The NHS is more digital than ever – electronic health record (EHR) adoption is universal in primary care, and the NHS App now serves more users than Netflix. Digitalisation is at the heart of the recently-announced NHS ten-year health plan, which is looking to drive efficiencies for staff and patients, while improving access to services and delivering preventative care, as evidenced by the newly-announced Neighbourhood Health Services hubs.
To achieve this effectively though, ultimately comes down to data – quality data that’s accessible at both a national and local level. At a national scale, consistent, high-quality information has the potential to let professionals spot emerging health trends, target resources where they are needed most, and measure progress fairly across every region. At a local level, it can act as the fuel supplying the new community-based, preventive models as they look to share information seamlessly between GP, acute, and community teams.
Gauging the data challenge
Unfortunately, the reality is that fragmented architectures and duplicate records often make the above vision a difficult one to realise in the NHS.
To illustrate this point, consider a typical A&E department: an unconscious patient arrives without identification and is booked into the hospital as John Doe. When his real details later surface, the record is updated but earlier visits, logged with slightly different demographics, have already spawned duplicate files that the patient administration system cannot easily recognise as the same person.
This causes inefficiencies in patient care and risks important data being missed that could have a negative knock-on effect for patients. The remedy for this is to build quality checks into the workflow, matching new entries against a master patient index, flagging gaps in real time, and routing them back to the data owner for correction. When cleansing is left until a migration or shared-care-record project, it is slow and expensive; quality by design costs less and lasts longer. Advanced analytics and AI can accelerate the spotting of outliers and potential merges, but final decisions still require trained staff and clear accountability.
However, even the cleanest records achieve little if they stay locked inside silos. In other words, turning quality into real-world impact demands equally robust governance. During COVID, controls on who could see what relaxed, however those emergency freedoms have now gone, and projects are back to wrestling with a thicket of data-sharing agreements.
Each one differs slightly, so healthcare teams spend significant time negotiating paperwork instead of delivering insight. Take GP records: current rules let a shared-care system pull the file only while a clinician is with the patient, banning wider population-health analysis.
As an alternative, a national, citizen-centred consent framework, surfaced through the NHS App, would let people opt in to anonymised research or proactive risk alerts with confidence. Consistent, transparent standards applied once and recognised everywhere would unblock innovation, protect privacy, and, crucially, allow local success stories to scale across the country.
Putting a foundational data architecture in place
High-quality data and governance have the potential to bring many benefits to the NHS, especially at a time of reform, but attaining these benefits will not be possible without having a modern data architecture in place. To do this effectively, the NHS needs to build it on open standards - FHIR for fast, secure exchange, and SNOMED CT for consistent clinical meaning - then run it on elastic cloud platforms that flex with demand.
To truly enable interoperability, real-time APIs must expose data at the source, replacing outdated overnight batch transfers. Whether data rests in a national lake or stays in local stores, the architecture must behave as a single fabric: query once, retrieve instantly. A federated pattern, similar to the EU Health Data Space, keeps ownership local while unlocking nation-wide insight. Clinicians feel the impact when an ankle X-ray from another trust appears in seconds, ending the familiar “ten-minute image hunt” and sparing patients repeat scans.
But architecture alone won’t transform care. Clinicians must also trust and feel comfortable with the tools. That means ring-fenced training time, user-centred screens aligned to real-world workflows, and responsive support. When systems work the way teams do, informal work-arounds, such as sharing images over WhatsApp, should quietly disappear.
