The impact of COVID-19 on surgical care and outcomes in England (COVID-19 Surgical Observatory) - project 2

In term In term in the September 2026 edition: the latest version runs to 19 December 2026.

Reference: DARS-NIC-400985-V3D1C
Current version: v2.3
Term of current version: 6 December 2024 to 19 December 2026
Start date: 20 December 2020
Data controller: Sole Data Controller
Commercial purposes: No
Sublicensing: No
Files released to date: 59

Why the data was released

Objective for processing

Barts Health NHS Trust requested Hospital Episode Statistics (HES) data, Emergency Care Data Set (ECDS), Civil Registration Deaths data, COVID-19 Hospitalisation in England Surveillance System (CHESS) data, and COVID-19 Second Generation Surveillance System (SGSS) data. The data have been used to quantify the risk of mortality and morbidity associated with COVID-19 among tens of thousands of NHS surgical patients, delays to surgical care. The data will also quantify the risk of mortality and morbidity associated with delays to surgical care, cancellations of surgical care, and the effect of geographical location, ethnicity, and socioeconomic deprivation. We will assess excess population mortality attributable to COVID-19 among patients with disease able to be treated by surgery, including both direct surgical deaths and indirect deaths, such as those due to cancelled procedures or delayed presentation/diagnosis due to COVID-19. Barts Health NHS Trust are requesting data access beyond 2020-2021 because our initial analyses only examined the first wave of the pandemic and have not captured the subsequent burden of morbidity and mortality, in particular resulting from on-going delays to surgical care.

Emerging data suggests that surgical patients with perioperative SARS-CoV-2 infection, identified either before or after surgery, are at very high risk of pulmonary complications (50%) and death (24%). This is more than 20 times the usual 1% risk of postoperative mortality. The largest study of surgical patients with COVID-19 comprised 1128 patients from 235 hospitals in 24 countries. However, this represents only 484 patients from the UK, so the findings may not be generalisable to NHS patients. In addition, these data were collected at the height of the pandemic and only report outcomes of surgical patients with COVID-19, so they lack reliable (COVID-19 negative) comparator. To protect patients, strict infection control procedures have been, adopted in NHS hospitals, which has severely disrupted surgical throughput. This may cause unintended harm by delaying urgent surgery, including cancer treatment.

The requested data will be used to report the true risk of surgery with COVID-19 and prevent avoidable harm by providing data for policymakers and health leaders to plan the NHS strategy for a dynamic recovery of surgical services. It will also allow policymakers to balance the excess mortality associated with acquiring COVID-19 during surgical admissions, against the excess mortality due to delays in the provision of surgical treatment.

Cohort: Each patient will enter the cohort on their first date of OP/A&E/APC meeting criteria. All subsequent OP/A&E/ECDS/APC data for each of those patients are needed to allow longitudinal follow-up. Linkage to civil registration death data is required for date of death estimation.

The study has two core aims:

1. To describe the incidence and outcomes of COVID-19 amongst patients undergoing surgery.

2. To describe patient characteristics, excess mortality, and other important patient outcomes, amongst patients living with diseases able to be treated by surgery.

NOTE: The study team comprises of substantial employees from Barts Health NHS Trust and Queen Mary University of London.

For aim one, the study team will divide the cohort into two groups:

• COVID-surgery cohort (those undergoing surgery between 1st January 2020 to 31st December 2024).

• A historical comparator cohort (those undergoing surgery between 1st April 2015 and 31st December 2020).

This will allow the study team to:

• Quantify the 30-day and 90-day postoperative mortality associated with COVID-19.

• Investigate the influence of ethnicity, socioeconomic deprivation, sex, and age on 30-day postoperative mortality.

• Map regional variation in 30-day and 90-day postoperative mortality.

For aim two, the study team will divide the cohort into two groups:

• COVID-outpatients cohort (those attending surgical outpatient clinics or attending A&E with a surgical condition between 1st June 2019 and 31st December 2024).

• A historical comparator cohort of patients attending surgical outpatient clinics or attending A&E with a surgical condition between 1st April 2015 and 30th June 2019.

This will allow the study team to:

• Estimate the deficit in procedures performed amongst those presenting to surgical outpatient clinics and A&E, stratified by primary diagnosis, speciality, and age, compared to the historical comparator cohort.

• Determine the rate of death amongst those presenting to surgical outpatients and A&E, accounting for procedures performed.

Only pseudonymised patient-level data will be used. The following datasets are required for the aims of the project:

• HES Outpatients (OP)

OP data for all patients attending a surgical clinic between 1st June 2019 and 31st December 2024 and 1st April 2015 and 30th June 2019 is being requested. OP data will help capture ‘untreated disease able to be treated by surgery’ and measure the number of additional deaths indirectly caused through delaying surgery. To minimise the data requested, the study team have identified the surgical outpatient clinics that data is needed from.

• HES Admitted Patient Care (APC)

APC data for all patients undergoing surgery between 1st January 2020 and 31st December 2024 and 1st April 2015 and 31st December 2020 is being requested to help understand the risk of death among patients associated with COVID-19.

• Emergency Care Data Set (ECDS) / Accident and Emergency (A&E)

ECDS data for all patients attending A&E between 1st May 2020 and 31st December 2020 is being requested. A&E data for all patients attending A&E between 1st June 2019 and 31st December 2020 and 1st April 2015 and 30th June 2019 is being requested. This will help to further capture ‘untreated disease able to be treated by surgery’, as there may be patients who present to A&E with a disease that they would normally have surgery for, but are instead sent home due to the given hospital situation. ECDS is being requested along with A&E data as ECDS replaced A&E data in May 2020 as the primary reporting structure for emergency care data.

• Civil Registration Deaths

The latest available Civil Registration Deaths data and linkage to HES data will allow quantification of postoperative mortality and determine the rate of death among those presenting to surgical outpatients and A&E.

• COVID-19 Hospitalisation in England Surveillance System (CHESS)

The latest available CHESS data will be used to capture detailed hospital admissions data in patients requiring hospitalisation due to COVID-19 infection. Patients that are awaiting surgery are at high risk of severe COVID-19 due to both their advanced age and the burden of chronic disease.

• COVID-19 Second Generation Surveillance System (SGSS)

The latest available SGSS data is required for accurate testing data to determine if patients awaiting surgery have tested positive for COVID-19, which will likely impact whether the patient undergoes surgery. Patients that are awaiting surgery are at high risk of severe COVID-19 due to their advanced age and burden of chronic disease.

The HES OP, APC, ECDS and A&E data will be used for both cohort selection and subsequent data set creation.

This project is the second of two data applications to NHS England as part of the ‘COVID-19 Surgical Observatory’ study. The principal aim of the overall study is to describe the ongoing impact of COVID-19 on NHS surgical services. The study is divided into three projects, each using routinely collected hospital episode data and civil registration data from England. The first data application (“DARS-NIC-375669-J7M7F-v0”) will look to understand the recovery of NHS surgery after COVID-19 by accessing the NHS England Data Access Environment. This data application is focussed on achieving the other two aims as described in this application.

Barts Health NHS Trust will be the data controller and also process the data at Queen Mary's, Queen Mary University of London will be the data processor. All analyses will be carried out by substantive employees of the data processors. If any employees of the data processors are found to not follow the rules of the agreement, they will face serious consequences i.e. termination of contract. The project has received funding from Barts Charity, apart from this, no other organisations or funders are involved.

All outputs will be aggregated in line with NHS England guidance and standard statistical disclosure methods. The findings of the project will support decision making at a national, regional, and local level across England, influencing the teams that plan care across the NHS. Only summary/aggregated level data with small numbers suppressed in line with the HES Analysis Guide will be included in the outputs and publications.

No data will be used for commercial purposes and only aggregated data will be provided to third parties (e.g. in preparing reports for publication).

The lawful basis for processing personal data under the UK 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.

Processing activities

Substantive employees of Barts Health NHS Trust and Queen Mary University of London will take part in the processing of the data. There will be no flow of data into NHS England. The linkage to civil registration death data will be performed by NHS England. The data will be held in the Pragmatic Clinical Trials Unit (PCTU), Queen Mary University of London data safe haven. All data storage, processing and analysis will take place within the Queen Mary University of London PCTU data safe haven.

The core data set will include all APC, ECDS, A&E and OP episodes of care from the dates requested, and date of death from civil registration death data. This dataset will be used for both cohort selection and subsequent data set creation. CHESS and SGSS data will provide detailed hospital admissions data and accurate testing data required for the research aims. Pseudonymised record level data will be transferred into the Data Safe Haven at the PCTU, Queen Mary University of London by the data manager. The data will be held and analysed in the secure environment (PCTU Safe Haven) which is accessed remotely using two factor authentications.

The study cohort will be derived from the core data set to be analysed in line with aim 1 and 2 of the project.

For aim 1, a cohort of all patients undergoing surgery in the UK between 1st January 2020 and 31st December 2024 will be created, with a historical comparator cohort of all patients undergoing surgery in the UK between 1st April 2015 and 31st December 2020. SARS-CoV-2 infection will be identified using ICD10 coding, and the incidence of SARS-CoV-2 infection as a number with a proportion will be reported. Regional variation in the incidence of SARS-CoV-2 infection among surgical patients and associated mortality by NHS regions will be mapped and presented using a heat map. Sex, age, ethnicity, and socioeconomic deprivation will be reported for the full cohort.

For aim 2, the one-year mortality of patients with disease able to be treated by surgery, identified by clinic attendance and OPCS4 codes for surgery, after 1st January 2020 will be compared to a historical reference cohort. The number (and proportion) of patients in each cohort that (a) undergo surgery (b) do not undergo surgery, and the risk of mortality associated with each will be reported, as well as other important patient outcomes and characteristics. All deaths reported to national registers for ICD10 codes associated with disease able to be treated by surgery will be screened to capture patients with disease able to be treated by surgery who did not attend an outpatient clinic. The excess population mortality attributable to COVID-19 among patients with disease able to be treated by surgery will be estimated, including both direct surgical deaths and indirect deaths, due to COVID-19.

During the pandemic, some patients who would normally be admitted via the emergency department and go on to have surgery, may not have had surgery. To reliably identify emergency department diagnoses associated with subsequent surgical treatment, emergency department diagnostic codes for patients undergoing surgery (defined by the provided OPCS code list "opcs_grouping") in HES APC between 1st January 2015 - 31st December 2019 who were admitted via the emergency department will be used. The steps to do this are as follows:

Step 1: Find all patient records undergoing surgery in HES APC between 1st January 2015 and 31st December 2019 by filtering against OPCS code list.

Step 2: Restrict to those admitted via A&E.

Step 3: Aggregate all emergency department codes recorded for these patients.

Step 4: Use those codes with a frequency of >1% as a list of 'emergency department surgical diagnoses’.

Step 5: This is the third criteria on which a patient may enter the cohort (i.e. presence of >=1 emergency department surgical diagnoses').

The generated outputs will be aggregated data that is reviewed by the data manager to ensure it meets NHS England statistical disclosure control, and there will be no attempts to identify individuals from the data. All levels of processing will take place within the PCTU Data Safe Haven.

Data will only be accessed and processed by substantive employees of Barts Health NHS Trust and Queen Mary University of London. All data will be stored at Queen Mary University of London only. Access to the data is controlled by two factor authentications with user specific identification and auditing. The data will not be accessed or processed by any other third parties not mentioned in this agreement. To mitigate the risk of re-identification, only pseudonymised data will be used.

All researchers hold training in information governance for purposes of research.

Expected output

Only aggregated data with small numbers suppressed in line with the HES Analysis Guide will be presented in the outputs. Development of new tools or algorithms from this work is not anticipated.

The overarching aim of this project is to generate national data to inform evidence-based health policymaking by understanding the continuing impact of the COVID-19 pandemic on surgery and surgical patients in England. This will help with understanding: (1) which patients have surgery and which are waiting for an operation (including the surgical backlog), (2) the risk of dying or developing a complication after surgery, (3) the influence of factors like ethnicity, sex, age, socio-economic deprivation, geography and chronic conditions on access to surgery and outcomes after surgery, (4) direct surgical deaths and indirect deaths, such as those due to delayed treatment or diagnosis and the impact of vaccination, (5) resource requirements associated with ongoing and future surgical activity, to support health policy planning.

The main target of the dissemination activities will be healthcare policymakers, clinicians, patients, and their carers. The expected output will be a series of reports, published in high-impact journals, which are expected to directly influence health policy. The dissemination strategy includes: harnessing the organisations substantial global social media network; press releases via print and online media; circulation through the medical Royal Colleges; and through direct contacts at NHS England and the Department of Health.

Plain English summaries will be produced for patients and the public to understand the results of the analyses. The team will also disseminate the findings through mainstream media (e.g. BBC news, Channel 4 News, Times Newspaper etc.), social media (e.g. Twitter) and on the Queen Mary University London website (https://www.qmul.ac.uk/ccpmg/).

Existing outputs from this project have described the substantial reduction in surgical activity during the first part of the pandemic[1] and the increased risk of mortality for patients with COVID-19 that undergo surgery[2], which have impacted national health policy. Analyses examining the impact of the pandemic on dental surgery, surgery for children and the predicted lifetime risk of requiring surgery are on-going. The team aim to publish outputs in open access formats, to facilitate access by policymakers, clinicians, and members of the public. The data from NHS England will not be used for any other purpose other than that outlined in this agreement.

Barts Health NHS Trust are requesting (1) an extension to the expiry date of the Data Sharing Agreement to allow us to complete analyses currently in progress using data currently held and (2) access to additional years of data (to present day) to facilitate contemporaneous analyses of the surgical population.

Note. The original application included a project with analogous analysis of NHS data from Wales using the SAIL Databank. This project has been completed and published. All current and future analyses will only use data from NHS England.

[1] https://www.bjanaesthesia.org/article/S0007-0912(21)00273-7/fulltext

[2] https://www.bjanaesthesia.org/article/S0007-0912(21)00312-3/fulltext

Expected measurable benefits

During the early phases of the pandemic response, clinicians reported that infection control procedures designed to protect patients and staff in hospitals led to dramatic, but unquantified, reductions in surgical throughput. Early plans for the delivery of surgery did not balance the risk of complications due to COVID-19, against accurate data describing the risk of harm due to delays in treatment for surgical patients. The analyses of the data identified a 33% reduction surgical activity during the initial part of the COVID-19 response and a strong relationship between COVID-19 infection and increased risk of mortality among surgical patients, which informed guidelines for surgical and perioperative care.

Since the start of the pandemic there has been a continued and worsening backlog of scheduled NHS appointments. However, the current magnitude of the deficit of surgical activity and the impact on NHS patients is not clear. It is in the public’s interest that surgical and perioperative care is planned appropriately, and that the potential harms of the reduced provision of surgical care are fully characterised.

The findings of this project will be published and publicised widely. The intended audience is those who provide and plan care within the NHS, including clinicians, managers, and policymakers at all levels as well as specialist groups such as the BMJ Technology Assessment Group (TAG). The outputs will be produced by Barts Health and will provide detailed data analysis to facilitate active planning of surgical services in a way that is not currently possible, since there is no routine national reporting of surgical activity or outcomes. The team aim to submit the first report for publication within 12 months after receiving the data.

The study team aim to describe regional variations in care will facilitate nationwide learning. The geographical modelling will support local healthcare leaders in understanding how their regional challenges differ to other areas, which will be vitally important in the event of future regional lockdowns. The analyses of diversity characteristics like ethnicity, age and socioeconomic deprivation will support NHS leaders in improving surgical care for patients at the highest risk of complications after surgery and COVID-19.

The benefits can be measured once the findings are published and vital statistics are provided to NHS leaders. This is particularly important as the pandemic recovery moves into new phases, and decisions related to care in the NHS will be continuingly reassessed. The outputs and publications produced will influence the decision-making process as the circumstances change, and this will be seen implemented within the NHS services.

This will benefit societal health and wellbeing by minimising the impact of delayed or cancelled procedures in the recovery from COVID-19 on the delivery of surgical treatments. In the event of future outbreaks of COVID-19, or during the winter influenza season, the data will ensure NHS leaders can maximise surgical activity across NHS regions and minimise the detrimental impact of delayed surgery on the health of nation.

Lay summaries of the findings will be developed in collaboration with the patient and public involvement representatives and Barts Health NHS Trust patient volunteers. Publication in peer reviewed journals will support learning in other countries dealing with disruption to surgery as a result of COVID-19. Professional bodies e.g. Royal College of Anaesthetists/ The Royal College of Surgeons of England will review and integrate the findings within their reports which will be disseminated to care providers across England.

Benefits reported so far

[1] https://www.bjanaesthesia.org/article/S0007-0912(21)00273-7/fulltext

[2] https://www.bjanaesthesia.org/article/S0007-0912(21)00312-3/fulltext

Datasets on the current version

Legal basis for provision: Health and Social Care Act 2012 – s261(2)(a)

Datasets approved under DARS-NIC-400985-V3D1C-v2.3
Dataset	Type of data	Sensitivity	Frequency	Confidential data
Civil Registrations of Death	Anonymised - ICO Code Compliant	Sensitive	Ongoing	Does not include the flow of confidential data
COVID-19 Hospitalization in England Surveillance System	Anonymised - ICO Code Compliant	Non-Sensitive	One-Off	Does not include the flow of confidential data
COVID-19 SGSS First Positives (Second Generation Surveillance System)	Anonymised - ICO Code Compliant	Sensitive	One-Off	Does not include the flow of confidential data
Emergency Care Data Set (ECDS)	Anonymised - ICO Code Compliant	Non-Sensitive	One-Off	Does not include the flow of confidential data
HES:Civil Registration (Deaths) bridge	Anonymised - ICO Code Compliant	Non-Sensitive	One-Off	Does not include the flow of confidential data
Hospital Episode Statistics Accident and Emergency (HES A and E)	Anonymised - ICO Code Compliant	Non-Sensitive	One-Off	Does not include the flow of confidential data
Hospital Episode Statistics Admitted Patient Care (HES APC)	Anonymised - ICO Code Compliant	Non-Sensitive	Ongoing	Does not include the flow of confidential data
Hospital Episode Statistics Outpatients (HES OP)	Anonymised - ICO Code Compliant	Non-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.

Patient opt-outs were not applied to any of the 59 files released under this agreement, across every version. About opt-outs

Files released against version 2.3 of this agreement, summarised by dataset.

Files released under DARS-NIC-400985-V3D1C-v2.3
Dataset	Files	First released	Last released	Opt-outs applied
Hospital Episode Statistics Outpatients (HES OP)	17	March 2026	March 2026	No
Hospital Episode Statistics Admitted Patient Care (HES APC)	10	March 2026	March 2026	No
Hospital Episode Statistics Accident and Emergency (HES A and E)	5	March 2026	March 2026	No
Civil Registrations of Death	2	March 2026	March 2026	No
COVID-19 SGSS First Positives (Second Generation Surveillance System)	1	March 2026	March 2026	No
Emergency Care Data Set (ECDS)	1	March 2026	March 2026	No

Version history

The register lists each renewal of this agreement as a separate row. This site has 3 versions.

DARS-NIC-400985-V3D1C-v2.3 6 December 2024 to 19 December 2026

Title: The impact of COVID-19 on surgical care and outcomes in England (COVID-19 Surgical Observatory) - project 2
Commercial: No
Sublicensing: No
Datasets: 8
Files released: 36

Datasets: Civil Registrations of Death; COVID-19 Hospitalization in England Surveillance System; COVID-19 SGSS First Positives (Second Generation Surveillance System); Emergency Care Data Set (ECDS); HES:Civil Registration (Deaths) bridge; Hospital Episode Statistics Accident and Emergency (HES A and E); Hospital Episode Statistics Admitted Patient Care (HES APC); Hospital Episode Statistics Outpatients (HES OP)

What changed from DARS-NIC-400985-V3D1C-v1.7

Text removed is ~~struck through~~; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Fields changed from DARS-NIC-400985-V3D1C-v1.7
Field	Was	Became
Start date	~~2024-05-03~~	2024-12-06

Processing activities

[14 paragraphs unchanged] All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).

Unchanged: Objective for processing, Expected output, Expected measurable benefits, Benefits reported.

DARS-NIC-400985-V3D1C-v1.7 3 May 2024 to 19 December 2026

Title: The impact of COVID-19 on surgical care and outcomes in England (COVID-19 Surgical Observatory) - project 2
Commercial: No
Sublicensing: No
Datasets: 8
Files released: 0

What changed from DARS-NIC-400985-V3D1C-v0.17

Text removed is ~~struck through~~; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Fields changed from DARS-NIC-400985-V3D1C-v0.17
Field	Was	Became
Start date	~~2020-12-20~~	2024-05-03
End date	~~2023-12-19~~	2026-12-19
COVID-19 Hospitalization in England Surveillance System: legal basis	~~Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; Health and Social Care Act 2012 – s261(2)(b)(ii)~~	Health and Social Care Act 2012 – s261(2)(a)
COVID-19 SGSS First Positives (Second Generation Surveillance System): legal basis	~~Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; Health and Social Care Act 2012 – s261(2)(b)(ii)~~	Health and Social Care Act 2012 – s261(2)(a)
COVID-19 SGSS First Positives (Second Generation Surveillance System): sensitivity	~~Non-Sensitive~~	Sensitive
Civil Registrations of Death: legal basis	~~Health and Social Care Act 2012 - s261 - 'Other dissemination of information'~~	Health and Social Care Act 2012 – s261(2)(a)
Emergency Care Data Set (ECDS): legal basis	~~Health and Social Care Act 2012 - s261 - 'Other dissemination of information'~~	Health and Social Care Act 2012 – s261(2)(a)
HES:Civil Registration (Deaths) bridge: legal basis	~~Health and Social Care Act 2012 - s261 - 'Other dissemination of information'~~	Health and Social Care Act 2012 – s261(2)(a)
Hospital Episode Statistics Accident and Emergency (HES A and E): legal basis	~~Health and Social Care Act 2012 - s261 - 'Other dissemination of information'~~	Health and Social Care Act 2012 – s261(2)(a)
Hospital Episode Statistics Admitted Patient Care (HES APC): legal basis	~~Health and Social Care Act 2012 - s261 - 'Other dissemination of information'~~	Health and Social Care Act 2012 – s261(2)(a)
Hospital Episode Statistics Outpatients (HES OP): legal basis	~~Health and Social Care Act 2012 - s261 - 'Other dissemination of information'~~	Health and Social Care Act 2012 – s261(2)(a)

Objective for processing

Barts Health NHS Trust ~~are requesting~~ requested Hospital Episode Statistics (HES) data, Emergency Care Data Set (ECDS), Civil Registration [8 words unchanged] (CHESS) data, and COVID-19 Second Generation Surveillance System (SGSS) data. The data ~~is requested~~ have been used to quantify the risk of mortality and morbidity associated with ~~SARS-CoV-2 infection~~ COVID-19 among tens of thousands of NHS ~~patients that have already had surgery,~~ surgical patients, delays to surgical care. The data will also quantify the risk of mortality and morbidity associated with delays to surgical care, cancellations of surgical care, and the effect of geographical location, ethnicity, and socioeconomic deprivation. ~~The data~~ We will ~~also quantify the~~ assess excess population mortality attributable to COVID-19 among patients with disease able to [13 words unchanged] as those due to cancelled procedures or delayed presentation/diagnosis due to COVID-19. Barts Health NHS Trust are requesting data access beyond 2020-2021 because our initial analyses only examined the first wave of the pandemic and have not captured the subsequent burden of morbidity and mortality, in particular resulting from on-going delays to surgical care. [5 paragraphs unchanged] 2. To ~~estimate~~ describe patient characteristics, excess ~~mortality~~ mortality, and other important patient outcomes, amongst patients living with diseases able to be treated by surgery. [2 paragraphs unchanged] • COVID-surgery cohort (those undergoing surgery between 1st January 2020 to 31st ~~August 2020).~~ December 2024). [6 paragraphs unchanged] • COVID-outpatients cohort (those attending surgical outpatient clinics or attending A&E with a surgical condition between 1st June 2019 and 31st December ~~2020).~~ 2024). [6 paragraphs unchanged] OP data for all patients attending a surgical clinic between 1st June 2019 and 31st December ~~2020~~ 2024 and 1st April 2015 and 30th June 2019 is being requested. OP [31 words unchanged] team have identified the surgical outpatient clinics that data is needed from. [1 paragraph unchanged] APC data for all patients undergoing surgery between 1st January 2020 and 31st ~~August 2020~~ December 2024 and 1st April 2015 and 31st December 2020 is being requested to help understand the risk of death among patients associated with COVID-19. [3 paragraphs unchanged] The latest available Civil Registration Deaths data and linkage ~~using the HES:Civil Registration (Deaths) bridge~~ to HES data will allow quantification of postoperative mortality and determine the rate of death among those presenting to surgical outpatients and A&E. [5 paragraphs unchanged] This project is the second of two data applications to NHS ~~Digital~~ England as part of the ‘COVID-19 Surgical Observatory’ study. The principal aim of [43 words unchanged] understand the recovery of NHS surgery after COVID-19 by accessing the NHS ~~Digital~~ England Data Access Environment. This data application is focussed on achieving the other two aims as described in this application. [1 paragraph unchanged] Data will only be accessed by the Data Controller and Data Processor [18 words unchanged] Haven at the Pragmatic Clinical Trials Unit, Queen Mary University of London. ~~The Data Safe Haven (ODS code: 8HN69-PCTU) achieved ‘Standards Met’ on the DSP Toolkit (17th March 2020).~~ All outputs will be aggregated in line with NHS ~~Digital~~ England guidance and standard statistical disclosure methods. The findings of the project will [32 words unchanged] the HES Analysis Guide will be included in the outputs and publications. [1 paragraph unchanged] The legal basis for processing personal data is performance of a task by a public organisation in the public interest (Article 6(1)e of the Data Protection Act 2018) and for processing special category data is Article 9(2)j of the same, as the purpose is scientific research. The lawful basis for processing personal data under the UK 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.

Processing activities

Substantive employees of Barts Health NHS Trust and Queen Mary University of [7 words unchanged] of the data. There will be no flow of data into NHS ~~Digital.~~ England. The linkage to civil registration death data will be performed by NHS ~~Digital.~~ England. The data will be held in the Pragmatic Clinical Trials Unit (PCTU), [16 words unchanged] place within the Queen Mary University of London PCTU data safe haven. The core data set will include all APC, ECDS, A&E and OP [83 words unchanged] environment (PCTU Safe Haven) which is accessed remotely using two factor authentications. ~~The Safe Haven (ODS code: 8HN69-PCTU) meets existing information security requirements and achieved ‘Standards Met’ on the DSP Toolkit (17th March 2020).~~ [1 paragraph unchanged] For aim 1, a cohort of all patients undergoing surgery in the UK between 1st January 2020 and 31st ~~August 2020~~ December 2024 will be created, with a historical comparator cohort of all patients undergoing [62 words unchanged] age, ethnicity, and socioeconomic deprivation will be reported for the full cohort. For aim 2, the one-year mortality of patients with disease able to be treated by surgery, identified by clinic ~~attendance, during the COVID-19 pandemic~~ attendance and OPCS4 codes for surgery, after 1st January 2020 will be compared to a historical reference cohort. The number (and proportion) [12 words unchanged] undergo surgery, and the risk of mortality associated with each will be ~~reported.~~ reported, as well as other important patient outcomes and characteristics. All deaths reported to national registers for ICD10 codes associated with disease [46 words unchanged] estimated, including both direct surgical deaths and indirect deaths, due to COVID-19. [6 paragraphs unchanged] The generated outputs will be aggregated data that is reviewed by the data manager to ensure it meets NHS ~~Digital~~ England statistical disclosure control, and there will be no attempts to identify individuals from the data. All levels of processing will take place within the PCTU Data Safe Haven. [3 paragraphs unchanged]

Expected output

[1 paragraph unchanged] The overarching aim of this project is to generate national data to inform evidence-based health policymaking by understanding ~~what~~ the continuing impact of the COVID-19 pandemic on surgery ~~occurred during the pandemic, the risk of death among~~ and surgical patients ~~associated with COVID-19 and the total mortality across England among patients with disease able to be treated by surgery.~~ in England. This will help with understanding: (1) which patients ~~had~~ have surgery and ~~who is still~~ which are waiting for an ~~operation,~~ operation (including the surgical backlog), (2) the risk of dying or developing a complication after ~~an operation during the pandemic,~~ surgery, (3) the influence of factors like ~~ethnicity~~ ethnicity, sex, age, socio-economic deprivation, geography and ~~gender~~ chronic conditions on ~~survival~~ access to surgery and outcomes after ~~surgery during this time, and~~ surgery, (4) direct surgical deaths and indirect deaths, such as those due to delayed treatment or ~~diagnosis.~~ diagnosis and the impact of vaccination, (5) resource requirements associated with ongoing and future surgical activity, to support health policy planning. Colleagues in Wales plan to perform analogous analyses to provide wider context to this work. Their analyses will not include or be based on the record level data or results from this study. The data for each study will be held separately. The research findings from each respective study will be published together in a single paper to increase the generalisability and impact of the study. The main target of the dissemination activities will be healthcare policymakers, clinicians, patients, and their carers. The expected output will be a series of reports, published in high-impact journals, which are expected to directly influence health policy. The dissemination strategy includes: harnessing the organisations substantial global social media network; press releases via print and online media; circulation through the medical Royal Colleges; and through direct contacts at NHS England and the Department of Health. The main target of the dissemination activities will be healthcare policymakers, clinicians, patients, and their carers. The expected output will be a series of reports, published in high-impact journals, which are expected to directly influence health policy. The dissemination strategy includes: harnessing a global social media network set up by collaborators in the CovidSurg research collaborative, which has a presence in over 100 countries; press releases via print and online media; circulation through the medical Royal Colleges; and through direct contacts at NHS England and the Department of Health. Plain English summaries will be produced for patients and the public to understand the results of the analyses. The team will also disseminate the findings through mainstream media (e.g. BBC news, Channel 4 News, Times Newspaper etc.), social media (e.g. Twitter) and on the Queen Mary University London website (https://www.qmul.ac.uk/ccpmg/). A plain English summary will also be produced for patients and the public to understand the postoperative mortality associated with COVID-19. Barts Health will also disseminate the aggregated findings through mainstream media (e.g. BBC news, Channel 4 News, Times Newspaper etc.) and social media (e.g. Twitter). A website will be established summarising the findings. Existing outputs from this project have described the substantial reduction in surgical activity during the first part of the pandemic[1] and the increased risk of mortality for patients with COVID-19 that undergo surgery[2], which have impacted national health policy. Analyses examining the impact of the pandemic on dental surgery, surgery for children and the predicted lifetime risk of requiring surgery are on-going. The team aim to publish outputs in open access formats, to facilitate access by policymakers, clinicians, and members of the public. The data from NHS England will not be used for any other purpose other than that outlined in this agreement. The analysis of the initial pandemic period (1st January – 31st August 2020) will be submitted for publication in a high impact journal by summer 2021. This will be followed by the analysis of excess mortality from disease able to be treated by surgery later in 2021. All publications will be open access, and can be accessed by policymakers, clinicians, and members of the public. The data from NHS Digital will not be used for any other purpose other than that outlined in this agreement. Barts Health NHS Trust are requesting (1) an extension to the expiry date of the Data Sharing Agreement to allow us to complete analyses currently in progress using data currently held and (2) access to additional years of data (to present day) to facilitate contemporaneous analyses of the surgical population. Note. The original application included a project with analogous analysis of NHS data from Wales using the SAIL Databank. This project has been completed and published. All current and future analyses will only use data from NHS England. [1] https://www.bjanaesthesia.org/article/S0007-0912(21)00273-7/fulltext [2] https://www.bjanaesthesia.org/article/S0007-0912(21)00312-3/fulltext

Expected measurable benefits

~~Clinicians report~~ During the early phases of the pandemic response, clinicians reported that infection control procedures designed to protect patients and staff in hospitals ~~have~~ led to ~~a dramatic reduction~~ dramatic, but unquantified, reductions in surgical throughput. ~~So far,~~ Early plans for the delivery of surgery ~~have~~ did not ~~balanced~~ balance the risk of complications due to COVID-19, against accurate data describing the risk of harm due to delays in treatment for surgical patients. ~~It is in~~ The analyses of the ~~public’s interest that care is planned appropriately,~~ data identified a 33% reduction surgical activity during the initial part of the COVID-19 response and a ~~balance is struck~~ strong relationship between ~~preventing harm through~~ COVID-19 infection ~~control~~ and ~~treating disease through surgery.~~ increased risk of mortality among surgical patients, which informed guidelines for surgical and perioperative care. The findings of this project will be published and publicised widely. The intended audience is those who provide and plan care within the NHS, including clinicians, managers, and policymakers at all levels as well as specialist groups such as the BMJ Technology Assessment Group (TAG). The outputs will be produced by Barts Health and will provide detailed data analysis to facilitate active planning of surgical services in a way that is not currently possible, since there is no routine national reporting of surgical activity or outcomes. Since the start of the pandemic there has been a continued and worsening backlog of scheduled NHS appointments. However, the current magnitude of the deficit of surgical activity and the impact on NHS patients is not clear. It is in the public’s interest that surgical and perioperative care is planned appropriately, and that the potential harms of the reduced provision of surgical care are fully characterised. Reporting the regional variations in care will facilitate UK-wide learning. The geographical modelling will support local healthcare leaders in understanding how their regional challenges differ to other areas, which will be vitally important in the event of regional lockdowns. The analyses of ethnicity and socioeconomic deprivation will support NHS leaders in improving surgical care for patients at the highest risk of complications after surgery and COVID-19. The findings of this project will be published and publicised widely. The intended audience is those who provide and plan care within the NHS, including clinicians, managers, and policymakers at all levels as well as specialist groups such as the BMJ Technology Assessment Group (TAG). The outputs will be produced by Barts Health and will provide detailed data analysis to facilitate active planning of surgical services in a way that is not currently possible, since there is no routine national reporting of surgical activity or outcomes. The team aim to submit the first report for publication within 12 months after receiving the data. The benefits can be measured once the findings are published and vital statistics are provided to NHS leaders. This is particularly important as the pandemic moves into new phases, and decisions related to care in the NHS will be continuingly reassessed. The outputs and publications produced will influence the decision-making process as the circumstances change, and this will be seen implemented within the NHS services. The study team aim to describe regional variations in care will facilitate nationwide learning. The geographical modelling will support local healthcare leaders in understanding how their regional challenges differ to other areas, which will be vitally important in the event of future regional lockdowns. The analyses of diversity characteristics like ethnicity, age and socioeconomic deprivation will support NHS leaders in improving surgical care for patients at the highest risk of complications after surgery and COVID-19. This will benefit societal health and wellbeing by minimising the impact of infection control measures on the delivery of surgical treatments. In the event of future peaks of COVID-19, or during the winter influenza season, the data will ensure NHS leaders can maximise surgical activity across NHS regions and minimise the detrimental impact of COVID-19 on the health of nation. The benefits can be measured once the findings are published and vital statistics are provided to NHS leaders. This is particularly important as the pandemic recovery moves into new phases, and decisions related to care in the NHS will be continuingly reassessed. The outputs and publications produced will influence the decision-making process as the circumstances change, and this will be seen implemented within the NHS services. Lay summaries of the findings will be developed in collaboration with patients, as the ongoing disruption to care is of concern to those waiting for care. Publication in peer reviewed journals will support resumption of care in other countries dealing with the COVID-19 pandemic and the associated disruption. Professional bodies e.g. Royal College of Anaesthetists/ The Royal College of Surgeons of England will review and integrate the findings within their reports which will be disseminated to care providers across England. This will benefit societal health and wellbeing by minimising the impact of delayed or cancelled procedures in the recovery from COVID-19 on the delivery of surgical treatments. In the event of future outbreaks of COVID-19, or during the winter influenza season, the data will ensure NHS leaders can maximise surgical activity across NHS regions and minimise the detrimental impact of delayed surgery on the health of nation. ~~The first report is expected within two months of receiving data access, with sequential reports following from this. This will be achieved for cost 6 months from data access.~~ Lay summaries of the findings will be developed in collaboration with the patient and public involvement representatives and Barts Health NHS Trust patient volunteers. Publication in peer reviewed journals will support learning in other countries dealing with disruption to surgery as a result of COVID-19. Professional bodies e.g. Royal College of Anaesthetists/ The Royal College of Surgeons of England will review and integrate the findings within their reports which will be disseminated to care providers across England.

Benefits reported

~~Yielded Benefits is not a requirement for new applications.~~ Existing outputs from this project have described the substantial reduction in surgical activity during the first part of the pandemic[1] and the increased risk of mortality for patients with COVID-19 that undergo surgery[2], which have informed national health policy. Analyses examining the impact of the pandemic on dental surgery, surgery for children and the predicted lifetime risk of requiring surgery are on-going. [1] https://www.bjanaesthesia.org/article/S0007-0912(21)00273-7/fulltext [2] https://www.bjanaesthesia.org/article/S0007-0912(21)00312-3/fulltext

Objective for processing

The study has two core aims:

1. To describe the incidence and outcomes of COVID-19 amongst patients undergoing surgery.

2. To describe patient characteristics, excess mortality, and other important patient outcomes, amongst patients living with diseases able to be treated by surgery.

NOTE: The study team comprises of substantial employees from Barts Health NHS Trust and Queen Mary University of London.

For aim one, the study team will divide the cohort into two groups:

• COVID-surgery cohort (those undergoing surgery between 1st January 2020 to 31st December 2024).

• A historical comparator cohort (those undergoing surgery between 1st April 2015 and 31st December 2020).

This will allow the study team to:

• Quantify the 30-day and 90-day postoperative mortality associated with COVID-19.

• Investigate the influence of ethnicity, socioeconomic deprivation, sex, and age on 30-day postoperative mortality.

• Map regional variation in 30-day and 90-day postoperative mortality.

For aim two, the study team will divide the cohort into two groups:

• COVID-outpatients cohort (those attending surgical outpatient clinics or attending A&E with a surgical condition between 1st June 2019 and 31st December 2024).

• A historical comparator cohort of patients attending surgical outpatient clinics or attending A&E with a surgical condition between 1st April 2015 and 30th June 2019.

This will allow the study team to:

• Determine the rate of death amongst those presenting to surgical outpatients and A&E, accounting for procedures performed.

Only pseudonymised patient-level data will be used. The following datasets are required for the aims of the project:

• HES Outpatients (OP)

• HES Admitted Patient Care (APC)

• Emergency Care Data Set (ECDS) / Accident and Emergency (A&E)

• Civil Registration Deaths

• COVID-19 Hospitalisation in England Surveillance System (CHESS)

• COVID-19 Second Generation Surveillance System (SGSS)

The HES OP, APC, ECDS and A&E data will be used for both cohort selection and subsequent data set creation.

No data will be used for commercial purposes and only aggregated data will be provided to third parties (e.g. in preparing reports for publication).

The lawful basis for processing personal data under the UK 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:

Expected output

Only aggregated data with small numbers suppressed in line with the HES Analysis Guide will be presented in the outputs. Development of new tools or algorithms from this work is not anticipated.

[1] https://www.bjanaesthesia.org/article/S0007-0912(21)00273-7/fulltext

[2] https://www.bjanaesthesia.org/article/S0007-0912(21)00312-3/fulltext

Benefits reported

[1] https://www.bjanaesthesia.org/article/S0007-0912(21)00273-7/fulltext

[2] https://www.bjanaesthesia.org/article/S0007-0912(21)00312-3/fulltext

DARS-NIC-400985-V3D1C-v0.17 20 December 2020 to 19 December 2023

Title: The impact of COVID-19 on surgical care and outcomes in England (COVID-19 Surgical Observatory) - project 2
Commercial: No
Sublicensing: No
Datasets: 8
Files released: 23

Objective for processing

Barts Health NHS Trust are requesting Hospital Episode Statistics (HES) data, Emergency Care Data Set (ECDS), Civil Registration Deaths data, COVID-19 Hospitalisation in England Surveillance System (CHESS) data, and COVID-19 Second Generation Surveillance System (SGSS) data. The data is requested to quantify the risk of mortality associated with SARS-CoV-2 infection among tens of thousands of NHS patients that have already had surgery, and the effect of geographical location, ethnicity, and socioeconomic deprivation. The data will also quantify the excess population mortality attributable to COVID-19 among patients with disease able to be treated by surgery, including both direct surgical deaths and indirect deaths, such as those due to cancelled procedures or delayed presentation/diagnosis due to COVID-19.

The study has two core aims:

1. To describe the incidence and outcomes of COVID-19 amongst patients undergoing surgery.

2. To estimate excess mortality amongst patients living with diseases able to be treated by surgery.

NOTE: The study team comprises of substantial employees from Barts Health NHS Trust and Queen Mary University of London.

For aim one, the study team will divide the cohort into two groups:

• COVID-surgery cohort (those undergoing surgery between 1st January 2020 to 31st August 2020).

• A historical comparator cohort (those undergoing surgery between 1st April 2015 and 31st December 2020).

This will allow the study team to:

• Quantify the 30-day and 90-day postoperative mortality associated with COVID-19.

• Investigate the influence of ethnicity, socioeconomic deprivation, sex, and age on 30-day postoperative mortality.

• Map regional variation in 30-day and 90-day postoperative mortality.

For aim two, the study team will divide the cohort into two groups:

• COVID-outpatients cohort (those attending surgical outpatient clinics or attending A&E with a surgical condition between 1st June 2019 and 31st December 2020).

• A historical comparator cohort of patients attending surgical outpatient clinics or attending A&E with a surgical condition between 1st April 2015 and 30th June 2019.

This will allow the study team to:

• Determine the rate of death amongst those presenting to surgical outpatients and A&E, accounting for procedures performed.

Only pseudonymised patient-level data will be used. The following datasets are required for the aims of the project:

• HES Outpatients (OP)

OP data for all patients attending a surgical clinic between 1st June 2019 and 31st December 2020 and 1st April 2015 and 30th June 2019 is being requested. OP data will help capture ‘untreated disease able to be treated by surgery’ and measure the number of additional deaths indirectly caused through delaying surgery. To minimise the data requested, the study team have identified the surgical outpatient clinics that data is needed from.

• HES Admitted Patient Care (APC)

APC data for all patients undergoing surgery between 1st January 2020 and 31st August 2020 and 1st April 2015 and 31st December 2020 is being requested to help understand the risk of death among patients associated with COVID-19.

• Emergency Care Data Set (ECDS) / Accident and Emergency (A&E)

• Civil Registration Deaths

The latest available Civil Registration Deaths data and linkage using the HES:Civil Registration (Deaths) bridge will allow quantification of postoperative mortality and determine the rate of death among those presenting to surgical outpatients and A&E.

• COVID-19 Hospitalisation in England Surveillance System (CHESS)

• COVID-19 Second Generation Surveillance System (SGSS)

The HES OP, APC, ECDS and A&E data will be used for both cohort selection and subsequent data set creation.

This project is the second of two data applications to NHS Digital as part of the ‘COVID-19 Surgical Observatory’ study. The principal aim of the overall study is to describe the ongoing impact of COVID-19 on NHS surgical services. The study is divided into three projects, each using routinely collected hospital episode data and civil registration data from England. The first data application (“DARS-NIC-375669-J7M7F-v0”) will look to understand the recovery of NHS surgery after COVID-19 by accessing the NHS Digital Data Access Environment. This data application is focussed on achieving the other two aims as described in this application.

Data will only be accessed by the Data Controller and Data Processor and only at the approved locations. The data will be accessed, analysed, and processed within the Data Safe Haven at the Pragmatic Clinical Trials Unit, Queen Mary University of London. The Data Safe Haven (ODS code: 8HN69-PCTU) achieved ‘Standards Met’ on the DSP Toolkit (17th March 2020).

All outputs will be aggregated in line with NHS Digital guidance and standard statistical disclosure methods. The findings of the project will support decision making at a national, regional, and local level across England, influencing the teams that plan care across the NHS. Only summary/aggregated level data with small numbers suppressed in line with the HES Analysis Guide will be included in the outputs and publications.

No data will be used for commercial purposes and only aggregated data will be provided to third parties (e.g. in preparing reports for publication).

The legal basis for processing personal data is performance of a task by a public organisation in the public interest (Article 6(1)e of the Data Protection Act 2018) and for processing special category data is Article 9(2)j of the same, as the purpose is scientific research.

Expected output

Only aggregated data with small numbers suppressed in line with the HES Analysis Guide will be presented in the outputs. Development of new tools or algorithms from this work is not anticipated.

The aim of this project is to generate national data to inform evidence-based health policymaking by understanding what surgery occurred during the pandemic, the risk of death among surgical patients associated with COVID-19 and the total mortality across England among patients with disease able to be treated by surgery. This will help with understanding: (1) which patients had surgery and who is still waiting for an operation, (2) the risk of dying after an operation during the pandemic, (3) the influence of factors like ethnicity and gender on survival after surgery during this time, and (4) direct surgical deaths and indirect deaths, such as those due to delayed treatment or diagnosis.

Colleagues in Wales plan to perform analogous analyses to provide wider context to this work. Their analyses will not include or be based on the record level data or results from this study. The data for each study will be held separately. The research findings from each respective study will be published together in a single paper to increase the generalisability and impact of the study.

The main target of the dissemination activities will be healthcare policymakers, clinicians, patients, and their carers. The expected output will be a series of reports, published in high-impact journals, which are expected to directly influence health policy. The dissemination strategy includes: harnessing a global social media network set up by collaborators in the CovidSurg research collaborative, which has a presence in over 100 countries; press releases via print and online media; circulation through the medical Royal Colleges; and through direct contacts at NHS England and the Department of Health.

A plain English summary will also be produced for patients and the public to understand the postoperative mortality associated with COVID-19. Barts Health will also disseminate the aggregated findings through mainstream media (e.g. BBC news, Channel 4 News, Times Newspaper etc.) and social media (e.g. Twitter). A website will be established summarising the findings.

The analysis of the initial pandemic period (1st January – 31st August 2020) will be submitted for publication in a high impact journal by summer 2021. This will be followed by the analysis of excess mortality from disease able to be treated by surgery later in 2021. All publications will be open access, and can be accessed by policymakers, clinicians, and members of the public. The data from NHS Digital will not be used for any other purpose other than that outlined in this agreement.

Benefits reported

Yielded Benefits is not a requirement for new applications.

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, the earliest of which is July 2021.

July 2021 — already listed in the earliest edition this site holds, so it may be older.
1 version: DARS-NIC-400985-V3D1C-v0.17
December 2022
Register-wide edit DARS-NIC-400985-V3D1C-v0.17 — Datasets: legal basis: “~~s261(1) and~~” taken out. Made to 639 agreements in this edition, so it is reported once, on the changes page, and not counted as an amendment of this agreement.
January 2023
Amended DARS-NIC-400985-V3D1C-v0.17
- Datasets: + COVID-19 SGSS First Positives (Second Generation Surveillance System) · ~~− COVID-19 Second Generation Surveillance System (SGSS)~~
June 2024
1 version added: DARS-NIC-400985-V3D1C-v1.7
February 2025
1 version added: DARS-NIC-400985-V3D1C-v2.3

"Amended in place" means NHS England changed the record without issuing a new version number. The register publishes no changelog for those edits; this site infers them by comparing editions. An edit is attributed to the edition it first appears in, not to the date it was made.

Cite this page

NHS England (2026) Data Uses Register, September 2026 edition, agreement DARS-NIC-400985-V3D1C, “The impact of COVID-19 on surgical care and outcomes in England (COVID-19 Surgical Observatory) - project 2”. Read via NHS Data Access Explorer (unofficial), https://healthdatauses.uk/agreements/dars-nic-400985-v3d1c/ (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-400985-V3D1C to see the original rows.