QResearch data linkage project (ODR1819_247)
Queen Mary University of London · Academic
In term In term in the September 2026 edition: the latest version runs to 29 April 2027.
- Reference
- DARS-NIC-656839-K5V9L
- Current version
- v4.2
- Term of current version
- 11 July 2025 to 29 April 2027
- Start date
- Before 22 May 2023
- Data controller
- Sole Data Controller
- Commercial purposes
- Yes
- Sublicensing
- Yes
- Files released to date
- 6
Why the data was released
Objective for processing
Queen Mary University of London (QMUL) requires access to NHS England National Disease Registration Service (NDRS) data for the following research projects:
Q-Research Linked Database and Q-Covid.
QRESEARCH:
The QResearch project aims to develop and maintain a high-quality database of general practice-derived data linked to secondary care data for use in ethical medical research. The database is used for medical research into the causes of disease, history of treatment and outcomes. The QResearch database (GP data only) is distinct from the linked asset (QResearch linked database).
This Data Sharing Agreement (DSA) authorises QResearch to onward share of NDRS Cancer Registry data, Radio Therapy Dataset (RTDS) and Systemic Anti Cancer Dataset (SACT) data with other UK Universities via the QResearch database.
The onward sharing of the data will be subject to the following restrictions:
• QMUL is only permitted to onward share SACT and RTDS where there is a linked cancer registration record.
• QMUL will only share data that can be linked to a GP record they have received from EMIS Health.
Q-COVID:
The Q-Covid project aims to continue to develop an evidence-based risk prediction model that estimates a person’s combined risk of catching coronavirus and being admitted to hospital, catching coronavirus and dying, and dying of coronavirus following a positive PCR test.
There are currently two-ongoing Q-Covid projects that require continued access to RTDS and SACT data, these are:
• Uptake and comparative safety of new COVID-19 therapeutics by age, sex, region, ethnicity, comorbidities, medication, deprivation, risk level and evidence of prior COVID infection. https://www.qresearch.org/research/approved-research-programs-and-projects/uptake-and-comparative-safety-of-new-covid-19-therapeutics/
• Development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population. https://www.qresearch.org/research/approved-research-programs-and-projects/development-and-evaluation-of-a-tool-for-predicting-risk-of-short-term-adverse-outcomes-due-to-covid-19-in-the-general-uk-population/
After these projects conclude NHS England would not expect any further Q-Covid projects to use NDRS data.
The level of the Data is pseudonymised.
The Data is minimised as follows:
- The NDRS Cancer Registry data is limited to 01/01/1995 - latest available
- The RTDS and SACT data is limited to 2010 -- latest available, only data that link to a NDRS Cancer Registry Record will be supplied
The study team have liaised extensively with the NDRS Production team to ensure that the data being requested and retained is limited to only those data items that are necessary to achieve the purpose outlined within this Data Sharing Agreement (DSA).
Under a separate DSA (DARS-NIC-382794-T3L3M) NHS England provision Civil Registration of Deaths, COVID-19-related datasets and all sub-sets of Hospital Episode Statistics (HES). This Data will be linked to the NDRS data disseminated under this DSA, and the GP data contained within the Q-Research database (received from EMIS Health).
The patient-level data linked to QResearch (QResearch linked database) is only accessed by either:
1. QMUL for research projects approved by QMUL QResearch Governance Approvals Route*. This access will be restricted to individuals substantively employed by QMUL, students registered with QMUL and individuals from other universities that have an honorary contract or secondment agreement with QMUL.
2. other UK Universities for research projects that have been approved by the QResearch Governance Approvals Route. This will be supported by the sublicence data-sharing model.
QMUL is the controller who has determined the purpose and means of processing the data being disseminated by NHS England. As the sole controller, QMUL is responsible for ensuring that data will only be processed as described within this DSA.
The lawful basis for processing personal data under the UK General Data Protection Regulation (GDPR) is Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller.
The lawful basis for processing special category data under the UK GDPR is Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.
Dancing House Consulting process the data disseminated under this Agreement under the direction of QMUL.
Dancing House Consulting provide IT services to QMUL, this includes backup services and database administration services. Dancing House Consulting supply support, but do not access data for any other reason. Therefore, any access to the data held under this agreement for any other reason would be considered a breach of the agreement.
The funding for this work comes from multiple sources. Current funders include but are not limited to:
- National Institute for Health Research (NIHR).
- Wellcome Trust
- Health Data Research UK (HDR UK)
- Cancer Research UK
- Blood cancer UK
- Pancreatic cancer UK
- Children with Cancer UK
Funding is ongoing and will continue to be obtained from several different sources.
* QResearch Governance Approvals Route
Research undertaken using the data from the QResearch-linked database continues to be processed using the existing arrangements with respect to scientific review and the provision of annual reports to the Derby Research and Ethics Committee (DREC).
All research projects have to be peer-reviewed, original, hypothesis-driven or hypothesis tested and intended for publication in an academic peer-reviewed journal. All research undertaken using the QResearch database and linked data are subject to independent peer review and the results of all research are published.
Researchers are charged for the work in generating the outputs for research projects and a contribution to the running costs. All subsequent research outputs from QResearch are made publicly and freely available. Risk prediction algorithms derived from QResearch-linked data such as QCancer are published as free open-source software and also licensed for a fee as closed-source software from third parties such as Queen Mary Innovations and ClinRisk Ltd for organisations unable to use the open source.
A summary of the QResearch Application Governance Process is detailed below:
1) Researchers originate a research question and write an outline protocol.
2) Pre-submission enquiry
3) IF feasible, cost estimate & letter of support
4) Researchers secure funding
5) A detailed data specification is produced
6) Co-produce a lay summary with Patient and Public Involvement (PPI) groups
7) Submit the Application
8) Review by Scientific Committee & feedback is given
9) Revisions if needed
10) Obtain approval
11) Timeline agreed for extraction
12) Approve within one month (with associated sublicence agreement in place before NHS England Data is released, if the application is not from QMUL)
Requests are submitted and then reviewed at the monthly QResearch Science Committee. The minutes of the Science Committee is published here https://www.qresearch.org/about/scientific-committee/committee-minutes/
The committee advises the QResearch team on scientific issues relating to research applications, ensuring that each application has a clear research question or hypothesis which is likely to lead to generalisable findings capable of publication in a peer-reviewed medical journal. They advise if the research meets a minimum scientific standard and if not, amendments that will be required. They also assess the risks involved and will seek advice from QResearch Advisory Group if required. The committee ensures they follow the criteria and principles set out by the QResearch Advisory Board in assessing and advising on research applications where data is requested from the QResearch or QResearch-linked databases.
The Chief Investigator for QResearch is responsible for ensuring that data access is provided in accordance with the protocol, and ethics approval for the research database and following the advice of the advisory and scientific committees.
The researchers do not have access to the entire QResearch-linked database. Once an application has been approved (and a sub-licence agreement is in place), a subset of the pseudonymised record-level data (as approved for the study) will be extracted and stored on QMUL servers (as described in more detail in section 5b Processing Activities) and researchers will be given a login to remotely access the specific extract via QMUL servers to conduct their analysis. All remote access must take place within the UK. No record-level data can be downloaded by researchers as the IT system restricts this.
For further information on the application governance process please see the links to the QResearch website below.
QResearch Home Page: https://www.qresearch.org/
Scientific Committee – QResearch: https://www.qresearch.org/about/scientific-committee/
Approved Research Programs and Projects – QResearch: https://www.qresearch.org/research/research-programs-and-projects/
Data – QResearch: https://www.qresearch.org/data
The Data are linked to the existing QResearch database to be used for medical research by academics employed by UK universities. QResearch was a not-for-profit collaboration between the QMUL and Egton Medical Information Systems (EMIS). QResearch was part of EMIS’ corporate social responsibility portfolio and provides GP data from contributing GP practices on a not-for-profit basis. EMIS are not involved with processing the NHS England or GP data at QMUL.
The Data will never be used for sales or marketing purposes.
The Data will only be used for research and analyses where there is a clear benefit to health and social care in England and Wales in order for NHS England to be confident that QMUL meets the requirements under the Health and Social Care Act 2012 as amended by the Care Act 2014.
In line with the National data opt-out policy, opt-outs are not applied because the data is not Confidential Patient Information as defined in section 251(10) and section 251(11) of the National Health Service Act 2006
Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). https://digital.nhs.uk/ndrs/patients/opting-out
Processing activities
EMIS Health (commercial supplier of GP computer systems) process the GP data from the original data controllers (GP practices) and sends it to QMUL. EMIS is not able to access or process any GP data once it is located at QMUL.
EMIS Health is not able to access the NHS England data under any circumstances. GP practices (data controllers) have permitted the GP data it supplies to be linked with the data from NHS England for purposes determined by the Principal Investigator at QMUL and described in this DSA.
No data will flow to NHS England for this DSA.
Before providing data to QMUL, NHS England will use the Open Pseudonymiser software (www.openpseudonymiser.org) to pseudonymise the NHS England data at source. NHS England will use a project-specific ‘salt’ key to ensure that the identifiers are specific to QMUL. NHS England retains the salt key, meaning that QMUL is unable to re-identify the data but can still link the data with the pseudonymised GP data. QMUL will not hold or be given access to a copy of the pseudonymisation salt key.
NHS England provide QMUL with the relevant records and fields from the following NDRS datasets: Cancer Registration, SACT and RTDS datasets.
The Data will contain no directly identifying data items. The Data will be pseudonymised, and there will be no attempt nor requirement to re-identify individuals by linking the records with other data already held by QMUL.
NHS England provides the Data to QMUL via Secure Electronic File Transfer (SEFT). The Data will be linked to other data already contained within the QResearch database at the individual patient level using a pseudonymised version of the NHS number which has been supplied in both GP data and the NHS England data. The linkage will incorporate the following data, all of which are pseudonymised:
• The NDRS data disseminated under this DSA
• The Civil Registration of Deaths, COVID-19-related datasets and all sub-sets of Hospital Episode Statistics (HES) provisioned under DARS-NIC-382794-T3L3M
• Intensive Care National Audit & Research Centre (ICNARC) data
• Lung Cancer Screening Data
QMUL uses offsite backup services administered by Dancing House Consulting but hosted by QMUL.
The Data will be accessed by authorised personnel via remote access. The Data will always remain on QMUL servers.
Researchers are prohibited from and not technically capable of downloading or copying data to local devices.
The data will not leave the UK at any time. All remote access must take place within the UK.
The QResearch database linked to NHS England data will only be accessed by a limited number of substantively employed, individuals within the QResearch unit. They will produce subsets of the data that will be accessed by QMUL (with access restricted to individuals substantively employed by QMUL students registered with QMUL and individuals from other universities that have an honorary contract or secondment agreement) or its sublicensee(s) as per the QResearch Application and Approvals process.
The subsets of data are then used for undertaking research as described in this DSA. These staff will process and analyse the subset of data to address an approved research question(s).
All personnel accessing the Data have been appropriately trained in data protection and confidentiality.
Regular reviews will be undertaken to ensure that all appropriate controls are in place to minimise any risk of re-identification.
QMUL conducts an annual internal audit for auditing the technical controls in place. The scope of the internal audit applies to the review of the QResearch Systems Level Security Policy and QResearch Workstation Setup Requirements.
Expected output
The outputs are research papers which are published in peer reviewed academic scientific journals and presented at academic conferences. All research is published in academic journals with a link from the QResearch website on an ongoing basis. The publications are accompanied by press releases from relevant organisations and highlighted on social media.
Results are also regularly shared with patient participants on the QResearch Advisory Board and PPI representatives on individual research projects.
Examples of conferences include the annual academic conference for the Society of Academic Primary Care and the UK Research and Innovation (UKRI); international conferences such as the North American Primary Care Research Group; the annual conferences of the EMIS National User Group (a national education and research charity representing the GP practices which contribute data to QResearch); annual conferences run by cancer charities such as Macmillan Cancer Support and Pancreatic Cancer UK; local and regional conferences run by the Nottingham Biomedical Research Centre.
Results are also shared with policymakers, including the Chief Medical Officer's (CMO’s) office, the Medicines and Healthcare Products Agency (MHRA), Joint Committee on Vaccination and Immunisation (JCVI), the Department of Health and Social Care (DHSC), Scottish Office and National Institute for Health Care Excellence (NICE) guideline committees on a regular basis via their stakeholder consultations in order to support the development of relevant guidelines.
Outputs will only contain aggregate-level data with small numbers suppressed in line with the HES analysis guide.
No indicators are produced that show the performance of an organisation – indeed the identity of the GP practices contributing to QResearch is not shared with any third party.
Examples of research-related outputs:
The outputs include a risk prediction tool (QCovid) to identify those at high risk of severe outcomes from COVID-19 (including those with cancer and on cancer treatments) and multiple COVID-19-related research reports, research papers which are published in peer-reviewed academic scientific journals (for example, British Medical Journal (BMJ) and Lancet Journals) and presented at academic conferences (for example, Annual Scientific Meeting of the Society for Academic Primary Care (SAPC).
Other outputs include an analysis of the safety of COVID-19 vaccinations and of the uptake, safety and effectiveness of monoclonal antibodies among people with blood cancer.
All research is published in academic journals with a link from the QResearch website on an ongoing basis.
A list of all publications arising from the QResearch database https://www.qresearch.org/publications/research-papers/
Examples of research outputs:
Research funded by INNOVATE UK to develop a risk stratification tool to identify those at high risk of oesophageal cancer will likely lead to a more efficient way of identifying patients who might be eligible for the Cytosponge device (which is an alternative to endoscopy). This is especially important given the limitations on use of endoscopy arising from the COVID-19 pandemic (results expected 2023/4).
Another project funded by INNOVATE UK investigates the risks and benefits and health economic consequences of the pilot lung cancer screening program is expected to inform the development of the national screening program (results expected 2023/4).
Expected measurable benefits
The QResearch database is widely used by researchers to help understand patterns of disease, safety or medicines, development of prediction tools, research into health inequalities and other similar research questions where the results are likely to have benefits for patients, the NHS or to improve understanding of the disease. The research results continue to result in new knowledge and experience regarding disease epidemiology, health inequalities, drug safety, and methods of identifying patients at high risk of serious illnesses. Every year new research is published in high-impact international research journals such as the British Medical Journal and the British Journal of General Practice. The research is ongoing with target dates for individual projects rather than one overall target date.
A complete list of research papers using the QResearch database is published at http://www.qresearch.org/SitePages/publications.aspx
Research arising from the QResearch database including the linked data has been used to inform national policy. For example, research findings have been included in NICE guidelines on suspected cancer, fragility fracture, diabetes, and lipid modification. Research findings have informed the NHS Health Checks programme and Department of Health guidelines on health checks.
Examples of research include an assessment of the safety of COVID-19 vaccines among people with cancer; an investigation of potential links between diabetes drugs and cancer; quantification of the risk of breast cancer associated with various types of oral contraceptive pills and HRT.
Benefits reported so far
There have been many yielded benefits arising from work. The team have derived two key benefits from the Q Research work, two examples;
HES and Mortality Linked data:
Cancer prediction modelling
The database was used to develop the QCancer – www.qcancer.org which assesses the risk that a patient may have a current undiagnosed cancer based on the patient’s risk factors and symptoms. The tool quantifies overall cancer risk and risk of individual cancers to help management decisions e.g. to refer the patient for an urgent 2-week wait or to organise more investigations or to reassure and review the patients as needed. the tools is embedded in GP systems and available for use in clinical consultations. Similar tools are being developed to help identify cancer among children and young people and to inform targeted screening programs among adults better.
QResearch linked database was used to develop the NIHR-funded QCOVID tool https://digital.nhs.uk/coronavirus/risk-assessment/clinical-tool which identifies patients at risk of COVID-19 death and hospital admission. It is used to risk stratify the entire population to add patients to the shielded patient list and prioritise them for vaccination. It is also used as a clinical tool in consultation between patients and clinicians to personalise risk improve decision making and guide interventions including immunosuppressed patients with cancer and those receiving chemotherapy.
In summary, the benefits yielded so far include the cancer work;
Benefits for individuals – personalised risk estimates to improve decision making; prioritisation for referral, screening and other measures including workplace adjustments.
Benefits for clinicians – more reliable objective information on cancer risks to support decision making; automated calculation to supplement decision making (avoids the need for every clinician to assess risk factors individually).
Benefits for researchers- tools to stratify patients for clinical trial entry, which may help make trials run more efficiently and report more quickly,
Benefits for policymakers – better evidence base to inform the development of policy (e.g. distribution of vaccination, prioritisation of novel therapeutics), ensuing equity (e.g adjusting risk by ethnicity to avoid widening health inequalities), the cost-effectiveness of the use of resources and appropriate defendable prioritisation; planning of services.
Datasets on the current version
Legal basis for provision: Health and Social Care Act 2012 – s261(2)(a)
| Dataset | Type of data | Sensitivity | Frequency | Confidential data |
|---|---|---|---|---|
| NDRS Cancer Registrations | Anonymised - ICO Code Compliant | Sensitive | Ongoing | Does not include the flow of confidential data |
| NDRS National Radiotherapy Dataset (RTDS) | Anonymised - ICO Code Compliant | Sensitive | Ongoing | Does not include the flow of confidential data |
| NDRS Systemic Anti-Cancer Therapy Dataset (SACT) | Anonymised - ICO Code Compliant | Sensitive | Ongoing | Does not include the flow of confidential data |
Files released
Files released counts only files released externally by DARS. Access granted in NHS England's own systems, such as its Secure Data Environment, is not included.
This agreement permits sublicensing: the applicant may pass data on to others. Anything passed on is not recorded in this register.
Patient opt-outs were not applied to any of the 6 files released under this agreement, across every version. About opt-outs
Files released against version 4.2 of this agreement, summarised by dataset.
| Dataset | Files | First released | Last released | Opt-outs applied |
|---|---|---|---|---|
| NDRS Cancer Registrations | 1 | July 2025 | July 2025 | No |
| NDRS National Radiotherapy Dataset (RTDS) | 1 | July 2025 | July 2025 | No |
| NDRS Systemic Anti-Cancer Therapy Dataset (SACT) | 1 | July 2025 | July 2025 | No |
Version history
The register lists each renewal of this agreement as a separate row. This site has 4 versions — earlier versions exist, but none has been listed in an edition this site holds.
DARS-NIC-656839-K5V9L-v4.2 11 July 2025 to 29 April 2027
- Title
- QResearch data linkage project (ODR1819_247)
- Commercial
- Yes
- Sublicensing
- Yes
- Datasets
- 3
- Files released
- 3
Datasets: NDRS Cancer Registrations; NDRS National Radiotherapy Dataset (RTDS); NDRS Systemic Anti-Cancer Therapy Dataset (SACT)
What changed from DARS-NIC-656839-K5V9L-v3.6
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2025-07-11 |
Unchanged: Objective for processing, Processing activities, Expected output, Expected measurable benefits, Benefits reported.
DARS-NIC-656839-K5V9L-v3.6 31 January 2025 to 29 April 2027
- Title
- QResearch data linkage project (ODR1819_247)
- Commercial
- Yes
- Sublicensing
- Yes
- Datasets
- 3
- Files released
- 0
Datasets: NDRS Cancer Registrations; NDRS National Radiotherapy Dataset (RTDS); NDRS Systemic Anti-Cancer Therapy Dataset (SACT)
What changed from DARS-NIC-656839-K5V9L-v2.3
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Title | QResearch data linkage project (ODR1819_247) | |
| Applicant organisation | QUEEN MARY UNIVERSITY OF LONDON | |
| Start date | 2025-01-31 |
Data controllers:
+ QUEEN MARY UNIVERSITY OF LONDON · − UNIVERSITY OF OXFORD
Objective for processing
The
Queen Mary
University of
Oxford
London (QMUL)
requires access to NHS England National Disease Registration Service (NDRS) data for the following research projects:
[1 paragraph unchanged]
Q-RESEARCH:
QRESEARCH:
The
Q-Research
QResearch
project aims to develop and maintain a high-quality database of general practice-derived
[18 words unchanged]
research into the causes of disease, history of treatment and outcomes. The
Q-Research
QResearch
database (GP data only) is distinct from the linked asset (QResearch linked database).
Under the Public Health England Office of
This
Data
Release (PHE ODR), the Q-Research project was granted permission
Sharing Agreement (DSA) authorises QResearch
to onward share
the
of
NDRS Cancer Registry
data with other UK Universities. The project team are now seeking additional permissions to use the
data,
Radio Therapy Dataset (RTDS) and Systemic Anti Cancer Dataset (SACT) data
for Q-Research; and, onward share the RTDS and SACT data via the Q-Research database
with other UK
Universities.
Universities via the QResearch database.
[1 paragraph unchanged]
•
The University of Oxford
QMUL
is only permitted to onward share SACT and RTDS where there is a linked cancer registration record.
•
The University of Oxford
QMUL
will only share data that can be linked to a GP record they have received from EMIS Health.
[6 paragraphs unchanged]
To support Q-Research and Q-Covid, Public Health England (PHE) Office for Data Release (ODR) previously disseminated NDRS Cancer Registry data (from January 1993 to December 2018), NDRS Radiotherapy Dataset (RTDS; from July 2018 to May 2020) previously for use in Q-Covid only and NDRS Systemic Anti-Cancer Therapy (SACT) data (from July 2018 to May 2020) previously for use in Q-Covid only.
The level of the Data is pseudonymised.
The study team now requests to receive the latest available data for the NDRS Cancer Registry, RTDS and SACT, and to receive both SACT and RTDS records for cohort members dating back to 2010 onwards.
The Data is minimised as follows:
All data being disseminated is deemed to be pseudonymised.
The data requested will be minimised as follows:
[3 paragraphs unchanged]
Under a separate
Agreement
DSA
(DARS-NIC-382794-T3L3M) NHS England provision Civil Registration of Deaths, COVID-19-related datasets and all sub-sets of Hospital Episode Statistics (HES). This
data
Data
will be linked to the NDRS data disseminated under this
Agreement,
DSA,
and the GP data contained within the Q-Research database (received from EMIS Health).
[1 paragraph unchanged]
1.
the University of Oxford
QMUL
for research projects approved by
the University of Oxford
QMUL
QResearch Governance Approvals Route*. This access will be restricted to individuals substantively employed by
the University of Oxford,
QMUL,
students registered with
the University of Oxford
QMUL
and individuals from other universities that have an honorary contract or secondment agreement with
the University of Oxford.
QMUL.
[1 paragraph unchanged]
The University of Oxford
QMUL
is the controller who has determined the purpose and means of processing the data being disseminated by NHS England. As the sole controller,
the University of Oxford
QMUL
is responsible for ensuring that data will only be processed as described within this DSA.
[2 paragraphs unchanged]
Dancing House Consulting process the data disseminated under this Agreement under the direction of
the University of Oxford.
QMUL.
Dancing House Consulting provide IT services to
the University of Oxford,
QMUL,
this includes backup services and database administration services. Dancing House Consulting supply
[20 words unchanged]
for any other reason would be considered a breach of the agreement.
[9 paragraphs unchanged]
*
The University of Oxford
QResearch Governance Approvals Route
[2 paragraphs unchanged]
Researchers are charged for the work in generating the outputs for research
[38 words unchanged]
licensed for a fee as closed-source software from third parties such as
Oxford University Innovations,
Queen Mary Innovations and ClinRisk Ltd
for organisations unable to use the open source.
[12 paragraphs unchanged]
12) Approve within one month (with associated sublicence agreement in place before NHS England Data is released, if the application is not from
the University of Oxford)
QMUL)
[3 paragraphs unchanged]
The researchers do not have access to the entire QResearch-linked database. Once
[18 words unchanged]
data (as approved for the study) will be extracted and stored on
the University of Oxford
QMUL
servers (as described in more detail in section 5b Processing Activities) and researchers will be given a login to remotely access the specific extract via
the University of Oxford
QMUL
servers to conduct their analysis. All remote access must take place within the UK. No record-level data can be downloaded by researchers as the IT system restricts this.
[5 paragraphs unchanged]
The
data
Data
are
requested to link
linked
to the existing QResearch database to be used for medical research by academics employed by UK universities. QResearch
is
was
a not-for-profit collaboration between the
University of Oxford
QMUL
and Egton Medical Information Systems (EMIS). QResearch
is
was
part of EMIS’ corporate social responsibility portfolio and provides GP data from
[8 words unchanged]
are not involved with processing the NHS England or GP data at
the University of Oxford.
QMUL.
Researchers are charged for generating the outputs from research projects and contributing to the running costs. All subsequent research outputs from QResearch are made publicly and freely available. Risk prediction algorithms derived from QResearch linked data such as QRISK2 are published as free open source software and also licensed for a fee as closed source software from organisations such as Oxford University Innovations and ClinRisk Ltd for organisations unable to use the open source.
[1 paragraph unchanged]
The
NHS England data
Data
will only be used for research and analyses where there is a
[8 words unchanged]
England and Wales in order for NHS England to be confident that
Oxford
QMUL
meets the requirements under the Health and Social Care Act 2012 as amended by the Care Act 2014.
In line with the National data opt-out policy, opt-outs are not applied because the data is not Confidential Patient Information as defined in section 251(10) and
(11)
section 251(11)
of the National Health Service Act 2006
[1 paragraph unchanged]
Processing activities
EMIS Health (commercial supplier of GP computer systems) process the GP data from the original data controllers (GP practices) and sends it to
the University of Oxford.
QMUL.
EMIS is not able to access or process any GP data once it is located at
the University of Oxford.
QMUL.
EMIS Health is neither a data processor nor a data controller for the data provided by NHS England under this Agreement.
EMIS Health is not able to access the NHS England data under
[18 words unchanged]
data from NHS England for purposes determined by the Principal Investigator at
the University of Oxford
QMUL
and described in this
agreement.
DSA.
No data will flow to NHS England for this
Agreement.
DSA.
Before providing data to
the University of Oxford,
QMUL,
NHS England will use the Open Pseudonymiser software (www.openpseudonymiser.org) to pseudonymise the
[9 words unchanged]
a project-specific ‘salt’ key to ensure that the identifiers are specific to
the University of Oxford.
QMUL.
NHS England retains the salt key, meaning that
the University of Oxford
QMUL
is unable to re-identify the data but can still link the data with the pseudonymised GP data.
The University of Oxford
QMUL
will not hold or be given access to a copy of the pseudonymisation salt key.
NHS England
will
provide
the University of Oxford
QMUL
with the relevant records and fields from the following NDRS datasets: Cancer Registration, SACT and RTDS datasets.
The
data
Data
will contain no directly identifying data items. The
data
Data
will be pseudonymised, and there will be no attempt
or
nor
requirement to re-identify individuals by linking the records with other data already held by
the University of Oxford.
QMUL.
NHS England provides
pseudonymised data
the Data
to
the University of Oxford
QMUL
via Secure Electronic File Transfer (SEFT). The
data
Data
will be linked to other data already contained within the QResearch database
[26 words unchanged]
The linkage will incorporate the following data, all of which are pseudonymised:
• The NDRS data disseminated under this
Agreement
DSA
[3 paragraphs unchanged]
The University of Oxford
QMUL
uses offsite backup services
provided
administered
by Dancing House
Consulting.
Consulting but hosted by QMUL.
The
data
Data
will be accessed by authorised personnel via remote access. The
data
Data
will always remain on
the servers at the University of Oxford.
QMUL servers.
[2 paragraphs unchanged]
The QResearch database linked to NHS England data will only be accessed
[12 words unchanged]
They will produce subsets of the data that will be accessed by
the University of Oxford
QMUL
(with access restricted to individuals substantively employed by
the University of Oxford,
QMUL
students registered with
the University of Oxford
QMUL
and individuals from other universities that have an honorary contract or secondment agreement) or its sublicensee(s) as per the QResearch Application and Approvals process.
The subsets of data are then used for undertaking research as described in this
agreement.
DSA.
These staff will process and analyse the subset of data to address an approved research question(s).
[1 paragraph unchanged]
There is no requirement to re-identify individuals from the data and no attempts will ever be made to do this.
[1 paragraph unchanged]
The University of Oxford
QMUL
conducts an annual internal audit for auditing the technical controls in place.
[10 words unchanged]
of the QResearch Systems Level Security Policy and QResearch Workstation Setup Requirements.
Unchanged: Expected output, Expected measurable benefits, Benefits reported.
Objective for processing
Queen Mary University of London (QMUL) requires access to NHS England National Disease Registration Service (NDRS) data for the following research projects:
Q-Research Linked Database and Q-Covid.
QRESEARCH:
The QResearch project aims to develop and maintain a high-quality database of general practice-derived data linked to secondary care data for use in ethical medical research. The database is used for medical research into the causes of disease, history of treatment and outcomes. The QResearch database (GP data only) is distinct from the linked asset (QResearch linked database).
This Data Sharing Agreement (DSA) authorises QResearch to onward share of NDRS Cancer Registry data, Radio Therapy Dataset (RTDS) and Systemic Anti Cancer Dataset (SACT) data with other UK Universities via the QResearch database.
The onward sharing of the data will be subject to the following restrictions:
• QMUL is only permitted to onward share SACT and RTDS where there is a linked cancer registration record.
• QMUL will only share data that can be linked to a GP record they have received from EMIS Health.
Q-COVID:
The Q-Covid project aims to continue to develop an evidence-based risk prediction model that estimates a person’s combined risk of catching coronavirus and being admitted to hospital, catching coronavirus and dying, and dying of coronavirus following a positive PCR test.
There are currently two-ongoing Q-Covid projects that require continued access to RTDS and SACT data, these are:
• Uptake and comparative safety of new COVID-19 therapeutics by age, sex, region, ethnicity, comorbidities, medication, deprivation, risk level and evidence of prior COVID infection. https://www.qresearch.org/research/approved-research-programs-and-projects/uptake-and-comparative-safety-of-new-covid-19-therapeutics/
• Development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population. https://www.qresearch.org/research/approved-research-programs-and-projects/development-and-evaluation-of-a-tool-for-predicting-risk-of-short-term-adverse-outcomes-due-to-covid-19-in-the-general-uk-population/
After these projects conclude NHS England would not expect any further Q-Covid projects to use NDRS data.
The level of the Data is pseudonymised.
The Data is minimised as follows:
- The NDRS Cancer Registry data is limited to 01/01/1995 - latest available
- The RTDS and SACT data is limited to 2010 -- latest available, only data that link to a NDRS Cancer Registry Record will be supplied
The study team have liaised extensively with the NDRS Production team to ensure that the data being requested and retained is limited to only those data items that are necessary to achieve the purpose outlined within this Data Sharing Agreement (DSA).
Under a separate DSA (DARS-NIC-382794-T3L3M) NHS England provision Civil Registration of Deaths, COVID-19-related datasets and all sub-sets of Hospital Episode Statistics (HES). This Data will be linked to the NDRS data disseminated under this DSA, and the GP data contained within the Q-Research database (received from EMIS Health).
The patient-level data linked to QResearch (QResearch linked database) is only accessed by either:
1. QMUL for research projects approved by QMUL QResearch Governance Approvals Route*. This access will be restricted to individuals substantively employed by QMUL, students registered with QMUL and individuals from other universities that have an honorary contract or secondment agreement with QMUL.
2. other UK Universities for research projects that have been approved by the QResearch Governance Approvals Route. This will be supported by the sublicence data-sharing model.
QMUL is the controller who has determined the purpose and means of processing the data being disseminated by NHS England. As the sole controller, QMUL is responsible for ensuring that data will only be processed as described within this DSA.
The lawful basis for processing personal data under the UK General Data Protection Regulation (GDPR) is Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller.
The lawful basis for processing special category data under the UK GDPR is Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.
Dancing House Consulting process the data disseminated under this Agreement under the direction of QMUL.
Dancing House Consulting provide IT services to QMUL, this includes backup services and database administration services. Dancing House Consulting supply support, but do not access data for any other reason. Therefore, any access to the data held under this agreement for any other reason would be considered a breach of the agreement.
The funding for this work comes from multiple sources. Current funders include but are not limited to:
- National Institute for Health Research (NIHR).
- Wellcome Trust
- Health Data Research UK (HDR UK)
- Cancer Research UK
- Blood cancer UK
- Pancreatic cancer UK
- Children with Cancer UK
Funding is ongoing and will continue to be obtained from several different sources.
* QResearch Governance Approvals Route
Research undertaken using the data from the QResearch-linked database continues to be processed using the existing arrangements with respect to scientific review and the provision of annual reports to the Derby Research and Ethics Committee (DREC).
All research projects have to be peer-reviewed, original, hypothesis-driven or hypothesis tested and intended for publication in an academic peer-reviewed journal. All research undertaken using the QResearch database and linked data are subject to independent peer review and the results of all research are published.
Researchers are charged for the work in generating the outputs for research projects and a contribution to the running costs. All subsequent research outputs from QResearch are made publicly and freely available. Risk prediction algorithms derived from QResearch-linked data such as QCancer are published as free open-source software and also licensed for a fee as closed-source software from third parties such as Queen Mary Innovations and ClinRisk Ltd for organisations unable to use the open source.
A summary of the QResearch Application Governance Process is detailed below:
1) Researchers originate a research question and write an outline protocol.
2) Pre-submission enquiry
3) IF feasible, cost estimate & letter of support
4) Researchers secure funding
5) A detailed data specification is produced
6) Co-produce a lay summary with Patient and Public Involvement (PPI) groups
7) Submit the Application
8) Review by Scientific Committee & feedback is given
9) Revisions if needed
10) Obtain approval
11) Timeline agreed for extraction
12) Approve within one month (with associated sublicence agreement in place before NHS England Data is released, if the application is not from QMUL)
Requests are submitted and then reviewed at the monthly QResearch Science Committee. The minutes of the Science Committee is published here https://www.qresearch.org/about/scientific-committee/committee-minutes/
The committee advises the QResearch team on scientific issues relating to research applications, ensuring that each application has a clear research question or hypothesis which is likely to lead to generalisable findings capable of publication in a peer-reviewed medical journal. They advise if the research meets a minimum scientific standard and if not, amendments that will be required. They also assess the risks involved and will seek advice from QResearch Advisory Group if required. The committee ensures they follow the criteria and principles set out by the QResearch Advisory Board in assessing and advising on research applications where data is requested from the QResearch or QResearch-linked databases.
The Chief Investigator for QResearch is responsible for ensuring that data access is provided in accordance with the protocol, and ethics approval for the research database and following the advice of the advisory and scientific committees.
The researchers do not have access to the entire QResearch-linked database. Once an application has been approved (and a sub-licence agreement is in place), a subset of the pseudonymised record-level data (as approved for the study) will be extracted and stored on QMUL servers (as described in more detail in section 5b Processing Activities) and researchers will be given a login to remotely access the specific extract via QMUL servers to conduct their analysis. All remote access must take place within the UK. No record-level data can be downloaded by researchers as the IT system restricts this.
For further information on the application governance process please see the links to the QResearch website below.
QResearch Home Page: https://www.qresearch.org/
Scientific Committee – QResearch: https://www.qresearch.org/about/scientific-committee/
Approved Research Programs and Projects – QResearch: https://www.qresearch.org/research/research-programs-and-projects/
Data – QResearch: https://www.qresearch.org/data
The Data are linked to the existing QResearch database to be used for medical research by academics employed by UK universities. QResearch was a not-for-profit collaboration between the QMUL and Egton Medical Information Systems (EMIS). QResearch was part of EMIS’ corporate social responsibility portfolio and provides GP data from contributing GP practices on a not-for-profit basis. EMIS are not involved with processing the NHS England or GP data at QMUL.
The Data will never be used for sales or marketing purposes.
The Data will only be used for research and analyses where there is a clear benefit to health and social care in England and Wales in order for NHS England to be confident that QMUL meets the requirements under the Health and Social Care Act 2012 as amended by the Care Act 2014.
In line with the National data opt-out policy, opt-outs are not applied because the data is not Confidential Patient Information as defined in section 251(10) and section 251(11) of the National Health Service Act 2006
Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). https://digital.nhs.uk/ndrs/patients/opting-out
Expected output
The outputs are research papers which are published in peer reviewed academic scientific journals and presented at academic conferences. All research is published in academic journals with a link from the QResearch website on an ongoing basis. The publications are accompanied by press releases from relevant organisations and highlighted on social media.
Results are also regularly shared with patient participants on the QResearch Advisory Board and PPI representatives on individual research projects.
Examples of conferences include the annual academic conference for the Society of Academic Primary Care and the UK Research and Innovation (UKRI); international conferences such as the North American Primary Care Research Group; the annual conferences of the EMIS National User Group (a national education and research charity representing the GP practices which contribute data to QResearch); annual conferences run by cancer charities such as Macmillan Cancer Support and Pancreatic Cancer UK; local and regional conferences run by the Nottingham Biomedical Research Centre.
Results are also shared with policymakers, including the Chief Medical Officer's (CMO’s) office, the Medicines and Healthcare Products Agency (MHRA), Joint Committee on Vaccination and Immunisation (JCVI), the Department of Health and Social Care (DHSC), Scottish Office and National Institute for Health Care Excellence (NICE) guideline committees on a regular basis via their stakeholder consultations in order to support the development of relevant guidelines.
Outputs will only contain aggregate-level data with small numbers suppressed in line with the HES analysis guide.
No indicators are produced that show the performance of an organisation – indeed the identity of the GP practices contributing to QResearch is not shared with any third party.
Examples of research-related outputs:
The outputs include a risk prediction tool (QCovid) to identify those at high risk of severe outcomes from COVID-19 (including those with cancer and on cancer treatments) and multiple COVID-19-related research reports, research papers which are published in peer-reviewed academic scientific journals (for example, British Medical Journal (BMJ) and Lancet Journals) and presented at academic conferences (for example, Annual Scientific Meeting of the Society for Academic Primary Care (SAPC).
Other outputs include an analysis of the safety of COVID-19 vaccinations and of the uptake, safety and effectiveness of monoclonal antibodies among people with blood cancer.
All research is published in academic journals with a link from the QResearch website on an ongoing basis.
A list of all publications arising from the QResearch database https://www.qresearch.org/publications/research-papers/
Examples of research outputs:
Research funded by INNOVATE UK to develop a risk stratification tool to identify those at high risk of oesophageal cancer will likely lead to a more efficient way of identifying patients who might be eligible for the Cytosponge device (which is an alternative to endoscopy). This is especially important given the limitations on use of endoscopy arising from the COVID-19 pandemic (results expected 2023/4).
Another project funded by INNOVATE UK investigates the risks and benefits and health economic consequences of the pilot lung cancer screening program is expected to inform the development of the national screening program (results expected 2023/4).
Benefits reported
There have been many yielded benefits arising from work. The team have derived two key benefits from the Q Research work, two examples;
HES and Mortality Linked data:
Cancer prediction modelling
The database was used to develop the QCancer – www.qcancer.org which assesses the risk that a patient may have a current undiagnosed cancer based on the patient’s risk factors and symptoms. The tool quantifies overall cancer risk and risk of individual cancers to help management decisions e.g. to refer the patient for an urgent 2-week wait or to organise more investigations or to reassure and review the patients as needed. the tools is embedded in GP systems and available for use in clinical consultations. Similar tools are being developed to help identify cancer among children and young people and to inform targeted screening programs among adults better.
QResearch linked database was used to develop the NIHR-funded QCOVID tool https://digital.nhs.uk/coronavirus/risk-assessment/clinical-tool which identifies patients at risk of COVID-19 death and hospital admission. It is used to risk stratify the entire population to add patients to the shielded patient list and prioritise them for vaccination. It is also used as a clinical tool in consultation between patients and clinicians to personalise risk improve decision making and guide interventions including immunosuppressed patients with cancer and those receiving chemotherapy.
In summary, the benefits yielded so far include the cancer work;
Benefits for individuals – personalised risk estimates to improve decision making; prioritisation for referral, screening and other measures including workplace adjustments.
Benefits for clinicians – more reliable objective information on cancer risks to support decision making; automated calculation to supplement decision making (avoids the need for every clinician to assess risk factors individually).
Benefits for researchers- tools to stratify patients for clinical trial entry, which may help make trials run more efficiently and report more quickly,
Benefits for policymakers – better evidence base to inform the development of policy (e.g. distribution of vaccination, prioritisation of novel therapeutics), ensuing equity (e.g adjusting risk by ethnicity to avoid widening health inequalities), the cost-effectiveness of the use of resources and appropriate defendable prioritisation; planning of services.
DARS-NIC-656839-K5V9L-v2.3 13 May 2024 to 29 April 2027
- Title
- QResearch-Oxford data linkage project (ODR1819_247)
- Commercial
- Yes
- Sublicensing
- Yes
- Datasets
- 3
- Files released
- 0
Datasets: NDRS Cancer Registrations; NDRS National Radiotherapy Dataset (RTDS); NDRS Systemic Anti-Cancer Therapy Dataset (SACT)
What changed from DARS-NIC-656839-K5V9L-v1.7
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Title | QResearch-Oxford data linkage project (ODR1819_247) | |
| Start date | 2024-05-13 | |
| End date | 2027-04-29 |
Objective for processing
[18 paragraphs unchanged]
- The NDRS Cancer Registry data is limited to
01/01/1995- 31/12/2020.
01/01/1995 - latest available
- The RTDS and SACT data is limited to
2010- 31/10/2022,
2010 -- latest available,
only data that link to a NDRS Cancer Registry Record will be supplied
[51 paragraphs unchanged]
Unchanged: Processing activities, Expected output, Expected measurable benefits, Benefits reported.
Objective for processing
The University of Oxford requires access to NHS England National Disease Registration Service (NDRS) data for the following research projects:
Q-Research Linked Database and Q-Covid.
Q-RESEARCH:
The Q-Research project aims to develop and maintain a high-quality database of general practice-derived data linked to secondary care data for use in ethical medical research. The database is used for medical research into the causes of disease, history of treatment and outcomes. The Q-Research database (GP data only) is distinct from the linked asset (QResearch linked database).
Under the Public Health England Office of Data Release (PHE ODR), the Q-Research project was granted permission to onward share the NDRS Cancer Registry data with other UK Universities. The project team are now seeking additional permissions to use the Radio Therapy Dataset (RTDS) and Systemic Anti Cancer Dataset (SACT) data for Q-Research; and, onward share the RTDS and SACT data via the Q-Research database with other UK Universities.
The onward sharing of the data will be subject to the following restrictions:
• The University of Oxford is only permitted to onward share SACT and RTDS where there is a linked cancer registration record.
• The University of Oxford will only share data that can be linked to a GP record they have received from EMIS Health.
Q-COVID:
The Q-Covid project aims to continue to develop an evidence-based risk prediction model that estimates a person’s combined risk of catching coronavirus and being admitted to hospital, catching coronavirus and dying, and dying of coronavirus following a positive PCR test.
There are currently two-ongoing Q-Covid projects that require continued access to RTDS and SACT data, these are:
• Uptake and comparative safety of new COVID-19 therapeutics by age, sex, region, ethnicity, comorbidities, medication, deprivation, risk level and evidence of prior COVID infection. https://www.qresearch.org/research/approved-research-programs-and-projects/uptake-and-comparative-safety-of-new-covid-19-therapeutics/
• Development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population. https://www.qresearch.org/research/approved-research-programs-and-projects/development-and-evaluation-of-a-tool-for-predicting-risk-of-short-term-adverse-outcomes-due-to-covid-19-in-the-general-uk-population/
After these projects conclude NHS England would not expect any further Q-Covid projects to use NDRS data.
To support Q-Research and Q-Covid, Public Health England (PHE) Office for Data Release (ODR) previously disseminated NDRS Cancer Registry data (from January 1993 to December 2018), NDRS Radiotherapy Dataset (RTDS; from July 2018 to May 2020) previously for use in Q-Covid only and NDRS Systemic Anti-Cancer Therapy (SACT) data (from July 2018 to May 2020) previously for use in Q-Covid only.
The study team now requests to receive the latest available data for the NDRS Cancer Registry, RTDS and SACT, and to receive both SACT and RTDS records for cohort members dating back to 2010 onwards.
All data being disseminated is deemed to be pseudonymised.
The data requested will be minimised as follows:
- The NDRS Cancer Registry data is limited to 01/01/1995 - latest available
- The RTDS and SACT data is limited to 2010 -- latest available, only data that link to a NDRS Cancer Registry Record will be supplied
The study team have liaised extensively with the NDRS Production team to ensure that the data being requested and retained is limited to only those data items that are necessary to achieve the purpose outlined within this Data Sharing Agreement (DSA).
Under a separate Agreement (DARS-NIC-382794-T3L3M) NHS England provision Civil Registration of Deaths, COVID-19-related datasets and all sub-sets of Hospital Episode Statistics (HES). This data will be linked to the NDRS data disseminated under this Agreement, and the GP data contained within the Q-Research database (received from EMIS Health).
The patient-level data linked to QResearch (QResearch linked database) is only accessed by either:
1. the University of Oxford for research projects approved by the University of Oxford QResearch Governance Approvals Route*. This access will be restricted to individuals substantively employed by the University of Oxford, students registered with the University of Oxford and individuals from other universities that have an honorary contract or secondment agreement with the University of Oxford.
2. other UK Universities for research projects that have been approved by the QResearch Governance Approvals Route. This will be supported by the sublicence data-sharing model.
The University of Oxford is the controller who has determined the purpose and means of processing the data being disseminated by NHS England. As the sole controller, the University of Oxford is responsible for ensuring that data will only be processed as described within this DSA.
The lawful basis for processing personal data under the UK General Data Protection Regulation (GDPR) is Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller.
The lawful basis for processing special category data under the UK GDPR is Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.
Dancing House Consulting process the data disseminated under this Agreement under the direction of the University of Oxford.
Dancing House Consulting provide IT services to the University of Oxford, this includes backup services and database administration services. Dancing House Consulting supply support, but do not access data for any other reason. Therefore, any access to the data held under this agreement for any other reason would be considered a breach of the agreement.
The funding for this work comes from multiple sources. Current funders include but are not limited to:
- National Institute for Health Research (NIHR).
- Wellcome Trust
- Health Data Research UK (HDR UK)
- Cancer Research UK
- Blood cancer UK
- Pancreatic cancer UK
- Children with Cancer UK
Funding is ongoing and will continue to be obtained from several different sources.
* The University of Oxford QResearch Governance Approvals Route
Research undertaken using the data from the QResearch-linked database continues to be processed using the existing arrangements with respect to scientific review and the provision of annual reports to the Derby Research and Ethics Committee (DREC).
All research projects have to be peer-reviewed, original, hypothesis-driven or hypothesis tested and intended for publication in an academic peer-reviewed journal. All research undertaken using the QResearch database and linked data are subject to independent peer review and the results of all research are published.
Researchers are charged for the work in generating the outputs for research projects and a contribution to the running costs. All subsequent research outputs from QResearch are made publicly and freely available. Risk prediction algorithms derived from QResearch-linked data such as QCancer are published as free open-source software and also licensed for a fee as closed-source software from third parties such as Oxford University Innovations, for organisations unable to use the open source.
A summary of the QResearch Application Governance Process is detailed below:
1) Researchers originate a research question and write an outline protocol.
2) Pre-submission enquiry
3) IF feasible, cost estimate & letter of support
4) Researchers secure funding
5) A detailed data specification is produced
6) Co-produce a lay summary with Patient and Public Involvement (PPI) groups
7) Submit the Application
8) Review by Scientific Committee & feedback is given
9) Revisions if needed
10) Obtain approval
11) Timeline agreed for extraction
12) Approve within one month (with associated sublicence agreement in place before NHS England Data is released, if the application is not from the University of Oxford)
Requests are submitted and then reviewed at the monthly QResearch Science Committee. The minutes of the Science Committee is published here https://www.qresearch.org/about/scientific-committee/committee-minutes/
The committee advises the QResearch team on scientific issues relating to research applications, ensuring that each application has a clear research question or hypothesis which is likely to lead to generalisable findings capable of publication in a peer-reviewed medical journal. They advise if the research meets a minimum scientific standard and if not, amendments that will be required. They also assess the risks involved and will seek advice from QResearch Advisory Group if required. The committee ensures they follow the criteria and principles set out by the QResearch Advisory Board in assessing and advising on research applications where data is requested from the QResearch or QResearch-linked databases.
The Chief Investigator for QResearch is responsible for ensuring that data access is provided in accordance with the protocol, and ethics approval for the research database and following the advice of the advisory and scientific committees.
The researchers do not have access to the entire QResearch-linked database. Once an application has been approved (and a sub-licence agreement is in place), a subset of the pseudonymised record-level data (as approved for the study) will be extracted and stored on the University of Oxford servers (as described in more detail in section 5b Processing Activities) and researchers will be given a login to remotely access the specific extract via the University of Oxford servers to conduct their analysis. All remote access must take place within the UK. No record-level data can be downloaded by researchers as the IT system restricts this.
For further information on the application governance process please see the links to the QResearch website below.
QResearch Home Page: https://www.qresearch.org/
Scientific Committee – QResearch: https://www.qresearch.org/about/scientific-committee/
Approved Research Programs and Projects – QResearch: https://www.qresearch.org/research/research-programs-and-projects/
Data – QResearch: https://www.qresearch.org/data
The data are requested to link to the existing QResearch database to be used for medical research by academics employed by UK universities. QResearch is a not-for-profit collaboration between the University of Oxford and Egton Medical Information Systems (EMIS). QResearch is part of EMIS’ corporate social responsibility portfolio and provides GP data from contributing GP practices on a not-for-profit basis. EMIS are not involved with processing the NHS England or GP data at the University of Oxford.
Researchers are charged for generating the outputs from research projects and contributing to the running costs. All subsequent research outputs from QResearch are made publicly and freely available. Risk prediction algorithms derived from QResearch linked data such as QRISK2 are published as free open source software and also licensed for a fee as closed source software from organisations such as Oxford University Innovations and ClinRisk Ltd for organisations unable to use the open source.
The data will never be used for sales or marketing purposes.
The NHS England data will only be used for research and analyses where there is a clear benefit to health and social care in England and Wales in order for NHS England to be confident that Oxford meets the requirements under the Health and Social Care Act 2012 as amended by the Care Act 2014.
In line with the National data opt-out policy, opt-outs are not applied because the data is not Confidential Patient Information as defined in section 251(10) and (11) of the National Health Service Act 2006
Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). https://digital.nhs.uk/ndrs/patients/opting-out
Expected output
The outputs are research papers which are published in peer reviewed academic scientific journals and presented at academic conferences. All research is published in academic journals with a link from the QResearch website on an ongoing basis. The publications are accompanied by press releases from relevant organisations and highlighted on social media.
Results are also regularly shared with patient participants on the QResearch Advisory Board and PPI representatives on individual research projects.
Examples of conferences include the annual academic conference for the Society of Academic Primary Care and the UK Research and Innovation (UKRI); international conferences such as the North American Primary Care Research Group; the annual conferences of the EMIS National User Group (a national education and research charity representing the GP practices which contribute data to QResearch); annual conferences run by cancer charities such as Macmillan Cancer Support and Pancreatic Cancer UK; local and regional conferences run by the Nottingham Biomedical Research Centre.
Results are also shared with policymakers, including the Chief Medical Officer's (CMO’s) office, the Medicines and Healthcare Products Agency (MHRA), Joint Committee on Vaccination and Immunisation (JCVI), the Department of Health and Social Care (DHSC), Scottish Office and National Institute for Health Care Excellence (NICE) guideline committees on a regular basis via their stakeholder consultations in order to support the development of relevant guidelines.
Outputs will only contain aggregate-level data with small numbers suppressed in line with the HES analysis guide.
No indicators are produced that show the performance of an organisation – indeed the identity of the GP practices contributing to QResearch is not shared with any third party.
Examples of research-related outputs:
The outputs include a risk prediction tool (QCovid) to identify those at high risk of severe outcomes from COVID-19 (including those with cancer and on cancer treatments) and multiple COVID-19-related research reports, research papers which are published in peer-reviewed academic scientific journals (for example, British Medical Journal (BMJ) and Lancet Journals) and presented at academic conferences (for example, Annual Scientific Meeting of the Society for Academic Primary Care (SAPC).
Other outputs include an analysis of the safety of COVID-19 vaccinations and of the uptake, safety and effectiveness of monoclonal antibodies among people with blood cancer.
All research is published in academic journals with a link from the QResearch website on an ongoing basis.
A list of all publications arising from the QResearch database https://www.qresearch.org/publications/research-papers/
Examples of research outputs:
Research funded by INNOVATE UK to develop a risk stratification tool to identify those at high risk of oesophageal cancer will likely lead to a more efficient way of identifying patients who might be eligible for the Cytosponge device (which is an alternative to endoscopy). This is especially important given the limitations on use of endoscopy arising from the COVID-19 pandemic (results expected 2023/4).
Another project funded by INNOVATE UK investigates the risks and benefits and health economic consequences of the pilot lung cancer screening program is expected to inform the development of the national screening program (results expected 2023/4).
Benefits reported
There have been many yielded benefits arising from work. The team have derived two key benefits from the Q Research work, two examples;
HES and Mortality Linked data:
Cancer prediction modelling
The database was used to develop the QCancer – www.qcancer.org which assesses the risk that a patient may have a current undiagnosed cancer based on the patient’s risk factors and symptoms. The tool quantifies overall cancer risk and risk of individual cancers to help management decisions e.g. to refer the patient for an urgent 2-week wait or to organise more investigations or to reassure and review the patients as needed. the tools is embedded in GP systems and available for use in clinical consultations. Similar tools are being developed to help identify cancer among children and young people and to inform targeted screening programs among adults better.
QResearch linked database was used to develop the NIHR-funded QCOVID tool https://digital.nhs.uk/coronavirus/risk-assessment/clinical-tool which identifies patients at risk of COVID-19 death and hospital admission. It is used to risk stratify the entire population to add patients to the shielded patient list and prioritise them for vaccination. It is also used as a clinical tool in consultation between patients and clinicians to personalise risk improve decision making and guide interventions including immunosuppressed patients with cancer and those receiving chemotherapy.
In summary, the benefits yielded so far include the cancer work;
Benefits for individuals – personalised risk estimates to improve decision making; prioritisation for referral, screening and other measures including workplace adjustments.
Benefits for clinicians – more reliable objective information on cancer risks to support decision making; automated calculation to supplement decision making (avoids the need for every clinician to assess risk factors individually).
Benefits for researchers- tools to stratify patients for clinical trial entry, which may help make trials run more efficiently and report more quickly,
Benefits for policymakers – better evidence base to inform the development of policy (e.g. distribution of vaccination, prioritisation of novel therapeutics), ensuing equity (e.g adjusting risk by ethnicity to avoid widening health inequalities), the cost-effectiveness of the use of resources and appropriate defendable prioritisation; planning of services.
DARS-NIC-656839-K5V9L-v1.7 22 May 2023 to 21 May 2024
- Title
- QResearch and Q-Covid (ODR1819_247)
- Commercial
- Yes
- Sublicensing
- Yes
- Datasets
- 3
- Files released
- 3
Datasets: NDRS Cancer Registrations; NDRS National Radiotherapy Dataset (RTDS); NDRS Systemic Anti-Cancer Therapy Dataset (SACT)
Objective for processing
The University of Oxford requires access to NHS England National Disease Registration Service (NDRS) data for the following research projects:
Q-Research Linked Database and Q-Covid.
Q-RESEARCH:
The Q-Research project aims to develop and maintain a high-quality database of general practice-derived data linked to secondary care data for use in ethical medical research. The database is used for medical research into the causes of disease, history of treatment and outcomes. The Q-Research database (GP data only) is distinct from the linked asset (QResearch linked database).
Under the Public Health England Office of Data Release (PHE ODR), the Q-Research project was granted permission to onward share the NDRS Cancer Registry data with other UK Universities. The project team are now seeking additional permissions to use the Radio Therapy Dataset (RTDS) and Systemic Anti Cancer Dataset (SACT) data for Q-Research; and, onward share the RTDS and SACT data via the Q-Research database with other UK Universities.
The onward sharing of the data will be subject to the following restrictions:
• The University of Oxford is only permitted to onward share SACT and RTDS where there is a linked cancer registration record.
• The University of Oxford will only share data that can be linked to a GP record they have received from EMIS Health.
Q-COVID:
The Q-Covid project aims to continue to develop an evidence-based risk prediction model that estimates a person’s combined risk of catching coronavirus and being admitted to hospital, catching coronavirus and dying, and dying of coronavirus following a positive PCR test.
There are currently two-ongoing Q-Covid projects that require continued access to RTDS and SACT data, these are:
• Uptake and comparative safety of new COVID-19 therapeutics by age, sex, region, ethnicity, comorbidities, medication, deprivation, risk level and evidence of prior COVID infection. https://www.qresearch.org/research/approved-research-programs-and-projects/uptake-and-comparative-safety-of-new-covid-19-therapeutics/
• Development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population. https://www.qresearch.org/research/approved-research-programs-and-projects/development-and-evaluation-of-a-tool-for-predicting-risk-of-short-term-adverse-outcomes-due-to-covid-19-in-the-general-uk-population/
After these projects conclude NHS England would not expect any further Q-Covid projects to use NDRS data.
To support Q-Research and Q-Covid, Public Health England (PHE) Office for Data Release (ODR) previously disseminated NDRS Cancer Registry data (from January 1993 to December 2018), NDRS Radiotherapy Dataset (RTDS; from July 2018 to May 2020) previously for use in Q-Covid only and NDRS Systemic Anti-Cancer Therapy (SACT) data (from July 2018 to May 2020) previously for use in Q-Covid only.
The study team now requests to receive the latest available data for the NDRS Cancer Registry, RTDS and SACT, and to receive both SACT and RTDS records for cohort members dating back to 2010 onwards.
All data being disseminated is deemed to be pseudonymised.
The data requested will be minimised as follows:
- The NDRS Cancer Registry data is limited to 01/01/1995- 31/12/2020.
- The RTDS and SACT data is limited to 2010- 31/10/2022, only data that link to a NDRS Cancer Registry Record will be supplied
The study team have liaised extensively with the NDRS Production team to ensure that the data being requested and retained is limited to only those data items that are necessary to achieve the purpose outlined within this Data Sharing Agreement (DSA).
Under a separate Agreement (DARS-NIC-382794-T3L3M) NHS England provision Civil Registration of Deaths, COVID-19-related datasets and all sub-sets of Hospital Episode Statistics (HES). This data will be linked to the NDRS data disseminated under this Agreement, and the GP data contained within the Q-Research database (received from EMIS Health).
The patient-level data linked to QResearch (QResearch linked database) is only accessed by either:
1. the University of Oxford for research projects approved by the University of Oxford QResearch Governance Approvals Route*. This access will be restricted to individuals substantively employed by the University of Oxford, students registered with the University of Oxford and individuals from other universities that have an honorary contract or secondment agreement with the University of Oxford.
2. other UK Universities for research projects that have been approved by the QResearch Governance Approvals Route. This will be supported by the sublicence data-sharing model.
The University of Oxford is the controller who has determined the purpose and means of processing the data being disseminated by NHS England. As the sole controller, the University of Oxford is responsible for ensuring that data will only be processed as described within this DSA.
The lawful basis for processing personal data under the UK General Data Protection Regulation (GDPR) is Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller.
The lawful basis for processing special category data under the UK GDPR is Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.
Dancing House Consulting process the data disseminated under this Agreement under the direction of the University of Oxford.
Dancing House Consulting provide IT services to the University of Oxford, this includes backup services and database administration services. Dancing House Consulting supply support, but do not access data for any other reason. Therefore, any access to the data held under this agreement for any other reason would be considered a breach of the agreement.
The funding for this work comes from multiple sources. Current funders include but are not limited to:
- National Institute for Health Research (NIHR).
- Wellcome Trust
- Health Data Research UK (HDR UK)
- Cancer Research UK
- Blood cancer UK
- Pancreatic cancer UK
- Children with Cancer UK
Funding is ongoing and will continue to be obtained from several different sources.
* The University of Oxford QResearch Governance Approvals Route
Research undertaken using the data from the QResearch-linked database continues to be processed using the existing arrangements with respect to scientific review and the provision of annual reports to the Derby Research and Ethics Committee (DREC).
All research projects have to be peer-reviewed, original, hypothesis-driven or hypothesis tested and intended for publication in an academic peer-reviewed journal. All research undertaken using the QResearch database and linked data are subject to independent peer review and the results of all research are published.
Researchers are charged for the work in generating the outputs for research projects and a contribution to the running costs. All subsequent research outputs from QResearch are made publicly and freely available. Risk prediction algorithms derived from QResearch-linked data such as QCancer are published as free open-source software and also licensed for a fee as closed-source software from third parties such as Oxford University Innovations, for organisations unable to use the open source.
A summary of the QResearch Application Governance Process is detailed below:
1) Researchers originate a research question and write an outline protocol.
2) Pre-submission enquiry
3) IF feasible, cost estimate & letter of support
4) Researchers secure funding
5) A detailed data specification is produced
6) Co-produce a lay summary with Patient and Public Involvement (PPI) groups
7) Submit the Application
8) Review by Scientific Committee & feedback is given
9) Revisions if needed
10) Obtain approval
11) Timeline agreed for extraction
12) Approve within one month (with associated sublicence agreement in place before NHS England Data is released, if the application is not from the University of Oxford)
Requests are submitted and then reviewed at the monthly QResearch Science Committee. The minutes of the Science Committee is published here https://www.qresearch.org/about/scientific-committee/committee-minutes/
The committee advises the QResearch team on scientific issues relating to research applications, ensuring that each application has a clear research question or hypothesis which is likely to lead to generalisable findings capable of publication in a peer-reviewed medical journal. They advise if the research meets a minimum scientific standard and if not, amendments that will be required. They also assess the risks involved and will seek advice from QResearch Advisory Group if required. The committee ensures they follow the criteria and principles set out by the QResearch Advisory Board in assessing and advising on research applications where data is requested from the QResearch or QResearch-linked databases.
The Chief Investigator for QResearch is responsible for ensuring that data access is provided in accordance with the protocol, and ethics approval for the research database and following the advice of the advisory and scientific committees.
The researchers do not have access to the entire QResearch-linked database. Once an application has been approved (and a sub-licence agreement is in place), a subset of the pseudonymised record-level data (as approved for the study) will be extracted and stored on the University of Oxford servers (as described in more detail in section 5b Processing Activities) and researchers will be given a login to remotely access the specific extract via the University of Oxford servers to conduct their analysis. All remote access must take place within the UK. No record-level data can be downloaded by researchers as the IT system restricts this.
For further information on the application governance process please see the links to the QResearch website below.
QResearch Home Page: https://www.qresearch.org/
Scientific Committee – QResearch: https://www.qresearch.org/about/scientific-committee/
Approved Research Programs and Projects – QResearch: https://www.qresearch.org/research/research-programs-and-projects/
Data – QResearch: https://www.qresearch.org/data
The data are requested to link to the existing QResearch database to be used for medical research by academics employed by UK universities. QResearch is a not-for-profit collaboration between the University of Oxford and Egton Medical Information Systems (EMIS). QResearch is part of EMIS’ corporate social responsibility portfolio and provides GP data from contributing GP practices on a not-for-profit basis. EMIS are not involved with processing the NHS England or GP data at the University of Oxford.
Researchers are charged for generating the outputs from research projects and contributing to the running costs. All subsequent research outputs from QResearch are made publicly and freely available. Risk prediction algorithms derived from QResearch linked data such as QRISK2 are published as free open source software and also licensed for a fee as closed source software from organisations such as Oxford University Innovations and ClinRisk Ltd for organisations unable to use the open source.
The data will never be used for sales or marketing purposes.
The NHS England data will only be used for research and analyses where there is a clear benefit to health and social care in England and Wales in order for NHS England to be confident that Oxford meets the requirements under the Health and Social Care Act 2012 as amended by the Care Act 2014.
In line with the National data opt-out policy, opt-outs are not applied because the data is not Confidential Patient Information as defined in section 251(10) and (11) of the National Health Service Act 2006
Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). https://digital.nhs.uk/ndrs/patients/opting-out
Expected output
The outputs are research papers which are published in peer reviewed academic scientific journals and presented at academic conferences. All research is published in academic journals with a link from the QResearch website on an ongoing basis. The publications are accompanied by press releases from relevant organisations and highlighted on social media.
Results are also regularly shared with patient participants on the QResearch Advisory Board and PPI representatives on individual research projects.
Examples of conferences include the annual academic conference for the Society of Academic Primary Care and the UK Research and Innovation (UKRI); international conferences such as the North American Primary Care Research Group; the annual conferences of the EMIS National User Group (a national education and research charity representing the GP practices which contribute data to QResearch); annual conferences run by cancer charities such as Macmillan Cancer Support and Pancreatic Cancer UK; local and regional conferences run by the Nottingham Biomedical Research Centre.
Results are also shared with policymakers, including the Chief Medical Officer's (CMO’s) office, the Medicines and Healthcare Products Agency (MHRA), Joint Committee on Vaccination and Immunisation (JCVI), the Department of Health and Social Care (DHSC), Scottish Office and National Institute for Health Care Excellence (NICE) guideline committees on a regular basis via their stakeholder consultations in order to support the development of relevant guidelines.
Outputs will only contain aggregate-level data with small numbers suppressed in line with the HES analysis guide.
No indicators are produced that show the performance of an organisation – indeed the identity of the GP practices contributing to QResearch is not shared with any third party.
Examples of research-related outputs:
The outputs include a risk prediction tool (QCovid) to identify those at high risk of severe outcomes from COVID-19 (including those with cancer and on cancer treatments) and multiple COVID-19-related research reports, research papers which are published in peer-reviewed academic scientific journals (for example, British Medical Journal (BMJ) and Lancet Journals) and presented at academic conferences (for example, Annual Scientific Meeting of the Society for Academic Primary Care (SAPC).
Other outputs include an analysis of the safety of COVID-19 vaccinations and of the uptake, safety and effectiveness of monoclonal antibodies among people with blood cancer.
All research is published in academic journals with a link from the QResearch website on an ongoing basis.
A list of all publications arising from the QResearch database https://www.qresearch.org/publications/research-papers/
Examples of research outputs:
Research funded by INNOVATE UK to develop a risk stratification tool to identify those at high risk of oesophageal cancer will likely lead to a more efficient way of identifying patients who might be eligible for the Cytosponge device (which is an alternative to endoscopy). This is especially important given the limitations on use of endoscopy arising from the COVID-19 pandemic (results expected 2023/4).
Another project funded by INNOVATE UK investigates the risks and benefits and health economic consequences of the pilot lung cancer screening program is expected to inform the development of the national screening program (results expected 2023/4).
Benefits reported
There have been many yielded benefits arising from work. The team have derived two key benefits from the Q Research work, two examples;
HES and Mortality Linked data:
Cancer prediction modelling
The database was used to develop the QCancer – www.qcancer.org which assesses the risk that a patient may have a current undiagnosed cancer based on the patient’s risk factors and symptoms. The tool quantifies overall cancer risk and risk of individual cancers to help management decisions e.g. to refer the patient for an urgent 2-week wait or to organise more investigations or to reassure and review the patients as needed. the tools is embedded in GP systems and available for use in clinical consultations. Similar tools are being developed to help identify cancer among children and young people and to inform targeted screening programs among adults better.
QResearch linked database was used to develop the NIHR-funded QCOVID tool https://digital.nhs.uk/coronavirus/risk-assessment/clinical-tool which identifies patients at risk of COVID-19 death and hospital admission. It is used to risk stratify the entire population to add patients to the shielded patient list and prioritise them for vaccination. It is also used as a clinical tool in consultation between patients and clinicians to personalise risk improve decision making and guide interventions including immunosuppressed patients with cancer and those receiving chemotherapy.
In summary, the benefits yielded so far include the cancer work;
Benefits for individuals – personalised risk estimates to improve decision making; prioritisation for referral, screening and other measures including workplace adjustments.
Benefits for clinicians – more reliable objective information on cancer risks to support decision making; automated calculation to supplement decision making (avoids the need for every clinician to assess risk factors individually).
Benefits for researchers- tools to stratify patients for clinical trial entry, which may help make trials run more efficiently and report more quickly,
Benefits for policymakers – better evidence base to inform the development of policy (e.g. distribution of vaccination, prioritisation of novel therapeutics), ensuing equity (e.g adjusting risk by ethnicity to avoid widening health inequalities), the cost-effectiveness of the use of resources and appropriate defendable prioritisation; planning of services.
Register history
When this agreement appeared in, or was edited in, each monthly edition of the register. Built by comparing every edition this site holds.
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June 2023 —
first listed. 1 version: DARS-NIC-656839-K5V9L-v1.7
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June 2024
1 version added: DARS-NIC-656839-K5V9L-v2.3
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February 2025
1 version added: DARS-NIC-656839-K5V9L-v3.6
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August 2025
1 version added: DARS-NIC-656839-K5V9L-v4.2
Cite this page
NHS England (2026) Data Uses Register, September 2026 edition, agreement DARS-NIC-656839-K5V9L, “QResearch data linkage project (ODR1819_247)”. Read via NHS Data Access Explorer (unofficial), https://healthdatauses.uk/agreements/dars-nic-656839-k5v9l/ (accessed [date]).
This address stays the same, but the page is rebuilt with each monthly edition, so the citation names the edition it shows. Every edition's data is kept in the facts store.
Source: datausesregister_september2026.xlsx, September 2026 edition of the NHS England Data Uses Register. Search that workbook for DARS-NIC-656839-K5V9L to see the original rows.