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The NHS is facing extraordinary challenges, from growing demand on services to financial pressures that leave little room for experimentation. These pressures create an environment where change can feel daunting, and traditional methods often feel like the only safe option.
If there is a way forward that doesn’t involve relentless cycles of improvement projects or costly external consultancy, can NHS organisations adopt it?
AI and advanced analytics offer a way to rethink how we approach these challenges—not by replacing the dedication and expertise of NHS teams, but by amplifying it. This is not about criticism; it’s about understanding why things are the way they are and working together to explore different ways of achieving meaningful, lasting change.
Here are the lessons we are learning when we apply process mining and LLMs in our ongoing work with A&E Teams.
1. Turning Insights into Action: Moving Beyond Dashboards
The NHS has invested heavily in dashboards and data platforms, but too often, these tools end up underutilised—not because the data isn’t valuable, but because it doesn’t connect to the realities of frontline decision-making.
Our recent work with A&E teams has shown that the right tools, combined with the right approach, can change this dynamic. For example:
- Breaches linked to blood test delays: Through process mining, we discovered that breaches were driven by delays in transporting blood samples, rather than laboratory capacity. By increasing portering resources, the issue was resolved without the need for time-consuming cycles of improvement projects.
- Data interrogation with advanced analytics in seconds: When local structured and unstructured data can be interrogated using LLMs and process mining analytics, A&E teams can immediately engage with advanced analytics without additional analytical skills.
- Revealing hidden bottlenecks: Work with A&E departments continues to uncover new insights, highlighting areas for practical, impactful change that weren’t previously visible. Further findings are expected to be shared in the new year (2025).
These examples demonstrate that AI can help teams go beyond surface-level metrics, uncovering root causes that might otherwise remain hidden.
2. Process Mining: A Window into Patient Journeys
Traditional improvement programmes often focus on league tables and benchmarking, which, while useful, rarely translate into the tailored interventions needed to address local challenges.
Process mining offers a different approach. By analysing patient journey data, it highlights inefficiencies and bottlenecks, creating a clearer path to improvement.
For example, in the case of A&E departments, process mining visualised actual patient journeys that clinicians and operational teams recognise, helping everyone to validate concerns raised by staff about delays and inefficiencies. These insights didn’t just point out what was wrong—they provided a basis for common understanding of the problem and hence agreement on practical, localised solutions.
By working in partnership with NHS teams, we’ve seen how these insights can reduce the reliance on external consultants and instead empower staff to take ownership of their own improvement journeys.
3. Making Analytics Accessible and Practical
One of the barriers to change in the NHS is the perception that advanced analytics tools are too complex or technical to be useful on the ground. And let’s be honest—many traditional analytics solutions reinforce this perception, relying on charts and graphs that don’t always translate into clear actions.
AI changes this by presenting insights in a more human-friendly way:
- Conversational tools: AI can interact with users in plain language, making data accessible to everyone.
- Localised recommendations: Instead of generic solutions, AI tools can provide insights tailored to a department or hospital’s unique context.
- Immediate insights: By processing data in seconds, AI can give teams the answers they need, when they need them.
This isn’t about replacing human expertise but supporting it with tools that work for the people on the frontlines of care.
4. Understanding the NHS Context
The NHS doesn’t struggle because of a lack of effort, innovation, or commitment. It struggles because the scale of the challenges it faces requires a different approach.
AI isn’t a magic solution, and it’s not a substitute for the expertise of NHS staff. What it can do is save time, reduce complexity, and highlight opportunities for meaningful change—allowing staff to focus on what really matters: delivering the best possible care for patients. For example:
- By automating routine tasks like producing daily situation reports or monthly board papers, AI can free up time for clinical and operational teams.
- By identifying low-value patient activities like prevent repeat patient triage, it can help NHS teams prioritise efforts where they’ll have the most impact.
- By triangulating large volumes of structure and unstructured local data, it can help provide precise and relevant insights to help NHS teams identify impactful actions that work in their context.
These are small but meaningful changes that, when applied across the system, can create a significant shift in how resources are used and how challenges are tackled.
5. A Shared Journey Towards Change
The NHS has seen many new technologies and initiatives over the years, but not all have lived up to their promises. It’s understandable that leaders might approach AI with caution, or even scepticism.
That’s why the focus needs to be on working together, starting small, and building solutions that reflect the realities of NHS organisations. This isn’t about throwing out everything that’s come before—it’s about enhancing existing capabilities with new tools and approaches that make things better.
As the saying goes, “The future has arrived—it’s just not evenly distributed yet.”
AI has the potential to make a difference, but only if we take the time to understand what NHS teams truly need and how these tools can support—not replace—their expertise.
Looking Ahead
There’s no one-size-fits-all solution for the challenges facing the NHS, but the examples from A&E teams show that change is possible. It starts with listening, understanding, and working collaboratively to explore what’s possible.
If you’re curious about how this approach might work in your organisation, or if you’d like to hear more about the insights we’re uncovering, we would love to have a conversation.
Together, we can explore how to move beyond the status quo and build a future that works—not just for patients, but for the incredible people who make the NHS what it is.