Value for money assessment

In reviewing the Data for R&D Programme for the value it has delivered against expectations we have assessed:

• the amount of funding received, how this compared to the original intent and how it has been spent
• the delivery against expected achievements set out in the Programme business case
• the progress against the original benefits set out

When looking at the value for money of a project or programme it is considered best practice to focus on the '4 Es' of:

• Economy: is the programme buying inputs (resources, staff) at the best price?
• Efficiency: is the programme converting inputs into outputs (services delivered) with minimal waste?
• Effectiveness: are the outputs delivering the intended outcomes (impacts)?
• Equity: is the allocation of benefits fair across the ecosystem (or will it be)?

We have therefore set the highlights of our findings out against these areas. A more detailed review is included in Appendix D.

The Programme has delivered substantial enabling infrastructure and momentum despite funding and structural constraints, but achieving long term value for money will depend on strengthening cost control, performance management, benefits capture and fair distribution across the ecosystem.

The key value for money lessons learned and recommendations are covered in 'Lessons learned and recommendations'.

The Programme has broadly lived within its funding but has not optimised inputs due to structural constraints. Over 2022/23 to 2024/25, it secured £206 million against an original £175 million approval (reduced from the original ask of £200 million in the business case), with an additional £81 million for 2025/26 taking total funding to around £290 million (this includes about £19 million of non-core pass through funding). An average underspend of approximately £5 million a year reflects delayed approvals, annual stop–start releases of funding and capital and revenue budgets not aligning to actual programme needs rather than cost reduction.

Central programme spend follows NHS commercial guidance, but despite an agreed 3-year programme of funding, repeated 1-year settlements and programme 'end dates' have made it hard to recruit permanent staff, driving reliance on short-term resource, which is inherently more expensive than a substantive workforce. Going forward, creating a stable environment where suitably capable permanent resources can be onboarded swiftly and retained effectively will be critical to long term economically effective delivery.

At the regional level, SDEs are embedded in host NHS trusts, integrated care boards (ICBs) or health innovation networks and Programme funding is a contribution to wider costs. This means there is no clean, standalone view of the total cost of SDEs available to the Programme. This is exacerbated by the fact that the SDEs are all independent of the Programme, their governance chains run through their host bodies, and there is no central power to mandate activities or require access to information.

Across the SDE Network, there are high costs which have to be met for access to data from 3rd-party systems providers despite the underpinning work being undertaken under central frameworks contracts, which should include this access in the requirements.

Despite funding instability, the Programme has built the core research infrastructure and supporting functions, but efficiency is weakened by fragmented structures and immature performance management. Central funding has created:

• a research ecosystem, comprising of the NHSE SDE, regional SDEs, and NHS DigiTrials
• public trust and engagement in the governance through, for example, data access committees and a programme of national public deliberations
• defined operating models

However, loosely federated delivery, variable maturity, and limited central leverage over SDEs, due to their independent structuring and governance, means the Data for R&D Programme team cannot easily standardise processes or mandate consistent reporting, leading to inefficiencies. Additionally, the lack of linked or centralised systems, particularly a customer relationship management (CRM) system, means that providing data for reporting is resource intensive, even with some SDEs having suitable stand-alone tools. The ongoing discovery of the complexities of providing the services and the differing levels of SDE maturity have made these activities difficult until now but the overall programme is now at a point where the benefits outweigh the effort of implementation.

The Programme has recognised these weaknesses and is acting by:

• introducing 'Baseline' run and maintain vs 'Transform' investment and change funding categories so transformation projects can be actively managed
• building account management for SDEs
• starting work on agreements that strengthen reporting obligations
• exploring standardised business systems
• commissioning a comprehensive performance management framework

These steps are necessary to reduce waste, improve visibility and support targeted interventions.

The Programme has made tangible progress on strategic objectives but is more effective as a foundational enabler than as a direct deliverer of end outcomes. The original programme business case forecast around £1.7 billion of quantified benefits over 10 years, revised to £1.4 billion after funding changes and then to £1.6 billion as delivery expectations evolved. However, these benefits were largely framed as long run, system level impacts. For example, changes to disease areas such as cancer outcomes, cardio-vascular disease or operational improvements such as imaging efficiency or growth outcomes such as the life sciences use of real-world data. While it is the Programme’s direct role to provide infrastructure and services that enable others to deliver those benefits.

This review has found:

• benefits were included for which the data and services provided are only early 'enablers', preventing control over delivery and making attribution and measurement difficult
• the only clearly attributable direct benefit to date is SDE income, which is being measured but needs validation and richer data from SDEs
• other real benefits (such as productivity gains, process improvements, reduced duplication, regional standardisation) exist but are not fully documented, although remedial work is underway following an internal review
• governance, standardisation and support for benefits management are incomplete

At the same time, substantive outputs have been achieved. For example:

• the SDE Network now exists, covering the whole population of England
• over 5,700 people have been engaged through patient and public involvement and engagement (PPIE)
• there is a coherent commercial framework and pricing structure that is conceptually agreed but not consistently applied across all SDEs
• standardised templates for key documents and processes are in development, but this is still a work in progress
• there is aggregated profit and loss monitoring for the Programme (but not at local level on an individual SDE basis)

There is breakeven modelling showing a credible but challenging pathway to covering operating costs by 2027/28, with risk-adjusted revenues for the current pipeline forecast at around £10 million (not all delivered in 25/26).

These outputs match the Programme’s role as a foundational platform, which will support many future improvements in health outcomes or operational efficiencies even if these are not yet visible or attributable.

Equity is emerging positively but remains incomplete. The Programme’s design and delivery explicitly sought to enhance the research data landscape by funding 11 regional SDEs, and the national SDE (England), creating England-wide coverage and reducing historic concentration of data infrastructure in a few centres. Funding has supported a broad mix of regions, and SDEs typically sit within NHS trusts that serve varied populations, including more deprived areas.

Public and patient benefit has been a central emphasis, including:

• significant investment in PPIE, including examples like West Midlands allocating about 10% of its budget to engagement
• national public deliberations
• local PPIE in SDE design
• development of communities of practice around PPIE, information governance and communications

Data use registers across all SDEs are intended to improve transparency about who benefits from access.

However, some risks remain.

Variation in SDE maturity and local capacity means that some regions are currently better able to exploit the Network’s opportunities than others.

Genomics, imaging and complex multimodal datasets have not yet been integrated at the scale originally envisaged, limiting equitable access to cutting-edge capabilities. There are examples of the use of integrated datasets that include genomic, imaging and hospital data - the Genomics England (GEL) driver project for example, which onboarded radiology and pathology image data that was then linked to clinical data and genomics profiles to support the training of deep learning models for cancer diagnoses and therapy.

Commercial arrangements and revenue opportunities may cluster around more advanced SDEs unless pipeline management and governance deliberately support equal distribution.

Overall, the Programme shows reasonable levels of economy under difficult conditions, improving levels of efficiency, strong effectiveness as an enabler (rather than an outcomes engine), and promising but incomplete equity potential.

Strengthening financial transparency, performance and benefits management, along with developing a collaborative and equitable operating model design under Health Data Research Service will be crucial to locking in value for money.