Dig a little deeper, and the ambition is even more striking:

• ‍Obesity: a government “moonshot” to tackle it.
• GP access: ending the 8am scramble, delivering urgent care closer to home, and potentially phasing out hospital outpatients by 2035.
• Innovation: making the NHS the most AI-enabled health system in the world, while leading globally in genomics.
• Economy: helping people get back to work and supporting the industries of the future.
• Technology: a single patient record, a fully AI-enabled hospital estate, and an NHS app that, by 2028, will act as the “front door” to the entire NHS.

It’s hard to argue with these areas of focus. Equally, it’s hard not to notice how ambitious this is compared to the last decade of progress around NHS reform. However, there is a chance that this time is different. The pressures are understood, the tools are ready, and the political alignment is unusually strong:

• Finances: almost 40% of government spending is going into the NHS at a time when social care and defence also demand attention.
• Demographics: ageing populations and shifting treatment patterns are driving unprecedented demand.
• Technology: AI, genomics, telehealth, and integrated EPRs are at a maturity level unimaginable ten years ago.
• Workforce: shortages in GPs, radiologists, and nurses, along with new working patterns, mean old models just don’t add up anymore.
• Policy alignment: strong cross-departmental backing creates an unusual window for structural change.

So the ambition is right, and the moment is right. The real question is whether we can deliver it. And here’s where the NHS needs a new playbook: one that doesn’t assume reform can simply be designed in Whitehall and pushed out nationally, but instead creates disciplined ways to test, adapt and scale solutions in the messy reality of frontline care.
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Why Current Approaches Fall Short

Even well-resourced programmes sometimes struggle to deliver expected impact. New services and care models can inadvertently increase demand or costs. NHS 111 or urgent care centres, for example, expanded access but sometimes drove more patients into hospitals rather than alleviating pressure.

The impact of innovation programmes often depends on how they are structured:

• Top-down:
  When challenges are defined centrally rather than emerging from frontline experience, solutions risk being less relevant or harder to adopt. Greater practitioner-led problem definition can ensure interventions meet real operational needs.‍

• Fragmented:
  ‍Learning doesn’t always travel across sites or regions, meaning insights from one locality may not benefit others. Building stronger networks and knowledge-sharing mechanisms can accelerate improvement system-wide.

• ‍Deployment challenges:
  ‍Innovations can stall if pathways for procurement, commissioning, and integration are unclear. Planning for scale from the outset helps ensure promising solutions reach more patients and settings.

The consequence is predictable: money, time, and effort are invested, but the system sees limited returns. Inefficiencies persist, and opportunities to improve outcomes, reduce costs, or streamline care are lost. Without structured experimentation, innovation can end up reproducing the very problems it was meant to solve.
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What is a Challenge Programme?

A challenge programme is a structured, problem-first approach to innovation. It starts with a question:

“How might we… transform care delivery, redesign pathways, or optimise resources?”

It mobilises a diverse set of actors - frontline staff, innovators, commissioners, and community partners - to co-create and test interventions in real-world conditions. Unlike traditional approaches, where solutions are pitched to pre-defined domains, a challenge programme embeds experimentation directly into the system. Interventions are tested, refined, and scaled based on operational evidence. 

A notable example of effective practitioner-led experimentation is the NHS Test Beds Programme. By bringing together NHS organisations, technology companies, patients, and carers, the programme demonstrated how real-world pilots can test integrated digital solutions safely and effectively. Innovations were refined through iterative feedback, combining technology with pathway redesign, and generating evidence that could be scaled across the NHS. The Test Beds Programme highlights the value of embedding experimentation within operational realities, showing that collaboration between frontline staff, innovators, and commissioners can produce realisable benefit ratios relative to more traditional models.

The principle is simple: complex problems cannot be solved top-down alone. In the start-up world, where uncertainty is expected and outcomes rarely guaranteed, success comes from disciplined experimentation, rapid iteration, and evidence-based scaling. The NHS can borrow these principles to improve delivery, reduce cost, and generate sustainable impact.
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How a Challenge Programme Works

Challenge programmes are time-bound, cohort-driven, and problem-first:

• Discovery Phase:
  Frontline staff, patients, and stakeholders explore care delivery in detail, validating assumptions, uncovering hidden pain points, and grounding challenges in operational reality.

• Challenge Definition & Open Call:
  Problems are advertised across the market - start-ups, SMEs, large providers, and social enterprises. Selection focuses on sector knowledge, adaptability, and collaborative mindset, not just pre-made solutions.

• Ecosystem Preparation:
  Staff, patients, commissioners, and clinical leads are oriented and supported. Feedback loops allow innovators to refine interventions, sometimes embedding teams in live pathways for trial periods under co-design governance.

• Evaluation & Scaling:
  Innovations are rigorously evaluated, with evidence standards and operational outcomes tracked. Stakeholders capable of adoption are engaged to ensure solutions scale effectively.

Why a Challenge Programme Alone Isn’t Enough

Even the best programmes have limits. Lessons from the NHS AI in Health and Care Award illustrate this:

• Integration hurdles: Solutions struggled to fit existing IT systems and clinical workflows.
• Sustainability gaps: Maintaining AI models required monitoring, updates, and training, often unplanned.
• Scalability constraints: Interventions effective in one setting did not always translate elsewhere, highlighting the need for tailored deployment and national support.

These examples underline a broader truth: Structured experimentation must be complemented by careful management of uncertainty, robust governance, and planning for long-term sustainability and scale.
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What’s Missing in Existing Programmes

Across NHS innovation initiatives, four dimensions are critical to maximise impact:‍

1. Place-Based: Anchored locally, reflecting operational realities, population needs, and wider ecosystem interactions (social care, local government, employers, civil society).
2. Networked: Connected across sites to share insights, evidence, and best practice.
3. Challenge-Led: Driven by real-world problems, informed by frontline experience rather than top-down mandates.
4. Deployment-Focused: Clear pathways for commissioning, procurement, integration, and scale.

While many programmes have made valuable contributions, some innovations - such as AI pilots - have shown the importance of robust governance, national coordination, and implementation support to fully realise their potential. Emphasising these dimensions can help ensure that promising solutions are effectively adopted, scaled, and sustained across the NHS.
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A Network-Based Approach for Systemic Transformation

To maximise impact, we propose a network-based challenge programme that embeds experimentation directly into the NHS system while ensuring learning is transferable and interventions are scalable.

Core Components:

• Discovery & Challenge Definition:
  User - and professional - led sprints validate assumptions and define meaningful challenges. This also involves looking at what has worked in other locations to address similar challenges. 

• Open Call & Innovator Pairing:
  ‍Start-ups, SMEs, and larger organisations are matched with operational partners to co-develop solutions.

• Embedded Experimentation:
  ‍Trial interventions in live pathways with real-time feedback.

• Evaluation & Evidence:
  Apply robust standards, including consent, governance, and measurable outcomes. This component needs to be layered throughout the programme setup and execution, not just at the evaluation stage. 

• Deployment & Change Support:
  Provide funding, governance frameworks, and compliance solutions to reduce adoption barriers.

• Networked Learning:
  Multiple sites share insights and synthesise evidence without imposing a single model. This can be done by including a set of Network Partners, such as a Royal College, ICB, or even a body such as the Ministry of Defence’s JHub that spans multiple geographies.

Implementation Phases:

Example: System-Level Pilot

‍A Primary Care Network, working with local GP practices, deploys this Challenge Programme model to improve hypertension management:

• Discovery Sprints:
  Cross-functional teams - including clinicians, social care staff, public health officers, and patient representatives - map operational and patient challenges. Ethnographic research is conducted in GP practices, while comparative studies explore novel care models. The Department for Health and Social Care (DHSC), in coordination with ICSs and local hospitals, provides policy guidance and data access, while Health Innovation Networks and the King’s Fund offer expertise in evidence synthesis and system-level insight.

• Open Call & Innovator Pairing:
  ‍Start-ups, SMEs, and larger organisations are matched with operational partners to co-develop evidence-driven solutions. For instance, Barnados might partner with an AI Lab and a local major employer to design a technology-enabled care model. NHS Confederation supports engagement with providers, while professional bodies and Royal Colleges provide clinical oversight and assurance. Key charities such as Mind or Age UK contribute lived-experience perspectives.

• Embedded Experimentation:
  Four solution teams trial interventions in live pathways, iterating based on patient adherence, staff workload, and resource efficiency. Local government public health teams monitor population-level impacts, while Care Quality Commission (CQC) and National Institute for Health and Care Excellence (NICE) provide assurance on safety, governance, and compliance. Specialist charities (e.g., Sickle Cell Society, Blood Cancer UK) may be engaged if specific patient cohorts are involved.

• Networked Learning & Evaluation:
  ‍Lessons are shared across multiple Challenge Labs, feeding into national guidance while respecting local context. These Challenge Labs have been set up in advance, and have a level of funding allocated to incentivise their successful participation. Medicines and Healthcare products Regulatory Agency (MHRA) input ensures regulatory compliance where technology or AI interventions are used. A staged evaluation, conducted one year post-implementation, captures operational impact and patient outcomes. Results are disseminated across PCNs, Challenge Labs, Health Innovation Networks, and key national bodies, including DHSC and NHS Providers, to support broader adoption.
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Key Considerations for NHS Challenge Programmes

To ensure safety, effectiveness, and scalability, programmes must address:‍

• Evidence Standards: Use robust evaluation, including randomisation where appropriate.
• Data Governance: Secure consent and organisational alignment before interventions, with clear data protocols.
• Risk Management: Engage all stakeholders responsible for care quality and safety; prevent unacceptable failures.
• Funding & Change Support: Plan for post-pilot adoption, providing resources, governance, and change management.
• Simplifying Compliance: Reduce barriers through standardised agreements and delivery plans, learning from successes like the national stroke AI rollout.
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To Conclude - Learn Before You Deliver, Not After‍

The NHS 10 Year Plan is a thoughtful call to action that is focused on the right problems. To help it succeed, we believe calculated risk taking and experimentation alongside robust measurement, is how the NHS can deliver on this Plan. Doing this in a place-based way that accepts the nuance and complexity of the challenges to be solved, bringing clinicians, local governments, third sector, entrepreneurs, and patients along helps ensure the right feedback loops and improve the chances for success. 

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Special thanks to the following contributors:
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Tara Donnelly (Founder of Digital Care and former Chief Digital Officer of NHS England)
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Malte Gerhold (Director of Innovation and Improvement of the Health Foundation and Executive Director of the Care Quality Commission)

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