Engaging with you about the NCCID
We have been engaging with the people using or affected by our imaging database to understand concerns and answer questions.
The National COVID-19 Chest Imaging Database (NCCID) contains X-ray and other medical images of the chest. It is a national resource being used by hospitals across the country to support better understanding of the virus and develop technology enabling the best care for patients hospitalised with a severe infection.
Getting your views
To provide an opportunity for questions and discussions about the management and use of the NCCID, we have been holding workshops with national patient groups and individuals from hospital trusts.
The purpose was to inform patients and the public on how data about them is being used, how it is being safeguarded, and what impact the data has had on COVID-19 research.
We also discussed the creation of a National Medical Imaging Platform, which will broaden the scope of the NCCID to include all medical images, including X-Rays, CT Scans, MRI, Mammograms, and Ultrasound.
What people wanted to know
Across the workshops run by the NHS AI Lab, people wanted to understand how data about them is being used, how much control they have over their own data, for example opting out, and how the data is safeguarded. We discussed the following topics:
Data access controls
People questioned the robustness of the data access process. Some of the concerns assumed that a much more permissive and unregulated environment exists than is actually the case. They were reassured to hear that data access is well regulated and that any use of the NCCID involves a careful set of procedures. For example, when a data access request is submitted to the NCCID, the request, which needs to meet certain criteria, is approved or rejected by a Data Access Committee - a panel made up of clinicians, academics, commissioners and patients.
The benefit to COVID-19 patients
Individuals who attended the workshops valued knowing what research had been enabled off the back of sharing data with the NCCID. They wanted to know how data about them had been used for the purposes of advancing COVID research and what type of research and findings they had enabled.
The protection of data
Workshop participants expressed concern about data privacy and the risk of reidentification. They welcomed the fact that all data is pseudonymised in the NCCID, which is a technique that separates data from direct identifiers (for example name, surname, NHS number) and replaces them with a pseudonym (for example, a reference number), so that identifying an individual from that data is not possible without additional information. Moreover, patients understood that the NCCID is solely centralising data that already exist in NHS trusts and the pseudonymisation step adds a layer of protection.
Our next steps
From these workshops, it is clear that people are eager to understand the technical nuances around data and how privacy can be preserved, but that we need to find ways of doing it that are accessible to everyone.
To help with this, we have created new and accessible information about how patient data is used in the NCCID.
Following the success of the COVID-19 chest imaging database, the NHS AI Lab Imaging team is looking at developing a National AI Medical Imaging Platform (NMIP) and we would very much like patients and the public to co-design the governance of this platform with us.
The NMIP would include large volumes of data and different types of medical imaging for use in testing and developing AI technologies for a range of health and social care needs. As the NHS AI Lab looks to develop the NMIP it will be important to obtain data from a wide population base and geographical spread to avoid unintended bias in the system.
If you would to like to be involved in this work and want to feedback on the governance of the NMIP please contact the imaging team at firstname.lastname@example.org.
See how you can get involved in some of our other AI programmes by visiting our information page: NHS AI Lab: Get involved.