NHS Data Architecture

A collaborative approach to health and care data across the NHS.

NHS Data Architecture provides a collaborative approach for defining, structuring and managing health and care data across the NHS.

It brings together agreed standards, governance and supporting services to help organisations work with data more consistently.

By creating shared foundations, NHS Data Architecture helps improve data quality and interoperability, making it easier for information to move between different systems and be understood in a consistent way.

This work is evolving

NHS Data Architecture is being developed over time.

This page will continue to be updated as new services, standards, tools and guidance become available.

Why NHS Data Architecture matters

Health and care data is created and managed across many organisations and digital systems.

Information about people, organisations, services, medicines and other aspects of health and care may be recorded in different ways. This can make it harder to share, compare and reuse data consistently.

NHS Data Architecture helps address this challenge by providing a common approach to how data is described, structured and managed.

This supports:

more consistent data across systems
improved interoperability
better data quality
greater reuse of existing information
more reliable analysis and reporting

How NHS Data Architecture works

NHS Data Architecture is built on a number of connected foundations.

Each foundation focuses on a different aspect of how data is defined, structured, managed or improved.

Together, they help create a shared understanding of health and care data across organisations and systems.

Foundations of NHS Data Architecture

Reference and master data

Provides a trusted and consistent source of information about important health and care concepts such as people, organisations, locations, medicines and services.

It helps create a common source of truth that can be used consistently across systems and organisations.

Without a consistent way of describing important concepts, information can be interpreted differently by different systems. For example, when information refers to a medicine, there needs to be confidence that everyone is referring to the same medicine and its associated information. Reference and master data helps reduce ambiguity and supports more reliable sharing and use of information.

Data design, standards and modelling

Defines how information is structured and how data items relate to one another.

This includes the NHS Canonical Data Model, which provides a common way of representing health and care data.

Individual pieces of information often tell only part of the story. For example, a patient may attend an appointment, have a test and then receive a prescription. Data design and modelling helps ensure these connections are represented consistently, creating a more complete picture of a person's health and care journey.

It also supports systems to work together more effectively by using common structures from the outset. This helps build interoperability into the design of services and systems from the beginning, rather than relying on additional translation or mapping later.

Data linkage

Supports the safe and consistent linking of records from different sources using agreed approaches, identifiers and methods.

Information recorded by a GP surgery and a hospital may relate to the same person, but each setting may record and identify that person in a different ways. Data linkage uses a range of information to help determine when records relate to the same individual so they can be understood together rather than remaining isolated in separate systems.

This enables organisations and clinicians to make better use of information that already exists when analysing data, planning services and making decisions.

Metadata

Provides additional information and context about data, such as where it came from, how it has been structured and how it should be used.

Without context, data can be difficult to interpret correctly. Metadata helps provide that additional context. It can also show who created a dataset, when it was last updated and limitations users should be aware of before using it. This helps users understand the information they are working with and use it with greater confidence.

Data quality

Supports the effective use of data by helping ensure information is trustworthy and suitable for its intended purpose.

Poor quality data can lead to incorrect conclusions or decisions. More broadly, missing, duplicated or inaccurate information can affect how data is understood and used. Data quality helps identify and address these issues, giving users greater confidence in the information they rely on.

How the foundations work together

These foundations are most valuable when they work together.

For example, details about a medicine can use trusted and consistent information, common data structures, metadata and data quality processes. Together, these foundations help ensure information can be understood, shared and reused consistently across health and care services.

NHS Data Architecture builds on existing standards and approaches already used across health and care, rather than creating entirely new ways of working. This helps organisations make use of established standards while supporting greater consistency and interoperability across systems.

These foundations support a shared understanding of data across the NHS. When they work together, information can be interpreted, shared and reused more consistently. This helps reduce duplication, avoid conflicting interpretations of information and support better-informed decisions across health and care services.

Creating a shared data structure

At the centre of NHS Data Architecture is the NHS Canonical Data Model (CDM).

The CDM provides a common logical structure for health and care data. It helps different systems describe information in a consistent way, making it easier to understand, share and reuse.

The CDM is technology agnostic and can be implemented in different ways by different systems and organisations.

Governance and assurance

Trust and confidence are essential parts of NHS Data Architecture.

Governance and assurance help ensure that data is designed, managed and used in a safe, consistent and reliable way.

This includes:

governance arrangements that support consistent implementation
quality assurance processes
controlled management of change
alignment with relevant standards, policies and requirements
monitoring and support for future compliance activities

Governance and assurance also help ensure that new services, systems and data products align with NHS Data Architecture from the outset. This supports greater consistency across the NHS, reduces duplication of effort and helps systems work together more effectively.

As NHS Data Architecture continues to evolve, governance and assurance processes will help maintain confidence in how data is defined, managed and used across health and care services.

Last edited: 11 August 2026 3:59 pm