Citizens' Jury on QCovid: Report on the jury's conclusions and key findings

1. Introduction

Background

Development of the QCovid® model

At the beginning of the pandemic, the four Chief Medical Officers (CMOs) from across the UK identified people they believed were at the highest risk from Covid-19 based on a number of health conditions.^[2] People who were identified through this process were placed on what became known as the 'shielding list' or the 'highest risk list' and asked to strictly self-isolate and minimise contact with other people.

Once there was more medical and other relevant evidence about Covid-19, the four CMOs asked the University of Oxford to develop a more sophisticated way to identify people who were at the highest risk of death or a bad outcome from Covid-19. The University developed a risk model, called QCovid®, that used a range of factors such as age, sex, ethnicity and existing medical conditions to predict an individual's cumulative risk of hospitalisation and/or death from Covid-19.^[3]

The four QCovid® tools

There are four main ways of using QCovid® that have been explored by the Scottish Government to date. These are referred to as 'tools' or 'use cases' and include:

Clinical tool: an online tool which would be available to GPs and clinicians to determine patient risk. They would sit with a patient and enter the patient's data into the tool to generate a risk score. Patients with a high risk score could then be added to the highest risk list by their GP.

Public-facing tool: available to the public online. An individual could enter their own data and a risk score would be generated by the QCovid® model.

Population tool (using non-anonymised data): running the risk model through health records at a national level to identify all those individuals at the highest risk. Anyone identified in this way would be informed that they were at high risk and could be added to the highest risk list.

Population tool (using anonymised data): running QCovid® through anonymised health records at a national or regional basis. This would not identify actual individuals at risk but would allow governments and health boards to see how many people in a certain area were at risk for research and planning purposes.

Use of QCovid® in England

In February 2021, the UK Government used QCovid® in order to identify people who should be prioritised for the first Covid-19 vaccines in England. They ran QCovid® through health records at a national level to identify which individuals were at the highest risk from Covid-19. Those individuals were then placed on England's shielding list and received a vaccine ahead of people who were deemed to be less vulnerable.

At the same time, the UK Government developed and gave GPs access to a clinical tool based on QCovid®. This allowed GPs in England to check an individual patient's risk from Covid-19 and add anyone with a high risk score to the shielding list.

A timeline summarising the development and use of QCovid® is shown in Figure 1 below.

Potential use of QCovid® in Scotland

The Covid Highest Risk Division within the Population Health Directorate at the Scottish Government considered ways to identify individuals at high risk from Covid-19 by deploying QCovid®. The clinical and public-facing tools based on QCovid® were considered for development, but in early 2022 it was decided not to proceed with either of those. This decision was largely based on concerns that QCovid® did not take account of vaccine boosters or the Omicron variant. The Scottish Government is still considering whether to use QCovid®, or a similar model, at a population level if it was updated to take account of vaccine boosters and the effect of the Omicron variant.

The Scottish Government recognised that there would be ethical issues associated with any use of a risk prediction model like QCovid®, but particularly in running one through large datasets of personal health information. As part of the Scottish Government's commitment to ensuring open, honest and transparent government, Ipsos Scotland was commissioned to conduct a Citizens' Jury to better understand the public's views on the use of a risk prediction model like QCovid®.

Objectives

The objectives of this public engagement were to explore attitudes towards QCovid®, and similar risk prediction models, and the different ways in which they could be deployed. The public engagement aimed to understand specifically:

• any ethical concerns around deploying a model like QCovid® in different ways, particularly running the risk model through population level health records.
• any ethical concerns around deploying a model like QCovid® in different scenarios (such as the emergence of a new variant of Covid-19 that is resistant to current vaccines; a waning of current vaccines against existing variants; or low prevalence rates of Covid-19 in a world where vaccines are effective).
• any circumstances or scenarios when the public benefits of using QCovid® would outweigh private concerns over the use of personal data.