Real-world evidence has the potential to transform current models of evidence generation. It allows us to better substantiate the benefit of a medical intervention outside clinical trials. Data is taken from sources such as electronic health records, medical claims data and disease registries.

Here at NICE, we want to use real-world data to resolve gaps in knowledge. By making better decisions sooner, we will be able to more quickly drive innovation into the hands of health and care professionals to enable best practice.

Over the last year, we’ve made great progress towards this goal. In June 2022, we published our real-world evidence framework. This identifies when such data can be used, and describes how best to plan, conduct and report real-world evidence studies.

The European Health Data and Evidence Network and the GetReal Institute

In October 2022, NICE hosted a half-day virtual workshop: ‘Regulators are formally adopting real-world evidence, when will health technology assessment?’ We hosted the event as part of our work within the Innovative Medicines Initiative (IMI) grant-funded project European Health Data and Evidence Network (EHDEN). We organised it in collaboration with the GetReal Institute of which NICE is a founding member.

IMI EHDEN is establishing a network of healthcare databases in Europe. Each database in the network conforms to the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM). This model aims to standardise the format and content of data so that data resources can be queried to answer important questions quickly and efficiently.

The network also supports the aims of the GetReal Institute to facilitate the adoption and implementation of real-world evidence in healthcare decision-making in Europe. This important partnership places NICE at the forefront of global developments in this field.

The workshop

We developed the workshop for a broad audience including health technology assessment agencies, industry, academia and not-for-profit organisations. The workshop explored:

  • Developments in the use of real-world evidence at the European Medicines Agency (EMA).
  • Implications and opportunities for health technology assessment agencies and their stakeholders.

Developments at the EMA – DARWIN EU®

The EMA and the European Medicines Regulatory Network recently established the Data Analysis and Real World Interrogation Network (DARWIN EU®). Using the OMOP CDM, DARWIN EU® delivers real-world evidence from across Europe on diseases, populations and the use and performance of medicines. This enables EMA and other organisations in the European medicines regulatory network to use this data whenever needed throughout the lifecycle of a medicinal product.

Implications and opportunities

As part of the workshop, I presented 2 use cases that we are leading on within IMI EHDEN. One focusses on oncology and the other on COVID-19.

One of the difficulties health technology assessment agencies face when assessing treatments for cancer is the uncertainty surrounding long-term projections for overall survival. This is due to insufficient follow-up in clinical trials. During my presentation, I explained how we are exploring the use of data from EHDEN partners to examine real-world survival rates from common cancers (such as breast, lung and colorectal) and one rarer cancer (head and neck). We are using this data to create a dashboard that will help us examine long-term survival projections. This could be used to validate trial-based survival extrapolations, helping health technology agencies like NICE to make better decisions for the benefit of patients and society as a whole.

I also outlined a COVID-19 project we are leading in collaboration with the University of Oxford. We are analysing data from the EHDEN network to assess the effectiveness of baricitinib, tocilizumab and remdesivir in a hospital setting. This demonstrates the potential application of real-world evidence in health technology assessment. It will enable NICE and other health technology assessment organisations to make robust decisions more quickly.

Next steps

The workshop prompted discussion between panellists and speakers, who identified some key steps to support decision-making in health technology assessment:

  • Develop a training strategy to help upskill users and beneficiaries of real-world evidence within health technology assessment.
  • Identify projects that will help develop methodology and build trust in real-world evidence.
  • Use real-world data to define and characterise patient populations and natural history of disease.

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