How unified data can supercharge the NHS in 2026

The NHS is entering 2026 with rising momentum. Productivity has improved by 2.7% across the sector between April and July 2025, as a result of stronger digital foundations and the wider use of modern data tools across hospitals, primary care, and integrated care systems.

Although the NHS embracing AI has significant potential, it's essential that GP practitioners are equipped and upskilled to use these technologies safely and effectively. A recent survey shows that three in 10 GPs are already using AI tools in patient consultations, including supporting their diagnosis of the patient’s condition. Using digital tools without adequate training or oversight increases the risk of errors and unintended consequences.

To guide this next phase of adoption, a new National Commission is preparing the framework for AI across the health service, setting the tone for a year of decisive progress. The opportunity ahead lies in a shift in approach, with data intelligence and unified data being at the centre of transformation.

The NHS holds vast amounts of data, but real progress will come when this data is connected, contextualised, and made easily accessible to clinicians and operational leaders so they can act quickly and confidently.

Data intelligence will help the NHS create richer insight, build trust in analytic outputs, and support people throughout the system who make time-sensitive decisions every day. With stronger foundations and a growing national appetite for change, 2026 could be the year when unified data becomes routine practice, rather than aspiration.

Technology that fits the workflow

Clinicians work under intense pressure and face an ever-growing administrative load. Digital tools, including AI, will only succeed if they fit smoothly into these daily clinical workflows. This type of technology should assist teams by reducing administrative tasks and providing tools to help make decisions, rather than drive their behaviour or make decisions for them without any human involvement.

The solutions which succeed are the ones built with frontline experience from the very beginning. When partners, suppliers, and clinical teams actually co-develop solutions, the technology ends up fitting far better into real-world practice. This kind of thoughtful workflow integration encourages adoption, builds trust, and removes unnecessary steps, rather than adding more.

To maximise impact, insight should only appear at the point of need during consultations, triage, discharge planning, and referral. Data entry should be kept to a minimum and, ideally, happen in the background. Routine checks can be automated, with only the most important information surfaced to the clinician.

With this approach, digital transformation becomes something that genuinely supports care, rather than complicates it. A tech-enabled environment puts the right information in the right place at the right moment, helping staff spend more time with patients and where it matters the most.

Workforce capability will define success

Advanced analytics and AI have shaped and transformed healthcare discussions for years, but many systems introduced new tools without the corresponding investment in workforce readiness. As a result, both data teams and frontline staff often experienced frustration.

The NHS is preparing a new productivity and upskilling plan that will focus on supporting staff to become AI ready, data ready, and analytics capable. This direction reflects a global truth: progress depends on people who understand how to interpret, question, and apply insights.

Two groups will require this type of targeted support the most. Firstly, data scientists, analysts, and informatics teams will need advanced training, so they can work with complex data environments and build strong analytic assets. Secondly, frontline clinicians will require improved digital literacy, so they feel confident using outputs from analytic platforms. Training should sit alongside real-world development, including placements, secondments, and shared learning between industry experts and NHS teams. These two types of exchange help people understand how technology functions on the ground and create long term capability within the health service.

A new era for the Single Patient Record

The Single Patient Record continues to evolve as a major national ambition. Early programmes focused on bringing health information into one place, which supported safer and more efficient care. The next stage requires a much broader view, reflecting the direction set out in the NHS 10-Year Plan, which emphasises more personalised, preventative, and coordinated models of care. A patient’s experience is shaped by far more than clinical interactions alone. Housing, employment, education, financial security, and other social factors all influence health outcomes and service demand.

The ability to combine health and non-health data creates a fuller picture of every person and every household. This richer context helps clinicians understand risk, helps care coordinators support vulnerable groups and helps neighborhood teams tailor prevention programmes with greater precision. This aligns closely with the medium-term planning framework, which calls for system-wide collaboration and data-driven approaches to deliver change together across 2026/27 to 2028/29.

The future of the Single Patient Record lies in this wider lens. A health-only view limits insight and keeps vital context outside the care pathway. A unified view supports real person-centred care and gives local teams a powerful tool for planning and intervention.

Decision intelligence for integrated and neighbourhood care

The NHS will introduce new organisational structures in 2026. Integrated health organisations will oversee full care pathways across local systems, and neighbourhood teams will play a larger role in community-based care and prevention. These models depend on close collaboration across services, which increases the volume and variety of data they must interpret. Without a clear approach to unifying and contextualising that data, decision makers face uncertainty and delays.

Decision intelligence provides a structured method for building contextual data assets that link information across services, sectors, and settings. It helps teams identify risk earlier, coordinate care more effectively, and plan resources with greater clarity. In community settings, it supports prevention through insight into households, support networks, and local patterns of need.

This approach aligns with the national shift toward proactive population health, ensuring that decisions rely on reliable evidence, rather than fragmented records or isolated analytics.

Strong foundations for trusted AI

Over several years, the NHS invested in predictive models and risk tools, but many struggled due to inconsistent data quality, limited contextual information, or a narrow focus on clinical variables. Trust suffered when outputs felt unreliable or difficult to apply.

Unified data strengthens the foundations of AI. It allows models to draw on richer information, reduces data quality issues, and improves transparency. When AI performs well, clinicians gain confidence and analytics teams gain a platform for continuous improvement. This approach complements existing investments across the NHS. It supports better performance from current models, rather than calling for complex new algorithms or large-scale data collection.

A future shaped by research and household insight

The upcoming Health Data Research Service will create a powerful national asset for research, clinical trials, and long-term value creation. It will attract interest from academia, life sciences, and technology partners while providing a secure foundation for breakthroughs in treatments and care delivery.

Another emerging opportunity lies in household level intelligence. Understanding relationships and responsibilities within households helps identify safeguarding issues, predict care needs, and design more effective prevention programmes. This moves population health from individual risk to shared environments and supports services that work closely with families and communities.

A unified future

The NHS has an extraordinary opportunity in 2026. Unified data, decision intelligence, and strong workforce capability can transform care quality, operational performance, and long-term population health. Progress depends on clear purpose, thoughtful integration, and a commitment to building trust across the system.

With the right foundations, the NHS can create a modern, resilient, and insight-driven service that supports healthier lives throughout the United Kingdom.

About the author

Ram Rajamaran is a healthcare & life sciences industry leader at Quantexa. He has almost two decades of demonstrated experience in digital transformation, productivity, and cost improvement in the hospital and healthcare industry. He has worked across global health economies; namely, the UK NHS, the Nordics, Kingdom of Saudi Arabia, and the Americas. Before joining Quantexa as their healthcare & life sciences lead, Rajamaran ran his own healthcare data and analytics consultancy for four years, delivering over 30 projects to the NHS and globally. Prior to that, he was the EMEA lead for GE Healthcare’s Command Centre business, where he was part of the leadership team responsible for commercialising and localising the solution and implementing Bradford Teaching Hospitals Command Centre. Rajamaran is passionate about combining artificial intelligence techniques and other innovative technologies to solve complex problems and improve patient outcomes.