe patient discharge and free up critical hospital beds. Tools such as predictive analytics, automated task coordination and digital communication systems are already helping NHS Trusts identify discharge-ready patients earlier, streamline processes, and reduce unnecessary delays.

Yet the real measure of success isn’t just how quickly patients leave hospital — it’s what happens next. That’s where technology can make a lasting difference. By breaking down data silos and combining AI with accessible communication tools, NHS Trusts can keep patients connected, reassured and supported throughout their recovery.

Digital check-ins and real-time monitoring don’t just ease pressure on hospitals; they provide patients and families with the confidence that care doesn’t stop at the hospital doors. From confirming medication plans to flagging early signs of deterioration, these post-discharge interventions help reduce readmissions, improve recovery experiences, and ensure that hospital beds remain available for those who need them most.

Turning discharge into a digitally enabled process is one of the most effective ways to make recovery more reliable — and the healthcare system more resilient.

Trusts are already using this approach to reduce readmissions, improve recovery confidence and make better use of stretched inpatient beds. When recovery is supported digitally, it becomes proactive — not reactive.

Recovery is not just about staying out of hospital. It’s about progress, and with AI, NHS teams can now monitor that progress in real time.

Remote monitoring tools allow clinicians to track vital signs, symptoms and recovery patterns from home. AI can analyse that data to spot early warning signs — like increasing pain, mobility issues or signs of infection — before they become acute.

This doesn’t just help patients. It helps families, carers and the wider health system by reducing the need for unplanned appointments and emergency visits.

When combined with sentiment analysis — using natural language processing to detect concern or confusion in patient messages — this becomes a complete feedback loop. One that is constantly learning, responding, and improving outcomes.

Across all of this, integration is key. Many NHS Trusts are still operating in silos, with digital tools that work well in isolation but don’t connect across the patient pathway.

AI offers the opportunity to join these dots. Whether it’s linking appointment systems with discharge planners, or integrating community services with hospital records, connected data creates connected care.

Low-code platforms make this easier. They allow local teams to adapt and integrate AI-driven tools around their workflows without waiting on central IT. That flexibility is what makes digital progress sustainable.

Just as importantly, AI supports staff. By reducing repetition, surfacing key information and automating routine processes, it gives professionals time back for patients — not just paperwork.

How to scale

Recent NHS Trust Performance League tables highlight that many of the top-performing Trusts are those already embedding AI and low-code technologies into their operations. While these rankings reflect a broad range of metrics — from estate management to clinical outcomes — it’s clear that effective communication and digital coordination are key enablers of high-quality care.

For this success to scale, digital transformation and AI implementation must stay practical. That means focusing on proven, repeatable interventions. It means listening to staff about what slows them down, and it means designing tools that are inclusive, interoperable and user-friendly.

Low-code platforms play a crucial role in this. They 
give frontline teams the power to build and refine AI-driven digital services without needing deep technical skills. Self-referral portals, digital triage forms, and post-discharge workflows can be created in weeks instead of months or years. By putting control into the hands of those closest to patient care, low-code reduces reliance on overstretched IT teams and speeds up innovation.

Just as importantly, low-code creates a safe environment to experiment. When development is slow and tied up in procurement, there’s little room to test, learn, or improve. Low-code flips that model — enabling fast iteration, local ownership, and the freedom to adapt quickly when something doesn’t work.

This kind of agility is critical in a system as complex as the NHS. Digital solutions must not only solve today’s challenges but also be flexible enough to evolve. That means choosing technologies designed to support both immediate transformation and long-term strategic goals.

For the NHS to become truly digital and deliver on the 10 Year Plan, it needs platforms that can flex to local needs now, while staying robust and relevant into the next decade. Scalable, low-code solutions provide that foundation — ensuring innovation can grow alongside the health system, not in spite of it.

Building confidence and consistency

To make the most of AI across the patient pathway, NHS organisations must also focus on building confidence in its use — among staff, patients and system leaders. That confidence grows when AI tools are deployed with transparency, evaluated clearly, and adapted quickly based on feedback. When clinicians see that automation helps reduce admin rather than clinical autonomy, and when patients find digital touchpoints helpful instead of alienating, trust builds naturally.

Consistency is the next step. Right now, use of AI and automation varies significantly between Trusts and regions. Sharing what works — and why — can help scale progress more evenly across the system. National frameworks, integrated care boards and regional collaboratives all have a role to play in enabling this spread of best practice.

Digital champions at the local level are also crucial. Frontline teams who co-create digital tools are far more likely to use and improve them. That grassroots ownership ensures technology stays relevant and responsive, rather than becoming a top-down mandate.

Ultimately, AI should be viewed not as a standalone project, but as part of a broader cultural shift — towards agile service design, real-time problem solving and joined-up patient care.

A practical path forward

Conversations about NHS transformation must focus 
on tangible, measurable improvements. The priority 
now is implementation — delivering proven digital solutions at scale and embedding them into everyday operations.

AI and automation should be used where they can make the biggest impact: improving patient flow, 
reducing unnecessary appointments, and supporting recovery at home. These technologies are not aspirational — they’re already in use across the NHS, producing reliable gains in efficiency, patient engagement, and care coordination.

What’s needed is a system-wide commitment to adopting what works, removing friction for frontline teams, and ensuring patients experience continuity, not confusion. It’s about making recovery processes smarter, repeatable and consistently effective.

AI should help the NHS do what it does best — deliver timely, safe and person-centred care — with fewer gaps and greater confidence. Because in the end, smarter services aren’t about the tech. They’re about delivering better experiences for patients and professionals alike.