NHS Digital Data Release Register - reformatted

Guy's And St Thomas' NHS Foundation Trust projects

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

🚩 Guy's And St Thomas' NHS Foundation Trust was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. Guy's And St Thomas' NHS Foundation 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.

Non-Hodgkin Lymphoma in Young Adults A Prospective UK population-based study of incidence, treatment and outcomes. (ODR1516_460) — DARS-NIC-656771-F4K5X

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, Identifiable (Mixture of confidential data flow(s) with consent and non-confidential data flow(s))

Legal basis: Other-The Health Service (Control of Patient Information) Regulations- Regulation 2, Consent (Reasonable Expectation); Other-The Health Service (Control of Patient Information) Regulations- Regulation 2

Purposes: No (NHS Trust)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2024-03-15 — 2024-09-15

Access method: One-Off

Data-controller type: GUY'S AND ST THOMAS' NHS FOUNDATION TRUST

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations

Objectives:

***This agreement permits Guy's and St Thomas' NHS Foundation Trust to retain data which was historically disseminated by Public Health England (PHE) for the following study - 'Non-Hodgkin lymphoma (NHL) is the least understood of the haematological malignancies that occur during the transitional ‘young adult’ decade between ages 15 and 25 years'. No further processing beyond that supporting the secure retention of the data is permitted under this Agreement. ***

Non-Hodgkin lymphoma encompasses a spectrum of lymphoid neoplasms that together are the fifth most common malignancy occurring in young adults in the UK. From 1995 to 2006 the English Cancer Registries recorded an average of 120 cases of NHL per year, in 16 to 25-year-olds inclusive, but excluding cases in Scotland and Wales. The aggressive lymphomas, diffuse large B-cell lymphoma (DLBCL) and Burkitt lymphoma (BL) comprise 60% of the total, followed by anaplastic large cell lymphoma (ALCL) and T-lymphoblastic lymphoma (T-LBL). Other types of NHL occurring at this age, follicular lymphoma and cutaneous T-cell lymphoma, appear to be more indolent than in older adults.

Lymphoma diagnosis has advanced substantially with the advent of molecular and genetic markers. Consequently, the true incidence of the individual NHL types as currently defined is unknown. To compound the uncertainty NHL diagnosis remains difficult, particularly at this age where the relative proportions of aggressive NHL types shift from a childhood to an adult pattern. Cancer registry data for this age record a significant proportion as ‘NHL, not otherwise specified’.

Information about treatment outcome using standard regimens is scanty, in part because this age group has the lowest trial entry outside the very elderly, with only 16% being recruited into available trials. Poor trial entry has been cited as the likely reason for the failure of adolescent and young adult (AYA) patients to benefit from the improvements in cancer survival which have occurred in younger and older patients over the past 10-15 years; the ‘AYA Gap’. Cancer registry mortality data, show worse survival for patients aged 15-24 compared to children, for all lymphomas combined and for DLBCL and lymphoblastic lymphomas.

A widely held explanation for this inferior curability through adolescence is that, in addition to changes in the relative frequency between NHL types, there is a change in biology within individual diseases, leading to greater chemotherapy resistance. An alternative explanation for the poor treatment outcomes is the difference in therapeutic approach used by paediatric and adult oncologists for the most commonly occurring aggressive lymphomas, as seen for older teenagers and young adults with ALL.

There is lack of information on treatment and outcomes specific for this age group. Evidence from Ontario (Canada) has demonstrated that place of treatment, and by inference treatment used, influences the outcome of NHL more than for any other malignancy at this age. All this adds urgency to resolve uncertainty around the interaction of age, biology, and therapy on treatment outcomes for young adults with NHL. A recent review urges for “real time” collection and analysis of treatment and outcome data as the most effective way to form hypotheses and evolve treatment strategies. Not only is this a rapid way to provide immediate patient benefit through optimising treatments, it is also better for early identification of toxicities and late effects than more traditional retrospective analysis. Others have highlighted the need for tissue samples to be made available for detailed biological analysis to improve treatment and outcomes.

The UK, with its young adult cancer treatment network, is in a unique position to collect national population-based data on NHL diagnosis, treatment and outcome to fill this void. Our study design will provide the basis to improve clinical care, as well as set the agenda for future research into this complex group of young adult tumours.

Study Aims
1. To establish the incidence of the different subtypes of non-Hodgkin lymphoma (NHL), defined by currently accepted diagnostic criteria, in older teenagers and young adults in the UK.
2. To document treatment regimens being used and related outcomes for each NHL type in a prospective three-year cohort, as a scoping study to inform future treatment recommendations and to inform rational clinical trial design.
3. To establish a diagnostic tissue resource, with linked clinical data, for future study.

Study population:
The study will capture diagnosis and treatment data for all patients with NHL diagnosed between their 15th and 30th birthdays in England, Wales, and Scotland over a 3-year period (2015-2017) with clinical outcomes collected for a minimum 2 years following diagnosis. The data held under this Agreement covers those diagnosed in England only.

While the primary target age is 16 to 24 years inclusive, we will extend the age range to include 15 to 29 years inclusive, to encompass fully the period of biological transition. This also matches the US SEER incidence and survival statistics, 1975-2000. Based on registry data, over 3 years we estimate that we shall recruit 400 patients aged 16 to 24 years, and 650 patients aged 15 to 29 years inclusive. NHL disease types: All diseases classified as non-Hodgkin Lymphoma will be included.

Expected Benefits:

This research will improve understanding of NHL in this age group, help identify the most effective treatments for each NHL subtype, inform the design of future clinical trials, and lead to more young people with NHL being cured with toxicity-free long term survival.

Processing:

***This agreement permits Guy's and St Thomas' NHS Foundation Trust to retain data which was historically disseminated by Public Health England (PHE) for the following study - 'Non-Hodgkin lymphoma (NHL) is the least understood of the haematological malignancies that occur during the transitional ‘young adult’ decade between ages 15 and 25 years'. No further processing beyond that supporting the secure retention of the data is permitted under this Agreement. ***

Three sources of information were used to identify patients:
i) British Lymphoma Pathology Group (BLPG). For early identification of patients, optimal for prospective treatment data collection, we have sought support from the BLPG, whose members review >90% of all NHL cases in the UK to make or confirm the diagnosis. The group members are supportive in principle of individually notifying the study co-coordinator when they identify a new patient. The BLPG, as an organisation, will encourage but not coordinate participation.
ii) Principal Treatment Centre TYA MDTs. The clinical teams at all Principal and larger Designated TYA Centres will be asked to notify new patients to the study coordinator at diagnosis.
iii) Public Health England National Cancer Registration Service (for which this agreement covers)

Public Health England provided information on all reported cases of NHL within the study age range (England and Wales), to capture those patients not otherwise identified. This may be particularly important for patients diagnosed at age 25 and older.

KHP Data Analytics and Modelling COVID-19 Research data warehouse — DARS-NIC-381719-L6D2H

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant (Statutory exemption to flow confidential data without consent)

Legal basis: CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Health and Social Care Act 2012 - s261(5)(d)

Purposes: No (NHS Trust)

Sensitive: Non-Sensitive

When:DSA runs 2021-02-08 — 2021-09-30

Access method: One-Off

Data-controller type: GUY'S AND ST THOMAS' NHS FOUNDATION TRUST, KING'S COLLEGE HOSPITAL NHS FOUNDATION TRUST

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Critical Care
  2. Hospital Episode Statistics Critical Care (HES Critical Care)

Objectives:

With the spread of novel COVID-19 in the UK since January 2020 there is a rapid need to undertake research to inform the clinical response. Guy’s and St Thomas’ (GSTT) and King’s College Hospital NHS Foundation Trusts (KCH) have been initially at the epicentre of the UK pandemic, and it is anticipated that there will be significant ongoing activities within these trusts as subsequent waves develop. In line with HDRUK championing the use of health data to support research and innovation that addresses challenges presented by the COVID-19 pandemic, GSTT and KCH have set up a KHP COVID Data Analytics & Modelling Group and have established a Research Data Warehouse. Both trusts are part of King’s Health Partners (KHP). Linking the Research data warehouse with nationally collected data sets will allow the development of risk calculators for primary care that would help with investigating best treatment plans for individuals throughout their entire experience with Covid-19.

GSTT and KCH are the data controllers for this project.

The purpose of this programme is to utilise the electronic health records (EHRs) to identify patients tested for COVID-19, Influenza and for respiratory pathogens routinely tested for in the KHP laboratories for those attending with respiratory illness and describe them phenotypically - allowing tracking and comparison of disease progression, care, initial and long term outcomes. Therefore - a wide range of research questions can be asked and answered using this data.

Routine data to be collected includes clinical, laboratory and demographic data from all patients tested for COVID-19, Influenza and other respiratory pathogens (e.g Parainfluenza, Legionella). All data as specified for these patients from 01/01/2016 onwards will be available.. All projects requesting access to the data within the data warehouse will be COVID-19 only focused only
The finalised dataset available in the datawarehouse would include, but will not be limited to:
• Patient history and co-morbidities
• Observations
• Pathology test results
• Demographics
• Prescription data
• Imaging data

Research questions will be discussed and agreed by a core group of clinicians and academics including the Chief Clinical Information Officer and R&D Director. Each question will have clinical input from appropriate persons e.g. ICU consultant. Given the exceptional circumstances of this public health crisis, an expedited review process for all data access requests will be used. Data minimisation principles will be followed for each release of data.
Data will only be permitted to be analysed by a member of Kings Health Partners (KHP). Both trusts mentioned in this agreement are part of King’s Health Partners (KHP), as well as the University.

This programme will utilise clinical and academic expertise across Kings Health Partners (KHP).
KHP brings together a world leading research led university Kings College London, and three successful NHS Foundation Trusts: Guy’s and St Thomas’, King’s College Hospital and South London and Maudsley.

KHP is one of only eight Academic Health Sciences Centres in England designated by the Department of Health. These include:
• Bristol Health Partners
• Cambridge University Health Partners
• Imperial College
• Manchester
• Newcastle Health Innovation Partners
• Oxford Academic Health Partners
• UCL Partners

Only data from KCH and GSTT will be involved in this project, as South London and Maudsley is a Mental health service provider.
The three founding trusts serve a local population which is among the most ethnically, socially and economically diverse in the world. Together they provide a full range of medical and healthcare services, from acute and specialist medical care, local and highly specialised mental healthcare, and services that promote physical and psychological wellbeing.

Linkage with the Hospital Episode Statistics Critical Care data would allow for tracking repeat admissions into GSTT, post and prior COVID-19 diagnosis, Influenza and other respiratory pathogens while providing information on admissions to critical care units besides GSTT.

All linkage will enable better understanding on long term healthcare, utilisation, and outcomes and will allow for a better understanding and prediction of future healthcare requirements.

Studying longer term outcomes will allow an assessment of new policy changes to healthcare or the implementation of a new therapy. There is a risk of Covid-19 being with us for an extended period of time, and investigating the relationship between treatments in primary and secondary care will be crucial in handling any future waves of the epidemic, and is necessary for reasons of public interest in the area of public health. None of the research uses identifiable data.

All data is pseudonymised at source, and data linkage will occur within the GSTT fire wall.

Data requested from NHS Digital will include the HES Critical Care data set, to track long term outcomes of patients tested/treated for Covid-19, flu and other respiratory pathogens and subsequent Critical Care admissions and outcomes. The full HES Critical Care data set, for patients tested for Covid-19, Flu and other respiratory pathogens is requested. Data minimisation standards will be adhered to, as only data from January 2020 onwards would be requested, and only for the patients specified. As Covid-19 is likely to be with us for some time, and there is uncertainty around the long term effects of this disease, the patient level data request would be for most data up until the most recent poitn available - looking for Critical Care treatment In the future.

The use of the data described received ethical approval in July 2020 and meets all the required ethical and legal requirements. This data is secondary use, and processing outside of GDPR requirements would be unlawful. The risks around confidentiality are low, Data processing and storage of the source data will be within the trust firewall meeting all security requirements of GSTT. Data released for analysis will be pseudo-anonymised. All steps for data minimisation, secure transfer, storage and access will be adhered to.

Data acquisition would not involve the capture of any new data. Instead it would involve cataloguing EHR data and standardising it in such a way that it has the potential to be aggregated.

The finalised dataset made available to researchers at GSTT/KCH/KCL would include the following hospital data, linked to the critical care data provided by NHS Digital :

• Patient history and co-morbidities
• Observations (Including blood panels and vital signs)
• Pathology test results
• Demographics (including gender, age, index of multiple deprivation)
• Prescription data
• Imaging data (including x-ray and CT scan data)
• Primary care data from Lambeth data net (including data on long term conditions, medications, vaccination history and demographics)

GSTT has obtained generic ethical approval for research projects using the stored data, under conditions agreed with the Research Ethics Committee (REC), without requirement for KHP researchers to apply individually to the REC for approval, for COVID-19 projects only.

An example of such projects would be:
- Impact of ethnicity on outcome of severe COVID-19 infection. Data from an ethnically diverse UK tertiary centre, IMD effects of outcomes of Covid -19.
Association between Renin-angiotensin-aldosterone system (RASS) inhibitors and clinical outcomes in patients with COVID-19: a cohort study in London).

All data requests will require an application, that will be discussed and agreed by a core group of clinicians and academics including the Chief Clinical Information Officer and Research & Development Director.

Each question will have clinical input from appropriate persons e.g. ICU consultant, and each request must be approved by this group before any data is released.

Once an application has been approved, selected data points will be made available for researchers in a secure, restricted access KCL supported platform in which to undertake the analysis.

Data minimisation principles will be followed for each release of data. Data will only be permitted to be analysed by a member of KHP. No data will be shared with any other organisations not mentioned in this agreement. Only data points specifically required for each project will be requested/released. Identifiable data will not be available to researchers.

A log of all questions will be maintained and will be reported annually to the REC and to the host Research & Development department via the annual progress report.

All data transfers for research/investigative purposes will be logged and linked to the research questions. Data transfers will be covered by data sharing agreements confirming the terms and conditions of transfer where applicable.

Access to data will include researcher data retention and limit use to a particular study or set of studies.
All research/studies will be COVID19 related only.

All data are copies of data held in clinical systems, there is no obligation to retain these data. In line with NHS guidance if the project were to end, Data would be securely deleted.

Data controllers: Guys and ST Thomas NHS Foundation Trust, Kings College Hospital NHS Foundation Trust
Data Processors: Certain members of KHP including Guys and St Thomas NHS Foundation Trust, Kings College Hospital NHS Foundation Trust, and KCL (King's College London)

The legal basis relied on for processing under the General Data Protection Regulation (GDPR) is Article 6 (1)(E) - (processing is necessary for the performance of a task in the public interest or in the exercise of official authority vested in the controller) and Article 9 (2)(I) ("Processing is necessary for reasons of public interest in the area of public health, such as protecting against serious cross-border threats to health or ensuring high standards of quality and safety of health care and of medicinal products or medical devices, on the basis of Union or Member State law which provides for suitable and specific measures to safeguard the rights and freedoms of the data subject, in particular professional secrecy";) as the legal basis to process special category data (health data). Both data controllers for this project are considered public bodies as they are health care trusts - therefore can rely on Article 6 (1)(E). The projects this data will be used for are solely related to COVID-19, a current worldwide pandemic, therefore meeting the criteria as necessary for the interest of public health.

Expected Benefits:

With the spread of novel COVID-19 in the UK since January 2020 there is a rapid need to undertake research to inform the clinical response. Guy’s and St Thomas’ (GSTT) and King’s College Hospital NHS Foundation Trusts (KCH) are at the epicentre of the UK pandemic having seen over 4000 patients at the time of writing. This is in line with HDRUK who are championing the use of health data to support research and innovation that addresses challenges presented by the COVID-19 pandemic.

All linkage will enable understanding of long term healthcare utilisation and outcomes and will allow for a better understanding and prediction of future healthcare requirements. Studying longer term outcomes will allow an assessment of new policy changes to healthcare or the implementation of a new therapy. There is a risk of Covid-19 being with us for an extended period, and investigating the relationship between treatments in primary and secondary care will be crucial in handling any future waves of the pandemic and is necessary for reasons of public interest in the area of public health.

Out puts generated using this data will allow for more informed information around treatments, risk factors and severity of disease. Outputs of these messages to be communicated with the scientific and medical community as well as the public and patients.

Benefits to medical community and patients of this information would be to allow more well informed decisions with regards to Covid-19. For example, one project will be looking at the impact of symptom on set date and hospital presentation and comparing with future presentations. This particular project (amongts othrs) has the potential to inform medical staff at the front door, and of patients and public of when is a more demonstrably advantageous time to present given severity and length of symptoms.

GSTT have previously engaged with the GSTT Biomedical Research Centre Public and Patient Involvement Advisory Group and have sought their opinions on the sharing, collection and use of data in research. A FAQ (Frequencly Asekd Questions) session on data concerns of the patients has been completed and is available on the GSTT BRC website. Please see here:
https://www.guysandstthomas.nhs.uk/research/patients/use-of-data.aspx

Outputs:

The following may be produced because of this data processing:
a. Reports as requested
b. Submissions to peer reviewed journals
c. Presentations
d. Conferences as requested and as it is feasible.
e. Development and implementation of prediction tools and algorithms

Examples of such would be:

- Submissions around looking at symptom onset date before hospital presentation, outcome impact
- Algorithms around Prediction which patients have COVID19 based on presentation/’at the door’ symptoms and preliminary tests results, to enable accurate traiging of patients.
- Aggregate level data (with small number suppression applied in line with the HES analysis guide) would be contained in these outputs only.
Data will always be released at a high enough level of aggregation to prevent others being able to ‘recognise' a particular individual.

Each research project will aim to have their own website with contact details and key results. Research Snapshots will also be published. These are summaries of projects suitable for patients and lay audiences. The Research Database team will maintain a publicly accessible register of research projects using data from the database on the GSTT Biomedical Research Centre website. For transparency and interaction, the Health Reasearch Authority are publicly publishing a list of all COVID-19 NHS REC approved studies which is already live here: https://www.hra.nhs.uk/covid-19-research/approved-covid-19-research.

Processing:

All data flows will be at a patient level.

NHS Number, Local Identifier (Study ID), Gender, Date of Birth and postcode will be transferred to NHS Digital from GSTT. The cohort will consists of people who were admitted to GSTT and KCH since January 2020 and were tested for CV19 and other respiratory pathogens as described above.

NHS Digital will return a pseudonymised data set back to GSTT - including a study ID (all other identifiers removed) and the HES Criticial Care dataset from 19/20 onwards.

It is anticipated this process will be of an adhoc nature, and routine flows will not be required from NHS Digital (ie - data is not required on a repeat routine quarterly basis)

Once HES data is linked to the GSTT Data, using the local identifier (Study ID), all data minimisation standards, and pseudonymisation and transformation will take within the GSTT fire wall, before data is realised for analysis.

Data is pseudonymised and linked by GSTT within the GSTT firewall. Statistical analysis will take place within secure KCL research environments. All data that is made available for analysis will be separated from source data, and re linkage will not be possible.

There will be no requirement/attempt to re-identify individuals.

All data requests will require an application, that will be discussed and agreed by a core group of clinicians and academics including the Chief Clinical Information Officer and R&D Director. Each question will have clinical input from appropriate persons e.g. ICU consultant, and each request must be approved by this group before any data is released.

Given the exceptional circumstances of this public health crisis, an expedited review process for all data access requests will be used

Data requests will only be granted for applications related to CV19 research.

Once an application has been approved, selected data points will be made available for researchers in a secure, restricted access KCL supported platform in which to undertake the analysis.

All data transfers for research /investigative purposes will be logged and linked to the research questions. Data transfers will be covered by data sharing agreements confirming the terms and conditions of transfer where applicable.

All data processing is only carried out by substantive employees of the data processor, GSTT, KCH or KCL or data controller, GSTT or KCH. All staff have been appropriately trained in data protection and confidentiality.

All data will be accessed using remote desktop access onto the secure research environments within KCL. Access to data within GSTT will also be through secure remote desktop connections into the GSTT/KCH fire walls.

A log of all research questions and projects will be maintained and will be reported annually to the REC and to the host Research + Development department via the annual progress report.

Transforming Cancer Services Team for London access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-228903-Z0F4V

Type of data: information not disclosed for TRE projects

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

Purposes: No (NHS Trust, Agency/Public Body)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-12-23 — 2020-12-22 2020.01 — 2024.11.

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: GUY'S AND ST THOMAS' NHS FOUNDATION TRUST, NHS ENGLAND (QUARRY HOUSE), NHS SOUTH EAST LONDON ICB - 72Q

Sublicensing allowed: No

Datasets:

  1. National Cancer Waiting Times Monitoring DataSet (CWT)
  2. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)

Objectives:

This agreement is for Guy's and St Thomas' NHS Foundation Trust (Hosting the Transforming Cancer Services Team (TCST) London) to access the National Cancer Waiting Times Monitoring Data Set (NCWTMDS) via the Cancer Waiting Times system. Guy's and St Thomas' NHS Foundation Trust are the legal entity who host the Transforming Cancer Services Team London.

The Transforming Cancer Services programme was established April 2014 to provide strategic leadership, clinical advice, oversight, cohesion and guidance for implementing the National Cancer Strategy for London, Five Year Forward View and the Operational and Planning Guidance. This includes better cancer survival, expanded screening to improve prevention and early detection of cancer, introduction of primary HPV testing for cervical screening and faster tests, results and treatment for people with worrying symptoms.

The Transforming Cancer Services Team (London) aim to improve outcomes for patients through a pan-London clinically led, patient-centred collaborative approach.

The Transforming Cancer Services Team (TCST) in partnership with key stakeholder aims to deliver:
• Equity in access to treatment and reduced variation in outcomes, benchmarking and data;
• Sharing scarce expertise and capability;
• Sharing of good practice across London, prevents duplication of efforts, builds momentum, ensures co-ordinated approach;
• Working closely with the three cancer alliances in London and with NHS England specialist commissioning to deliver at scale across London
• Senior TCST team members linked with local STPs enabling local delivery and ensuring local ownership.
Workstreams in our programme include:
• In year delivery of cancer waits
• Diagnostics capacity, demand and optimisation
• Early Diagnosis
• Living With and Beyond Cancer
• Governance, Safety, Quality and Leadership
The Transforming Cancer Services Team (London) (TCST) vision is for all London residents to have access to world class care before and after a cancer diagnosis.

Delivery of cancer waiting time standards is a top priority for CCGs, STPs, NHS England and TCST. The Transforming Cancer Services Team (London) have supported systems across London to deliver improvements to cancer waits through provision of training and expertise, analytical tools to understand the 62 day pathway and sharing of good practice such as use of tools to right size a providers MDT coordinator/tracker workforce.

Cancer intelligence and analysis underpins the specialist expertise and targeted interventions provided by TCST. TCST is also able to support NHS England’s Cancer Transformation PMO in monitoring and reporting on pan-London cancer metrics through the work TCST undertakes. Design and decisions are undertaken by TCST.

The independent Cancer Taskforce set out an ambitious vision for improving services, care and outcomes for everyone with Cancer: fewer people getting Cancer, more people surviving Cancer, more people having a good experience of their treatment and care, whoever they are and wherever they live, and more people being supported to live as well as possible after treatment has finished.

Guy's and St Thomas' NHS Foundation Trust are the substantive employer for all TCST staff. They are, therefore, the data controller who processes data.

The Transforming Cancer Services Team London are not a Cancer Alliance. They provide London-wide support for improving cancer services (i.e. much broader geographical reach than a Cancer Alliance) and, in terms of cancer waiting times, they provide all the pan-London analysis across London, supporting NHS England, NHS Improvement and Sustainability and Transformation Partnerships (STPs), and working with Cancer Alliances in improving cancer waiting times.

The Healthy London Partnership fund the Transforming Cancer Services Team. The Healthy London Partnership is a partnership of London’s NHS service (Clinical Commissioning Groups, Health Education England, NHS England, NHS Digital, NHS Improvement, trusts and providers), the Greater London Authority, the Mayor of London, Public Health England and London Councils. The aims of the Healthy London Partnership is to work toward the common goals set out in the Better Health for London, NHS Five Year Forward View and the Devolution agreement.

The Healthy London Partnership fund the Transforming Cancer Services Team which is hosted within Guy’s and St Thomas’ NHS Foundation Trust.

The Transforming Cancer Services Team will be responsible for:
• A once-for-London approach to implementing the national strategy
• Providing subject matter expertise, evidence and intelligence for cancer commissioning support
• Working with partners to reduce variation and deliver improved cancer outcomes
• Primary care development and education
• Targeted service improvement in secondary care
• Monitoring breaches of the 62 day waiting time across London

The Transforming Cancer Services Team will analyse data to:
- Compare performance across London, by Cancer Alliance, Trust, STP and CCG.
- Benchmark
- Analyse breaches
- Support local clinical audits
- Support local service improvement
- Quantify treatment volumes

This is a holistic pan-London approach and will span 24 Trusts and 33 Clinical Commissioning Groups – although any outputs to these organisations would be aggregated with small number suppression.

Expected Benefits:

The Cancer Waiting Times standards are key operational standards for the NHS, which aim to reduce the waits for diagnosis and treatment for Cancer patients, which will support improvements to survival rates and improve patient experience. This includes the new 28 day faster diagnosis standard being introduced as a standard from April 2020.

In London a key enabler to achieve these standards, and thus improve survival and patient experience is the role of TCST to work with providers, commissioners and both local and national NHS bodies to understand and support the improvement of patient pathways. Access to the Cancer Waiting Times data as detailed in the above will enable TCST to have and support informed discussions with and between providers, commissioners, alliances and regional bodies, enabling the optimal allocation of resources to improve performance against these standards.

Improvement would be expected on an on-going basis with standards already in place for nine standards:-
• 2 week wait urgent GP referral – 93%
• 2 week wait breast symptomatic – 93%
• 31 day 1st treatment - 96%
• 31 day subsequent surgery – 94%
• 31 day subsequent drugs – 98%
• 31 day subsequent radiotherapy – 94%
• 62 day (GP) referral to 1st treatment – 85%
• 62 day (screening ) referral to 1st treatment – 90%
• 62 day upgrade to 1st treatment – locally agreed standard
In addition this access and use of data will be key in delivering the new 28 day faster diagnosis standard being introduced from 2020, with reports showing both completeness and shadow compliance with the standard being used to support uptake and understanding.

This access and the resulting outputs will enable TCST to undertake local analysis beyond the Cancer Waiting times operational standards, supporting improvements to Cancer patients pathways beyond those already achieved by improving performance against standard set. This could include reviewing times between treatments, or treatment rates.

The overall aim of this type of additional analysis would be to support improvements to Cancer patients survival and experience, as well as supporting of appropriate commissioning at the CCG, STP and specialist commissioner level.


Additional benefits include:
- The ability to re-design services, that will aid equity in access – The detailed analysis across all of London enables identification of which services are achieving rapid access for patients and enables us to share this good practice, both through London wide workshops and the established London wide working with cancer alliances, STPs and providers .

- Reduction variation in outcomes – This data enables identification of variation across London, for example where one part of London is achieving shorter waits for a particular cancer pathway where other parts of London are not. This is used to inform discussion in London wide meetings to understand why this is the case and what actions can be taken within London to reduce this variation .

- The ability to share expertise and capability across London and benchmark regionally – Benchmarking is a key reason for access to this data across London to provide ready comparisons across the region. Through close working with the three cancer alliances TCST undertakes once for London analysis that saves this being undertaken three times, and enables sharing of analytical expertise in cancer waits.

- Having a holistic pan-London view to enable closer working across STPs and Cancer Alliances – Pan London analysis underpins the strong working relationships we have across London and enables the Transforming Cancer Services team to provide the London wide support that CCGs and NHSE have commissioned TCST to provide.

Outputs:

Outputs fall into the following categories:

1) Pan-London Analysis to support delivery of Cancer Waiting Times standards. This can be viewed at Trust, Cancer Alliance, CCG and regional level across London – identifying elements of good practice and variation, and supporting clinical/commissioning discussions to improve patient pathways
a. Comparative Cancer Waiting Times performance at tumour group and individual tumour site (i.e. ICD10 code) level.
b. Analysis of Cancer Waiting Times performance by treatment modality to identify areas of variation and inform discussions.
c. Grouping length of waits for standards to inform discussions on going beyond constitutional standards
d. Analysis of free text and derived breach reason fields to identify trends in reasons for delays.
e. Analysis of flows of patients at local, alliance, regional and out of region level including analysis by provider trust site
f. Outlier identification including exceptionally long waits.
g. Longitudinal analysis of activity and performance to support commissioning discussions regarding flows between organisations.
h. modelling of future performance linked to regional service improvement work (local and regional).

2) Cancer Waits analysis (not directly linked to constitutional standards) for the aim of identifying variation which may impact Cancer patient’s outcomes or patient experience.

Previous work on this has included modelling effects of reallocation in secondary and tertiary centres, and comparisons of performance where intertrust transfer has been an element of their care pathway.

The overarching aim of all future analysis/outputs is to inform priorities and support commissioning to improve Cancer pathways including reducing Cancer incidence and mortality, improving Cancer survival, improving patient experience, improving service efficiency and meeting national constitution standards relating to Cancer patients.

The majority of these outputs will be repeated at monthly, quarterly or annual schedules depending on the reporting type.

Processing:

The Cancer Wait Times (CWT) system collects and validates the National Cancer Waiting Times Monitoring Data Set (NCWTMDS), allowing performance to be measured against operational Cancer standards. Data is validated and records merged to the same pathway to cover the period from referral to first definitive treatment for Cancer and any additional subsequent treatments.

The CWT system then determines whether the operational standard(s) that apply were met or not for the patient and the accountable provider(s). The CWT system holds NCWTMDS in a series of pre-aggregated static reports. These reports are available monthly and quarterly data (aligned with the National Statistics for Cancer Waiting Times published by NHS England). Users can query the CWT system to generate reports to feedback on the progress towards meeting these targets.

TCST will have access to the Cancer Wait Times (CWT) System at the regional level. The TCST will use the data to produce a range of quantitative measures (counts, crude and standardised rates and ratios) that will form the basis for a range of statistical analyses of the fields contained in the supplied data as defined by TCST. This will enable TCST to offer support to enable discussions between, commissioners, acute providers and the three London Cancer Alliances.

Only staff members of Guy's and St Thomas' NHS Foundation Trust will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on Guy's and St Thomas' NHS Foundation Trust servers and/or NHS England based servers (back-up storage only is provided by NHS England via their server). Role Based Access Control prevents access to data downloads to employees outside of the analytical team responsible for producing outputs; the intelligence team of the TCST.

The CWT system is hosted by NHS Digital, access to and usage of the system is fully auditable. Users must comply with the use of the data as specified in this agreement. The CWT system complies with the requirements of NHS Digital Code of Practice on Confidential Information, the Caldicott Principles and other relevant statutory requirements and guidance to protect confidentiality.

Approved users will log into the system via an N3 connection and will use a Single Sign-On (users are prompted to create a unique username and password).

TCST Users are not permitted to upload data into the system.

Access to the CWT system data is restricted to employees who are substantively employed by the TCST Hosts Data Controller (Guy's and St Thomas' NHS Trust) in fulfilment of their public health function.

Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.

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)

The Transforming Cancer Services Team will have user access based on the Pan-London footprint, (made up of CCGs listed under Data Minimisation below) to the Cancer Waiting Times System. The user will be able to access the provider extracts from the portal for any provider where at least 1 patient for whom they are the registered within the geographic region under data minimisation (below) for that individual's GP practice appears in that setting.

Although the user may have access to pseudonymised patient information not related to the Pan-London footprint, users must only process and analyse data for which they have a legitimate relationship

Access within the Transforming Cancer Services Team is limited to those with a need to process the data for the purposes described in this agreement. The Transforming Cancer Services Team will have multiple Pan-London footprint access as defined within the Data Minimisation section below:


DATA MINIMISATION

Transforming Cancer Services Team based on the geographical region below subject to:
• Patients who are normally registered and/or resident within any of the CCGs listed below (including historical activity where the patient was previously registered or resident in another commissioner).

NHS Barking and Dagenham CCG
NHS Barnet CCG
NHS Bexley CCG
NHS Brent CCG
NHS Bromley CCG
NHS Camden CCG
NHS Central London (Westminster) CCG
NHS City and Hackney CCG
NHS Croydon CCG
NHS Ealing CCG
NHS Enfield CCG
NHS Greenwich CCG
NHS Hammersmith and Fulham CCG
NHS Haringey CCG
NHS Harrow CCG
NHS Havering CCG
NHS Hillingdon CCG
NHS Hounslow CCG
NHS Islington CCG
NHS Kingston CCG
NHS Lambeth CCG
NHS Lewisham CCG
NHS Merton CCG
NHS Newham CCG
NHS Redbridge CCG
NHS Richmond CCG
NHS Southwark CCG
NHS Sutton CCG
NHS Tower Hamlets CCG
NHS Waltham Forest CCG
NHS Wandsworth CCG
NHS West Essex CCG
NHS West London CCG

TCST may access record level pseudonymised data which includes the system generated pseudo CWT patient ID and aggregate data with unsuppressed small numbers.
Any record level data extracted from the system will not be processed outside of the authorised users of the system.
Aggregated reports only with small number suppression can be shared externally

All access to data is auditable by NHS Digital.

Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204554-Y7F3H

Type of data: information not disclosed for TRE projects

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

Purposes: No (NHS Trust, Network)

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

When:DSA runs 2019-02-01 — 2020-01-31 2019.09 — 2024.11.

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: GUY'S AND ST THOMAS' NHS FOUNDATION TRUST

Sublicensing allowed: No

Datasets:

  1. National Cancer Waiting Times Monitoring DataSet (CWT)
  2. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)

Objectives:

This agreement is for the South East London Cancer Alliance to access Cancer Waiting Times data. However, the Cancer Alliance is not a legal entity - its staff (and those accessing the Cancer Waiting Times data) are substantively employed by Guys and St Thomas' NHS Trust . Guys and St Thomas' NHS Trust is therefore the lead organisation, and the data controller who processes data. In this agreement, therefore, all references to accessing the data refer to the legal entity - Guys and St Thomas NHS Trust.

Improvements for Cancer patients

The independent Cancer Taskforce set out an ambitious vision for improving services, care and outcomes for everyone with Cancer: fewer people getting Cancer, more people surviving Cancer, more people having a good experience of their treatment and care, whoever they are and wherever they live, and more people being supported to live as well as possible after treatment has finished.

Cancer Alliances

Cancer Alliances, which have been set up across England, are key to driving the change needed across the country to achieve the Taskforce’s vision. Bringing together local clinical and managerial leaders from providers and commissioners who represent the whole Cancer pathway, Cancer Alliances provide the opportunity for a different way of working to improve and transform Cancer services. Cancer Alliance partners will take a whole population, whole pathway approach to improving outcomes across their geographical ‘footprints’, building on their relevant Sustainability and Transformation Plans (STPs). They will bring together influential local decision-makers and be responsible for directing funding to transform services and care across whole pathways, reducing variation in the availability of good care and treatment for all people with Cancer, and delivering continuous improvement and reduction in inequality of experience. They will particularly focus on leading transformations at scale to improve survival, early diagnosis, patient experience and long-term quality of life. Successful delivery will be shown in improvements in ratings in the Clinical Commissioning Group (CCG) Improvement and Assessment Framework (IAF), including, importantly, in the 62 day wait from referral to first treatment standard.
https://www.england.nhs.uk/publication/ccg-iaf-methodology-manual/


Cancer Wait Times (CWT) system

The Cancer Wait Times (CWT) system collects and validates the National Cancer Waiting Times Monitoring Data Set (NCWTMDS), allowing performance to be measured against operational Cancer standards. Data is validated and records merged to the same pathway to cover the period from referral to first definitive treatment for Cancer and any additional subsequent treatments.
The CWT system then determines whether the operational standard(s) that apply were met or not for the patient and the accountable provider(s). The CWT system holds NCWTMDS in a series of pre-aggregated static reports. These reports are available monthly and quarterly data (aligned with the National Statistics for Cancer Waiting Times published by NHS England). Users can query the CWT system to generate reports to feedback on the progress towards meeting these targets.


South East London Cancer Alliance

Guys and St Thomas NHS Trust will directly access the Cancer Waiting Times System on behalf of South East London Cancer Alliance across South East London, which covers a population of 1.9 million people.

Guys and St Thomas NHS Trust works with health organisations across South East London including 3 acute providers, and 6 clinical commissioning groups.

Acute Providers

•Guys and St Thomas NHS Trust
•King's College Hospital NHS Foundation Trust
•Lewisham and Greenwich NHS Trust

CCGs
• Lambeth CCG
• Southwark CCG
• Lewisham CCG
• Greenwich CCG
• Bexley CCG
• Bromley CCG

Data access

The CWT system provides one organisation (the lead organisation) representing each Cancer Alliance, with access to the following;
a) Aggregate reports (which may include unsuppressed small numbers)
b) Pseudonymised record level data - users can directly download this data from the CWT system
c) I-View Plus tool

Lead organisations will only access patient records which fall within the Cancer Alliances' footprint of responsibility based on the patients' CCG of responsibility. This Cancer Alliance is limited to South East London Cancer Patients.

A) Aggregate reports including small numbers
Aggregate data is available in the form of reports at Provider (Trust) and Clinical Commissioning Group (CCG) level.
Small numbers may be included in the aggregate data reports and are essential for analyses carried out by lead organisations.

Investigating breaches
Guys and St Thomas' NHS Trust routinely monitor performance and standards using the CWT system, particularly in relation to breaches of the 62 day wait target. Due to the large number of potential Trust/CCG combinations, breach counts could result in small numbers as in some cases there are less than 6 breaches in a whole year. Given that financial penalties are linked to target breaches counts must accurately reflect the true percentage without suppression.

Mitigating risk of re-identification
Risk of disclosure is minimised as the dataset does not include patient demographics (increasing risk of re-identification) that may allow users to identify an individual e.g. there are no age, ethnic categories or geographic breakdowns based on patient postcode.

Additionally, the aggregation categories are such that the data is not at a lesser granular level e.g. the source NCWTMDS data collects information at ICD diagnosis code level, but the CWT system aggregates at tumour group level – e.g. Head & Neck, Upper GI, lower GI, Breast etc.

B) Pseudonymised record level extracts
Lead organisations will access record level pseudonymised data which includes the system generated pseudo CWT patient ID.

Any record level data extracted from the system will not be processed outside of the authorised users of the system.

C) i-View Plus
iView Plus uses cube functionality to allow lead organisations to produce graphs, charts and tabulations from the data through the construction of queries. The data in iView plus is split by operational standard being measured and can then be analysed against a range of dimensions collected in the data and measures such as count, percentage and median. The outputs of iView Plus are aggregate, and no record level data can be obtained, however some queries may result in small numbers and these currently have limited disclosure control applied, see A) for further explanation.
iView Plus holds published data, the lowest organisational granularity is trust level, data can also be aggregated to CCG level and other health hierarchies.

Guys and St Thomas' NHS Trust will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements.

Guys and St Thomas' NHS Trust use of the data will fall into two separate categories, each requiring different levels of suppression, and onward sharing both within the Cancer Alliance and with wider NHS stakeholders;

Purpose One - Aggregate local reports
Generation of routine Cancer Waiting Times reports at Provider (Trust) or CCG level. Guys and St Thomas' NHS Trust will access a summary of the totals for the Providers (Trust) and CCG's that are treating cancer patients where they have a commissioning responsibility for that patient (based on the CCG they are aligned to). This analysis would then be shared with the providers and commissioners and used to inform service improvement by providing benchmarked comparable data. The format of this report would be in a tabulated or graphical form (i.e. not record level) but may contain small numbers. An example of where small numbers would not be suppressed would be in relation to cases of breaches against a standard where small numbers would be essential to ensure the report is meaningful.

Examples of this type of analysis include:
a. Comparative Cancer Waiting Times performance at tumour group and individual tumour site (i.e. ICD10 code) level for Trusts and CCGs across the geography
b. Analysis of Cancer Waiting Times performance by treatment modality
c. Grouping length of waits for standards
d. Analysis of free text and derived breach reason fields to identify trends in reasons for delays
e. To provide assurance through comparative analysis (e.g. orphan record identification, active monitoring proportions and validation of waiting list adjustments entered)
f. Analysis of flows of patients including analysis by provider trust site
g. Reviewing waits between surgery and radiotherapy for Head and Neck Cancer patients with a maximum recommended wait of 6 weeks
h. Reviewing routes to diagnosis of patients
i. Quantifying treatment volumes by provider organisation including analysis treatment rates

Purpose Two - Sharing of record level data (including free text breach reasons) with providers and commissioners responsible for direct patient care for that patient. This will be for local audit purposes.

The two broad purposes for this would be;

1) To support audit work
2) Investigate individual outliers to the national standards

Pathway analysis will be undertaken, identifying trends in reasons for breaches. The analysis will inform system wide pathway improvements and compliance to the national standards. Examples of potential changes to achieve this could be to support trusts in additional resources and processes and also to facilitate discuss between trusts for example in reaching agreement for diagnostics between trusts.

Examples of the types of reasons for this include;
a. Patients waiting excessively long period of time to seen of received treatment
b. Free text breach reasons identifying areas of concern which require more detail or clarification from provider
c. Identification of 28 day standard exceptions - National guidance states patients who are diagnosed with cancer should be informed face to face, this would highlights numbers of patients who are not told in person by provider
d. Audits to review orphan records which require local providers to review local patient’s records

Record level data (pseudonymised) will be shared via NHS.net email accounts and access will be controlled by password protecting all files.

Yielded Benefits:

Access to the national Cancer Waiting Times (CWT) data via the NHS Digital portal has given the South East London (SEL) Cancer Alliance the ability to access granular CWT data with immediacy which has been particularly beneficial for the faster diagnosis standard (FDS) data from the start of the financial year. This has allowed the South East London Cancer Alliance to immediately understand performance and drivers, using locally developed dashboarding leveraging off the national CWT data, across South East London (SEL). This has allowed an understanding for areas of focus for the Cancer Alliance FDS Implementation Lead, which has led to improvements in performance in Breast and Head and Neck pathways and local discussion with both trusts and commissioners via the cancer alliance infrastructure (tumour level boards, provider boards) on how to improve pathways to meet the FDS standard, and is critical to improve challenged areas such as Colorectal, Gynaecology, and Urology By breaking down the data, for example by sub tumour specialty and clinical commissioning group (CCG), the SEL Cancer Alliance can understand the volumes in throughput of patients by geography and specific tumour. In addition the associated waiting times can be compared to other clinical indicators, such as numbers of stage 1 and 2 cancers, as well as identifying specific sub-specialty pathways that are outliers against the standards in specific areas of the alliance geography, and can identify disparity in performance between SEL providers for Urology cancer. Using CWT data can identify areas of inequality, ensure tumour level work plans include reducing inequality within the alliance geography and increasing patient equity of service. The data is used to break down 62 day activity to look at shared performance between individual providers for SEL residents and the cancer alliance have been able to identify pathways with specific providers that are negative outliers against the timed pathways. For example in 2019/20 so far, 62 day performance in Urology for cases shared between Kings College Hospital and Guy’s and St Thomas is at 10% compliance which is the lowest shared provider pathway performance for one of the largest in volume. The data is used to compare treatment rates and volumes by CCG/provider trust to support projects that focus on repatriation of treatment activity between provider trusts A recently performed deep dive into patients that have multiple two week wait referrals prior to diagnosis over variable time periods has supported the expansion of rapid diagnosis centres as part of the NHS National Cancer Long Term Plan.

Expected Benefits:

1) Benefits type: Supporting delivery of CWT standards
The Cancer Waiting Times standards are key operational standards for the NHS, which aim to reduce the waits for diagnosis and treatment for Cancer patients, which will support improvements to survival rates and improve patient experience. This includes the new 28 day faster diagnosis standard being introduced as a standard from April 2020.

A key enabler to achieve these standards, and thus improve survival and patient experience is the role of Cancer Alliances locally to work with providers and commissioners to improve patient pathways. Access to the Cancer Waiting Times data as detailed in the above will enable Cancer Alliances to have informed discussions and allocate resources optimally to improve performance against these standards. It will also enable Cancer Alliances to work with local providers and commissioners to identify outliers against the standards, and mitigate the risk of similar delays for other patients.

Improvement would be expected on an on-going basis with standards already in place for nine standards:-
• 2 week wait urgent GP referral – 93%
• 2 week wait breast symptomatic – 93%
• 31 day 1st treatment - 96%
• 31 day subsequent surgery – 94%
• 31 day subsequent drugs – 98%
• 31 day subsequent radiotherapy – 94%
• 62 day (GP) referral to 1st treatment – 85%
• 62 day (screening) referral to 1st treatment – 90%
• 62 day upgrade to 1st treatment – locally agreed standard
In addition this access and use of data will be key in delivering the new 28 day faster diagnosis standard being introduced from 2020

2) Benefits type: Improvements beyond constitutional standards
This access and resulting analysis will enable Cancer Alliances to undertake local analysis beyond the Cancer Waiting Times operational standards to support improvements to Cancer patients pathways beyond those already achieved by improving performance against standard set. This could include reviewing times between treatments, or treatment rates.

The overall aim of this type of additional analysis would be to support improvements to Cancer patient’s survival and experience. The Cancer Taskforce recommendation set out a number of ambitions to be met nationally and locally by 2020 including improving 1 year survival for Cancer to 75%, and improving the proportions of patients staged 1 or 2 to 62%. For both of these improvements to the diagnostic and treatment pathways are key, and require Cancer Alliances to be able to analyse the Cancer Waiting Times dataset to identify sub-optimum pathways and resulting improvements.

Outputs:

Outputs fall into the following categories:

1) Analysis to support delivery of Cancer Waiting Times standard and identify variation, including clinical discussions to improve patient pathways
a. Comparative Cancer Waiting Times performance at tumour group and individual tumour site (i.e. ICD10 code) level for Trusts and CCGs.
b. Analysis of Cancer Waiting Times performance by treatment modality to inform discussions
c. Grouping length of waits for standards to inform discussions on going beyond constitutional standards
d. Analysis of free text and derived breach reason fields to identify trends in reasons for delays.
e. To provide assurance through comparative analysis (e.g. orphan record identification, active monitoring proportions and validation of waiting list adjustments entered)
f. Analysis of flows of patients including analysis by provider trust site
g. Outlier identification including exceptionally long waits to inform individual queries to providers

2) Cancer Waits analysis (not directly linked to constitutional standards) for the aim of identifying variation which may impact Cancer patient’s outcomes or patient experience. Examples for use of the data may include reviewing waits between surgery and radiotherapy for Head and Neck cancer patients with a maximum recommended wait of 6 weeks and using the data source to validate surgical numbers by provider trust.

The overarching aim of all future analysis/outputs is to inform priorities and potential investment to improve Cancer pathways including reducing Cancer incidence and mortality, improving Cancer survival, improving patient experience, improving service efficiency and meeting national constitution standards relating to Cancer patients.

Processing:

Access to the Cancer Wait Times (CWT) System will enable Cancer Alliances to undertake a wide range of locally-determined and locally-specific analyses to support the Cancer Taskforce vision for improving services, care and outcomes for everyone with Cancer.

Only the lead organisation Guys and St Thomas' NHS Trust will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the Guys and St Thomas' NHS Trust servers. Role Based Access Control prevents access to data downloads to employees outside of the analytical team responsible for producing outputs; the South East London Accountable Cancer Network informatics team.

The CWT system is hosted by NHS Digital, access to and usage of the system is fully auditable. Users must comply with the use of the data as specified in this agreement. The CWT system complies with the requirements of NHS Digital Code of Practice on Confidential Information, the Caldicott Principles and other relevant statutory requirements and guidance to protect confidentiality.

Access to the CWT system will be granted to individual users only when a valid Data Usage Certificate (DUC) form is submitted to NHS Digital via the lead organisations Senior Information Risk Officer (SIRO), and where there is a valid Data Sharing Agreement between the lead organisation and NHS Digital.

Approved users will log into the system via an N3 connection and will use a Single Sign-On (users are prompted to create a unique username and password).

Guys and St Thomas' NHS Trust users will access:

a) Aggregate reports (which may include unsuppressed small numbers)

b) Pseudonymised record level data - users can directly download this data from the CWT system

c) I-View Plus tool (aggregated - access to produce graphs, charts/tabulations from the data through the construction of queries). This will give users access to run bespoke analysis on pre-defined measures and dimensions. It delivers the same data that is available through the reports and record level downloads (i.e. it will not contain patient identifiable data).

Any record level data extracted from the system will not be processed outside of Guys and St Thomas' NHS Trust unless otherwise specified in this agreement. Following completion of the analysis the record level data will be securely destroyed.

Users are not permitted to upload data into the system.

Data will only be available for the Providers (Trust) and CCG's that are treating cancer patients where they have a commissioning responsibility for that patient (based on the CCG that this Cancer Alliance is aligned to).

The data will only be shared with other members of the Cancer Alliance in the format described in purpose 1 and purpose 2 of this agreement. The primary method for sharing outputs is via e-mail; for example as part of Alliance meeting papers.

Where record level data is shared with individual trusts these are shared only with trust(s) who were involved in the direct care of the patient, only via NHS.net email accounts.

As part of partnership working to improve Cancer Waiting Times performance, outputs may be shared with national/ regional bodies including the South East London sustainability and transformation partnership (STP). Data will only be shared as described in purpose one and purpose two of this agreement and where recipient organisations hold a valid Data Sharing Agreement with NHS Digital to access Cancer Waiting Times data.

Training on the CWT system is not required as it is a data delivery system and it does not provide functionality to conduct bespoke detailed analysis. User guides are available for further assistance.

Access to the CWT system data is restricted to Cancer Alliance employees who are substantively employed by the Data Controller in fulfilment of their public health function.

The Cancer Alliances will use the data to produce a range of quantitative measures (counts, crude and standardised rates and ratios) that will form the basis for a range of statistical analyses of the fields contained in the supplied data.
Typical uses will include:
1) Analysis to support delivery of Cancer Waiting Times standard and identify variation, including clinical discussions to improve patient pathways
a. Comparative Cancer Waiting Times performance at tumour group and individual tumour site (i.e. ICD10 code) level for Trusts and CCGs.
b. Analysis of Cancer Waiting Times performance by treatment modality to inform discussions
c. Grouping length of waits for standards to inform discussions on going beyond constitutional standards
d. Analysis of free text and derived breach reason fields to identify trends in reasons for delays.
e. To provide assurance through comparative analysis (e.g. orphan record identification, active monitoring proportions and validation of waiting list adjustments entered)
f. Analysis of flows of patients including analysis by provider trust site
g. Outlier identification including exceptionally long waits to inform individual queries to providers

2) Cancer Waits analysis (not directly linked to constitutional standards) for the aim of identifying variation which may impact Cancer patient’s outcomes or patient experience. Examples for use of the data may include reviewing waits between surgery and radiotherapy for Head and Neck cancer patients with a maximum recommended wait of 6 weeks and using the data source to validate surgical numbers by provider trust.

Pneumococcal Vaccination to Accelerate Immune Recovery in Sepsis Survivors (VACIRiSS) — DARS-NIC-650245-T6C6T

Type of data: information not disclosed for TRE projects

Opt outs honoured: Identifiable, No (Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (NHS Trust)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2024-01-05 — 2025-01-04 2024.02 — 2024.05.

Access method: One-Off

Data-controller type: GUY'S AND ST THOMAS' NHS FOUNDATION TRUST

Sublicensing allowed: No

Datasets:

  1. Demographics
  2. Hospital Episode Statistics Admitted Patient Care (HES APC)

Objectives:

Guy’s and St Thomas’ NHS Foundation Trust requires access to NHS England data for the purpose of the following Clinical Trial: Vaccination for immune recovery following sepsis Trial” (VACIRiSS).

The following is a summary of the aims of the Clinical Trial provided by Guy’s and St Thomas’ NHS Foundation Trust:

“This Clinical Trial aims to find out if a safe and widely used vaccine (a Pneumoccocal vaccine) can help in preventing new infections for patients who survive an Intensive Care Unit (ICU) admission with sepsis. The Trial will also explore if the vaccine would help those who do get new infections to recover more quickly.

“214 adult patients have been recruited to be part of the study; 183 of these were recruited from sites in England and Wales. All patients are registered with a GP and the reason for admission to intensive care unit or high dependence unit was sepsis. They were put into one of two groups. This was decided by chance. One group received a single injection of Pneumococcal vaccine. One group received a dummy vaccine that contained no active ingredients. There was an equal chance of receiving the vaccine or the dummy injection. Neither the patient or the doctors and nurses knew which group participants were in. This type of study is called a “double-blind, placebo controlled, randomised trial” and it ensures that the treatment is tested fairly.

“Participants of this study are followed up for one year after their first admission with sepsis to determine whether vaccination reduces infection rate and severity during this time. Blood samples were also taken to determine the ways by which vaccination might work .”

The following NHS England data will be accessed:
• Hospital Episode Statistics Admitted Patient Care – necessary to (i) identify patients readmitted to hospital and whether that readmission was due to an infection; and (ii) understand the hospital costs of such readmissions. Hospital costs will be estimated by using the Healthcare Resource Group code provided from the HES Admitted Patient Care dataset to assign a cost per bed-day taken from published reference costs.
• Demographics data - necessary to provide Date of Death used to calculate duration of survival (a required endpoint) by counting the days from the date of randomisation.

The level of the data will be identifiable - necessary to enable linkage of the data with data collected from the participants themselves and other information collected by the Trial sites including medical records and GP records.

The data will be minimised as follows:
• Limited to a cohort of 183 adults recruited from 9 NHS critical care units in England and Wales between 18 August 2018 to 20 April 2022.

Participants are recruited under informed patient consent where possible. In the circumstance the participant was not able to consent for themselves, a legal representative of the participant was approached and consent was obtained via the legal representative. The study holds ethical approval and this method of recruitment comes under Medicine for Human Use (Clinical Trials) Regulations 2004. Should the participant regain capacity during the study, informed patient consent would be sought.

Guy’s and St Thomas’ NHS Foundation Trust is the research sponsor and the controller as the organisation responsible for ensuring that the data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;
This study would be in the public interest to explore if administering a commonly available vaccine could reduce infection related hospitalisation in sepsis survivors. The results of the trial could potentially have an effect on policy making decisions, and health care pathway.

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

This processing is in the public interest because the aim is to explore if administering a commonly available vaccine could reduce infection related hospitalisation in sepsis survivors. The results of the trial could potentially have an effect on policy making decisions, and health care pathway. The funding is provided by the National Institute for Health Research (NIHR), through a NIHR Clinical Scientist Award. The funding is specifically for the VACIRiSS Trial described . Funding is in place until completion of the trial publication.

The Intensive Care National Audit and Research Centre (ICNARC) is a processor acting under the instructions of Guy’s and St Thomas’s NHS Foundation Trust. ICNARC’s role is limited to processing the data according to the agreed protocol and statistical analysis plan.

Exponential-E Ltd is a processor providing IT back up services to ICNARC and will store copies of the data as contracted by ICNARC.

Babble Cloud (SUI) Limited will provide external desktop and network managed services and will provide remote access to ICNARC servers hosted by Exponential-E Ltd.

As part of NIHR Funding requirements, the trial was overseen by a Trial Steering committee and a Data Monitoring committee to ensure best practice of research governance. Both these committees for the VACIRiSS trial consisted of a number of health care professionals, providing independent advice to the Chief Investigator.

The statistician at ICNARC will be the only person accessing the record level data. The Chief Investigator who is a substantive employee of University of Edinburgh working under an Honorary contract with Guy’s and St Thomas’ NHS Foundation Trust and other trial investigators will receive output data which is aggregated derived data. This will be amalgamated summary data from all four home nations and it will not be possible for a recipient to determine the country or trial site of any individual from the data. The reports may included unsuppressed small numbers as permitted by the HES Analysis Guide given the national level of the data.

Patient and Public Involvement and Engagement activity was conducted during the idea development, design, planning, and conduct of the VACIRiSS trial. The engagement was to explore whether patients would be interested in participating in such a trial. This engagement led to further development of the information sheet.

Expected Benefits:

The findings of this research study are expected to contribute to evidence-based decision-making for policy-makers, local decision-makers such as doctors, and patients to inform best practice to improve the care, treatment and experience of health care users relevant to the subject matter of the study.

The use of the data could:
• help the system to better understand the health and care needs of populations.
• lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience.
• advance understanding of the need for, or effectiveness of, preventative health and care measures for particular populations or conditions such as obesity and diabetes.
• support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

The aim of VACIRiSS trial is to evaluate the immunogenicity and heterologous effects of single dose 13-valent conjugate pneumococcal vaccine (PCV-13) in preventing infection related rehospitalisation or death in sepsis survivors and to collect outcome event data with necessary precision to inform future definitive trial design.

This clinical trial is to evaluate the effect of the single dose vaccine, and to determine whether a future clinical trial is feasible, and necessary. If the results show that a further trial is viable, the results of this trial could have potential value for patients either presenting with sepsis or developing sepsis in hospital.

It is hoped that through publication of findings in appropriate media, the findings of this research will add to the body of evidence that is considered by the bodies, organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients – critically ill patients who survive hospitalisation due to sepsis.

A lay persons’ summary of the principal findings of the results will be sent to all clinical sites and to patients involved in the study at their request. In addition, a lay persons’ summary will be sent to local and national patient support and liaison groups for wide dissemination (e.g. ICU Steps, hospital patient groups, Intensive Care Society, UKCritical Care Research Group). A report of the study findings will be sent to the funder NIHR.

Outputs:

The expected outputs of the processing will be:
• A report of findings to NIHR
• Submissions to peer reviewed journals [The primary manuscript will be submitted within 6-8 weeks of linkage data availability. This will include completed follow up data, primary, secondary, and exploratory biological outcomes.
• Presentations at appropriate conferences, which may include the European or UK Societies of Intensive Care Medicine or similar

The outputs will not contain NHS England data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:
• Journals
• Social media
• Public events such as conferences highlighted above
• Reports to the funder including a lay summary
• VACIRiSS Study website and posts on ICNARCs social media accounts (e.g. ICNARC has more than 7,000 followers on Twitter, https://twitter.com/icnarc?lang=en)

It is difficult to predict target dates, as it is dependent on data linkage, analysis, manuscript write up, submission to journal, peer review, manuscript revisions, and finally acceptance of publication. The average time from submission to acceptance is around 3-4 months.

Processing:

ICNARC will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Date of Birth, Postcode and a unique person ID (VACIRiSS Trial number)) for the cohort to be linked with NHS England data.

NHS England data will provide the relevant records from the HES Admitted Patient Care and Demographics datasets to ICNARC. The data will contain no direct identifying data items but will contain a unique person ID which can be used to link the data with other record level data already held by the recipient.

The data will not be transferred to any other location.

The data will be stored on servers at Exponential-E Ltd.

ICNARC uses offsite back-up services provided by Exponential-E Ltd.

Babble Cloud (SUI) Limited will provide external desktop and network managed services and will have remote access to ICNARC servers hosted by Exponential-E Ltd

The data will be accessed by the statistician via remote access. The data will remain on the servers at Exponential-E Ltd at all times.

Personnel are prohibited from downloading or copying data to local devices.

The data will not leave England at any time.

Access to the record level data is restricted to the Statistician who is a substantive employee of ICNARC who has authorisation from the Chief Investigator. The Chief Investigator will not have access to the record level data and will only receive derived aggregated outputs which comply with the disclosure rules set out in the HES Analysis Guide.

All personnel accessing the data have been appropriately trained in data protection and confidentiality.

The data will be linked at person record level with cohort data obtained from 183 consented study participants.

The data will be combined with publicly available data on the average costs of a hospital bed day for a given Healthcare Resource Groups (HRG) code based on the National Schedule of NHS Costs.

The NHS England data will be combined with information from one site in Scotland and one site in Northern Ireland.

There will be no requirement and no attempt to reidentify individuals when using the data.

The identifying details will be stored in a separate database to the linked dataset used for analysis. All analyses will use the pseudonymised dataset. There will be no requirement and no attempt to reidentify individuals when using the pseudonymised dataset.

The Statistician from the Intensive Care National Audit and Research Centre will process the data for the purposes described above.

A follow-up of GLACIER (a study to investigate the Genetics of LobulAr Carcinoma In situ in EuRope) and ICICLE (A study to Investigate the genetiCs of In situ Carcinoma of the ductaLsubtypE). (ODR1920_145) — DARS-NIC-656860-Q5Q9Q

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, Identifiable, No (Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (NHS Trust)

Sensitive: Sensitive

When:DSA runs 2023-01-10 — 2024-01-09 2023.10 — 2023.10.

Access method: One-Off

Data-controller type: GUY'S AND ST THOMAS' NHS FOUNDATION TRUST

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care (HES APC)
  2. NDRS Cancer Registrations
  3. NDRS Linked HES Outpatient
  4. NDRS National Radiotherapy Dataset (RTDS)
  5. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)
  6. NDRS Linked HES APC

Objectives:

On 1 February 2023, NHS Digital merged with NHS England. NHS England has assumed responsibility for all activities previously undertaken by NHS Digital. The merger was completed by a statute change. Any reference made to NHS Digital within this Data Sharing Agreement is in reference to the merged organisation known as NHS England.

The Data Recipient will conduct a follow-up to the GLACIER and ICICLE studies, 5-10 years after the initial recruitment of participants, in order to investigate the survival of breast carcinoma, rates of recurrence and new diagnoses in women with different subtypes of disease.
The aim of the study is to obtain survival data on participants with lobular carcinoma in situ, invasive lobular carcinoma and ductal carcinoma in situ who were recruited to the GLACIER and ICICLE studies between 2007 and 2013.
Survival data including date and cause of death, follow-up information on recurrence and data relating to new diagnoses will be requested for all women who gave full consent to further studies in order to analyse participants' risk of further disease after breast cancer, or death after breast cancer, according to initial tumour type.

Yielded Benefits:

Thus far, novel associations have been discovered between further disease occurrence after initial diagnosis and the presence of single nucleotide polymorphisms

Expected Benefits:

This data will allow us to ascertain whether any of the genes investigated in the initial study will increase chances of lobular breast cancer and ductal carcinoma in situ, and affect survival or progression.
It will also allow us to identify tumour biomarkers associated with survival in invasive lobular carcinoma, and progression of lobular carcinoma in situ and ductal carcinoma in situ to invasive disease.
Having this predictive information on different tumour types could change the way that patients are treated, enabling targeted treatment of different tumour types.

Outputs:

Outputs expected include:
Reports
Submissions to peer-reviewed journals
Presentations
Conferences
PhD Thesis

For all outputs produced, no identifiable information will be included, and instead will be aggregate numbers within groups. Results will be shared to all sites included with the original studies.

Outputs are expected to be completed by the end of 2026 (31/12/2026)

Processing:

Data will be received at Guy's & St Thomas' Hospital (both data controller and processor), only identifiable by original study ID, the linkage of which is held solely by the Chief Investigator.
Data will be stored securely on Guy's & St Thomas' Hospital computers which are password controlled, and access will be limited to those involved directly in this project.
Once received, data will be verified then each participant given another unique identifier.
Data will then be cleaned and reshaped into a format which enables analysis, and analysed to answer the study questions.
The results of the analysis will be shared and disseminated.

Epidemiology and Prognosis in Acute Myocarditis — DARS-NIC-144568-D7G6V

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (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 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (NHS Trust Site, NHS Trust)

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

When:DSA runs 2019-10-15 — 2020-10-14 2019.01 — 2022.11.

Access method: One-Off, Ongoing

Data-controller type: GSTT @ ROYAL BROMPTON HOSPITAL, ROYAL BROMPTON HOSPITAL, GUY'S AND ST THOMAS' NHS FOUNDATION TRUST

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Civil Registration - Deaths
  3. HES:Civil Registration (Deaths) bridge
  4. Civil Registration (Deaths) - Secondary Care Cut
  5. COVID-19 Hospitalization in England Surveillance System
  6. COVID-19 Second Generation Surveillance System
  7. HES-ID to MPS-ID HES Admitted Patient Care
  8. Civil Registrations of Death - Secondary Care Cut
  9. Hospital Episode Statistics Admitted Patient Care (HES APC)
  10. COVID-19 Second Generation Surveillance System (SGSS)
  11. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Objectives:

Royal Brompton and Harefield NHS Trust aims to describe the longitudinal epidemiological trends of acute myocarditis to provide a contemporary, population-level assessment of the burden of disease and how this may have changed over the last 20 years. National data is therefore required over a 20 year period under this agreement recognising changes and variation arising from medical, biological, geographical and social factors.

Myocarditis means inflammation of the heart muscle and is known to predominantly affect young adults aged between 19-35 years. It is usually related to a recent viral infection. Patients often present with severe, sudden-onset chest pain mimicking a heart attack, difficulty breathing due to weakened heart muscle, and/or palpitations due to electrical rhythm disturbances within the heart. However, myocarditis also affects infants and older adults where causative factors and clinical outcomes are poorly characterised. In the long-term, up to one third of patients are at risk of developing heart failure, known as dilated cardiomyopathy, or experiencing a sudden cardiac arrest.

Few studies have investigated the epidemiology of myocarditis on a population level, and there is NO data on the incidence and prevalence of myocarditis within the UK. Historical studies focused on small cohorts, such as Finnish military conscripts in Helsinki. The WHO Global Burden of Disease study was not directly relevant to the UK and provided no data on patient prognosis. Whilst there are a growing number of clinical research studies investigating new diagnostic tools and treatments in myocarditis, these small groups of recruited study participants represent the 'tip of an iceberg.'

The Trust seeks to obtain all available data on hospital admissions specifically due to 'myocarditis' (I40, I51.4, I01.2, I09.0) in all age groups across England/Wales over the last 20 years. Data on age, sex, ethnicity, length of admission, method of admission, Intensive Therapy Unit (ITU) bed days and specific cardiac procedures (including cardiac catheterisation, endomyocardial biopsy, pacemaker/implantable cardioverter defibrillator (ICD)/ ventricular assist device (VAD) implantation and cardiac transplantation) would be important to record. Data on readmission would be useful to understand predictors of disease recurrence, and ultimately, linkage to mortality data with cause of death would provide new insights into clinical outcomes in a real-world setting. Geographical data may be helpful to understand whether social deprivation or pollution levels are implicated.

The Trust also seeks to obtain the same depth of HES and linked mortality information on hospital admissions due to pericarditis and myocardial infarction. Myocarditis overlaps with pericarditis (inflammation of the adjacent lining of the heart; collectively referred to as myopericarditis) and again there are no data on the incidence, prevalence or prognosis of pericarditis within the UK. Myocardial infarction represents a distinct disease process due to restriction in coronary blood supply but also presents with sudden-onset, severe chest pain. There are many published studies and national audits on myocardial infarction within the UK. Within this application, data on myocardial infarction is requested to allow accurate understanding and comparison across the same HES data elements on the scale and scope of myocarditis.

Up to one third of patients with myocarditis develop heart failure and dilated cardiomyopathy (DCM). DCM is the leading cause for needing a heart transplant in the UK. The Trust seeks to obtain the same depth of HES and linked mortality information on these hospital admissions to allow epidemiological and prognostic assessment of myocarditis relative to heart failure and dilated cardiomyopathy overall. Furthermore, it is expected that myocarditis may be recorded as a secondary diagnosis in a significant but yet unknown number of these admissions. Failing to detect these cases would lead to underestimation of the burden of myocarditis.

Based on extrapolation from published data (Papadakis et al, 2009), the Trust estimates that myocarditis accounts for one sudden cardiac death each week in an individual aged <35 years of age in the UK. From a mechanistic perspective, this occurs due to electrical disturbances within the heart due to the initial myocardial injury. The Trust seeks to obtain the same depth of HES and linked mortality information in order to understand the true burden of myocarditis resulting in sudden cardiac arrest with or without successful resuscitation.

Data is requested over a 20 year period to study the longitudinal epidemiological trends linked to medical (e.g. technological advances in troponin assays, echocardiography, cardiac MRI for improved detection), social (e.g. increasing population density, pollution levels, changing work patterns) and biological (e.g. viral aetiology, drug and toxin use) changes over this time period. Twenty years allows for optimal longitudinal assessment based on published literature although the applicant is aware of the reduced depth of data in the earlier years. Data is requested for all age groups recognising that while myocarditis predominantly affects young adults, it remains an important cause for heart failure in young infants and older age groups due to altered immune responses and overlap with other systemic inflammatory conditions - the understanding of myocarditis in these groups is particularly limited. National data is requested in order to remove geographical bias due to regional differences in viral aetiology and healthcare systems, ultimately informing changes to clinical guidelines and policies on a national level.

Given the growing public interest in sudden cardiac deaths and cardiac transplantation amongst young individuals, there is a pressing need to improve the understanding of the epidemiology and prognosis of myocarditis. Early detection through improved awareness would make a significant contribution to individual patient care in all age groups, including infants and elderly patients, where understanding is further limited. Looking back to understand unique features of patients that subsequently suffered disease recurrence or death will enable clinicians to better identify these high-risk individuals at initial presentation.

Yielded Benefits:

Analyses of epidemiological trends in myocarditis admissions and outcomes were presented by the Study Lead at the American Heart Association Annual Scientific Session in November 2019 in Philadelphia, USA, and subsequently published in the medical journal, ‘Circulation’. This is available online to the public at the following address: https://www.ahajournals.org/doi/10.1161/circ.140.suppl_1.11463. This has been highlighted by Cardiomyopathy UK and the Janson’s Myocarditis Foundation (the two leading patient charitable organisations) to clinicians and patients across the UK. This data has been presented to myocarditis patient groups hosted at the Royal Brompton Hospital and organised by Cardiomyopathy UK (https://www.cardiomyopathy.org/information-events-myocarditis-information-evening/myocarditis-information-evening-for-parents-and-relatives-1). The project and findings have been made publicly available on a dedicated webpage (https://www.rbht.nhs.uk/research/our-research/active-research-studies/epidemiology-and-prognosis-acute-myocarditis). Further analyses were subsequently conducted by the Study Lead and presented in their PhD, which was recently awarded by Imperial College London on 1st October 2020. These findings were compiled into a scientific manuscript over the 2019 Winter period but this was not submitted for publication due to the emergence of the COVID-19 pandemic and ensuing rise in myocarditis cases earlier in 2020. The latest evidence from cardiac MRI studies of patients that have recovered from COVID-19 has yielded conflicting findings. In one study, up to 60% of individuals with prior COVID-19 infection had undiagnosed features of ongoing inflammation within the heart consistent with myocarditis (https://jamanetwork.com/journals/jamacardiology/fullarticle/2768916). This work has had major public health implications; for example, in the US all college sports were stopped for a period due to concern about myocarditis and high-level sports post-COVID (https://www.theatlantic.com/health/archive/2020/09/covid-19-heart-pandemic-coronavirus-myocarditis/616420/). However, subsequently there has been strong divergent opinion suggesting a much lower prevalence. In order that the study team firstly better assess the prevalence but also help guide national policy, better quality data from across England will be very important. This project extension seeks to strengthen and build upon the initial body of research epidemiology by including the impact of COVID-19 on myocarditis and its related conditions (heart failure, pericarditis, sudden cardiac death and myocardial infarction), both in the period before and during the initial peak and potentially any future surges over the next 12 months to improve understanding of disease trends, regional prevalence, severity and clinical management.

Expected Benefits:

Heart failure and sudden cardiac death are two separate but important worldwide health problems with high morbidity and mortality that can both arise from acute myocarditis at any age. Heart failure is reported to occur in up to one third of patients with acute myocarditis and has a major global economic burden through healthcare costs and lost productivity through heart failure hospitalisations. Based on published data from ONS, myocarditis is thought to account for approximately 1 sudden cardiac death under 35 years of age each week in the UK. Such events commonly feature in the media headlines and understandably generate considerable anxiety and questions.

By accruing data on the real-world burden of acute myocarditis resulting in hospital admission, relative to other similarly presenting conditions, and its downstream consequences in terms of recurrence, DCM and mortality, the Trust hopes to greatly enhance the understanding of this poorly characterised disease and dispel the old myth that myocarditis is; (i) rare and (ii) benign. Specific outputs and further details are include below:

1. Accurate and contemporary data on incidence and prevalence within the UK would reveal health trends over time and support national service planning and provision. Early detection through improved recognition and awareness arsing from this study both amongst the public and medical staff would make a significant contribution to individual patient care and healthcare resource allocation.

2. Reductions in length of hospital admission due to defined diagnostic pathways from the Consensus pathway may both reduce hospital expenditure and employment productivity loss. Improved diagnostic confidence amongst clinicians with published data to support their clinical-decision making will improve the patient journey and outcome.

3. Better risk stratification of those patients at great risk of subsequent DCM and sudden cardiac arrest may provide a window to intervene at a much earlier stage in the disease where therapy is far more likely to make a difference. Once the disease has occurred and resulted in a complication, intervention is always more complicated, costly and less likely to deliver favourable results.

4. The findings from this study will form the basis of the researcher's PhD and be published in high-impact medical journals with guidance from the Public Health Department at Imperial College. This work is expected to be completed within 6-12 months of receiving the data within the time-scale of a higher research degree. The outputs will be supported and promoted through the British Heart Foundation Press Office, with whom the lead researcher has worked previously (https://www.bhf.org.uk/news-from-the-bhf/news-archive/2017/june/heart-scans-reveal-cause-of-sudden-cardiac-arrests-in-the-young), as well as Cardiomyopathy UK and the Alexander Janson Fund for publicising the results and conveying these findings to patients and their families. This is exemplified by the 3rd annual myocarditis patient and relatives evening due to be held at the Trust on 14th November 2018 (details of previous events found here: http://www.rbht.nhs.uk/research/research-news-2/patients-share-experiences-of-myocarditis-at-information-day/, https://www.cardiomyopathy.org/news--media/latest-news/post/268-myocarditis-patient-and-relatives-information-evening, http://www.rbht.nhs.uk/research/research-news-2/charity-funding-boosts-myocarditis-research-and-patient-support/, http://alexanderjansonsfund.org/wp-content/uploads/2017/01/patient-information-slides.pdf).

5. Data generated from this study in all its forms (incidence, prevalence, age groups, gender differences, geographical variation, viral aetiology, social deprivation status, length of admission, investigations, treatments, recurrences, sudden death, heart failure and mortality) will be compiled into an epidemiological high-impact paper and a Consensus statement paper, both of which will be publicised and promoted through Imperial College, the BHF and Cardiomyopathy UK. Based on this evidence demonstrating the scope of the problem and the need for improved UK guideline support, the Trust intends to propose the development of NICE guidelines for managing patients with myocarditis. These will be proposed to the NICE Committee through established links within the Trust.

6. Ultimately, better evidence and information on the scale and scope of myocarditis will highlight and inform future directions for medical research, including the design of large multi-centre studies to evaluate new emerging immunological therapies. The overall aim is to improve patient outcomes.

Outputs:

In this study, the Trust aims to investigate the following features with definable outputs as detailed below:

1. Incidence and prevalence of myocarditis– there are no studies published to date that have examined the incidence and prevalence of acute myocarditis (or myopericarditis) on a national level. Estimates from the WHO Global Burden of disease study of 2013 suggest myocarditis affects 23 out of 100,000 people. However, there is a wide spectrum of clinical presentation and disease detection. In the wake of a number of sudden cardiac deaths due to myocarditis (http://www.bbc.co.uk/news/health-40408536; http://www.bbc.co.uk/news/health-11542429; http://www.bbc.co.uk/news/entertainment-arts-39193367; http://www.bbc.co.uk/news/uk-england-birmingham-41988846), there is a need for improved understanding of disease epidemiology and in turn, awareness and recognition. At present, there is no understanding of whether the number of cases of myocarditis is increasing or decreasing within the UK. The Trust will analyse and write up this data for publication in a high-impact medical journal, such as the Lancet or British Medical Journal (BMJ). Data will also be circulated widely through our partners, the British Heart Foundation and Cardiomyopathy UK.

2. Long-term complications and prognosis of myocarditis – published studies investigating long-term outcome are subject to bias amongst recruited individuals and provide a narrow window into possible outcomes. Most of these studies have been performed on patients with biopsy-proven myocarditis in Germany and study outcomes may not be reflective of UK practice given geographical variation, for example, in viral aetiology. The Trust will analyse and write up this data for publication in a high-impact medical journal, such as the Lancet or BMJ.

3. Gender differences – no studies have specifically investigated age and sex differences in patients affected by acute myocarditis. There is evidence that myocarditis typically affects young men from 19-35 years of age. By studying all age groups across the county, the Trust will generate up-to-date knowledge of this within the NHS - this will improve treating clinicians’ understanding and awareness of who is typically affected by myocarditis.

4. Seasonal variation – from the Trust's experience of recruiting patients from across South East England into a genetics myocarditis research study based within the Trust, the number of new cases appears to be greatest during the Winter months. The Trust aims to explore this on a national level through the HES dataset. This will again be published in a high-impact medical journal providing new insights into seasonal variation. This could have a significant impact on health-care resource utilisation.

5. Geographical variation – the Trust hypothesises that myocarditis is predominantly a disease of major towns and cities rather than rural or coastal areas. Given that viral infection remains the leading aetiology, geographical differences are likely, in addition to differences depending on socio-economic status. These findings will again be published and circulated widely through the BHF and Cardiomyopathy UK.

6. Diagnostic approaches – there are currently no clinical recommendations to guide patient diagnosis and management in the UK. Individual practice varies between clinicians and hospitals, which has again been clear from the researcher's myocarditis research experience. As a result, there appears to be a postcode lottery for length of hospital admissions, investigations and treatments. By studying the national trends in length of admission, diagnostic tests performed (cardiac MRI, coronary angiogram, cardiac biopsy) and treatments delivered (pacemaker/ICD implantation, cardiac transplantation), the Trust aims to write-up and publish a Consensus statement paper supported by the BHF and co-authored by leading Cardiology consultants with expertise in myocarditis from across the country to unify and guide the way in which patients with myocarditis are diagnosed and treated in future. Such a UK-centric document is greatly needed. Improved diagnostic confidence and approaches to management will translate in improved patient experience and clinical outcomes, which can be reassured after an interval.

7. Recurrence rates and prognosis – there are no published studies that have examined the real-world risks of recurrence following an acute episode of myocarditis. This is one of the most common questions asked by patients, and at present, the Trust is unable to base a response on any published evidence. HES data will allow the Trust to estimate how many patients are readmitted, and whether this typically occurs in the short or long-term. Such data would be useful from a healthcare economics perspective, and again alleviate patient concerns if appropriate to do so.

8. Mortality rate – the number of patients that die as a result of acute myocarditis or related complications within the UK remains unknown. Whilst clinical outcomes in patients suffering a heart attack have vastly been improved in recent years due to developments and advances in service provision and coronary angioplasty, the Trust expects that the mortality rate from myocarditis is likely to be: (i) underestimated and (ii) unchanged over the last 20 years despite advances in other areas. Knowledge of this information once disseminated through high-impact publications, the BHF and Cardiomyopathy UK will likely spur further public interest, funding and research into the condition.

Data generated through this application will be analysed within the Trust and disseminated widely through a number of channels within the year. These will include scientific publication in high-impact medical journals, such as the Lancet and BMJ, as well as lay summaries for communication with patient and public groups through established links with the British Heart Foundation, Imperial College London, Cardiomyopathy UK and Alexander Jansons Fund. Of note, the Trust has arranged it's 3rd annual myocarditis patient and relatives information evening on 14th November 2018 in partnership with Cardiomyopathy UK with the specific aim of providing support and education to individuals affected by myocarditis. Through the planned Consensus statement paper and other established links with guideline committees such as NICE, the Trust hopes to improve and standardise the diagnosis, treatment and surveillance of patients with myocarditis.

Processing:

In summary, the Trust is seeking HES and linked mortality data on a population level for acute myocarditis to investigate the changing epidemiological trends and long-term prognosis of this disease. The Trust does NOT require patient identifiable information.

The Trust would like to obtain all available (pseudonymised) data on hospital admissions specifically due to 'myocarditis' (I40, I51.4, I01.2, I09.0 – full list of diagnostic codes copied below) in all age groups across England over the last 20 years. Data on age, sex, ethnicity, length of admission, method of admission, ITU bed days, specific cardiac procedures (including cardiac catheterisation, endomyocardial biopsy, pacemaker/ICD/VAD implantation and cardiac transplantation) and discharge medication (if available) would be important to record. Geographical data may be helpful to understand whether social deprivation or pollution levels are implicated.

Readmission data is requested in order to understand the likelihood of myocarditis recurrence over the study period as it is recognised that a subset of patents will suffer a recurrence many years later. At present, there are few tools to identify such patients at the time of index presentation. Alternative diagnoses made at the time of readmission may also be due to complications, such as heart failure and cardiac arrhythmia as described above.

To facilitate accurate comparisons with other conditions of overlapping biology (pericarditis), clinical presentation (myocardial infarction) and better understanding of long-term complications (sudden cardiac arrest and dilated cardiomyopathy), the Trust seeks the same depth of HES and mortality linked data on these linked diagnoses (codes listed below).

All data received would be subject to protection and storage within Royal Brompton Hospital's restricted swipe card access department on restricted file servers operating behind an NHS specification firewall. All data stored on or transmitted by a computer of any sort at any location will be encrypted with password protected, 256 bit AES standard encryption. The data will be analysed by the researcher and the chief/principal investigator, who are both employed by Royal Brompton and Harefield NHS Foundation Trust. This analysis will only take place at the Royal Brompton Hospital.

The data will not be linked with any record level data other than that which is described in this agreement. There will be no requirement nor attempt to re-identify individuals from the data. The data will not be made available to any third parties except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

The diagnostic codes required relate to:
(i) Myocarditis:
(ii) Pericarditis
(iii) Dilated cardiomyopathy and heart failure
(iv) Cardiac arrest
(v) Myocardial infarction.

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).

Project 8 — DARS-NIC-35239-W2W9R

Type of data: information not disclosed for TRE projects

Opt outs honoured: N

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC

Purposes: ()

Sensitive: Sensitive

When:2017.12 — 2018.02.

Access method: One-Off

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Office for National Statistics Mortality Data

Objectives:

Home Mechanical Ventilation (HMV) is used for patients with symptomatic hypoventilation, they are small devices that can be used at home at night time or during day, dependent upon disease progression.

There is a need for a long term study of the effects of HMV in patients with hypercapnic COPD, as there is a considerable morbidity, and mortality with frequent hospital admissions associated with this condition. There are also an increasing number of referrals of patients with hypercapnic COPD to units specialising in ventilatory support for consideration of HMV, yet there is no good evidence for the long term effectiveness of this therapy. For the purposes of this trial HMV is used for patients chronic end stage chronic obstructive pulmonary disease.

The hypothesis of this study is that the HMV and home oxygen therapy (HOT) compared to HOT alone will reduce re-admission to hospital in COPD patients who remain persistently hypercapnic following an exacerbation requiring non invasive ventilation (NIV).

The primary outcome is to evaluate admission free survival with comparison between HMV and HOT and HOT alone. This data will be analysed by time to event analyses. Duration of hospital admissions will be also analysed.

If the trial shows a clinical benefit, it will be important to know if the addition of HMV in patients with hypercapnic COPD represents an optimal use of medical resources. Any additional health benefits have to be judged against the costs of resources required to produce them. The trial will include an analysis of the incremental cost-effectiveness and cost-utility analysis of the two study treatments; HMV with home oxygen and home oxygen therapy alone.

Data regarding health economic costs will be obtained on an on-going basis by the research team. The main end-point in the cost-effectiveness analysis will be cost per admission avoided.

Costs will include analysis of the equipment costs, maintenance and support costs for the HMV, analysis of medical, nursing and support staff and all hospital admissions. Cost-effectiveness and cost-utility acceptability curves will be analysed on the v13 (1.8.11) 8 basis of a simulation exercise in order to represent the uncertainty surrounding these ratios. Health related quality of life will be measured using a number of validated questionnaires.

NHS digital is being asked to supply data on all trial participants who were alive at trial completion and thus the end of intensive trial follow up. Although it is expected that the majority have died some patients may still be alive. The request for data is 2 fold both to confirm health status and to supply, were applicable, date of death and cause of death data.

Guys and St Thomas Hospital NHS Trust (GSTT) received hospital admissions data via NHS Trusts directly.

Expected Benefits:

There are over 3 million people in the UK suffering from COPD. Current costs are £800 million per year to the NHS for those that suffer from COPD, which equates to £1.3 million per 100,000. Exacerbations of COPD represent 1 in 5 hospital admissions with 25% of patients having evidence of respiratory failure at admission. Current evidence demonstrates that an average of 15% of COPD patients will die within 3 months of being admitted with an exacerbation, rising to 30% at 1 year in patients who have had a severe exacerbation requiring respiratory support.

The data provided by NHS Digital will allow the study to provide extended mortality data for patients included in the trial to examine for an effect on long term mortality. The outcome of the analysis will provide further information for professionals in this area. Medical specialists will have added information to assist patients in decision making around initiation of HMV. The data will also allow the trial to support commissioners and the trust when considering the importance of changes to service delivery. The dissemination plan will allow these key groups to be targeted.

The dissemination plan is to publish in a high ranking general and respiratory medical journal with allied presentations at international and national conferences to ensure key opinion leaders are aware of the results. These opinion leaders can use the information when meeting with their local commissioners to change their clinical practice within UK health care. This analysis is a secondary analysis to a study published in the Journal of the American Medical Association (JAMA – Impact Factor 44) the main study findings are already influencing local policy for the provision of HMV with changes to the patient pathway following an acute exacerbation of COPD. Furthermore the study findings have been incorporated into the recently publish German Thoracic Society guidelines on HMV in COPD demonstrating the effective reach of the dissemination strategy.

The data has the potential to assess the mortality benefit of this novel therapy in COPD patients with the most severe disease and high symptom burden. The current evidence from the trial has suggested a benefit to patients in terms of reduced hospital admissions and flare ups of their respiratory disease. This has obvious benefits to both the patient and the health care system (both primary and secondary care). The planned analysis on longterm survival will add weight to the potential patient benefits. The dissemination plan is to publish in a high ranking general or respiratory medical journal with allied presentations at international and national respiratory conferences to ensure key opinion leaders are informed of the trial outcomes and potential benefits to patient care.

It is anticipated that the overall study will enhance patient care and wellbeing for patients with end stage COPD and identify those that should receive HMV and therefore, reduce hospital readmissions.

Outputs:

The findings will be published and not be influenced by the funders investment.

The dissemination of results are being performed with key respiratory journals and key respiratory conferences as the data will be of great interest to the respiratory physicians with regards to current and future clinical practice. In line with the usual practice within the research group lay summary of the data will be presented to patient participation groups and the Lane Fox Patient Association.

All outputs will contain only aggregate level data with small numbers suppressed in line with HES analysis guide.

When complete the data will be included within journals and conferences: -

Current conferences/presentations to be targeted:

British Thoraric Society (BTS)

Attendees - Respiratory specialists (consultants & trainees), GPs with interest in respiratory medicine, Respiratory Physiotherapists.

Journals to be targeted:
Medical journal publication (general or respiratory)

Speciality Groups:
Medical Grand Round GSTT (Guys and St Thomas Trust) - December 2017. Medical Grand Round is a trust seminar that is held monthly and is open to all the consultants within the trust, medical staff and final year medical students. It is a highly esteemed seminar to present at and the output will demonstrate what research is being undertaken within the trust.

This data will not be used to establish a protocol for a clinical trial nor will it be used to show performance of an organisation.

The timeline on processing and analysing the data and subsequent publication will be approximately 6 months post receipt of data from NHS Digital.

Processing:

GSTT will provide a list of NHS numbers with dates of birth to NHS Digital. NHS Digital will share back to GSTT Study ID, Date Of Death and Cause of Death.

From the data GSTT receive a study identifier will be allocated and this is what will be used for further analysis. The original NHS identifier will then be removed and original transferred data deleted in line with application information. The information needs to be provided in an identified format so it can be match to the rest of the patient data stored within the database from the original trial. This database is de-identified but has a matching document stored in accordance with the original research ethics committee application.

GSTT will retrieve cause of death for analysis purposes only.
GSTT may use the date of death to determine how soon patients died post participation into the trial.

The de-identified death data will be added to a generic database with no personal identifiable data only a study identifier, for example STH34. This will be performed by the identified ONS users.

The whole database will then be analysed. Only the named authorised users will have access to the data supplied by NHS Digital.

The extracted data will be used to show how many of the participants have died after their participation into the trial and if their cause of death was linked to the pathology they had which made them eligible for the trial initially. The data access will demonstrate mortality numbers for participants with the pathology included into the study.

The data which will be shared will be suppressed inline with ONS Disclosure controls.

All processing of ONS data is in accordance with standard ONS terms and conditions.

Record level data will not be shared with any third party, all those accessing the data will be substantive employees of GSTT.


All organisations party to this agreement are required 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).

Project 9 — DARS-NIC-91878-Y4M2P

Type of data: information not disclosed for TRE projects

Opt outs honoured: N, Y

Legal basis: Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Non Sensitive

When:2017.12 — 2018.02.

Access method: One-Off

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care

Objectives:

Infective endocarditis (IE) is a life-threatening condition caused by infection within the heart, most commonly on a heart valve. IE is much more common in people who have undergone a heart valve replacement. Since 2007 a new keyhole method of heart valve replacement – transcatheter valve implantation (TVI) – has been available, which avoids the need for open heart surgery. TVI is mainly used for patients who are too frail to undergo open heart surgery.

There are very few studies examining the risk of IE after valve replacement by TVI. Guys & St Thomas NHS Foundation Trust want to understand how many patients develop this complication, which patients are affected, and to look at how many patients ultimately survive. Guys & St Thomas NHS Foundation Trust also plan to compare the risk of IE after TVI with the risk of IE after conventional open heart surgery. Finally, Guys & St Thomas NHS Foundation Trust will look at whether the number of heart valve replacement patients who develop IE has changed over time. Specifically, the study will look at the numbers of patients with IE before and after 2008, when UK guidelines from NICE advised stopping antibiotics prescriptions for prevention of IE.

The study design is a retrospective cohort analysis. Patients who have undergone TVI will be identified from datasets held by the National Institute for Cardiovascular Outcomes Research (NICOR) - the UK TAVI registry (for transcatheter aortic valve intervention), the National Congenital Heart Disease Audit (for transcatheter pulmonary valve intervention), and the Adult Cardiac Surgery Audit (for surgical valve replacement). These NICOR datasets will then be linked to Hospital Episode Statistics to identify patients who have subsequently developed IE. NICOR will send the data identifying these patient cohorts to NHS Digital, who will carry out the linkage. To obtain information about the diagnosis and management of prosthetic valve IE, the research team will contact the consultant who performed the TVI procedure and request further specific information from the patient's record.

In summary, the objectives of this study are

a) to identify the rates of infective endocarditis (IE) after minimally invasive valve replacement (transcatheter valve implantation; TVI), compared with open surgical valve replacement (SVR)

b) to describe the clinical outcomes (e.g. survival) for patients who are diagnosed with IE following TVI or SVR

c) to determine which patient groups are at highest risk of IE after prosthetic valve replacement by TVI or SVR

d) to identify anatomical or procedural factors which are associated with increased risk of IE after TVI or SVR

e) to assess whether the incidence of IE has changed since modification of NICE guidelines on antibiotic prophylaxis. From 2008 onwards NICE advised doctors and dentists not to prescribe routine antibiotic prophylaxis for prevention of infective endocarditis in those with a prosthetic heart valve. The study will analyse whether this guidance has affected the rates of infective endocarditis amongst patients with a prosthetic valve.

Expected Benefits:

Outputs will benefit future patients receiving prosthetic valves, in addition to cardiologists and microbiologists managing the care of patients with infective endocarditis.

Two major benefits are anticipated:

a) This study will help ascertain whether there has been a rise in cases of infective endocarditis (IE) in patients who have undergone prosthetic valve replacement since UK guidelines were changed (to restrict use of antibiotic prophylaxis) in 2008. This will provide surrogate evidence on the efficacy of antibiotic prophylaxis, and in turn, information on whether the UK currently has the correct policy on use of antibiotic prophylaxis.

b) Insight into risk factors and outcome for patients who develop infective endocarditis after transcatheter valve replacement. This is a rapidly growing field, but the incidence, risk factors and outcomes are largely unknown. This is the first study assessing these questions in the UK and potentially would be the largest dataset in the world to date.

Outputs:

To disseminate the results of the study to the wider heart valve disease population, Guys and St Thomas NHS Foundation Trust plan to present the results at major conferences where the key patient representative groups are present (e.g. American College of Cardiology, European Society of Cardiology).

Guys & St Thomas NHS Foundation Trust expect that this project will lead to submission of up to 3 manuscripts to high level general or specialist peer reviewed journals (e.g. British Medical Journal, The Lancet, Journal of the American College of Cardiology, Circulation).

The Trust will also disseminate results through the British Heart Valve Society and Heart Valve Voice, and plan to present the data at a transcatheter valve patient meeting.

Due to journal charges and a lack of central funding the study anticipates that publications will not (initially) be open access, but the study will upload pre-publication manuscripts in open-access repositories.

The timescale for submission is 1-2 years following release of the linked datasets.

This study is independent of NICE and the findings would be published in the peer-reviewed literature. If there was evidence of increasing rates of IE, the study would notify NICE once the manuscript was accepted for publication.

Outputs will contain only aggregate level data with small numbers suppressed in line with the HES analysis guide.

This is a non-commercial project and data will not be used for sales and marketing purposes

Processing:

Data capture
Guys & St Thomas NHS Foundation Trust will use three NICOR datasets (the National Cardiac Surgery Audit, the UK TAVI registry, and the National Congenital Heart Disease Audit) to identify patients who have undergone transcatheter and surgical valve replacement, and details of their procedure. These patient cohorts will be electronically linked to Hospital Episode Statistics (HES) Admitted Patient Care episodes to identify any patient with a primary diagnosis of “acute or subacute infectious endocarditis” (ICD-10 code I33.0), "endocarditis, valve unspecified" (ICD-10 code I38) or "endocarditis and heart valve disorders in diseases classified elsewhere (ICD-10 code I39)". After linkage of the NICOR datasets to HES, all patient identifiers will be removed with the exception of NHS number for the transcatheter valve intervention with infective endocarditis cohort. For this subgroup (estimated to be approximately 70-140 patients) the study plan to contact the Consultant Cardiologist who performed the operation, in order to request limited data regarding the diagnosis and management which is not available by any other means.

Patient populations
a) Transcatheter valve implantation (TVI) patients -
Patients who have undergone transcatheter aortic valve replacement will be identified from UK TAVI registry. Those who have undergone transcatheter pulmonary valve intervention will be identified from the National Audit of Congenital Heart Disease.
b) Surgical valve replacement patients -
Patients who have undergone surgical aortic valve implantation will be identified from the NICOR Adult Cardiac Surgery Audit. Those who have undergone surgical pulmonary valve implantation will be identified from the NICOR Adult Cardiac Surgery Audit and the National Congenital Heart Disease Audit.

Individual patient data
For patients diagnosed with IE after TVI the study has permission from the Confidentiality Advisory Group (CAG) to obtain the patient’s NHS number from NHS Digital. Guys & St Thomas NHS Foundation Trust will then contact the operating consultant to request additional information from the patient’s record.

Study Endpoints
Primary endpoint/analysis:
a) Incidence of IE after TVI and SVR
Secondary endpoints/analyses:
a) Time to diagnosis of IE from valve intervention
b) Patient characteristics in the TVI-IE cohorts (vs those without IE)
c) Prosthetic valve characteristics in the TVI-IE cohorts (vs those without IE)
d) Procedural factors in the TVI-IE cohorts (vs those without IE)
e) Multivariate predictors of IE in patients undergoing TVI
f) Survival of patients diagnosed with IE in the TVI and SVR cohorts
g) Incidence of IE in patients with a prosthetic heart valve before and after 2008
h) Use of prophylactic antibiotics in TVI-IE (vs those without IE)
i) Diagnostic imaging tests/results in those with TVI-IE
i) Microbiology (blood culture/valve explant) in patients with IE
j) Management of patients diagnosed with TVI-IE
k) Analyses above divided by paediatric/adult populations

Statistical Analysis
Patient characteristics will be reported as categorical or continuous variables as appropriate. Group comparisons will be made using the Student t test or Wilcoxon rank sum test (numerical variables), or the chi-square or Fisher exact test for categorical variables. The study aims to identify independent predictors of IE in the TVI and SVR cohorts using a Cox proportional hazard analysis. Survival of those with IE will be reported using Kaplan-Meier analysis. Guys & St Thomas NHS Foundation Trust will also use Kaplan-Meier curves to show the proportion of valves after TVI and SVR which remain free from infective endocarditis over time.

Details of physical security arrangements for data processing:
NHSD will provide the NICOR-HES linked datasets, which will contain the NHS numbers for patients within the TVI-IE cohort. These datasets will be downloaded directly from NHSD using secure file transfer. The datasets will be stored on a dedicated laptop (with encrypted hard drive) which when not in active use, will always kept within locked storage in the Department of Cardiology at St Thomas's Hospital, and is not transported outside of the Department. All data will also be encrypted (to minimum standard AES 256), and a BIOS password will be used to make sure data and device can only be accessed by authorised users (see below). There will be no secondary copies of the datasets. The data will not be used on mobile devices.

Data analysis
The dataset will only be analysed on a dedicated laptop (see above) within the Department of Cardiology at St Thomas's Hospital. This computer will be connected within the Guy's & St Thomas's NHS Foundation Trust maintained network. The data will only be analysed by individuals substantively employed by Guy's and St Thomas' NHS Foundation Trust.

Guy's and St Thomas' NHS Foundation Trust will receive two datasets from NHS Digital. The non-TVI group will contain pseudonymised HES data and the TVI group will contain the same HES fields plus NHS number which is identifiable. Once the NHS number has been used to obtain further data from clinicians it will be securely destroyed. From this point the working dataset used for the analysis will be pseudonymised and will only contain the patient's study number and thus no direct patient identifiers.

The dataset will never be sent by email or transferred onto memory sticks or external hard drives. Where email is required (for example, with individual patient's consultants to gather clinical data), NHS secure email will be used as the only means of communication.

The data will only be used for the purposes described in this document.

HES data for the analysis of alcohol related frequent attenders to hospitals — DARS-NIC-44383-L6C0X

Type of data: information not disclosed for TRE projects

Opt outs honoured: N, Anonymised - ICO Code Compliant, No

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

Purposes: No (NHS Trust, Academic)

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

When:DSA runs 2017-02-01 — 2020-01-31 2017.03 — 2017.05.

Access method: One-Off

Data-controller type: SOUTH LONDON AND MAUDSLEY NHS FOUNDATION TRUST

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Civil Registration (Deaths) - Secondary Care Cut
  3. HES:Civil Registration (Deaths) bridge
  4. HES-ID to MPS-ID HES Admitted Patient Care
  5. Hospital Episode Statistics Admitted Patient Care (HES APC)
  6. Civil Registrations of Death - Secondary Care Cut

Objectives:

The purpose of processing the data is to ascertain "The nature, natural history and characteristics of alcohol-related frequent attenders", by exploring data held within hospital episode statistics to understand this group of patients better including their health and social care needs. The project has 2 specific aims:
Aim 1: Explore in a sample of hospital attenders, which medical and socio-demographic characteristics are associated with alcohol-related frequent attendance and different patterns of health service utilisation.
Aim 2: Explore costs of health service use by Alcohol Related Frequent Attenders (ARFAs).

The two aims are explored by two separate studies outlined below.
Study 1: Natural history of ARFAs
From national Hospital Episodes Statistics (HES) 2011/12 service use pattern of a pseudonymised cohort of ARFAs during 2015/16, 2014/15, 2013/14, 2012/13, 2011/12. This will yield data on natural history of ARFAs including: co-morbidities (ICD 10 code), mode of admission, length of stay, readmissions, age, gender and geography. The researcher will compare ARFA findings to 3 other groups of patients from 2015/16-2011/12 national HES: non-alcohol-related-frequent attenders, non-alcohol-non-frequent attenders and alcohol-related-non-frequent attenders.
Data on the characteristics of frequent attenders and non-frequent attenders will be analysed using STATA SE. A logistic regression approach will be used to explore the variables derived from HES; demographics, diagnosis and attendance frequency.
The analysis of HES will produce a list of characteristics which are generic to ARFAs eg average age, average level of income deprivation etc which will be used to populate a risk stratification model initially for South London and then nationally. The risk stratification model will then be used to calculate the number of people (ARFAs) who could potentially benefit from accessing ARFA services such as 'assertive outreach' (specialist mental health services) treatment both nationally and locally

Study 2: The cost burden associated with ARFAs
Costs of health service usage by the 2015/16 ARFA cohort will be calculated per capita (on the basis of 2015/16 tariffs and occupied beddays) and compared to the costs of non-alcohol related frequent attenders. Total costs of ARFAs will be scaled up to national costs based on epidemiological results from study 1. Costs will be calculated from the health service perspective and will not explore full costs of ARFAs to society.
Sensitivity analysis- Using different assumptions and scenarios, how costs vary based on the definition of an ARFA used will be investigated ie comparing the costs to Kings Health Partners (KHP) of ARFAs with varying number of visits per year. Current literature documents multiple ARFA definitions and impact of ARFAs on health services may be important in finalising a definition going forward.

Expected Benefits:

Excess alcohol consumption is a growing public health problem, causing 5.3% of deaths worldwide in those aged under 60 years. In the UK, alcohol use is the fourth greatest risk factor for years lived with disability and is second only to tobacco as the leading preventable cause of ill health, costing the NHS £2.7 billion annually, with 78% on hospital based care.

Alcohol related hospital admissions have doubled in the last 8 years in England and reducing this burden is a key priority of government public health strategy. It is estimated that 1-2% of attendances to UK A&Es are made by ‘frequent attenders’. Studies show that ‘frequent attenders’ to A&E are also frequent users of other health and social care facilities. There has been a recent call for further research into the predictors of frequent use of healthcare services, supporting the notion that these subgroups are not adequately defined.

Alcohol related frequent attenders (ARFAs) are thought to account for 6.7% of frequent attenders. With no singularly defined way of recording and monitoring ARFA hospital admissions/attendances it is difficult to understand the true burden of ARFAs on the NHS. 21 hospitals in England run programmes for ARFAs , with no common method of identifying patients for treatment. By better understanding the characteristics of ARFAs and their patterns of usage of health services through this study, it is hoped it may become possible to identify preventative interventions to avoid further harms to their own health and prior to assimilating high costs to health services.

This study will benefit patients and the Trusts within the Kings Health Partners through the development of the risk stratification. This will ensure that ARFAs can receive the specialist treatment that they require, affording them direct health benefits in a setting that is more suited to their needs than in an A&E department, but will contribute to a reduction in hospital admissions with concomitant savings to the NHS.

Outputs:

The proposed project directly informs the design and purpose of services for ARFAs at Kings Health Partners hospitals (Guys and St Thomas', Kings College and South London and the Maudsley NHS Trusts). The analysis of HES will produce a list of characteristics (at aggregated level and will not contain data pertaining to individuals) which are generic to ARFAs eg average age, average level of income deprivation etc which will be used to populate a risk stratification model initially for South London and then nationally. The risk stratification model will then be used to calculate the number of people (ARFAs) who could potentially benefit from accessing ARFA services such as assertive outreach treatment both nationally and locally, informing commissioning of services.

This population risk stratification project is part of a wider project to optimise services for ARFAs at KHP, which includes setting up an assertive outreach services (specialist mental health services) to specifically meet the needs of ARFAs.

The project is directly supervised by 2 Professors of Addictions at the National Addictions Centre based at KCL, one of whom leads the alcohol strategy for Kings Health Partners hospitals (Guys and St Thomas', Kings College and South London and the Maudsley NHS Trusts). The alcohol strategy steering group includes lay members, service users and other researchers and clinicians working on alcohol-based projects across South London. The principal investigator reports project progress to the alcohol strategy steering group.

The principal investigator and Professor/alcohol strategy lead are also part of the ARFA clinical network for South London, which meets every 6 weeks. The group consists of practitioners and clinicians working with ARFAs so provides direct insight in to the day-to-day treatment and issues for this particular patient group. The principal investigator reports project progress to this group.

Finally, the principal investigator’s project progress is also monitored on a quarterly basis through King's College London. Project findings are due to be reported November 2018 but due to the close working arrangements with clinicians described above, will inform service design from the outset.

The outputs from all of the projects will include peer reviewed papers in academic journals which will be submitted for publication by May 2018. In addition, lay summaries such as newsletters and blogs (on behalf of the South London Academic Health Science Network and Collaboration for Leadership in Applied Health and Care will be produced (March 2017-April 2018). Conference and seminar presentations to academic, policy, professional in the fields of public health and addiction sciences and public audiences will be made between March 2017 and November 2018. All reports and presentations will be produced containing aggregate results with small numbers suppressed that show trends over time, differences across providers, commissioners, geographical areas and by patient subgroups and patient characteristics. The results will contain estimated correlations showing associations between patient outcomes and patient characteristics, hospital, institutional, geographic and environmental factors.
 
Information about this study and its use of data will be made available to the general public through the South London CLAHRC website. 

Outputs will contain only aggregate level data with small numbers suppressed in line with the HES analysis guide.

Processing:

The applicant will be undertaking processing activities for this project. The applicant (Consultant in public health medicine/innovation fellow) is trained in health care analytics and epidemiology and is up to date with NHS information governance training (last update June 2016).

The applicant holds an employment contract with Guy’s and St Thomas’ NHS Trust which is part of King’s Health Partners (together with King’s College Hospital NHS Trust, King's College London and South London and the Maudsley NHS Trust). As part of the Guy’s and St Thomas’ employment contract,the applicant holds a King’s Health Partners’ “research passport” to enable her to conduct research from any other of the NHS Trust sites within King’s Health Partners. The applicant will be conducting the proposed research from South London and the Maudsley (SLAM) NHS Trust site, as firstly this is where she is geographically based for work; and secondly, because SLAM currently host HES data, having the necessary IT infrastructure and ability to meet information governance requirements.

In terms of the data processing pathway:
- The inpatient HES data is downloaded from NHS Digital and stored on South London and the Maudsley NHS Trust’s server. The server is held on-site at SLAM, and access is restricted to named individuals according to SLAM’s security policy.
- Storage will be on a storage area network and secured by active directory user group.
- Remote access to the database is permitted, but only through terminal Services via secure token (so processing is still carried out on site), and with local printing and downloading disabled.
- Only staff who have signed a confidentiality agreement and have received IG training are permitted access.
- All access to individual files is recorded, and a sample audited to investigate the existence of any adverse incidents, and ensure that appropriate access has been maintained.
- The HES data is imported into STATA SE. Once held in STATA, The applicant will view the data and select a specific cohort for each individual study. Commonly a process will initially take place to define the particular cohort of interest in terms of e.g. individual diagnostic codes or procedure codes. The researchers will use routinely available filter definitions where possible, but may amend these based on the nature of each study’s group of interest. Depending on the research a similar control group may be established.
- The applicant then analyses the data, before applying the relevant disclosure controls to any output. Software used will be STATA SE; typically this will involve analysis on several outcome measures, risk adjustment and the construction of control groups.
- No record level data would be linked to this dataset, but it may be combined with publically available demographic or geographic data, for example in relation to local Trust performance
- Outputs are thus produced which consist of aggregate data (or indicator/statistical data) only with small numbers suppressed in line with the HES analysis guide.

The applicant will be the only person who will access the data. They are a substantive employee of Guys and St Thomas' which includes in the employment contract a research passport for the other sites in the Kings Health Partners. The data requested will only be used for the purposes described in this document.

South London and Maudsley NHS Foundation Trust will not link the data disseminated by NHS Digital to any other data they may already hold.

Project 11 — DARS-NIC-35216-D6G6M

Type of data: information not disclosed for TRE projects

Opt outs honoured: Y

Legal basis: Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Sensitive

When:2016.09 — 2016.11.

Access method: One-Off

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care

Objectives:

To establish the relapse rate of infective endocarditis within one year, in patients treated with heart valve surgery at the Guys & St Thomas Trust (GSTT) centre over a 10 year period.

Infective endocarditis (IE) is a deadly disease associated with high mortality (15 - 30%) and severe complications. It is caused by transient bacteria in the bloodstream attaching on to the endocardium and heart valves leading to destruction of the valve tissue with often fatal consequences. Emergency treatment is required in a specialist centre with intensive and prolonged intravenous antibiotic therapy and often high risk cardiac valve surgery. This is a costly and protracted treatment regime including intensive care and frequent outpatient follow ups. Added to this is the ever increasing concern regarding antimicrobial resistance and antibiotic side effects. Should the patient survive the initial episode and treatment, there remains an elevated risk of relapse. However, because the incidence is low and the early mortality rate high, there is limited evidence to improve the management and randomised trials are almost impossible to conduct. Therefore retrospective studies (such as this audit) can provide valuable new information for meta-analysis. As GSTT are a specialist centre, there is a cohort of patients treated for IE that can provide valuable evidence to improve management of IE.

The objective for this project is to evaluate whether the antibiotic regime (which is shorter and therefore less costly than internationally recommended) is as effective at reducing the relapse rate of infective endocarditis in patients treated surgically (i.e. undergoing valve replacement surgery) at the centre. This is over a 10 year period.

By assessing each patient for confirmed relapse or new episode of IE within the first year of surgery GSTT can provide a robust evaluation. Any relapse or new episode can only be confirmed by hospital admission and clinical diagnosis. Therefore this is key information that is required.

GSTT have an identified cohort of 247 individual patients, including information relating to relapse, new episode or death. 40 patients have incomplete information that need to be clarified.

As the incidence of endocarditis is a rare occurrence, only a small number of datasets (40) are required to complete this project. The overall cohort is small (@ 250). However, this is considered a significantly large evaluation (most other projects cover only 30-40 individuals) and the absence of 40 datasets will seriously undermine the impact of the analysis and the quality of the results.

As GSTT are a tertiary centre, not all patients live locally and further episodes and/or relapses may have been treated at other hospitals elsewhere, of which GSTT are unaware. This includes some patients who are poor compliers with medical care and have no registered GP.

Some patients have since died and records of the one year post surgery period are no longer available from their GPs. For surviving patients, some GPs are unable to clarify the one year post operative period.

As this is a service evaluation and not a research study there is no patient consent process. Therefore, Section 251 approval has been obtained to request Hospital Episode Statistics (HES) from the Health and Social Care Information Centre (HSCIC). The HES data requested will fill in data gaps for deceased patients and patients with unknown history after treatment.

Consultant code is required as diagnosis for IE can be complex. It may be necessary for the Trust to contact the Consultant responsible for the care episode to discuss and clarify diagnosis. This will ensure all findings are accurate.



Expected Benefits:

The final report will be fed back to GSTT clinicians and implemented into clinical practice.

If the findings show a low relapse rate after abbreviated antibiotic treatment courses, GSTT anticipate these findings will influence UK practice and national/international guidelines. The results will be published in a peer-reviewed journal and will thus be available to reviewers planning future national or international guidance documents.

The consequences of a shorter-than-recommended courses of antibiotics are reduced costs, less generation of antimicrobial resistance, and less antibiotic side effects.

The patient benefit will be improved survival combined with a shorter hospital stay and fewer hospital clinic follow ups.

A target date is difficult to define in this situation but current practice at the Trust site will be immediately implemented based on the evidence.

Outputs:

The aim is to produce a detailed summary of all patients treated over the 10 year period that will demonstrate any relapse after surgery for infective endocarditis in a centre that uses shorter than internationally recommended antibiotic courses. This will include bacteria specific infection and tailored antibiotic regimes used.

The final report will be a service evaluation for GSTT that will be fed back to the clinicians and implemented into standard clinical practice. GSTT will also submit findings for publication in high level medical journals (the initial target journal is "Heart") in order to influence national/international guidelines such as NICE.

The Cardiovascular Patient Forum have agreed for the Trust to present and discuss their project in September (26th) 2016.

Processing of data is now expected to be by the end of August 2016 with subsequent publication of reports and journal submissions.

An annual report will be sent to CAG by April 2017.

All outputs will only contain aggregated data with small numbers suppressed in line with HES analysis guide.

Full and final analysis and identifiable data destruction will be completed within 6 months of receiving the data.

Processing:

GSTT have conducted the following information searches on our cohort of 247 patients:

All patients have been assessed for readmission to this Trust within 1 year of surgery and any episodes clarified for IE.
All patients deceased within 1 year of surgery have cause of death analysis completed by death certification.
All surviving patients’ GPs have been contacted for evidence of admission for IE within one year of surgery to other hospitals – several have been unable to clarify.

40 patients have incomplete follow up information because either:
1. the patient is now deceased
2. has left the UK.
3. the GPs have been unable to confirm accurate health history within one year following surgery.

Once GSTT have received the HES data from HSCIC, they will identify any admissions for episodes of endocarditis or possible endocarditis.
These will then be investigated by contacting the relevant hospitals' microbiology department for clarification and confirmation of diagnosis and required treatment. Once all necessary information has been obtained, the data will be aggregated. Diagnosis for IE can be complex. It may be necessary for the Trust to contact the Consultant responsible for the care episode to discuss and clarify diagnosis should, and only if, a HES record suggests a possible episode of IE. The patients' sensitive and identifiable data will be required in this situation to ensure the correct patient is discussed. This will ensure all findings are accurate. Once diagnosis is clarified, all identifiable and sensitive data will be anonymised along with the rest of the cohort data.

All other admission data will be disregarded and destroyed.