Good TREs work

Barts Health NHS Trust projects

74 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).


🚩 Barts Health NHS Trust was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. Barts Health NHS Trust may not have compared the two files, but the identifiers are consistent between datasets, and outside of a good TRE NHS Digital can not know what recipients actually do.

The impact of COVID-19 on surgical care and outcomes in England (COVID-19 Surgical Observatory) - project 2 — DARS-NIC-400985-V3D1C

Opt outs honoured: Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (NHS Trust)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2020-12-20 — 2023-12-19 2022.02 — 2022.09.

Access method: One-Off

Data-controller type: BARTS HEALTH NHS TRUST

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. COVID-19 Hospitalization in England Surveillance System
  3. COVID-19 Second Generation Surveillance System
  4. Emergency Care Data Set (ECDS)
  5. HES:Civil Registration (Deaths) bridge
  6. Hospital Episode Statistics Accident and Emergency
  7. Hospital Episode Statistics Admitted Patient Care
  8. Hospital Episode Statistics Outpatients

Objectives:

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.

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 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:
• 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 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)
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 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)
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 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.

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.

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 Benefits:

Clinicians report that infection control procedures designed to protect patients and staff in hospitals have led to a dramatic reduction in surgical throughput. So far, plans for the delivery of surgery have not balanced 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 public’s interest that care is planned appropriately, and a balance is struck between preventing harm through infection control and treating disease through surgery.

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.

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 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.

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.

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.

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.

Outputs:

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.

Processing:

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 Digital. The linkage to civil registration death data will be performed by NHS Digital. 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 Safe Haven (ODS code: 8HN69-PCTU) meets existing information security requirements and achieved ‘Standards Met’ on the DSP Toolkit (17th March 2020).

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 August 2020 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, during the COVID-19 pandemic 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. 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 Digital 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.

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).


Epidemiology of traumatic brain injury in England — DARS-NIC-465144-J4C3T

Opt outs honoured: Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (NHS Trust)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2022-02-14 — 2025-02-13 2022.08 — 2022.08.

Access method: One-Off

Data-controller type: BARTS HEALTH NHS TRUST

Sublicensing allowed: No

Datasets:

  1. Bridge file: Hospital Episode Statistics to Diagnostic Imaging Dataset
  2. Civil Registration (Deaths) - Secondary Care Cut
  3. Diagnostic Imaging Dataset
  4. Emergency Care Data Set (ECDS)
  5. HES:Civil Registration (Deaths) bridge
  6. Hospital Episode Statistics Admitted Patient Care

Objectives:

The aim of processing NHS Digital data is to determine at a population level, the incidence of head injury (the event of a person receiving a blow to the head), traumatic brain injury (a dysfunction in the normal working of the brain due to a head injury), intracranial haemorrhage, neurosurgical intervention, and death within 28 days of injury.

Traumatic brain injuries can result in significant morbidity and mortality, and leads to a significant healthcare need for patients, the healthcare system and society. To understand the need, it is essential to understand the size of the problem. Patients may experience a head injury. A head injury is distinct from a brain injury, because it is possible to sustain a head injury without a brain injury. Patients or their associates may choose to attend an Emergency Department because they sustained a head injury. Within the Emergency Department they may be diagnosed with a brain injury. They may be admitted into the hospital or they may be discharged home. Epidemiological studies report all these rates, i.e. Emergency Department attendance rate, hospital admission rate, head injury rate and brain injury rate. Between 1974 and 2013, 30 studies of the epidemiology of head injuries were published internationally. Of those, 22 (73%) reported total ED attendances per year; 20 (67%) reported ED attendance rate; 12 (40%) reported hospital admission rate; 28 (93%) reported head injury rate and 25 (83%) reported brain injury rate. Of note only one of those studies purported to be a national analysis of head and brain injury epidemiology, but this was extrapolated from survey data and so was not truly national. This research aims to be the first truly national study of head and brain injury epidemiology, and to be comparable to any previous research. In order to achieve this, accurate ED attendance data, in addition to admission data, is required for analysis. For this reason, specific fields within ECDS as defined in the DARS product specification, minimised as far as possible, have been requested for all ED attendances.

The processing will be carried out under Articles 6(1)e and 9(2)j of the General Data Protection Regulations (GDPR). Article 6(1)e states that processing of data is lawful if ‘processing is necessary for the performance of a task carried out in the public interest’. Consequently, the lawful basis for processing is under ‘Public task’. Article 9(2)j states that processing is permitted for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes for the special category health data. The research is in the public interest, will involve processing using sophisticated statistical techniques, and is directly related to health.

The data requested will be processed using the population of England as a denominator for national population incidence calculations, and the number of patients attending Emergency Departments in a year for Emergency Department attendance rate calculations. The data will be stratified by age category, sex, ethnicity, geography and deprivation index in order to identify subgroups of the overall population that are at increased risk of significant outcomes. This will be invaluable information for healthcare planners. Those independent variables will be used in logistic regression models to identify risk factors for five dependent variables (outcomes) including head injury, traumatic brain injury, intracranial haemorrhage, neurosurgery, and death.

There are five previously published articles on the epidemiology of traumatic brain injury in the UK, which are based on data from the 1970s onwards. None are national, four are based on in-patient cohorts, and so bias to the severe end of the TBI spectrum, and one is based on data from a single Emergency Department. The existing data are therefore both out of date and incomplete and are of limited utility to health care planners.

The data subjects are all patients who attended an Emergency Department in England in 2019. The population of interest are those with a head injury, based on the criteria defined below.

Patients with head injury will be defined as follows:
1. A patient having one or more of the chief complaints:
a. Injury of head (disorder)
b. Traumatic injury (disorder) AND linked Diagnostic Imaging Data Set (DIDS) record of having had a Computerized Axial Tomography (CT) head, or CT head and cervical spine, but NOT CT head, cervical spine and other e.g. chest, abdomen & pelvis. This is because National Institute for Health and Care Excellence (NICE) guidance on imaging after head injury advises CT cervical spine if a head CT is being done and there is a suspicion of cervical spine injury.
2. Or, a patient having any chief complaint and one or more of the Emergency Care Data Set (ECDS) diagnoses of
a. Closed fracture of skull (disorder)
b. Open fracture of skull (disorder)
c. Crushing injury of skull and intracranial contents (disorder)
d. Traumatic brain injury with no loss of consciousness (disorder)
e. Traumatic brain injury with brief loss of consciousness (disorder)
f. Traumatic brain injury with moderate loss of consciousness (disorder)
g. Traumatic intracranial subdural hematoma (disorder)
h. Traumatic intracranial extradural hematoma (disorder)
i. Traumatic intracranial subarachnoid haemorrhage (disorder)
j. Cerebral haemorrhage following injury (disorder)
k. Moderate head injury (disorder)
l. Major head injury (disorder)
m. Diffuse brain injury (disorder)
n. Contusion of brain (disorder)

Patients with intracranial traumatic brain injury or haemorrhage are subsets based on the ECDS diagnosis. Patients who had neurosurgery are defined based on the Hospital Episode Statistics (HES) Admitted Patient Care (APC) procedure codes. Mortality within 28 days of index event will be taken from Office for National Statistics (ONS) data (Civil Registrations Deaths Secondary Care Cut).

Data from the Emergency Care Data Set (ECDS), the Diagnostic Imaging Data Set, Hospital Episode Statistics Admitted Patient Care and Civil Registrations Deaths data sets are being requested. These are necessary to identify emergency department (ED) attendances, reason for attendance being head injury, diagnosis of attendance being brain injury, in the overall ED population. They are also necessary to determine whether any independent characteristics such as ethnicity, language, accommodation status or index of deprivation is associated with head or brain injury. DIDS is necessary to determine ED patients who had a CT scan of the head or head and cervical spine. HES APC is necessary to determine those patients who had neurosurgery. Civil Registration Deaths is necessary to identify patients who died and whether it was within 28 days of the index event.

All ECDS records are requested for several reasons. 1) In order to describe the population incidence of attendance to the ED with head injury amongst the population of England. 2) To describe the population incidence of TBI amongst the population of England. 3) To describe the incidence of head injury amongst the population of people that attend EDs in England. 4) To identify the association (if any) with TBI of independent variables including age, sex, ethnicity, language, accommodation and index of multiple deprivation. 5) Because an understanding of the overall population attending, specifically with respect to characteristics of patients that could be associated with head or brain injury and used in some of the mathematical analysis (namely age, sex, ethnicity, language, accommodation, geographical region, and deprivation measure) will be required to enable readers of the results to make comparisons with characteristics of patients in their area, or that attend their hospitals. 6) Because part of the mathematical analysis (also called statistical modelling), will employ a technique called hurdle modelling. This uses characteristics from the overall population (including those patients that do not have head injury) to create a final mathematical model that predicts brain injury in patients with head injury.

No identifiable data is being requested from NHS Digital. 16 months of data has been requested, which includes one year of analysis (2019) and two months on either side. This will account for the prevalent pool effect, which is a phenomenon that occurs when an episode could be either a first or a follow up episode. For instance, a patient attending an ED with a head injury in January could be attending because they had just suffered a head injury, or because they were returning with ongoing symptoms following a head injury in the preceding December. Without including ‘buffer months’ on either side of the study period, the returned patients in January, whose index event is outside the study period, and those that have a head injury in the December within the study period and return in the following January (outside the study period), could not be identified. These follow up attendances are important for an accurate understanding of the population incidence and for health care planning. Data for all of England has been requested. There are no alternative less intrusive ways of performing this research.

Data has been minimised as far as possible. Only data directly relevant to the study is requested. No personal identifiers are requested, the minimum number of datasets (four) are included and for a single year period of analysis (plus two months each side). A pseudonymised identifier is required to link the four requested databases. A single year of data (plus two months each side) is necessary to accurately report the population incidence of the defined outcomes. The data for all of England has been requested because this study is relevant to all of England and because geographical variation in head and traumatic brain injury rates is critical for health care planning. Since people of all ages sustain head injuries, it is not possible to filter by age. Consequently, age but not date of birth is requested. The clinical procedure is filtered by a specific Operating Procedure Codes (OPCS). All patients’ emergency department episodes for the study period will be requested because patients reattend with head injury, either because of a repeated head injury or ongoing symptoms related to the initial injury (index event). Because within the study there is a predefined two-month period after which a repeat attendance is not likely to be due to the index event, to avoid the prevalent pool effect, two months prior to the analysis period and two months after the analysis period are included in the data request. The number of fields within ECDS, HES APC, DIDS and ONS mortality has been minimised to include only those relevant to answering the study question.

The Royal London Hospital Emergency Department Research Team Patient and Public Involvement (PPI) group consists of six members. The study team shared the study protocol with the PPI group and asked for their views and feedback. The study protocol was then updated based on the PPI group feedback. The PPI group act in an advisory role only and Barts Health NHS Trust make the final decision regarding any changes/updates to the study (as the data controller). In addition to the local PPI group, the charity Headway has been invited to be represented on the study committee.

The sole data controller who also process the data is Barts Health NHS Trust. This work is funded from the Principle Investigator account of the Chief Investigator, held by the Barts Health NHS Trust Joint Research Methods Office. There are no other funders/commissioners.

The study committee members' organisations are Barts Health NHS Trust (Royal London Hospital), Queen Mary University London, Hospital Sulpetrie (Paris, France), Lancashire Teaching Hospital NHS Foundation Trust, Addenbrookes Hospital NHS Trust and London School of Hygiene and Tropical Medicine. Apart from Barts Health NHS Trust (the data controller who determines the purpose for processing), members of other organisations are only acting in an advisory capacity and will not have access to the NHS Digital data. The Information Commissioner’s Office “Are we a joint controller?” checklist was used (available at https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/key-definitions/controllers-and-processors/) to determine that none of the members on the committee are joint data controllers.

Yielded Benefits:

This is a new Data Sharing Agreement. No data has been disseminated by NHS Digital for this research study. There are therefore no yielded benefits to date.

Expected Benefits:

Estimates of the population incidence of head injury are based on data from fifty years ago that there are 1.4 million patients sustaining a head injury. Data on population incidence of mild traumatic brain injury (TBI) are even less reliable. However, it is thought to be common, and the consequences of even mild TBI are thought to be devastating with as many as 50% of patients with mild TBI having ongoing symptoms a year after injury and 10% who were in work prior to the injury still unable to return to work at a year.

Commissioners and acute care trusts may, for the first time, have information on local head and traumatic brain injury patterns, which may inform TBI services and the creation of head injury clinics. Independent factors such as age, sex, ethnicity, housing status and deprivation will be tested for association with head and traumatic brain injury. Understanding the association between characteristic properties of the population and a disease process is key for designing public health measures to reduce the disease burden.

In addition, this research hopes to address and support several recommendations identified in a recent call for a concerted effort to tackle the health problem in England posed by traumatic brain injury (Maas, Menon et al., The Lancet Neurology, 2017). Several recommendations were set including performing rigorous epidemiological studies to capture the changing patterns of epidemiology and to identify high-risk groups and key targets for improved prevention and management of TBI. This research is designed to address this recommendation, by defining a priori potential high-risk groups, based on age, sex, ethnicity, language, accommodation status (homelessness), economic deprivation, and geographical area. The policy makers and clinical community hope to then use the limited resources that are allocated to TBI education, prevention and treatment to focus any impact on groups or regions that are found to be high risk.

A further recommendation was to standardise epidemiological monitoring of TBI to allow accurate measurement of incidence, prevalence, and mortality, and comparison of rates of access to community, hospital, and residential care. The UK healthcare system is near unique in that it is a single payer system with multiple centrally held records. The methodology employed in this research, namely defining five head injury outcomes, and utilising nationally held pseudonymised patient level records, may be beneficial for future research due to its simple and replicable methodology. The study protocol will be made available for free in an open access environment for replication.

TBI in specific populations was explicitly named as a research priority. Defined populations include children, adolescents, and the elderly. Because this research will stratify by age, the rates of the five outcomes in this research will be specifically measured within these populations. Describing TBI by mechanisms and cause of injury is also a research priority and is part of the descriptive part of the analysis plan in this research. This may be beneficial to determine incidence and outcomes for the defined population and may inform policy changes, clinical care improvements and further research.

Effective strategies for TBI prevention are urgently needed and hope to deliver cost savings that help to fund research and improved access to health care for TBI. By identifying high risk groups, this research will, in addition to answering the core research question, be hypothesis generating and identify further areas of epidemiological and public health research that may be best placed to reduce the impact of head injuries and TBI.

Furthermore, outcomes that quantify the overall burden of disability from TBI need to be developed. Understanding the proportion of patients who develop high severity outcomes such as surgery or death following TBI is a critical contributor to quantifying disability. This research is uniquely placed to answer that question.

Outputs:

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

The final results will be submitted to a high impact factor peer reviewed journal such as The Lancet, and be presented at national and international conferences including but not limited to The International Conference on Emergency Medicine and The Royal College of Emergency Medicine Scientific Conference. The output is expected to be cited frequently.

The study expert committee includes members of influential national bodies including the committee that manages the National Institute for Health and Care Excellence guidelines for the management of Head Injury. The results of this study are likely to influence future iterations of this guideline, which is the basis for head injury management in all Emergency Departments in England and Wales.

Publicity following from the study results, and dissemination of the results outside of the scientific community, will be managed by the Barts Health NHS Trust communications department, and streams will include social media and news reports. The social media presence is yet to be created.

The outcomes of the study (containing aggregated data with small numbers suppressed in line HES Analysis guidance) will be shared with The Royal London Hospital Emergency Department Research Team Patient and Public Involvement (PPI) group and their feedback obtained.

Specialist charity groups e.g. Headway will be contacted and given copies of the study results.

Once the data has been made available by NHS Digital, the study team anticipate a requirement of six months to process and analyse, and a further six months to write up and submit for publication.

Processing:

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).

There will be no data linkage undertaken with NHS digital data provided under this agreement that is not already noted in this agreement.

Data from the Emergency Care Data Set (ECDS), the Diagnostic Imaging Data Set (DIDS), Hospital Episode Statistics Admitted Patient Care (HES APC), and Civil Registrations Deaths is being requested. Each data set will be at patient level with each patient having a pseudonymised identifier. The datasets will be aggregated at record level based on the pseudonymised identifier as part of processing within the Barts Health NHS Trust environment.

Data flows:
- NHS Digital will filter the requested datasets according to criteria explained in section 5a (Objective for Processing) of the agreement.
- NHS Digital will then upload the data to the Secure Electronic File Transfer (SEFT) account.
- Barts Health NHS Trust will then download the data to the Trust's secure network drive.
- Data will then be analysed to produce the required outcomes of the study.

No linkage to any other data other than those requested in this application is planned.

No matching of data to publicly available data sets is planned.

No attempt to re-identify individuals will be made.

Data processing will only be carried out by substantive employees of Barts Health NHS Trust who will have been trained in data protection and confidentiality (this includes the PhD students who are members of the study committee as they are also substantively employed by the data controller). All individuals processing data will have completed the Office for National Statistics Safe Researcher Course. The data will be stored in a password protected drive within a networked drive of Barts Health NHS Trust. System access will be granted by the Barts Health NHS Trust IT team. A monthly log of data processing episodes, and a final total log of all episodes will be generated.


Continuation of order NIC-147204-CGWY5 MR1283: DARE (Diabetes Alliance for Research in England) - NE London Diabetes Research Network Locality — DARS-NIC-291938-R6V3V

Opt outs honoured: No - consent provided by participants of research studY, Identifiable, No (Consent (Reasonable Expectation))

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (NHS Trust)

Sensitive: Non Sensitive, and Sensitive

When:DSA runs 2019-05-31 — 2022-05-30 2017.09 — 2022.03.

Access method: Ongoing, One-Off

Data-controller type: BARTS HEALTH NHS TRUST, QUEEN MARY UNIVERSITY OF LONDON

Sublicensing allowed: No

Datasets:

  1. MRIS - Cohort Event Notification Report
  2. MRIS - Cause of Death Report
  3. MRIS - Flagging Current Status Report
  4. MRIS - Members and Postings Report
  5. Demographics

Objectives:

The aim of this study is to establish an epidemiologically based sample of all patients with diabetes within the regions included in the Diabetes Research Network (DRN). By collecting the same non-invasive samples as per clinical care it will be possible to perform tests to look for markers of the complications of diabetes. DNA will be taken from all consenting patients and molecular and genetic information will be combined with clinical information to provide a resource to look for gene/environment interaction in the development of Type 1, Type 2 and other forms of diabetes and their associated complications.

Data access is restricted to those named in section 7 of this agreement. Any changes will be notified to the HSCIC.

Yielded Benefits:

The DARE study has contributed to the recruitment of over 25 ethically approved NIHR portfolio studies to date and has involved the participation of over 2,200 people registered on the database. These studies are aimed at either finding a cure for diabetes or improving health of those with diabetes. Having this database has accelerated the research process and provided evidence which has improved health care provision. For example, the team recently searched for a study called REVITA-2. This study for over weight people with type 2 diabetes (T2D) is trialling a new investigative procedure in the small intestine (duodenum). The study is designed to safely alter the inner surface of the duodenum to improve control of blood sugar. The study was very difficult to recruit to. Using DARE the Team were able to identify nearly 200 people meeting the criteria with 5% of these going on to be screened into the study. The benefit for DARE members is that they have access to some of the latest research studies which they may be interested in. The yielded benefit to the company is that they will now be undertaking another study - REVITA -3 which will improve the health of many others with T2D. In another completely different study DARE members were also contacted about a questionnaire - the Diabetes Essential Care Study - which asked their opinion about Diabetes Care provision in primary care. So far nearly 2000 people have responded and presentations have been made on preliminary findings to the study steering committee. The next yielded benefit is to make reports to local CCGs on the findings which could have a beneficial affect on service provision. All outputs will be aggregated with small numbers suppressed in line with the HES Analysis Guide.

Expected Benefits:

The expected benefit of the DARE database is that study team can continue to offer people registered the opportunity to take part in diabetes research. Recruitment is sometimes a difficult aspect of any research and can be costly in terms of searching and advertising. Studies using the database can expect to have an increased chance of recruiting more efficiently and quickly. This speeds up the evidence gained from the research and may lead to prompt changes in treatment and care, improving self management etc. The indirect expected benefit of being on the DARE database is that many members are likely to attend outreach events organised by the study team and have access to new information about their diabetes which in turn improves health and well being for people with diabetes.




Outputs:

The main output is an up-to-date database for the DARE study which means that the study team can contact their members about research opportunities when they become available. They will also be holding a series of public engagement events with researchers and clinicians. The first such event was on 13th November 2018 where they invited people from the database to listen to presentations on diabetes research which they may be interested in. The event was also attended by the charity Diabetes UK and latest information on diabetes and self management was distributed. Members were also allowed to vote on future presentations and make recommendations. The day was highly evaluated and a report was sent to all invited members. The study team also have a twitter account to promote such events. Another large event is being planned in the autumn of 2019. The study team also intend to email and post a twice yearly newsletter giving latest information on diabetes research and other relevant material to members. The first newsletter is anticipated to be in Spring 2019. It is the study team's intention to submit abstracts and presentations for relevant diabetes professional conferences e.g. Diabetes UK and International Diabetes Federation and publish our findings in appropriate journals e.g. Diabetic Medicine.

All outputs will be aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

No contact will be made with any individual(s) who could be identified from the information supplied, other than as specified in the protocol and associated documents.

Use of the data supplied is for the sole purpose set out above. The Data must not be shared with any other organisation or named individual not explicitly referred to within this agreement. If the information referred to herein is subject to an FOI or other request to share the Data, then agreement from the HSCIC must be sought before undertaking this.

The Dataset must not be shared with any third party in the format in which it is provided to you by the HSCIC.

Information tools derived from this Dataset will not be provided to any organisations without the specific consent of the HSCIC.

Any publications derived from this Data by any party must be subject to ONS confidentiality guidance on the release of birth and death and Health Statistics: The National Statistician sets standards for protecting confidentiality, including a guarantee that no statistics will be produced that are likely to identify an individual unless specifically agreed with them, where the guarantee is judged against the standard that ‘it would take a disproportionate amount of time, effort and expertise for an intruder to identify a statistical unit to others, or to reveal information about that unit which is not already I the public domain.’

Specifically, undertake to ensure that appropriate controls are in place, to ensure compliance with the HSCIC’s, Small Numbers Special Terms and Conditions. Such controls will, as a minimum, meet the requirements of condition 3.3 of the Small Numbers Special Terms and Conditions and more generally satisfy Section 5 of the ONS confidentiality guidance.


The impact of COVID-19 on surgical care and outcomes in England (COVID-19 Surgical Observatory) — DARS-NIC-375669-J7M7F

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: No (NHS Trust)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2020-09-24 — 2021-09-23 2020.10 — 2021.05.

Access method: System Access
(System access exclusively means data was not disseminated, but was accessed under supervision on NHS Digital's systems)

Data-controller type: BARTS HEALTH NHS TRUST

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Critical Care
  3. Hospital Episode Statistics Outpatients

Objectives:

The study group are requesting access to the National Health Service (NHS) Digital Data Access Environment (DAE) to process Hospital Episode Statistics (HES) data on a continuous system access basis.

This processing is required to determine the disruption caused to NHS procedures during the period of the COVID-19 pandemic, to map how procedures are re-starting and to determine the potential impact of future waves of COVID-19 on services.

More than 8 million hospital procedures take place annually within the NHS. The repurposing of staff, equipment and facilities led to many procedures being cancelled. Prior to the COVID-19 pandemic, some 1.8 million patients were awaiting care, and preliminary models suggest that a further 2.2 million procedures were cancelled or delayed because of the initial peak. However, this model relies on several assumptions about the number of procedures that were cancelled and how rapidly services can resume. Social distancing and pre-procedural testing guidance, as well as the potential need to cancel further procedures should there be new peaks will limit how quickly services can re-establish.

The requested data will be used to inform policy makers at a local and national level about the ongoing need for care, to support future care provision and to plan for subsequent waves should they emerge. Potential approaches, including use of independent sector bed capacity and segregation of hospitals into COVID-free and COVID-affected sites have all been suggested, but there is limited information to support decision making.

All data will be accessed via the secure DAE and will be used to:
1. Accurately determine how many procedures were cancelled during the initial peak of the pandemic
2. Monitor resumption of procedures (including diagnostics and surgical procedures), the characteristics of those undergoing procedures, geographical variation and associated outcomes (including length of hospital stay, critical care utilisation, re-attendance)
3. Determine the impact of future waves of COVID-19 on future NHS care
4. Produce refined projections of the likely need for surgical care and resources required to do this based on existing models.
5. To contextualise these in the context of overall hospital utilisation and historic patterns of care.

Only non-identifiable and pseudonymised patient-level data will be used. Access to historical data (1st April 2014 to 31st December 2019) is required to provide comparisons to the COVID-19 year (1st January 2020 onwards). Processing the data on a rolling basis in the DAE will allow near real time monitoring of the resumption of care.

The following datasets are required for the aims of this project:
• HES Admitted Patient Care (APC)
• HES Critical Care (CC)
• HES Outpatients (OP)

Admitted Patient Care data will be used to determine the number of patients undergoing procedures, their characteristics, and outcomes. Data will be accessed for all inpatient records such that the resumption of surgery can be contextualised against the number of patients in hospital with other conditions.

Adult critical care data will be used to determine the frequency with which patients require critical care following procedures, and comparison with historical data will enable analysis of how critical care utilisation for surgery changed in the context of a surge in requirement due to the COVID-19 pandemic.

Outpatient data is required as many diagnostic procedures take place on an outpatient basis.

Barts Health NHS Trust will be the data controller who also processes data, Queen Mary University of London will be data processor along with Barts. All analyses will take place within the secure NHS Digital data access environment by substantive employees of a data processor.

There is no flow of identifiable patient data and as such, ethical review is not required. Data will be accessed only by the data controller and processors using the secure DAE. 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 Benefits:

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 policy makers at all levels. With preliminary data suggesting that in England alone, more than 2 million NHS operations could be cancelled by March 2021, it is in the public’s interest that care provided is planned appropriately to ensure the health of the nation is not compromised. Any harms associated with delayed care or cancelled operations need to be understood in the case of future disruptions to services due to subsequent waves of COVID-19.

The outputs will present the national volume of surgery and associated hospital procedures during second and subsequent phases of the pandemic, alongside outcomes of those undergoing these procedures. This will highlight the extent at which the nation has been affected by the pandemic, and in turn influence the decisions involved in reintroducing surgical care. To further support health policy planning, the outputs will determine the resource requirements associated with ongoing and future surgical and associated hospital procedure activity.

The findings of the project will impact patients across England mainly those awaiting surgery and associated hospital procedures. With more than 8 million hospital procedures usually taking place annually within the NHS, widespread cancellations have affected the care of patients on a large scale.

There has already been substantial attention paid to the resumption of care in the NHS, at present there is limited data to inform how this is going on and the associated outcomes. The outputs will be produced by the controller and these data will provide vital statistics to support decision making at a national, regional, and local level across England.

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.

The benefits are expected to be achieved over an extended period as the series of reports are published. The use of the DAE provides the flexibility to access and rapidly analyse the latest version of the data. 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.

The results of the outputs are likely to confirm the need to increase surgical activity to compensate for the backlog of surgeries that were cancelled during the pandemic, and for the many patients on the waiting list. This will influence the plans set-out by NHS Trusts across England to resume surgical care i.e. expansion of resources, but also determine ways to avoid disruptions in the face of new waves of COVID-19 by implementing testing and PPE policies.

After publication of the findings, reports will be generated to national and local leaders to support the decision-making process. 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. If there are further peaks, it is anticipated that the winter months will be particularly difficult. The aim is to have the monthly extract/analysis flow established so decision making can be directly informed during urgent and critical time points that may arise due to COVID-19.

The first report is expected within two months of receiving data access, with sequential reports following from this.

Outputs:

Only summary/aggregated data with small numbers suppressed in line with the HES Analysis Guide will be presented in the main scientific report. No record level data will be included in any of the study 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 policy making for surgical care during the recovery phase of the COVID-19 pandemic, and in the case procedures are suspended in response to future peaks of COVID-19. Colleagues in Wales plan to perform analogous analyses to provide wider context to this work. The 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 and Social Care.

A plain English summary will also be produced for patients and the public to help understand the impact of COVID-19 on national surgical activity and hospital resources. 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 as they emerge.

The aim is to submit the first report for publication in a high-impact journal in early 2021. This will be followed by a series of publications describing the delivery of surgical care as the pandemic response enters new phases. All publications will be open access, and can be accessed by policy makers, 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.

Processing:

Barts Health NHS Trust and Queen Mary University of London will be processing the data at all stages. There will be no flow of data into NHS Digital, and there will be no external linkage. All queries will be performed within the secure NHS Digital DAE and the outputs will be in line with NHS Digital guidance. There will be no attempt to identify individuals from the data.


Processing activities, aim 1):

Pseudonymised record level data will be queried within the DAE to generate an aggregated anonymised data report at the level of primary procedure for each month for the following processing activities:

1. Historical numbers of procedures performed monthly will be determined from the historical comparison period of HES APC and OP
2. The number of procedures performed monthly from 1st March to 1st June, will be determined and compared to historical procedures
3. Type of procedure, patient characteristics, and outcomes of these two time periods will be compared
4. The frequency of critical care utilisation and duration of critical care stay will be determined from linking HES APC and ACCD
5. The total number of patients admitted in the same period will be determined to provide context to findings from activities 1. to 4.

Processing activities, aim 2):

Pseudonymised record level data will be queried within the DAE to generate an aggregated anonymised data report at the level of primary procedure for each month for the following processing activities:

1. On a monthly basis for a 12-month period, the DAE HES APC and HES OP will be queried to determine how rapidly procedures are being resumed within the NHS.
2. Type of procedure, patient characteristics and outcomes will be presented on a rolling monthly basis
3. The frequency of critical care utilisation and duration of critical care stay will be determined from linking HES APC and HES ACCD
4. The frequency of hospital re-attendance and duration of hospital stay will be determined from HES APC
5. The total number of patients admitted in the same period will be determined to provide context to findings from activities 1. to 3.

Processing activities, aim 3):

Pseudonymised record level data will be queried within the DAE to generate an aggregated anonymised data report at the level of primary procedure for each month for the following processing activities:

1. Should new waves of COVID-19 emerge, the study team will monitor the number of procedures performed as recorded in HES APC and HES OP
2. This will be used to update existing models of the deficit of procedures performed
3. As further waves are likely to be more regionally located, further analyses in specific regions will be performed.

Processing activities, aim 4):

Pseudonymised record level data will be queried within the DAE to generate an aggregated anonymised data report for the following processing activities:

1. HRG codes from the historical comparison period will be used to refine estimates of the cost of surgical care.
2. ODS codes will be used to identify procedures performed in different settings (including independent sector institutions) to provide an estimate of independent sector bed utilisation by the NHS.
3. Activities 1. and 2., in combination with the number of procedures cancelled during the COVID-19 period, will be used to update existing resource utilisation models.

Data will only be processed by substantive employees of the data controller and data processors set out in this agreement.

To mitigate the risk of reidentification, only pseudonymised data will be used and data will be accessed remotely via established, secure environments that meet existing information security requirements. The data is stored by NHS Digital.

Any exports of data will be performed in line with NHS Digital guidance and the data sharing agreement.

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).


MR1486 - International Surgical Outcomes Study: Long-term survival. — DARS-NIC-68740-X7R2N

Opt outs honoured: Yes - patient objections upheld, Identifiable, Yes (Mixture of confidential data flow(s) with consent and flow(s) with support under section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7), Consent (Reasonable Expectation); Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Consent (Reasonable Expectation); Health and Social Care Act 2012 – s261(7)

Purposes: No (NHS Trust)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2019-07-10 — 2022-07-09 2019.11 — 2019.11.

Access method: One-Off

Data-controller type: BARTS HEALTH NHS TRUST

Sublicensing allowed: No

Datasets:

  1. MRIS - Flagging Current Status Report
  2. MRIS - Cause of Death Report
  3. Hospital Episode Statistics Admitted Patient Care

Objectives:

The objective for processing these data are to complete studies related to the International Surgical Outcomes Study (ISOS) UK Cohort that require mortality data. The mortality data will allow Barts Health NHS Trust to determine the long-term survival following surgery.

As the team are performing scientific research at a public institution, the legal basis for processing personal data for this purpose at Barts falls under Article 6(1)(e) of the General Data Protection Regulations (GDPR), i.e. “a task carried out in the public interest”. It also falls under Article 9(2)(j), “processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes”.

The European Surgical Outcome Study (EuSOS) was completed in 2012 and is completely separate to this study.

The International Surgical Outcomes Study (ISOS) was a separate study completed in 2014. This data agreement relates to the long term follow up of the International Surgical Outcomes Study (ISOS) UK Cohort. The team are performing a survival analysis of patients recruited in the UK during ISOS. The main International Surgical Outcomes Study completed in 2014, identified that patients suffering complications were far more likely to die than those who didn’t. This study will be exploring the long term survival of those who have had surgery, and will provide further evidence to support ongoing research in this field.

The other phases of the International Surgical Outcomes Study have been completed. The aim for this mortality data is to answer what the long-term survival is following surgery and how this differs for those suffering complications. The team anticipates the long-term survival data being used in a main analysis of the whole dataset and will consider further subgroup analyses as appropriate.

The purpose of the project is to obtain mortality data for patients who consented to linkage in the International Surgical Outcomes Study and to describe the long-term survival of these patients. The team requires record level data, pseudonymised by unique ISOS study ID, to cover a follow up period of 3 years. National death data is required as patients may be treated in a different geographical location to their area of residence. Data is only requested for ISOS cohort (7045). There are no other alternative, less intrusive ways to determine the long-term survival of this patient cohort.

This agreement has a mixed approach to the common law duty of confidentiality:
1) Consent from first year of follow up (confirmed by CAG).
2) Section 251 for the following two years of follow up.

Section 251 support has been obtained. The Confidentiality Advisory Group have confirmed that the study consent material was valid for the purposes of linkage for the first year, and section 251 support has been obtained for a further 2 years of follow up to enable the team to obtain data pertaining to the three year survival of participants enrolled in ISOS.

Other NHS Trusts in England recruited patients to the study, but the study is led by Barts Health NHS Trust and all data is held by the Trust. Barts Health NHS Trust are the sole Data Controller who also process data. National Institute for Health Research (NIHR) are funders of the ISOS study.

The ethical approval (to enable support under section 251 NHS Act 2006, ref:18/YH/0310) raised no new ethical concerns.

There is no risk of harm by dissemination, informing patients, clinicians, researchers and policy-makers of the long-term survival following surgery will lead to further improvements in care.

Expected Benefits:

To date, no data is available describing the long term outcomes of surgical patients in England. The Trust anticipate this research to be hypothesis generating, thus the benefit to wider health and social care is by identifying potential health problems and raising awareness of these. It is hoped this will add to a body of evidence to further research in this area to address potential problems, leading to improvement in health. Around 5.1 million patients each year have surgery in the NHS, and there is a huge potential to benefit these groups with further research.

This research aims to better understand the long-term benefits and potential harms of surgery, as well as the human and financial cost of providing surgery within the NHS. The following groups could benefit:
• Patients undergoing surgery
• Clinicians (anaesthetists and surgeons)
• NHS Hospital Trusts
• Non-NHS healthcare organisations
• Researchers

Dissemination is in the public interest as it will provide insights into the risks of surgery and those patients at particular risk of death after surgery. This will potentially lead to improvements in care, which is within the public interest.

The outputs will provide robust figures describing survival after surgery and therefore achieve the stated purpose.

This final project of ISOS will provide important context for earlier studies, and fuel further research into this important subject area. These have been published in a number of journals and explored a number of important areas including the use of critical care after surgery, how acute kidney damage associates with poor outcomes after surgery and the use of simple interventions, like checklists, to improve outcome. Surgery is often considered successful by healthcare professionals if a patient survives until hospital discharge. As a result, the majority of surgical research studies stop collecting data after hospital discharge or until 30-days post-surgery. However, evidence from the USA suggests that the presence of any complications after surgery, even minor ones, can reduce long-term survival.

This has not been demonstrated in a UK cohort, but the results are expected to be similar. Furthermore, feedback from surgical patients suggests that most people undergoing surgery expect to survive to hospital discharge and would only consider the surgery successful if they return to a certain level of pre-morbid function. Therefore, there is a gap between patient expectation of surgery and the evidence from the majority research studies about the long-term results of surgery. This study aims to describe the patterns of survival up to three years after surgery in the UK. This could lead to changes in the way that surgery is planned or delivered and could ultimately benefit patients undergoing surgery.

The target date for completion of these projects will be 1st January 2020.

Outputs:

The following outputs will be produced as a result of the data processing;

1. Reports for funding bodies, Confidentiality Advisory Group and the Research Ethics Committee.
2. The team anticipates at least one submission to a high-impact peer reviewed journal. E.g. British Journal of Anaesthesia. Further pre-specified subgroup analysis plans will be considered including a further investigation of specific complications.
3. The team anticipates presenting the findings to local groups of interest (including anaesthesia & surgical specialties).
4. The team anticipates presenting the results at relevant scientific conferences e.g. Evidence Based Perioperative Medicine Congress (London).
5. Data will be made available on the ISOS study website so that participants and interested parties are able to review.

Aggregated data only will be available in the outputs, with small numbers suppressed.

The team have strong links with the Royal College of Anaesthetists Patient and Public Involvement group who will promote the findings from the study amongst its networks of patients and the public. Additionally, the team are involved in the Perioperative Medicine Programme at the Royal College of Anaesthetists and would anticipate these results impacting on policy recommendations made by this important group. The team will approach relevant policy-makers should any results be of particular interest to this group.

Results will be published on the ISOS website, and the team will disseminate through existing channels to professional societies (Royal College of Anaesthetists, Royal College of Surgeons), interested patient groups (including the Patient, Carer and Public Involvement group at the Royal College of anaesthetists) and presentations to professional groups at conferences/talks. These presentations will be either in the form of webcasts, posters or presentations.

The findings of this work will be highly influential on further research exploring long-term outcomes after surgery which is currently a very poorly researched field.

The target dates for publication of the first draft of the manuscript is 01/01/2020.

Processing:

The administrative study sponsor organisation for the International Surgical Outcomes Study (ISOS) study was the Queen Mary University of London (QMUL). Before starting the projects outlined in this agreement the data set was transferred to Barts Health NHS Trust from QMUL. Barts Health NHS Trust are the data controller organisation for this agreement and projects outlined in it. Record-level mortality linked data will not be transferred outside of Barts Health NHS Trust.


The steps to be performed to process the data under this agreement is as follows:

a. Investigators at 110 hospitals in England have already entered data on to a secure online e-CRF for the ISOS study.
b. The ISOS study team hold study data including patient identifiable information.
c. The ISOS study team will remove study data to create a dataset with only patient identifiers and the ISOS ID. The patient identifiable fields are: Name, date of birth, sex and postcode.
d. The ISOS study team will also create a pseudonymised dataset with study data and ISOS ID, but no other patient identifiers.
e. The identifiable dataset will be transferred to NHS Digital using a secure method of transfer.
f. NHS Digital will link the patient identifiers to mortality (death) data using the patient identifiers.
g. NHS Digital will then remove patient identifiers, leaving only the ISOS ID and mortality data.
h. NHS Digital will transfer the linked dataset to the ISOS study team at Barts Health NHS Trust.
i. The ISOS Study team will combine the ISOS study data set with the mortality linked data, using the ISOS ID.
j. Pseudonymised data will be kept separately from identifiable data and mortality data will not be linked back to identifiable data.
k. ISOS Study team will complete the statistical analyses using the pseudonymised data set. Only aggregated statistical outputs, meeting current statistical disclosure control standards, will be removed from the Barts Health Trust
l. The results of the sub-studies will be disseminated via peer-review publication and at academic conferences/meetings.

No linkage, other than that described within the agreement is permitted and no further data linkage will be undertaken.

Re-identification is not permitted under this data sharing agreement.

The study team is located at Barts Health NHS Trust. All of the team are substantively employed by Barts Health NHS Trust, except for the Chief Investigator who has a substantive contract with Queen Mary University of London and an Honorary contract with Barts Health NHS Trust. All members of the study team have information governance training and are Good Clinical Practice trained.

All data disseminated under this agreement will be processed and stored at Barts NHS Trust. No data is to be transferred stored or processed at QMUL. Data will be held in a secure file on the Barts Health Computer network. This will be accessible only to named members of the research team. This can be accessed only on site and via password protected accounts assigned to named team members. All data is stored on Barts Health servers, the Barts Health computing network is compliant with existing information security/governance requirements.

NHS Digital reminds all organisations party to this agreement of the need to 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 ie: employees, agents and contractors of the Data Recipient who may have access to that data).

Only three years follow up data is permitted from the data sharing agreement start date.


NICOR Commissioning through Evaluation (CtE) Registries/Audits: Left Atrial Appendage Occlusion (LAAO), Mitral valve repair (Mitraclip), and Patent Foramen Ovale Closure (PFOC). (Previously DARS-NIC-53806-V9J4G-v0.8) — DARS-NIC-151212-B5Z3R

Opt outs honoured: Y, Anonymised - ICO Code Compliant (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012, Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012), , Other-Health and Social Care Act 2012 - s261(2)(b)(ii)

Purposes: No (NHS Trust)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2019-01-25 — 2024-01-24 2018.03 — 2018.05.

Access method: One-Off

Data-controller type: BARTS HEALTH NHS TRUST

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Office for National Statistics Mortality Data
  3. Civil Registration (Deaths) - Secondary Care Cut
  4. HES:Civil Registration (Deaths) bridge

Objectives:

The National Institute for Cardiovascular Outcomes Research (NICOR) hosted at Barts Health NHS Trust require HES Admitted Patient Care and ONS Mortality data for use in an audit of patients who have undergone one of three procedures. Percutaneous mitral valve leaflet repair for mitral regurgitation using MitraClip; Left Atrial Appendage Occlusion (LAAO); and Patent Foramen Ovale Closure (PFOC) procedures. Previous service provision has been unstructured and delivered by providers who had attempted to establish services through negotiation with local specialised commissioners.

In April 2013, NHS England became responsible for directly commissioning specialised services and published a clinical commissioning policy statement which stated that percutaneous mitral valve leaflet repair for mitral regurgitation using MitraClip, LAAO and PFOC procedures would not be routinely funded as the current evidence base had been of insufficient quality. NHS England developed ‘Commissioning through Evaluation’ (CtE) to support the commissioning of clinical activity around an evaluation programme to add to the current evidence base for designated technologies. The overall aim was to provide a clinical and economic evaluation of the MitraClip and the other two procedures. Funding was provided for a limited number of high risk patients as determined by an appropriately constituted Multi-disciplinary Team (MDT) process.

Prior to 2013 service provision was unstructured and delivered by providers who attempted to establish services through negotiation with local specialised commissioners. The majority of procedures were commissioned through individual funding requests or by individual Trusts funding treatments by other means. In April 2013 NHS England became responsible for commissioning specialised services. However as the evidence base for percutaneous mitral valve leaflet repair for mitral regurgitation using MitraClip, LAAO and PFOC procedures was of insufficient quality the procedures were not to be routinely funded.

Because of the remit of NICE in terms of developing evidence based guidance NHSE, the principal funder, commissioned NICE to establish the ‘Commissioning through Evaluation’ (CTE) programme in order to gather further evidence to support commissioning of designated technologies. The overall aim was to develop a model for both clinical and economic evaluation of the three procedures which could be used in future for other similar new health technology procedures.

NICE contracted with the Newcastle upon Tyne Hospitals NHS Foundation Trust (NUTH) which hosts one of the NICE External Assessment Centres (EAC) with the task of establishing this programme. The NUTH EAC houses a team of scientists, economists and engineers, who provide an independent assessment of evidence for innovative medical devices and associated economic analysis. The team are substantive employees of NUTH.

With its extensive experience and excellent reputation in conducting national cardiovascular audits and registries, the National Institute for Cardiovascular Outcomes Research (NICOR) was commissioned by NUTH to develop, host and maintain the three cardiovascular registries.

NICOR are acting as sole data controller for the CtE datasets because these datasets contain variables over and above those needed for the NUTH purposes, which might be of interest to other applicants for the audit data. The NUTH/NICE would not be expected to have to be part of the approvals process for such applications, should they occur. The national CtE Steering Group and a number of Working Groups were established to define the datasets. The Working Groups deemed that the datasets should be designed to answer as many questions as was felt clinically and administratively relevant for the purposes of evaluating the technology in more detail. The datasets were approved by the Working Groups and the Steering Group.

As well as determining the datasets and defining the audit questions, NICOR is also responsible for managing all aspects of the data collection process, data security, data storage, cleaning/validation of data, data linkage with ONS/HES and reporting. The reporting function includes providing pseudonymised data extracts to NUTH as per its requirements, receiving all variables needed for the purposes of the agreed independent analyses. A key deliverable of this contract is to provide NUTH with a pseudonymised linked clinical PFOC, MitraClip and LAAO raw data with ONS and HES data extract. ONS and HES linked data are required from NHS Digital to allow analysis of future clinical events rates after the initial treatment (principally rates of strokes/cerebrovascular events and death).

The work aims to gather more data on the safety and effectiveness of three complex cardiology procedures
which are not currently routinely funded by the NHS, but nonetheless may show significant promise as a
future treatment. The data gathered from centres undertaking these procedures is to be analysed to inform
future commissioning intentions.

This is not an experimental research project, but an evaluation of service delivery. There is no specific hypothesis being tested. NICOR have defined 11 specific questions to frame the CtE evaluation programme:
1) Can UK clinical teams undertaking MitraClip reproduce the reduction in mitral regurgitation seen in the early clinical trials?
2) Is reduction in mitral regurgitation mediated by MitraClip associated with improvements in quality of life?
3) Does MitraClip improve survival rates?
4) Does MitraClip reduce the frequency of subsequent hospital admissions?
5) Are the early benefits in reduction in mitral regurgitation maintained in the medium-term? Is there a need for repeat treatment over time (either by a repeat percutaneous procedure or surgery)?
6) What proportion of patients referred to a specialist Mitraclip service as defined in the CtE documents were assessed by the MDT as suitable for the intervention? What proportion of the patients considered suitable for the procedures received it and what proportion of them benefited?
7) What are the short and medium term risk of complications from MitraClip use?
8) Are clinical outcomes with MitraClip associated with particular patient characteristics (clinical or demographic)?
9) What are the full procedural costs of using MitraClip to the NHS?
10) What costs savings might occur in the NHS as a result of MitraClipTM therapy?
11) Is MitraClip cost-effective from the perspective of the NHS?

It is intended that the data reported from the registries will be used to part inform an update of IPG 309
(The NICE Interventional Procedures Guidance on MitraClip), which will be reviewed by NICE, in light of the
CtE registry findings.

Separately, NHS England Commissioning Policies for all 3 cardiac procedures will also be reviewed, with a view to future patient access to these treatments.

Yielded Benefits:

There were a number of benefits realised once the work had been completed: 1) The ability to look at cardiovascular admissions which may be related to, and affected by, the medical management of a patient’s condition. This will provide a much more detailed and complete picture of readmissions, and help determine the full impact of the original treatment on readmission rates and mortality outcomes. 2) The ability to evaluate readmission rates and reasons for readmission will be extremely beneficial to commissioners, healthcare economists and regulatory bodies such as NICE in terms of assessing the long term effects on patients undergoing the various cardiac procedures. It will allow assessment of the effect of different variables on these outcomes and the assessment of the total burden of care, thereby aiding an analysis of cost effectiveness. 3) To provide additional insight into outcomes (especially adverse reactions such as stroke) which Barts Health (NICOR)/NUTH can then include in any reports used to inform quality improvement work/evaluation of new health technology. Linkage to the HES dataset would allow further exploration of the geographic, socio-economic and organisational data of patients in much more detail. This may lead to a better understanding of commissioning patterns within the UK. In addition, the HES dataset collects information on augmented care and the patient care pathway. 4) To identify relevant safety and efficacy outcomes that were not known to the clinicians undertaking the procedures in the tertiary centres because the relevant episodes of care took place in other hospitals. Should these treatments become routinely commissioned, these types of outputs will be useful for future reports derived from data collected by NICOR. At present, for LAAO and PFOC, two reports have been submitted to NHS England using registry data alone, describing patient outcomes such as mortality and post-procedure neurological events, which have been reported by the centres following up their patients. The MitraClip report was also to NHS England in February 2018 and described patient outcomes such as mortality and post-procedure events requiring hospital readmission. It has been vital to use the Civil Registration and HES data, linked to each registry for realising the following benefits: (i) to confirm that all deaths and post-procedure hospital readmissions (for neurological / cardiac events) have been captured in the registry. NICOR do not have 100% follow up of CtE cases - so do not know if there is missing information for many patients post-procedure. (ii) where additional events are identified in Civil Registration and HES, the combination of registry-reported outcomes and Civil Registration / HES recorded outcomes will validate the mortality rates and efficacy measures (stroke prevention rates and cardiac outcomes) of these 3 procedures and provide more robust data to NHS England. These data will directly inform NHS England's commissioning policy decision-making, which will determine patient access to these procedures in future. Where there have been discrepancies between the registry and HES/Civil Registration recorded data NICOR have endeavoured to take additional steps to validate the registry data (particularly where there has been perceived 'safety issue'.

Expected Benefits:

There are a number of expected benefits:
1) The ability to look at cardiovascular admissions which may be related to, and affected by, the medical management of a patient’s condition. This will provide a much more detailed and complete picture of readmissions, and help determine the full impact of the original treatment on readmission rates and mortality outcomes.

2) The ability to evaluate readmission rates and reasons for readmission will be extremely beneficial to commissioners, healthcare economists and regulatory bodies such as NICE in terms of assessing the long term effects on patients undergoing the various cardiac procedures. It will allow assessment of the effect of different variables on these outcomes and the assessment of the total burden of care, thereby aiding an analysis of cost effectiveness.

3) To provide additional insight into outcomes (especially adverse reactions such as stroke) which Barts Health (NICOR)/NUTH can then include in any reports used to inform quality improvement work/evaluation of new health technology. Linkage to the HES dataset would allow further exploration of the geographic, socio-economic and organisational data of patients in much more detail. This may lead to a better understanding of commissioning patterns within the UK. In addition, the HES dataset collects information on augmented care and the patient care pathway.

4) To identify relevant safety and efficacy outcomes that were not known to the clinicians undertaking the procedures in the tertiary centres because the relevant episodes of care took place in other hospitals.

Should these treatments become routinely commissioned, these types of outputs will be useful for future reports derived from data collected by NICOR.

The NUTH will perform an updated literature review and analysis of the clinical data and will provide a report to NHS England aimed at answering the specific service evaluation questions. The answer to some of these questions is dependent on the ONS and HES linked data.

At present, for LAAO and PFOC, two reports have been submitted to NHS England using registry data alone, describing patient outcomes such as mortality and post-procedure neurological events, which have been reported by the centres following up their patients. The MitraClip report will be submitted to NHS England in February 2018 and will describe patient outcomes such as mortality and post-procedure events requiring hospital readmission. At present, this too will contain registry data alone.

However, ONS and HES data, linked to each registry, are vital to:
(i) confirm that all deaths and post-procedure hospital readmissions (for neurological / cardiac events) have been captured in the registry. NICOR do not have 100% follow up of CtE cases - so do not know if there is missing information for many patients post-procedure.
(ii) where additional events are identified in ONS and HES, the combination of registry-reported outcomes and ONS / HES recorded outcomes will validate the mortality rates and efficacy measures (stroke prevention rates and cardiac outcomes) of these 3 procedures and provide more robust data to NHS England. These data will directly inform NHS England's commissioning policy decision-making, which will determine patient access to these procedures in future. NHS England has scheduled the review of all 3 procedures as part of their annual commissioning round and has funded these CtE procedures (2014-2017) to obtain "real world" data on outcomes for patients treated in the NHS setting.

The review of the initial NHS experience with these treatments aligned to an updated review of the world literature will enable NHS England Specialised Commissioning to update its commissioning policies regarding the use of the MitraClip, LAAO and PFOC procedures.

Outputs:

Aggregate data with small numbers suppressed in line with the HES Analysis Guide which has been derived from the data in this application will be contained within reports published in 2018. These reports are presented to NICE and NHS England. They may also be made available to other stakeholders. The reported data may also be visualised in various formats on-line, as relevant to the stakeholders. No record level data or patient identifiable data will be released in any report. The publication date for these outputs is early 2018. (Results from authorised work may also be subsequently published in peer-reviewed journals).

NICOR already receive data under DARS-NIC-359940-W1R7B to complete six national cardiovascular audits. Specific outputs from that agreement include:
1) Making the comparisons of disease/treatment outcome by hospital as well as any relevant comparisons between journeys of care.
2) Adjust the analysis used for 1 (above) to ensure that 'risk' is taken correctly into account.
3) As part of the registry dataset, national data is added on the treatment/disease the researcher is interested in to ensure that they have data for all patients.
4) Analysis is also provided directly to NICE to enable them to make a decision as the whether the device/treatment should be included in national guidelines.

It is hoped that similar outputs will be achieved with the data requested in this agreement. Please note that the data under this agreement NIC-151212 will not be linked to the NHS Digital data held under other agreements.

NICOR provides monthly reports to NUTH.

The primary purpose of the ONS/HES linked data is to inform the CtE programme.

All published reports are made available on the NICOR website. This only happens once the funder has reviewed and approved the report for publication.

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

Through a specifically designed database, NICOR receives patient identifiable data collected by NHS Hospital Trusts about patients who have had a Mitraclip, LAAO and PFOC together with data about the treatment itself and outcomes both to hospital discharge and during predetermined follow-up periods. From the agreed dataset, those
fields needed to answer the specific evaluation questions are provided to the NUTH. No patient identifiable data is shared with NUTH. The datasets for the three registries are available on the NICOR website.

NICOR will send the following identifiers to NHS Digital for NHS Digital to provide NICOR with linked ONS mortality and HES data:
Member Number
Name (both forename & surname)
Postcode
NHS Number
Gender
Date of Birth

This data is then linked to HES Admitted Patient Care data. HES APC data will be used to evaluate frequency and duration of re-admissions and pre-admissions for patients recorded in the above mentioned registries. The OPCS4 and ICD10 codes are requested for each linked patient. These will be used to search for any episodes of stroke/cardiovascular event, postcardiac CtE procedure etc. and also linked to HES ONS data to find out if any of the cohort has died.

ONS data will be used, firstly, to identify patients who have died out of hospital, or in between follow-up appointments, where their deaths may not be known by their treating centre (therefore missing from the registry follow up data). This will validate the mortality rate found using registry data alone. Secondly, to confirm registered cause of death and determine whether this is of neurological or cardiac origin. This will allow the study to determine how many of the deaths in these patients may be attributed to failure of the procedure, or another cause.

The ONS/HES linked data (returned to NICOR). Member number is the only identifiable data returned. The senior developer will then re-link the member number to the identifiers. Once the initial analysis has taken place, all identifiers are stripped from the data. All data are securely stored on a departmental shared drive, which is restricted to staff working on the project. The nominated staff (substantive employees of NICOR) have varying levels of permissions to view and access the data depending on their position and involvement.

The ONS/HES linked data transferred from NICOR to NUTH contains no patient identifiers and will be stored securely within the NUTH network which has access protected in accordance with the NUTH ‘Network Security & Access Control Policy’. Access to the data will be restricted to authorised staff working on the project.

The York Health Economics Consortium (YHEC) is not involved in any data processing - they will only receive aggregated (in line with the HES analyses guide) outputs of the analyses from NUTH such as mortality rates and hospital readmission rates, to be used as inputs to their economic modelling work for NHS England.

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 ie: employees, agents and contractors of the Data Recipient who may have access to that data).

All processing of ONS data will be in line with ONS standard conditions.


Project 7 — DARS-NIC-07205-H2D1K

Opt outs honoured: Y, N ()

Legal basis: Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012)

Purposes: ()

Sensitive: Sensitive

When:2016.12 — 2017.02.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - Cause of Death Report

Objectives:

1. To establish whether women who should have been recalled for breast screening and were not, have died from breast cancer, possibly resulting from inappropriate ceasing of screening.
2. To establish whether any women who are recorded as having died are in fact still alive and not being offered breast screening and are at risk of an undetected cancer progressing.

Following the identification of an SUI in 2011 relating to the incorrect removal (‘inappropriate ‘ceasing’) of a woman from the breast screening programme by the Central and East London Breast Screening Service (CELBSS) it was agreed that an audit should be undertaken of all women with a ‘ceased’ status for breast screening within the Central and East London Breast Screening Service and related Exeter databases. The total number of women in the audit was 2299. That audit has been completed, with the exception of those women recorded as being deceased, a number of whom were ceased from the programme before their death.

1019 were recorded as deceased by the breast screening programme. Barts are seeking more information on that cohort, to confirm they have deceased and whether they died of breast cancer. Barts will provide the complete details of those women to HSCIC.

Once Central East London Breast Screening Service receive the data set from HSCIC, it will pseudonymised (Pseudo-ID, fact and cause of death) and pass it to PHAST to produce a dataset specifying those who died, those who died of breast cancer and those still alive.
PHAST is a not-for-profit consultancy and they have identified a clinician and an analyst who have honorary contracts with Barts Health and will only view anonymised data within the location specified in this agreement.

Once Central East London Breast Screening Service has completed the audit the data will be disposed of appropriately.

The legal basis for the data in the cohort is covered under direct care pathway due to the clinical relationship that Barts have with the patients.

Expected Benefits:

The avoidance of harm to women who should have been offered breast screening, but remain outside the programme. These women could be offered screening as soon as they are identified with the data provided.
Establishing whether significant harm resulted from the incorrect removal from the programme, such that women had an undetected cancer which killed them. Not only is this important information for the service, patient’s families have a right to know.
There will be no commercial benefits from this work. It is not research and will not be published in a scientific journal.

Outputs:

Barts will receive from PHAST a database that will include pseudo ids and the categories the patients fall into. For those patient still alive, the data will be re-identified to ensure screening is taking place.
Given the time that has elapsed seeking these data, the sooner the better to minimise the chance of continuing harm to patients.

Processing:

Barts NHS Trust to provide a cohort of patients through to the HSCIC where the HSCIC will provide back patient status from the ONS Mortality database matching only to those persons who are in the originally supplied cohort.


Project 8 — DARS-NIC-226652-N1G2N

Opt outs honoured: Y ()

Legal basis: Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012)

Purposes: ()

Sensitive: Non Sensitive, and Sensitive

When:2016.04 — 2016.08.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - Flagging Current Status Report
  2. MRIS - Cause of Death Report

Objectives:

1. To establish whether women who should have been invited for breast screening and were not, have died from breast cancer, possibly resulting from inappropriate ceasing of screening.
2. To establish whether any women who are recorded as having died are in fact still alive and not being offered breast screening and are at risk of an undetected cancer progressing.

Background
Following the identification of an SUI in 2011 relating to the incorrect removal (‘inappropriate ‘ceasing’) of a woman from the breast screening programme by the Central and East London Breast Screening Service (CELBSS) it was agreed that an audit should be undertaken of all women with a ‘ceased’ status for breast screening within the Central and East London Breast Screening Service and related Exeter databases. The total number of women in the audit was 2299. That audit has been completed, with the exception of those women recorded as being deceased, a number of whom were ceased from the programme before their death. 1019 were recorded as deceased by the breast screening programme. We are seeking more information on that cohort, to confirm they have deceased and whether they died of breast cancer. We can provide the complete details of those women to HSIC.

Expected Benefits:

The avoidance of harm to women who should have been offered breast screening, but remain outside the programme. These women could be offered screening as soon as they are identified with the data provided.
Establishing whether significant harm resulted from the incorrect removal from the programme, such that women had an undetected cancer which killed them. Not only is this important information for the service, patient’s families have a right to know.
There will be no commercial benefits from this work. It is not research and will not be published in a scientific journal.

Outputs:

A dataset providing name, date of death, and cause of death if it was breast cancer. Given the time that has elapsed seeking these data, the sooner the better to minimise the chance of continuing harm to patients.

Processing:

Once we receive the data set, we will anonymise it and pass it to PHAST to produce a dataset identifying those who died and date of death, of those, those who died of breast cancer and date of death and those still alive.
PHAST is a not-for-profit consultancy and they have identified a clinician and an analyst who have honorary contracts with Barts Health and will only view anonymised data.
Once we have completed the audit the data will be disposed of appropriately.