Why NHS Organisations Struggle with Data Fragmentation

Why NHS Organisations Struggle with Data Fragmentation (and How to Fix It) 

Across the NHS, data has never been more important or more difficult to use effectively. Rising demand, workforce pressure and sustained scrutiny of performance mean NHS leaders need timely, reliable insight into patient flow, waiting lists and outcomes. Yet for many organisations, data fragmentation remains one of the biggest barriers to improvement. 

Only 27% of public sector organisations believe their data infrastructure provides a comprehensive view of operations or transactions. 
Source: State of Digital Government Review 

Despite years of digital investment, NHS data is still spread across multiple systems: EPRs, PAS, diagnostics, community services, spreadsheets and legacy on-premise data warehouses. The result is a fragmented view of patient journeys and operational performance, exactly when clarity is needed most. 

This challenge is not unique to healthcare. As explored in our 2026 UK Public Sector Data Trends report, fragmented data foundations are now one of the most consistent barriers to transformation across public services, but in the NHS, the consequences are particularly immediate. 

Why this matters now: waiting lists, targets and pressure on access 

The 92% RTT target 

Meeting the 92% Referral to Treatment (RTT) standard requires more than headline waiting list numbers. Trusts need detailed, timely visibility into: 

• Where patients are waiting in pathways 

• Which cohorts are most at risk of breaching 

• How capacity constraints vary by specialty and site 

Fragmented data makes it harder to: 

• Prioritise patients based on clinical urgency 

• Allocate theatre, diagnostic and workforce capacity effectively 

• Intervene early when performance begins to slip 

The RTT standard requires 92% of patients to start consultant-led treatment within 18 weeks, a target that depends on accurate, timely pathway data. 

The financial and political backdrop: less margin for inefficiency 

Data fragmentation is becoming more problematic because of the current NHS financial context. 

Recent national announcements reinforce several realities: 

• NHS funding growth is below historic real-terms averages 

• Waiting list reduction remains a top political priority 

• Trusts and ICBs face multi-billion-pound financial pressures 

• Productivity and efficiency gains are now explicit expectations 

• Significant investment is being directed toward digital and data transformation 

The UK public sector spends £26bn per year on digital technology, yet an estimated £45bn per year of savings remains unrealised through digitisation and modernisation. 

At the same time, workforce constraints and organisational change mean NHS organisations must deliver improvement without increasing operational complexity. 

As highlighted in the 2026 UK Public Sector Data Trends report, constrained budgets are accelerating the shift toward cloud modernisation, data consolidation and cost-optimised platforms across the public sector, healthcare included. 

What data fragmentation looks like in practice across the NHS 

For many NHS organisations, fragmentation shows up in familiar ways: 

• Legacy on-premise data warehouses that struggle to scale 

• High maintenance cost of legacy systems and brittle ETL pipelines 

• Data silos between acute, community, mental health and social care 

• Slow data warehouse analytics during reporting peaks 

• Limited ability to analyse unstructured clinical data 

58% of public sector IT leaders cite skills and talent gaps as a major barrier to digital transformation, increasing the risk of complex, hard-to-maintain data estates. 

These challenges directly affect operational leaders trying to improve access, manage risk and reduce waiting times. 

A different approach: unifying data to prioritise care 

Recent NHS examples highlight a clear shift: rather than replacing every system, organisations are unifying fragmented data using modern cloud data platforms. 

The NHS waiting list video featuring Snowflake shows how bringing data together creates a clearer view of patient waiting lists, helping NHS teams: 

• Identify bottlenecks earlier 

• Prioritise patients more effectively 

• Improve access to care 

• Support faster treatment decisions 
  
  

Real-world proof: Imperial College Healthcare NHS Trust 

Imperial College Healthcare NHS Trust provides a strong example of how data warehouse modernisation can address fragmentation at scale. 

By moving away from a constrained legacy environment and adopting a modern cloud data platform, Imperial has been able to: 

• Integrate data from multiple clinical and operational systems 

• Improve performance and reliability of analytics workloads 

• Enable faster access to insight for both technical and non-technical users 

• Build a scalable foundation for advanced analytics and future AI use cases 
  

Read the Full Case Study

Snowflake’s Performance Index improvements have delivered ~27% query performance gains since 2022, supporting faster insight without added infrastructure complexity. 

What “good” looks like for NHS data foundations 

NHS organisations making progress on data fragmentation tend to share common characteristics: 

• A single, trusted data layer supporting multiple use cases 

• Near-real-time insight into patient flow and demand 

• Reduced dependency on fragile, high-maintenance ETL pipelines 

• Strong governance for sensitive patient data 

• A platform that supports analytics today and AI tomorrow 

How NHS organisations can start fixing fragmentation 

A pragmatic path forward typically includes: 

• Identifying high-impact operational use cases (e.g. RTT pathways, patient flow) 

• Consolidating fragmented datasets into a governed cloud data platform 

• Reducing reliance on manual reconciliation and legacy pipelines 

• Improving performance and scalability of analytics workloads 

• Building confidence in data as a decision-making asset 
  

This phased approach allows trusts and ICBs to deliver value quickly while modernising sustainably, a critical requirement under current financial pressures. 

From fragmented data to faster, more informed care 

Data fragmentation is not a failure of effort, it is the result of systems evolving faster than architectures. But with waiting lists, productivity and outcomes under sustained scrutiny, standing still is no longer an option. 

Modern cloud data platforms give NHS organisations the ability to unify data, prioritise care more effectively and support national targets, while reducing operational burden and improving value from existing resources. 

2026 must be the year of data readiness because better data foundations directly enable better patient access and outcomes. 

To see how this fits into the wider public sector landscape, read our 2026 UK Public Sector Data Trends report.