NHS Digital Data Release Register - reformatted

The Clatterbridge Cancer Centre NHS Foundation Trust projects

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

🚩 The Clatterbridge Cancer Centre NHS Foundation Trust was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. The Clatterbridge Cancer Centre 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.

Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204580-F5B0C

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), Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (NHS Trust, Network)

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

When:DSA runs 2019-02-18 — 2020-02-17 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: THE CLATTERBRIDGE CANCER CENTRE 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 Cheshire and Merseyside 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 The Clatterbridge Cancer Centre NHS Foundation Trust. The Clatterbridge Cancer Centre NHS Foundation 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 - The Clatterbridge Cancer Centre NHS Foundation 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.


Cheshire and Merseyside Cancer Alliance

The Clatterbridge Cancer Centre NHS Foundation Trust (the Clatterbridge Cancer Centre) will directly access the Cancer Waiting Times System on behalf of Cheshire and Merseyside Cancer Alliance , which covers a population of more than 2 million people.

The Clatterbridge Cancer Centre NHS Foundation Trustworks with health organisations across Cheshire and Merseyside including 14 acute and specialist providers, 12 clinical commissioning groups, 1 community providers and 8 hospices.

Acute/Specialist Providers
Countess of Chester Hospital NHS Foundation Trust (Acute)
East Cheshire NHS Trust (Acute)
Mid Cheshire Hospitals NHS Foundation Trust (Acute)
Aintree University Hospital NHS Foundation Trust (Acute)
Alder Hey Children’s NHS Foundation Trust (Specialist)
Liverpool Heart and Chest Hospital NHS Foundation Trust (Specialist)
Liverpool Women’s NHS Foundation Trust (Specialist)
Royal Liverpool and Broadgreen University Hospitals NHS Trust (Acute)
Southport and Ormskirk Hospital NHS Trust (Acute)
St Helens and Knowsley Teaching Hospitals NHS Trust (Acute)
The Walton Centre NHS Foundation Trust (Specialist)
Warrington and Halton NHS Foundation Trust (Acute)
Wirral University Teaching Hospital NHS Foundation Trust (Acute)

CCGs
NHS Eastern Cheshire
NHS South Cheshire
NHS Vale Royal
NHS West Cheshire
NHS Liverpool
NHS Halton
NHS Knowsley
NHS South Sefton
NHS Southport and Formby
NHS St Helens
NHS Warrington
NHS Wirral

Community Providers

Bridgewater Community NHS Trust

Hospices

Claire House
Hospice of the Good Shepherd
Halton Haven
Wirral Hospice St Johns
St Roccos Hospice
Queenscourt Hospice
Wollowbrook Hospice
St Josephs Hospice
Woodlands Hospice
Marie Curie Hospice




Data access

The CWT system provides one organisation (the Clatterbridge Cancer Centre NHS Foundation Trust) 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

The Clatterbridge Cancer Centre NHS Foundation Trust 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 12 CCG's listed above 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 the Clatterbridge Cancer Centre NHS Foundation Trust.

Investigating breaches
The Clatterbridge Cancer Centre NHS Foundation 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
The Clatterbridge Cancer Centre 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 the Clatterbridge Cancer Centre NHS Foundation Trust 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.

The Clatterbridge Cancer Centre NHS Foundation Trust will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements.

The Clatterbridge Cancer Centre NHS Foundation Trust’s 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. The Clatterbridge Cancer Centre NHS Foundation 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 patients 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:

Cancer Alliances have previously had access to Cancer Waiting Times reports and pseudonymised data through the system on Open Exeter, under an agreement with NHS England. This has enabled analysis to inform service improvement both to achieve the national Cancer Waiting Times standards and also wider Cancer pathway improvement work, which will have contributed to oncoming improvements to Cancer survival, and patient experience. Examples of specific work undertaken by this Cancer Alliance previously include:-:- - Baselining mapping work with acute providers to understand cancer pathways, - Monthly reports to inform discussions with Acute Provider CEOs, Cancer Clinicians and Cancer Managers across the area, - Information to support the development of transformational funding bids which focus on pilot work on vague symptom pathways, clinical - Triage and patient navigator work. - Data to support clinical discussions within their 12 Tumour Site Specific Group Meetings.

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 patients 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 Clatterbridge Cancer Centre NHS Foundation Trust will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the the Clatterbridge Cancer Centre NHS Foundation Trust servers. Role Based Access Control prevents access to data downloads to employees outside of the analytical team responsible for producing outputs.

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 organisation’s 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).

The Clatterbridge Cancer Centre NHS Foundation 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 the Clatterbridge Cancer Centre NHS Foundation 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). Cheshire and Merseyside Cancer Alliance will only access data for patients within their geographical remit- namely in the Cheshire and Merseyside region.

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 NHSmail.
Aggregate data/ graphical outputs may be shared 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 NHS England, NHS Improvement, local CCG's and Providers. 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 Clatterbridge Cancer Centre NHS Foundation Trust 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.

Un-CoV-er: Understanding the impact of SARS- CoV-2 infection in patients with blood cancer. (ODR1718__301) — DARS-NIC-656811-F7T9C

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (NHS Trust)

Sensitive: Sensitive

When:DSA runs 2023-12-11 — 2026-12-10 2024.05 — 2024.05.

Access method: Ongoing

Data-controller type: THE CLATTERBRIDGE CANCER CENTRE NHS FOUNDATION TRUST

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations
  2. NDRS Linked Cancer Waiting Times (Treatments only)
  3. NDRS Linked DIDs
  4. NDRS Linked HES AE
  5. NDRS Linked HES APC
  6. NDRS Linked HES Outpatient
  7. NDRS National Radiotherapy Dataset (RTDS)
  8. NDRS Rapid Cancer Registrations
  9. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Objectives:

The Clatterbridge Cancer Centre NHS Foundation Trust requires access to NHS England data for the purpose of the following research project: Un-CoV-er: Understanding the impact of SARS- CoV-2 infection in patients with blood cancer.

The following is a summary of the aims of the research project provided by The Clatterbridge Cancer Centre NHS Foundation Trust:
The overall aim of this study is to establish an evidence base that will lead to a more stratified approach to protecting people with blood cancer from COVID-19 during the chronic phase of the pandemic. The study has been designed as a population-based, observational, retrospective cohort study and will involve the analysis of England-wide data obtained from the National Cancer Registration and Analysis Service (NCRAS) and NHS England. It will be performed in two parts.

Part 1: Incidence and severity of SARS-CoV-2 infection

This part of the study will document the incidence and severity of SARS-CoV-2 infection in people with blood cancer compared to a control cohort representative of the general population. It will also elucidate risk factors for acquiring SARS-CoV-2 infection and experiencing severe or fatal COVID-19 outcomes. Key research questions are:

What was the rate of SARS-CoV-2 infection in people with blood cancer during the different phases of the pandemic, and how does this compare with the general population?

What were the risk factors for acquiring SARS-CoV-2 infection in people with blood cancer?

What was the rate of severe or fatal COVID-19 in people with blood cancer who were infected with SARS-CoV-2, and how does this compare with the general population?

What were the risk factors for developing severe or fatal COVID-19 in people with blood cancer who were infected with SARS-CoV-2?


Part 2: Impact of COVID-19 on cancer diagnosis, management and outcomes

A range of COVID-19 mitigation strategies were implemented at the start of the pandemic aiming to reduce the risk of viral exposure, minimise iatrogenic immunosuppression and free up capacity in secondary care to deal with the COVID surge. However, the extent to which these measures were implemented and their effect on cancer diagnosis, treatment and outcomes is unclear. Part 2 of the study will capture this information, not only to shed light on the overall uptake and impact of COVID-19 mitigation strategies, but also as a retrospective evaluation of specific treatments. Key research questions are:

How did the diagnosis and management of different types of blood cancer change as a result of the pandemic?

Were specific changes in the diagnosis and management of blood cancer uniformly distributed, or were some patient groups affected more than others?

What was the clinical effectiveness, toxicity and cost effectiveness of novel or variant treatment approaches applied during the course of the study?


The following NHS England data will be accessed and disseminated annually:


• Linked NDRS Cancer Registration is the cohort-defining dataset alongside linked Rapid Cancer Registrar Dataset (RCRD) and Systemic Anti-Cancer Treatment (SACT) and will help identify the different types of blood cancers. Furthermore, it will provide the necessary information related to when the diagnosis was made, length of diagnosis and its relation to patient demographics.

• NDRS Hospital Episode Statistics Admitted Patient Care (HESAPC), NDRS Hospital Episode Statistics Accident & Emergency (HESAE), NDRS Hospital Episode Statistics Outpatients (HESOP). These datasets are necessary as it will help understand the emergency, inpatient and outpatient admissions related to therapy that the patient has received. Furthermore, it will enable correlation with patient demographics to understand if particular patients are at risk of complications such as treatment side effects as well as COVID infections. HES data will also enable health economics analyses.

• NDRS Cancer Waiting Times (Treatment only) (CWT) dataset is necessary as it will help to understand the differences in cancer waiting times pre- and post-COVID.

• NDRS Diagnostic Imaging Dataset (DID) dataset is necessary as it will help to understand the route to diagnosis and any geographic variation in access to diagnostic imaging. Furthermore, it will help in health economics analysis.

• NDRS National Radiotherapy Dataset (RTDS) is the dataset that will help provide information about radiotherapy treatment received and enable correlation with patient demographics. Furthermore, health economic analysis will be performed using this dataset.

• NDRS Systemic Anti-Cancer Therapy (SACT) dataset is crucial in providing information about anti-cancer therapy received pre- and post-COVID and how this relates to demographics, geography, markers of social deprivation and patient outcomes.

• NDRS Rapid Cancer Registration Dataset (RCRD) dataset is required to complement the cancer registration data and provide more concurrent cases of cancer diagnosis.


The level of the data will be pseudonymised.


The data will be minimised as follows:
For all datasets:
• Limited to data from January 2014 to the most recent available data.
• Pseudonymised data will be obtained for data minimisation purposes.
• Limited to conditions relevant to the study identified by specific ICD or OPCS codes; ICD-O-3/ICD-10
o ICD-10: C44, C81-C96.
o ICD-O-3: 9590/3, 9591/3, 9596/3, 9597/3, 9650/3, 9651/3, 9652/3, 9653/3, 9654/3, 9655/3, 9659/3, 9661/3, 9662/3, 9663/3, 9664/3, 9665/3, 9667/3, 9670/3, 9671/3, 9673/3, 9675/3, 9678/3, 9679/3, 9680/3, 9684/3, 9687/3, 9688/3, 9689/3, 9690/3, 9691/3, 9695/3, 9698/3, 9699/3, 9700/3, 9701/3, 9702/3, 9705/3, 9708/3, 9709/3, 9712/3, 9714/3, 9716/3, 9717/3, 9718/1, 9718/3, 9719/3, 9724/3, 9725/3, 9726/3, 9727/3, 9728/3, 9729/3, 9731/3, 9732/3, 9733/3, 9734/3, 9735/3, 9737/3, 9738/3, 9740/1, 9740/3, 9741/3, 9742/3, 9750/3, 9751/3, 9752/1, 9753/1, 9754/3, 9755/3, 9756/3, 9757/3, 9758/3, 9759/3, 9760/3, 9761/3, 9762/3, 9764/3, 9765/1, 9766/1, 9767/1, 9768/1, 9769/1, 9800/3, 9801/3, 9805/3, 9806/3, 9807/3, 9808/3, 9809/3, 9811/3, 9812/3, 9813/3, 9814/3, 9815/3, 9816/3, 9817/3, 9818/3, 9820/3, 9823/3, 9826/3, 9827/3, 9831/3, 9832/3, 9833/3, 9834/3, 9835/3, 9836/3, 9837/3, 9840/3, 9860/3, 9861/3, 9863/3, 9865/3, 9866/3, 9867/3, 9869/3, 9870/3, 9871/3, 9872/3, 9873/3, 9874/3, 9875/3, 9876/3, 9891/3, 9895/3, 9896/3, 9897/3, 9898/1, 9898/3, 9910/3, 9911/3, 9920/3, 9930/3, 9931/3, 9940/3, 9945/3, 9946/3, 9948/3, 9950/3, 9960/3, 9961/3, 9962/3, 9963/3, 9964/3, 9965/3, 9966/3, 9967/3, 9970/1, 9971/1, 9971/3, 9975/3, 9980/3, 9982/3, 9983/3, 9984/3, 9985/3, 9986/3, 9987/3, 9989/3, 9991/3, 9992/3.


The Clatterbridge Cancer Centre NHS Foundation Trust is 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.


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 it will identify patient variables which may correlate with the severity of COVID and treatment outcomes. The analyses will identify patients who may be at particular risk of worse outcomes and help inform policy and strategy to improve patient care for the most disadvantaged patients. Furthermore, it will enable the identification of the best clinical treatment algorithms for patients with cancer in the post-COVID era.


The funding comes from multiple sources. Current funders include:
• Isle of Man Anti-Cancer Association – Funding is in place until 31/07/2023.
• Gilead Sciences Ltd – Funding is in place for 12 months from payment of the first instalment of the grant.
• The Clatterbridge Cancer Centre NHS Foundation Trust – The date for funding is to be decided as a no-cost extension has been applied for, but it is likely to be another 1 year.
• Blood Cancer UK – Funding is in place for 36 months.
• University of Liverpool – Funding is in place until 14 July 2023.
Funding to continue the work described will be sought on an ongoing basis.

The funder(s) will have no ability to suppress or otherwise limit the publication of findings.


The University of Liverpool are processors acting under the instructions of The Clatterbridge Cancer Centre NHS Foundation Trust. University of Liverpool’s role is limited to processing and storing the data.

1) Data will be accessed by undergraduate, Masters or PhD students affiliated with University of Liverpool. Any student working with the data held under this Agreement must have completed relevant data protection and confidentiality training and are subject to University of Liverpool’s policies on data protection and confidentiality. Any students accessing the data will do so under the supervision of a substantive employee of University of Liverpool. University of Liverpool would be responsible and liable for any work carried out by students. These students would only work on the data for the purposes described in this Agreement.

2) An individual with an honorary contract with the University of Liverpool . The individual has completed mandatory data protection and confidentiality training and is subject to University of Liverpool’s policies on data protection and confidentiality. The individual accessing the data is a substantive employee of AIMES Management Service. University of Liverpool would be responsible and liable for any work carried out by the individual. The individual would only work on the data for the purposes described in this Agreement. AIMES Management Service are required as they specialise in data integration, curation and cleaning and this is something which was not available at the University of Liverpool at the time. Furthermore, the sponsor had worked with the organisation and approved its funding. There is a contract in place to specify the scope of the work.


A patient representative has been already approached to be part of the study team. The patient representative is strongly supportive of the overall aim of the study as well as its specific objectives and will contribute to the refinement and prioritisation of specific research questions. The patient representative is also willing to play an active role in disseminating the findings to service users.


In line with the National data opt-out policy, opt-outs are not applied because the data is not Confidential Patient Information as defined in section 251(10) and (11) of the National Health Service Act 2006.

Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). https://digital.nhs.uk/ndrs/patients/opting-out.

Yielded Benefits:

Expected Benefits:

The project is of national interest and has become recognised project as part of the NCRI haemato-oncology portfolio of projects. The results will further understanding of blood cancers as a whole. The results may add to a body of evidence available to policymakers that they can use to better inform and optimise the provision of health and social care.


Particularly, the project will identify patients at risk of COVID infections and worse outcomes. This will enable risk stratification of these patients. Furthermore, analyses will guide healthcare workers towards which treatments are effective in particular groups of patients (based on clinical/demographics) and how to manage them effectively. Specifically, the project will look at novel agents in blood cancers and understand their toxicity profile which will complement data from clinical trials. This will help to understand the true burden of side effects in the patient cohort so that they could be risk-managed appropriately.


The research findings will be shared with stakeholders and policymakers, including national policy steering groups such as NCRI haemato-oncology groups, patient groups, associations, and publications. The analyses conducted will focus on both clinical and patient-centric perspectives, aiming to generate maximum public benefit through the study's outputs. By analysing this extensive dataset, it is aimed to bridge the knowledge gap regarding patient outcomes in real-world settings. This analysis will provide insights into the true burden of the disease and the impact of various factors, such as baseline patient characteristics and treatment received, in the context of the COVID-19 pandemic. The results obtained from clinically relevant research questions will guide the development of optimal treatment strategies and inform national BSH guidelines on treatment algorithms. Ultimately, the overarching objective is to enhance patient care by utilising real-world data to shape future medical practices.


A group of patients from prominent patient organisations such as Lymphoma Action and Chronic Lymphocytic Leukaemia (CLL) support association have been engaged. They are an integral part of the UnCoVer project and help develop and prioritise the research clinical questions. Furthermore, the Clatterbridge Cancer Centre NHS Foundation Trust are in dialogue with Blood Cancer UK regarding the output of the analysis guiding the Blood Cancer Action Plan. The outputs from the research will be disseminated to patients and presented at their meetings, local and international meetings. The project has been widely advertised to national experts in blood cancers through the NCRI Lymphoma and Haemato-oncology Groups and has received positive feedback already. Furthermore, the Clatterbridge Cancer Centre NHS Foundation Trust aim to present the findings at large international conferences and publish in high-impact journal to ensure that the findings of the project are advertised to a wider audience.

Outputs:

The expected outputs of the processing will be:
• Submissions to peer reviewed journals
• Presentations at national and international conferences


The data will include summary of patients and descriptive statistics. It will not contain patient level information.


The outputs will be communicated to relevant recipients through the following dissemination channels:
• Journals
• Posters displayed at American Society of Haematology (ASH), European Haematology Association (EHA), British Society of Haematology (BSH) amongst other haematology conference.


It is expected that the first publication to submit in a peer reviewed journal is to be ready in about 9 months, after this, there should be quick succession of publications every 4-6 months (or less), as the data analyses process becomes more efficient. Prior to these publications, it may be aimed to present these findings as oral/poster presentations at ASH/EHA/BSH conferences.

Processing:

No data will flow to NHS England for the purposes of this Agreement.

NHS England data will provide the relevant records from the HESAPC, HESAE, HESOP, CWT, DID, Cancer Registrations, Rapid Cancer Registrations, RTDS, SACT, NCDA, CPES datasets to the University of Liverpool. 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 be stored on servers at the University of Liverpool. University of Liverpool uses offsite back-up services provided by the IT services at the University.

The data will be accessed onsite at the premises of University of Liverpool who will use the relevant subset of data to undertake the socio-economic analysis described above and this will be accessed onsite at the University of Liverpool.

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

The data will not leave England/Wales at any time.

Access is restricted to employees or students of University of Liverpool who have authorisation from Principal Investigator. Access will be restricted and granted by the respective University’s IT support centre .

The Clatterbridge Cancer Centre NHS Foundation Trust is not permitted to access the data. All personnel accessing the data have been appropriately trained in data protection and confidentiality.

The data will not be linked with any other data outside of the scope of the agreement and
there will be no requirement and no attempt to reidentify individuals when using the data.

The study team will analyse the data for the purposes described above.

Project 3 — DARS-NIC-14170-X2G3L

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, N, Y (Section 251)

Legal basis: National Health Service Act 2006 - s251 - 'Control of patient information'. , Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012, Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012)

Purposes: ()

Sensitive: Sensitive, and Non Sensitive

When:2019.05 — 2017.05.

Access method: One-Off

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Civil Registration - Deaths
  3. HES:Civil Registration (Deaths) bridge
  4. Hospital Episode Statistics Accident and Emergency
  5. Hospital Episode Statistics Outpatients
  6. Office for National Statistics Mortality Data

Objectives:

National Clinical Analysis and Specialised Applications Team (NATCANSAT) is hosted by The Clatterbridge Cancer Centre NHSFT. NATCANSAT supports a range of DH and NHS organisations involved with National Cancer and Cardiac Programs by providing detailed analysis as required with reference to specific diagnoses and/or procedures. Only individuals substantively employed by the Trust, working for NATCANSAT, have access to the data.

Pseudonymised Data
Wherever possible, analyses are undertaken using pseudonymised data but identifiers are necessary for different reasons. Unique Identifiers are required only for the linkage process, in order to generate pseudonymised datasets for further analysis. Careful consideration is always given to the use of identifiable data, and whether it is appropriate or necessary for the purpose.

This approach alongside the wider availability of linked data sources has allowed NATCANSAT to limit its use of identifiable data very considerably in recent years.

Pseudonymised and sensitive extracts are used to carry out analysis of hospital activity for a range of diagnosis and procedure codes, in order to support the objectives identified below. The extract contains all records to support work which compares affected patients with more general populations, or to provide denominators for complex analysis.

Identifiable Data for Cancer/Cardiac
Identifiable extracts are for patients identifiers for patients identified as having diagnoses or procedures which are relevant to cancer or cardiovascular disease. These will be linked to the full HES dataset, to the radiotherapy dataset (RTDS), and other data sources as set out in the CAG approvals granted. They will also be used with geographical information systems (GIS) to carry out spatial analysis.

Date of Birth is preferred by cancer registry linkage algorithms where it is used to validate the NHS number in the absence of a valid NHS Number status indicator in the HES data.
NHS number is used as the key field for linkages carried out by NATCANSAT, it is requested from all of the data sources NATCANSAT link to.

Postcode of home address from the HES database is requested for geographical location purposes. Full Postcode is used in conjunction with geographical information systems to establish a grid reference for the patient’s home. This allows work to establish the geographical spread of patients, and to identify catchment areas and population and measure variations in provision of service in relation to other factors.

NATCANSAT have carried out large scale analyses of cancer service provision in the UK since 1998, these analyses have been used to allocate resources from central capital resource programs and to inform the processes for policy making and business case development across the DH and NHS. PIAG originally granted section 60 support for this use of data in 2003, and this was expanded to also facilitate linkage to cancer registration data and sharing of data between NATCANSAT and the English cancer registries in 2003 and 2004. In 2013 NATCANSAT reviewed it’s use of Cancer Data and made a new application to CAG replacing a number of previous approvals, this approval (CAG 1-06(FT2)/2013) provides the legal basis to hold identifiable data for patients with a diagnosis of cancer, or undergoing procedures relevant to cancer, and to link these data to a range of related datasets and has been reviewed and upheld by CAG each year since.

NATCANSAT analyse data to demonstrate variation in coronary heart disease (CHD) service provision in England for preparation of guidance, planning service configuration and identifying areas for action. PIAG granted section 60 support in 2003 for NATCANSAT to hold identifiable data for patients with a diagnosis of cardiovascular disease, or undergoing procedures related to cardiovascular disease, and to link these data to other specific datasets. This approval (PIAG 4-09(g)/2003) has been reviewed and upheld each year.

The objectives are described in detail below, when NATCANSAT is tasked to carry out a specific piece of analysis work to meet these objectives, a governance review is undertaken by the Senior Analyst specifying the work alongside the Head of NATCANSAT, or the Senior Analyst responsible for Information Governance. The purpose of the review is to establish whether it is appropriate to carry out the work in terms of
• Will the output from the work meet the needs of the request?
• Is the output already available elsewhere?
• Does NATCANSAT have permission to use the required data for the purpose specified?
• Does NATCANSAT have a legal basis to process the data needed for the purpose specified?

The purpose of analysis is to fulfil the objectives below;
Objective One
• Policy Development (eg: provision of specific tabulations for expert clinical groups, or for inclusion in DH policy publications)
NATCANSAT supports DH expert working groups and committees in their development of policy. In order to provide analysis which:
o supports clinical trial or other evidence regarding the new policy being proposed (eg: variation in outcome for patients undergoing a particular procedure who have a particular diagnosis)
o helps to identify the volume of cases which might be impacted by a change (eg: the number of patients requiring readmission to hospital after undergoing a particular procedure)
o assesses the effect that a new policy might have on the service (eg: identify the additional resources which might be required if the criteria for undertaking a particular procedure are changed)

Objective Two
• Performance Management (eg: provision of tabulations or interactive tools which identify variations in service between providers and/or identify trends in response to change)
NATCANSAT provides support to DH and the NHS as identified in section 4 above in identifying progress in the implementation of new policy, or identifying trends in specific measurables which may indicate progress towards a particular target or goal. Performance management objectives fall into the following categories:
o Development of a measure or measures which can be used to report on progress (including a clear definition of patient cohort and outcome)
o Baseline reporting of performance against the measure(s)
o Regular reporting of change in the measure.
(eg: NATCANSATs support of the implementation of the 23-hour model for breast cancer surgery)

Objective Three
• Benchmarking (eg: provision of tabulations or interactive tools which identify variations in activity or outcome between providers)
Benchmarking analysis forms an important part of NATCANSAT’s output in order to inform the service of variations in practice and outcome, to identify areas of strength and weakness in the service which may form examples of good practice, or require additional support. The variation identified may lead to changes in policy.

Objective Four
• Service Planning/Reconfiguration (eg: geographical analysis to identify likely patient flows associated with a change in service, or to predict the impact on travel times)
NATCANSAT provides to NHS and DH organisations (Restricted to the organisations included in the SRSA 2007, s42(4) ) a range of analyses associated with service reconfiguration on a local or national basis. Analyses range from calculation of the resources required at a new facility and the potential reduction in activity at those facilities currently providing a service, to assessment of the most appropriate locations for a new national service, including the projected activity at each location.

Yielded Benefits:

NATCANSAT was reconfigured during 2017 and a large number of staff were made redundant. As a consequence of this, the only project completed was a piece of valuable work under objective 3, which benchmarked the outcome (survival) of patients with non-small cell lung cancer between different radical radiotherapy treatment regimes. Further similar work is planned attempting to replicate the results for further years (as the cancer registry data becomes available), and for different tumour sites.

Expected Benefits:

Objective One
• Policy Development
NATCANSAT supports DH expert working groups and committees in their development of policy. Analysis of the HES (and linked) data benefits patients by facilitating evidence based decision making by these groups, where the policy being developed needs to include:
o Numbers of patients and outcomes for specific patient cohorts
o Volume of cases affected by a proposed change
o Impact of the change in the service (cost/resources/travel times/critical mass etc)
Example: DH Cardiovascular Strategy
Supported by the analysis carried out by NATCANSAT, the committee developing the strategy made a number of recommendations regarding the improvement of diagnosis and treatment of Cardiovascular Disease, which will save lives, and improve the quality of life of survivors.

Objective Two
• Performance Management
NATCANSAT provides support to NHS and DH organisations in identifying progress in the implementation of new policy, or identifying trends in specific measurables which may indicate progress towards a particular target or goal. Performance management benefit patients by facilitating service improvement in the following ways:
o Development of a measure or measures which can be used to report on progress (including a clear definition of patient cohort and outcome)
o Baseline reporting of performance against the measure(s)
o Regular reporting of change in the measure.
• As a result cost reductions and improved care can be provided.
Example: Performance Management – 23 hour breast model
The monthly performance management data provided to NHS Improvement and participating providers on their progress in implementing shortened lengths of stay for patients undergoing mastectomies supported NHS Improvement to work with Providers to implement the new policy resulting in reduced costs for the service and improved outcomes for patients.

Objective Three
• Benchmarking
Benchmarking analysis work carried out by NATCANSAT benefits patients by informing the service of variations in practice and outcome, identifying areas of strength and weakness in the service which may form examples of good practice, or require additional support. The variation identified may lead to changes in policy.
Example: Benchmarking – Transforming In-patient Care
The National Cancer Director used a breakdown of trends in bed days for cancer patients by year/disease type/patients classification/speciality/admission method in order to identify the reasons for variation in length of stay for cancer patients and to highlight areas where reductions might be possible. This facilitated a reduction in the cancer bed days, resulting in cost savings for the service and improvement in quality of life for cancer patients.

Objective Four
• Service Planning/Reconfiguration
NATCANSAT provides to NHS and DH organisations a range of analyses associated with service reconfiguration on a local or national basis. Analyses range from calculation of the resources required at a new facility and the potential reduction in activity at those facilities currently providing a service, to assessment of the most appropriate locations for a new national service, including the projected activity at each location.
Example: Service Reconfiguration – Cardiac Revascularisation Service
NATCANSATs analysis facilitated the provision of a cardiac revascularisation service at optimal locations, and an accurate estimate of the expected demand in each location. As a result the service was able to locate these services optimally and provide the appropriate resources at each site. The outcome of this change will be to save lives by ensuring that patients have access to this life-saving treatment in a timely fashion, and to save money by ensuring that the correct resources are installed in each facility.

Outputs:

Outputs are in the form of anonymised, aggregate tables and interactive tools, and also maps and narrative.

Interactive tools normally consist of a ‘microsite’ using SQL server reporting services and SQL server cubes placed on a website and accessed securely. Identifiable or sensitive items are NEVER included in the source data used to populate interactive tools. Only the minimal dataset needed is included. Record level extracts are NEVER shared with third parties.

Output which is shared with third parties (beyond sub-licenses) does not include aggregations which are able to produce ‘small numbers’ as defined in the HES Analysis Guide (eg: data is not aggregated below Strategic Health Authority level), or small numbers are suppressed, including totals/sub-totals, in line with the HES Analysis Guide.

Analysis has been used:
• Analysis of resection rates for prostate cancer using linked cancer registration and HES data for 2009 and 2010 for a cancer network This work used identifiable data for linkage purposes. The complete Cancer Registration database was needed in order to include those patients with prostate cancer who had not been admitted to hospital (and had no HES record) in the denominator.
• Analysis of the NHS footprint for long term survivors of cancer using HES data with updated death data for the National Survivorship Initiative. Identifiable data was needed for linkage to the demographics batch tracing service, to carry out up-to-date survival analysis for these patients.
• DH Cardiovascular Strategy where it supported important decision making around the placement of the service for acute cardiac revascularisation services, thus ensuring access to this life saving treatment for patients in all geographical areas. Identifiable data was needed for linkage to the demographics batch tracing service, to carry out up-to-date survival analysis for these patients.
• DH Cardiac Rehabilitation Document which outlines analysis demonstrating the positive impact of rehabilitation on re-admission rates after cardiac events, and supports the development of business cases to provide this important service to improve patient care. No identifiable data used for this analysis.
• DH Enhanced Recovery Program where it was used to support the implementation of a program to improve patient safety and reduce costs by shortening length of stay and minimizing side effects before and after surgery. No identifiable data used for this analysis.
• In breast cancer surgery work, there was a significant reduction in length of stay for breast cancer surgery. This was not caused by the production of data, but the progress reports produced facilitated the intervention of the NHS Improvement team to ensure that the targets were met. No identifiable data used for this analysis.
• Liverpool CCG microsite- monthly monitoring of a variety of reports on a monthly schedule completing each month within 6 weeks of receipt of the data from MMES. No identifiable data used for this analysis.
• Detailed analysis of Adrenalectomies for the DH Expert working group of the British Association of Endocrine Surgeons to inform the development of national guidance on the organisation of adrenal surgery. Produced in September 2014, for publication in a peer-reviewed journal in 2015. No identifiable data used for this analysis
• Emergency Admissions Catchment Map (based on all Emergency Episodes) for CQC produced in September 2014. No identifiable data used for this analysis
• In-patient Mental Health catchment area/population/proportional activity analysis was due February 2015, but delayed as a result of our extended application process for data. No identifiable data used for this analysis
• Analysis of hospital care received by people dying as a result of suicide during the last months of life had been requested in late 2014, NATCANSAT has been unable to deliver this work due to the extended application process for data. It is expected that this work will still be of value once the approval process is complete. No identifiable data used for this analysis.
• Cancer Commissioning Toolkit which is used by commissioners to identify and address variation in cancer service provision No identifiable data used for this analysis
• These data have been used previously to respond rapidly to the needs of NHS Improvement (now NHSIQ) to measure progress of its activities in shortening length of stay for breast cancer surgery, and implementation of Enhanced Recovery after orthopaedic and colorectal procedures. The breast cancer surgery work was the subject of an HSCIC case study on the use of HES data http://www.hscic.gov.uk/casestudy/breastcancersurgery No identifiable data used for this analysis

Some examples of specific outputs relating to the Cancer and Cardiac work are available on the following links -
CANCER: http://www.natcansat.nhs.uk/data/hescancer.aspx
CARDIAC: http://www.natcansat.nhs.uk/data/hescardiac.aspx

Processing:

Extracts are processed to mark relevant records using a range of groupings which allow a rapid response to specific queries (eg: identifying episodes which involve particular diagnoses and procedure codes in isolation, or as a group, identifying episodes for patients who have relevant features in earlier or later episodes, linking episodes together to identify groups of procedures carried out over a period of time). The processed tables are then readily available to respond to queries as they arrive from government and the service.

The majority of the analysis completed is done using non-identifiable/non-sensitive data alone. Only the more complex and sophisticated analysis including data linkage to sources without HES ID require identifiable data, and only analysis specifically around the patient’s GP and Consultant require sensitive data. However, for completeness, the whole processing activity undertaken using the data is described below. Activities including the sensitive or identifiable data are clearly identified.
1. Non-identifiable data is received from the HSCIC and imported in to a SQL database.
2. A number of fields are added to the data, which are populated with data derived from other items in the record, or other records in the data for the same patient (all from the non-identifiable extracts).
Eg: Activity records are flagged if they contain a cancer diagnosis
Activity records are flagged if there is another record in the same extract which contains a cancer diagnosis
‘current provider’ are populated with the current provider code for the record – this changes if the provider has merged or changed identity since the activity took place.
3. Identifiable/Sensitive data is received from the HSCIC and imported in to a SQL database. This table is only accessed by one analyst responsible for creating extracts (extract analyst)
4. The identifiers are used by the extract analyst to link to other data sources (cancer registrations, radiotherapy) and are used to augment the annual extract data tables generated in steps 1&2.
Eg: Activity records are flagged if the patient has received radiotherapy
Activity records are populated with the tumour site and histology, and date of diagnosis from the cancer registrations database
5. The SQL tables are processed to generate OLAP cubes which facilitate rapid analysis. An OLAP cube is a multidimensional data array, which ‘slices and dices’ a large dataset, allowing subsections to be rapidly summated.
6. An ‘output analyst’ (who does not have access to the identifiable data), will then use the table or cubes to carry out analysis and generate outputs.
7. When analysis is requested which is not supported by the existing tables and cubes, it may be possible to add new fields to the table/cubes which will support the analysis, or it may be necessary for the ‘extract analyst’ to return to the raw non-identifiable or identifiable/sensitive data in order to create a new data source for the analysis. An ‘output analyst’ will then use the new data source to generate the outputs needed. Cubes/Tables developed for a specific task will contain the minimum possible information needed. This may include sensitive data, and/or record level data.
8. HES data is also used to augment other datasets (eg: to add detailed surgical data to the cancer registration database). In these cases the ‘extract’ analyst uses the identifiable data to carry out linkage, and then generates a pseudonymised version of the extract table in line with the HES analysis guide, to be used by the ‘output analyst’.
9. NHS Number is used for linkage to other data sources (Cancer Registrations taken from PHE and/or ONS, Radiotherapy Dataset, Cancer Audit Databases, in order to augment the HES data using data items from these sources, or to augment the other data sources with data items from HES.(carried out in step 4,7 or 8)
10. Postcode is used for geographical analysis, where it is used to:
a. correctly ascribe the patient’s residence to a range of geographical areas (eg: CCG/LAT, or to a catchment area calculated by NATCANSAT using travel times, patients flows or projections),
b. plot the patient on a map using a grid reference
c. identify socioeconomic measures for the patient’s residence
d. carry out travel time analysis from the patients residence to service locations or proposed service locations

Example: Objective 1 - Policy Development – DH Cardiovascular Strategy
DH in development of a cardiovascular strategy needed information on the patient pathway for patients suffering cardiac events, undergoing cardiac revascularisation procedures, with or without subsequent cardiac surgery. This analysis required the extract analyst to build a specific data table made up of patient pathway data extracted from a series of hospital admissions and outpatient attendances. The ‘extract analyst’ requested up-to-date death data using the NHS number, Date of birth and Postcode for relevant patients from the Demographics Batch Tracing service, and linked this (without the identifiers) to the data table using HESID. This data table was then passed to an ‘output analyst’ who was able to generate the outputs needed.

Example: Objective 2 - Performance Management – 23-hour breast model
As part of the ‘Transforming Inpatient Care’ initiative aimed at reducing patient bed days in hospital, a new model of care was developed for patients with breast cancer undergoing mastectomy. Outputs were needed in the form of tables which indicated the length of stay, and the readmission rate for patients admitted to hospital for a mastectomy. The ‘extract analyst’ was able to add new fields to the data table created in step 2 above, which flagged the relevant records, and identified those with readmissions to hospital. The output analyst was then able to use the table to generate the outputs needed. The process was repeated each month upon receipt of the MMES data in order to provide timely progress reports.


Example: Objective 3 - Benchmarking – Transforming In-patient Care
The National Cancer Director wanted to monitor the number of hospital bed days being used for patients with cancer. Using the tables generated in step 2 above, an extract analyst was able to generate monthly updates on the number of bed days used broken down by a number of key parameters.(eg: provider unit, cancer diagnosis, speciality)


Example: Objective 4 - Service Reconfiguration – Cardiac Revascularisation Service
New policy had indicated that people suffering a myocardial infarction should be able to receive revascularisation treatment promptly in order to improve outcomes. In order to implement the policy, it was needed to identify locations where the service should be offered so that all members of the population would be within easy reach of a facility. NATCANSAT undertook a population based geographical analysis to identify the key locations for the service to ensure that this was possible. New fields were added to the table by the extract analyst to identify patients who had received this treatment, and also those who might have benefitted from it had it been available to them. The output analyst used these data to estimate the demand at each of the locations, which could be used to calculate the resources needed.

More complex processing activities are undertaken on a one-off basis, in order to support the development of policy or measure progress in specific areas.

Generally, a specific extract is generated to be used by the NATCANSAT analyst for all but the most straightforward analysis, in order to minimize sharing of irrelevant data within the team, and to facilitate efficient working.

Data Minimisation
As part of this application, the data required has been rationalised and HES data currently held by NATCANSAT no longer covered by this agreement will be securely destroyed.

Data supplied in 2012 from the PROMS database has been destroyed.
Data supplied in 2012 from the SUS/PbR database has been destroyed.

National Data is requested as projects include all of England.
Years from 1997 onwards are requested to facilitate benchmarking over the maximum period possible. (earlier years do not include HESID, and use ICD9 diagnosis codes so analysis is complex) Long period trend analysis is important when identifying variations in rare conditions or procedures.
Minimal identifiers, sensitive fields and non-identifiable fields are requested to carry out the analysis set out in this application.