Key Stats at a Glance
- Improved patient outcomes and confidence
- Validated capacity gains for frontline staff
- AI literacy embedded across leadership teams
Client & Context
NHS Diagnostics in the Midlands faced mounting pressures: increasing demand, workforce strain, and ambitious targets set by the NHS Long Term Plan. Reducing “Did Not Attends” (DNAs) and unnecessary appointments was central to improving both patient outcomes and operational efficiency.
While AI and automation were already being explored across individual Trusts, efforts were fragmented. Without a unified, strategic approach, the region risked duplicating work, missing ROI, and failing to deliver on national objectives.
Hudson & Hayes was brought in to design and deliver a cohesive strategy for AI adoption in diagnostics, aligned with both clinical needs and operational realities.
The Challenge
The key pain points included:
- High DNA rates and unnecessary appointments, driving inefficiency and increasing costs.
- Fragmented adoption of AI, with promising use cases identified but no centralised roadmap.
- Limited AI literacy among clinicians and leaders, making it difficult to identify, assess, and implement opportunities.
- Risk of falling short of NHS Long Term Plan goals if systemic improvements were not achieved.
At stake was the ability to improve patient access, reduce anxiety and waiting times, and release clinical capacity to focus on those most in need
The Solution
Hudson & Hayes applied its GenAscend methodology, moving from education through discovery to solution design and prototyping.
1. Educate & Align
- Delivered AI literacy enablement for NHS leaders and ICS representatives, including clinicians.
- Ran workshops on AI fundamentals, governance, and practical applications in diagnostics.
- Shared real-world case studies to demonstrate what was possible and inspire buy-in.
2. Discover & Reimagine
- Conducted a comprehensive assessment of AI opportunities across diagnostics services.
- Identified key processes where AI could reduce inefficiencies, such as appointment scheduling and patient engagement.
- Built a benefits model, linking potential capacity gains and ROI to clinical and operational priorities.
3. Build & Transform
- Developed and validated patient-facing AI solution POC,, including a conversational AI Appointment Assistant accessible via mobile, web, SMS, or the NHS App.
- Implemented nudges, reminders, and multimedia content to reduce DNAs and improve patient preparedness.
- Prototyped scalable, low-friction access options (e.g., QR codes on appointment letters, secure SMS links).
Key Outcomes
The engagement delivered measurable benefits:
- Identified 90,000 unnecessary appointments opportunity, freeing up vital clinical capacity.
- Patient confidence improved through accessible, on-demand AI support available 24/7.
- Validated capacity gains, ensuring resources were redirected to patients most in need.
- Unified strategy across the region, consolidating learnings and preventing duplication.
- End-to-end AI enablement delivered, ensuring NHS leaders and clinicians gained the literacy to continue building capability.
Conclusion
By taking a structured, collaborative approach, Hudson & Hayes helped NHS Diagnostics transform fragmented experimentation into a unified AI-enabled programme. The elimination of 90,000 unnecessary appointments demonstrates both the scale of efficiency achievable and the direct positive impact on patient outcomes.
With AI literacy embedded and a validated roadmap in place, NHS Diagnostics is now positioned to scale adoption further, improving access, efficiency, and patient experiences across the region.
