Real-world evidence framework

Real-world data can improve our understanding of:

  • health and social care delivery
  • patient outcomes and experiences
  • the value of new or existing interventions.

We want to use real-world data to resolve gaps in knowledge and drive forward access to innovations for patients. We developed this framework to deliver on this ambition.

We've also developed a summary of the framework to support users less familiar with real-world data. The summary also describes the principles of high-quality evidence.

View the framework

About the framework

The framework aims to advance the use of real-world evidence in our guidance by:

  • identifying when we can use real-world data to reduce uncertainties and improve guidance
  • describing best-practices for planning, conducting, and reporting real-world evidence studies.

This will help:

  • improve the transparency and quality of real-world evidence used to inform our guidance
  • improve committee trust in real-world evidence studies
  • ensure we use real-world evidence where it helps to:
    • reduce uncertainties
    • improve recommendations
    • speed up access of patients to new effective interventions.

The framework does not set minimum standards for the acceptability of evidence. Please refer to the relevant NICE manuals below for information on how we make recommendations:

The framework is most relevant to those developing evidence to inform our guidance. It's also relevant to patients, those collecting data, and reviewers of evidence.

We've also developed the evidence standards framework for digital health technologies. This lays out what good levels of evidence for digital health technologies look like. It's aimed at innovators and commissioners of digital health technologies.

How we developed the framework

We developed the framework by collecting research and existing best-practice guidance. We obtained this from research, professional organisations and other regulatory or health technology assessment bodies.

During development, we received feedback on the framework through a series of workshops and through public consultation. The stakeholders involved included:

  • patients and patient organisations
  • health charities
  • healthcare professionals
  • the pharmaceutical and medical technologies industries
  • data controllers and contract research organisations
  • academia
  • international health technology assessment bodies
  • NICE committee members
  • UK health system partners.

Based on the feedback received, we revised the framework.

We would like to thank everyone who took part in the development and review of the real-world evidence framework.

The preliminary version of the real-world evidence framework (Word) that we developed for the updated NICE health technology evaluations manual is also available.

User profiles

To help us develop the framework, we created fictional user profiles. We used these to illustrate how different users can engage with the real-world evidence framework and its benefits. This is an example profile:

"I'm clinical lead for a medical technology company creating an early warning system to track patients’ progression in intensive care.

"We want to collect data to demonstrate the impact of deploying our device in routine clinical settings on system outcomes including staff time and time patients spend in hospital.

"The framework is useful for guiding the collection of data. In particular it helps us understand the variables that we need to collect to demonstrate value and how this should be reported."

Shaun, persona of a clinical lead at a small MedTech company

Plans for further development

This is a living framework and we will update it based on our learnings from its implementation. We will also collect case studies to show and describe the successful and unsuccessful uses of real-world data to inform guidance. There will be at least one update before July 2023.

Based on feedback given during consultations and other activities within NICE, we will also consider extending the framework to cover more priority topics in real-world data.