Evaluating integrated neighbourhood teams: building the evidence commissioners need

England's NHS is moving care closer to home – but is it working? Integrated Neighbourhood Teams bring together GPs, community nurses, social workers, and hospital specialists to coordinate care for people living with frailty. The model is promising, and several teams are already operating across Oxfordshire. But until now, no one has rigorously measured whether they actually reduce hospital stays, cut costs, or improve how services are used.

That evidence gap matters. Commissioners are making investment decisions about scaling these teams – decisions worth millions of pounds – largely on professional consensus rather than hard data.

Our approach and partners

ARC OxTV researchers are evaluating four frailty-focused Integrated Neighbourhood Teams across Oxfordshire – in Bicester, OX3, Banbury Alliance, and Banbury Cross – comparing healthcare activity 12 months before and 12 months after each team launched.

The evaluation draws on linked primary and secondary care data, tracking changes in healthcare costs, appointment patterns, and hospital length of stay. The analytical method – interrupted time series regression – allows the team to isolate the effect of the new care model from broader trends, without requiring a randomised trial.

This is a genuinely collaborative effort. The research team at the University of Oxford is working alongside Lily O'Connor at NHS Buckinghamshire, Oxfordshire and Berkshire West Integrated Care Board, Alex Clift at Oxford University Hospitals NHS Foundation Trust, and primary care teams from each neighbourhood team site. That close partnership ensures the analysis reflects how services actually run – not just how they look in a dataset.

What we found – and why it matters

This evaluation is ongoing, with full results expected later in 2026. What the work has already delivered is the infrastructure and partnerships needed to answer questions that commissioners urgently need answered:

1. A system-wide analytical framework linking primary and secondary care data across four INT sites – enabling like-for-like comparison of costs, activity, and outcomes before and after implementation.
2. Strengthened analytical capacity across partner organisations, with shared methods that can be reused for future service evaluations beyond this project.
3. A replicable evaluation model demonstrating how quasi-experimental methods can assess complex system changes where randomised trials are neither feasible nor appropriate.

What this means

For patients living with frailty, this work will provide the first rigorous evidence on whether integrated neighbourhood care delivers on its promise – more coordinated support, fewer unnecessary hospital admissions, and more timely care closer to home.

For the health system, the stakes are higher still. Integrated care is a centrepiece of NHS strategy, yet the evidence base for specific delivery models remains thin. This evaluation gives commissioners and service planners in Oxfordshire – and potentially across England – the data they need to make confident decisions about where to invest, what to scale, and what to redesign.

What needs to happen next

The most immediate need is straightforward: complete the analysis and get results into the hands of the people who can act on them – commissioners at NHS Buckinghamshire, Oxfordshire and Berkshire West ICB, local NHS trusts, and the INT teams themselves.

Beyond that, two systemic barriers need attention. First, variation in how different neighbourhood teams are set up and run makes comparison difficult; greater standardisation of core data collection would strengthen future evaluations. Second, incomplete routine data capture remains a persistent problem – the NHS cannot evaluate what it does not reliably record.

Policymakers should use these findings, once available, to guide decisions about scaling integrated neighbourhood team models across England.

Lessons for future research

This project demonstrates the practical value of quasi-experimental designs – specifically interrupted time series regression – for evaluating complex service changes in real-world NHS settings. Where randomisation is not feasible (and in system-level service redesign, it rarely is), these methods offer a credible alternative for generating the kind of evidence commissioners need.

The collaborative approach, embedding researchers alongside operational teams, also proved essential for ensuring data quality and the interpretability of results.