Having been in operation for over 20 years, it’s a great example of how a Trusted Research Environment (TRE) can support particular areas of research. QResearch is ideally suited to studies and analyses such as:
- Case-control studies
- Cross sectional surveys
- Cohort studies
- Feasibility studies
- Sample size calculations.
Julia Hippisley-Cox told us about QResearch and what it is helping to achieve.
How did QResearch come about and how were the technical capabilities established?
It was co-founded by GP academic Professor Julia Hippisley-Cox and Dr David Stables, co-founder of EMIS in 2002. EMIS is a leading supplier of healthcare IT systems that was originally established by two GPs to give clinicians access to complete and shared medical records, no matter where patients present for care.
In 2002 EMIS joined forces with the University of Nottingham to create QResearch. The vision was to establish a high-quality research database to support ethical research, which would lead to new knowledge to both improve patient care and inform health policy.
It was the first time GPs had shared the electronic health record data with a research organisation, and led the way for other research initiatives benefiting from the wealth of information therein contained . Building on the original design used for GP data, over subsequent years the team added new data linkages to hospital, cancer and mortality data and most recently to COVID-19 datasets.
Have the HDR UK National Core Studies supported the development of QResearch?
They have – by providing funding and technical support, developing standards, establishing the community and offering opportunities for engagement.
What data is available in your TRE, and how can researchers access this data?
The QResearch linked database has high quality data to support world-leading research to improve our understanding of disease and improve patient care. It provides secure access to datasets including:
- GP data
- Cancer Registry Data linked to QResearch
- Civil Registration Data linked to QResearch
- Hospital Episode Statistics linked to QResearch
- Intensive Care National Audit & Research Centre (ICNARC) linked to QResearch
- Second Generation Surveillance System (SGSS) – COVID test data linked to QResearch
- Pregnancy Registry
- COVID National Immunisation Database (NIMS).
Accessing the data involves a comprehensive application process which starts with a feasibility assessment, ensures that funding is in place, that a detailed data specification is agreed, a lay summary is produced and that other necessary conditions to uphold data privacy and security are met.
How have the public and patients been involved in the development of QResearch and how do you maintain trust and transparency?
Patient and public involvement and engagement is critical to our organisation – our Advisory Board and Scientific Committee are directly involved in developing research questions, in prioritising projects, in the interpretation of projects and in dissemination. This has recently included helping us design infographics to summarise the output of our research, which we have found a really engaging form of communication with the general public. We publish a summary of all intended uses of the data and add in the outputs once ready.
Tell us about a project where QResearch has played a key role
One example is the QCovid risk calculator which estimates the risk of a patient catching COVID and dying. The ability to identify the most vulnerable was recognised as an urgent need during the early stages of the pandemic.
The calculator takes various factors into account, allowing a patient to be compared to a similar person with no risk factors, and also showing how this ranks against the general population. It also, separately, calculates the risk and ranking of catching Covid and being admitted into hospital. The model, developed by NIHR-funded researchers from 12 institutions, informed UK health policy, and helped NHS Digital prioritise 820,000 people for vaccination.
The team began with an analysis of a pre-existing database of more than eight million people. The information included pseudonymised GP records, hospital records, COVID-19 test results and death registrations corresponding to the first wave of the pandemic.
The researchers considered characteristics such as age, gender, ethnicity and body mass index (BMI). They also looked at the effects of certain treatments and medical conditions.
The outcome demonstrated the value of a multidisciplinary team with various specialisms being able to access data from a Trusted Research Environment in order to deliver innovative research and improvements for the healthcare system.
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