By Assad Tabet, Senior Vice President Healthcare & Life Sciences UKI & Europe, Mastek
The UK has long wrestled with health inequality, but growing pressures on public services are greater emphasizing the issue.
For many people in the UK, the circumstances of their daily lives continue to shape how long and how well they live. People living in the most deprived areas develop long-term health conditions almost a decade earlier and have shorter life expectancies than those in more affluent communities. The consequences extend beyond individual health outcomes, placing considerable strain on both public services and the economy.
The causes of these inequalities are clear. Poor housing, insecure work, environmental factors, and unequal access to care all contribute to shaping health outcomes. However, knowing the problem has not been enough to solve it, the UK does not lack health data, it lacks the connections needed to turn that data into action.
Breaking down the barriers between data and care
Significant progress has been made in digitising healthcare. The widespread adoption of electronic patient records marks an important milestone in modernising the NHS. However, digitisation alone does not deliver transformation.
Data remains fragmented as clinical information is held within NHS systems, while equally important insights into housing, employment, and environmental conditions sit across government departments and local authorities. These datasets rarely connect in a meaningful way.
This fragmentation limits the ability to understand the full picture. Without a joined-up view, healthcare systems are often left responding to illness rather than anticipating and preventing it.
A more integrated approach would enable what is often described as a ‘total patient view’. By combining clinical data with social and environmental factors, it becomes possible to better understand risk, predict outcomes, and intervene earlier. This represents a shift from isolated care delivery to truly integrated population health management.
From shared data to shared action
The introduction of the NHS Federated Data Platform marks a critical step forward. By enabling NHS organisations to share operational data, it is already improving areas such as waiting list management, workforce planning, and service coordination.
Its long-term potential goes much further. If aligned with wider government data initiatives, the platform could act as the backbone for cross-government collaboration. Bringing together datasets on housing, air quality, employment, and access to services would unlock new ways of tackling health inequality.
This is about more than efficiency. It is about changing how the system works. Instead of reacting to illness, the NHS and its partners could anticipate need and prevent issues before they escalate.
What happens when data works together
During the COVID-19 pandemic, the Zoe Health Study demonstrated the power of combining patient-generated data with clinical datasets. With over 4.5 million contributors, it became the world’s largest real-time study of COVID-19, enabling faster identification of symptoms, hotspots, and risk factors, and directly informing public health responses. So, the benefits of integrated data are already visible in practice.
At a local level, data sharing has also delivered practical improvements. In Sheffield, collaboration between the NHS and local authorities revealed a pattern of increased emergency admissions linked to gaps in weekend care. Targeted interventions reduced unnecessary hospital visits and improved outcomes for vulnerable groups.
These examples highlight how connecting data enables more informed decisions and more effective services.
Using data to predict, prevent, and protect
One of the most powerful advantages of cross-government data sharing is its ability to enable prevention.
Today, much of healthcare is reactive. Patients are treated once conditions develop or worsen. But many of these conditions are influenced by factors that exist long before a clinical diagnosis.
Better data integration can change this. Linking housing data with health records could help identify individuals living in conditions that increase the risk of respiratory illness. Combining employment and health data could highlight communities vulnerable to mental health challenges. Environmental data could inform targeted interventions in areas affected by poor air quality.
There is also growing potential in citizen-generated data. Mobile apps and wearable devices are capturing real-time insights into behaviour and wellbeing. When used responsibly and with consent, this data can provide a better understanding of population health trends.
Together, these capabilities point to a future where healthcare is proactive, personalised, and preventative.
Trust is the foundation of data sharing
Data sharing must be underpinned by strong governance and public trust. Frameworks such as the UK’s Data Sharing Governance Framework and the Caldicott Principles provide guidance on privacy, security, and ethical data use. These include requirements for data minimisation, anonymisation, and strict access controls.
However, governance alone is not sufficient. Public confidence depends on clear communication and meaningful engagement. People need to understand how their data is used, why it matters, and how it is protected.
Locally tailored engagement strategies are essential to ensure that data initiatives are understood and supported, particularly in communities most affected by health inequalities.
Turning potential into progress
The UK has the capabilities needed to make meaningful progress on health inequality. The challenge now lies in delivering a coordinated approach that turns potential into measurable impact.
Improving how connected data is across government enables earlier intervention, more targeted support, and smarter use of resources. It gives decision-makers a richer understanding of the social, economic, and environmental factors that shape health outcomes.
The opportunity is clear, but realising it will require alignment across organisations, agreed standards, and trust in how data is used. The challenge now is turning these foundations into tangible outcomes.