NHS Digital Data Release Register - reformatted

NHS England (quarry House) projects

1313 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).

🚩 NHS England (quarry House) was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS England (quarry House) 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.

National Heart Failure Audit 2016-17 Report — DARS-NIC-42272-S9J3L

Type of data: Aggregated

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

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(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii), Internal flow of aggregate tables only

Purposes: No, This data sharing agreement is not an intended legal document, it is a reference document to evidence data flows. The agreement will not be signed as a legal document. It will instead be signed by internal NHS England colleagues. NHS England has commissioned NHS Arden and Greater East Midland Commissioning Support Unit (Arden and GEM) to host the National Institute for Cardiovascular Outcomes Research (NICOR) to continue to manage the six national cardiovascular audits: • Myocardial Ischaemia National Audit Project (MINAP – concerning heart attacks or other acute coronary syndromes) • National Heart Failure Audit (NHFA) • National Audit for Percutaneous Coronary Interventions (NAPCI – relating to a non-surgical method used to open narrowed arteries that supply the heart muscle with blood) • National Congenital Heart Disease Audit (NCHDA – relating to procedures performed for a cardiac defect present from birth) • National Adult Cardiac Surgery Audit (NACSA) • National Audit of Cardiac Rhythm Management (NACRM) NICOR's national audit programme comprises of two types of audits: two specialist domains that are concerned with the disease processes (MINAP and NHFA) and four that cover delivery of specific services (procedures for patients with congenital heart disease, percutaneous coronary intervention, cardiac surgery and the management of cardiac rhythm abnormalities). The aim of these NICOR audits is to measure and report delivery of care against defined guidance standards and to enable the improvement of the quality of care and outcomes of patients with a range of cardiac conditions. Individuals who are already included in NICOR’s six national cardiovascular audit databases have their hospital and mortality outcomes reported under DARS-NIC-359940-W1R7B. As of 24 June 2022, NHS England is the data controller, commissioner and funder for all NICOR's audits and registries. The audits are based on prospectively collected data on patients in all NHS and independent healthcare providers in England and Wales. NICOR is the delivery arm of Arden and GEM (formal processor) for managing the audits and data processing. This Data Sharing Agreement concerns the NHFA which is a national clinical audit which monitors the care and treatment of hospitalised heart failure patients in England and Wales. The audit collects data on patients with an unscheduled admission to hospital in England and Wales, who are discharged with a primary diagnosis of heart failure. It was established in 2007 and has collected over 580,000 records of heart failure-coded hospital episodes. The audit aims to capture data on clinical indicators which have a proven link to improved outcomes for heart failure patients, and to encourage the increased use of clinically recommended diagnostic tools, disease modifying treatments and referral pathways. The audit publishes case ascertainment and clinical practice analysis at Trust and hospital level, and feeds back on this to NHS England and the Care Quality Commission (CQC). The hospital level HES Admitted Patient Care (APC) tabulation data requested under this Data Sharing Agreement is the minimum level of data required for case ascertainment purposes. NICOR (Arden and GEM) only receive data concerning the number of patients who received care by individual hospitals and trusts. This data allows NICOR to complete a comparison of HES-recorded heart failure admissions with National Heart Failure Audit-recorded heart failure admissions. There is no alternative, or less intrusive way of achieving the purpose stated within this Agreement. The HES APC data supplied by NHS England will be used to produce ‘participation’ tables for audit purposes, to determine whether hospitals are fully participating in the audit. This will confirm the validity of the numbers that are reported by the hospitals to other NHS databases e.g., HES data and Best Practice Tariff. The CQC also use data from NHFA for monitoring the performance of hospitals, this case ascertainment process provides them with the required quality assurance. Aggregate HES data at Trust (and component hospital) level will be compared to the number of records submitted to the audit by each Trust and Health Board, to measure case ascertainment for participating centres. This is a key quality indicator. NICOR requires small numbers unsuppressed for their NHFA Annual Report. If numbers were suppressed, comparison to HES figures with the number of records that hospitals have submitted would result in NICOR numbers being inaccurate. i.e. If 300 cells are suppressed with each cell representing up to 7, that is up to 2100 admissions excluded from the total, which is a significant amount. To address the GDPR principle of Data Minimisation, NICOR request that the data received is restricted to patients who have been discharged from hospital (with hospital code) with a diagnosis of heart failure. NICOR only use the latest annual HES data year to analyse case ascertainment. Once the analysis is complete, NICOR destroy the previous year’s data request. NICOR is hosted by Arden and GEM which as the sole data processor only processes the data for the purposes described in this Agreement. NHS England relies on the Article 6(1)(e) legal basis for processing personal data under UK GDPR - "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 is justified through commissioning arrangements which link back to NHS England and other national bodies with statutory responsibilities to improve quality of health care services. NHS England rely on Article 9(2)(h) of the UK GDPR as the legal basis for processing special category data. "Processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services on the basis of Union or Member State law or pursuant to contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3". This is justified as NHS England are responsible for provision of health and social care, and management of systems and compliance. (Academic, internal NHS transfer)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-01-31 — 2020-01-30 2016.09 — 2023.11.

Access method: One-Off

Data-controller type: HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), NHS ENGLAND (QUARRY HOUSE), NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

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

Objectives:

The National Heart Failure Audit is a national clinical audit which monitors the care and treatment of hospitalised heart failure patients in England and Wales and collects data on patients with an unscheduled admission to hospital in England and Wales who are discharged with a primary diagnosis of heart failure. It was established in 2007 and has now collected over 200,000 records of heart failure-coded hospital episodes.

The audit aims to capture data on clinical indicators which have a proven link to improved outcomes for heart failure patients, and to encourage the increased use of clinically recommended diagnostic tools, disease modifying treatments and referral pathways. The audit publishes case ascertainment and clinical practice analysis at Trust and hospital level, and feeds back on this to NHS England and the Care Quality Commission.

The data supplied by NHS Digital (formerly known as Health and Social Care Information Centre) will be used to produce ‘participation’ tables for audit purposes, to determine whether hospitals are fully participating in the audit. Aggregate HES data at Trust level will be compared to the number of records submitted to the audit by each Trust and Health Board, to measure case ascertainment.

For the purpose of the heart failure national report NICOR cannot allow for any small numbers to be suppressed, because otherwise when comparing HES figures with the number of records that hospitals have submitted to the audit, NICOR’S numbers will be inaccurate. If 300 cells are suppressed, that is up to 1500 admissions excluded from the total, which is quite a significant amount.

The data is required for a national clinical audit so the data needs to be as accurate as possible. Over 200 hospitals in England and Wales are assessed against the data NICOR publish in reports in Quality Accounts and by the CQC.

Yielded Benefits:

The Heart Failure audit is used by NHS England to support the Best Practice Tariff (BPT), a model that was created to incentivise care that is high quality and cost effective with the aim to reduce unexplained variation in the quality of care. The heart failure BPT was introduced in April 2015, to be an incentive to delivering specialist input in to the care of heart failure patients admitted to secondary care as an emergency as outlined in the NICE clinical guidelines 108 ‘Chronic heart failure: Management of chronic heart failure in adults in primary and secondary care’ and the clinical guideline 187 ‘Acute heart failure: diagnosing and managing acute heart failure in adults’ and the chronic heart failure quality standard (QS9). This feeds into the findings of the Heart Failure audit report year highlighting that outcomes are better for patients that access specialist care, overall improving mortality. For Chief Executives, Medical and Clinical Directors The Heart Failure audit is now comprehensive. Trusts and Health Boards should be aware that there is considerable variation in the quality of care delivered by different hospitals, and in different wards within a hospital. For Multidisciplinary Heart Failure Teams and Heart Failure leads and networks Recommendations on how to encourage and support quality improvement work targeted at improving limitations in care of people with acute heart failure. For Commissioners Ensure that the commissioners understand their local Heart Failure team and that it is properly constituted and fully commissioned along with use of the audit report to understand how the Heart Failure team commissioned by them compares with other Trusts and understanding service gaps and limitations in local Heart Failure care and work with the Trust to address gaps in service.

Expected Benefits:

The audit aims to drive up the quality of the diagnosis, treatment and management of heart failure by collecting, analysing and disseminating data, measuring improvements in participation in the National Heart Failure Audit; eventually to improve mortality and morbidity outcomes for heart failure patients.

Audit data is used in a number of ways to drive improvement in heart failure services and patient outcomes. Primarily, data is fed back to individual hospitals to report on their clinical practice and outcomes over time.

The audit provides participation rates, and hospital level data to organisations such as the Care Quality Commission’s Quality and Risk Profiles, the NHS Choices website and data.gov.uk. In addition to this, the audit produces an annual report, which is publically available: an archive of National Heart Failure Audit Reports can be found on the Annual reports webpage.

There are future plans to provide anonymised National Heart Failure Audit data, by hospital, to Cardiac Networks and Clinical Commissioning Groups.

Audit data is also used for research purposes, to investigate further the causes, treatment and management of heart failure. More information about the research use of National Heart Failure Audit and NICOR data can be found on the Research section the NICOR website: - http://www.ucl.ac.uk/nicor/audits/heartfailure/research

Outputs:

Past Outputs
NICOR UCL published the National Heart Failure Audit Report 2013/14 on the 20 October 2015.

The seventh annual report for the National Heart Failure Audit presents findings and recommendations based on patients with an unscheduled admission to hospital, who were discharged or died with a primary diagnosis of heart failure between 1 April 2013 and 31 March 2014. The report covers all NHS Trusts in England and Health Boards in Wales that admit patients with acute heart failure.

The report is aimed at all those involved in collecting data for the National Heart Failure Audit, including those involved in collecting data for the National Heart Failure Audit, as well as clinicians, hospital chief executives, managers, clinical governance leads commissioners, patient groups and many others. The report includes clinical findings at national and local levels and patient outcomes. Participation tables are produced and published every year in the report.

Future outputs
NICOR will use aggregate HES data with small numbers suppressed at Trust level to produce ‘participation tables’ in the National Heart Failure Audit Annual Report each year with publication to be confirmed. Participation tables are produced and published every year in the report.

The publication will be distributed in hard copy to all Trust Chief Executives, and clinicians in the heart failure community, and also made publically available on the NICOR website. It will also be published by HQIP on its PARCAR (participation and case ascertainment) webpages.

Processing:

Comparison of HES-recorded heart failure admissions with National Heart Failure Audit-recorded heart failure admissions to determine case ascertainment rate.

HSCIC supply tabulated HES APC data for the year only specified in this agreement for ICD 10 codes for heart disease. Data is broken down at provider level.

NICOR (UCL) will publish aggregated data with small number suppression within the National Heart Failure Audit Annual Report for the current financial year in hard copy to all Trust Chief Executives and clinicians in the heart failure community; also made publically available on NICOR website

HQIP will publish aggregated data with small number suppression in-line with the HES analysis guide within the National Heart Failure Audit Annual Report for the current financial year; made publically available on PARCAR (participation and case ascertainment) webpages. For clarity, no record level data will be shared with any third party; all individuals with access to the record level data are employed by the data processor. No data will be transferred outside the EEA.

Barts Health NICOR NCAP (Previously known as CCAD - Central Cardiac Audit Database - MR1233) — DARS-NIC-359940-W1R7B

Type of data: Identifiable

Opt outs honoured: Yes - patient objections upheld, Identifiable, Anonymised - ICO Code Compliant, Yes, No (Section 251, Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012), Health and Social Care Act 2012, Health and Social Care Act 2012 – s261(7), National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No, This data sharing agreement is not an intended legal document, it is a reference document to evidence data flows. The agreement will not be signed as a legal document. It will instead be signed by internal NHS England colleagues. The six national cardiovascular audits (named below) and the UK Transcatheter Aortic Valve Implantation (TAVI) registry are managed by the National Institute for Cardiovascular Outcomes Research (NICOR) which is hosted at NHS Arden and Greater East Midland Commissioning Support Unit (Arden and GEM CSU). The data processing work carried out by NICOR transferred to Arden and GEM from Barts Health NHS Trust on 23 June 2022. The NICOR audits and TAVI registry are based on prospectively collected, patient-level data on patients in all NHS providers in England and Wales. These audits, collectively termed the National Cardiac Audit Programme (NCAP) audits, are commissioned by NHS England (NHSE). Arden and GEM will hold the funding and data* for all NICOR Audits and Registries including NCAP (*the data is technically held on NICOR servers housed at a Redcentric data centre under the control of NICOR staff). The audits included in NCAP are: • Myocardial Ischaemia National Audit Project (MINAP- heart attack) - Includes all adult patients with acute coronary syndromes (any condition resulting from the sudden reduction of blood flow to the heart, which leads to shortness of breath and sudden chest pain), collecting information on the management of patients admitted with a diagnosis of myocardial infarction (heart attack) and other acute coronary syndromes. • National Heart Failure Audit (NHFA): Includes all patients with an unscheduled admission to hospital with heart failure, collecting data on patients discharged from acute hospitals with a primary diagnosis of heart failure • National Congenital Heart Disease Audit (NCHDA): Includes cardiac (relating to the heart) or intrathoracic (within the chest) great vessel procedures carried out in patients under the age of 16 years, and all adult congenital cardiac procedures performed for a cardiac defect present from birth • National Adult Cardiac Surgery Audit (NACSA): Includes all adult patients undergoing major heart surgery • National Audit for Cardiac Rhythm Management (NACRM): Includes all adult patients with implanted devices or receiving interventional procedures for the management of cardiac rhythm disorders. • National Audit for Percutaneous Coronary Interventions (NAPCI): Includes all adult patients on whom a percutaneous cardiovascular intervention (PCI) procedure (a non-surgical method used to open narrowed arteries that supply the heart muscle with blood) is performed. • The UK TAVI registry: Includes all patients who have undergone a procedure to implant a TAVI device (a percutaneous method to implant a new aortic valve). The aim of these audits/ registries is to measure and report delivery of care against defined guidance standards and to enable the improvement of the quality of care and outcomes of patients with a range of cardiac conditions. The care pathways for these patients are complex and thus the data collected within the audits, combined with Hospital Episode Statistics (HES) and/or Civil Registration mortality data, provide high quality comparative information of the clinical practice/processes and patient outcomes in these clinical areas. For example, it enables the comparison of disease and treatment options and outcome by Trust, hospital, unit and in some audits by consultant (NACSA and NAPCI). Where the data indicates performance is an ‘outlier’ of expected outcomes, NICOR (at Arden & GEM) work to NHSE-defined processes and standards, and with NHS organisations to explore this further and recommend quality improvement work, if required. All results are made available on public facing websites and on the websites of the audit associated Professional Societies. The NICOR website highlights the latest reports but allows access to previously published reports. National Data Opt-Outs (NDOs) have been historically applied to the data disseminated under this agreement following support from the Confidentiality Advisory Group (CAG). The National Data Opt-Out (NDO) enables patients to opt-out from the use of their confidential patient information for research and planning purposes where the data flows rely upon Regulation 5 of the Health Service COPI (Control of Patient Information) Regulations 2002. It is a standard condition of support under Regulation 5 of the COPI Regulations 2002 that patient wishes are respected. In line with the National Data Opt-Out Operational Policy the Confidentiality Advisory Group (CAG) may exceptionally advise the decision-maker that the NDO should not apply to a specific data flow supported under Regulation 5 of the COPI Regulations 2002. In the case of the NCAP and TAVI registry, this has been supported. The justification to not apply the NDOs are as below: The NCAP and TAVI registry have direct implications for changes in clinical care pathways at local, regional and national level. The audits and registry aim for 100% inclusivity and case ascertainment figures are either very high or increasing annually. The audits/ registry collect data on all-comer patients with varying risk profiles; collection of the highest risk groups is essential for these programmes. The opt-out figures have increased significantly but with high variance between regions; this non-random variation is extremely problematic for monitoring of public health and healthcare delivery. Civil Registration data Death data (death status and date of death) will be linked to the NCAP and TAVI registry data to provide short-term and long-term survival outcomes. Demographic data will be used to facilitate this. HES Admitted Patient Care (APC) Data NICOR's annual report will include the details of comorbidities and complications which are collected in the audit/ registry data. However, in some cases HES APC data is needed to supplement the audit/ registry data. Linkage to the full HES dataset would allow further exploration of the geographic, socio-economic and organisational data of patients more detail. This could lead to a better understanding of commissioning patterns within the UK. In addition, the HES dataset collects information on augmented care and the patient care pathway, and covers readmissions which are an important requirement for outcomes analysis. The level of data will be identifiable in order to validate the success of the data linkage. The data will be minimised as follows: - Limited to data for a cohort supplied by NICOR, including any individual meeting the inclusion criteria for one or more of the aforementioned clinical audits/ the TAVI registry. In late 2022, there were ~40,000 individuals on the TAVI registry. - Limited to data between 2000 and the latest available year of data, in order to be able to conduct longitudinal analyses for the audits/ registry and the VICORI programme. The primary reason for which NICOR uses Civil Registration data/HES APC linked data is to work out the treatment outcomes for the patients treated by the hospitals and clinicians. A key part of the reason for conducting the National Cardiovascular Audit Programme (NCAP) is to be able to benchmark each hospital against other hospitals in terms of the number of patients that died following treatment/care provided by the hospitals. Up until and including current practice, the key criteria for bench-marking hospitals and individual clinicians for the Clinical Outcomes Publication (COP) reports is the mortality rate (or reverse of this - survival rate). This can only be worked out by using Civil Registration linked data. Although the NACSA domain of NCAP uses hospital reported mortality data for bench-marking purposes, not all domains of NCAP have accurate hospital reported mortality data, e.g. the national congenital heart disease domain requires the Civil Registration data for the risk adjustment model. The outcomes data (NICOR audit linked data to civil registrations) is also being used by the NHS to support Best Practice Tariff - particularly for the National Heart Failure Audit and Myocardial Ischaemia National Audit Project (MINAP) – a quality improvement initiative to reward hospitals that provide a high standard of care. Only the minimum amount of data fields required for audit purposes is requested. HES Tabulation Data Hospital level HES Tabulation data (small numbers unsuppressed) is required for case ascertainment purposes. The Data Sharing Agreements DARS-NIC-318886-M1B9L, DARS-NIC-42272-S9J3L and DARS-NIC-64572-X0Q4D cover these purposes. The tabulated data is released under these Agreements. VICORI NCAP data linked with tracked mortality data and patient level HES APC data is required for the Virtual Cardio-Oncology Research Institute (VICORI) programme run by The University of Leicester, NHS England and NICOR. This body of work is divided into several different work packages. These are detailed further in Data Sharing Agreement DARS-NIC-143888-H0W2N. DATA CONTROLLERSHIP NHS England (NHSE) is the controller for this Agreement, representing the English NCAP audit and TAVI registry data. Digital Health and Care Wales (DHCW) are the controller for Welsh data in the NCAP audits and TAVI registry, including from the Civil Registration (Deaths) and Demographics data released under this Agreement. The permissions for the flow of the Welsh mortality data are represented under DARS-NIC-717493-V2R4K. As data controller and commissioner, NHSE is responsible for determining which projects/topics are included, for project specification development, procurement and extension activities, contract management, authorising data sharing requests, and the publication of project outputs. The NCAP project specifications developed by NHSE set out the purpose of the project, the patient groups and clinical services to evaluate and the types of data to collect. NHSE are part of the NICOR data access request approvals process which authorises data sharing applications from third parties. The data shared with any third parties is only NICOR data. NHS England’s data is not onward shared with anyone unless they have a specific current NHS England approved Data Sharing Agreement in place. LEGAL BASIS JUSTIFICATION: NHS England relies on the Article 6(1)(e) legal basis under UK GDPR - "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 is justified through commissioning arrangements which link back to NHS England and other national bodies with statutory responsibilities to improve quality of health care services. NHS England rely on Article 9(2)(i) of the UK GDPR as the legal basis for processing. “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”. This is justified as the NHSE commissioned audits and registries aim to drive improvements in the quality and safety of care and to improve outcomes for all patients. (Academic, internal NHS transfer)

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

When:DSA runs 2019-04-01 — 2020-07-31 2017.06 — 2023.11.

Access method: One-Off, Ongoing

Data-controller type: HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), NHS ENGLAND (QUARRY HOUSE), NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Office for National Statistics Mortality Data
  3. Bridge file: Hospital Episode Statistics to Mortality Data from the Office of National Statistics
  4. Civil Registration - Deaths
  5. MRIS - Members and Postings Report
  6. Demographics
  7. MRIS - Cause of Death Report
  8. MRIS - Scottish NHS / Registration
  9. MRIS - Flagging Current Status Report
  10. Civil Registration (Deaths) - Secondary Care Cut
  11. HES:Civil Registration (Deaths) bridge
  12. MRIS - Cohort Event Notification Report
  13. HES-ID to MPS-ID HES Admitted Patient Care
  14. Civil Registrations of Death - Secondary Care Cut
  15. Hospital Episode Statistics Admitted Patient Care (HES APC)
  16. Civil Registrations of Death

Objectives:

The processing is to enable NICOR to undertake its HQIP contracted audit work - reports and aggregate table reports at the unit or consultant level. Specifically to enable the delivery, by NICOR staff, of the National Cardiovascular Audit Programme the 6 audits

• Myocardial Ischaemia National Audit (MINAP)
• Adult Cardiac Surgery Audit
• National Heart Failure Audit
• Congenital Heart Disease Audit,
• Cardiac Rhythm Management Audit
• Adult Cardiac Interventions Audit
as contracted between NICOR and HQIP.

The data may also be used to enable the delivery of additional audit analysis, with the approval of HQIP and as requested by those being audited (NHS Units and associated Consultants).

Yielded Benefits:

The audit data is being used by the NHS to support Best Practice Tarrif - particularly for Heart Failure and MINAP - a quality improvement initiative to reward hospitals that provide a high standard of care. This year, NICOR have harmonised the six national clinical cardiovascular audits into a national cardiac audit programme with 6 separate domains. This means that NICOR are standardising the approach in terms of (methodology, data collection, data completeness and data quality) conducting the audits. This will be reported back to all key stakeholders, commissioners, trusts, patients and public and clinicians data in a relevant and meaningful way which will lead to improvements in the quality of care provided. NICOR are using the audit data for developing risk adjustment models for Heart Failure and MINAP - to ensure that the reports are reliable and are being interpreted accurately and meaningfully.

Expected Benefits:

There are a number of expected benefits for example;
1. The ability to look at cardiovascular admissions which may be related to, and impacted on by, the medical management of a patient’s heart failure. This will provide a much more detailed and complex picture of readmissions, and help us to determine the full impact that good and poor management of specific cardiac conditions has on readmission rates and mortality outcomes.
2. The ability to utilise readmission for reasons other than, but connected to, major cardiac surgery as an outcome measure would be extremely beneficial in terms of assessing the long term effects on patients undergoing the various cardiac surgical procedures, and what effect different variables have on these outcomes.
3. Provide additional insight into outcomes (especially adverse reactions such as stroke) which we can then include these in our annual reports used to inform quality improvement work. Linkage to the full HES dataset would allow further exploration of the geographic, socio-economic and organisational data of patients more detail. This could lead to a better understanding of commissioning patterns within the UK. In addition, the HES dataset collects information on augmented care and the patient care pathway.
4. The ability to investigate cumulative missed opportunities for patient care and major cardiovascular and cerebrovascular events.
5. The ability to determine case ascertainment rates and underreporting of procedures and patient admissions.
These types of outputs will be included in the various publications NICOR produces including annual and other public reports (in various formats) for the key stakeholders such as clinicians, trusts, commissioners and patients. The information in the reports will be useful for Quality Improvement purposes.

Outputs:

The outputs will be audit reports (in various formats) which will be published throughout 2016/17.

Processing:

Processing by NHS Digital of the cardiovascular audit data is required with both HES and ONS Mortality data, as done previously. Both HES and ONS data will be linked systematically by NHS Digital to the patient records submitted by hospitals/units, for each of the 6 audits using a number of variables (NHS Number, ID Number, Surname, Forename, Date of Birth, Gender, Postcode). NICOR will provide these patient identifiers to NHS Digital for linkage purposes.
NHS Digital return to NICOR the linked HES and ONS data (fields detailed elsewhere).
Before the linked data is used NICOR remove all patient identifiable fields so that the final dataset will be pseudonymised before the audit work is undertaken. No variables which might identify individuals (PID) will ever be published, reported or shared with a third party. Such analysis will only contain aggregated small numbers suppressed data in line with the HES Analysis guide.

The Strategy Unit (part of NHS Midlands and Lancashire CSU): analytical support to NHS and partner organisations — DARS-NIC-05206-L1V6D

Type of data: Pseudonymised

Opt outs honoured: N, Y, No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

Legal basis: Health and Social Care Act 2012, Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012), 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', NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: Yes, NHS Midlands and Lancashire Commissioning Support Unit (MLCSU) are the sole data controller under this agreement. However MLCSU is not a legal entity as MLCSU forms part of NHS England (NHSE). NHSE are therefore listed as the data controller as the legal entity and MLCSU are listed as a data processor who manage the data. NHS Midlands and Lancashire CSU (MLCSU) is part of The NHS Transformation Unit which is a hosted service of Northern Care Alliance NHS Foundation Trust. Employees accessing the data under this Agreement are employed by Northern Care Alliance NHS Foundation Trust but have an honorary contract with MLCSU. Access to the data supplied under this Agreement is restricted to employees of MLCSU and The NHS Transformation Unit only and access by an employee of Northern Care Alliance NHS Foundation Trust would constitute a breach of the DSA. The purpose of this Agreement is to support contractual and strategic bench-marking across Midlands and Lancashire, for programmes such as planning, commissioning, assessing service quality, performance improvement, and activity and outcomes monitoring. For example, this includes: • provision of analytical intelligence to Integrated Care Boards (ICBs) e.g. for benchmarking of similar health economies or populations in England • in-depth analyses of specific services or pathways to better understand the reasons behind differences in outcomes between health economies • supporting large scale transformation projects involving multiple commissioning organisations • quantitative evaluations and monitoring to estimate the impact of service changes or improvement initiatives The CSU’s customer base consists of: ICBs, Trusts, Local Authorities for the purposes of public health and social care, CQC, Sustainability and Transformation Partnerships, Public Health England, Department of Health, Clinical senates, Strategic clinical networks, NHS England, NHS Improvement, and health charities. Only pseudonymised data is processed under this Agreement. MLCSU wish to retain latest available data previously disseminated data up to 2020/21 of the following data-sets: - Hospital Episode Statistics Critical Care (HES CC) - Hospital Episode Statistics Admitted Patient Care (HES APC) - Hospital Episode Statistics Outpatients (HES OP) - Hospital Episode Statistics Accident and Emergency (HES A&E) (1 year only) - Mental Health Service Dataset (MHSDS) - Secondary Uses Service Payment by Results A&E (SUS PbR A&E) - Secondary Uses Service Payment by Results Outpatients (SUS PbR OP) - Secondary Uses Service Payment by Results Spells (SUS PbR Spells) - Secondary Uses Service Payment by Results Episodes (SUS PbR Episodes) - Civil Registration (deaths) - Patient Reported Outcome Measures (PROMS) - Patient Reported Outcome Measures Linkable to HES - Diagnostic Imaging Dataset (DIDS) - Emergency Care Dataset (ECDS) (1 year only) The specific services and products that will utilise the data are: A. QIPP (Quality Innovation Productivity and Prevention) opportunity packs. These reports provide a summary of performance, cost, and activity levels for individual ICBs/trusts compared with other similar ICBs/trusts. Information in the reports is used to inform strategic planning. Inpatient, outpatient, and A&E hospital services are all included in the reports. The reports were originally produced for ICBs within the CSU's core geography, however, MLCSU has since been asked to produce reports for ICBs across England. The value of these packs in supporting healthcare organisations to assist with their statutory duty to commission/provide high quality and best value services for their populations is clearly proven. B. Development of decision support tools for patients and clinicians to help them make better decisions when deciding whether a patient should undergo a joint replacement procedure. The development of the tools requires advanced statistical analysis to establish the relationship between a range of patient characteristics and procedure outcomes (as measured by PROMs data). Once established, the statistical relationships will be used within the tools to allow a clinician to use individual patient characteristics to provide an estimate of the likely benefit of the procedure for the patient. This extra information can help the patient and clinician make the best informed decision about whether to proceed with the operation. A national panel dataset (i.e. cross-sectional time series data) will ensure that modelled relationship is as robust as possible and maximise the predictive power of the tool (vital given that the tool will be used to support decisions about patient care). A number of local ICBs with programmes aimed at improving orthopaedic services have expressed an interest in piloting the tool to help establish its efficacy. C. Projects on behalf of ICBs and Strategic Clinical Networks (part of NHS England) to model expected future mental health activity levels and capacity requirements. Integral to this work are discussions with clinicians and commissioning stakeholders about the expected impacts of planned changes or interventions (e.g. schemes to increase early diagnosis of mental health conditions). The CSU work with these stakeholder groups to ‘quantify’ their judgements about expected impacts and use these as inputs to statistical models. To inform this process the CSU produce a range of supporting analyses to help participants understand current activity, past trends in activity, and differences between commissioning geographies. The provision of this supporting data is essential for helping stakeholders to make considered and informed estimates, based on a clear understanding of past progress and performance. Without access to record level data, the CSU would not be able to accurately adjust activity in-line with participants' judgements. In particular, the statistical models of future mental health activity that are developed as a result of these discussions would suffer from an increased risk of overestimating the effects of planned changes (due to issues of double counting), which is unavoidable without access to record level data. To provide the supporting materials MLCSU requires national datasets spanning multiple years. The CSU's professional experience is that providing longer-term trends is extremely important when trying to understand the relative contributions of multiple factors to changes in different types of mental health activity. Attempting to rely on shorter time series would limit the value derived from these facilitated modelling exercises and materially increase the risk of making incorrect assumptions about likely future developments. D. Projects on behalf of ICBs to understand how the nature and scale of healthcare utilisation changes as a result of changes in demography. A specific aim of this work is to investigate how patient need, and service utilisation changes towards the end of a person’s life (ONS mortality data is required for this work). MLCSU is developing a new approach to estimating the likely impact of an ageing population on future healthcare demand. The new approach will take into account not only the future size and age structure of a population but also changes in the numbers of people projected to be in their final months of life. Without access to linked national data on hospital activity and mortality this work would not be possible. When constructing statistical models to estimate possible future states the availability of historical data, and in particular, long time series of data is hugely important. Without a good understanding of the statistical relationships between variables over time it is extremely difficult to construct models capable of delivering useful insights about what path the future might take. As part of this project MLCSU will seek to understand how patterns of healthcare utilisation at the end of life have changed over time, for example, in response to advances in medical technology and new treatments. E. Projects to understand longer-term trends. Describing changes in acute utilisation over the long term provides insights that are lost when focusing on the most recent past. Striking reductions, for example, in case mix-adjusted length of stay following an emergency hospital admission or the frequency of admissions to psychiatric inpatient units only really become apparent when viewed over a long time frame. These longer-term perspectives demonstrate the enormous positive changes that have been achieved in the past and can motivate and guide health economies seeking improvements in areas that seem equally intractable. To omit or remove this historical data would eliminate the potential for these insights. The CSU has deployed this kind of longitudinal analysis (going back to pre-2000) recently in support of several Sustainability and Transformation Partnerships as they seek to respond to national requirements. When attempting to understand or explain historical hospital utilisation rates, or forecasting future rates, the longer the time series, the more robust (on average) the explanation or forecast. While for time series models, it might be argued that there are diminishing returns from including ever older data points, this is not necessarily the case for causal models. The CSU are frequently asked to model the potential implications of new models of care. These ‘new’ models are more commonly reinventions or adaptations of earlier models. The ‘NHS Five Year Forward View’ describes a number of new care models which move away from a purchaser-provider split in favour of lead-provider arrangements. To many these proposed models mirror or approximate arrangements that existed in the NHS prior to the development of primary care trusts. If analysed and interpreted appropriately, data relating to these earlier periods can provide useful insights into the unintended consequences of ‘new’ care models, and the CSU are being asked to do this to support STPs and national Vanguards in meeting the national requirements placed upon them. Integrated Care Boards (ICBs) pay for the CSU out of their management allowance which is set by central government, a form of internal SLA within the NHS. Therefore funding for the processing of the data is provided by the NHS through the ICB. MLCSU and the Strategy Unit provide services on behalf of NHSE to other (client) organisations within the health and social care sector. These client organisations will be involved as funders and customers for projects undertaken by the Strategy Unit. The processing under this Agreement is necessary for MLCSU and the Strategy Unit to perform the tasks required of it by NHS England, namely provision of analytical intelligence and support to ICBs and other health and social care organisations. These tasks are objectively necessary for the effective functioning of a publicly-funded healthcare system and as such fall under Article 6(1)(e), performance of a task carried out in the public interest or in the exercise of official authority vested in the controller. The provision of accurate analytical intelligence is necessary for the effective management of the health and social care system and as such the processing under this Agreement falls under Article 9(2)(h) of the GDPR. The data controller have determined that the data requested is the minimum amount necessary and the least intrusive way to achieve the objective of this Agreement. The data is pseudonymised and is required for the effective operation and administration of a publicly-funded healthcare system. The data-sets supplied under this Agreement have an established history of use within the UK healthcare system. Microsoft Limited supply Cloud Services to Midlands and Lancashire Commissioning Support Unit are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data. Lima Networks Ltd supply IT infrastructure and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data. (Commissioning Support Unit (CSU), internal NHS transfer)

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

When:DSA runs 2019-09-01 — 2021-01-31 2017.09 — 2023.11.

Access method: One-Off, Ongoing

Data-controller type: NHS MIDLANDS AND LANCASHIRE COMMISSIONING SUPPORT UNIT, NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No, Yes

Datasets:

  1. Bespoke Extract : SUS PbR A&E
  2. Bespoke Extract : SUS PbR APC Episodes
  3. Bespoke Extract : SUS PbR APC Spells
  4. Bespoke Extract : SUS PbR OP
  5. Bridge file: Hospital Episode Statistics to Diagnostic Imaging Dataset
  6. Office for National Statistics Mortality Data
  7. Bridge file: Hospital Episode Statistics to Mortality Data from the Office of National Statistics
  8. Hospital Episode Statistics Outpatients
  9. Hospital Episode Statistics Accident and Emergency
  10. Hospital Episode Statistics Admitted Patient Care
  11. Diagnostic Imaging Dataset
  12. Hospital Episode Statistics Critical Care
  13. Patient Reported Outcome Measures
  14. HES:Civil Registration (Deaths) bridge
  15. Civil Registration - Deaths
  16. Mental Health Services Data Set
  17. Mental Health Minimum Data Set
  18. Patient Reported Outcome Measures (Linkable to HES)
  19. Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set
  20. Secondary Uses Service Payment By Results Episodes
  21. Secondary Uses Service Payment By Results Outpatients
  22. Secondary Uses Service Payment By Results Spells
  23. Secondary Uses Service Payment By Results Accident & Emergency
  24. Mental Health and Learning Disabilities Data Set
  25. Bespoke Monthly Extract : SUS PbR A&E
  26. Bespoke Monthly Extract : SUS PbR APC Episodes
  27. Bespoke Monthly Extract : SUS PbR OP
  28. Bespoke Monthly Extract : SUS PbR APC Spells
  29. Civil Registration (Deaths) - Secondary Care Cut
  30. Secondary Uses Service Payment By Results Accident & Emergency
  31. Emergency Care Data Set (ECDS)
  32. HES-ID to MPS-ID HES Accident and Emergency
  33. HES-ID to MPS-ID HES Admitted Patient Care
  34. HES-ID to MPS-ID HES Outpatients
  35. Civil Registrations of Death - Secondary Care Cut
  36. Diagnostic Imaging Data Set (DID)
  37. Hospital Episode Statistics Accident and Emergency (HES A and E)
  38. Hospital Episode Statistics Admitted Patient Care (HES APC)
  39. Hospital Episode Statistics Critical Care (HES Critical Care)
  40. Hospital Episode Statistics Outpatients (HES OP)
  41. Mental Health and Learning Disabilities Data Set (MHLDDS)
  42. Mental Health Minimum Data Set (MHMDS)
  43. Mental Health Services Data Set (MHSDS)
  44. Patient Reported Outcome Measures (PROMs)

Objectives:

To support contractual and strategic benchmarking across Midlands and Lancashire, for programmes such as planning commissioning and productivity, service quality and performance improvement, and activity and outcomes monitoring for local populations.
The CSU needs:
• The provision of analytically based intelligence for a range of Clinical Commissioning Groups (CCGs) for benchmarking of similar health economies or populations in England, not just in the CSU’s area.
• To provide in depth analysis of all aspects of a specific service areas and allow comparisons with other CCG areas or health economies known to have better outcomes or new/different pathways.
• To support large scale transformation projects that may impact several commissioners (CCGs)
• Descriptive analyses of healthcare needs, demands or supply including comparisons between providers, commissioners and geographical areas, analysis over time and of the characteristics of patients and the services they receive.
• Retrospective analyses exploring the reasons for observed changes in healthcare provision and health outcomes
• Prospective modelling of the impact of planned or proposed changes in healthcare services on healthcare activity, travel times and resource use
• Quantitative evaluations and monitoring estimating the impact of service redesign of improvement initiatives on healthcare and outcomes
• To develop tools and information packs to support patients, clinicians, commissioners and providers to make informed decisions about healthcare service provision, organisation and strategy

The specific services and products that will utilise the data are the following :-
A. QIPP (Quality Innovation Productivity and Prevention) opportunity packs which provide a summary of performance, cost and activity levels for individual CCGs/trusts compared to other local CCGs/trusts. The packs include aggregate analysis in relation to QIPP priorities covering Inpatient, Outpatient and A&E but are subject to change in line with the QIPP programme. These packs were originally produced for those CCGs within the CSU's core geography (Birmingham and the Black County). However the CSU have now been requested to provide packs for a wider range of CCGs and trusts including all Staffordshire, Lancashire, Herefordshire, Worcestershire, Shropshire and Telford and Wrekin. The CSU have also had requests from as far afield as Cornwall. The value of these packs (as demonstrated by the willingness to pay) in supporting CCGs/trusts to assist with their statutory duty to commission/provide high quality and best value services for their populations is clearly proven and as such the CSU will be offering the packs to all CCGs trusts in England. In addition to the wider provision of packs the CSU's existing customers have also requested that the packs be enhanced to offer comparisons against national nearest neighbour comparators or bespoke comparators (for example Birmingham combined CCGs compared with other large cities). Customers for the packs also can request ‘deep dive’ analyses to explore identified opportunities in greater detail

B. Development of decision support tools for clinicians to help them make better decisions when deciding whether a patient is suitable for Hip or knee replacement procedures. The development of the tools requires sophisticated statistical analysis to establish the relationship between a range of patient characteristics and procedure outcomes (as measured by PROMs data). The statistical relationships will be used within the tools whereby it will allow a clinician to input patient characteristics and provide an estimate of the likely benefit of the procedure for the patient. This additional information can help both the patient and their clinician make the best informed decision about whether to proceed with the operation. In order to ensure that that relationship is as robust as possible and to maximise the predictive power of the tool (which is vital given that the tool will be used to support important decisions about patient care) a full national dataset is required. In order to further validate the relationship and establish its robustness over time (which will be important for clinician and patient confidence in the tool) the CSU will be carrying out the analysis on all data years. The development of these tools will establish a prototype for the development of other similar products for other procedures where data is available through the PROMS dataset such as Varicose vein surgery etc. However for the purposes of this request the CSU are requesting only PROMS data relating to hip and knee procedures. A number of Local CCGs with programmes aimed at improving orthopaedic services (across all of Staffordshire for example) have confirmed that they plan to put this tool into practice on an initial pilot basis as soon as it is available. The CSU have also been approached by a number of other CCGs who have indicated that they would also be interested in applying the tool once its efficacy has been established.

C. Projects on behalf of CCGs and Strategic Clinical Networks (part of NHS England) to model expected future Mental Health activity levels and capacity requirements within a CCG after taking into account the impact of projected demographic changes and also the potential impact of mental health prevention strategies, admission avoidance strategies and length/intensity of treatment reduction strategies. An integral part of this work is to elicit modelling parameters from clinicians and commissioning stakeholders relating to expected impacts on activity levels as a result of planned changes or interventions. In order to do this the CSU produce a range of supporting analyses to help them to understand current activity levels, trends in activity and also how they compare with others. Provision of this supporting data is key to helping stakeholders to make considered and robust estimates based on a clear understanding of past progress and performance against other relevant comparators. In order to provide this comparative benchmarking the CSU require full national datasets covering multiple years. As the CSU are requesting the full set of historical data, they felt it important to clarify their rationale for doing so. In terms of the number of years of data requested, the CSU's professional experience has shown that providing longer term trends (in excess of 5 years) is often important, given the level of variation that exists, in order to evidence general trends. Being able to show local trends in the context of national trends is also essential for sophisticated interpretation. Shorter time series can often be misleading in this respect and as such could result in incorrect assumptions about future levels of demand.

D. Projects on behalf of CCGs to understand how the nature and scale of healthcare utilisation changes as a result of changes in demographics. One specific aim of this work (for which ONS mortality data is required) is to investigate how patient need, demand and service utilisation changes towards the end of a person’s life. In addition it will also allow the CSU to develop a new approach to estimating the likely impact of an ageing population on future healthcare demand. The new approach will take into account not only the future size and age structure of a population but also changes in the proportion of the population who are estimated to be in their final months of life. It is also worth noting that NHS England have expressed interest in the CSU's development of this method of forecasting future demand as part of their national Fit for the Future programme (FFF).

The project requires national level datasets in order that the analysis is as statistically robust as possible. It will also allow the CSU to establish the extent to which utilisation prior to death varies across the country. Benchmarking analysis (including historical trend analysis) will be carried out in order to provide estimates of the potential scale of opportunity for reducing acute healthcare activity (or developing alternatives to acute provision) for those patients at the end of life. Benchmarking and trend analysis will also enable the identification of those Trusts or CCGs who may be more advanced in end of life care provision. As part of this project the CSU will also be considering how patterns of utilisation at the end of life have changed over time (advances in medical technology and new treatments will certainly have had an impact on levels of service utilisation particularly for older people). Long term trends in excess of five years will be important in order to identify and have confidence in historical trends and applying these trends to future estimates.

E. Other specific projects are:

1 Describing changes in acute utilisation over the long term provides insights that are lost when focusing on the most recent past. Striking reductions, for example, in casemix-adjusted length of stay following an emergency acute hospital admission or the frequency of admissions to psychiatric inpatient units only really become apparent when viewed over a long time frame. These longer-term perspectives demonstrate the enormous positive changes that have been achieved in the past and can motivate and guide health economies seeking improvements in areas that seem equally intractable. To delete older data would eliminate the potential for these insights. The CSU have deployed this kind of longitudinal analysis (going back to pre-2000) recently in support of several Sustainability and Transformation Plans (STPs - compromising of CCGs, trusts, Foundation Trusts, Local Authorities and other key local partners) as they seek to address the requirements placed upon them nationally.

2 When explaining historical acute hospital utilisation rates, or forecasting future rates, the longer the time series, the more robust (on average) the explanation or forecast. Whilst for time series models, it might be argued the diminishing returns result from adding very old data points, this is not necessarily the case for causal models.

3 The CSU are frequently asked to model the potential implications of new models of care. These ‘new’ models are more commonly reinventions or adaptations of earlier models. The ‘NHS Five Year Forward View’ describes a number of new care models which move away from a purchaser-provider split in favour of lead-provider arrangements. To many these proposed models mirror or approximate arrangements that existed in the NHS prior to the development of primary care trusts. If analysed and interpreted appropriately, data relating to these earlier periods can provide useful insights into the unintended consequences of ‘new’ care models and the CSU are being asked to do this to support STPs and national Vanguards in meeting the national requirements placed upon them.

Data will only be used for the purposes outlined above, and any requirement to change the purpose will be subject to a separate request to NHS Digital.

Yielded Benefits:

MLCSU's work is dedicated to helping commissioners, providers, charities, and government to solve complex problems by providing evidence-informed analysis and advice. This is carried out as better evidence leads to improved decision making and implementation. A. QIPP opportunity packs—these reports have facilitated commissioners to target interventions for reducing acute hospital activity. B. PROMS—this work has helped commissioners to determine whether rates of orthopaedic surgery are the result of differences in clinical thresholds for surgery. C. Mental Health activity modelling—the modelling in this area has provided powerful evidence of the need to integrate mental and physical health care, this is borne out by NHS England commissioning the CSU to produce reports for all 44 STPs. D: Impact of demography—this work has been used by commissioners in strategic plans that set the foundations for planning and contracting future levels of healthcare activity and expenditure. MLCSU suggests that that the value of its work is perhaps best judged based on feedback from its customers. "The Strategy Unit are inspiring in their commitment, dedication to evidence and use of innovative analysis as a way to improve health and care." Professor Sir Bruce Keogh—National Medical Director, NHS England "I just wanted to drop you a note to say how impressed I have been with the work you and the team have recently undertaken on the 'Making the Case for Integrating Mental and Physical Health Care' report. The product you provided was extremely well researched and presented. The delivery to the MH Alliance board generated significant discussion across the system. On a personal level, the presentation and report gave me a more informed narrative and evidence to help me further drive the West Midlands Mental Health Commission priorities whilst ensuring we adopt a whole population level health promotion approach. I would urge other areas to commission this report as a baseline assessment to develop a better understanding of the potential integration opportunities across STP and local footprints". Superintendent Sean Russell—Mental Health Lead, West Midlands Combined Authority "The Black Country STP has been an early adopter of this important study by the Strategy Unit. We saw its potential to inspire a transformation of our response to the physical health needs of mental health service users so we commissioned an earlier version to inform the development of our plan. Some of the differentials in both health outcomes and health service utilisation are chastening but we have been able to use these findings (and the summary of the evidence base provided) to begin building a broad coalition of local partners to identify and implement practical changes. I commend it enthusiastically to colleagues as a catalyst for much needed change". Andy Williams—Accountable Officer, Sandwell and West Birmingham CCG.

Expected Benefits:

As described by the examples listed above, the CSU’s work provides customers (CCGs, Trusts, Local Authorities for the purposes of public health and social care, CQC, Sustainability and Transformation Partnerships, Public Health England, Department of Health, Clinical senates, Strategic clinical networks, NHS England, NHS Improvement, and health charities) with understanding and insight that enables them to make the best decisions about the healthcare services they commission or provide. Improved decision making will have a direct effect on the quality of care and outcomes for patients. The CSU's work is limited to the health and social care arena and outputs will be used only by health and social care organisations.

With respect to the outputs listed above, the CSU wishes to highlight the following benefits:

A. QIPP opportunity packs – these reports continue to help focus commissioner plans and direct resources to areas most likely to lead to improvements in quality, outcomes, and cost savings.

B. PROMS decision support tool – the CSU’s work on a decision support tool is aimed at helping patients and clinicians make improved joint decisions about whether to undergo joint replacement surgery. This would help to minimise both the financial cost of such procedures and avoid unnecessary pain and risk for some patients who are unlikely to experience benefits.

C. Mental Health activity modelling – in 2017, NHS England commissioned the CSU to produce a report titled "Making the Case for Integrating Mental and Physical Health Care" for all 44 STPs. The objectives of the report were to highlight the level of health inequalities experienced by users of specialist mental health services, to provide insight on the use of acute hospital services by mental health service users, identify groups that could benefit from targeted interventions, and provide a summary of effective interventions for improving the physical health of mental health service users. An integrated mental and physical health approach is one of the three priority actions described in the Five Year Forward View for Mental Health. In 2017-18, the CSU are committed to further work focussed on some of the issues uncovered by the report.

D. Impact of demography – understanding how demographic change will impact on population healthcare use is a central question for healthcare planners. It sets the scale of the financial challenge in health economy plans and underpins all large scale healthcare reconfigurations and long-term healthcare contracts. Overstating or understating the impact of demographic pressures may lead a health economy to set unduly radical or conservative plans for cost savings, by helping health economies to produce improved estimates of the likely impact this risk is mitigated.

Palliative and end of life care – improving palliative and end of life care is a Department of Health commitment
https://www.gov.uk/government/publications/choice-in-end-of-life-care-government-response The CSU’s reports in this area highlight variation and provide greater transparency around current practice.

The CSU are not the end user of the outputs they produce, however they regularly receive positive feedback from their customers and currently receive repeat business from around 75% of customers.

Note on CSU's customer base:
With the introduction of STPs, the CSU's customer base has rapidly become a collective local 'health and care economy', comprising a number of different organisation types within the NHS. For this reason, all parties involved in STPs are referred to as customers. Depending on how an individual STP chooses to operates, different members may be directed to take responsibly for particular programmes of work such that the CSU could be directly commissioned by any member organisation on behalf of the collective STP.

In 2016, Public Health England appointed the CSU to a 4-year framework agreement to supply data science and health impact assessment services.

In 2017, NHS England commissioned the CSU to produce a report titled "Making the Case for Integrating Mental and Physical Health Care" for all 44 Sustainability and Transformation Partnerships. The end users of these reports are all the organisations that make up local STPs.

Outputs:

Previous outputs:
A. QIPP opportunity packs – these reports provide in-depth information to support commissioning organisations in developing their strategic plans. The focus of these reports is comparative information on utilisation rates for subsets of acute hospital activity (inpatient, outpatient, and A&E) that are amenable to interventions targeted at reducing levels of acute hospital activity.

The reports are bespoke to individual commissioning organisations and are only provided to those organisations that place an order. The CSU have produced similar reports for several years. In a typical year the CSU might expect to produce about 30 such reports.

B. PROMS decision support tool – development work to test the concept of a tool that allows clinicians to use patient characteristics to obtain an estimate of likely benefit from receiving a joint replacement procedure.

C. Mental Health activity modelling – in 2017, the CSU undertook a substantial project looking at the physical health of people who use mental health services. The CSU produced a series of analyses that highlighted significantly poorer health outcomes for mental health patients. The CSU produced locally-focussed reports for a number of commissioning organisations, before NHS England commissioned the CSU to produce a report titled "Making the Case for Integrating Mental and Physical Health Care" for all 44 STPs.

D. Impact of demography – for several years the CSU have produced reports that provide in-depth analysis of the likely impact of demographic changes on future acute healthcare utilisation. The focus of these reports is the effect of changes in population size, age structure and health status on levels of acute healthcare activity across a range of delivery points. The reports are bespoke to individual commissioning organisations and are only provided to those organisations that place an order. In a typical year the CSU might expect to produce about 30 such reports.

In 2017, the CSU produced a report for NHS England describing the context and status of end of life care services across the West Midlands Region. Sustainability and Transformation Partnerships need to include proposals to improve choice in end of life care in their strategic plans. A second report focussed on palliative and end of life care for children and young people was later commissioned by NHS England to help understand characteristics and levels of resource required by children with life-limiting and or life-threatening conditions.

All our reports/outputs conform to relevant legislation and guidance with respect to confidentiality and other important considerations.


Planned outputs:
A. QIPP opportunity packs – as in previous years, the CSU has been tasked with producing reports that provide in-depth information to support commissioning organisations in developing their strategic plans. The CSU expect to produce about 30 such reports in 2017-18. In 2017-18, the CSU have been asked to further develop the reports to include a version suitable for Sustainability and Transformation Partnerships (STPs).

B. PROMS decision support tool – development work to test the concept of a tool that allows clinicians to use patient characteristics to obtain an estimate of likely benefit from receiving a joint replacement procedure. In particular, the CSU have been asked to consider the relationship between surgeon specialisation and patient outcomes. Most studies looking at the relationship between surgical activity and outcomes have focussed on procedure volume i.e. the volume-outcome relationship. But recently, the existence of a specialisation-outcome that is independent of the volume-outcome relationship has been advanced.

C. Mental Health activity modelling – the CSU expect to produce a number of follow-up analyses based on previous work looking at the physical health of people who use mental health services. The exact focus of this work is yet to be confirmed but may include in-depth reviews of specific patient groups e.g. CAMHS, substance misuse; pathway modelling; or exploring relationships with other datasets e.g. primary care, IAPT.

D. Impact of demography – as in previous years, the CSU has been tasked with producing reports that provide in-depth analysis of the likely impact of demographic changes on future acute healthcare utilisation. The CSU expect to produce about 30 such reports in 2017-18. In 2017-18, the CSU have been asked to further develop the reports to include a version suitable for Sustainability and Transformation Partnerships (STPs).

In 2017-18 the CSU has been tasked with further developing our methods for understanding the impact of demographic changes on future healthcare utilisation. The CSU intend to do this by drawing on the relationship between healthcare use and proximity to death. The proposed methods will require combining mortality data and hospital activity data.

Processing:

The data will be stored on a secure server and accessed through a SQL server database by a small group of named analytical staff working within the Strategy Unit of the CSU. Those staff are based at the premises detailed in this application (Kingston House). The data in its raw form will not be loaded into any tool or provided as part of any product or output. All outputs will contain only data which is aggregated, with small numbers suppressed in line with the HES Analysis Guide.

SUS PBR
As detailed in the “Objectives section” (Objective A) accessing the national SUS PBR data will enable the CSU to offer the QIPP packs to all CCGs/trusts in England as well as allowing the CSU to improve the packs through the use of better comparative groups (i.e. nearest neighbours). In producing these packs the data required is extracted using SQL server and analysed using MS Excel to produce the charts and tables included within the packs.

PROMS
As detailed in the “Objectives” section (Objective B) the PROMS data will be used to develop a decision support tool, PROMS data will be extracted from SQL server and analysed using appropriate statistical analysis software (STATA or R) in order to establish the relationship between a range of patient characteristics (e.g. age, gender, co-morbidities) and the procedure outcomes based on PROM scores.
The tool that will be developed will not contain any patient data. The tool that will be provided to the customer(s) will only contain a mathematical algorithm based on the established statistical relationships between patient characteristics and outcomes.

Mental Health Minimum Dataset (MHMDS)
The MHMDS will be used to model expected future activity levels and capacity requirements within CCGs after taking into account the impact of projected demographic changes and also the potential impact of mental health prevention strategies, admission avoidance strategies and length/intensity of treatment reduction strategies. Patient level data is required to enable the CSU to adjust and remove activity in line with expected changes. Using patient level data also allows the CSU minimise the impact of overestimating impacts as a result of double counting which is not possible with aggregate data.
As outlined in the “objective” section the data will be used in two ways firstly it will be used to provide supporting benchmarking and historical trend analyses to support modelling parameter setting. For this aspect of the project data extracts will be produced using SQL server and downloaded into MS Excel to produce the charts and tables required.

Secondly it will be used to create a model to estimate future activity levels after accounting for changes in demographics and the impact of changes to service provision. The model will be constructed using SQL server to process the data applying any modelling factors and parameters. Aggregate output files from SQL server will be downloaded and analysed in MS Excel in order to produce the required charts and tables for inclusion in reports.
The dataset will also be used to develop prospective intervention specific models to estimate changes in mental health team activity levels and the scale of potential savings as a result of the introduction of specific strategies to reduce the need for mental health services. These strategies may include, for example, schemes to increase early diagnosis of mental health conditions. This will help the CCG to better understand the costs and benefits of proposed changes allowing them to make better decisions about the effective use of commissioning resources. As with the higher level modelling in order to develop specific intervention impact models requires the production of benchmarking and trend analyses to help the customer to make judgments on the likely scale of impact of specific interventions. These judgments are incorporated into the model so it is important that they are based as far as possible on the best available data available. These prospective models will be constructed within SQL server and aggregate outputs downloaded into MS Excel to produce required outputs. The reports and any accompanying data tables will contain only data which is aggregated, with small numbers suppressed in line with the HES Analysis Guide.

ONS mortality data
As detailed in the “Objectives” section (Objective D) the ONS mortality data combined with the national HES data will be used to understand how the nature and scale of healthcare utilisation changes as a result of changes in demographics. It will also allow the CSU to develop a new approach to estimating the impact of an ageing population on future healthcare demand. As with the other datasets the ONS data will be stored within a SQL server database and the data required for this analysis will be extracted and analysed within MS Excel or other appropriate statistical software packages such as STATA or R in order to establish the mathematical relationship between proximity to death and healthcare utilisation which can be used in future (and potentially some of the current modelling work outlined in this document). During these data transfers into appropriate analysis software packages the data will not leave the secure environment.

Any other projects that may make use of this work (for example the NHS England Fit For the Future programme) would only utilise the methodology derived from this project and would not use the actual ONS data. The reports and any accompanying data tables will contain only data which is aggregated, with small numbers suppressed in line with the HES Analysis Guide.

Across all of the above processing, processing will be only carried out by CSU staff with the appropriate governance and access.

The data will not be used to link at record level to other datasets (other than where already provided in linked or bridging form by NHS Digital). The data may however be linked to organisational level data such as already exists within the public domain.

For clarity, the DSCRO may not process the data for the CSU other than initially downloading the data and storing it on the servers accessible by the CSU, and hence is not listed as a data processor.

National radiotherapy demand and capacity modelling — DARS-NIC-661891-S1S9Q

Type of data: Pseudonymised

Opt outs honoured: No (Flow to de-identified environment - no analysis on confidential patient information)

Legal basis: NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: This is an internal request to access pseudonymised National Disease Registration Service (NDRS) data. Access to the data is required to support a project to inform future radiotherapy provision and capital investment by forecasting future demand for linear accelerators and the capacity required to meet this demand.

As a secondary aim, the project aims to explore variation in radiotherapy uptake and both the magnitude and drivers of this variation.
The project has three main objectives:
1. provide projections of liner accelerator (LINAC; a device used in radiation treatments) demand and capacity projections to support Cancer Alliances to develop radiotherapy equipment replacement capital plans
2. inform national demand growth assumptions and provide projections of capacity and equipment replacement needs under different scenarios. This will enable NHSE's national radiotherapy team to provide effective challenges to support the development of system replacement plans that can deliver NHS Long Term Plan commitments relating to radiotherapy
3. assess variation in current levels of access to radiotherapy and quantify both the magnitude and drivers of this variation. This work will inform, and then be informed by complementary data into variation in cancer access so that any necessary improvement actions can be identified and developed.

The data requested will allow for pathway-level modelling of future radiotherapy demand and an assessment of levels of uptake of radiotherapy. The requested data will do this by providing the required level of detail on current activity, including treatment pathways and patient flow.

Access to pseudonymised subsets of the following datasets is required:
NDRS Cancer Registry (April 2016 to Latest Available)
NDRS Radiotherapy Dataset (RTDS)(April 2016 to Latest Available)

The data will be minimised as follows:
• Limited to patients that received radiotherapy treatment from April 2016 onwards
The applicant has undertaken signification work with the NDRS Data Production team to ensure that the data being accessed is the minimum amount necessary to achieve the purpose of this project.

NHS England determines the purpose and means of processing. NHS England has entered into a Data Processing Agreement with Edge Health Ltd, which will process the data under the instruction of NHS England.

Edge Health Ltd had been recruited by the appropriate NHS England tendering process; they were considered to be the most appropriate service provider for the processing outlined. NHS England have followed the DPIA IG process and have an appropriate Data Processing Agreement in place.


The lawful basis for processing personal data under the UK General Data Protection Regulation (GDPR) is Article 6(1)(e)- processing is necessary for the performance of a task carried out in the public interest or 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)(h)- processing is necessary for preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services based on Union or Member State law or under a contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3. NHS England is responsible for the provision of health and social care, and the management of systems and compliance.


As this is an internal request for data, this application will not go on to form a legally binding Data Sharing Agreement. (internal NHS transfer)

Sensitive:

When:DSA runs 2023-03-24 — No 2023.04 — 2023.11.

Access method:

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: Yes

Datasets:

  1. NDRS Cancer Registry
  2. NDRS National Radiotherapy Dataset (RTDS)
  3. NDRS Cancer Registrations

Objectives:

The initial analysis will provide two reports. These will include:
- An Operational Delivery Network (ODN) level forecast of radiotherapy demand for the next 5 years, this will include an estimate of the "missed" referrals due to the pandemic. This will be broken down by the tumour pathway.
- An estimate of the capacity (LINAC volume) requirement, by ODN over the same time period
- An identification of the geographies with the lowest access to radiotherapy, and the drivers of this

Data in the outputs will be aggregated to ODN and pathway level, with a forecast of future demand, under different scenarios, for each ODN over the next 5 years. This will give volumes of activity which are materially above that required for small number suppression.

The results of the initial analysis will not be made publicly available. The purpose of the work is to inform future investment decisions taken by NHS England on radiotherapy capacity and therefore the output from the analysis will remain within NHS England. Where relevant, estimates for individual ODNs may be shared with the relevant ODNs in order to inform local investment decisions. NHS England will remain the sole owner of the results of the analysis.
NHS England will review the reports and look at what information can and should be made publically available. The intention is to ensure that there will be an output for the public once NHS England have reviewed the initial analysis.

The analysis will be completed by the end of 2023.

Myocardial Ischaemia National Audit Project (MINAP) Annual Report — DARS-NIC-64572-X0Q4D

Type of data: Aggregated, Pseudonymised

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

Legal basis: 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), Internal flow of aggregate tables only

Purposes: No, This data sharing agreement is not an intended legal document, it is a reference document to evidence data flows. The agreement will not be signed as a legal document. It will instead be signed by internal NHS England colleagues. NHS England has commissioned NHS Arden and Greater East Midland Commissioning Support Unit (Arden and GEM) to host the National Institute for Cardiovascular Outcomes Research (NICOR) to continue to manage the six national cardiovascular audits: • Myocardial Ischaemia National Audit Project (MINAP – concerning heart attacks or other acute coronary syndromes) • National Heart Failure Audit (NHFA) • National Audit for Percutaneous Coronary Interventions (NAPCI – relating to a non-surgical method used to open narrowed arteries that supply the heart muscle with blood) • National Congenital Heart Disease Audit (NCHDA – relating to procedures performed for a cardiac defect present from birth) • National Adult Cardiac Surgery Audit (NACSA) • National Audit of Cardiac Rhythm Management (NACRM) NICOR's national audit programme comprises of two types of audits: two specialist domains that are concerned with the disease processes (MINAP and NHFA) and four that cover delivery of specific services (procedures for patients with congenital heart disease, percutaneous coronary intervention, cardiac surgery and the management of cardiac rhythm abnormalities). The aim of these NICOR audits is to measure and report delivery of care against defined guidance standards and to enable the improvement of the quality of care and outcomes of patients with a range of cardiac conditions. Individuals who are already included in NICOR’s six national cardiovascular audit databases have their hospital and mortality outcomes reported under DARS-NIC-359940-W1R7B. As of 24 June 2022, NHS England is the data controller, commissioner and funder for all NICOR's audits and registries. The audits are based on prospectively collected data on patients in all NHS and independent healthcare providers in England and Wales. NICOR is the delivery arm of Arden and GEM (formal processor) for managing the audits and data processing. This Data Sharing Agreement concerns the MINAP which contains information about the care provided to patients who are admitted to hospital with acute coronary syndromes (heart attack). Its findings have been made public since 2003 via annual public reports. MINAP aspires to include complete information about the care of every patient admitted to hospital with heart attack. By so doing there can be greater confidence in the reliability of subsequent analyses and in the validity of comparisons between participating hospitals. The audit must publish case ascertainment at Trust and hospital level to ensure it is capturing all relevant cases. Pseudonymised hospital provider codes are required for this reason. This aspect of data quality is fed back to participating centres, to NHS England and regulatory bodies such as the Care Quality Commission (CQC). The tabulated HES Admitted Patient Care data requested under this Data Sharing Agreement is the minimum level of data required for case ascertainment purposes. NICOR (Arden and GEM) only receive data concerning the number of patients who received care by individual hospitals and trusts. This data allows NICOR to complete a comparison of HES-recorded acute coronary syndrome with MINAP-recorded acute coronary syndrome admissions. There are no alternative less intrusive ways of achieving the purpose. The HES APC data supplied by NHS England will be used to produce ‘participation’ tables for audit purposes, to determine whether hospitals are fully participating in the audit. This will confirm the validity of the numbers that are reported by the hospitals to other NHS databases e.g., HES data and Best Practice Tariff. Aggregate HES data at Trust (and component hospital) level will be compared to the number of records submitted to the audit by each Trust and Health Board, to measure case ascertainment for participating centres. This is a key quality indicator. NICOR requires small numbers unsuppressed for the Annual Reports. If numbers were suppressed, comparison to HES figures with the number of records that hospitals have submitted would result in the NICOR numbers being inaccurate. i.e. if 300 cells are suppressed with each cell representing up to 7, that is up to 2100 admissions excluded from the total, which is a significant amount. To address the GDPR principle of Data Minimisation, NICOR request that the data received is restricted to patients who have been discharged from hospital with a diagnosis of ST segment elevation Myocardial infarction (STEMI) and Non-ST-elevation myocardial infarction (NSTEMI). NICOR only use the latest annual HES data year to analyse case ascertainment. Once the analysis is complete and the annual reports have been published, NICOR destroy the previous year’s data request. NICOR is hosted by Arden and GEM which as the sole data processor only processes the data for the purposes described in this agreement. NHS England relies on the Article 6(1)(e) legal basis for processing personal data under UK GDPR - "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 is justified through commissioning arrangements which link back to NHS England and other national bodies with statutory responsibilities to improve quality of health care services. NHS England rely on Article 9(2)(h) of the UK GDPR as the legal basis for processing special category data. "Processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services on the basis of Union or Member State law or pursuant to contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3". This is justified as NHS England are responsible for provision of health and social care, and management of systems and compliance. (Academic, internal NHS transfer)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2018-01-10 — 2021-01-09 2021.05 — 2023.11.

Access method: One-Off

Data-controller type: HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), NHS ENGLAND (QUARRY HOUSE), NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

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

Objectives:

The Healthcare Quality Improvement Partnership (HQIP) have commissioned, on behalf of NHS England as part of the National Clinical Audit and Patient Outcomes Programme (NACPOP), six national cardiovascular audits which are managed by the National Institute for Cardiovascular Outcomes Research (NICOR) hosted by Barts Health NHS Trust.

The six audits, collectively termed the National Cardiac Audit Programme (NCAP) audits, are based on prospectively collected, data on patients in all NHS providers in England and Wales. NCAP is managed by NICOR, and their funding contract for the National Cardiac Audit Programme runs until June 2022.

NCAP collects data from two domains that are concerned with particular disease processes (heart attacks and heart failure) and four that cover delivery of specific services (procedures for patients with congenital heart disease, percutaneous coronary intervention, cardiac surgery and the management of cardiac rhythm abnormalities). The aim of these NCAP audits is to measure and report delivery of care against defined guidance standards and to enable the improvement of the quality of care and outcomes of patients with a range of cardiac conditions.

The Myocardial Ischaemia National Audit Project (MINAP) is one of the six focal areas for audit within the NCAP that contains information about the care provided to patients who are admitted to hospital with acute coronary syndromes (heart attack). Its findings have been made public since 2003 via annual public reports.

MINAP aspires to include complete information about the care of every patient admitted to hospital with heart attack. By so doing there can be greater confidence in the reliability of subsequent analyses and in the validity of comparisons between participating hospitals. The audit must publish case ascertainment at Trust and hospital level to ensure it is capturing all relevant cases. This aspect of data quality is fed back to participating centres, to NHS England and regulatory bodies.

Hospital Provider codes (pseudonymised) are now required as MINAP must publish an audit case ascertainment at Trust AND hospital level to ensure it is capturing all relevant cases for feeding back to NHS England and the Care Quality Commission.

The tabulated HES Admitted Patient Care data requested is necessary for the performance of a task carried out in the public interest, namely improving the quality of care for people being treated for heart attack – Myocardial Ischaemia.

There are no alternative, less intrusive ways of achieving the purpose.

This agreement has Joint Data Controllership - consisting of the Healthcare Quality Improvement Partnership (HQIP) and NHS England.

NHS England is responsible for determining which projects/topics are included as part of the NCAPOP. HQIP, as commissioner of the NCAPOP, is responsible for project specification development, procurement and extension activities, contract management and authorising data sharing requests. NHS England, as a funder of the NCAPOP, participates within specification development, procurement and project extension activities and authorises the publication of project outputs.

NHS England is involved with developing the scope and purpose of the NCAPOP projects through participation within specification development activities and may authorise (as chair of the specification development meetings) the final project specifications. These specifications set out the purpose of the project, the patient groups and clinical services to evaluate and the types of data to collect. NHS England are a representative upon the HQIP Data access request group which authorises data sharing applications from third parties.

NHS England is responsible for determining which projects/topics are included as part of the NCAPOP. HQIP, as commissioner of the NCAPOP, is responsible for project specification development, procurement and extension activities, contract management and authorising data sharing requests. NHS England, as a funder of the NCAPOP, participates within specification development, procurement and project extension activities and authorises the publication of project outputs.

NHS England is involved with developing the scope and purpose of the NCAPOP projects through participation within specification development activities and may authorise (as chair of the specification development meetings) the final project specifications. These specifications set out the purpose of the project, the patient groups and clinical services to evaluate and the types of data to collect. NHS England are a representative upon the HQIP Data access request group which authorises data sharing applications from third parties.

NICOR is hosted by Bars Health NHS Trust, as such Barts Health NHS Trust is the sole data processor, and only processes the data for the purposes described in this agreement.

Legal Basis Justification:
HQIP and NHS England both rely on the Article 6 (1) (e) legal basis under GDPR - "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 is justified through commissioning arrangements which link back to NHS England and other national bodies with statutory responsibilities to improve quality of health care services.

HQIP rely on Article 9 (2) (i) as the legal basis for processing under GDPR - "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". This is justified as all projects aim to drive improvements in the quality and safety of care and to improve outcomes for patients.

NHS England rely on Article 9(2)(h) of the GDPR as the legal basis for processing. "Processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services on the basis of Union or Member State law or pursuant to contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3". NHS England are responsible for provision of health and social care, and management of systems and compliance.

Yielded Benefits:

MINAP presented case ascertainment rates for participating Trusts – expressed as the ratio of the number of cases coded as myocardial infarction (in Hospital Episode Statistics (HES) data provided by NHS Digital for England to the number of cases submitted to MINAP – for the first time in 2017. This has repeated annually since. Analysis revealed wide variation in case ascertainment. Some hospitals submit significantly fewer cases to MINAP than would be expected based upon the corresponding HES codes; others submit many more cases to MINAP than appear in HES. This latter point – a greater than expected number of cases submitted to MINAP – appears counterintuitive. It is likely to represent differences in hospital coding practices. So, for example, in 2018 while the median case ascertainment rate for English Trusts is 99%, there are 11 Trusts that have rates above 150% (implying substantially greater MINAP submissions than coded discharges) and 11 Trusts that have rates below 50% (implying inadequate case finding). Given the documented variation, MINAP will work with participating centres to better understand existing coding practice. This will lead to a request for additional ICD codes in HES returns. Additionally NICOR are mandated by HQIP to maintain and improve 'Data Quality'. Markers of data quality include: • Timeliness of reporting - how soon after, and how often during, the relevant period of reporting are reports made available? • Accuracy/validity of submitted data - are the data submitted to the audit a true reflection of the care provided? • Data completeness - for each case, how many of the data fields are completed? • Case ascertainment - what proportion of the entire 'population' of patients with the clinical condition of interest is submitted to the National Audit? Following receipt of previous HES data, MINAP has been able to report on this last aspect of data quality - case ascertainment. The audit publishes case ascertainment and clinical practice analysis at Trust and hospital level, and feeds back on this to NHS England and the Care Quality Commission. The hospital level HES tabulation data requested is the minimum level of data required for case ascertainment purposes, which basically means that it’s a check for verifying the number of patients submitted to NICOR with the number of patients’ coded by the hospitals for HES. The data we receive is number of patients who received care by individual hospitals. So the hospital level HES tabulation data is NOT at patient level. We do not consider this to be “intrusive” however, there are no other ‘less intrusive’ ways of achieving this purpose. The data supplied by NHS Digital will be used to produce ‘participation’ tables for audit purposes, to determine whether hospitals are fully participating in the audit. This will confirm the validity of the numbers that are reported by the hospitals to other NHS databases e.g. HES data and Best Practice Tariff. The CQC also use our data for monitoring the performance of hospitals. For this case ascertainment process provides them with the required quality assurance.

Expected Benefits:

The primary benefit is in the calculation (and presentation) of case ascertainment rates for participating centres.

Case ascertainment is an important aspect of data quality and provides an estimate as to what proportion of patients with the clinical condition under study are submitted to the audit. The publication of case ascertainment rates encourages participating centres to include as many patients as possible. This minimises the risk of hospitals ‘cherry picking’ patients for the audit and enables the audit to measure like with like and provide national comparative data.

A secondary benefit is in an understanding of the coding practices of participating hospitals with respect to similar cardiac conditions

Transparency with respect to degree of participation in mandated clinical audit: The audit provides participation rates, and hospital level data, to organisations such as the Care Quality Commission’s Quality and Risk Profiles, the NHS Choices website and data.gov.uk. Case Ascertainment is also presented within annual public reports.

Improved data quality: Publication and comparison of case ascertainment will identify poorer performing hospitals and encourage such hospitals to improve the quality of the data they submit. At the same time higher performing hospitals can receive credit.

Confidence in the implications (and generalizability) of national audit: Access to HES trusts level data is crucial for establishing case ascertainment and ensuring the quality of patient care and patient outcomes is being monitored for all patients. Case ascertainment is key to measuring equity of access and care. This will lead to:
(a) Improvements in patient care, as the NCAP supports both quality assurance and quality improvement initiatives both locally and nationally.
(b) Understanding differences in hospital coding practices: Variation in cases ascertainment may also point to differences in HES coding practices between hospitals.

Outputs:

The MINAP audit publishes case ascertainment and clinical practice analysis at Trust and hospital level, and feeds back on this to NHS England and the Care Quality Commission.

NICOR must deliver to HQIP and NHS England the NCAP Annual Report - as a contracted deliverable. Following the formal sign off and publication of the NCAP 2020 Annual Report there will be some individual discussions and presentations of the report e.g. at conferences. These presentations may not necessarily include the HES tabulation data, but the publication and any presentations would be based on the NCAP Annual Report (which uses HES tabulation data for case ascertainment purposes).

Both the National Cardiac Audit Programme (NCAP) 2020 Annual Report and the domain-specific Summary MINAP Annual Report will be distributed electronically to Trust chief executives, clinicians, British Cardiovascular Society and to other stakeholders. These reports are also publicly available online on the HQIP webpages and on the NICOR website: https://www.nicor.org.uk/national-cardiac-audit-programme/. Analyses from NCAP appear in Quality Accounts and are made available to CQC visiting teams.

All outputs will be restricted to aggregate data with small number suppressed in line with the HES analysis guide.

Processing:

All those with access to the data are substantive employees of Bart's Health NHS Trust. All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

There will be no flow of data into NHS Digital. NHS Digital will flow tabulated HES APC data to Barts Health NHS Trust. There will be no subsequent flow of data.

The data from NHS Digital will not be used for any other purpose other than those outlined in this agreement. The data received from NHS Digital will not be linked to other available datasets.

The HES tabulation data will be used to determine whether hospitals are fully participating in the audit. Aggregate HES data at Trust (and component hospital) level will be compared to the number of records submitted to the audit and expressed (in tabular format) as case ascertainment rates for participating centres. This is a key quality indicator.

For the purpose of the MINAP annual report, NICOR cannot allow for any small numbers to be suppressed. If numbers were supressed, comparison to HES figures with the number of records that hospitals have submitted would result in NICOR numbers being inaccurate. I.e. If 300 cells are suppressed, that is up to 1500 admissions excluded from the total, which is a significant amount.

The tabulated HES data is stored on a shared drive only accessible to NICOR staff. Once the annual reports have been published, the data for that year is destroyed is destroyed.

Upon instruction from NHS Digital, a Certificate of Data Destruction must be completed by the Data Controller confirming the data has been appropriately disposed of following use.

Flu – Vaccination Programme – Ethnic Category information for secondary uses — DARS-NIC-402116-G1T7V

Type of data: Identifiable

Opt outs honoured: Identifiable (Statutory exemption to flow confidential data without consent)

Legal basis: CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002

Purposes: No, The purpose of the dissemination is to support the NHS England national call/recall for flu vaccination programme. The dissemination will provide Ethic category data to link to their existing systems. Ethnic category is required for: • Risk stratification of COVID patients to identify those at high risk of complications • Management reporting for flu/COVID vaccinations to address health inequalities • The management of the flu vaccinations is vital to ensure that the COVID vaccination programme can proceed efficiently and the two are linked by the time period required inbetween an individual taking the flu vaccination and the first COVID vaccination. The two processes are intrinsically linked and the provision of ethnic category data is vital to both. Ethnic category is required for the flu vaccination element to ensure that there is optimal coverage of uptake of the vaccine across the population. Reporting on uptake by ethic category will allow the system to manage the vaccine programme. Optimal management of the flu vaccine programme is important to help manage the national covid pandemic to try and prevent a double peak for both flu and Covid. The management of the flu vaccine has implications on the management of any Covid vaccine in that anyone who has had a flu vaccine may not then receive a COVID-19 vaccine within a certain time period and so the management of the two together is essential. Certain ethnic groups have been connected with increased morbidity and mortality in cases of CV19 and optimal uptake in these populations would be desirable if and when a CV vaccine is available. It is essential that the two programmes are coordinated to accommodate the developing characteristics of the pandemic, and any interfaces between the vaccines, and their delivery processes as they are established. Data disseminated under this agreement will not be used for performance management purposes. (Agency/Public Body, internal NHS transfer)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2020-09-17 — 2021-09-16

Access method: One-Off, Ongoing

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. GPES Data for Pandemic Planning and Research (COVID-19)
  2. Hospital Episode Statistics Accident and Emergency
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Outpatients
  5. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
  6. Hospital Episode Statistics Accident and Emergency (HES A and E)
  7. Hospital Episode Statistics Admitted Patient Care (HES APC)
  8. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

The purpose of the dissemination is to support the NHS England national call/recall for flu vaccination programme. The dissemination will provide Ethic category data to link to their existing systems.

Ethnic category is required for:
• Risk stratification of COVID patients to identify those at high risk of complications
• Management reporting for flu/COVID vaccinations to address health inequalities
• The management of the flu vaccinations is vital to ensure that the COVID vaccination programme can proceed efficiently and the two are linked by the time period required inbetween an individual taking the flu vaccination and the first COVID vaccination. The two processes are intrinsically linked and the provision of ethnic category data is vital to both.

Ethnic category is required for the flu vaccination element to ensure that there is optimal coverage of uptake of the vaccine across the population. Reporting on uptake by ethic category will allow the system to manage the vaccine programme.

Optimal management of the flu vaccine programme is important to help manage the national covid pandemic to try and prevent a double peak for both flu and Covid. The management of the flu vaccine has implications on the management of any Covid vaccine in that anyone who has had a flu vaccine may not then receive a COVID-19 vaccine within a certain time period and so the management of the two together is essential.

Certain ethnic groups have been connected with increased morbidity and mortality in cases of CV19 and optimal uptake in these populations would be desirable if and when a CV vaccine is available.

It is essential that the two programmes are coordinated to accommodate the developing characteristics of the pandemic, and any interfaces between the vaccines, and their delivery processes as they are established.

Data disseminated under this agreement will not be used for performance management purposes.

Expected Benefits:

The data supplied through this agreement will help NHS England to support the management of the flu vaccine programme with the aim of reducing pressure on the NHS throughout the winter period. In turn this will relieve pressure within the NHS assist them in the management of the ongoing COVID-19 pandemic response.

The implementation of this service will deliver a centralised service for the management of seasonal flu immunisation and is an essential component of NHS England’s response to the COVID-19 pandemic. Benefits anticipated are;

1. help to ensure that any second “spike” in coronavirus infections in England separated in time as far as possible from the annual flu epidemic – so minimising pressures on NHS resources

2. provide a protype for the delivery of a subsequent national COVID-19 immunisation programme by establishing a dynamic infrastructure capable of responding rapidly to target appropriate cohorts across the whole population of England.

Outputs:

The system provides a Business Intelligence (BI) solution using Microsoft Power-BI which allows comprehensive dashboarding and analysis of the vaccination programme in real time.

This service is an integral part of the call/recall process and drives initiatives to increase uptake. Dashboards will be provided at national, regional, STP, local authority, ICS/P or GP practice level and in each case will only cover statistics for the citizens covered at that area.

Processing:

NHS Digital will send NHS Number and ethic category data to System C and Graphnet.

The data is then linked to the following feeds that System C and Graphnet already receive from NHS Digital;

o Demographics
o Vaccine activity data
o At risk cohorts

The data is then used for reporting vaccine uptake rates by Central South West CSU in aggregate form. Aggregated data will also be shared with ImmForm for PHE reporting. ImmForm is the system used by the Department of Health, the National Health Service and Public Health England to:

• record data in relation to uptake against immunisation programmes and incidence of flu-like illness
• provide vaccine ordering facilities for the NHS

Graphnet Health Ltd and System C Healthcare Ktd are acting as data processors in this agreement.

The National Imunisation Management service uses two integrated standard off the shelf software systems: the System C “CarePlus” immunisation system, and the Graphnet “CareCentric” shared record system, (System C and Graphnet are part of a Care Alliance).

CarePlus currently manages immunisations for around half of children in England and combined with CareCentric it delivers the children’s immunisation programme for all of Greater London. CareCentric holds and provides access to very detailed clinical records including primary care records for over 12m English citizens. Together they will work to utilise NIMS in the best possible platform.

NHS Digital will check the GDPPR and HES data will be checked fortnightly for any new information and if found that data will be released to NHS England so that they have the most current data to work from.

HES data for all CSUs and NHS England NIC-371243-H1P5T-2019/20 — DARS-NIC-371243-H1P5T

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

Legal basis: Health and Social Care Act 2012, 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 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(2)(b)(ii), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: Yes, Commissioning Support Units (CSUs) are part of NHS England (NHS E), and provide comprehensive business intelligence (BI) services to a wide range of NHS organisations, this includes both standard analytics and reporting, deep-dives and diagnostic exercises to offer insight and intelligence on a commissioner’s health economy. In addition, CSUs offer business intelligence applications allowing self-service access to a range of dashboards and configurable reports. Tools are available on a subscription-basis only to NHS organisations, limited to Clinical Commissioning Groups (CCGs), internally within the CSUs through specialist support teams, by CCG member practices, and by local authorities. The Commissioning Support Units providing the services are: - North East London Commissioning Support Unit - North of England Commissioning Support Unit - South, Central and West Commissioning Support Unit - Midlands and Lancashire Commissioning Support Unit - Arden and Greater East Midlands Commissioning Support Unit NHS England’s lawful basis for processing is 6(1)(e) ‘…exercise of official authority…’. For special categories (health) data the basis is 9(2)(h) ‘…health or social care…’. NHS England (as the legal entity) is the sole data controller, and the CSUs (as part of NHS England) are data processors. Microsoft Azure provides cloud storage services for all commissioning support units and is therefore a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data. ANS Group Ltd are assisting South Central and West CSU to transition to CLOUD services and are therefore a data processor. ANS Group will be supplying support, platform build and management services for SCW CSU’s Cloud environment. As such, they could have access to pseudonymised / aggregate / anonymous data through system administration accounts. Whilst ANS Group are a data processor as they will have sight of the data, they will not process the data for any other purpose than IT support. ANS Group using the data for any other purpose would be considered a breach of this agreement. Hospital Episode Statistics (HES)and Emergency Care Data Set (ECDS) are required to provide support to CCGs, other commissioning bodies, and local authorities working with CSUs to meet their statutory duties under the Health & Social Care Act 2012 and to support NHS health economy wide transformation projects. The full, national set of HES and ECDS data allows complex and detailed modelling and benchmarking of activity and diagnostic interventions (numbers and rates), essential to successful commissioning of services and contract monitoring, including analysing relationships and influences between A&E, Inpatient and outpatient care and use of diagnostic services. This will especially support benchmarking work for CCGs, other commissioning clients and local authorities taking part in health economy wide transformation projects that require detailed and comprehensive hospital level data. There will be no direct linkage between HES data records and other data already used by any CSU or in the BI tools. HES data may be presented alongside other data but not linked to it – for example a report may contain HES data alongside workforce statistics, weather reports etc. CCGs only receive local/regional commissioning flows of data such as SUS and local flows filtered by resident/registered populations, so analysis undertaken on national data such as HES provides significant added value. These data sources will allow CCGs, other commissioning organisations and local authorities to benchmark and highlight areas of variation, so that best practice can be identified in similar health economies anywhere in England. The data purpose relates to the need for national data for comparative analysis, benchmarking and forecasting, and this requirement for CSUs has specified support from NHS England. Having an extended time trend also provides valuable longer-term context when looking at health populations (e.g. health needs analysis, health economics) and service transformation. National data covering a number of years is required for benchmarking purposes, enabling users to compare themselves on a national footprint. CSUs therefore require HES data with a 10-year rolling history to enable them to provide accurate time-series forecasting methodologies. Forecasting, particularly with regards to winter surge management or financial planning, are key areas of interest for the NHS currently and are areas that the NHS North of England CSU (NECS) have used the HES data to support most recently. As the NHS evolves, there is a greater emphasis on CCGs forming part of larger collaborations called Sustainability and Transformation Partnerships (STPs), and CSUs need to accelerate this way of working throughout the country, through partnerships of care providers and commissioners in an area STPs. Some areas are now ready to go further and more fully integrate their services and funding, and CSUs will back them in doing so (Integrated Care Systems). Provision of modelling support to emergent Integrated Care Systems (ICSs) thus supporting the whole health system through modelling demand and capacity primarily in secondary care. To support the on-going budgetary pressures the NHS is faced with, the BI services and CSU BI tools offer significant support to commissioners on their Quality, Innovation, Productivity and Prevention (QIPP) programmes. Identifying service areas where the commissioner is an outlier that may then require re-procurement of a clinical service, comparisons with peer groups and best practice to understand how a change in approach might deliver a financial saving. Working together with patients and the public, NHS commissioners and providers, as well as local authorities and other providers of health and care services, ICS’s will plan how best to provide care, while taking on new responsibilities for improving the health and wellbeing of the population they cover. Under this agreement, the CSUs will use the data provided for 2 purposes: i) benchmarking dashboards and reports, and ii) bespoke analytics and reporting. The HES data will be utilised within CSU BI tools to provide a range of benchmarking dashboards and reports as required to address specific priorities. This may include mortality, end of life, procedures of limited clinical value, new to follow-up ratios, readmissions etc. The ability to present a national and peer-group picture of locally defined indicators is the ambition. HES data will be presented independently of existing data flows within a bespoke dashboard as well as to supplement current reports/dashboards, for example using HES to calculate a national readmission rate to be presented on a locally fed readmission report. As well as within the BI tool, HES data will be used by the BI team for bespoke analytics and reporting. This will include analysis on behalf of individual CCGs who have requested a deep dive, for a particular area and want to understand how they compare to other areas. It will also help support whole provider and health economy analysis where service re-configurations are being proposed. (Commissioning Support Unit (CSU), internal NHS transfer)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-09-03 — 2020-09-02 2017.06 — 2023.11.

Access method: Ongoing, Frequent Adhoc Flow

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No, Yes

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Accident and Emergency
  3. Hospital Episode Statistics Critical Care
  4. Hospital Episode Statistics Outpatients
  5. Diagnostic Imaging Dataset
  6. Bridge file: Hospital Episode Statistics to Diagnostic Imaging Dataset
  7. Emergency Care Data Set (ECDS)
  8. HES-ID to MPS-ID HES Accident and Emergency
  9. HES-ID to MPS-ID HES Admitted Patient Care
  10. HES-ID to MPS-ID HES Outpatients
  11. Diagnostic Imaging Data Set (DID)
  12. Hospital Episode Statistics Accident and Emergency (HES A and E)
  13. Hospital Episode Statistics Admitted Patient Care (HES APC)
  14. Hospital Episode Statistics Critical Care (HES Critical Care)
  15. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

The HES data will only be used by North and East London Commissioning Support Unit (NELCSU) to provide support to Clinical Commissioning Groups (CCGs) and other commissioning bodies working with NELCSU to meet their statutory duties under the Health & Social Care Act 2012 and NHS health economy wide transformation projects that require detailed hospital level data.

The pseudonymised record level HES data is interrogated only by approved NELCSU substantively employed analysts to provide benchmarking and comparative information to NELCSU clients and NHS health economy wide transformation projects that require detailed hospital level data.

The full, national set of HES data allows complex and detailed modelling and benchmarking of activity, essential to successful commissioning of services and contract monitoring, including analysing relationships and influences between A&E, Inpatient and outpatient care. This will especially support benchmarking work for CCG clients taking part in health economy wide transformation projects that require detailed and comprehensive hospital level data (for example from local SUS data feeds the applicant only receives data for their CCG’s registered population, which does not allow whole trust activity to be considered) and allow CCGs to benchmark and identify best practice in similar health economies anywhere in England.

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

Yielded Benefits:

Some of the yielded benefits of HES data to date are: 1) Assisting NHS England in London, at identifying the rates of GP referrals to hospitals across all the CCGs in London. There is a lot of variation, both between CCGs and between GP Practices within a CCG area and NELCSU have compared these in a way that accounts for these areas very different populations (in statistical terms this is known as “standardisation”. The NHS is experiencing significant pressure and unprecedented levels of demand. The average annual growth in GP referrals between 2009/10 and 2014/15 was 3.9%. Growth in 2015/16 compared to 2014/15 was 5.4%. For the same period, other referrals, which include consultant to consultant referrals grew by 6.7%. There is clearly a significant need for the NHS to manage the demand that flows into hospitals by ensuring that only the most appropriate cases are referred for face to face consultation. There is also evidence to suggest that a referral to hospital is not always necessary. NHS England have published a demand management “Good Practice Guide” covering areas such as “peer review of referrals”, “shared decision making” and “advice and guidance”. The results of this analysis help identify which geographies to target, inform the conversation around appropriate areas to change and help monitor the impact of any implemented demand management schemes. 2) Assisting a CCG in the South of England implement improvements in the area of diabetes and respiratory disease. The improvements will involve the health system – GPs, hospitals, community services – working more effectively together (or in the jargon working in a more “integrated” way). HES data has been used to identify variation in “outcomes” to identify potential areas to target. For example HES data was used to identify the numbers of patients admitted with complications of diabetes, as these are an indicator that a patient’s condition has deteriorated, something that could possibly be counteracted with better management of a patient’s condition within primary care. Are these numbers high relative to other areas? How much do they vary by GP practice? What is the real reason behind this variation? Integrated care schemes internationally have evidenced significant benefits in improving patient outcomes, experience of care and reducing costs to the health system. This project is the first stage of a pilot, and will be extended out to a wider geography and to other clinical areas. 3) Identifying potential influences on high A&E attendance rates. Within London, most A&E departments are under huge pressure from rising A&E demand. However, the rate of increase does vary significantly by geography and by patient group. By using national HES data NHS North and East London Commissioning Support Unit were able to undertake statistical modelling of most of the known drivers of A&E attendance and try to understand the relative importance of each. For example, patient ethnicity appears to be one influence. Those ethnic groups with high attendance rates can be targeted through communication campaigns or through their GPs to encourage use of alternative services where possible. The better that the reasons for growing A&E demand can be understood, the more effective commissioners can be in tackling the root cause of the issue.

Expected Benefits:

CCGs and Local Authorities (Public Health teams) have joint statutory duties under the Health and Social Care Act 2012 to plan and commission services and jointly assess the needs of their patients and populations, to ensure that health improvements and better outcomes are measurable, identifiable and attainable.

Analysis of HES and DIDs data helps these organisations achieve this by providing the greatest scope to evaluate outcomes of care and improvement in their health services against peer groups and national achievement – providing a more extensive and complete base of knowledge for decision making than data on their own patients alone (SUS data).

Measurable benefits can occur, for example, through gradual improvement in outcome over a number of years, to more immediate commissioning new services where a gap is identified, or de-commissioning failing services by identifying lower outcomes than is acceptable, compared to the norm.

Examples of benefits achieved to date include:
a. NELCSU supported a major reconfiguration of cancer and cardiac services in North London. The detailed numbers to support the case for change were extracted from the raw HES data. This was a complex exercise, requiring clinical input to define the primary and secondary coding of the patient cohorts affected by the change. This would only be possible through using very granular data which covers whole hospital activity (rather than for our customer CCGs). The rigour of the work helped with forming realistic planning assumptions and obtaining clinical and provider buy in for changes.
b. NELCSU are currently supporting NHS England with work identifying the highest and lowest referrers within London by CCG and by GP Practices within each CCG. This work requires whole London data and as it adopts age and sex standardisation needs data to a very granular level. We have also applied certain filters that improve the accuracy of the benchmarking from detailed analysis of the data. This project is currently supporting NHS England in a London-wide demand management programme which aims to ease the pressure on acute hospitals by targeting those CCGs and practices with abnormally referral rates.

Outputs:

Outputs are on an on going basis (i.e., no target date) as the HES data in general is used to support general commissioning and public health needs, and is not aimed at a specific report or deadline for use.

All outputs informed by information retrieved from the HES data tables are governed by adherence to the HES guidance on suppression of small numbers. Users of the data abide by the HES Analysis Guide which means that all outputs released must be aggregated with small numbers suppressed.

HES allows NELCSU to provide intelligence for programmes whose scope demands activity benchmarking of the CSU's clients (CCGs) against similar health economies or populations in England. SUS data does not allow this scope. National data also supports NHS health economy wide transformation projects that require detailed and comprehensive hospital level data.

Commissioners can compare with any service known to have better outcomes or new pathways, or support large scale transformation projects that may impact several commissioners across, for example, the North London area.

Outputs expected are aggregated data to support reports or decisions across examples such as the following:
• Elements of Joint Strategic Needs Assessments (JSNA) - to support CCGs/Local Authorities to consider the needs of their local populations and in how they respond with effective commissioning of services to properly meet those needs, by enabling, for example views of the use of secondary services by different patient groups by condition, ethnicity, etc.
• Quality, Innovation, Productivity and Prevention (QIPP) development - identifying and benchmarking areas across England with better practice than locally, to help evaluate high costs and poor outcomes in hospital care.
• Providing data on hospital admissions in-year to support monitoring of national ambitions, such as avoiding unnecessary admissions across CCGs, by practice, condition, hospital trust. CCGs are required to monitor and make progress on national outcome measures and ambitions by NHS England, and use of national benchmarking is promoted heavily by initiatives such as Right Care ‘Commissioning for Value’ (on behalf of NHSE). Without access to national data such as HES, CCGs cannot be ultimately certain that they are making progress or making decisions on the best basis possible.


Diagnostic Imaging is an acknowledged area of over/ duplicate treatment and so a fruitful area for NELCSU to investigate and to support improvement initiatives (eg Right Care). The DIDs data with linkage to HES will help with any deep dives and provide further opportunities for gaining insight from this data. As an example some of NELCSU customer CCGs have very high diagnostic intervention rates per head of population (eg for MRIs). Having DIDs data allows NELCSU to have the detailed data to be able to investigate these type of issues in more detail and provide useful outputs.

Processing:

Only an approved list of NELCSU substantively employed analysts have access to the full set of pseudonymised data tables, via secure server based Structured Query Language (SQL) querying. The data will only be for the purposes described in this document and not for any other purposes, including being used in data tools.

CSU analysts interrogate the data to produce aggregated output for monitoring care outcome and activity for a CCG’s population, patient group, condition or service provider, including trends over time in any given activity or care process. For example, trends over time can be modelled to produce forecasts of future activity, taking into account population growth or changes in service configuration.

National data is necessary to benchmark against any CCG peer groups (as defined by NHS England), or any other care pathway or group of patients. Benchmarking allows an individual CCG to evaluate its own care processes and outcomes against other similar commissioning populations, with a view to identifying areas for improvement or to identify best practice. National data also supports NHS health economy wide transformation projects or other commissioning initiatives that require detailed and comprehensive hospital level data.

Analysts will only release aggregated data with small numbers suppressed in line with the HES Analysis Guide.

The data is being held within a data centre which also holds data on behalf of other organisations. The applicant agrees that the data under this agreement must be held and remain separate to all other data (except where explicitly stated within the agreement), and accepts full responsibility for the breach of this agreement should this not be the case. In order to mitigate this risk, it is strongly recommended that the applicant considers the best practice controls as detailed in ISO 27017:2015 Code of practice for information security controls based on ISO/IEC 27002 and ISO 27018:2014, which establish commonly accepted control objectives, controls and guidelines for implementing measures to protect Personally Identifiable Data.

For clarity, any access by Interxion to data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

National Audit for Percutaneous Coronary Interventions (Angioplasty) - HES Tabulation data — DARS-NIC-318886-M1B9L

Type of data: Aggregated, Pseudonymised

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

Legal basis: 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), Internal flow of aggregate tables only

Purposes: No, This data sharing agreement is not an intended legal document, it is a reference document to evidence data flows.  The agreement will not be signed as a legal document.  It will instead be signed by internal NHS England colleagues. NHS England has commissioned NHS Arden and Greater East Midland Commissioning Support Unit (Arden and GEM) to host the National Institute for Cardiovascular Outcomes Research (NICOR) to continue to manage the six national cardiovascular audits: • Myocardial Ischaemia National Audit Project (MINAP-– concerning heart attacks or other acute coronary syndromes) • National Heart Failure Audit (NHFA) • National Adult Percutaneous Interventions Audit (NAPCI- relating to a non-surgical method used to open narrowed arteries that supply the heart muscle with blood) • National Congenital Heart Disease Audit (NCHDA- relating to procedures performed for a cardiac defect present from birth) • National Adult Cardiac Surgery Audit • National Cardiac Rhythm Management Audit As of 24 June 2022, NHS England is the data controller, commissioner and funder for all NICOR's audits and registries. The audits are based on prospectively collected data on patients in all NHS and independent healthcare providers in England and Wales. NICOR is the delivery arm of Arden and GEM (formal processor) for managing the audits and data processing. NICOR's national audit programme comprises of two types of audits: two specialist domains that are concerned with the disease processes (heart attacks and heart failure) and four that cover delivery of specific services (procedures for patients with congenital heart disease, percutaneous coronary intervention, cardiac surgery and the management of cardiac rhythm abnormalities). The aim of these NICOR audits is to measure and report delivery of care against defined guidance standards and to enable the improvement of the quality of care and outcomes of patients with a range of cardiac conditions. Individuals who are already included in NICOR’s six national cardiovascular audit databases have their hospital and mortality outcomes reported under DARS-NIC-359940-W1R7B. This Data Sharing Agreement concerns The National Audit for Percutaneous Coronary Interventions (NAPCI) which is one of the six focal areas for audit within the National Cardiac Audit Programme (NCAP) that contains information about the care provided to patients who are admitted to hospital for percutaneous coronary interventions (PCIs). The audit's findings have been made public for many years through its annual reports published on the NICOR website. NAPCI aims to capture data on clinical indicators which have a proven link to improved outcomes, and to encourage the increased use of clinically recommended diagnostic tools, disease modifying interventions/treatments and referral pathways. The NAPCI aspires to include complete information about the care of every patient admitted to hospital with coronary disease requiring percutaneous coronary intervention / angioplasty. By so doing there can be greater confidence in the reliability of subsequent analyses and in the validity of comparisons between participating hospitals. The audit must publish case ascertainment at Trust and hospital level to ensure it is capturing all relevant cases. This aspect of data quality is fed back to participating centres, to NHS England and regulatory bodies. The data supplied by NHS England will be used to produce participation tables for audit purposes and to determine whether hospitals are fully participating in the audit. Aggregate HES APC data at hospital level will be compared to the number of records submitted to the audit by each Trust and hospital, to measure case ascertainment. The hospital level HES tabulation data requested is the minimum level of data required for case ascertainment purposes. NICOR only receive data concerning the number of patients who received care by individual hospitals. The HES tabulation data will be used to determine whether hospitals are fully participating in the audit. Aggregate HES data at Trust (and component hospital) level will be compared to the number of records submitted to the audit and expressed (in tabular format) as case ascertainment rates for participating centres. This is a key quality indicator. There are no alternative less intrusive ways of achieving the purpose. The HES Tabulation data is only required once a year for case ascertainment purposes. Once the audit data has been analysed and the annual reports have been published, the HES tabulation data is destroyed. NICOR is hosted by Arden and GEM which as the sole data processor only processes the data for the purposes described in this agreement. For NICOR’s annual reports, the HES Tabulation data requires all small numbers to be unsuppressed, because otherwise when comparing HES figures with the number of records that hospitals have submitted to the audit, NICOR’S numbers will be inaccurate. If 300 cells are suppressed (with each suppressed cell representing up to 7) that is up to 2100 admissions excluded from the total, which is quite a significant amount. The data with small numbers not suppressed will allow the comparison of the number of cases a hospital has submitted to the audit with the actual number the hospital has treated as recorded in the HES data. To address the GDPR principle of Data Minimisation, NICOR request that the data received is restricted to patients who have been discharged from hospital (with hospital code) with a diagnosis of percutaneous coronary intervention (PCI)/angioplasty. NHS England relies on the Article 6(1)(e) legal basis under UK GDPR – “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 processing activities described within this agreement can be deemed to be in the public interest because processing may result in improvements in the quality of care for people undergoing Percutaneous Coronary Interventions. NHS England rely on Article 9(2)(h) of the GDPR as the legal basis for processing. "Processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services on the basis of Union or Member State law or pursuant to contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3". NHS England are responsible for provision of health and social care, and management of systems and compliance. (Academic, internal NHS transfer)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2020-03-20 — 2021-03-19 2021.04 — 2023.11.

Access method: One-Off

Data-controller type: HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), NHS ENGLAND (QUARRY HOUSE), NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

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

Objectives:

The Healthcare Quality Improvement Partnership (HQIP) has commissioned, on behalf of NHS England as part of the National Clinical Audit and Patient Outcomes Programme (NACPOP), six national cardiovascular audits which are managed by the National Institute for Cardiovascular Outcomes Research (NICOR) based within Barts Health NHS Trust.
• Myocardial Ischaemia National Audit Project (MINAP)
• National Heart Failure Audit (NHFA)
• National Congenital Heart Disease Audit
• National Adult Cardiac Surgery Audit
• National Cardiac Rhythm Management Audit
• National Adult Percutaneous Interventions Audit (NAPCI)

National Institute of Cardiovascular Outcomes Research (NICOR) conducts the national cardiac audit programme (NCAP) of which NAPCI is one of six domains. NICOR is hosted by Barts Health NHS Foundation Trust, and the Trust also holds funding for NCAP, as such Barts Health NHS Foundation Trust process the data for the purposes described in this agreement. However, as NICOR monitor’s all hospitals (including Barts Health’s) performance through national clinical audit this work has to be kept at an arms’ length from Barts Health.

The six audits, collectively termed the National Cardiac Audit Programme (NCAP) audits, are based on prospectively collected, patient-level data on patients in all NHS providers in England and Wales. NCAP is managed by NICOR, and their funding contract for the National Cardiac Audit Programme runs until June 2022.

NCAP collects data from two domains that are concerned with particular disease processes (heart attacks and heart failure) and four that cover delivery of specific services (procedures for patients with congenital heart disease, percutaneous coronary intervention, cardiac surgery and the management of cardiac rhythm abnormalities). The aim of these NCAP audits is to measure and report delivery of care against defined guidance standards and to enable the improvement of the quality of care and outcomes of patients with a range of cardiac conditions.

The National Audit for Percutaneous Coronary Interventions (NAPCI) is one of the six focal areas for audit within the NCAP that contains information about the care provided to patients who are admitted to hospital for percutaneous coronary interventions (PCIs). The audit's findings have been made public for many years through its annual reports published on the NICOR website.

NAPCI aims to capture data on clinical indicators which have a proven link to improved outcomes, and to encourage the increased use of clinically recommended diagnostic tools, disease modifying interventions/treatments and referral pathways. The NAPCI aspires to include complete information about the care of every patient admitted to hospital with coronary disease requiring percutaneous coronary intervention / angioplasty. By so doing there can be greater confidence in the reliability of subsequent analyses and in the validity of comparisons between participating hospitals. The audit must publish case ascertainment at Trust and hospital level to ensure it is capturing all relevant cases. This aspect of data quality is fed back to participating centres, to NHS England and regulatory bodies.

The data supplied by NHS Digital will be used to produce participation tables for audit purposes and to determine whether hospitals are fully participating in the audit. Aggregate HES APC data at hospital level will be compared to the number of records submitted to the audit by each Trust and Health Board, to measure case ascertainment. The hospital level HES tabulation data requested is the minimum level of data required for case ascertainment purposes. Barts Health NHS Trust only receive data concerning number of patients who received care by individual hospitals.

For the purpose of this report NICOR cannot allow for any small numbers to be suppressed, because otherwise when comparing HES figures with the number of records that hospitals have submitted to the audit, NICOR’S numbers will be inaccurate. If 300 cells are suppressed (with each suppressed cell representing up to 7) that is up to 2100 admissions excluded from the total, which is quite a significant amount. The data with small numbers not suppressed will allow the comparison of the number of cases a hospital has submitted to the audit with the actual number the hospital has treated as recorded in the HES data. Small number suppression will be applied to the audit outputs.

With appropriate IG and other permissions the NAPCI data is also used for research purposes, to investigate further the causes, treatment and management of heart disease requiring PCI.

To address the GDPR principle of Data Minimisation, NICOR request that the data received is restricted to patients who have been discharged from hospital (with hospital code) with a diagnosis of percutaneous coronary intervention (PCI)/angioplasty.

NHS England is responsible for determining which projects/topics are included as part of the NCAPOP. HQIP, as commissioner of the NCAPOP, is responsible for project specification development, procurement and extension activities, contract management and authorising data sharing requests. NHS England, as a funder of the NCAPOP, participates within specification development, procurement and project extension activities and authorises the publication of project outputs.

NHS England is involved with developing the scope and purpose of the NCAPOP projects through participation within specification development activities and may authorise (as chair of the specification development meetings) the final project specifications. These specifications set out the purpose of the project, the patient groups and clinical services to evaluate and the types of data to collect. NHS England are a representative upon the HQIP Data access request group which authorises data sharing applications from third parties.

Therefore, both HQIP and NHS England are Data Controllers. GDPR Legal Basis for data dissemination for HQIP is the General Data Protection Regulation Article 6(1)(e) and Article 9(2)(i) and for NHS England is the General Data Protection Regulation Article 6(1)(e) and Article 9(2)(h). The processing activities described within this agreement can be deemed to be in the public interest because processing may result in improvements in the quality of care for people being treated for people undergoing Percutaneous Coronary Interventions.

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).

Yielded Benefits:

The NAPCI audit has allowed NICOR to identify centres that are consistently falling below national benchmarks. Letter are sent from the British Cardiovasular Intervention Society (BCIS) clinical standards group to any centre whose total PCI numbers fall below 200 for 3 successive years. Regional commissioners may need to discuss with local providers. The audit has indicated that a focus is needed to reverse the deterioration in ambulance response times for patients with ST-elevation myocardial infarction. In addition, although the overall Door-To-Balloon times are good, there is still considerable variation between hospitals. Improvement in the slower centres is therefore also needed to improve patient care. These centres have been advised to contact hospitals that perform well to see what lessons can be learned. This report highlighted that it is important that many centres improve the rapidity of Non-ST-Myocardial Infarction (NSTEMI) patient access to invasive cardiology investigation and treatment for patients. As a result of the NAPCI reports there has been a substantial shift in practice to the use of radial access for PCI of which the UK can be proud. The few operators who have yet to change their practice have been be encouraged to make use of the educational resources available in the UK and, given the high percentages of the large majority, are very likely to have colleagues who can help support their shift in practice. NICOR have advised that trusts should introduce day case procedures for patients undergoing elective PCI, hospitals should seek to modify their pathways and ward structures to reduce unnecessary overnight stays for patients. Based on the findings of the NAPCI report, NICOR have advised that the hospitals not meeting the standards for the use of drug-eluting stents during primary PCI should review their cases to see where improvements can be made.

Expected Benefits:

The primary benefit of this work is in the calculation (and presentation) of case ascertainment rates for participating centres.

Case ascertainment is an important aspect of data quality and provides an estimate as to what proportion of patients with the clinical condition under study are submitted to the audit. The publication of case ascertainment rates encourages participating centres to include as many patients as possible. This minimises the risk of hospitals͚ 'cherry picking' patients for the audit and enables the audit to measure like with like and provide national comparative data.

A secondary benefit is in an understanding of the coding practices of participating hospitals with respect to similar cardiac conditions.

Improved data quality: Publication and comparison of case ascertainment will identify poorer performing hospitals and encourage such hospitals to improve the quality of the data they submit. At the same time higher performing hospitals can receive credit.

Confidence in the implications (and generalisability) of national audit: Access to HES trusts level data is crucial for establishing case ascertainment and ensuring the quality of patient care and patient outcomes is being monitored for all patients. Case ascertainment is key to measuring equity of access and care. This will lead to:
(a) Improvements in patient care, as the NCAP supports both quality assurance and quality improvement initiatives both locally and nationally;
(b) Understanding differences in hospital coding practices: Variation in cases ascertainment may also point to differences in HES coding practices between hospitals.

Outputs:

NICOR must deliver to HQIP and NHS England the NCAP Annual Report - as a contracted deliverable. Following formal sign off by NHSE and HQIP the NCAP 2021 Annual Report and the NAPCI Summary Report will be published. After which there will be some individual discussions and presentations of the report e.g. at conferences. These presentations may not necessarily include the HES tabulation data, but the publication and any presentations would be based on the NCAP Annual Report (which uses HES tabulation data for case ascertainment purposes).

These annual reports will be distributed electronically to Trust chief executives, clinicians, British Cardiovascular Society and to other stakeholders. These reports are also publicly available online on the HQIP on its webpages on the NICOR website: https://www.nicor.org.uk/national-cardiac-audit-programme/

Both the NCAP 2021 Annual Report and the domain-specific NAPCI Summary Annual Report will be distributed electronically to Trust chief executives, clinicians, British Cardiovascular Society and to other stakeholders. These reports are also publicly available online on the HQIP webpages on the NICOR website: https://www.nicor.org.uk/national-cardiac-audit-programme/.

Analyses from NAPCI and NCAP Reports appear in Quality Accounts and are made available to CQC visiting teams.

The NAPCI audit publishes case ascertainment and clinical practice analysis at Trust and hospital level, and feeds back on this to NHS England and the Care Quality Commission. The hospital level HES tabulation data requested is the minimum level of data required for case ascertainment purposes, which basically means that it’s a check for verifying the number of patients submitted to NICOR with the number of patients’ coded by the hospitals for HES. The data received is number of patients who received care by individual hospitals (with a hospital code).

The NAPCI data is used in a number of ways to drive improvement in PCI (angioplasty) services and patient outcomes. Primarily, data is fed back to individual hospitals to report on their clinical practice and outcomes over time.

NICOR recently published the NAPCI 2020 Annual Report (released December 2020) which presents case ascertainment rates for participating Trusts in Hospital Episode Statistics (HES) tabulated data provided by NHS Digital in England to the number of cases submitted to NAPCI.

The audit provides participation rates, and hospital level data, to organisations such as the Care Quality Commission's Quality and Risk Profiles, the NHS Choices website and data.gov.uk. Case Ascertainment is also presented within annual public reports.

Additionally NICOR are mandated by HQIP to maintain and improve 'Data Quality'. Markers of data quality include:
• Timeliness of reporting - how soon after, and how often during, the relevant period of reporting are reports made available?
• Accuracy/validity of submitted data - are the data submitted to the audit a true reflection of the care provided?
• Data completeness - for each case, how many of the data fields are completed?
• Case ascertainment - what proportion of the entire 'population' of patients with the clinical condition of interest is submitted to the National Audit?
Following receipt of previous HES data, NAPCI has been able to report on this last aspect of data quality - case ascertainment.

Processing:

There will be no flow of data into NHS Digital. NHS Digital will flow tabulated HES APC data to Bart’s Health NHS Trust. There will be no subsequent flow of data.

All who will be processing NHS Digital data are substantive employees of Bart's Health NHS Trust.

The NAPCI audit aims to drive up the quality of the diagnosis, treatment and management of PCI by collecting, analysing and disseminating data, measuring improvements in participation in the NAPCI; eventually to improve mortality and morbidity outcomes for patients receiving PCI procedures.

The HES tabulation data will be used to determine whether hospitals are fully participating in the audit. Aggregate HES data at Trust (and component hospital) level will be compared to the number of records submitted to the national audit and expressed (in tabular format) as case ascertainment rates for participating centres. This is a key quality indicator. The NAPCI audit publishes case ascertainment and clinical practice analysis at Trust and hospital level and provides feedback on this to NHS England and the Care Quality Commission. For the purpose of the NAPCI Annual Report, NICOR cannot allow for any small numbers to be suppressed.

The tabulated HES data is stored on the NICOR shared drive only accessible to NICOR staff. Once the reports have been published the data is destroyed.

To protect patient confidentiality, when presenting results calculated from HES data, outputs will contain only aggregate level data with small numbers suppressed in line with HES analysis guide. When publishing HES data, it must be ensured that cell values from 1 to 7 are suppressed at a local level to prevent possible identification of individuals from small counts within the table. Zeros (0) do not need to be suppressed. All other counts will be rounded to the nearest 5.

The data from NHS Digital will not be used for any other purpose other than that outlined in this agreement. It will also not be linked to any other data sets. There will be no attempt to re-identify the data. Onward sharing of data which is not aggregated with small number suppression is not permitted.

Upon instruction from NHS Digital, a Certificate of Data Destruction must be completed by the Data Controller confirming the data has been appropriately disposed of following use.

End of life care – 3 or more emergency admissions in last 90 days of life — DARS-NIC-180255-K0B3N

Type of data: Aggregated, Pseudonymised

Opt outs honoured: No (Internal flow of aggregate tables only)

Legal basis: Internal flow of aggregate tables only

Purposes: To produce an indicator for the CCG Improvement and Assessment Framework (CCG IAF). (internal NHS transfer)

Sensitive:

When:DSA runs 2018-04-30 — No 2023.04 — 2023.11.

Access method:

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

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

Objectives:

At CCG, STP and England level, for 2016: · Count of individuals (unique HES identifier) recorded in hospital admissions data (HES) with 3 or more emergency hospital admissions starting during the last 90 days of life. · The total number of deaths excluding neo-natal deaths We require these outputs by the end of April 2018.

IGARD amendments Sept 2019; include NHSE as a data controller, Plics timescales/sharing Plics data with NHSE, add PROCODE field in HESMMES, Theatres Data set Mandatory request and CSDS disclosure rules — DARS-NIC-15814-C6W9R

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

Legal basis: Health and Social Care Act 2012, 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), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, This data sharing agreement is not an intended legal document, it is a reference document to evidence data flows. The agreement will not be signed as a legal document. It will instead be signed by internal NHS England colleagues. NHS England (NHSE) is a statutory body and its statutory functions, duties and powers reserved to the Board are to ‘ensure compliance with the concurrent duty, held with the Secretary of State for Health, to continue the promotion in England of a comprehensive health service’. NHSE’s supporting statutory duties are set out in the NHS Act 2006, S13 E, Health and Social Care Act 2012 s23 and require NHSE to secure continuous improvement in the quality of health and public health services provided to individuals. NHSE leads the National Health Service (NHS) in England. NHSE are responsible for the budget, planning, delivery and day-to-day operation of the commissioning side of the NHS in England as set out in the Health and Social Care Act 2012. NHSE has responsibility for a wide range of purposes and hold Statutory Duties, including commissioning specialised services, paying for primary care, public health services, offender healthcare and specific services for the armed forces. NHSE is also legally required to undertake a range of non-commissioning functions, including oversight of Integrated Care Boards (ICBs) and new care models assurance, reviewing major service changes, development of policy and financial allocations. One of the key changes under the new Health and Social Care bill is the creation of 42 Integrated Care Boards (ICB) constituted of new legal entities which replace clinical commissioning groups (CCGs). Concurrent with this legal change, the Sustainability and Transformation Partnerships (STPs) are being replaced by Integrated Care Systems (ICS). NHSE have a separate Data Sharing Agreement (DSA) with NHS England which outlines its detailed statutory duties in which NHS England disseminated datasets are used for. The areas can be summarised as the provision of an ad-hoc and routine analysis and reporting service to support the work of NHSE in the following responsibility areas: 1. Proactive management of commissioned services; including contract management, performance management, needs and inequalities analysis, benchmarking, service review and development, planning, budgets and allocations and general commissioning assurance activities. 2. Analysis and reporting to support QIPP (Quality, Innovation, Productivity and Prevention) programme activities. 3. Data quality analysis and data quality management, to ensure data processing has been carried out effectively. 4. Advanced analytics to support evaluation of service transformation. NHSE’s uses of data sourced under this agreement will only be in accordance to its statutory duties and functions, any external sharing of data will comply with the respective disclosure control rules as outlined in the DSA. In summary NHSE’s core duties and functions relate to: NHS Act 2006 13 D Duty as to effectiveness, efficiency etc. The Board must exercise its functions effectively, efficiently and economically. (e.g. commissioning of health services - see below) 1H The National Health Service Commissioning Board and its general functions (1) There is to be a body corporate known as the National Health Service Commissioning Board (‘the Board’) (2) The Board is subject to the duty under section 1(1) concurrently with the Secretary of State except in relation to the part of the health service that is provided in pursuance of the public health functions of the Secretary of State or local authorities. (3) For the purpose of discharging that duty, the Board- (a) has the function of arranging for the provision of services for the purposes of the health service in England in accordance with this Act, and (b) must exercise the functions conferred on it by this Act in relation to clinical commissioning groups so as to secure that services are provided for those purposes in accordance with this Act. 13 G Duty as to reducing inequalities The Board must, in the exercise of its functions, have regard to the need to- (a)reduce inequalities between patients with respect to their ability to access health services, and (b)reduce inequalities between patients with respect to the outcomes achieved for them by the provision of health services (hence collecting ethnic origin). 13 K Duty to promote innovation (1) The Board must, in the exercise of its functions, promote innovation in the provision of health services (including innovation in the arrangements made for their provision). The above supporting the purposes stated in the Data Provision Notice (DPN): • inform new methods of pricing NHS services; • inform new approaches and other changes to the design of the currencies used to price NHS services; • inform the relationship between provider characteristics and cost; • help trusts to maximise use of their resources and improve efficiencies, as required by the provider licence; • identify the relationship between patient characteristics and cost; • support an approach to benchmarking for regulatory purposes. Article 6(1)(e) is being used as the General Data Protection Regulation (GDPR) legal basis for processing. NHSE is a public authority. The Data Protection Act 2018 s7(1)(a) defines ‘public bodies’ for the purpose of the GDPR as ‘a public authority as defined by the Freedom of Information (FOI) Act 2000’. The FOI Act 2000 Part 1, section 3 (1)(a)(i) specifies that a public authority means any body which is listed in Schedule 1. Schedule 1 of the FOI Act 2000 lists special health authorities as public authorities and NHSE is a statutory body under the Health and Social Care Act 2012. GDPR Article 9(2)(h) is also being relied upon: Processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services on the basis of Union or Member State law or pursuant to contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3. • The data are required for the purpose of commissioning. • The data required by the data controllers is the least intrusive to the data subject possible to be able to conduct their functions. • The data required for commissioning purposes is pseudonymised by NHS England to minimise the risk of identification. NHSE require access to the following data sets; • Hospital Episode Statistics (HES) • Mental Health Data Sets (Mental Health Minimum Data Set (MHMDS)) (Mental Health and Learning Disabilities Data Set (MHLDDS)) (Mental Health Services Data Set (MHSDS)) • Improving Access to Psychological Therapies (IAPT) • Secondary Uses Service Payment by Results (SUS PbR) • HES and SUS linkage • Patient Reported Outcome Measures (PROMS) • Diagnostic Imaging Data Set (DIDS) • Civil Registration Deaths (CRD)-HES linked data • Patient Level Information Costing System (PLICS) data for Acute, Mental Health and Community Services, Ambulance and IAPT providers • Cancer Waiting Times Data (CWT) • Emergency Care Data Set (ECDS) • Community Services Data Set (CSDS) • Spend Comparison Tool data (previously referred to as ‘PPIB’) as collected by NHSD under a mandatory request • Theatres data as collected by NHS England under a mandatory request The purposes for access are; (1) Licensing providers of NHS services in England (Part 3, Chapter 3 of the 2012 Act), in particular, ensuring that providers comply with the conditions of their license relating to continued provision of health care services for the purposes of the NHS. And, promoting the integration of care where this would improve the quality and efficacy of care and/or drive efficiencies (Part 3, Chapter 1 of the 2012 Act) This includes; The Costing Transformation Programme (CTP), was established to implement Patient Level Information Costing System (PLICS) across Acute, Mental Health, Ambulance, Community and IAPT providers. The programme entails: a. Introducing and implementing new standards for patient level costing; b. Developing and implementing one single national cost collection to replace current multiple collections; c. Establishing the minimum required standards for costing software and promoting its adoption; and d. Driving and encouraging sector support to adopt Patient Level Costing methodology and technology. Developing the Carter Programme (now productivity and improvement activities in the NHS) and the Model Hospital dashboard and metrics -a nationally available online information system, with a series of themed compartments which present key performance metrics for different areas across the hospital, community services, mental health services and ambulance services. Enabling providers to compare performance against their peers and national benchmarks and identify areas where they need to improve and develop products to help support service improvements and NHS operational productivity. Health Education England (HEE), NHS Resolution, UK Health Security Agency (UKHSA) and the National Institute for Health and Care Excellence (NICE) are added to the approved list of Arms Length Bodies (ALBs) who have access to data in the Model Hospital portal. They will access and use the data in accordance with the purposes and terms of use as applicable to other approved ALBs (which includes NHSE, Care Quality Commission (CQC), NHS England and Department of Health and Social Care (DHSC)). Developing the ‘Getting It Right First Time' programme (GIRFT) - supporting and offering expertise to the NHS and elsewhere on the provision of surgical and medical hospital services. The GIRFT programme develops hospital level data packages to help encourage the development of improvement plans for each hospital and develop products to help support service improvements within hospitals. A national recommendation report is developed. Hospitals are expected to monitor the implementation of their improvement plans using data shared on the Model Hospital dashboard. Request related to Circle data (independent provider of NHS services) and sharing of GIRFT data packs: There are number of combined services delivered partly by Nottingham University Hospital and partly by Circle (independent sector). In order to look at the entire services delivered to patients in Nottingham, GIRFT require information from both providers. The combined service are due to the following: -A private organisation (Circle) provide services in Nottingham University Hospital, which the private organisation tendered for and were awarded a contract. -The consultants who provide the service are employed either by Nottingham University Hospital or the private organisation (Circle). The private organisation (Circle) manages the services and submits data to SUS using their Organisation Data Service (ODS) code as the provider code. -Given that the services are combined with the same patients, GIRFT would like to share metric values calculated from HES data records against Nottingham University Hospital and Circle. Hence, GIRFT would like to share single data pack with both providers to help encourage the development of improvement plans and support service improvement within hospitals. Studying how a failing provider's activity could be re-directed to other hospitals. The National Clinical Improvement Programme (NCIP) is part of the Getting it Right First Time Programme (GIRFT). The objective of NCIP is to develop metrics for personal performance to individuals consultants in support of appraisal and useful information as a learning tool. Theatres data (Mandatory Request) Theatres data was released under an earlier version of DARS-NIC-15814-C6W9R. This data is now held and processed under DARS-NIC-213403-P3R8Q for the below described purposes: NCIP is a DHSC initiated Programme that is part of the wider Getting It Right First Time (GIRFT) programme. The NCIP will be a digital product that will present NHS consultants in England -surgeons, in the first instance -with pseudonymised information relating to their clinical activity that will enable them to analyse and compare their outcomes with national benchmarks. This information will support quality improvement activities, with the aim of delivering improved patient care. The request is for NHS England to establish and operate an information system for the collection and analysis of theatre data from between five and seven NHS Foundation Trusts (discovery sites) in support of the NCIP. The purpose of requesting NHS England to establish the NCIP Theatre Data Set Discovery Information System is to enable assessment of the potential of theatre data to enhance the attribution of surgical activity to consultants, as recorded in Hospital Episode Statistics (HES) Admitted Patient Care (APC) data, and to explore potential other uses of the data (e.g. unit-level productivity measurement) with a view to developing a national theatre data set. Inaccurate attribution of existing activity data to consultants is a risk to the success of NCIP. This data will be patient level data that is sourced from local theatre systems within NHS trusts. This information is necessary to enable data linkage to HES APC data at procedure level and for relevant activity data to be shared with the consultants concerned via the NCIP portal. The collection also identifies the surgeons and anaesthetists involved. There are no intended publications of the Theatre Data Set Discovery collection. (2) Developing, publishing and enforcing the national tariff (Part 3, Chapter 4 of the 2012 Act), which will include: NHSE has a statutory duty to publish the national tariff. In order to comply with the statutory duty, NHSE needs access to Casemix HES patient level data to facilitate the development, quality assurance and monitoring of the national tariff system policy. In particular the national tariff must specify: a. health care services which are or may be provided for the purposes of the NHS b. the method used for determining national price c. the national price of each of those services d. the method used for deciding whether to approve an agreement under section 124 and for determining an application under section 125 (local modifications of prices) e. the rules governing local variations to national prices and the rules governing local price setting arrangements where there is no national price (3) NHSE change their working pattern frequently as part of investigating future models/projects. NHSE uses HES and SUS PbR data to calculate the pricing analysis and improvement models. PROMS is also required for pricing analysis. PROMS will be used for future design of Impact Assessment works and efficiency measures in which NHSE will be able to assess the performance of trusts. Linked PROMS data will enable impact analysis of new outcome-based payment models for in hospital services and therefore will assist in the design and evaluation of suitability of partially outcome-based payment as a part of the national payment system. PROMS will also be used to support the new payment system for Urgent and Emergency Care as this payment system is envisaged to have a link to patient outcomes. Overseas visitor (OVS) to SUS PbR The addition of OVS field to the existing SUS PbR data feed is requested for use by various NHSE programmes/projects and in support of the discharge of NHSE’s statutory duties and functions as set out in the DSA. This includes for programmes such as Model Hospital (in for example the overseas visitor compartment), GIRFT (who want to add a little more context to some of the GIRFT reports) where a Trust is behind programme on a workstream, to assess if they can identify that they have inflated activity from for example Health Tourism. Presently, NHSE can make comments like ‘they’re near an airport’ but quantifying this would be far more accurate) and other NHSE programmes for the purposes of wider programmes specific to projects to overseas cost recovery. Outputs of the data will be used in accordance to the existing limitations of data use for the wider SUS PbR data NHSE already receives. (4) Preventing anti-competitive behaviour by providers and commissioners NHS Procurement, Patient Choice and Competition Regulations 2013, in particular (Part 3, Chapter 2 of the Act): Assessing activity in any given Local Health Economy to ensure that any competition in the health sector is fair and that it operates in the best interests of patients. Cancer Waiting Times data, NHSE and/or NHS programmes sponsored by NHSE may process Cancer Waiting Times data to: o Provide performance insights for all trusts o Conduct analysis of individual trusts performance against each indicator down to the individual tumour or treatment type; and o Develop performance management information that will guide conversations with individual trusts as required. Performance data may be shared with trusts and will form part of the performance report to relevant committees. This is in the form of high-level aggregate activity data which is at trust level. It is provided in the form of a report for purposes of meeting the legal requirements related to competition which is a statutory duty of NHSE re preventing anti-competitive behaviour. No pseudo or record level data is provided all data is aggregated. Under section 79 of the Health and Social Care Act 2012 (Part 3, Chapter 2), NHSE has a duty to provide advice to the Competition and Markets Authority (CMA) on the benefits of a proposed merger. Transactions involving trusts are subject to a regulatory framework designed to ensure that proposed transactions work well for patients. This has two main components: competition review of mergers by the CMA and risk assessment of transactions by NHSE. This is to ensure the proposals serve the best interests of patients, from both good governance and competition perspectives. NHSE works closely with trusts contemplating a transaction to help them navigate the regulatory issues, including the CMA’s framework for mergers. NHSE can help trusts identify potential competition concerns at an early stage and engage with the CMA to determine if and when the CMA would want to review a transaction. This helps the providers plan their transaction, identify risks sufficiently early saving time and money for themselves and the wider regulatory system. NHSE seeks to work with the CMA and share its analysis of HES data with them and with those trusts that are considering or being considered for merger. (5) NHSE will share the analysis and underlying data back with the trusts about whom the data pertains. NHSE will notify NHS England of each trust as and when a merger is being risk assessed by NHSE. Any such access/sharing of data would only take place where the provider has an existing DSA for HES data in place with NHS England. Before any access/sharing of analysis and data with trusts takes place, NHSE will ensure that suitable controls are in place by reviewing the trusts security arrangements and entering into a DSA such that the HES data is used by the Trust solely in line with the purposes set out within the agreement. (6) NHSE requires the HES Continuous Inpatient (CIP) spell as a metric calculation and monthly IAPT from NHS England and wish to use this as part of NHSE’s remit in developing the Single Oversight Framework (SOF) for trusts. NHSE are standardising their methodology in SOF to calculate re-admission metric as per national definition, which is to calculate readmissions from Continuous Inpatient Spells. The purpose of the SOF is to help identify where providers may benefit from, or require, improvement support, to meet the standards required of them in a safe and sustainable way. It sets out how NHSE identify providers potential support needs and determines the way they work with each provider to ensure appropriate support is made available where required. There are a number of NHS England data sets used to develop metrics in the SOF, this is an additional metric to help measure Emergency readmissions within 30 days of discharge from hospital. Emergency Care Dataset (ECDS) NHSE have previously received daily reports from providers which included a number of items which could be calculated from the ECDS. This meant that providers were submitting the same information twice leading to data provision burden on providers. The ECDS feed from NHS England has replaced the daily feeds given by the providers. NHSE and/or NHS Programmes within NHSE use the ECDS data to support delivery of their statutory functions and support direct improvement and or oversight of trusts. A likely programme using the data will be winter/resilience planning. NHSE will process ECDS for the purpose of the delivery of Lord Carter programme/report looking at NHS Operational productivity as well as meeting key requirements in the NHS Long Term Plan. This data will be used to develop metrics in the Model Hospital and for GIRFT and wider NHS efficiency and productivity programmes in delivery of all our statutory functions as outlined above. NHSE requires access to HES, SUS PbR, HES and SUS linked, PROMS, DIDS and Mental Health linked data collected over a number of years by NHS England to: (7) Ensuring that NHS trusts comply with their duty under section 26 of the NHS Act 2006 to exercise their functions efficiently, economically and effectively, including: Supporting and developing the indicators in the Single Oversight Framework which are used to monitor the performance of Trusts. Indicators from HES include, long average lengths of stay, high new to follow-up ratios and long waits at A&E, early identification of any problems to help NHSE to highlight these issues with clinical and management staff in Trusts, and help to avert poor outcomes. Supporting other work programmes including activity dashboards such as Systems Economics Dashboard, A&E, HES browser. Other outputs are research, developmental work, statistical analyses in order to help offer support to providers. Ad hoc analyses carried out, would typically involve data sets such as HES, Mental health data and SUS PbR. NHSE have engaged the Royal National Orthopaedic Hospital NHS Trust (RNOH) as a data processor to develop and expand the Getting it Right First Time (GIRFT) Programme, which is a programme to improve the productivity, efficiency and quality of care of NHS providers. Community Services Dataset (CSDS) is required for the purposes of the Carter programme (productivity and improvement programmes), GIRFT and development of metrics for community services Model Hospital compartments. Data requested is pseudonymised patient level and a monthly flow of data is required (after the bulk load of all data from when CSDS was collected). This data will be used to develop metrics in the Model Hospital and for GIRFT and wider NHS efficiency and productivity programmes. The CSDS will be used in accordance with discharging relevant statutory duties as set out in this agreement. Improving Access to Psychological Therapies (IAPT) activity data is requested for use by various NHSE programmes/projects and to support the discharge of relevant statutory duties and functions as set out in this DSA. This includes for programmes such as Model Hospital (specifically development of an IAPT compartment), the pricing team to include PLICS portal/dashboard, costing transformation programme, single oversight framework and use of data for the GIRFT programme (e.g. in order to identify outcomes and measures around service improvement). (Agency/Public Body, internal NHS transfer)

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

When:DSA runs 2019-12-16 — 2020-03-31 2017.06 — 2023.11.

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

Data-controller type: MONITOR, NHS ENGLAND LONDON (SKIPTON HOUSE), NHS TRUST DEVELOPMENT AUTHORITY, NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Critical Care
  2. Hospital Episode Statistics Outpatients
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Accident and Emergency
  5. Bespoke Monthly Extract : SUS PbR OP
  6. Bespoke Monthly Extract : SUS PbR A&E
  7. Bespoke Monthly Extract : SUS PbR APC Episodes
  8. Bespoke Monthly Extract : SUS PbR APC Spells
  9. Bespoke Monthly Extract : SUS PbR Critical Care
  10. Standard Monthly Extract : SUS PbR OP
  11. Standard Monthly Extract : SUS PbR APC Spells
  12. Standard Monthly Extract : SUS PbR APC Episodes
  13. Standard Monthly Extract : SUS PbR A&E
  14. Patient Level Costing data (PLICS)
  15. Diagnostic Imaging Dataset
  16. Patient Reported Outcome Measures (Linkable to HES)
  17. Mental Health Services Data Set
  18. Bridge file: Hospital Episode Statistics to Diagnostic Imaging Dataset
  19. Standard Monthly Extract : SUS PbR Critical Care
  20. Civil Registration (Deaths) - Secondary Care Cut
  21. Secondary Uses Service Payment By Results Accident & Emergency
  22. Secondary Uses Service Payment By Results Episodes
  23. Secondary Uses Service Payment By Results Outpatients
  24. Secondary Uses Service Payment By Results Spells
  25. Civil Registration - Deaths
  26. HES:Civil Registration (Deaths) bridge
  27. Community Services Data Set
  28. Mental Health and Learning Disabilities Data Set
  29. Mental Health Minimum Dataset
  30. Standard Monthly Extract : SUS PbR Readmissions
  31. National Cancer Waiting Times Monitoring DataSet (CWT)
  32. NCIP Theatre Data Set Discovery Project
  33. Emergency Care Data Set (ECDS)
  34. Patient Level Costing Acute Data Set HES-APC (NHSI)
  35. Patient Level Costing Acute Data Set HES-OP (NHSI)
  36. Patient Level Costing Acute Data Set HES-AE (NHSI)
  37. NCIP Theatre Data Set Discovery Project Bridging File
  38. Bespoke Monthly Extract : SUS PbR Readmissions
  39. Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set
  40. Improving Access to Psychological Therapies Data Set
  41. Mental Health Minimum Data Set
  42. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
  43. Secondary Uses Service Payment By Results Accident & Emergency
  44. HES-ID to MPS-ID HES Accident and Emergency
  45. HES-ID to MPS-ID HES Admitted Patient Care
  46. HES-ID to MPS-ID HES Outpatients
  47. Improving Access to Psychological Therapies Data Set_v1.5
  48. Linked-Patient Level Costing Integrated Data Set (Linked-PLCINTDS)_NHSI
  49. Patient Level Costing Ambulance Data (NHSI)
  50. Patient Level Costing Early Implementers Data Set - Linked-PLCEIDS (NHSI)
  51. Civil Registrations of Death - Secondary Care Cut
  52. Community Services Data Set (CSDS)
  53. Diagnostic Imaging Data Set (DID)
  54. Hospital Episode Statistics Accident and Emergency (HES A and E)
  55. Hospital Episode Statistics Admitted Patient Care (HES APC)
  56. Hospital Episode Statistics Critical Care (HES Critical Care)
  57. Hospital Episode Statistics Outpatients (HES OP)
  58. Improving Access to Psychological Therapies (IAPT) v1.5
  59. Mental Health Minimum Data Set (MHMDS)
  60. Mental Health Services Data Set (MHSDS)
  61. Improving Access to Psychological Therapies (IAPT) v2
  62. Patient Level Costing Early Implementers Further Services Data Set - PLCEIFSDS (NHSI)

Objectives:

This is for the purpose of fulfilling Monitor’s statutory duties. To do this, Monitor requires access to HES, SUS PbR, PROMS, and Mental Health linked data collected over a number of years by NHS Digital to fulfil aspects of Monitor’s role prescribed under the Health and Social Care Act 2012 (the “2012 Act”). Specifically:

- Licensing providers of NHS services in England (Part 3, Chapter 3 of the 2012 Act), in particular, ensuring that providers comply with the conditions of their license relating to continued provision of health care services for the purposes of the NHS. This includes;

****Update Jan 17

• Developing the Carter Programme and the Model Hospital dashboard and metrics – a nationally available online information system, with a series of themed compartments which present key performance metrics for different area across the hospital, enabling providers to compare performance against their peers and national benchmarks, and identify areas where they need to improve.

• Developing ‘The Getting It Right First Time Programme’ (GIRFT) - supporting and offering expertise to the NHS and elsewhere on the provision of surgical and medical hospital services. The GIRFT programme develops hospital level data packages to help encourage the development of improvement plans for each hospital. A national recommendation report is developed. Hospitals are expected to monitor the implementation of their improvement plans using data published on the ‘Model Hospital’ dashboard.

*******
• Studying how a failing provider's activity could be re-directed to other hospitals.


- Developing, publishing and enforcing the national tariff (Part 3, Chapter 4 of the 2012 Act), which will include:
• Investigating the effects of potential tariff changes on Local Health Economies
• Developing new reimbursement currencies
• Analysing and validating the national priced payment by results (“PbR”) activity for any given provider

- Promoting the integration of care where this would improve the quality and efficacy of care and/or drive efficiencies (Part3, Chapter 1 of the 2012 Act)

- Preventing anti-competitive behaviour by providers and commissioners NHS Procurement, Patient Choice and Competition Regulations 2013, in particular (Part 3, Chapter 2 of the Act):
• assessing activity in any given Local Health Economy to ensure that any competition in the health sector is fair and that it operates in the best interests of patients
• Providing advice and guidance to NHS organisations who are considering mergers

- Developing modules of analyses and understanding relationships between health care provision and acute secondary services across any given Local Health Economies (Part3, Chapter 1 of the 2012 Act).

Monitor change their working pattern frequently as part of investigating future models/projects. Previously Monitor used the HES and SUS PbR data to calculate the pricing analysis and improvements made to the model and analysis therefore means that PROMS is now required for pricing. PROMS will also be used for future design of Impact Assessment works and efficiency measures in which Monitor will be able to have a wider range of data in order to assess the performance of trusts. Having the linked PROMS would enable impact analysis of new outcome based payment models for in hospital services and therefore would assist in the design and evaluation of suitability of partially outcome based payment as a part of the national payment system. PROMS will also be used to support the new payment system for Urgent and Emergency Care as this payment system is envisaged to have a link to patient outcomes.

Having Mental Health data of a sensitive nature will enable Monitor to understand the relationship between mental health care and acute secondary services across all Local Health Economies (LHE) in England.

Casemix HES:
Under the Health and Social Care Act 2012, Monitor has a statutory duty to publish the national tariff, which is the system for NHS services. The National Tariff is produced in conjunction with NHS England. In order to comply with the statutory duty, Monitor needs access to Casemix HES patient level data to facilitate the development, quality assurance and monitoring of the national tariff system Policy.
In particular the national tariff must specify:
(a) health care services which are or may be provided for the purposes of the NHS,
(b) the method used for determining national prices
(c) the national price of each of those services
(d) the method used for deciding whether to approve an agreement under section 124 and for determining an application under section 125 (local modifications of prices).
(e) the rules governing local variations to national prices and the rules governing local price setting arrangements where there is no national price

PLICS:

NHS Improvement/Monitor’s Costing Transformation Programme (CTP), was established to implement PLICS across Acute, Mental Health, Ambulance and Community providers and. The programme entails:
• Introducing and implementing new standards for patient level costing;
• Developing and implementing one single national cost collection to replace current multiple collections;
• Establishing the minimum required standards for costing software and promoting its adoption; and
• Driving and encouraging sector support to adopt Patient Level Costing methodology and technology.

NHS Improvement (NHSI) was launched on 1 April 2016 and is the operational name for the organisation that brings together Monitor and the NHS Trust Development Authority (“TDA” plus a number of other teams). NHS Improvement operates as a single organisation, with a joint board and single leadership and operating model although the TDA and Monitor continue to exist as distinct legal entities with their continuing statutory functions, legal powers and staff.

Yielded Benefits:

The 2016 Pilot Collection of Patient Level Cost data at six acute Trusts proved that the draft patient level costing standards can be successfully implemented by NHS providers and that the process for data collection by NHS Digital for onward transmission to NHS Improvement can be completed successfully. This pilot provided a proof of concept for the methodology and process. A prototype portal to enable the pilot Trusts to use the data collected to benchmark costs is under development in partnership with those Trusts and will be ready by the end of March 2017 at which point the Trusts are ready to start to engage clinicians with the data • The information gathered from the PLICS programme will be used to enable NHS Improvement to perform its pricing and licensing functions under the HSCA more effectively. It will: • inform new methods of pricing NHS services; • inform new approaches and other changes to the design of the currencies used to price NHS services; • inform the relationship between provider characteristics and cost; • help trusts to maximise use of their resources and improve efficiencies, as required by the provider licence; • identify the relationship between patient characteristics and cost; and support an approach to benchmarking for regulatory purposes • The alignment of PLICS outputs with the Operational Productivity programme is key to benefits realisation. The data collected has already allowed NHS Improvement to link individual patient episode costs across different care settings. This is a key enabler for the development of new models of care and sustainable delivery of services. While it is too early to identify specific benefits arising from benchmarking across Trusts linked to the PLICS data collected in 2016 (and there will be limitations in the quality of the data collected in that pilot), case study evidence continues to confirm the value of patient level costs within each Trust for identifying efficiencies and service improvements, such that NHS Improvement continue to be confident that rolling out a consistent patient level methodology across all providers can derive significant benefits. NHS Improvement know of pilot sites which use the PLICS data created in 2016 to improve decision making for A&E; NHS Improvement have also received feedback that PLICS data provides more rapid outputs for operational decisions at a Trust level. This general picture was confirmed by the recent “mid-point review” of the Costing Transformation Programme, including senior stakeholders across Arm’s Length Bodies, including representatives of the Operational Efficiency Programme, GIRFT, along with representatives of providers and clinicians, continues to support the move to PLICS • Using linked PLICS minimises the burden on providers. Providers submit cost data with identifiers, which reduces extract sizes and simplifies the collection, reducing time and manpower required to extract and report patient level data. There is also a single version of truth for activity data, different collections define and count activity differently making it difficult to consolidate information from different sources for providers • It is also worth noting that a subset of Trusts will provide a representative sample of HRGs, to allow PLICS data collected to inform the development of the next tariff; one of the benefits of the move to PLICS being better quality cost data to inform NHSI’s Pricing functions

Expected Benefits:

Having access to NHS Digital data would enable Monitor to effectively fulfil its regulatory responsibilities and statutory obligations.

Examples of this include delivering a better contextual view of provider performance, providing assurance that providers of health care are meeting the terms of their license, prevention of anti-competitive behaviour by providers and commissioners.

Monitor are also working on the development of the national Tariff allowing providers of NHS care to be reimbursed for care provision according to the national tariff.

PROMS data will benefit healthcare by enabling a better more effective payment system which in turn would not just the users but all of the NHS.

Mental Health data will enable development of a consistent and systematic analysis on the relationship between mental health care and acute secondary services across all LHE in England. The outputs in Monitor’s Local Health Economy Intelligence data packs, will facilitate and build Monitor’s internal knowledge of the relationship between Mental Health and Physical Health care across each LHE in England. This will support regional teams to monitor their Trust, against a broader macro-economic context of their local health economy, and the dynamics at play between mental and physical health at a local level.

Casemix HES:
The National Tariff allows providers of NHS care to be reimbursed for care provision under the PBR Policy.

The information gathered from the PLICS is programme will be used to enable NHS Improvement to perform its pricing and licensing functions under the HSCA more effectively. It will:
• inform new methods of pricing NHS services;
• inform new approaches and other changes to the design of the currencies used to price NHS services;
• inform the relationship between provider characteristics and cost;
• help trusts to maximise use of their resources and improve efficiencies, as required by the provider licence;
• identify the relationship between patient characteristics and cost; and support an approach to benchmarking for regulatory purposes.

**Amendment Jan 2017**

The benefits that the CMH (and GIRFT programme as part of the MH works and portal that will host the dashboards) will bring to the NHS are the offerings of mechanisms via the MH dashboards that can measure a provider’s productivity and efficiency and help them to reduce unwarranted variation in productivity and ultimately save the NHS £5billion each year by 2020.

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Outputs:

Monitor is requesting permission to receive data without identifiers that will be queried, aggregated and combined in many different ways to support its objectives for processing above.
Some example outputs that will form part of those core functions are:

** Amendment update Jan 2017**
Developing the Carter Model Hospital and the GIRFT programme:
• Calculating metrics for the Model Hospital dashboard
• Calculating metrics for the hospital data packages and national recommendation reports, network or STP reports, ad hoc reports and peer-reviewed publications, under the following conditions:
o The hospital data packages will only be published to the hospital from which the data was originally sourced (therefore, we expect to show small numbers)
o National recommendation reports will only include aggregate data. No individual hospital will be named, and no small numbers will be shown.
o The ‘Model Hospital’ dashboard will identify individual hospitals, and small numbers will be supressed
o Network or STP reports, where data from more than one hospital are included and published to an audience that contains personnel from more than one NHS organisation, will identify individual hospitals, and small numbers will be supressed
o Ad hoc reports for NHS managers or clinicians (e.g. NHS England, NHS Improvement, Royal College of Surgeons, etc.) will identify individual hospitals, and small numbers will be supressed
o Articles in peer-reviewed publications will only include aggregate data. No individual hospital will be named, and no small numbers will be shown.

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- Reports on total tariff and activity by provider and commissioning body

- Referral patterns from GP practices to trusts

- Investigations of the effects of potential tariff changes on the health economy

- Modelling life-years-of-care

- Reporting activity by variable aggregations

- Taking enforcement action in relation to any non-compliance identified from analysis of the data

Some specific examples of outputs already produced, highlighting the range of analysis undertaken, and going some way to justify the need for such wide-reaching data, are:

December 2014
https://www.gov.uk/government/publications/making-local-health-economies-work-better-for-patients
This report summarises the findings of NHS England, Monitor and the NHS Trust Development Authority’s joint project to support 11 local health economies to develop clinically and financially sustainable 5-year strategic plans.

June 2015
https://www.gov.uk/government/publications/five-year-forward-view-time-to-deliver
This document looks at the progress made towards the ‘Five Year Forward View’, and sets out the next steps needed to be taken to achieve these shared ambitions. The paper starts a period of engagement with the NHS, patients and other partners on how to respond to the long-term challenges and close the health and wellbeing gap; the care and quality gap; and the funding and efficiency gap.

February 2016
https://www.gov.uk/government/consultations/nhs-national-tariff-payment-system-201617-a-consultation
This year’s national tariff proposals aim to give providers of NHS services the space to restore financial balance and support providers and commissioners to make ambitious longer term plans for their local health economies. These proposals will help providers and commissioners to work together to manage demand and deliver services more efficiently. This continues the development of the payment system for mental healthcare.

All outputs will be subject to small number suppression in line with the HES analysis guide. Monitor (and their Data Processors) will not supply record level data to any third party, and the data will not form part of any tool, product or analytical output which is made available on a commercial basis.

The Mental Health dataset will also generate informative slide(s) that capture the interactions of mental health patients with secondary acute services to provide contextual information within the LHE. It will be used as a module of analysis within Monitor’s LHE Intelligence Unit data packs that are used to support regional monitoring teams facilitate discussions with their trusts during the monitoring process, and possible the regional Tripartite (if issues identified that should be addressed by the LHE). The analytical outcomes/outputs of analysis will be shared with regional monitoring teams, and possible regional Tripartite (if outputs identify an issue that should be addressed in the LHE). (No underlying data will be shared with third parties or externally).

Casemix HES:
Within the period of the agreement only, Monitor will process the data to set National Tariff Prices for FY 2016/17 and subsequent years.
Monitor will hold the Intellectual Property Rights in the production of the National tariff and any derivative works from it.

Processing:

Data processing activities include:

**Amendment Jan 2017**

• Populating the Model Hospital dashboard and GIRFT programme ‘dashboard’ databases. Plans and reports identified above will be populated with metric values from the ‘dashboard’ database. Data may be extracted from the ‘dashboard’ database and provided to a third-party organisation who will then produce publications. In this case the following rules will apply:
o The third-party organisation must have a separate DSA (Data Sharing Agreement) with NHS Digital to handle HES/SUS data.
o The third-party organisation will be provided with aggregate data (i.e. no patient-level data will be provided) but the data may include unsuppressed small numbers. The third-party will have the necessary approvals in place to handle unsuppressed small numbers from NHS Digital before any access to data is granted.

One of the main points of the GIRFT work is to identify Trusts who are doing work at unsafe levels, so being able to show small numbers illustrates this more strongly than an <5 default code. Data would only be released with unsuppressed small numbers under a strict release protocol and only in data packs that are released to the Trust who submitted data to NHS Digital.

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Monitor staff will:
- Create aggregated summaries and reports of the data
- Analyse the data, and any derivatives works Monitor produce, for the purposes outlined in the previous section. Data will be accessed as data reports, aggregated summaries or within analysis tools
- Link the NHS Digital data with Casemix HES data and analyse them as part of Monitor’s role to develop the national tariff
• Linking will be done at patient level but this will only consist of pseudonymised data.

- Share the aggregated (data may be suppressed, take the form of indicators or gone through a cleansing process) data Monitor produce, and/or the results of Monitor’s analysis of the raw data with NHS England as part of Monitor’s joint role to develop the national tariff (NHSE have a separate license agreement with HSCIC for the raw data)

- Publish the following:

• results of Monitor’s analysis of the data;
• and data in aggregated and summary form

- Monitor may sub-contract work to sub-contractors working for and on behalf of Monitor. Their working arrangements will be the same as employed Monitor staff. They will sign up to the same Terms and Conditions as all permanent/temporary staff (as well as those confidentiality and data protection policies of their Agents). All data will be accessed via the same systems which Monitor staff access the data. Training and IG induction sessions are mandatory before anyone can access the data. Access to any IT and any data held therein is provided according to Monitor’s Access Control policy. Any NHS Digital data are only ever accessed by those who are fulfilling a purpose stated in the DSA and this is approved by the Information Governance Manager. When there is no longer a requirement for any sub-contractor to have access to the data, permissions are immediately revoked. Where there are any incidents or near misses the subcontractors are made aware of Monitors’ Incident and Reporting procedure.

- Data is processed to produce the required outputs and the development of SSIS packages to group data. Further processing is conducted in analytic and statistical applications

- Monitor (and their Data Processors) will not disseminate data In the format it is received, or any subset of the said data, to any third party not included in this agreement with the exception of the data to trusts via the GIRFT programme where data would only be shared when the necessary approvals and agreements are in place with NHS Digital.

- Aggregated and summarised data as well as the results of the analysis will ultimately be made public. Monitor will only publish analytical anonymous data

- Results of the analysis may be shared prior to publication with colleagues at other NHS organisations to inform future policy development

In addition, the Mental Health data will also be used to develop Monitor’s mental health modules of analysis within Monitor’s Local Health Economy Intelligence Unit data packs. The data will undergo analytical tests to assess the interactions between mental health and acute care (acute care activity by patients with mental health conditions across all local health economies in England). The data will not be linked to any other datasets.

Casemix HES:
The data will be used for research and analysis into pricing, including the impacts of pricing alternatives on stakeholders in the health sector.

Monitor needs to be able to share the Casemix HES and Grouper Output data with NHS England for the purpose of developing the National Tariff only.

The purpose of sharing the data with NHS England is to facilitate in the development of the national tariff. Both Monitor and NHS England have been mandated to produce this national tariff under the 2012 Act. Monitor will be sharing with NHS England the Casemix HES and Grouper Output data that have gone through a cleansing process including impact assessments used to determine the financial effects of these findings on the healthcare sector. This information Monitor will then share with NHS England who also conducts their own impact assessments. Separately, NHS England also receives the source Casemix/Grouper data from NHS Digital. The two sets of records are then used to determine and agree the national tariff.

For the purpose of the tariff production, Casemix HES data may be linked to patient level pseudonymised data specified in this agreement. For clarity, Casemix HES may be linked to HES MMES, SUS PbR, PROMS, and/or MHLLDS data at patient level. Other aggregated, non-identifiable datasets such as ODS, IMD, OPCS, ICD10 among others, will be analysed in combination with the Casemix HES data. The aggregated datasets will only be compared at a aggregated level and with small numbers suppressed in line with the HES analysis guide.

Monitor also requires the ability to share analysis derived from the Casemix HES data with NHS Digital.

Aggregated and summarized data as well as the results of the analysis will ultimately be made public. Monitor will only publish analytical anonymised data.

Access to the data will be restricted to people employed by or contracted to Monitor, NHS TDA, or NHS England.

Results of the analysis may be shared with colleagues at NHS Digital/DH/NHSE to inform future policy development.

Monitor will not use data for any commercial purpose.

PLICS:

PLICS data will be linked with HES data as provided in this agreement. This will be via the Episode number key.

To facilitate the development of a successful PLICS data collection system in the first instance, the following volunteer providers have agreed to participate in a pilot collection between July/August 2016 and September 2016.
• Buckinghamshire Healthcare NHS Trust
• Guy’s and St Thomas’ NHS Foundation Trust
• The Royal Free London NHS Foundation Trust
• The Royal Marsden NHS Foundation Trust
• The Royal Orthopaedic Hospital NHS Foundation Trust
• University Hospitals Birmingham NHS Foundation Trust
• Chelsea and Westminster NHS Foundation Trust

PLICs data shall be collected during July/August 2016 – September 2016 and will be used to test the ability of the system to successfully collect, collate, link, pseudonymise and validate data. Furthermore the pilot will look to establish clear mechanisms for safely transferring data to Monitor.

The processing activities here are limited solely to the pilot relating to the seven named Trusts.

PRECISION: PREvent ductal Carcinoma In Situ Invasive Overtreatment Now — DARS-NIC-727325-W4M7T

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

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

Purposes: No (Agency/Public Body)

Sensitive: Non-Sensitive

When:DSA runs 2023-10-10 — 2026-10-09

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON, NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

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

Expected Benefits:

The proposed study results are hoped will increase understanding of in situ breast cancer through characterising the different types of Ductal carcinoma in situ (DCIS) ,identifying markers molecular targets, and producing risk stratification models, all of which can be used in future research.

Ductal carcinoma in situ (DCIS) which means that some cells in the lining of the ducts of the breast tissue have started to turn into cancer cells. These cells are all contained inside the ducts. They have not started to spread into the surrounding breast tissue.

As a substantial proportion of breast cancer diagnoses are of in situ cancers, many patients could potentially benefit from the results of this project. This will be of great value by presenting methods of ascertaining those at higher risk of recurrence, progression, or contralateral incidence of breast cancer, allowing for tailored treatment accordingly and prevention of overtreatment.

Further, this study can provide feasible targets for future development of treatment as well as prophylaxis

Outputs:

For research articles, the consortium will follow ethical and data protection guidelines and respect the recommendations from the International Committee of Medical Journal Editors on Uniform Requirements for Manuscripts Submitted to Biomedical Journals, the Ethical Considerations in the Conduct and Reporting of Research, Authorship and Contributorship. The consortium will prioritise publications in open access journals to share as early and broadly as possible the research results with the community.

As a minimum requirement the consortium will follow the ‘green’ open access strategy and will ensure that the articles will be freely accessible at least after an embargo period defined by the publishers.

Processing:

No data will flow to NHS England for the purposes of this Agreement. The data requested under this agreement is for the invasive breast cancer cases which are sourced from NDRS. The Non-invasive data has been sourced from the SLOANE cohort data held by NHSE Screening team. Both sources of data are meeting different requirements of the study. The two cohorts will not be linked together as part of the research any attempts to do so would be a breach of this agreement.

NHS England will provide the relevant records from the HES, RTDS, SACT, CWT and Cancer Reg datasets to KCL The data will contain no direct identifying data items. The data will be pseudonymised and individuals cannot be reidentified through linkage with other data in the possession of the recipient. Researchers from KCL will analyse the data supplied under this agreement for the purposes described above.

The data will be stored on servers at AIMES.

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

Only Substantive employees of KCL are permitted to access pseudonymised data flowing under this agreement.

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

The data will not be linked with any other data.

There will be no requirement and no attempt to reidentify individuals.

NHS England Faster Data Program — DARS-NIC-616043-S9R4P

Type of data: Pseudonymised

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

Legal basis: Health and Social Care Act 2012 - s261(5)(d), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, In order to accelerate a reduction in elective waiting lists and waiting times, and to deliver the best quality care and outcomes for patients, the NHS needs timely, high quality data that can be appropriately accessed across the whole patient pathway (Primary Care through to Discharge). Commissioners of healthcare services need to plan and commission healthcare services in their local area through analysis of actual and projected use of those services. The Faster Data Flows (FDF) programme has been established to; provide more timely data to the system to support elective recovery, individual care coordination across Integrated Care Boards (ICBs) and to reduce the data reporting burden on providers. Through the implementation of automated daily data flows into a product that supports the ability to link data sets, provide tools back to providers and accountable organisations, the FDF programme will support commissioners in effective management of services. FDF will deliver this by implementing an automated daily flow of patient level data into the NHS National Data Platform (Foundry). The initial scope of work will focus on the collection of core patient identifiable data items for current inpatients, admissions, discharges and outpatient. Future scope to include data items covering: Theatre capacity data, Workforce allocation data, Cancelled operations, Outpatient Attendance data, Diagnostics activity, Referral data, e-Referral Service (ERS) data. Initially focusing on NHS Acute Trust with engagement starting with Community providers and ambitions to collect from Mental Health Trusts and Independent Sector Providers. This purpose of collecting this data is to support; Clinicians - to access information about individuals in their care that covers patient pathways and to show where care has been accessed in other organisations, to give the ability to make the right decisions and recommendations about their patient's individual care. Local and national commissioners/decision makers – with timely data about current services for planning, benchmarking, service improvement, response to crisis, and to comply with their statutory duties. The Faster Data Flows programme aims to deliver in the following areas in support of the principles and objectives of the NHS Data Strategy: • Monitoring and audit of health care provision and outcomes where such provision has been made; • Analysis of health care provision to ensure effective pathways, use of resources and capacity; • Establishing population health needs for strategic delivery planning; • Planning and administration of the provision made for health and health related care; • Identifying individuals with a high risk of suffering adverse consequences from infection, or whose immunisations are not up to date, with the aim of contacting them to offer an immunisation appointment; • Analysing demographic and health profiles for pandemic emergency planning • The Acute Patient Activity data will be used to support and accelerate recovery of elective waiting lists and waiting times as part of NHS England’s delivery plan for tackling the backlog of elective care. Existing flows are either not frequent or granular enough to support local planning and individual care co-ordination. Patient level data is required in the Data Services for Commissioners Regional Office (DSCRO) to apply the same pseudonymisation key in order to be able to link and combine this data with existing flows and deliver on the purpose outlined above. Sub-Licensing To achieve the stated aims the data, which will be disseminated via the Foundry platform, needs to be row level but will be pseudonymised. Consequently Sub-Licenses will be put in place with all organisations accessing the data. Sub-licensees will be limited to one of the following organisation types: • Integrated Care Boards • Acute Providers • Community Providers The purpose will be restricted to commissioning as per this section of this Data Sharing Agreement. The sub-licensees must keep the pseudonymised data separate from other identifiable data they hold. All sub-licensee organisations require approval from NHS England’s Senior Information Risk Owner. System users will be approved by the Senior Information Risk Owner or through delegated authority. Records of data sharing with sub-licensees must be maintained by the NHS England and made available to NHS Digital on request. NHS England's assessment of the purpose for processing this data has determined the legal basis for processing as 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 & Article 9(2)(h) - processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services on the basis of Union or Member State law or pursuant to contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3 of General Data Protection Regulation (GDPR). (Agency/Public Body, internal NHS transfer)

Sensitive: Sensitive

When:DSA runs 2022-11-18 — 2025-11-17

Access method: One-Off

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: Yes, No

Datasets:

  1. Acute Activity Data Set

Objectives:

In order to accelerate a reduction in elective waiting lists and waiting times, and to deliver the best quality care and outcomes for patients, the NHS needs timely, high quality data that can be appropriately accessed across the whole patient pathway (Primary Care through to Discharge). Commissioners of healthcare services need to plan and commission healthcare services in their local area through analysis of actual and projected use of those services.

The Faster Data Flows (FDF) programme has been established to; provide more timely data to the system to support elective recovery, individual care coordination across Integrated Care Boards (ICBs) and to reduce the data reporting burden on providers. Through the implementation of automated daily data flows into a product that supports the ability to link data sets, provide tools back to providers and accountable organisations, the FDF programme will support commissioners in effective management of services. FDF will deliver this by implementing an automated daily flow of patient level data into the NHS National Data Platform (Foundry). The initial scope of work will focus on the collection of core patient identifiable data items for current inpatients, admissions, discharges and outpatient. Future scope to include data items covering: Theatre capacity data, Workforce allocation data, Cancelled operations, Outpatient Attendance data, Diagnostics activity, Referral data, e-Referral Service (ERS) data. Initially focusing on NHS Acute Trust with engagement starting with Community providers and ambitions to collect from Mental Health Trusts and Independent Sector Providers.

This purpose of collecting this data is to support;

Clinicians - to access information about individuals in their care that covers patient pathways and to show where care has been accessed in other organisations, to give the ability to make the right decisions and recommendations about their patient's individual care.

Local and national commissioners/decision makers – with timely data about current services for planning, benchmarking, service improvement, response to crisis, and to comply with their statutory duties.

The Faster Data Flows programme aims to deliver in the following areas in support of the principles and objectives of the NHS Data Strategy:
• Monitoring and audit of health care provision and outcomes where such provision has been made;
• Analysis of health care provision to ensure effective pathways, use of resources and capacity;
• Establishing population health needs for strategic delivery planning;
• Planning and administration of the provision made for health and health related care;
• Identifying individuals with a high risk of suffering adverse consequences from infection, or whose immunisations are not up to date, with the aim of contacting them to offer an immunisation appointment;
• Analysing demographic and health profiles for pandemic emergency planning
• The Acute Patient Activity data will be used to support and accelerate recovery of elective waiting lists and waiting times as part of NHS England’s delivery plan for tackling the backlog of elective care.

Existing flows are either not frequent or granular enough to support local planning and individual care co-ordination. Patient level data is required in the Data Services for Commissioners Regional Office (DSCRO) to apply the same pseudonymisation key in order to be able to link and combine this data with existing flows and deliver on the purpose outlined above.

Sub-Licensing

To achieve the stated aims the data, which will be disseminated via the Foundry platform, needs to be row level but will be pseudonymised. Consequently Sub-Licenses will be put in place with all organisations accessing the data.

Sub-licensees will be limited to one of the following organisation types:
• Integrated Care Boards
• Acute Providers
• Community Providers

The purpose will be restricted to commissioning as per this section of this Data Sharing Agreement. The sub-licensees must keep the pseudonymised data separate from other identifiable data they hold.

All sub-licensee organisations require approval from NHS England’s Senior Information Risk Owner. System users will be approved by the Senior Information Risk Owner or through delegated authority. Records of data sharing with sub-licensees must be maintained by the NHS England and made available to NHS Digital on request.

NHS England's assessment of the purpose for processing this data has determined the legal basis for processing as 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 & Article 9(2)(h) - processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services on the basis of Union or Member State law or pursuant to contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3 of General Data Protection Regulation (GDPR).

Expected Benefits:

Benefits for Commissioners delivered by the Data Services for Commissioners collections through the FDF programme include:
• More timely access to data for Commissioners, allowing more rapid insight and response.
• Commissioner access to additional data items beyond those included in national disseminations. This allows Commissioners to respond to local need in a timely fashion.
• Access for Commissioners to Clinical Registries which link data across complex care pathways. The results provide access to accurate and comparative data so that care can be assessed against agreed clinical standards and used to improve patient outcomes and to support a variety of other initiatives.

This local flow with national standardisation will provide NHSE with more timely data to respond to pressures across the system at a national level.

For providers the main benefit of the programme, as well as supporting their ICB reporting requirements, will be realised by the reduction in reporting burden. The Faster Data Flows programme will collect activity data that metrics can be derived from to supply to SITREPS instead of manual processing. This will replace the need for providers to submit aggregate data items in various formats to multiple collection methods. The initial specifications covering outpatients, inpatients and discharges would replace the need for the submission of approx. 300 items that providers are required to collate and submit aggregately. As the programme progresses NHSE will identify duplicate collections that can be retired in place of faster data flows.

Outputs:

The Faster Data Flows Programme will provide outputs to approx. 142 acute providers, 150 community providers, 42 ICBs and NHSE teams through the Foundry platform. The frequent flow of data will feed into current products within Foundry that have been produced for the NHS in the form of dashboards, tools and products for example: NHS Performance Overview dashboard, Elective Recovery dashboard, Strategic planning tools, and the Integrated Care Systems (ICS) Workspace.

ICBs will contribute their requirements into outputs required for their local reporting needs and providers will have access to the platform to generate their own reports/dashboards/tools.

The wider/future vision is to provide a view of the whole patient pathway within Foundry. This will be through a pseudonymised patient view in that pulls together information from sources flowing into Foundry that cover the patient pathway and will help decision making for care co-ordination and identify where there may be blockages or improvement required in the healthcare system for that patient. This is intended to be accessed by providers and ICBs and where re-identification of the patient is required this will be granted through the DSCRO.

Through faster Data Flows NHSE will establish a route to provide data to areas in the NHSE that currently request manual aggregate data collections to reduce the current reporting burden on providers. NHSE envisages that this will be through a report in the platform where providers can view and verify their metrics and can provide these metrics to the SITREP(Situation Reports)/data collections owners.

Processing:

High level data flow:
i) Providers extract identifiable Acute Activity data from their electronic record systems and/or their data warehouse. An automated daily process will securely send the data to the Foundry platform instance operated and controlled by the NHS Digital DSCRO.
ii) The data will be processed and pseudonymised by the DSCRO.
iii) Pseudonymised data will be sent to the Foundry platform instance operated and controlled by NHS England (NHSE).
iv) Allowed linkage is between data released under this agreement and pseudonymised data NHS England receives under application DARS-NIC-139035-X4B7K & DARS-NIC-384608-C9B4L.

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.

Data Processors must only act upon specific instructions from the Data Controller.

Data can only be stored at the addresses listed under storage addresses.

All access to data is managed under controls known as Purpose-Based within Foundry. Users can only access data authorised by their role and the tasks that they are required to undertake.

SEGREGATION:
Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked.

Where the Data Processor and/or the Data Controller hold identifiable data with opt outs applied and identifiable data with opt outs not applied, the data will be held separately so data cannot be linked.

The identifiable collection of this data performed by NHS Digital is held within the DSCRO Data Landing Portal (DLP) & NHS Digital Foundry environment. Pseudonymised data held and processed by NHS England is held separately within the NHS England's National Data Platform. Where the Data Controller, Data Processor or NHS Digital hold both identifiable and pseudonymised data, the data will be held and processed separately, including data held within the Foundry system.

Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated to NHSE into the National Data Platform (Foundry). If a provider or commissioner requires the raw/clean data this will be subject to a DARS request into the DSCRO.

Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement.

Re-identification of patients will only occur for the purposes of direct care. The process of how this re-identification may occur is outlined below:

DIRECT CARE
The Re-identification process for direct care is as follows:
1. The user identifies a patient cohort to be re-identified for the purpose of direct care.
2. The user sends a re-id request to the DSCRO. This may be done through the user or CSU’s Business Intelligence (BI) Tool, or through a manual form.
3. The DSCRO assesses as to whether the request passes the specified re-identification process checks. Checks include if the requester is authorised to access identifiable data, if the number of patients in the cohort is appropriate, and that the request does not seem inappropriate or outside of expected parameters, including for example around timings and the requestor’s relationship with patients in the data. These checks are carried out either by DSCRO staff using pre-approved information (timing’s, requester’s identity etc) or via an automated system.
4. For automated systems, steps 1 - 3 wouldn’t apply in most cases as it would be the direct care professional who identifies the cohort and as long as they are an approved re-id user and have gone through security checks initially, they will be able to re-id without further checks.
5. If successful/approved, the DSCRO re-identifies the relevant data item(s) for the appropriate patients and returns the identifiable fields to Health or Care professional(s) with a legitimate relationship to the patient. The analyst does not see the identifiable record.
6. DSCROs retain an audit trail of all re-id requests.

Identifiable and pseudonymised data must be held and processed separately in order to ensure that the pseudonymised data is not re-identified outside of the situation where re-identification is permitted under this DSA.

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

The NHS National Data Platform (Foundry) sits on an Amazon Web Services platform under contract with NHS England. Within that secure cloud processing environment, Palantir (acting under instruction from NHS England) manage their platform. Palantir provide the Foundry platform as a hosted platform and data storage for NHSE and are therefore listed as processors. They supply the infrastructure and support to the system, but do not access patient identifiable data in the DSCRO. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data. This is located, stored and accessed in England and Wales.

Rapid Diagnostic Centre - Cancer TRE — DARS-NIC-411785-Z6X7M

Type of data: Pseudonymised

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 - s261(5)(d), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: Yes, Rapid Diagnostic Centres (RDCs) are being rolled out nationally as an important part of a broader strategy to deliver faster and earlier diagnosis and improved patient experience. In time, it is the vision for RDCs to offer: • A single point of access to a diagnostic pathway for all patients with symptoms that could indicate cancer; • A personalised, accurate and rapid diagnosis of patients’ symptoms by integrating existing diagnostic provision and utilising networked clinical expertise and information locally. The objectives of implementing RDCs are: • To support earlier and faster cancer diagnosis by assessing patients’ symptoms holistically and providing a tailored pathway of clinically relevant diagnostic tests as quickly as possible, targeting and reducing any health inequalities that may currently exist; • To create increased capacity through more efficient diagnostic pathways by reducing unnecessary appointments and tests; • To deliver a better, personalised diagnostic experience for patients by providing a series of coordinated tests and a single point of contact. • To reduce unwarranted variation in referral for, access to and in the reliability of relevant diagnostic tests by setting standards for RDCs nationally, mandating consistent data collection to enable benchmarking and providing regional support to roll out RDCs; • To improve the offer to staff with new roles which offer development opportunities, greater flexibility and a chance to work in innovative ways. NHS England is working with Cancer Alliances and local providers to iterate and standardise the RDC service model as lessons are learned from implementing them in practice. To support that work, NHS England are undertaking a programme of work evaluating RDCs and will utilise the data in NHS England's Secure Data Environment (SDE) for that purpose. The Rapid Diagnostic Centre dataset comprises of information collected from RDCs. To reduce the burden of data collection and reduce duplication and variation in data reporting, NHS England have sought to minimise the data items being collected in the RDC dataset. Through the RDC dataset being linked with other national datasets in the Cancer SDE, NHS England will be able to utilise relevant information that is already collected in those pre-existing datasets. NHS England have commissioned Ipsos MORI to undertake the evaluation work. Ipsos MORI has, in turn, sub-contracted the York Health Economics Consortium (YHEC) and the Strategy Unit hosted by Midlands and Lancashire Commissioning Support Unit (CSU) to undertake different elements of the programme. All three organisations are providing services under commercial contracts for the purpose of the RDC Evaluation described above. Each organisation has been chosen due to their demonstrable areas of expertise relevant to specific aspects of the evaluation which will lead to the benefits to the health and social care system described above. The programme covers three elements under evaluation: • Process evaluation undertaken by Ipsos MORI • Economic evaluation undertaken by YHEC • Impact evaluation undertaken by the Strategy Unit A strategy document outlining the analytical questions to be answered for each element of the programme will be maintained by NHS England. It is expected that this document will be updated over the course of the next 3 years as required as new questions emerge within the themes of process, economics and impact. NHS England will have sole responsibility for agreeing the content of the strategy document thereby determining the scope of the work to be undertaken by the data processors. Therefore, NHS England is the sole data controller for this programme and all work undertaken as part of the programme. Ipsos MORI, YHEC and Midlands and Lancashire CSU are all data processors acting under the instruction of NHS England. Ipsos MORI is unable to make decisions about how or why the data will be processed. Any such decisions, including decisions about the questions to be answered for the purpose of the evaluation and decisions about which data processors will undertake which work packages require approval from NHS England. In the process of reviewing and agreeing the content of the strategy document, NHS England will utilise an Evaluation Oversight Group and a Task and Finish Group. Those groups will provide advice to NHS England to support its decision-making although the final decisions will be taken by NHS England alone. The Evaluation Oversight Group comprises of representatives from the Cancer Alliance Data, Evidence and Analysis Service (CADEAS), clinical and research experts, patient representatives and information governance specialists. Both the Evaluation Oversight Group and the Task and Finish Group will review the strategy and the findings as they come out and may raise additional questions or themes for the programme to consider. The legal basis for NHS England to process personal data is GDPR Article 6(1)(e) ‘task in the public interest’ and for processing special categories of personal data NHS England rely on GDPR Article 9(2)(h) ‘processing is necessary for the purposes of preventative or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care…’. The following linked datasets will be required for the purposes of this programme of work: i) Rapid Diagnostic Centre (RDC) Minimum Dataset This data source contains information about patients referred to RDCs. It is of fundamental relevance to this programme of work. ii) National Cancer Registration Dataset This data source contains details of individuals’ diagnoses including details of cancer staging, first treatments, how advanced cancer was when diagnosed, etc. iii) Civil Registration Mortality This data source will be used to identify which patients on RDC pathways died and what caused those deaths in order to understand the impacts of RDCs on survival. iv) Cancer Waiting Times (CWT) This data source will be used to assess whether RDCs are impacting on time to diagnosis and are being effective in improving the speed of diagnoses by reducing the number of days to diagnosis and referral to first diagnostic tests. v) Hospital Episode Statistics (HES) The information in the Admitted Patient Care, Outpatient, Critical Care and Accident & Emergency, Uncurated Low Latency Hospital Data Set - Emergency Care will provide crucial information about patient care pathways. The analyses will need to consider what other health conditions patients are diagnosed with following referral to an RDC as RDCs aim to ensure appropriate onward referral links for people tested for but found not to have cancer and the programme is also concerned with the overall impact and economic impact of RDCs on the wider health system. Understanding patients’ comorbidities will also inform assessment of the impact of RDCs on cancer outcomes. vi) Rapid Cancer Registration Dataset The data will provide information of significant events that occur to each patient as they proceed through the diagnostic and therapeutic parts of the cancer pathway. The data will give NHSE key insights into the outcomes of patients who were referred on a non-site-specific (NSS) pathway (previously referred to as RDCs) and provide a comparative group of patients who had a similar outcomes but were not referred on an NSS pathway. This data will be used in conjunction with the Cancer Registration Dataset to better enrich analysis of the RDC Minimum Dataset by providing further overlap of records associated with the cohort of patients referred on NSS pathways. Data is not able to be limited to specific cohorts of patients within the SDE, all minimisation efforts will be implemented by the Data Processors under instruction from the Data Controller. The data subjects will be any patients with suspected cancer based on the Nice Guidelines referral criteria during the period from 2020 through to 2024. To understand patients’ relevant medical histories including details of comorbidities and referral pathways, the work will require access to some historical information. For this purpose, data is required from 2015 where available. The amount and type of data utilised per analysis will be minimised on a ‘per analysis’ basis (by dataset, by year and by fields or groups/categories of fields). (Agency/Public Body, internal NHS transfer)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-11-17 — 2022-11-16 2022.12 — 2023.11.

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: MONITOR, NHS ENGLAND (QUARRY HOUSE), NHS TRUST DEVELOPMENT AUTHORITY, NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Cancer Waiting Times (CWT) Data Set
  2. Civil Registration - Deaths
  3. Hospital Episode Statistics Accident and Emergency
  4. Hospital Episode Statistics Admitted Patient Care
  5. Hospital Episode Statistics Critical Care
  6. Hospital Episode Statistics Outpatients
  7. National Cancer Registration Data Set
  8. Rapid Diagnostic Centre Data Set
  9. Emergency Care Data Set (ECDS)
  10. Uncurated Low Latency Hospital Data Sets - Emergency Care
  11. Civil Registrations of Death
  12. Hospital Episode Statistics Accident and Emergency (HES A and E)
  13. Hospital Episode Statistics Admitted Patient Care (HES APC)
  14. Hospital Episode Statistics Critical Care (HES Critical Care)
  15. Hospital Episode Statistics Outpatients (HES OP)
  16. Rapid Cancer Registrations Data Set

Objectives:

Rapid Diagnostic Centres (RDCs) are being rolled out nationally as an important part of a broader strategy to deliver faster and earlier diagnosis and improved patient experience. In time, it is the vision for RDCs to offer:
• A single point of access to a diagnostic pathway for all patients with symptoms that could indicate cancer;
• A personalised, accurate and rapid diagnosis of patients’ symptoms by integrating existing diagnostic provision and utilising networked clinical expertise and information locally.

The objectives of implementing RDCs are:
• To support earlier and faster cancer diagnosis by assessing patients’ symptoms holistically and providing a tailored pathway of clinically relevant diagnostic tests as quickly as possible, targeting and reducing any health inequalities that may currently exist;
• To create increased capacity through more efficient diagnostic pathways by reducing unnecessary appointments and tests;
• To deliver a better, personalised diagnostic experience for patients by providing a series of coordinated tests and a single point of contact.
• To reduce unwarranted variation in referral for, access to and in the reliability of relevant diagnostic tests by setting standards for RDCs nationally, mandating consistent data collection to enable benchmarking and providing regional support to roll out RDCs;
• To improve the offer to staff with new roles which offer development opportunities, greater flexibility and a chance to work in innovative ways.

Whilst RDCs will be established for patients with symptoms that could indicate cancer, most patients seen by an RDC will not have cancer. A key wider benefit of RDCs will therefore be diagnosing serious non-cancer conditions more efficiently.

NHS England and NHS Improvement are working with Cancer Alliances and local providers to iterate and standardise the RDC service model as lessons are learned from implementing them in practice. To support that work, NHS England and NHS Improvement are undertaking a programme of work evaluating RDCs and will utilise the data in NHS Digital’s Cancer Trusted Research Environment (TRE) for that purpose.

The Rapid Diagnostic Centre dataset comprises of information collected from RDCs. To reduce the burden of data collection and reduce duplication and variation in data reporting, NHS England and NHS Improvement have sought to minimise the data items being collected in the RDC dataset. Through the RDC dataset being linked with other national datasets in the Cancer TRE, NHS England and NHS Improvement will be able to utilise relevant information that is already collected in those pre-existing datasets.

NHS England and NHS Improvement have commissioned Ipsos MORI to undertake the evaluation work. Ipsos MORI has, in turn, sub-contracted the York Health Economics Consortium (YHEC) and the Strategy Unit hosted by Midlands and Lancashire Commissioning Support Unit (CSU) to undertake different elements of the programme.

The programme covers three elements under evaluation:
• Process evaluation undertaken by Ipsos MORI
• Economic evaluation undertaken by YHEC
• Impact evaluation undertaken by the Strategy Unit

A strategy document outlining the analytical questions to be answered for each element of the programme will be maintained by NHS England and NHS Improvement. It is expected that this document will be updated over the course of the next 3 years as required as new questions emerge within the themes of process, economics and impact.

NHS England and NHS Improvement will have sole responsibility for agreeing the content of the strategy document thereby determining the scope of the work to be undertaken by the data processors.

Therefore, NHS England and NHS Improvement (comprised of Monitor and the Trust Development Authority (TDA)) are joint data controllers for this programme and all work undertaken as part of the programme. Ipsos MORI, YHEC and Midlands and Lancashire CSU are all data processors acting under the instruction of NHS England and NHS Improvement. Ipsos MORI is unable to make decisions about how or why the data will be processed. Any such decisions, including decisions about the questions to be answered for the purpose of the evaluation and decisions about which data processors will undertake which work packages require approval from NHS England and NHS Improvement.

In the process of reviewing and agreeing the content of the strategy document, NHS England will utilise an Evaluation Oversight Group and a Task and Finish Group.

Those groups will provide advice to NHS England and NHS Improvement to support its decision-making although the final decisions will be taken by NHS England and NHS Improvement alone.

The Evaluation Oversight Group comprises of representatives from the Cancer Alliance Data, Evidence and Analysis Service (CADEAS), clinical and research experts, patient representatives and information governance specialists.

Both the Evaluation Oversight Group and the Task and Finish Group will review the strategy and the findings as they come out and may raise additional questions or themes for the programme to consider.

The legal basis for NHS England and NHS Improvement to process personal data is GDPR Article 6(1)(e) ‘task in the public interest’ and for processing special categories of personal data NHS England and NHS Improvement rely on GDPR Article 9(2)(h) ‘processing is necessary for the purposes of preventative or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care…’.

The following linked datasets will be required for the purposes of this programme of work:

i) Rapid Diagnostic Centre (RDC) Minimum Dataset
This data source contains information about patients referred to RDCs. It is of fundamental relevance to this programme of work.

ii) National Cancer Registration Dataset
This data source contains details of individuals’ diagnoses including details of cancer staging, first treatments, how advanced cancer was when diagnosed, etc.

iii) Civil Registration Mortality
This data source will be used to identify which patients on RDC pathways died and what caused those deaths in order to understand the impacts of RDCs on survival.

iv) Cancer Waiting Times (CWT)
This data source will be used to assess whether RDCs are impacting on time to diagnosis and are being effective in improving the speed of diagnoses by reducing the number of days to diagnosis and referral to first diagnostic tests.

v) Hospital Episode Statistics (HES)
The information in the Admitted Patient Care, Outpatient, Critical Care and Accident & Emergency subsets of HES will provide crucial information about patient care pathways. The analyses will need to consider what other health conditions patients are diagnosed with following referral to an RDC as RDCs aim to ensure appropriate onward referral links for people tested for but found not to have cancer and the programme is also concerned with the overall impact and economic impact of RDCs on the wider health system. Understanding patients’ comorbidities will also inform assessment of the impact of RDCs on cancer outcomes.

The data subjects will be any patients with suspected cancer based on the Nice Guidelines referral criteria during the period from 2020 through to 2024.

To understand patients’ relevant medical histories including details of comorbidities and referral pathways, the work will require access to some historical information. For this purpose, data is required from 2015 where available. The amount and type of data utilised per analysis will be minimised on a ‘per analysis’ basis (by dataset, by year and by fields or groups/categories of fields).

Yielded Benefits:

The data described within this Agreement has not yet been made available to Ipsos MORI, YHEC and Midlands and Lancashire CSU, as such there are no yielded benefits.

Expected Benefits:

The primary benefit from using the Cancer TRE is that it will enable NHS England and NHS Improvement to reduce the burden of data collection on local service providers allowing NHS England and NHS Improvement to collect the minimum information on RDCs and to combine that with relevant information that is already collected via existing national datasets. This is a benefit to health care providers.

Having access to the combined data supports the wider aim of evaluating the impact and effectiveness of Rapid Diagnostic Centres in achieving the intended goals. If the evaluation demonstrates that RDCs are effective and are having a positive impact in terms of improving the patient experience and outcomes for patients with suspected cancer, the findings of this evaluation would enable NHS England and NHS Improvement to work with Cancer Alliances and local authorities to embed the RDC programme and improve the effectiveness of RDCs. If the evaluation demonstrates the intended goals for RDCs are being achieved, the information derived from the data in the Cancer TRE will support conversations with commissioning groups about developing sustainable funding models and evidencing the wider benefits of the RDC programme beyond cancer.

This programme of work aims to contribute to the following objectives:

• Supporting earlier and faster cancer diagnosis by assessing patients’ symptoms holistically and providing a tailored pathway of clinically relevant diagnostic tests as quickly as possible, targeting and reducing any health inequalities that may currently exist;

• Creating increased capacity through more efficient diagnostic pathways by reducing unnecessary appointments and tests;

• Delivering a better, personalised diagnostic experience for patients by providing a series of coordinated tests and a single point of contact.

• Reducing unwarranted variation in referral for, access to and in the reliability of relevant diagnostic tests by setting standards for RDCs nationally, mandating consistent data collection to enable benchmarking and providing regional support to roll out RDCs;

• Improving the offer to NHS staff with new roles which offer development opportunities, greater flexibility and a chance to work in innovative ways.

Outputs:

The Midlands and Lancashire CSU will develop and maintain a dashboard to feed back information on the impacts of RDCs over time. This will be used by Cancer Alliances to monitor and manage the performance of their respective RDCs. This dashboard will enable users to break down findings to study variation relating to factors such as ethnic groups, cancer types, etc. and will enable Cancer Alliances to interrogate their own data.

Ipsos MORI will produce quarterly and annual reports to NHS England and NHS Improvement summarising the progress and effectiveness of the RDCs based on analysis of the data in the Cancer TRE supplemented by external information gather through qualitative research undertaken by Ipsos MORI (e.g. interviews with patients, providers, etc.). These reports will be reviewed by the Evaluation Oversight Group and Task and Finish Group as described above and will inform NHS England and NHS Improvement’s ongoing decisions in respect of the strategy of the programme. These reports will also be shared with the Cancer Alliances and local Rapid Diagnostic Centres.

A monthly management information report will be produced outlining the key metrics on progress of the programme.

NHS England and NHS Improvement will determine if and what information will be made publicly available. Any published reports will contain only information that is aggregated with small numbers suppressed in line with the HES Analysis Guide. For example, it is possible that national data broken down by Cancer Alliance may be published.

Processing:

Individually authorised analysts employed by Ipsos MORI, YHEC or the Midlands and Lancashire CSU will be granted remote secure access to the Cancer Trusted Research Environment (TRE) within NHS Digital’s data platform, the Data Processing Service (DPS).

Within the Cancer TRE, the analysts will be able to access pseudonymised linked data from the datasets outlined above.

No details which directly identify data subjects, such as names, NHS Numbers, etc., will be accessible within the TRE.

Analysts will be able to access only the data they are permitted to see and can utilise a variety of analytical tools available within the TRE platform.

Only summary, aggregate results data (data will be aggregated with small numbers suppressed in line with the HES analysis guide) will be exported from the TRE and this will be subject to review and approval by the NHS Digital team providing the TRE. The objective of this will be to ensure that no output contains information which could be used either on its own or in conjunction with other data to breach an individual's privacy.

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 — 2023.11.

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.

OpenSAFELY and High Cost Drugs Linkage — DARS-NIC-397618-T8L8Z

Type of data: Identifiable

Opt outs honoured: Anonymised - ICO Code Compliant, Identifiable (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 England request this data to support their Coronavirus (COVID-19) research platform work (https://www.england.nhs.uk/contact-us/privacy-notice/how-we-use-your-information/covid-19-response/coronavirus-covid-19-research-platform/) which uses the OpenSAFELY secure analytics software (www.opensafely.org). NHS England is the data controller. NHS England has established honorary contracts with researchers at the DataLab at the University of Oxford and the Electronic Health Records (EHR) group at the London School of Hygiene and Tropical Medicine to assist in conducting Covid-19 relevant studies using the OpenSAFELY suite of analytic software - deployed inside existing electronic health record systems. The Phoenix Partnership (TPP) and Egton Medical Information Systems EMIS (GP electronic health record (EHR) software companies ) are the data processor listed in this agreement, under contract with NHS England. NHS England is the sole data controller; currently NHS England, TPP and EMIS are the data processors; GP Data from TPP and EMIS remains within the IT infrastructure of TPP and EMIS. There are therefore currently two examples of where the OpenSAFELY suite of analytics software are being used - OpenSafely-EMIS, and OpenSafely-TPP. OpenSAFELY is a suite of analytics software that is deployed inside an existing EHR system to carry out studies (using the underlying data) - created to deliver urgent results during the global COVID-19 emergency. It is now successfully delivering analyses across more than 24 million patients’ full pseudonymised primary care NHS records (TPP patient GP data). All the analytic software is open for security review, scientific review, and re-use. OpenSAFELY analytics software uses a new model for enhanced security and timely access to data: it does not transport large volumes of potentially disclosive pseudonymised patient data outside of the secure environments managed by the electronic health record software company; instead, trusted analysts can run large scale computation across near real-time pseudonymised patient records inside the data centre of the electronic health records software company. This pragmatic and secure approach has allowed the first analyses to be delivered in just five weeks from project start. Outputs are available here: https://opensafely.org/outputs/ and approved projects are available here - https://approved-projects.opensafely.pages.dev/approved-projects/ The GP infrastructure is accredited to the ISO 27001 information security standard and is NHS Data Security and Protection Toolkit compliant. Patient data has been pseudonymized at source for analysis and linkage using industry standard cryptographic hashing techniques (SHA512+salt). All pseudonymized datasets transmitted for linkage onto OpenSAFELY are encrypted. Access to OpenSafely-EMIS and OpenSafely-TPP is through a virtual private network (VPN) connection, restricted to a small group of researchers. The researchers, who hold honorary contracts with NHS England, only access OpenSafely-TPP or OpenSafely-EMIS to initiate database queries and statistical models; all database activity is logged; and only aggregate statistical outputs leave the environment following best practice for anonymization of results such as statistical disclosure control for low cell counts. A pseudonym is generated from the NHS number using the SHA 512 cryptographic hashing algorithm, in combination with a ‘salt’. This pseudonym is used to link datasets. The salt is transferred between data sharing organisations separately in an encrypted email, and a phone call is made to provide the decryption key to unencrypt the salt. The same salt is used by TPP and EMIS; the salt will be refreshed at 6 monthly intervals. Only restricted individuals in TPP, EMIS and the external data providers are aware of the salt. As a concrete example, TPP created an appropriate salt, which was shared by the process described above with the relevant individual in the Office of National Statistics (ONS). Both TPP and ONS applied the SHA 512 algorithm, in combination with a salt, to their NHS numbers. This creates a unique pseudonym for each NHS number which can be used to match records. The purpose of using a salt (only known to limited individuals involved in the data flow process) is to further reduce the risk of re-identifying any pseudonymised datasets through the use of brute force attacks. As both TPP and EMIS would have the technical ability to re-identify the data through the use of mapping tables, the data is considered as confidential and requires COPI to address the common law duty of confidentiality. There is a tiered level of restricted researcher access to the pseudonymised and de-identified data within OpenSafely-EMIS and OpenSafely-TPP providing enhanced security and privacy protections to the underlying dataset. The descriptions of these 'levels' are described in Processing Activities below. They range from Level 1 - Level 4. As of February 2022, 9 developers (with NHS England honorary contracts) have access to the level 2 or level 3 environment for development and maintenance purposes only. The Level 2 environment is where the event level pseudonymised data is held. The Level 3 environment is where the specific analysis’ cohort data is held. Researchers now only access the Level 4 environment where the aggregated results of their studies are held. The Level 4 environment is where researchers review the results and apply disclosure controls before requesting the data to be released. Two independent output-checkers review the results and only release them if there are no disclosure concerns. 72 researchers have access to the Level 4 environment; the 9 developers also have access to this Level 4 environment For the avoidance of doubt, no researchers can access the Level 1 data (which is where the identifiable data is de-identified and hashed). The full explanation of the levels is contained in processing activities below. With respect to the GP providers, TPP and EMIS, Level 1 refers to the source identifiable GP data which undergoes pseudonymisation and de-identification before being readied for linkage to create Level 2 data. This approach to maintaining patient privacy has support from MedConfidential: “It (OpenSAFELY) was designed and built to promote both research and patient confidentiality at the same time, rather than suggesting they’re opposites,” says one of the (MedConfidential’s) co-founders. https://www.economist.com/science-and-technology/2020/05/14/the-pandemic-has-spawned-a-new-way-to-study-medical-records Community - Local Provider Flow NHS England will use OpenSafely-EMIS and OpenSafely-TPP to process community local flow provider data provided by NHS Digital (filtered and specified to provide detail on high-cost drugs) to deliver specific analysis on various medicines with the potential to identify treatment targets or identify currently unknown risks to patients on these medications. The National Tariff High Cost Drugs List contains the High Cost Drugs which are not covered by national prices under the National Tariff Payment System. These drugs are typically used in a relatively small number of specialist centres rather than across all Trusts. Commissioners and providers are required to agree prices locally (https://www.gov.uk/government/news/high-cost-drugs). A protocol has been created to support examination of the association between the use of immunosuppression to treat immune mediated inflammatory diseases and severe COVID-19 outcomes among adults in England and NHS England are ready to start the analysis immediately if the high-cost drugs data is made available. A draft report has also been produced on the use of the data so far. The purposes for processing are to identify medical conditions and medications that affect the risk or impact of Covid-19 infection on individuals; this will assist with identifying risk factors associated with poor patient outcomes as well as information to monitor and predict demand on health services. High cost drug data can also be used to answer questions directly related to 'confounders' and those people in the UK who are shielding. NHS England can rapidly review how such specific medications are associated with COVID-19 related outcomes, such as mortality, to help inform clinical and policy decisions on shielding criteria. Although shielding restrictions have recently been relaxed, this information could inform important future decisions on shielding in the event of a future waves. Other NHS Digital Datasets NHS England will also use datasets it receives from NHS Digital under DARS-NIC-139035-X4B7K and DARS-NIC-384608-C9B4L in the OpenSafely platform to further enhance the data. These dataset include: - Secondary Uses Services Data (SUS+) - Second generation surveillance system (SGSS) - Civil Registration Data - Deaths Data provided via NHS Digital will be used to: - Determine which people are at highest risk of hospital admission, ventilation, or death, to inform 111 advice, management choices, seclusion advice, and service planning. For example, there may be certain pre-existing medical problems that put people at much higher risk of Covid-related admission or death, that have not yet been identified, and which mean new categories of people need to be in the high-risk group for self-seclusion during the pandemic. As COVID-19 continually is evolving, this is a continuous activity. - Rapidly assess specific hypotheses around treatment or prevention as they arise including: the possible benefits of chloroquine or antiretroviral medication for HIV; the possible hazards of ibuprofen; the possible benefits of inhaled corticosteroids; the benefits or hazards of drugs that up-regulate ACE2 receptors (such as ACE inhibitors and angiotensin receptor blockers); possible beneficial effects from the JAK inhibitor baricitinib. These can all be rapidly assessed by assessing rates of admission and death among those who have, and have not, been routinely taking such medications in primary care. - Combine disease dynamics modelling with near-real-time hyperlocal clinical data on prevalence and population at risk, to predict local spread and service need, and (for example) to design and evaluate exit strategies from lockdown. - Measure and mitigate the indirect health impacts of Covid-19: subject to approval NHS England can monitor the data to identify “Covid Aftershocks” and give early warning on clinical work displaced, such as cancer referrals, cardiovascular management, and vaccinations. NHS England can also help identify NHS organisations in need of additional support around delivering good care as the pandemic continues; and rapidly identify success stories from new best practice that others can learn from. - Rapidly evaluate the impact of national interventions (and collect outcomes data for pragmatic cluster randomised trials of preventative or treatment interventions), especially on specific patient groups. - Inform operational issues such as identifying NHS organisations in need of additional support around delivering good care on Covid, and non-Covid care as the pandemic continues; or identify the best practice others can learn from. OVERSIGHT OF PROJECT: Currently, given the need to rapidly prioritise the research questions that should be answered, the first wave of analyses have been decided by consensus amongst the team of OpenSAFELY researchers at the University of Oxford DataLab and the EHR group at the London School of Hygiene and Tropical Medicine. These researchers hold honorary contracts with NHS England and are operating in line with NHS England's requirements to support the response to COVID-19. The researchers discuss research protocols with the EHR vendors to ensure that the data within the EHR can be reasonably expected to answer the questions raised. A specific study protocol is written by the OpenSAFELY researchers and a Principle Investigator must give approval for the research to proceed. External researchers may provide advice on the study protocol. Following generation of the results, a paper is drafted which is shared with appropriate charity/professional representative groups for review. The pre-publication draft is shared with NHS England’s information governance team for review. Following revisions, the paper is submitted for publication in a peer-reviewed journal alongside being made openly available on a pre-print server. The OpenSAFELY researchers have deep expertise in the use of EHR data as well as epidemiological research. They also have access to a wider network of public health doctors and scientists advising the government, such as SAGE (Scientific Advisory Group for Emergencies), with contact with the Chief Medical Officer and Chief Scientific Advisor, and have drawn on such networks and individuals to inform analyses. NHS England has an established Oversight Board. The Oversight Board has had 4 meetings and their agenda, documents and meetings notes are publicly available: https://www.opensafely.org/governance/ Amendment to change data frequency The current dataset in OpenSAFELY-TPP is a one off collection covering submissions from FY 2018/19 and FY 2019/20, and there is no process in place to routinely update the information available in the High Cost Drug dataset. Whilst this is very useful for assessing events and outcomes early in the COVID-19 pandemic, a routine update of the data is needed to assess current high-priority questions and future important questions. For example, a routine update to this data will allow assessment of COVID-19 vaccine effectiveness in people using high-cost medicines or indeed people with a recorded diagnosis likely to be treated with a High Cost Drug. Therefore the controller is requesting the data frequency is changed to adhoc. This will allow regular (likely to be monthly) refreshes of the data that will better inform the changing medications required to treat COVID-19 as the virus continually evolves and effects patients differently. NHS North of England Commissioning Support Unit (CSU) host the North of England Data Services for Commissioners Regional Officer (DSCRO). North of England CSU is only being utilised for the dissemination of the data as this is processed through the CSU servers. The CSU does no further processing on the data. Legal Basis for Processing Data Data accessed under this Agreement will be processed in accordance with GDPR 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). Common Law Duty of Confidentiality Although the data is pseudonymised when it is disseminated, as TPP and EMIS are in receipt of the SALT key used for this project, the data is considered as confidential. NHS England are relying on Reg 3 (3) of the COPI Notice (2002) to allow the dissemination of confidential patient information without consent. (Agency/Public Body, internal NHS transfer)

Sensitive: Sensitive

When:DSA runs 2020-09-15 — 2021-03-30

Access method: One-Off

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Community-Local Provider Flows

Objectives:

NHS England request this data to support their Coronavirus (COVID-19) research platform work (https://www.england.nhs.uk/contact-us/privacy-notice/how-we-use-your-information/covid-19-response/coronavirus-covid-19-research-platform/) which uses the OpenSAFELY secure analytics software (www.opensafely.org). NHS England is the data controller. NHS England has established honorary contracts with researchers at the DataLab at the University of Oxford and the Electronic Health Records (EHR) group at the London School of Hygiene and Tropical Medicine to assist in conducting Covid-19 relevant studies using the OpenSAFELY suite of analytic software - deployed inside existing electronic health record systems. The Phoenix Partnership (TPP) and Egton Medical Information Systems EMIS (GP electronic health record (EHR) software companies ) are the data processor listed in this agreement, under contract with NHS England. NHS England is the sole data controller; currently NHS England, TPP and EMIS are the data processors; GP Data from TPP and EMIS remains within the IT infrastructure of TPP and EMIS. There are therefore currently two examples of where the OpenSAFELY suite of analytics software are being used - OpenSafely-EMIS, and OpenSafely-TPP.

OpenSAFELY is a new suite of analytics software that is deployed inside an existing EHR system to carry out studies (using the underlying data) - created to deliver urgent results during the global COVID-19 emergency. It is now successfully delivering analyses across more than 24 million patients’ full pseudonymised primary care NHS records (TPP patient GP data), with analyses about to begin using OpenSAFELY-EMIS and OpenSAFELY-TPP. All the analytic software is open for security review, scientific review, and re-use. OpenSAFELY analytics software uses a new model for enhanced security and timely access to data: it does not transport large volumes of potentially disclosive pseudonymised patient data outside of the secure environments managed by the electronic health record software company; instead, trusted analysts can run large scale computation across near real-time pseudonymised patient records inside the data centre of the electronic health records software company. This pragmatic and secure approach has allowed the first analyses to be delivered in just five weeks from project start. Outputs are available here: https://opensafely.org/outputs/.

The GP infrastructure is accredited to the ISO 27001 information security standard and is NHS Data Security and Protection Toolkit compliant.
Patient data have been pseudonymized as source for analysis and linkage using industry standard cryptographic hashing techniques (SHA512+salt). All pseudonymized datasets transmitted for linkage onto OpenSAFELY are encrypted. Access to OpenSafely-EMIS and OpenSafely-TPP is through a virtual private network (VPN) connection, restricted to a small group of researchers. The researchers, who hold contracts with NHS England, only access OpenSafely-TPP or OpenSafely-EMIS to initiate database queries and statistical models; all database activity is logged; and only aggregate statistical outputs leave the environment following best practice for anonymization of results such as statistical disclosure control for low cell counts.

A pseudonym is generated from the NHS number using the SHA 512 cryptographic hashing algorithm, in combination with a ‘salt’. This pseudonym is used to link datasets. The salt is transferred between data sharing organisations separately in an encrypted email, and a phone call is made to provide the decryption key to unencrypt the salt. The same salt is used by TPP and EMIS; the salt will be refreshed at 6 monthly intervals. Only restricted individuals in TPP, EMIS and the external data providers are aware of the salt.

As a concrete example, TPP created an appropriate salt, which was shared by the process described above with the relevant individual in the Office of National Statistics (ONS). Both TPP and ONS applied the SHA 512 algorithm, in combination with a salt, to their NHS numbers. This creates a unique pseudonym for each NHS number which can be used to match records. The purpose of using a salt (only known to limited individuals involved in the data flow process) is to further reduce the risk of re-identifying any pseudonymised datasets through the use of brute force attacks.

There is a tiered level of restricted researcher access to the pseudonymised and de-identified data within OpenSafely-EMIS and OpenSafely-TPP providing enhanced security and privacy protections to the underlying dataset. The descriptions of these 'levels' are described in Processing Activities below. They range from Level 1 - Level 4.

As of writing, 15 researchers are level 2 and 3 approved (accessing OpenSafely-EMIS and OpenSafely-TPP to initiate database queries and statistical models, the code for which are openly available on online on GitHub - a leading software development platform which has tools available for analysts and developers); 11 researchers are level 4 approved (they can only access and review the outputs of the statistical models ie the raw study results). In this tiered model the data between Level 2, 3 and 4 is increasingly less disclosive.
For the avoidance of doubt, no researchers can access the Level 1 data (which is where the identifiable data is de-identified and hashed). The full explanation of the levels is contained in processing activities below.
With respect to the GP providers, TPP and EMIS, Level 1 refers to the source identifiable GP data which undergoes pseudonymisation and de-identification before being readied for linkage to create Level 2 data.

This approach to maintaining patient privacy has support from MedConfidential: “It (OpenSAFELY) was designed and built to promote both research and patient confidentiality at the same time, rather than suggesting they’re opposites,” says one of the (MedConfidential’s) co-founders. https://www.economist.com/science-and-technology/2020/05/14/the-pandemic-has-spawned-a-new-way-to-study-medical-records

NHS England will use OpenSafely-EMIS and OpenSafely-TPP to process community local flow provider data provided by NHS Digital (filtered and specified to provide detail on high-cost drugs) to deliver specific analysis on various medicines with the potential to identify treatment targets or identify currently unknown risks to patients on these medications.
The National Tariff High Cost Drugs List contains the High Cost Drugs which are not covered by national prices under the National Tariff Payment System. These drugs are typically used in a relatively small number of specialist centres rather than across all Trusts. Commissioners and providers are required to agree prices locally (https://www.gov.uk/government/news/high-cost-drugs).

A drafted protocol has been created to support examination of the association between the use of immunosuppression to treat immune mediated inflammatory diseases and severe COVID-19 outcomes among adults in England and NHS England are ready to start the analysis immediately if the high-cost drugs data is made available.

The purposes for processing are to identify medical conditions and medications that affect the risk or impact of Covid-19 infection on individuals; this will assist with identifying risk factors associated with poor patient outcomes as well as information to monitor and predict demand on health services.
High cost drug data can also be used to answer questions directly related to 'confounders' and those people in the UK who are shielding. NHS England can rapidly review how such specific medications are associated with COVID-19 related outcomes, such as mortality, to help inform clinical and policy decisions on shielding criteria. Although shielding restrictions have recently been relaxed, this information could inform important future decisions on shielding in the event of a second wave.

Data provided via NHS Digital will be used to:

- Determine which people are at highest risk of hospital admission, ventilation, or death, to inform 111 advice, management choices, seclusion advice, and service planning. For example, there may be certain pre-existing medical problems that put people at much higher risk of Covid-related admission or death, that have not yet been identified, and which mean new categories of people need to be in the high-risk group for self-seclusion during the pandemic.

- Rapidly assess specific hypotheses around treatment or prevention as they arise including: the possible benefits of chloroquine or antiretroviral medication for HIV; the possible hazards of ibuprofen; the possible benefits of inhaled corticosteroids; the benefits or hazards of drugs that up-regulate ACE2 receptors (such as ACE inhibitors and angiotensin receptor blockers); possible beneficial effects from the JAK inhibitor baricitinib. These can all be rapidly assessed by assessing rates of admission and death among those who have, and have not, been routinely taking such medications in primary care.

- Combine disease dynamics modelling with near-real-time hyperlocal clinical data on prevalence and population at risk, to predict local spread and service need, and (for example) to design and evaluate exit strategies from lockdown.

- Measure and mitigate the indirect health impacts of Covid-19: subject to approval NHS England can monitor the data to identify “Covid Aftershocks” and give early warning on clinical work displaced, such as cancer referrals, cardiovascular management, and vaccinations. NHS England can also help identify NHS organisations in need of additional support around delivering good care as the pandemic continues; and rapidly identify success stories from new best practice that others can learn from.

- Rapidly evaluate the impact of national interventions (and collect outcomes data for pragmatic cluster randomised trials of preventative or treatment interventions), especially on specific patient groups.

- Inform operational issues such as identifying NHS organisations in need of additional support around delivering good care on Covid, and non-Covid care as the pandemic continues; or identify the best practice others can learn from.

OVERSIGHT OF PROJECT:
Currently, given the need to rapidly prioritise the research questions that should be answered, the first wave of analyses have been decided by consensus amongst the team of OpenSAFELY researchers at the University of Oxford DataLab and the EHR group at the London School of Hygiene and Tropical Medicine. These researchers hold honorary contracts with NHS England and are operating in line with NHS England's requirements to support the response to COVID-19. The researchers discuss research protocols with the EHR vendors to ensure that the data within the EHR can be reasonably expected to answer the questions raised. A specific study protocol is written by the OpenSAFELY researchers and a Principle Investigator must give approval for the research to proceed. External researchers may provide advice on the study protocol.

Following generation of the results, a paper is drafted which is shared with appropriate charity/professional representative groups for review. The pre-publication draft is shared with NHS England’s and NHSX’s information governance team for review. Following revisions, the paper is submitted for publication in a peer-reviewed journal alongside being made openly available on a pre-print server.

The OpenSAFELY researchers have deep expertise in the use of EHR data as well as epidemiological research. They also have access to a wider networks of public health doctors and scientists advising the government, such as SAGE (Scientific Advisory Group for Emergencies), with contact with the Chief Medical Officer and Chief Scientific Advisor, and have drawn on such networks and individuals to inform analyses.

NHS England and NHSX is currently working on a model to establish an Interim Oversight Board, with a view to a permanent and formalised independent Oversight Board and user group, to advise on the research pipeline and development roadmap, as well as holding the OpenSAFELY collaborative (TPP, EMIS, University of Oxford DataLab, EHR group of London School of Hygiene and Tropical Medicine, NHS England) to account on the ethical and efficient use of patient data. Details of this can be made available as soon as plans have been finalised.

Expected Benefits:

To determine which people are at highest risk of hospital admission, ventilation, or death, to inform 111 advice, management choices, seclusion advice, and service planning.

Rapidly assess specific hypotheses around treatment or prevention as they arise.

Combine disease dynamics modelling with near-real-time hyperlocal clinical data on prevalence and population at risk, to predict local spread and service need.

Measure and mitigate the indirect health impacts of Covid-19

Rapidly evaluate the impact of national interventions (and collect outcomes data for pragmatic cluster randomised trials of preventative or treatment interventions).

Inform operational issues such as identifying NHS organisations in need of additional support around delivering good care on Covid.

In addition, with regard to “high cost drugs”, NHS England will be able to deliver specific analysis on various medicines and it is possible that the analysis will identify new treatment targets or identify currently unknown risks to patients on these medications. An analytical protocol has been drafted to support examination of the association between the use of immunosuppression to treat immune mediated inflammatory diseases and severe COVID-19 outcomes amongst adults in England and NHS England are ready to start the analysis immediately if the high-cost drugs data is made available.

Another example is that “high-cost drugs” data can be used in studies on other medications prescribed by GPs to adjust for potential “confounders” and improve the assertions that can already be made using OpenSAFELY. For example, NHS England have assessed the relationship between non-steroidal anti-inflammatories (NSAIDs), such as ibuprofen, and negative COVID outcomes in people with rheumatoid arthritis (preprint submitted and expected to be available online within 48hours). NSAIDs are the mainstay of treatment in rheumatoid arthritis however in more severe forms of the disease “high-cost drugs” like adalimumab are also used. In the current study NHS England are not able to accurately measure disease severity which may give misleading results, or assess any positive or negative confounding effects of such high-cost drugs.

Another important analysis NHS England can conduct rapidly using the “high cost drugs” data relates to shielding. The UK government shielding guidance on people who are clinically extremely vulnerable from COVID-19 explicitly required people who are taking treatments that affect the immune response to shield since the outbreak of the pandemic. Many of these medications are contained in the “high-cost drugs” dataset and using this data in OpenSAFELY-EMIS and OpenSAFELY-TPP, NHS England can rapidly review how such specific medications are associated with COVID-19 related outcomes, such as mortality, to help inform clinical and policy decisions on shielding criteria. Although shielding restrictions have recently been relaxed, this information could inform important future decisions on shielding in the event of a second wave.

Failure to obtain sufficient data could significantly hamper the national COVID pandemic planning and response and adversely affect the preparedness for a potential second wave.

Outputs:

Reports commissioned by Scientific Advisory Group on Emergencies (SAGE), or Department of Health Chief Medical Officer (CMO) / Chief Scientific Advisor (CSA), Joint Biosecurity Centre, or requests that come through the NHS England single point of access that are relevant to the COVID-19 public health emergency.
Work is ongoing to onboard other researcher organisations to use the OpenSAFELY analytics software

Analyses, including supplements, will be openly published online, often initially to a pre-print journal, before submission to a peer review journal and be made available on the OpenSAFELY website as soon as possible (subject to journal restrictions on open access timelines): https://opensafely.org/outputs/

Abstracts/summaries may be used in conferences and for presentations.

As described above, all data outputs that leave OpenSAFELY-EMIS or OpenSAFELY-TPP will be aggregated and anonymised with small number suppression. There will be no restrictions on sharing such outputs which will also be shared with policy makers, the wider research community as well as the public.

The OpenSAFELY analytics software and associated tools and codelists are all open source and available for re-use (https://opensafely.org/code/); derived data that is published are not subject to any intellectual property.

All published outputs will only contain aggregated results with small number suppression applied.

An article has been published already about the use of the OpenSAFELY analytics software in regards to how it was used to characterise factors associated with COVID-19 death in 17 million patients.
https://www.nature.com/articles/s41586-020-2521-4

Processing:

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

Approximately 24m patient (circa 17m adults) pseudonyms from TPP, and approximately 35m from EMIS, will be given to the DSCRO’s (Data Services for Commissioners Regional Offices) to match against local flow high cost drug data.

DSCROs will share pseudonymised high cost drugs data directly with the electronic health record (EHR) vendors, TPP and EMIS respectively, who are acting as data processor for NHS England . Message transport is flexible, and can include MESH, depending on the capabilities of the DSCROs. The DSCROs have already been provided with the dataset schema required and the pseudonymisation salt. TPP and EMIS are the only data processors being used by NHSE England for their Coronavirus (COVID-19) research platform, which used the OpenSAFELY analytics software. EMIS subcontract Amazon Web Services as a processor to host the EMIS patient data on it's server - therefore they are also added as a processor to this agreement.

The Secretary of State for Health issued NHS England/Improvement a notice under the Health Service (Control of Patient Information) Regulations 2002 3(4) which enabled NHS England to collect the data required from GP practices directly from their EHR vendor. All information governance for this urgent project is handled by NHS England. The Data Protection Impact Assessment that was drafted approving data flows and access, approves linking pseudonymised and de-identified GP data to outcomes data from the new NHS England and NHSX data store and other sources, such as but not exclusive to: COVID–19 Patient Notification System (CPNS) deaths data; Intensive Care National Audit & Research Centre (ICNARC), Intensive Treatment Unit (ITU) admissions data; Second Generation Surveillance System (SGSS) Public Health England test data; Emergency Care Data Set/A&E patient-level data; Office of National Statistics death data.

The data flow is as follows:

High cost drugs (HCDs) matched by the DSCRO against TPP pseudonyms are only sent to TPP, and the HCDs matched by the DSCRO to EMIS pseudonyms are only sent to EMIS. Once inside TPP or EMIS, respectively, this data stays there.

In effect, there are two instances of OpenSAFELY: OpenSAFELY-EMIS , and OpenSAFELY-TPP. These are separate and remain so; TPP only have the TPP matched data and EMIS only the EMIS matched data.

Technically, the pseudonymised data ONLY resides inside the infrastructure/systems of TPP (or EMIS). TPP holds this on a local server (EMIS uses Amazon Web Services).
AWS receives the data from EMIS and it receives the data (HCD) from NHS Digital via EMIS also. It is also the place where the analysts carry out the analytics processing as part of OpenSAFELY-EMIS.

The OpenSAFELY analytics software is designed to protect patient privacy: the pseudonymised and de-identified patient data (and any data linked from external data providers) is processed into increasingly less disclosive tables (or “levels”), while preserving all the required detail in the data for research analysis. These Level 2, 3, and 4 data do not leave the environment of TPP (or EMIS).

Pseudonymised data from external databases (or data providers), such as HCDs from NHS Digital, once inside either OpenSAFELY-TPP (or OpenSAFELY-EMIS), does not leave the environment of TPP (or EMIS), except as aggregated and anonymous outcomes data after level 4 controls (such as small number suppression) are applied.

When reference is made to “OpenSAFELY-TPP” (or “OpenSAFELY-EMIS”), this is describing the level 2, 3 and 4 pseudonymised and de-identified data/database inside TPP (or EMIS) and the combined set of open-source analytics tools, code and codelists that are used by researchers to study this pseudonymised data.

These tools, code, codelists of OpenSAFELY, when run against (i.e. processing) the pseudonymised and de-identified EHR data, need to be downloaded to the environments of TPP (or EMIS) before they can be executed; this is initiated by a restricted group of researchers with approved access controls.

This table describes how the data available is managed to maintain patient privacy at different levels; the design is purposeful to support rapid research studies whilst keeping the data as minimally disclosive as possible. Once controls are applied to level 4 data, the aggregated study results are made openly available, such as in research papers and short data reports.

LEVEL 1:
Data type held: Identifiable patient data of EMIS and TPP
Where data is held: Held within EMIS and TPP
Controls applied: Under control of GP data controller restrictions eg. smart card access / role based access, with contracts with appropriate data processors, namely EMIS and TPP.
Accessed by: GP clinical staff for direct care.
Restricted access to data processor staff in EMIS and TPP respectively (for de-identification/pseudonymisation to create Level 2 data), working within their existing GPSoC / GPITF infrastructure.


LEVEL 2:
Data type held: Pseudonymised and de-identified event level coded data only. Linkage via pseudonym to similarly pseudonymised and de-identified data from external data providers
Where data is held: OpenSAFELY-EMIS and OpenSAFELY-TPP. OpenSAFELY is a suite of analytic software that is deployed inside the existing GPSoC / GPITF infrastructure of EMIS and TPP OpenSAFELY to run studies on the data made available.
Controls applied: Pseudonymisation and de-identification as per the DPIA. Only coded data is included (plus any associated numerical information). The following codes have been restricted from the dataset:
codes pertaining to gender related issues (such as reassignment), codes pertaining to treatment for assisted fertility (such as IVF), codes pertaining to treatment associated with termination of pregnancy, and codes pertaining/related to sexuality and sexual activity.
Researchers access via secure encrypted link
Whilst accessing OpenSAFELY, internet access on OpenSAFELY is restricted to GitHub; research study code and statistical modelling code are developed in GitHub. Once code is validated on test data, it is downloaded onto OpenSAFELY-EMIS or OpenSAFELY-TPP. Once the code is validated on test data, it is run against the pseudonymised and de-identified data. For the avoidance of doubt, the test data is all synthetic and created from OpenSAFELY analytics software code (no patient data is used to generate this), simply as data to test the statistical models on.
Accessed by: Researchers* who hold honorary contracts with NHS England and have signed Data Access Agreements to relevant access level. Currently researchers are from the University of Oxford Datalab team and the EHR Group of London School of Hygiene and Tropical Medicine (who work for the PI's of OpenSAFELY).

LEVEL 3:
Data Type Held: Study data of 1 row per pseudonym (patient). For example - male; over 70; has a history of cardiovascular disease; has been prescribed NSAIDs on repeat prescriptions; has no history of COPD; and has been diagnosed with COVID
Where data is held: As per LEVEL 2.
Controls applied: As per LEVEL 2.
Accessed by: As per LEVEL 2.

LEVEL 4: Aggregated study results following application of statistical models. An example of a raw study result: "An example raw study result: people on a blood pressure tablet have 1.4 times higher chance of being admitted to ITU with Covid-19", or "people with asthma are no more likely to be admitted to ITU with Covid-19 than anybody else"
Where data is held: As per LEVEL 2 and 3
Controls Applied: As per LEVEL 2 and 3. Also, study researchers review the aggregated study results for inconsistent outputs and apply both computational and human small number suppression to result cells before release outside of OpenSAFELY-EMIS or OpenSafely-TPP.

It is important to remember that the tools, code and codelists for the OpenSAFELY analytics software are made available as open-source on GitHub. The processing of the patient data occurs inside the TPP and EMIS EHR systems.

There are therefore only 2 dataflows of the data from NHS Digital that the DSCRO provides - one to OpenSAFELY-TPP only, one to OpenSAFELY-EMIS only.

The only data being requested under this agreement is Community Local Flow Provider Data. Further amendments/iterations of this Data Sharing Agreement will be submitted for approval to NHS Digital in the future should the scope of this work go outside the high cost drugs project that it currently covers.

All data that carries any privacy risk (even a theoretical risk, and even when pseudonymised) remains within the secure data centre of the EHR vendor, where it already resides. This also means that all activity is logged for independent review. All processing takes place in the same secure data centre, where the patients’ electronic records were already stored. The only information to ever leave the data centre is summary tables (with low numbers suppressed) from statistical models. Within the data centre, all pseudonymised data is stored in a tiered system of increasingly less disclosive data stores tailored to each analysis. All underlying software and research code is open to review for security profiling, scientific evaluation, and to re-use as open source tools improving science across the community. Overall this approach is therefore highly secure, and supports high quality science: in contrast to working on intermittent “data extracts”, this approach also ensures that the statistical models run across up-to-date records, which is vital during a global health emergency.
Approximately 24m patient (circa 17m adults) identifiers will be given to the DSCRO’s to match against local flow high cost drug data. DSCROs will share the high cost drugs data with the electronic health record (EHR) vendors who are acting as data processor for NHS England.

The approach to privacy and security exceeds standards for many other current EHR analysis projects. SQL (Structured Query Language - commands to extract data from a database) query access to the “event-level” data (level 2), which would otherwise present the highest theoretical privacy risk is severely restricted. NHS England then abstract the key clinical features of each patient for each analysis into a “feature store” for statistical analysis (level 3): this summary data is perfectly matched to the needs of each project, but substantially less vulnerable to re-identification attacks; it is nonetheless still managed to the highest privacy standards, as if it were security-critical event-level data. All access to the data on OpenSAFELY is over highly secure VPN for a very small number of highly trusted, named and experienced analysts whose activity is all fully logged. By building the analytics software inside the originating EHR vendors’ data centre, NHS England/OpenSafely completely avoid transporting large raw primary care datasets which would otherwise present a substantial privacy risk, even when pseudonymised.

Data in OpenSAFELY-EMIS and OpenSAFELY-TPP has both technical and organisational controls to make it de-identified; after pseudonymisation at source, it is de-identified (see below), and researchers have restricted access – they cannot access the event level data, and only a restricted group have contractual permissions to access minimally disclosive data e.g. patient 1, diabetes (y/n), ), covid -19 death (y/n). This undergoes statistical analysis and only aggregated outputs with small number suppression (including human and computer review) are published externally.

De-identification by:

Removal of intentional identifiers: NHS numbers, old format NHS Numbers, all hospital numbers, personal unique codes, unique pupil numbers (UPN), national insurance numbers, all other localised identification numbers, GMC (General Medical Council) numbers, NMC (Nursing Midwifery Council) numbers, GP national codes, prescribing authority identifiers, all other professional body identifiers, Organisation Data Service codes, Workgroup codes, Site codes, all usernames.

· Removal of associational identifiers: Mobile phone numbers, email addresses, telephone numbers, hardware and software unique identifiers, IP addresses.
· Removal of transactional unique identifiers: all unique booking reference numbers for appointments, contacts and referrals.
· Removal of functional unique identifiers: Titles, forenames, middle names, surnames, full dates of birth, full dates of death, house name, house number, street, full postcode.
· Removal of narrative text data: All narrative text on patient records is removed. In line with other UK primary care research database permissions, the dosage and quantity fields on prescribed medication are retained, but any script notes are removed.
· Removal of additional unstructured context: scanned images, medical drawings, letters, and all other record attachments.
· Derived data items and removal of exact original values: date of birth (MM/YYYY), partial postcodes at sector level, indices of multiple deprivation, the rurality-urban classification, geographic super-output area codes at each super output area level. Note – for organisations, the only geographic indicators stored are the lower super output areas and / or middle-level super output area code and the Local Authority code.

The data is not permitted to be re-identified.

Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204535-L4S1P

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

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', NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, This agreement is for the East Midlands Cancer Alliance and West Midlands Cancer Alliance to access Cancer Waiting Times data. However as the Cancer Alliances are not a legal entities, staff are substantively employed by NHS England - Midlands Region, who are the lead organisation, and the data controller who processes data. In this agreement therefore, all references to accessing patient level data refer to the legal entity – NHS England. The direction and aims of the Cancer Alliances, and within this the purpose in which the data included in this Data Sharing Agreement is processed, has consistently been determined by the Cancer Alliance's Cancer Boards. Chairs of these Cancer Boards are acting under honorary contract with NHS England Midlands region when fulfilling their role as Chair of the Cancer Board. The Chairs of the Cancer Alliance boards deliver the final decision on the alliance wide direction, and the purpose for processing this data, following consideration of advice from the other board members. Previously, Cancer Alliance staff were substantively employed by Nottingham University Hospitals NHS Trust who were the previous data controller. All Cancer Alliance staff are no longer employed by the Trust and are now employed by NHS England Midlands Region. In this iteration of the agreement, NHS England are the lead organisation, and the data controller who processes data. All references to accessing the data refer to the legal entity - NHS England. The Cancer Alliances, as agreed by the Cancer Alliance boards, have decided to retain Nottingham University Hospitals NHS Trust as a Data Processor during a transition period until 31/11/2023. 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 Taskforces 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. 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. Cancer alliances are also created to drive improvement in cancer outcomes. Align with the improvement trajectory set for cancer survival (also part of CCG IAF), cancer alliances are set to deliver the Faster Diagnostic Standards (FDS) from April 2021 (delayed from April 2020). FDS is part of CWT dataset, referring to the duration between urgent GP referral to patients being told whether they have a cancer diagnosis or not. The National Cancer Programme has confirmed that FDS, along with 62-day wait, will be key metrics within the 10 year NHS Plan that Cancer Alliances will be held accountable to. Thus without access to the data as outlined in this request, the Cancer Alliance will not be able to deliver work programme as outlined by the National Cancer Programme. The Cancer Alliance will directly access the Cancer Waiting Times System on behalf of alliance member trusts and CCGs The Cancer Alliances work with health organisations across East and West Midlands including the acute providers and CCG's listed below- Acute Providers East Midlands Chesterfield Royal Hospital Kettering General Hospital Northampton General Hospital Nottingham University Hospitals Sherwood Forest Hospitals United Lincolnshire Hospitals University Hospitals of Derby and Burton University Hospitals of Leicester Acute Providers West Midlands University Hospital of Birmingham Royal Orthopaedic Hospital Birmingham NHS Foundation Trust Birmingham Women’s and Children’s Hospital NHS Foundation Trust University Hospitals of Coventry and Warwickshire George Eliot Hospital NHS Trust South Warwickshire NHS Foundation Trust Worcestershire Acute Hospital NHS Trust Wye Valley NHS Trust Robert Jones and Agnes Hunt Orthopaedic Hospital NHS Trust Shrewsbury and Telford Hospital NHS Trust Burton Hospital Foundation Trust Walsall Healthcare NHS Trust Sandwell and West Birmingham Hospitals NHS Trust The Dudley Group NHS Foundation Trust The Royal Wolverhampton NHS Foundation Trust CCGs East Midlands Corby Derby and Derbyshire East Leicestershire and Rutland Leicester City Lincolnshire East Lincolnshire West Mansfield and Ashfield Nene Newark & Sherwood Nottingham City Nottingham North and East Nottingham West Rushcliffe South Lincolnshire South West Lincolnshire West Leicestershire CCG’s West Midlands Birmingham and Solihull Coventry and Warwickshire Hereford and Worcestershire Shropshire, Telford and Wrekin Staffordshire and Stoke-on-Trent The Black Country Data access The CWT system provides the Data Controller / Processor 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 organisation will only access patient records which fall within the Cancer Alliances' footprint of responsibility based on the patients' CCG of responsibility. 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 The Data Controller routinely monitors 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 does not cause the granularity of the data to be coarse, but finer and thus providing invaluable insight 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 Approved users 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 (permitting connections to SQL data sources) 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. The Cancer Alliances will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements. The Cancer Alliance'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. Lead organisations 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 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 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. 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 c. 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. accounts and access will be controlled by password protecting all files. (Agency/Public Body, Network, internal NHS transfer)

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

When:DSA runs 2019-01-02 — 2020-01-01 2019.09 — 2023.11.

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: NOTTINGHAM UNIVERSITY HOSPITALS NHS TRUST, NHS ENGLAND (QUARRY HOUSE)

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 East Midland 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 Nottingham University Hospitals NHS Trust. Nottingham University Hospitals 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 - Nottingham University Hospitals 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.


East Midlands Cancer Alliance

Nottingham University Hospitals NHS Trust will directly access the Cancer Waiting Times System for the East Midlands Cancer Alliance region, which covers a population of 4.7 million people.

East Midlands Cancer Alliance works with health organisations across the East Midlands including 7 acute providers and 19 clinical commissioning groups.

Acute Providers

Kettering General Hospital
Northampton General Hospital
Nottingham University Hospitals
Sherwood Forest Hospitals
United Lincolnshire Hospitals
University Hospitals of Derby and Burton
University Hospitals of Leicester


CCGs
Corby
East Leicestershire and Rutland
Erewash
Leicester City
Lincolnshire East
Lincolnshire West
Mansfield and Ashfield
Nene
Newark & Sherwood
Nottingham City
Nottingham North and East
Nottingham West
Rushcliffe
South Lincolnshire
South West Lincolnshire
Southern Derbyshire
West Leicestershire

Data access

The CWT system provides one organisation (Nottingham University Hospitals NHS 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

Nottingham University Hospitals NHS Trust’s 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 East Midlands 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 Nottingham University Hospitals NHS Trust.

Investigating breaches
Nottingham University Hospitals 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
Nottingham University Hospitals NHS Trust 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 Nottingham University Hospitals NHS 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.

Nottingham University Hospitals 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.

Nottingham University Hospitals NHS 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. Nottingham University Hospitals 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 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 East Midland Cancer Alliance previously include:- · Analyse 62 day performance across the region by trusts/ CCG and tumour site to understand problem areas and help us achieve future targets. · Analyse number 2WW referrals and 2WW performance across the region by trusts/ CCG and tumour site. · Analyse 31 day performance across the region by trusts/ CCG and tumour site. Using number of 31 day patients as a proxy for diagnosis. · Anonymised record level data would allow us to calculate mean wait times with 95% CI as well as other statistical tests. · Perform detailed trend analysis and create statistical process control charts of each target. Using a before and after approach to look at the impact of Cancer Alliance funding on priority areas

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 lead organisation, Nottingham University Hospitals NHS Trust, will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the Nottingham University Hospitals 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 Nottingham University Hospitals NHS Trust’s Senior Information Risk Officer (SIRO), and where there is a valid Data Sharing Agreement between Nottingham University Hospitals NHS Trust 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).

Nottingham University Hospitals 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 the Nottingham University Hospitals 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 NHS mail to NHS mail.
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 Midlands and East. 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 Nottingham University Hospitals NHS 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.


National Gastro Intestinal Cancer Audit comprising National Bowel Cancer Audit and National Oesophago-Gastric Cancer Audit — DARS-NIC-423859-V7S0R

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

Purposes: No (Agency/Public Body)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-05-07 — 2023-05-06 2021.06 — 2023.09.

Access method: Ongoing, One-Off

Data-controller type: HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. Emergency Care Data Set (ECDS)
  3. HES:Civil Registration (Deaths) bridge
  4. Hospital Episode Statistics Accident and Emergency
  5. Hospital Episode Statistics Admitted Patient Care
  6. Hospital Episode Statistics Outpatients
  7. HES-ID to MPS-ID HES Accident and Emergency
  8. HES-ID to MPS-ID HES Admitted Patient Care
  9. HES-ID to MPS-ID HES Outpatients
  10. Civil Registrations of Death - Secondary Care Cut
  11. Hospital Episode Statistics Accident and Emergency (HES A and E)
  12. Hospital Episode Statistics Admitted Patient Care (HES APC)
  13. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

The Gastro-Intestinal Cancer Audit Programme (GICAP) comprises of the National Bowel Cancer Audit (NBOCA) and the National Oesophago-Gastric Cancer Audit (NOGCA).

A contract was awarded in early 2018 by Healthcare Quality Improvement Partnership (HQIP) to the Royal College of Surgeons and NHS Digital (the legal entity of the data processor is “HSCIC” who are trading as “NHS Digital”) to deliver the Gastro-Intestinal (GI) Cancer audit for 3 years, until 31st May 2021. This has now been extended to May 2023, which is when this Agreement is due to expire.

The National Gastro-Intestinal Cancer Audit Programme is commissioned by the Healthcare Quality Improvement Partnership (HQIP) on behalf of NHS England as part of the National Clinical Audit and Patient Outcomes Programme (NCAPOP).

The purposes for processing the data under this Agreement have joint Data Controllership consisting of the Healthcare Quality Improvement Partnership (HQIP) and NHS England. HQIP is commissioned by NHS England to commission and manage the Gastro-Intestinal Cancer Audit Programme (GICAP), NHS England is a controller of the GICAP jointly with HQIP as together both organisations determine the purposes and means of processing.

NHS England is responsible for determining which projects/topics are included as part of the audits. HQIP, as commissioner of GICAP is responsible for project specification development, procurement and extension activities, contract management and authorising data sharing requests. NHS England, as a funder of the GICAP participates within specification development, procurement and project extension activities and authorises the publication of project outputs.

NHS England is involved with developing the scope and purpose of the GICAP project through participation within specification development activities and may authorise (as chair of the specification development meetings) the final project specifications. These specifications set out the purpose of the project, the patient groups and clinical services to evaluate and the types of data to collect. NHS England are a representative upon the HQIP Data access request group which authorises data sharing applications from third parties

The data requested is to be used for the performance of services under contract to the Healthcare Quality Improvement Partnership (HQIP). All Intellectual Property Rights (IPR) in any guidance, specifications, instructions, toolkits, plans, data, drawings, databases, patents, patterns, models, design, or other material, furnished or made available to NHS Digital as part of this request remains vested solely in HQIP. This IPR is in turn vested to NHS England through HQIP’s headline contract with them.

The Clinical Audits and Registries Management Service (CARMS) at NHS Digital, and the Clinical Excellence Unit (CEU) at the Royal College of Surgeons (RCS) will be processing the data under the direction of the data controllers, and only for the purposes described within this Agreement.

The aim of the National Bowel Cancer Audit is to assess the quality of care received by patients with bowel cancer in England and Wales. Similarly, the aim of the Oesophago-gastric Cancer Audit is to assess the quality of care received by patients with oesophago-gastric cancer or oesophageal high-grade dysplasia (a pre-cancerous condition) in England and Wales. The purpose of this application is to aid investigation into case ascertainment for bowel cancer and oesophago-gastric cancer or oesophageal high-grade dysplasia, and to better understand the impact of COVID-19 on the care and outcomes of those who fall within the inclusion criteria for GICAP.

To support this work the Clinical Audits and Registries Management Service (CARMS) within NHS Digital have, and will continue to receive HES APC, HES A&E, ECDS, HES OP and Civil Registration Deaths (Secondary Care Cut). The cohort is identified by ICD10 Diagnosis Codes or OPCS Procedure codes in HES and should return information on those who fit the inclusion criteria but are not included in the Audit cohort to enable assessment of case ascertainment, and the outcomes of those patients who are not currently in the Audit cohort.

The latest HES Admitted Patient Care (APC) data with linked mortality data is required on a quarterly frequency. This will be used to feedback quarterly results to hospital trusts much more quickly than is possible with the HES data linked to GICAP data. More timely data from the audits is high on the agenda of all stakeholders and is requested frequently at the Clinical Reference Groups of both audit streams. The contract for the GICAP states that development work will be carried out to provide more frequent more timely reporting. These timely results on key care processes and outcomes will support hospital trusts in their quality improvement work. Secondly, up to date HES-APC data with linked mortality data is needed urgently to assess the impact of the ongoing COVID-19 pandemic on the care and outcomes of patients with oesophago-gastric cancer and bowel cancer. To allow comparisons over multiple years HES APC will also be disseminated annually, and will be inclusive of the most recent five-years of data.


HES Outpatients’ (OP) data will be received on all patients with ICD10 Diagnosis Codes or OPCS Procedure codes associated with Bowel Cancer only. This will provide information on care earlier and later in patient’s pathways in order to assess their diagnostic pathway, identify how many visits and what procedures patients have undergone prior to and after a diagnosis being made. Having outpatient data will allow the audit to evaluate whether patients are being diagnosed in a timely and appropriate manner, assess whether they are receiving the surveillance they should following treatment, and identify patterns of care which indicate that the cancer has recurred or progressed.

HES A&E/ ECDS: Under this Agreement GICAP will receive HES A&E and ECDS data for all patients with ICD10 Diagnosis Codes or OPCS Procedure codes associated with Bowel Cancer Only. Access to A&E and ECDS data will be invaluable with regards to widening how NBOCA assesses the care of patients with bowel cancer, in particular the burden on patients in terms of unplanned hospital attendances. As an example, there is a need to examine the impact of chemotherapy and radiotherapy on patients in terms of acute toxicity. As part of this NBOCA will look at how many times patients present to A&E with problems related to the side-effects of these treatments. None of this is possible with the data currently held by NBOCA.

Civil Registration (Deaths) data is requested to better understand patient outcomes.

To address the GDPR Principle of Data Minimisation only fields that have been deemed necessary for the purposes of this work have been requested.

HQIP and NHS England both rely on the Article 6 (1) (e) of the GDPR as the lawful basis of processing - "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 is justified through commissioning arrangements which link back to NHS England and other national bodies with statutory responsibilities to improve quality of health care services.

HQIP rely on Article 9 (2) (i) as the legal basis for processing under GDPR - "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". This is justified as all projects aim to drive improvements in the quality and safety of care and to improve outcomes for patients.

NHS England rely on Article 9(2)(h) of the GDPR as the legal basis for processing. "Processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services on the basis of Union or Member State law or pursuant to contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3". NHS England are responsible for provision of health and social care, and management of systems and compliance.

Yielded Benefits:

The OG cancer audit has shown the following outcomes: 1. A reduction in the percentage of patients diagnosed following emergency admissions, compared to 5 years ago 2. An increase in the proportion of patients receiving curative surgery 3. Postoperative mortality (both 30 & 90 days) has continued to fall over the last 6 years 4. Individual NHS trusts can download their own data for local use from the Audit IT system, thereby supporting local clinical audit and service evaluation. The IT system also provides hospitals with access to a series of online reports that describes their own performance relative to national benchmarks. In addition to these clinical benefits, the CEU are able to report on national figures of treatment and outcomes of patients diagnosed with high-grade dysplasia. This is the only national source of data on these patients in the UK. The OG Cancer Audit is now a repository of data on over 80,000 patients with OG cancer across England & Wales which represents a unique resource of clinical data. The data is available for secondary use by researchers through the HQIP Data Access Request Process (please note that this does not contain any NHS Digital data other than aggregated data with small numbers suppressed). The OG Cancer audit project team is also working with CQC to implement improvements in data quality and completeness. The NBOCA has shown the following impacts: 1. A reduction in diagnosis following emergency admissions, compared to 5 years ago and a lower risk of death after curative surgery 2. An increase in the proportion of patients receiving curative surgery 3. Postoperative mortality (both 30 & 90 days) has continued to fall over the last 6 years. And evidence of an acceleration in reduction in mortality coinciding with the start of clinical outcomes publication. 4. Providers and surgeons with outcomes that are outside the expected range are notified by the audit each year. They are asked to carry out a review and provide a response to be published, describing the actions they have taken and will continue to take. NBOCA maintains close connections with CQC and the Welsh Government regarding the outlier process. 5. Individual NHS trusts can download their own data for local use from the Audit IT system, thereby supporting local clinical audit and service evaluation. The IT system also provides hospitals with access to a series of online reports that describes their own performance relative to national benchmarks. 6. Results of NBOCA on advanced bowel cancer directly led to the Pelican’s Advanced Cancer Quality Improvement programme. 7. The 2020 Annual Report showed that approximately 4% of patients aged 65 and over who are diagnosed with colorectal cancer have an accompanying diagnosis of dementia. These patients are a high-risk group with poor prognostic features including older age, poor fitness, and emergency presentation. 25% of patients with dementia undergo major resection compared to 62% of those without dementia, and 2-year survival rates are markedly worse (31% vs 65%). 8. New NICE guidelines have suggested that hospitals should be performing a minimum of 10 rectal cancer resections per year, and surgeons should be performing a minimum of 5 resections a year. The median annual number of rectal resections reported per site was 25 (interquartile range 19 to 36) with 5% of sites not performing above this threshold. At surgeon level, the median annual number of cases was 5 (interquartile range 3 to 7) with 56% of surgeons performing in line with the new NICE guideline

Expected Benefits:

By auditing the care delivered by cancer services, we can highlight areas where hospitals are doing well, and areas in which the quality of care can be improved. By producing information for all NHS services, it allows cancer services to compare themselves with others in England and Wales and share examples of good practice.

Trusts use the outcomes information in the annual reports to assess their care against national standards, clinical guidance and benchmark against the performance of other trusts. For example, the Audit outputs show whether trusts are following national recommendations such as those published by NICE and whether there is any variation in the provision of care. Risk-adjusted outcomes such as 90-day post-operative mortality enable the identification of potential outlier trusts, which are notified of their outlier status and will investigate the causes (these may be related to data quality issues or clinical practice). In cases where clinical practice is identified as contributing to poorer outcomes, trusts’ review and improvement of practices can have a direct impact on patient care.

The Audit can identify and report on such improvements in the following year's annual report. This provides commissioners and clinicians with a national picture of how patients are being treated, with the aim of reducing variation and driving up standards of care. Practice in trusts and local health boards across England and Wales will be compared against evidence-based standards from the Royal College of Radiologists to identify where current practice does not meet these standards

The trust profiles and individual consultant level Clinical Outcomes Programme measures are publicly available, providing transparency and supporting patient choice. The individual trust profiles are produced based on analysis for the last year (or for the last 3 years in the case of OG cancer) which helps trusts/local health boards identify how they are performing against national and regional figures over time.

The results of the audit are published on an annual basis to ensure that NHS Services have the most up to date information.

The Audit Project Team will continue to work with the Patient & Carer panel to produce a patient friendly report to support the annual report publications. The Panel continues to feedback that patients overwhelmingly support the audit and there has been a very positive response to the patient friendly version of the annual report. The patient friendly version of the report allows patients and their carers to better understand care pathways and potential outcomes.

The analyses provided in the Audit allow NBOCA and NOGCA to provide evidence-based recommendations with the aim to improve the quality of patient care.

Outputs:

Many of the outputs produced by NBOCA and NOGCA are contracted deliverables as part of an on-going part of the audit process commissioned by HQIP.

The Audit measures the quality of care received by patients diagnosed with bowel cancer and oesophago-gastric cancer or oesophageal high-grade dysplasia within NHS services in England and Wales. It is designed to evaluate the care pathways followed by patients once they have been diagnosed with these diseases and to assess outcomes. The findings of Audit are published in annual reports.

The National Bowel Cancer 2021 Annual report is targeted for publication in November 2021.
The National Bowel Cancer 2020 Annual report was published in December 2020.
The National Bowel Cancer 2019 Annual report was published in January 2020.
The National Bowel Cancer Audit published two short reports in July 2020 and will do the same in July 2021. It also released a prize-winning poster at a professional conference in 2019. Several papers and conference reports were published in 2020 using this data.

The National Oesophago-Gastric Cancer 2021 Annual report is targeted for publication in December 2021.
The National Oesophago-Gastric Cancer 2020 Annual report was published in December 2020.
The National Oesophago-Gastric Cancer 2019 Annual report was published in December 2019
This audit also published a short report in June 2019 and the summer of 2020. Several papers and conference reports were produced in the 2020 NHS Digital Data.

All reports are written in patient friendly language and can be understood by the lay reader, and The RCS takes the opportunity to disseminate their reports as widely as possible - as can be seen from the conferences attended to promote annual reports.
It is anticipated that the annual reports will be presented at the AUGIS, British Society of Gastroenterology (BSG) and ACPGBI annual meetings as a minimum and others as appropriate

Publication in peer-reviewed journals will allow presentation of the Audit methodology and results in more detail than in the Annual reports. For example, the findings of the 2016 Annual Report for NBOCA and NOGCA were published in several journals and presented at several conferences in 2017 including the annual meetings of each of the British Society of Gastroenterologists (BSG) the Association of Upper Gastro-intestinal Society (AUGIS) and the Association of Colo-proctologists in Great Britain and Ireland (ACPGBI). Presentations were also made at the PHE Cancer Data and Outcomes Conference.

The audit will provide national and trust level outcomes on end-of-life care.

The Audit will report on the feasibility of using information reported by patients themselves about the experience of their bowel cancer care and the feasibility of using information reported by patients themselves about the outcomes of their bowel cancer e.g., symptoms, functional status and quality of life.
The outputs are reported at National, Cancer Alliance and NHS Trust level. Examples of specific statistical outputs are:
NBOCA
• Percentage of patients with surgical intent
• Percentage of patients with complications
• Risk adjusted 90-day post-operative mortality
• Risk adjusted 2-year mortality
• Risk adjusted complication rate
• Percentage of adequate lymph node resections
• Percentage of positive resection margin
• Length of stay
• Percentage of unplanned readmissions

NOGCA
• Percentage of patients with curative treatment intent
• Risk adjusted 30- and 90-day post-operative mortality
• Percentage of adequate lymph node resections
• Percentage of positive resection margins
• Length of stay

Outputs on the management of patients with rectal cancer and advanced disease are also included in the NBOCA annual report.

Outliers at individual surgeon level and at trust level are identified through the analysis undertaken by the RCS CEU. Notifications are sent out for response from the individual surgeons and/or the trusts (as applicable). Their responses on the outlier measures are included in an appendix to the annual report. Clinical Outcomes Publication (COP) data is published on the professional bodies' websites (Advancing Knowledge and treatment of bowel disease (ACPGBI)/Association of Upper Gastrointestinal Surgeons (AUGIS) respectively) before being made available to the public via NHS Choices.

All outputs will be aggregated with small numbers suppressed except when assisting NHS Trusts in evaluating the reasons for their outlier status. Record level data for the relevant trust will be provided back to the trust upon request to NHS Digital, appropriate s251 is in place to allow the fact of death in relation to the two mortality indicators to be shared. Data files for these requests will be provided in a 256-bit encrypted zip file to a named individual via NHS.net; the password for the file will be sent to another named individual nominated by the trust, again using NHS.net email.

Processing:

No data are supplied to NHS Digital under this Agreement.

The DARS Data Production team will identify patients who fit the inclusion criteria but are not included in the Audit cohort using ICD10 Diagnosis Codes or OPCS Procedure Codes. This cohort of patients will then be linked to the data requested and securely transferred to CARMS. No identifiable data is supplied under this Agreement.

CARMS will then securely transfer the requested data to the Clinical Excellence Unit (CEU) at Royal College of Surgeons (RCS). The CEU will analyse this data to produce statistical tables for inclusion in the NBOCA and NOGCA annual reports.

The data received under this Agreement will not be linked to any other datasets. There will be no requirement to re-identify individuals from the pseudonymised data.

NHS Digital data will only be accessed and processed by substantive employees of the data processors and will not be accessed or processed by any other third parties not mentioned in this Agreement. All those processing the data have received appropriate training in data protection and confidentiality.

Once the data has been transferred to CEU, the Audit data (including NHS Digital data) is stored in a secure, IT environment at the Royal College of Surgeons of England (RCS). Access to the data is only available for approved individuals and security is maintained through the use of passwords and encryption.

National Gastro Intestinal Cancer Audit Programme (GICAP)- National Oesophago-Gastric Cancer Audit (NOGCA) — DARS-NIC-454669-H0H4X

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, Identifiable, Yes, No (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Agency/Public Body)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-05-07 — 2023-05-06 2021.06 — 2023.04.

Access method: Ongoing, One-Off

Data-controller type: HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

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

Objectives:

The Gastro-Intestinal Cancer Audit Programme (GICAP) comprises of the National Bowel Cancer Audit (NBOCA) and the National Oesophago-Gastric Cancer Audit (NOGCA).

A contract was awarded in early 2018 by Healthcare Quality Improvement Partnership (HQIP) to the Royal College of Surgeons and NHS Digital (the legal entity of the data processor is “HSCIC” who are trading as “NHS Digital”) to deliver the Gastro-Intestinal (GI) Cancer audit for 3 years, until 31st May 2021, this has now been extended to May 2023.

The National Gastro-Intestinal Cancer Audit Programme is commissioned by the Healthcare Quality Improvement Partnership (HQIP) on behalf of NHS England as part of the National Clinical Audit and Patient Outcomes Programme (NCAPOP).

The purposes for processing the data under this Agreement have joint Data Controllership consisting of the Healthcare Quality Improvement Partnership (HQIP) and NHS England. HQIP is commissioned by NHS England to commission and manage the Gastro-Intestinal Cancer Audit Programme (GICAP), NHS England is a controller of the GICAP jointly with HQIP as together both organisations determine the purposes and means of processing.

NHS England is responsible for determining which projects/topics are included as part of the audits. HQIP, as commissioner of GICAP is responsible for project specification development, procurement and extension activities, contract management and authorising data sharing requests. NHS England, as a funder of the GICAP participates within specification development, procurement and project extension activities and authorises the publication of project outputs.

NHS England is involved with developing the scope and purpose of the GICAP project through participation within specification development activities and may authorise (as chair of the specification development meetings) the final project specifications. These specifications set out the purpose of the project, the patient groups and clinical services to evaluate and the types of data to collect. NHS England are a representative upon the HQIP Data access request group which authorises data sharing applications from third parties.

The data requested is to be used for the performance of services under contract to the Healthcare Quality Improvement Partnership (HQIP). All Intellectual Property Rights (IPR) in any guidance, specifications, instructions, toolkits, plans, data, drawings, databases, patents, patterns, models, design, or other material, furnished or made available to NHS Digital as part of this request remains vested solely in HQIP. This IPR is in turn vested to NHS England through HQIP’s headline contract with them.

The Clinical Audits and Registries Management Service (CARMS) at NHS Digital, and the Clinical Excellence Unit (CEU) at the Royal College of Surgeons (RCS) will be processing the data under the direction of the data controllers and only for the purposes described within this Agreement.

The aim of the Oesophago-Gastric Cancer Audit is to assess the quality of care received by patients with oesophago-gastric cancer or oesophageal high-grade dysplasia (a pre-cancerous condition) in England and Wales. The Audit is based on prospectively collected patient level-data on patients diagnosed with invasive epithelial oesophago-gastric cancer or oesophageal high-grade dysplasia

To support the delivery of NOGCA, the Clinical Audits and Registries Management Service (CARMS) within NHS Digital have received and will continue to receive HES APC, Civil Registration (Deaths) and Demographics data on an annual basis. The applicant is satisfied that there is no other reasonable means for the data processor to achieve the purpose that is less intrusive to the data subjects.
• HES APC will allow the investigation of hospital utilisations and readmissions among patients with palliative treatment intent, with a specific focus on volume of care (number of procedures by the individual) and length of stay
• Demographics and Civil Registrations are requested to measure the performance of trusts and surgeons on the following measures: 30-day post-operative mortality and 90-day post-operative mortality.
• The data received will also allow the Audit to assess the impact of COVID-19 on hospital care and outcomes for NOGCA cohort members.

To address the GDPR Principle of Data Minimisation this request is limited to a cohort of ~85,000 individuals that make up the NOGCA cohort. In addition, only data fields that have been deemed necessary for the purpose of this work have been requested.

The OG Cancer audit has been continuous since 2006. Data is retained from that time up to the present. Retention of the data is essential to answering queries about previously published reports, although each audit only uses the five most recent years of data for reporting.

The data received from the Data Access Request Service (DARS, NHS Digital) is sent to CEU via CARMS to be linked to NOGCA audit data held by CEU. This is in turn linked to the Systemic Anti-Cancer Therapy (SACT) Dataset, Radiotherapy Dataset (RTDS), Patient Episodes Database for Wales (PEDW), the Case Mix Programme (CMP), Cancer Outcomes and Services Dataset (COSD) and Cancer Registration Data.

• SACT: The SACT data covers patients receiving cancer chemotherapy in, or funded by, the NHS in England. This data is collected by the National Cancer Registration and Analysis Service (NCRAS) within Public Health England (PHE) and can be requested via the Office for Data Release (ODR). Linkage will allow a more in-depth analysis of specific chemotherapy regimens and changes to prescribed treatments.
• RTDS: The RTDS hold information on every patient treated with Radiotherapy in the National Health Service in the UK. This data is collected by the NCRAS within Public Health England (PHE) and can be requested via the ODR. The linkage will allow the audit to explore whether the radiotherapy data items in the Audit could be dropped to ease the burden of data collection.
• PEDW: PEDW records all episodes of inpatient and day case activity in NHS Wales Hospitals. This is inclusive of planned and emergency admissions and minor and major operations. Hospital activity for Welsh residents treated in English Hospitals is also included. This data is collected by NHS Wales Informatics Service (NWIS), from whom this data can be requested.
• CMP: The CMP is hosted by the Intensive Care National Audit and Research Centre (ICNARC), from whom the CMP data can be requested. CMP is an audit of patient’s outcomes from adult, general critical care units (intensive care and combined intensive care/high dependency units) covering England, Wales, and Northern Ireland. Linkage will allow reporting patterns of care and outcomes while patients were admitted to critical care and the characteristics of the patients admitted to critical care.
• COSD: When linked to NOGCA data, the COSD linkage will enable GICAP to further determine the pathway of care for patients with advanced disease and to describe in further detail the management and outcomes of patients with GI cancer. This data is collected by NCRAS within PHE and can be requested via ODR.
• Cancer Registration: This linkage will supplement the cases that are recorded in COSD, as Cancer Registration services undertake active case finding and will pick up cases of oesophago-gastric cancer that have not been entered into the audits. This will help to further assess the representativeness of patients captured in NOGCA It is intended to use the data to assess the extent of possible missing data and any patterns relating to this, e.g., geographical areas under-reporting cases or any potential linkage to under presentation related to social deprivation.

HQIP and NHS England both rely on the Article 6 (1) (e) of the GDPR as the lawful basis of processing - "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 is justified through commissioning arrangements which link back to NHS England and other national bodies with statutory responsibilities to improve quality of health care services.

HQIP rely on Article 9 (2) (i) as the legal basis for processing under GDPR - "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". This is justified as all projects aim to drive improvements in the quality and safety of care and to improve outcomes for patients.

NHS England rely on Article 9(2)(h) of the GDPR as the legal basis for processing. "Processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services on the basis of Union or Member State law or pursuant to contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3". NHS England are responsible for provision of health and social care, and management of systems and compliance.

Yielded Benefits:

The OG cancer audit has shown the following outcomes: 1. A reduction in the percentage of patients diagnosed following emergency admissions, compared to 5 years ago 2. An increase in the proportion of patients receiving curative surgery 3. Postoperative mortality (both 30 & 90 days) has continued to fall over the last 6 years 4. Individual NHS trusts can download their own data for local use from the Audit IT system, thereby supporting local clinical audit and service evaluation. The IT system also provides hospitals with access to a series of online reports that describes their own performance relative to national benchmarks. In addition to these clinical benefits, the CEU are able to report on national figures of treatment and outcomes of patients diagnosed with high-grade dysplasia. This is the only national source of data on these patients in the UK. The OG Cancer Audit is now a repository of data on over 80,000 patients with OG cancer across England & Wales which represents a unique resource of clinical data. The data is available for secondary use by researchers through the HQIP Data Access Request Process (please note that this does not contain any NHS Digital data other than aggregated data with small numbers suppressed). The OG Cancer audit project team is also working with CQC to implement improvements in data quality and completeness.

Expected Benefits:

By auditing the care delivered by cancer services, we can highlight areas where hospitals are doing well, and areas in which the quality of care can be improved. By producing information for all NHS services, it allows cancer services to compare themselves with others in England and Wales and share examples of good practice.

Trusts use the outcomes information in the annual reports to assess their care against national standards, clinical guidance and benchmark against the performance of other trusts. For example, the Audit outputs show whether trusts are following national recommendations such as those published by NICE and whether there is any variation in the provision of care. Risk-adjusted outcomes such as 90-day post-operative mortality enable the identification of potential outlier trusts, which are notified of their outlier status and will investigate the causes (these may be related to data quality issues or clinical practice). In cases where clinical practice is identified as contributing to poorer outcomes, trusts’ review and improvement of practices can have a direct impact on patient care.

The Audit can identify and report on such improvements in the following year's annual report. This provides commissioners and clinicians with a national picture of how patients are being treated, with the aim of reducing variation and driving up standards of care. Practice in trusts and local health boards across England and Wales will be compared against evidence-based standards from the Royal College of Radiologists to identify where current practice does not meet these standards.

The trust profiles and individual consultant level Clinical Outcomes Programme measures are publicly available, providing transparency and supporting patient choice. The individual trust profiles are produced based on analysis for the last year (or for the last 3 years in the case of OG cancer) which helps trusts/local health boards identify how they are performing against national and regional figures over time.

The results of the audit are published on an annual basis to ensure that NHS Services have the most up to date information.

The Audit Project Team will continue to work with the Patient & Carer panel to produce a patient friendly report to support the annual report publications. The Panel continues to feedback that patients overwhelmingly support the audit and there has been a very positive response to the patient friendly version of the annual report. The patient friendly version of the report allows patients and their carers to better understand care pathways and potential outcomes.

The analyses provided in the Audit allow NOGCA to provide evidence-based recommendations with the aim to improve the quality of patient care.

Outputs:

Many of the outputs produced by NOGCA are contracted deliverables as part of an on-going part of the audit process commissioned by HQIP.

The Audit measures the quality of care received by patients with oesophago-gastric cancer and oesophageal high-grade dysplasia within NHS services in England and Wales. It is designed to evaluate the care pathway followed by patients once they have been diagnosed with either condition, and to answer questions related to the care they receive and their outcomes. The findings of the Audit are published in annual reports.
• The National Oesophago-Gastric Cancer 2021 Annual report is targeted for publication in December 2022.
• The National Oesophago-Gastric Cancer 2020 Annual report was published in December 2020.
• The National Oesophago-Gastric Cancer 2019 Annual report was published in December 2019
• This audit also published a short report in June 2019 and the summer of 2020. Reports for the Public and Patients are also published on an annual basis.

All reports are written in patient friendly language and can be understood by the lay reader, and The RCS takes the opportunity to disseminate their reports as widely as possible.

It is anticipated that the annual reports will be presented at the AUGIS and British Society of Gastroenterology (BSG) annual meetings as a minimum and others as appropriate

Publication in peer-reviewed journals will allow presentation of the Audit methodology and results in more detail than in the Annual reports. For example, the findings of the 2016 Annual Report for the OG audit were published in several journals and presented at several conferences in 2017 including the annual meetings of each of the British Society of Gastroenterologists (BSG) the Association of Upper Gastro-intestinal Society (AUGIS) and the Association of Colo-proctologists in Great Britain and Ireland (ACPGBI). Presentations were also made at the PHE Cancer Data and Outcomes Conference.

The audit will provide national and trust level outcomes on surgical care.

The outputs are reported at National, Cancer Alliance and NHS Trust Level. Examples of specific statistical outputs are:
• Percentage of patients with curative treatment intent
• Risk adjusted 30- and 90-day post-operative mortality
• Percentage of adequate lymph node resections
• Percentage of positive resection margins
• Length of stay

Outliers at individual surgeon level and at trust level are identified through the analysis undertaken by the RCS CEU. Notifications are sent out for response from the individual surgeons and/or the trusts (as applicable). Their responses on the outlier measures are included in an appendix to the annual report. Clinical Outcomes Publication (COP) data is published on the Association of Upper Gastrointestinal Surgeons (AUGIS) website before being made available to the public.

All outputs will be aggregated with small numbers suppressed except when assisting NHS Trusts in evaluating the reasons for their outlier status. Record level data for the relevant trust will be provided back to the trust upon request to NHS Digital, appropriate s251 is in place to allow the fact of death in relation to the two mortality indicators to be shared. Data files for these requests will be provided in a 256-bit encrypted zip file to a named individual via NHS.net; the password for the file will be sent to another named individual nominated by the trust, again using NHS.net email.

Processing:

To facilitate the linkage of the NOGCA Cohort to NHS Digital data CARMS securely transfer the following identifiers to the DARS Data Production Team
• Audit Tumour ID
• NHS Number
• DOB
• Sex
• Postcode

The Audit Tumour ID is a pseudo-identifier which is unique to each patient in the cohort. This primary key is used to reduce the flow of patient identifiers where data is requested from other data sets and where data is sent from the NHS Digital CARMS team to the Clinical Effectiveness Unit (CEU). The key is held by the NHS Digital CARMS team, who are acting as Data Processor for HQIP.

Following linkage to the NOGCA cohort, DARS securely transfer the requested data to the NHS Digital CARMS team containing no identifiers other than the Audit Tumour ID. In turn CARMS will securely transfer the data to CEU for linking to the audit data.

In tandem to this, the data processors will send patient identifiers and Audit Tumour ID to the respective data controllers for SACT, RTDS, PEDW, CMP, COSD, Cancer Registration data, to facilitate linkage.
The specifics of each linkage are as follows:

SACT
1. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode) are sent by the CARMS team to the Office for Data Release (ODR) in Public Health England. An Audit Tumour ID (a pseudonym which is unique to each patient in the cohort) is also sent to the ODR.
2. SACT data is returned to the RCS CEU with only the Audit Tumour ID, none of the other patient identifiers are returned.
3. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.
The CEU then analyse the linked Audit/SACT dataset to produce statistical tables for inclusion in the outputs listed in the next section. The CEU will not make record level information available to any other party. The CEU will only use the data for the stated purposes.

RTDS
1. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode) are sent by the CARMS team to the Office for Data Release (ODR), Public Health England
2. An Audit Tumour ID (a pseudonym which is unique to each patient in the cohort) is also sent to the Office for Data Release (ODR), Public Health England
3. RTDS data is returned to RCS CEU with only the Audit Tumour ID, none of the other patient identifiers are returned.
4. The Audit Tumour ID is used as a pseudonym to allow linkage to the Audit dataset.

The CEU then analyse the linked Audit/RTDS dataset to produce statistical tables for inclusion in the outputs listed in the next section. The CEU will not make record level information available to any other party. The CEU will only use the data for the stated purposes.

PEDW:
The audit will use the Hospital Site code where the patient was diagnosed to identify patients diagnosed in Wales. For these patients, the audit will then pull the NHS number, Date of Birth, Sex and Postcode to send the relevant cohort to NWIS. There is a risk that some patients are diagnosed in Wales but go on to receive treatment elsewhere, in which case the audit will not get any further information on those patients from PEDW.

1. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode) are sent by CARMS to NWIS only for patients identified as being diagnosed in Wales. The full audit cohort will not be sent to NWIS at any time. An Audit Tumour ID (a pseudonym which is unique to each patient in the cohort) is also sent to the NWIS
2. PEDW data is returned to CARMS with only the Audit Tumour ID, none of the other patient identifiers are returned.
3. The PEDW data with the Audit Tumour ID are sent by CARMS to the Clinical Effectiveness Unit (CEU) of the Royal College of Surgeons for linking to the Audit data that they already hold having previously been sent from CARMS to the CEU. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.

CMP:
1. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode) are sent by CARMS to ICNARC. An Audit Tumour ID (a pseudonym which is unique to each patient in the cohort) is also sent to INCARC
2. ICNARC data is returned to CARMS with only the Audit Tumour ID, none of the other patient identifiers are returned.
3. The ICNARC data with the Audit Tumour ID are sent by NHS Digital CARMS to the Clinical Effectiveness Unit (CEU) of the Royal College of Surgeons for linking to the Audit data that they already hold having previously been sent from CARMS to the CEU. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.

The CEU then analyse the linked Audit/ICNARC dataset to produce statistical tables for inclusion in the outputs listed in the next section. The CEU will not make record level information available to any other party. The CEU will only use the data for the stated purposes.

COSD:
1. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode) are sent by NHS Digital CARMS team to the Office for Data Release (ODR), Public Health England. An Audit Tumour ID is also sent to the Office for Data Release (ODR), Public Health England
2. COSD data is returned to RCS CEU with only the Audit Tumour ID, none of the other patient identifiers are returned.
3. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.

The CEU then analyse the linked Audit/COSD dataset to produce statistical tables for inclusion in the outputs listed in the next section. The CEU will not make record level information available to any other party. The CEU will only use the data for the stated purposes.

Cancer Registration Data:
1. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode) are sent by the CARMS team to the Office for Data Release (ODR), Public Health England. An Audit Tumour ID is also sent to the Office for Data Release (ODR), Public Health England.
2. Cancer Registration data is returned to RCS CEU with only the Audit Tumour ID, none of the other patient identifiers are returned.
3. Cancer Registration data is also returned for patients who fit the inclusion criteria but are not included in the Audit cohort.
4. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.

The CEU then analyse the linked Audit/Cancer Registration dataset to produce statistical tables for inclusion in the outputs listed in the next section. The CEU will not make record level information available to any other party. The CEU will only use the data for the stated purposes.

The CEU at the RCS will then analyse the linked dataset to produce statistical tables for inclusion in the audit.

The NHS Digital CARMS team have all relevant permissions in place to permit these linkages.

NHS Digital data will only be accessed and processed by substantive employees of the data processors and will not be accessed or processed by any other third parties not mentioned in this agreement. All those processing the data have received appropriate training in data protection and confidentiality.

Once the data has been transferred to CEU, NOGCA data (including NHS Digital data) is stored in a secure, IT environment at the Royal College of Surgeons of England (RCS). Access to the data is only available for approved individuals and security is maintained through the use of passwords and encryption.

National Gastro Intestinal Cancer Audit Programme (GICAP)- National Bowel Cancer Audit (NBOCA) — DARS-NIC-376603-K2J9R

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Identifiable, Anonymised - ICO Code Compliant, Yes, No (Section 251, Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(7), National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Agency/Public Body)

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

When:DSA runs 2021-05-07 — 2023-05-06 2018.06 — 2023.04.

Access method: One-Off, Ongoing

Data-controller type: HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), NHS ENGLAND (QUARRY HOUSE), HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP)

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. MRIS - Cause of Death Report
  3. MRIS - Flagging Current Status Report
  4. Hospital Episode Statistics Accident and Emergency
  5. Hospital Episode Statistics Outpatients
  6. Civil Registration - Deaths
  7. Demographics
  8. Emergency Care Data Set (ECDS)
  9. HES:Civil Registration (Deaths) bridge
  10. HES-ID to MPS-ID HES Accident and Emergency
  11. HES-ID to MPS-ID HES Admitted Patient Care
  12. HES-ID to MPS-ID HES Outpatients
  13. Civil Registrations of Death
  14. Hospital Episode Statistics Accident and Emergency (HES A and E)
  15. Hospital Episode Statistics Admitted Patient Care (HES APC)
  16. Hospital Episode Statistics Outpatients (HES OP)
  17. Civil Registrations of Death - Secondary Care Cut

Objectives:

Update March 2018 *******
The contract to run the bowel cancer audit as part of the Upper GI Cancer audit is still to be awarded by HQIP. This was expected to have taken place by the end of February 2018, giving 3 months notice to the end of the contract. As it has not yet happened there is the need to continue to hold, collect and process the data until it is known whether the RCS and NHS Digital will be awarded the contract to continue the audit or whether it will need to be arranged for transfer of the data to a new audit provider. The request to extend the deadline is to allow time for this contract situation to be resolved.

An additional request for 2017/18 HES APC data has been added, this was inadvertently missed off the previous application by the customer.

**********

The National Bowel Cancer Audit is based on prospectively-collected, patient-level data on patients diagnosed with colorectal cancer. This information is combined with other available datasets to provide a rich description of the care process and to minimise the burden of data collection on clinical staff.

The aim of the National Bowel Cancer Audit is to assess the quality of care received by patients with bowel cancer in England and Wales. Survival depends on early diagnosis through appropriate investigations, use of complicated surgical techniques and input from a range of professionals. The management of patients with this type of cancer is complex and requires multidisciplinary working. By collecting data from NHS Trusts providing care to bowel cancer patients the audit is able to provide outcomes on patient characteristics, treatment planning, postoperative outcomes and palliative treatment.

Bowel cancer is the third most common malignancy in the UK and affects approximately 33,000 people each year. Incidence is increasing and the prognosis for most patients diagnosed with bowel cancer remains poor.
HES data required for:
• Analysing patient follow up, such as emergency readmissions and stoma reversals.
• Audit-HES linked dataset used to investigate hospital utilisation and readmissions among patients with palliative treatment intent.
• Addressing the completion of chemotherapy among patients with palliative treatment intent.
• These outcomes are published in the Audit’s annual reports, which are used by trusts to assess whether they are meeting national guidance and benchmark their performance. If they are not then trusts will address and make improvements and this will then result in benefits to patients.

The National Bowel Cancer Audit is run by the Royal College of Surgeons (RCS) Clinical Effectiveness Unit (CEU) with data provision, management and publication provided by NHS Digital Clinical Audit and Registries Management Service (CARMS).

The request is also for HES data to be returned for patients who fit the inclusion criteria but are not included in Audit cohort.

The HES data with the Audit Tumour id is shared with the Clinical Effectiveness Unit of the Royal College of Surgeons for linking to the Audit data that they already hold. The Audit Tumour id is used for linkage purposes. The Audit Tumour ID key is held by NHS Digital CARMS.

Access to HES allows the Audit to substantially reduce the number of items from the bowel cancer dataset by retrieving relevant information on follow up and outcomes from Hospital Episode Statistics (dataset reduced from 130 plus data items to 43 data items since the audit has been linking to HES).

Death Data required for:
Date of Death will be linked to the Audit data to provide short-term and long-term survival outcomes so we can publish short-term and long-term mortality outcomes which evidence that patient survival is improving.

Place of Death (with NHS indicator code) will be used in analysis of the palliative care pathway, particularly whether patients die at home, the usual residence (if not home), in the hospital, or in another institutional setting. This will allow the Audit to provide national and trust level outcomes on end of life care.

Place of death will be in the form of a code from ONS known as Communal Establishment Code and will remove the potential of the address being identifiable to the patient.

Cause of Death will be used in analysis of whether patients are dying from their cancer or other causes.

An on-going part of the audit process commissioned by HQIP is the Clinical Outcomes Programme. The information from the audit is used to measure the performance of trusts and surgeons on the following 4 measures
• 90 day emergency readmission after major resection;
• 18 month stoma rate after major resection for rectal cancer;
• 90 day mortality after major resection;
• 24 month mortality after major resection.

Outliers at individual surgeon level and at trust level are identified through the analysis undertaken by the RCS CEU. Notifications are sent out for response by the individual surgeons and/ or the trusts (as applicable) and their responses are included in the annual report. To assist the trusts in evaluating the reasons for their outlier status, record level data for the relevant trust will be provided back to the trust upon request to NHS Digital. Data files for these requests will be provided in a 256 bit encrypted zip file to a named individual via NHS.net; the password for the file will be sent to another named individual nominated by the trust, again using NHS.net.

Whilst the provision of data back to trusts as part of the Clinical Outcomes Programme is not new, the ability to provide fact of death in relation to the 2 mortality indicators is a new element, which is supported by the CAG amendment approval letter.

Systemic Anti-Cancer Therapy (SACT) dataset required for:
The SACT data collection covers patients receiving cancer chemotherapy in or funded by the NHS in England. It relates to all cancer patients, both adult and paediatric, in acute inpatient, daycase, outpatient settings and delivery in the community. It covers chemotherapy treatment for all solid tumour and haematological malignancies and those in clinical trials.

Linkage will initially allow assessing the completeness of submissions of oncology records to the audit and explore whether the chemotherapy data items in the Audit could be dropped to ease the burden of data collection.
The request is also for SACT data to be returned for patients who fit the inclusion criteria but are not included in Audit cohort.

The SACT data with the Audit Tumour id is shared with the Clinical Effectiveness Unit of the Royal College of Surgeons for linking to the Audit data that they already hold. The Audit Tumour id is used for linkage purposes.

The Radiotherapy Dataset (RTDS) required for:
The RTDS holds information on every patient treated with radiotherapy funded by the National Health Service (NHS) in the UK.

Linkage will initially allow assessing the completeness of submissions of radiotherapy records to the audit and explore whether the radiotherapy data items in the Audit could be dropped to ease the burden of data collection.

The request is also for RTDS data to be returned for patients who fit the inclusion criteria but are not included in Audit cohort.

The RTDS data with the Audit Tumour id is shared with the Clinical Effectiveness Unit of the Royal College of Surgeons for linking to the Audit data that they already hold. The Audit Tumour id is used for linkage purposes.

National Emergency Laparotomy Audit (NELA) Dataset required for:
The NELA collects data on patients undergoing emergency laparotomy and is a Healthcare Quality Improvement Partnership funded Audit.
Linkage will initially allow the assessing of the patients submitted to the National Bowel Cancer Audit that have an emergency laparotomy.
The request is also for NELA data to be returned for patients who fit the inclusion criteria but are not included in the Audit cohort.

The NELA data with the Audit Tumour id is shared with the Clinical Effectiveness Unit of the Royal College of Surgeons for linking to the Audit data that they already hold. The Audit Tumour id is used for linkage purposes.


NHS England’s Cancer Patient Experience Survey Dataset required for:
The National Cancer Patient Experience collects information reported by patients themselves about the experience of their bowel cancer care.

Linkage would allow the assessing of how representative the Patient Reported Experience measure (PREMs) survey is of all groups of patients, including those not having a major resection and those receiving palliative and supportive care.

The request is for all the colorectal PREMs data to be sent to NHS Digital. The NHS number from the PREMs patients would be linked to the Audit data within NHS Digital.

The PREMs data with the Tumour id is shared with the Clinical Effectiveness Unit of the Royal College of Surgeons for linking to the Audit data that they already hold. The Audit Tumour id is used for linkage purposes.

The collection of PREMS data as part of this agreement is limited to prospective data from 2017 onwards, this follows a successful amendment request to CAG to address issues of notifying patients of the use of the data. This approval (outcome letter included in Evidence) supercedes the previous 2015 approval relating to use of retrospective PREMS data. The legal basis for the PROMS and PREMS linkage is the National Health Service Act 2006 - s251 - 'Control of patient information'. 2015 following a successful amendment request

NHS England’s National Cancer PROMs Programme of the National Survivorship Initiative Dataset required for:
NHS England’s National Cancer PROMs Programme of the National Survivorship Initiative collects information reported by patients themselves about the outcomes of their bowel cancer e.g. symptoms, functional status and quality of life.

Linkage would allow the assessing of the feasibility of using information reported by patients themselves about the outcomes of their bowel cancer.

The request is for all the colorectal PROMs data to be sent to NHS Digital. The NHS number from the PROMs patients would be linked to the Audit data within NHS Digital.

The PROMs data with the Tumour id is shared with the Clinical Effectiveness Unit of the Royal College of Surgeons for linking to the Audit data that they already hold. The Audit Tumour id is used for linkage purposes.

The collection of PROMS data as part of this agreement is limited to retrospective data only.

Welsh hospital episode data

The Patient Episode Database for Wales (PEDW) records all episodes of inpatient and day case activity in NHS Wales hospitals. This includes planned and emergency admissions, minor and major operations, and hospital stays for giving birth. Hospital activity for Welsh residents treated in hospitals in England is also included.
The data are collected and coded at each hospital. The records are then electronically transferred to the NHS Wales Informatics Service (NWIS), where they are validated and merged into the main database.

The request is also for PEDW data to be returned for patients diagnosed in Wales only who fit the inclusion criteria but are not included in Audit cohort.

The PEDW data with the Audit Tumour ID is shared with the Clinical Effectiveness Unit of the Royal College of Surgeons for linking to the Audit data that they already hold. The Audit Tumour ID only is used for linkage purposes.

Additional evidence has been added to this agreement in response to questions from IGARD (11.05.2017) about continued CAG support for the s251 approval relating to flow of PEDW data.


Intensive Care National Audit and Research Centre data:
The Intensive Care National Audit and Research Centre (ICNARC) hosts the case mix programme (CMP) from where NHS Digital will collect the data. The Case Mix Programme is an audit of patient outcomes from adult, general critical care units (intensive care and combined intensive care/high dependency units) covering England, Wales and Northern Ireland.

The CMP is listed in the Department of Health’s ‘Quality Accounts’ as a recognised national audit by the National Advisory Group on Clinical Audit & Enquiries (NAGCAE) for ‘Acute’ care.

Currently 100% of adult, general critical care units participate in the CMP. Other specialist units, including neurosciences, cardiac and high dependency units, also participate.

The CMP is open to both NHS (publically funded) and independent sector critical care units.

Critical care units collect data on all the patients they admit to their unit. They securely submit this data and the CMP team run over 600 validation checks, identifying errors and missing information. Units then have a chance to correct and complete the data before analyses.

ICNARC compare the data from these patients with the outcomes from other similar patients, other similar units and all the units in the CMP. The unit receives a Data Analysis Report which identifies trends over time showing how the unit compares with others and helps the unit understand more about the care they deliver. It aims to assist them in decision-making, resource allocation and local quality improvement.

The ICNARC data with the Audit Tumour ID is shared with the Clinical Effectiveness Unit of the Royal College of Surgeons for linking to the Audit data that is already held. The Audit Tumour ID only is used for linkage purposes.

Cancer Outcomes and Services Dataset (COSD)
COSD data when linked to National Bowel Cancer Audit (NBCA) data will be used to describe in further detail those patients with more advanced disease and rectal cancer and to assess the representativeness of patients captured in NBCA. This linkage will allow further investigation of the quality of the audit data and the opportunity to address concerns that there are cases of bowel cancer which are not being recorded in the audit. It is intended to use the data to assess the extent of possible missing data and any patterns relating to this, e.g. particular geographical areas under-reporting cases or any potential linkage to under presentation related to social deprivation. Linkage with COSD will enable the NBCA to further determine the pathway of care for patients with advanced disease and to describe in further detail the management and outcomes of patients with rectal cancer.

Cancer Registration Data
The Cancer Registration data will supplement the cases that are collected in COSD as Cancer Registration services undertake active case finding and will pick up cases of bowel cancer that have not been entered in to the NBCA. In order for the Audit to be able to report on the complete set of patients diagnosed with bowel cancer, records will be examined for patients who were identified in Cancer Registration data but who are not in NBCA. This will help to further assess the representativeness of patients captured in NBCA It is intended to use the data to assess the extent of possible missing data and any patterns relating to this, e.g. particular geographical areas under-reporting cases or any potential linkage to under presentation related to social deprivation.

Linkage to both COSD and Cancer Registration data will enhance the existing data collection to ensure that a full picture of the patient journey is collected for reporting purposes. The audit team will also look at the completeness of the collection of data items within COSD to assess whether any data items collected in the NBCA collection could be obtained from COSD in future years, thereby reducing the burden of collection on trusts going forwards. Linkage to the Cancer Registration data may also provide some options to reduce the collection burden in addition to providing information on the number of cases of bowel cancer which may be registered but are not included in the audit.

Yielded Benefits:

At national level the audit is able to report the following outcomes: - Overall 90-day mortality after major surgery has steadily reduced over five years from 5.4 per cent in 2010-11 to 3.8 per cent in 2014-15. - Two-year survival in patients having major surgery has improved from 80% in 2009-10 to 82% in 2012-13 - Rates of laparoscopic surgery have increased from 42% in 2010-11 to 61% in 2014-2015. There has been no rebound increase in rates of conversion from laparoscopic to open surgery over this time (9.0% to 8.5%) - The proportion of patients being seen by a clinical nurse specialist has increased from 87% in 2010-11 to 92% in 2014-15. - The rate of rectal cancer patients having a local excision to remove their cancer has increased from 5.3% in 2010-11 to 6.8% in 2014-15. Supporting local trust level improvement: - Since 2013, the audit has provided individual trust reports comparing results to the local and region and nationally. - In 2016, the audit started to provide MDTs with individualised slide packs of the trust results. 50% of MDTs reported using these. - Potentially outlying trusts report that they have carried out local quality improvement including case note review. - Clinical leads have reported taking their individual trust reports to their CEO to justify increased resources. Providing information to patients and the public - The 2016 patient friendly version of the annual report has had 474 downloads since the publication date in December 2016. - The Clinical Outcomes Publication data is published on NHS Choices. - The audit and the data in the reports are promoted to the public via bowel cancer charities.

Expected Benefits:

The Audit outcomes are published in annual reports, scientific journals and the consultant outcomes publications. The intended audience are clinicians, healthcare professionals, Medical Directors, CEs, audit managers, commissioners, NHS England, public and patients.

Trusts will use the outcomes in the annual reports to assess their care against national standards and benchmark against other trusts, make improvements which in turn will benefit patients. The Audit is able to identify and report the following year whether improvements have been made. The outputs will show whether the trusts are meeting national guidance such as NICE and whether there is any variation in the provision of care. The Audit outcomes such as 90-day post-operative mortality are risk-adjusted and any potential outlying trusts are identified as part of the Audit outlier policy. Trusts are notified that they are showing as an alarm and will investigate the cause; this can either be down to data quality issues or clinical practice. The trust will address the cause and either review the data submitted to the Audit or their clinical practice. Improvements in clinical practice have a direct impact on improvements in patient care.

The trust profiles are publically available, providing transparency and enabling patient choice.
Publishing 90-day post-operative mortality outcomes at individual consultant level provides transparency and enables patient choice.

Publishing in peer-reviewed journals will allow greater discussion of the strengths and weaknesses of the results, and will provide the benefit of peer-review of the work from third parties. The work is highly relevant to current clinical practice and publication will allow us to disseminate the findings widely amongst health professionals.

The SACT dataset would be linked to the audit dataset and would be used to assess completeness of submissions of oncology records to the audit and to explore whether the burden of data collection could be reduced by substituting audit items for items from the national chemotherapy dataset.

The RTDS dataset would be linked to the audit dataset and would be used to assess completeness of submissions of radiotherapy records to the audit and to explore whether the burden of data collection could be reduced by submitting audit items for items from the national radiotherapy dataset.

The NELA data will be linked to the National Bowel Cancer Audit data to provide further findings on emergency laparotomy patients and their treatments and outcomes.

Linkage to the Intensive Care data allows the Audit to report patterns of care and outcomes while patients were admitted to critical care. The Audit is able to examine the characteristics of the patients admitted to critical care.
The PROMs and PREMs data will be linked to the National Bowel Cancer Audit data to provide further findings on the feasibility of using information reported by patients themselves on the experience of their treatment and care the outcomes of their bowel cancer, and whether this can be incorporated into the National Audit.

The information from patients on how they rate their quality of life and treatment following their diagnosis for cancer will help the Health Service measure and improve the quality of future services and understand how the experience has affected patients’ longer term.

*******************************************amended text

Linkage to the COSD and Cancer Registration data will identify whether the Audit are missing cases and whether there is the potential for the NBCA to drop data items which could be collected via the COSD and potentially reduce the burden of data collection for trusts.

Linkage to the COSD will enable the NBCA to further explore and report on the management and outcomes of patients with rectal cancer and advanced disease.

Outputs:

Annual report
The National Bowel Cancer 2018 Annual report is targeted for publication in Autumn 2018. With publications in peer-reviewed journals in 2018.

Publication in peer-reviewed journals will allow presentation of the Audit methodology and results in more detail than in the Annual reports.

The Audit will provide national and trust level outcomes on end of life care.

The Audit will report on the feasibility of using information reported by patients themselves about the experience of their bowel cancer care and the feasibility of using information reported by patients themselves about the outcomes of their bowel cancer e.g. symptoms, functional status and quality of life.

Linking Date of Death to the Audit data will provide short-term and long-term survival outcomes.

The outputs are reported at National, Cancer Alliance and NHS Trust level. Examples of specific outputs are:
• Percentage of patients with surgical intent
• Percentage of patients with complications
• Risk adjusted 90-day post-operative mortality
• Risk adjusted 2 year mortality
• Risk adjusted complication rate
• Percentage of adequate lymph node resections
• Percentage of positive resection margin
• Length of stay
• Percentage of unplanned readmissions

The linked HES/Audit/death data dataset is also used to report the individual Consultant Outcomes as required by NHS England under Everyone Counts. The outcomes are 90-day post-operative mortality. The Consultant Outcomes are published on the Professional Body website and NHS Choices. The target date for delivery is Autumn 2018.
http://www.nhs.uk/Service-Search/Hospital/LocationSearch/7/Procedures?procedure=Gastrectomy
http://www.acpgbi.org.uk/surgeon-outcomes/

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

Linkage to ICNARC data will enable assessment of outcomes for patients that are cared for in intensive care following surgery to see if there are any differences in outcomes between different patient pathways. This will be progressed during 2017/18 with feasibility work once the data has been received from ICNARC.

Outputs from linkage to COSD and Cancer Registration data will relate to assessment of completeness of NBOCA data, assessment of missing cases and the potential to reduce the burden of collection in future years by using data from COSD and Cancer Registration and removing any duplication between these collections and the NBOCA dataset. This will be progressed during 2017/18 once the data request has been progressed with PHE Office of Data Requests and analysis will be included in outputs such as topic specific short reports or sections included in the next Annual Report.

If the linkage to COSD and Cancer Registration data identify data completeness and data quality issues then the NBCA will work with the Audit's Clinical Advisory Group and lead clinicians to encourage trusts to improve their data quality.

Outputs on the management of patients with rectal cancer and advanced disease will be included in the NBCA's annual report.

Processing:


Audit Tumour ID:

The Audit Tumour ID is a pseudonym, which is unique to each patient in the cohort. This primary key is used to reduce the flow of patient identifiers where data is requested from other data sets and where data is sent from CASU to CEU. The key is held by the NHS Digital CARMS team. The Audit Tumour ID is used for linkage to the HES, ONS, SACT, RTDS, NELA, PEDW, ICNARC, PROMs and PREMs data.

The Royal College of Surgeons Clinical Effectiveness Unit Audit Tumour ID which they use as a pseudonym. The CEU also receive Date of Death.

Processing activities:
1. All eligible NHS trusts submit data on their patients with bowel cancer to a system hosted by NHS Digital. This system holds data on patient characteristics, pre-treatment tumour stage, the staging process and the management plan of all patients and if appropriate data on process and outcomes of surgery, chemotherapy and radiotherapy. In keeping with minimum datasets and easing the burden on NHS staff, date of death, place of death and cause of death is not collected in the audit as it is recognised that this could be sought through the ONS. Date of death and place of death will be linked to the audit data to provide survival outcomes. Place of death will be in the form of a code from ONS known as Communal Establishment Code and will remove the potential of the address being identifiable to the patient.
2. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode ) are sent securely by the CARMS team to the data linkage team with an Audit Tumour ID (a pseudonym which is unique to each patient in the cohort) for linking to the HES data and also the DARS team for the death data.
3. HES data is returned to CARMS with only the Audit Tumour ID, none of the other patient identifiers are returned.
4. HES data is also returned for patients who fit the inclusion criteria but are not included in the Audit cohort.
5. Death data is returned to CARMS with only the Audit Tumour ID, none of the other patient identifiers are returned.
6. The HES data with the Audit Tumour ID and the Death data with the Audit Tumour ID are sent by the CARMS team to the Clinical Effectiveness Unit (CEU) of the Royal College of Surgeons for linking to the Audit data that they already hold having previously been sent from CARMS to the CEU. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.
7. The CEU then analyse the linked Audit/HES/death data dataset to produce statistical tables for inclusion in the outputs listed in the next section. The CEU will not make record level information available to any other party. The CEU will only use the data for the stated purposes.


Linkage to the SACT dataset:
1. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode) are sent by the CARMS team to the Chemotherapy Intelligence Unit within Public Health England. An Audit Tumour ID (a pseudonym which is unique to each patient in the cohort) is also sent to the Chemotherapy Intelligence Unit.
2. SACT data is returned to the CARMS team with only the Audit Tumour ID, none of the other patient identifiers are returned.
3. SACT data is also returned for patients who fit the inclusion criteria but are not included in the Audit cohort.
4. The SACT data with the Audit Tumour ID are sent by the CARMS team to the Clinical Effectiveness Unit (CEU) of the Royal College of Surgeons for linking to the Audit data that they already hold having previously been sent from CARMS to the CEU. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.
The CEU then analyse the linked Audit/SACT dataset to produce statistical tables for inclusion in the outputs listed in the next section. The CEU will not make record level information available to any other party. The CEU will only use the data for the stated purposes.


Linkage to the RTDS dataset:
1. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode) are sent by the CARMS team to the Office for Data Release (ODR), Public Health England
2. An Audit Tumour ID (a pseudonym which is unique to each patient in the cohort) is also sent to the Office for Data Release (ODR), Public Health England
3. RTDS data is returned to CARMS with only the Audit Tumour ID, none of the other patient identifiers are returned.
4. RTDS data is also returned for patients who fit the inclusion criteria but are not included in the Audit cohort.
5. The RTDS data with the Audit Tumour ID are sent by CARMS to the Clinical Effectiveness Unit (CEU) of the Royal College of Surgeons for linking to the Audit data that they already hold having previously been sent from CARMS to the CEU. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.
The CEU then analyse the linked Audit/RTDS dataset to produce statistical tables for inclusion in the outputs listed in the next section. The CEU will not make record level information available to any other party. The CEU will only use the data for the stated purposes.


Linkage to the NELA dataset:
1. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode ) are sent by the CARMS team to the National Institute of Academic Anaesthesia's Health Services Research Centre
2. An Audit Tumour ID (a pseudonym which is unique to each patient in the cohort) is also sent to the National Institute of Academic Anaesthesia's Health Services Research Centre.
3. NELA data is returned to the CARMS team with only the Audit Tumour ID, none of the other patient identifiers are returned.
4. NELA data is also returned for patients who fit the inclusion criteria but are not included in the Audit cohort.
5. The NELA data with the Audit Tumour ID are sent by CARMS to the Clinical Effectiveness Unit (CEU) of the Royal College of Surgeons for linking to the Audit data that they already hold having previously been sent from CARMS to the CEU. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.
The CEU then analyse the linked Audit/NELA dataset to produce statistical tables for inclusion in the outputs listed in the next section. The CEU will not make record level information available to any other party. The CEU will only use the data for the stated purposes.


Linkage to the NHS England’s Cancer Patient Experience Surveys
1. Audit Patient Identifiers (NHS number) are sent by the CARMS team to Public Health England.
2. An Audit Tumour ID (a pseudonym which is unique to each patient in the cohort) is also sent to PHE.
3. PREMs data is returned to the CARMS team with only the Audit Tumour ID, none of the other patient identifiers are returned.
4. PREMS data is also returned for patients who fit the inclusion criteria but are not included in the Audit cohort.
5. The PREMs data with the Audit Tumour ID are sent by the Clinical Audit Support Unit to the Clinical Effectiveness Unit (CEU) of the Royal College of Surgeons for linking to the Audit data that they already hold having previously been sent from CARMS to the CEU. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.


Linkage to NHS England’s National Cancer PROMs Programme of the National Survivorship Initiative.
1. Audit Patient Identifiers (NHS number) are sent by the CARMS team to the National Cancer Registration and Analysis Service (NCRAS), hosted by PHE.
2. An Audit Tumour ID (a pseudonym which is unique to each patient in the cohort) is also sent to NCRAS.
3. PROMs data is returned to CARMS with only the Audit Tumour ID, none of the other patient identifiers are returned.
4. PROMS data is also returned for patients who fit the inclusion criteria but are not included in the Audit cohort.
The PROMs data with the Audit Tumour ID are sent by CARMS to the Clinical Effectiveness Unit (CEU) of the Royal College of Surgeons for linking to the Audit data that they already hold having previously been sent from CARMS to the CEU. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.

Linkage to the Patient Episode Database for Wales (PEDW) dataset (from NHS Wales Informatics Service NWIS)

The audit will use the Hospital Site code where the patient was diagnosed; this tells the audit where the patient were diagnosed. If that is in Wales the audit will then pull the NHS number, Date of Birth, Sex and Postcode to send the relevant cohort to NWIS. There is a risk that the patients are diagnosed in Wales but are resident in England and go on to receive treatment elsewhere. In which case the audit won't get any further information on those patients from PEDW.

1. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode ) are sent by CARMS to NWIS only for patients identified as being diagnosed in Wales. The full audit cohort will not be sent to NWIS at any time. An Audit Tumour ID (a pseudonym which is unique to each patient in the cohort) is also sent to the NWIS
2. PEDW data is returned to CARMS with only the Audit Tumour ID, none of the other patient identifiers are returned.
3. PEDW data is also returned for patients who fit the inclusion criteria but are not included in the Audit cohort.
4. The PEDW data with the Audit Tumour ID are sent by CARMS to the Clinical Effectiveness Unit (CEU) of the Royal College of Surgeons for linking to the Audit data that they already hold having previously been sent from CARMS to the CEU. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.

The CEU then analyse the linked Audit/PEDW dataset to produce statistical tables for inclusion in the outputs listed in the next section. The CEU will not make record level information available to any other party. The CEU will only use the data for the stated purposes.

Additional evidence has been added to this agreement in response to questions from IGARD (11.05.2017) about continued CAG support for the s251 approval relating to flow of PEDW data.

Intensive Care National Audit and Research Centre data:
Linkage to Intensive Care National Audit and Research Centre (ICNARC) dataset:
1. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode ) are sent by CARMS to ICNARC. An Audit Tumour ID (a pseudonym which is unique to each patient in the cohort) is also sent to INCARC
2. ICNARC data is returned to CARMS with only the Audit Tumour ID, none of the other patient identifiers are returned.
3. The ICNARC data with the Audit Tumour ID are sent by NHS Digital CARMS to the Clinical Effectiveness Unit (CEU) of the Royal College of Surgeons for linking to the Audit data that they already hold having previously been sent from CARMS to the CEU. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.
The CEU then analyse the linked Audit/ICNARC dataset to produce statistical tables for inclusion in the outputs listed in the next section. The CEU will not make record level information available to any other party. The CEU will only use the data for the stated purposes.


Cancer Outcomes and Services Dataset
Linkage to Cancer Outcomes and Services Dataset
1. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode) are sent by NHS Digital CARMS team to the Office for Data Release (ODR), Public Health England. An Audit Tumour ID is also sent to the Office for Data Release (ODR), Public Health England
2. COSD data is returned to NHS Digital CARMS Team with only the Audit Tumour ID, none of the other patient identifiers are returned.
3. The COSD data with the Audit Tumour ID are sent by CARMS to the Clinical Effectiveness Unit (CEU) of the Royal College of Surgeons for linking to the Audit data that they already hold having previously been sent from CARMS to the CEU. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.
The CEU then analyse the linked Audit/COSD dataset to produce statistical tables for inclusion in the outputs listed in the next section. The CEU will not make record level information available to any other party. The CEU will only use the data for the stated purposes.

Cancer Registration data
Linkage to Cancer Registration data
1. Audit Patient Identifiers (NHS number, Date of Birth, Sex and Postcode) are sent by the CARMS team to the Office for Data Release (ODR), Public Health England. An Audit Tumour ID is also sent to the Office for Data Release (ODR), Public Health England.
2. Cancer Registration data is returned to CARMS with only the Audit Tumour ID, none of the other patient identifiers are returned.
3. Cancer Registration data is also returned for patients who fit the inclusion criteria but are not included in the Audit cohort.
4. The Cancer Registration data with the Audit Tumour ID are sent by CARMS to the Clinical Effectiveness Unit (CEU) of the Royal College of Surgeons for linking to the Audit data that they already hold having previously been sent from CARMS to the CEU. The Audit Tumour ID is used as a pseudonym to allow linkage of the datasets.
The CEU then analyse the linked Audit/ Cancer Registration dataset to produce statistical tables for inclusion in the outputs listed in the next section. The CEU will not make record level information available to any other party. The CEU will only use the data for the stated purposes.


The data requested is to be used for the performance of services under contract to the Healthcare Quality Improvement Partnership (HQIP). All Intellectual Property Rights in any guidance, specifications, instructions, toolkits, plans, data, drawings, databases, patents, patterns, models, design or other material, furnished or made available to the Health and Social Care Information Centre as part of this request remains vested solely in HQIP. This IPR is in turn vested to NHS England through HQIP’s headline contract with them’

ONS terms and conditions relating to the data being shared under this agreement will be adhered to.

The Bowel Cancer Audit has been continuous since 2002 and data is retained from that time up to the present. The data is retained so that any queries about previously published reports can be queried.

The audit reports on patients over the most recent 5 years. A refresh of data is required for the most recent 10 years. This is to provide the most up-to-date information on patients diagnosed during this 5-year reporting period, with 5 years’ preceding HES data to ensure that patients with a historic diagnosis of bowel cancer are not included as primary bowel cancer diagnoses. Data will be retained for 5 years after the end of the contract to allow queries about previously published results to be answered, and to ensure consistency checks can be carried out over multiple data extracts. This is In line with DH data retention requirements. The previous 5 years would only be used in the event of queries relating to previous audit years and the published annual reports from these years.



DSA with NHS Digital to enable the Cancer Alliance to access the CWT system — DARS-NIC-415025-V8S5S

Type of data: Pseudonymised

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information', NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, This agreement is for the Somerset, Wiltshire, Avon and Gloucestershire Cancer Alliance (SWAG) Cancer Alliance to access Cancer Waiting Times data. However as the Cancer Alliance is not a legal entity, as staff are substantially employed by NHS England, who are therefore the lead organisation, and the data controller who processes data. In this agreement therefore, all references to accessing patient level data refer to the legal entity – NHS South Central and West Commissioning Support Unit (listed as a processor) are also part of the legal entity NHS England and are permitted to process the data. Within NHS England are seven regions who support local systems to provide more joined up and sustainable care for patients. The regional teams are responsible for the quality, financial and operational performance of all NHS organisations in their region, drawing on the expertise and support of our corporate teams to improve services for patients and support local transformation. 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 Taskforces 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. 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. Cancer alliances are also created to drive improvement in cancer outcomes. Align with the improvement trajectory set for cancer survival (also part of CCG IAF), cancer alliances are set to deliver the Faster Diagnostic Standards (FDS) from April 2021 (delayed from April 2020). FDS is part of CWT dataset, referring to the duration between urgent GP referral to patients being told whether they have a cancer diagnosis or not. The National Cancer Programme has confirmed that FDS, along with 62-day wait, will be key metrics within the 10 year NHS Plan that Cancer Alliances will be held accountable to. Thus without access to the data as outlined in this request, the Cancer Alliance will not be able to deliver work programme as outlined by the National Cancer Programme. The Cancer Alliance will directly access the Cancer Waiting Times System on behalf of alliance member trusts and CCGs. SWAG Cancer Alliance works with health organisations across Somerset, Wiltshire, Avon and Gloucestershire including 7 acute providers and 4 CCGs Acute Providers Gloucestershire Hospitals NHS Foundation Trust North Bristol NHS Trust Royal United Hospitals Bath NHS Foundation Trust Salisbury NHS Foundation Trust Somerset NHS Foundation Trust Yeovil District Hospital NHS Foundation Trust CCGs NHS Bristol, North Somerset and South Gloucestershire CCG NHS Bath, Swindon and Wiltshire CCG NHS Gloucestershire CCG NHS Somerset CCG Data access The CWT system provides the Data Controller / Processor 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 organisation will only access patient records which fall within the Cancer Alliances' footprint of responsibility based on the patients' CCG of responsibility. 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 The Data Controller routinely monitors 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 Approved users 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. The Cancer Alliance will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements. The Cancer Alliance'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. Lead organisations 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 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 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. 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 c. 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. (Network, internal NHS transfer)

Sensitive: Sensitive

When:DSA runs 2020-11-30 — 2023-11-29 2021.11 — 2023.01.

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: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)

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 2021.
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 April 2021 (delayed from April 2020). Trusts are asked to ensure high level of data completeness for this item in 2019/20.

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 pathway and resulting improvements.

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 NHS England will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the NHS England 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 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).

SWAG 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 UCLH 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 NHS.net email accounts.

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 Improvement and NHS England.

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. As well as the percentage of 62 Day performance, we will also need to look at number of activities, total numbers of patients treated, number of patients treated before and after Day 62
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 (e.g., activity and breach share by first seen trust and treatment trust, and by tumour site)
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, by tumour site (e.g. median pathway durations, and the ability to track changes over time with "run charts" as per NHS Improvement requirements)
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 patients 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.

Peninsula Cancer Alliance CWT Data Sharing Agreement and CADEAS Data — DARS-NIC-406632-X0L2M

Type of data: Pseudonymised

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information', NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, This agreement is for the Peninsula Cancer Alliance Cancer Alliance to access Cancer Waiting Times data. However as the Cancer Alliance is not a legal entity, NHS England is therefore the lead organisation, and the data controller who processes data. In this agreement therefore, all references to accessing patient level data refer to the legal entity – NHS England. NHS South Central and West Commissioning Support Unit (listed as a processor) are permitted to process the data. Within NHS England are seven regions who support local systems to provide more joined up and sustainable care for patients. The regional teams are responsible for the quality, financial and operational performance of all NHS organisations in their region, drawing on the expertise and support of our corporate teams to improve services for patients and support local transformation. 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 Taskforces 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. 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. Cancer alliances are also created to drive improvement in cancer outcomes. Align with the improvement trajectory set for cancer survival (also part of CCG IAF), cancer alliances are set to deliver the Faster Diagnostic Standards (FDS) from April 2021 (delayed from April 2020). FDS is part of CWT dataset, referring to the duration between urgent GP referral to patients being told whether they have a cancer diagnosis or not. The National Cancer Programme has confirmed that FDS, along with 62-day wait, will be key metrics within the 10 year NHS Plan that Cancer Alliances will be held accountable to. Thus without access to the data as outlined in this request, Peninsula Cancer Alliance will not be able to deliver work programme as outlined by the National Cancer Programme. Peninsula Cancer Alliance will directly access the Cancer Waiting Times System on behalf of alliance member trusts and CCGs Peninsula Cancer Alliance works with health organisations across Devon and Cornwall However as the Cancer Alliance is not a legal entity, as staff are substantially employed by NHS England, who are therefore the lead organisation, and the data controller who processes data. In this agreement therefore, all references to accessing patient level data refer to the legal entity – NHS South Central and West Commissioning Support Unit (listed as a processor) are also part of the legal entity NHS England and are permitted to process the data. 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 Taskforces 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. 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. Cancer alliances are also created to drive improvement in cancer outcomes. Align with the improvement trajectory set for cancer survival (also part of CCG IAF), cancer alliances are set to deliver the Faster Diagnostic Standards (FDS) from April 2021 (delayed from April 2020). FDS is part of CWT dataset, referring to the duration between urgent GP referral to patients being told whether they have a cancer diagnosis or not. The National Cancer Programme has confirmed that FDS, along with 62-day wait, will be key metrics within the 10 year NHS Plan that Cancer Alliances will be held accountable to. Thus without access to the data as outlined in this request, the Cancer Alliance will not be able to deliver work programme as outlined by the National Cancer Programme. The Cancer Alliance will directly access the Cancer Waiting Times System on behalf of alliance member trusts and CCGs The Cancer Alliance works with health organisations across Devon and Cornwall including the acute providers and CCG's listed below- Acute Providers • Northern Devon Healthcare NHS Trust • Plymouth Hospitals NHS Trust • Royal Cornwall Hospitals NHS Trust • Royal Devon & Exeter NHS Foundation Trust • Torbay & South Devon Foundation NHS Trust Clinical Commissioning Groups (CCGs) • NHS Bath and North East Somerset, Swindon and Wiltshire CCG • NHS Kernow • NHS Devon CGG Data access The CWT system provides the Data Controller / Processor 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 organisation will only access patient records which fall within the Cancer Alliances' footprint of responsibility based on the patients' CCG of responsibility. 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 The Data Controller routinely monitors 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 Approved users 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. The Cancer Alliance will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements. The Cancer Alliance'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. Lead organisations 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 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 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. 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 c. 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. (Network, internal NHS transfer)

Sensitive: Sensitive

When:DSA runs 2021-03-31 — 2024-03-31 2021.11 — 2023.01.

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: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)

Objectives:

This agreement is for the Peninsula Cancer Alliance Cancer Alliance to access Cancer Waiting Times data.

However as the Cancer Alliance is not a legal entity, NHS England is therefore the lead organisation, and the data controller who processes data. In this agreement therefore, all references to accessing patient level data refer to the legal entity – NHS England. NHS South Central and West Commissioning Support Unit (listed as a processor) are permitted to process the data.

Within NHS England are seven regions who support local systems to provide more joined up and sustainable care for patients. The regional teams are responsible for the quality, financial and operational performance of all NHS organisations in their region, drawing on the expertise and support of our corporate teams to improve services for patients and support local transformation.

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 Taskforces 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.

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.

Cancer alliances are also created to drive improvement in cancer outcomes. Align with the improvement trajectory set for cancer survival (also part of CCG IAF), cancer alliances are set to deliver the Faster Diagnostic Standards (FDS) from April 2021 (delayed from April 2020). FDS is part of CWT dataset, referring to the duration between urgent GP referral to patients being told whether they have a cancer diagnosis or not.

The National Cancer Programme has confirmed that FDS, along with 62-day wait, will be key metrics within the 10 year NHS Plan that Cancer Alliances will be held accountable to. Thus without access to the data as outlined in this request, Peninsula Cancer Alliance will not be able to deliver work programme as outlined by the National Cancer Programme. Peninsula Cancer Alliance will directly access the Cancer Waiting Times System on behalf of alliance member trusts and CCGs

Peninsula Cancer Alliance works with health organisations across Devon and Cornwall However as the Cancer Alliance is not a legal entity, as staff are substantially employed by NHS England, who are therefore the lead organisation, and the data controller who processes data. In this agreement therefore, all references to accessing patient level data refer to the legal entity – NHS South Central and West Commissioning Support Unit (listed as a processor) are also part of the legal entity NHS England and are permitted to process the data.

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 Taskforces 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.

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.

Cancer alliances are also created to drive improvement in cancer outcomes. Align with the improvement trajectory set for cancer survival (also part of CCG IAF), cancer alliances are set to deliver the Faster Diagnostic Standards (FDS) from April 2021 (delayed from April 2020). FDS is part of CWT dataset, referring to the duration between urgent GP referral to patients being told whether they have a cancer diagnosis or not.

The National Cancer Programme has confirmed that FDS, along with 62-day wait, will be key metrics within the 10 year NHS Plan that Cancer Alliances will be held accountable to. Thus without access to the data as outlined in this request, the Cancer Alliance will not be able to deliver work programme as outlined by the National Cancer Programme. The Cancer Alliance will directly access the Cancer Waiting Times System on behalf of alliance member trusts and CCGs

The Cancer Alliance works with health organisations across Devon and Cornwall including the acute providers and CCG's listed below-

Acute Providers
• Northern Devon Healthcare NHS Trust
• Plymouth Hospitals NHS Trust
• Royal Cornwall Hospitals NHS Trust
• Royal Devon & Exeter NHS Foundation Trust
• Torbay & South Devon Foundation NHS Trust

Clinical Commissioning Groups (CCGs)
• NHS Bath and North East Somerset, Swindon and Wiltshire CCG
• NHS Kernow
• NHS Devon CGG

Data access

The CWT system provides the Data Controller / Processor 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 organisation will only access patient records which fall within the Cancer Alliances' footprint of responsibility based on the patients' CCG of responsibility.

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

The Data Controller routinely monitors 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

Approved users 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.

The Cancer Alliance will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements.

The Cancer Alliance'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. Lead organisations 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 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 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. 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
c. 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:

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 2021.
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 April 2021 (delayed from April 2020). Trusts are asked to ensure high level of data completeness for this item in 2019/20.

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 pathway and resulting improvements.

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 will directly access or download extracts from the Cancer Waiting Times system. 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 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 a secure connection and will use a Single Sign-On (users are prompted to create a unique username and password).

Approved 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 Data Controller or Data Processor 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 shared with other members of the cancer alliance in aggregated form (without small number suppression).

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 Improvement and NHS England.

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. As well as the percentage of 62 Day performance, we will also need to look at number of activities, total numbers of patients treated, number of patients treated before and after Day 62
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 (e.g., activity and breach share by first seen trust and treatment trust, and by tumour site)
d. Analysis of 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, by tumour site (e.g. median pathway durations, and the ability to track changes over time with "run charts" as per NHS Improvement requirements)
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 patients 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.

Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204512-H4R8C

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

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', NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, This agreement is for the Northern Cancer Alliance to access Cancer Waiting Times data. The purpose for which the data is processed under this agreement is determined by the cancer alliance. However, the Cancer Alliance is not a legal entity - its staff (and those accessing the Cancer Waiting Times data) are substantively employed by NHS England. NHS England 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 - NHS England. This agreement follows a National Cancer Waiting Times Monitoring Dataset - Cancer Alliance specific template. 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 Taskforces 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. 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. Cancer alliances are also created to drive improvement in cancer outcomes. Align with the improvement trajectory set for cancer survival (also part of CCG IAF), cancer alliances are set to deliver the Faster Diagnostic Standards (FDS) from April 2021 (delayed from April 2020). FDS is part of CWT dataset, referring to the duration between urgent GP referral to patients being told whether they have a cancer diagnosis or not. The National Cancer Programme has confirmed that FDS, along with 62-day wait, will be key metrics within the 10 year NHS Plan that Cancer Alliances will be held accountable to. Thus without access to the data as outlined in this request, the Cancer Alliance will not be able to deliver work programme as outlined by the National Cancer Programme. The Cancer Alliance will directly access the Cancer Waiting Times System on behalf of alliance member trusts and CCGs. The Northern Cancer Alliance works with health organisations across North Cumbria, North East England (Northumberland, Tyne & Wear, Co Durham, Teesside) and North Yorkshire. At the point of signing this includes 9 acute providers, 11 clinical commissioning groups, and 13 hospices. These numbers may change during the lifetime of the agreement due to alterations in the geographical responsibility of the Cancer Alliances and organisational splits and/or mergers. Data access The CWT system provides the Data Controller / Processor 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 organisation will only access patient records which fall within the Cancer Alliances' footprint of responsibility based on the patients' CCG of responsibility. 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 The Data Controller routinely monitors 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 Approved users 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. The Cancer Alliance will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements. The Cancer Alliance'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. Lead organisations 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 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 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. 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 c. 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. (Area Team, Network, internal NHS transfer)

Sensitive: Sensitive

When:DSA runs 2019-07-01 — 2022-06-30 2019.09 — 2023.01.

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: NHS ENGLAND (QUARRY HOUSE)

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 Northern 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 NHS England. NHS England 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 - NHS England.

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.


Northern Cancer Alliance

NHS England will directly access the Cancer Waiting Times System for the Northern Cancer Alliance region, which covers a population of 3.2 million people.

The Northern Cancer Alliance works with health organisations across North Cumbria, North East England (Northumberland, Tyne & Wear, Co Durham, Teesside) and North Yorkshire including 9 acute providers, 12 clinical commissioning groups, and 13 hospices.

Acute Providers

South Tyneside Healthcare NHSFT (RE9)
City Hospitals Sunderland NHSFT (RLN)
North Cumbria University Hospitals NHST (RNL)
Gateshead Healthcare NHSFT (RR7)
The Newcastle upon Tyne Hospitals NHSFT (RTD)
Northumbria Health Care NHSFT (RTF)
South Tees Hospitals NHSFT (RTR)
North Tees & Hartlepool NHSFT (RVW)
Co Durham & Darlington NHSFT (RXP)

CCGs
Darlington (00C)
Durham Dales, Easington & Sedgefield (00D)
North Durham (00J)
Hartlepool & Stockton on Tees (00K)
Northumberland (00L)
South Tees (00M)
South Tyneside (00N)
Sunderland (00P)
North Cumbria (01H)
Hambleton, Richmondshire & Whitby (03D)
Newcastle Gateshead (13T)
North Tyneside (99C)

Hospices

• St Oswald’s, Newcastle upon Tyne
• St Teresa’s, Darlington
• Teesside Hospice, Middlesbrough
• St Cuthbert’s Hospice, Durham
• Willow Burn Hospice, Lanchester
• North Northumberland Hospice Care, Alnwick
• Tynedale Hospice at Home, Hexham
• St Clare’s, Jarrow
• Alice Hospice, Hartlepool
• Butterwick, Bishop Auckland
• Eden Valley, North Cumbria
• Marie Curie – Newcastle
• Saint Benedict’s Hospice, Sunderland



Data access

The CWT system provides one organisation (NHS England) 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 North Cumbria, North East England and North Yorkshire 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
Lead organisations 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.

Lead organisations will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements.

Lead organisations 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. Lead organisations 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 NHS England will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the NHS England 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 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).

NHS England 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 Northern Cancer Alliance 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 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 CCGs 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 NHS England 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.

NHS England - Infections & Antimicrobial Resistance (AMR) Trusted Research Environment — DARS-NIC-448252-L2R6Q

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information', NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, (Agency/Public Body, internal NHS transfer)

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

When:DSA runs 2021-05-24 — 2022-05-23 2021.05 — 2023.01.

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

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Hospital Episode Statistics Admitted Patient Care
  3. Hospital Episode Statistics Critical Care
  4. Hospital Episode Statistics Outpatients
  5. Medicines dispensed in Primary Care (NHSBSA data)
  6. Civil Registration - Deaths
  7. Community Services Data Set
  8. Electronic Prescribing and Medicines Administration (EPMA) data in Secondary Care for COVID-19
  9. GPES Data for Pandemic Planning and Research (COVID-19)
  10. Emergency Care Data Set (ECDS)
  11. Civil Registrations of Death
  12. Community Services Data Set (CSDS)
  13. Hospital Episode Statistics Accident and Emergency (HES A and E)
  14. Hospital Episode Statistics Admitted Patient Care (HES APC)
  15. Hospital Episode Statistics Critical Care (HES Critical Care)
  16. Hospital Episode Statistics Outpatients (HES OP)
  17. COVID-19 Electronic Prescribing and Medicines Administration (ePMA) in Secondary Care
  18. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)

Objectives:

Background:

The World Health Organisation (WHO) has declared that Antimicrobial Resistance (AMR) is one of the top 10 global public health threats facing humanity. For this reason, in January 2019 the UK Government published a 5 Year UK Antimicrobial Resistance (AMR) National Action Plan (NAP) alongside a UK AMR 20 Year Vision Paper.

Every year in England:
- GPs prescribe 33.7 million course of antibiotics to patients
- A third of all inpatients, at any one time, are on antibiotic treatment
- Intravenous antibiotic prescriptions since 2021 have increased by 100% in Emergency departments and 6% in hospital wards since the focus on sepsis
- Over 90% of clinicians, when questioned, admit to giving ‘just in case’ antibiotics

More so, there is an emerging threat of pan-antibiotic resistance and equally slow growth and/or development of new treatments.

The purpose of the Antimicrobial Resistance (AMR) programme is therefore to work collaboratively to deliver on the following ambitions set out in the 5 Year NAP:
1) halve the number of healthcare-associated Gram-negative Bloodstream Infections, delivering a 25% reduction by 2021-2022 and the full 50% by 2023-2024.
2) reduce the number of specific drug-resistant infections in people by 10% by 2025
3) reduce UK antimicrobial use in humans by 15% by 2024
4) reduce community antimicrobial use by 25% by 2024

The above commitments are required due to:

● The growing burden on bloodstream infections (BIS) on health services and the need to understand better ways of preventing and managing BIS so as to improve outcomes and reduce costs
● The rate and frequency at which antimicrobials (antibiotics) are being prescribed and the need to encourage appropriate and proportionate use (including public messaging)

In turn, in order to achieve the above ambitions, there is a pivotal need for data relating to infection rates associated with AMR to be linked and the outputs, in due course, made available directly to NHS England (NHSE) so that NHSE can develop a dashboard service for NHSE AMR stakeholders who form part of the wider programme and NHS system. Key stakeholders include NHSE central and regional teams, CCGs, Integrated Care Systems, clinicians (primary and secondary care), providers and Public Health England (PHE).

The NHSE Medical Director, is the SRO for the Human Health elements of the NAP and so NHSE has a direct role in implementing the plan and in supporting partner organisations to implement key actions which fall within their responsibilities, including providing data to inform this work.

Context:

To do this, NHSE has so far undertaken an initial discovery phase of work by commissioning NHS Digital to design, develop and deliver a Trusted Research Environment (TRE) by end of March 2021, that enables national datasets relating to AMR to be imported to the TRE, the associated data linked and made available via a dashboard functionality prototype. NHS Digital are not determining the purpose or means of this agreement.

This has, for the first time, provided an environment to explore how national, patient level, linked datasets can be used to support AMR work.

The intention of a business intelligence dashboard tool in the longer term is primarily to:

a) Show performance at local, regional and national level, with a view to informing strategy development;
b) Support clinicians and pharmacists, with a view to understanding prescribing and outcomes and using that to inform clinical decisions for individual patients;

Status:

The initial discovery work ended on 31st March 2021.
The next post-discovery phase requires that NHSE staff, with NHSE as Data Controller, access the tools and data in the TRE to understand next steps.

This is so that NHSE analysts are able to analyse and manipulate the data in the TRE, so to inform, develop and implement a more permanent operating model during FY 21/22, whereby NHSE can build and develop a reliable stream of intelligence in line with the AMR programme’s needs and in line with the healthcare commitments set out in the 5 year National Action Plan.

This application is for the post-discovery phase only, to grant access to the NHS Digital TRE environment, to enable NHSE to gain a sufficient understanding of the data to shape development of the future operating model.

No other organisations other than NHSE will access or be involved in processing the data (other than NHS Digital staff who will provide support to the NHSE users).

Amendments to this agreement will follow once NHSE have had opportunity to further refine requirements in respect of the data and the processing that is required.

NHS England are processing the data being accessed under this agreement as part of the public task around research under Article 6(1)(e) and 9(2)(j) of the GDPR so as to undertake public health monitoring and statistics, in the public’s interest.
Data will only ever be used for purposes relating to healthcare or the promotion of health in line with the requirements of the Health and Social Care Act 2012 as amended by the Care Act 2014.

It is within the public interest because NHS England are required to be able to plan and deliver on the commitments set out in the UK AMR 5 Year National Action Plan, NHSE need to have reliable, detailed data about people susceptible to infection and or whom get an infection, alongside detailed data regarding treatment of infection and sepsis across community, primary and secondary care so as to effectively manage the delicate balance between infection treatment and antimicrobial resistance (i.e. the process of becoming resistant to antibiotics due over prescription/inappropriate usage of antibiotics).

Expected Benefits:

The anticipated benefits of this work are as follows:

• Clear understanding of the utility of the data to support the AMR programme aims, and identification of any gaps or issues
• Clear understanding of the utility of the data to support the future operating model, and identification of any gaps or issues
• The work will support development of an appropriate service design, such that in the longer term useful analysis can be shared with appropriate audiences in order to improve outcomes for patients
• This work will also deliver a roadmap for further development of the linked data, including the addition of more data assets which, if implemented, will further enrich understanding and improve outcomes

In the long-term, it is intended that access to the data will give NHSE the ability to develop a mechanism for viewing at different organisational and/or geographical levels a series of linked data items covering key factors which impact upon successful infection management and the management of antimicrobial resistance, in order to identify the key factors, locally, regionally or nationally, which are impacting upon poorer outcomes, and so inform where improved clinical practice or service delivery arrangements need to be considered.

The ultimate aims of the overarching project are to address the global problem of antibiotic resistance and facilitate clear communication and reassurance to the public on the use or non-use of antibiotics.

Outputs:

NHS Digital developers will collaborate with NHSE registered users to produce static visualisations of the data, which will be shared with AMR programme stakeholders in order to demonstrate the continuing value of the work being undertaken. These static visualisations will not contain record level data, they will show aggregated data with small numbers supressed. They will support the purpose described above, and contribute to the understanding of the value of the data, but will not themselves be used as part of a service.

Access to the pseudonymised record level data is expected to provide NHSE with a sufficient level of understanding of the data, to inform the plan for development of a dashboard service in the near future in line with delivering the commitments set out in the 5 year UK AMR National Action Plan (NAP).

The outputs from this initial stage will enable more robust stakeholder engagement in term of developing next steps.

Processing:

The datasets and the reason for requiring access to this national data within the TRE are:

● Hospital Episodes Statistics (HES): to identify admissions, diagnoses and other clinical information relating to patients with an infection
● Medicines dispensed in Primary Care (NHSBSA data): to identify key data regarding prescriptions for antibiotics
● Civil Registration Deaths: to identify mortality rates and reasons for mortality
● Community Services Data Set: to address health inequalities by monitoring outcomes

By linking and enabling access to the above data, NHSE will have a much richer source of intelligence of patients with infections and use of antimicrobial treatment, so as to support the government’s ambitions in the UK 5 year National Action Plan (NAP). The purpose is as follows:

• To assess the utility of the data to support the future operating model
• To assess the utility of the data to support the testing of hypotheses and discovery of new trends, for example:
o relating to cause of deterioration of admitted patients
o relating to management of infection along a full patient pathway between different care settings
o relating to antibiotic prescribing and its impact on the management of infection

No data will flow outside of NHS Digital.

The data within the TRE will be pseudonymised.

No identifiable data will be accessible within the TRE.

The NHS Digital Portal (TRE) system is hosted and access is audited by NHS Digital to ensure that use is appropriate and in line with the terms agreed in the Data Sharing Agreement.

NHSE substantive employees are only able to access the datasets detailed within this agreement. Access to the datasets detailed within this agreement is within the NHS Digital TRE.

All NHSE users will comply with the use of the data as specified in this agreement. Only registered TRE users will be able to access the TRE.

The NHSE analytical team will analyse and manipulate the data, in line with the purposes listed above only.

The data will be processed for the purposes described in this agreement.

Registered NHSE employees who are granted access to the TRE, will be supported in their use of the data by NHS Digital staff who have appropriate approved access to the data.
The NHSE Medical Director is the SRO for overseeing delivery of the Human Heath elements of the cross-government UK AMR National Action Plan (NAP). A number of workstreams have been set up by NHSE to support delivery of these elements. These workstreams rely on robust data from a plethora of data collections that capture information relating to infection, antimicrobial prescribing and patient outcomes across the healthcare system (i.e. community, primary and secondary care) in order to assess current and historical rates of infection, prescribing rates and prescribing efficacy across the patient pathway, so that workstreams can develop and implement effective plans that reduce drug resistance and ultimately lead to better outcomes for patients.

The clinical workstream leads have reviewed the datasets in detail, and identified the fields that they believe will bring value for their individual workstreams and support them to undertake the assessments described. Whilst some minimisation has been applied by restricting the fields to only those needed, further minimisation is anticipated once NHSE analysts have been able to access the data. The purpose of the exploration is to understand exactly which data items can support the clinical workstreams in their aims. Without full sight of the data fields as defined in the supporting spreadsheet, and over the period of time requested, NHSE are unable to evaluate the gaps and thereby the programme is at risk of missing vital information to meet the human healthcare ambitions.

National Cancer Waiting Times Monitoring Data Set (NCWTMDS) — DARS-NIC-192305-X3T0Y

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

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), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, The National Cancer Waiting Times Monitoring DataSet (NCWTMDS) is a national, patient level data collection by NHS Digital, under a Direction from NHS England (NHSE). The data are used for monitoring times taken to diagnose and treat patients with cancer and ensure these are in line with the expectations and rights of patients in the NHS Constitution. The NHS Digital NCWTMDS online system allows NHS providers to record data derived from patient care activity. This data can be used to: • monitor cancer waiting times targets • plan service improvements As a patient moves through the stages of their treatment pathway, data on referrals, treatments and diagnosis are derived from care records locally. The NCWTMDS provides the data used to publish the official cancer 62-day treatment target which is one of the key national statistics used to monitor the performance of the NHS. After collection, the cancer waiting times data can also be queried by NHS organisations, Cancer Alliances and the Department of Health and Social Care to provide reports and feedback on the progress towards meeting these targets. The NCWTMDS System will provide for NHS England online access to: A. Record level de-identified patient data (anonymised, without a record ID or pseudonym) B. Aggregate data (pre-defined tabulations, without disclosure control i.e. small number suppression) Some organisations accessing the NCWTMDS system are permitted to download data containing the identifier NHS number, or containing a pseudonymised record identifier; however under this agreement NHS England will not be permitted to have access to that level of data, and can only access record level pseudonymised data (with no pseudonymised ID) and aggregate data. NHS England previously had access to the dataset via Open Exeter, from Spring 2018 the dataset has been accessed via the new Cancer Waiting Times System and NHS Digital iView tool https://www.digital.nhs.uk/tools-for-accessing-data/iViewand-iViewPlus NHS England requires access to the system for the following purpose(s): 1. Use aggregate and record level data to produce monthly, quarterly and annual Official Statistics. Risk of disclosure are managed in line with official statistics protocols. 2. Use aggregate and record level data to undertake more detailed analysis and reporting to (i) monitor performance against the NHS constitutional standards in relation to cancer services. Monitoring and investigation of the data allows NHS England to meet its responsibilities in holding the healthcare system to account for delivering care to patients as set out in the constitution; (ii) support policy development, for example, evidence to inform changes to the CWT dataset and guidance, ensuring that NHS England policy decisions are based on a strong evidence base; and (iii) support operational delivery and service improvement, for example, identifying priority areas to focus on and making changes to pathways. This agreement will permit NHS England to share aggregate Cancer Waiting Times (CWT) data containing small numbers with the data controller and processor(s) named in each applicable Cancer Alliance data sharing agreement. This aggregate unsuppressed data can only be shared while both this agreement and the data sharing agreement for the relevant Cancer Alliance remains active, and where the Cancer Alliance agreement contains appropriate wording to cover this data sharing. If NHS England are notified that a Cancer Alliance's data sharing agreement has expired or otherwise ended then NHS England must ensure any flow of aggregate unsuppressed data to that Cancer Alliance is halted. The outputs shared with Cancer Alliances are aggregate data reports at various geographical levels which are essential to Cancer Alliances to enable analyses to be carried out and to understand local performance, both of individual providers and of the system in general. This analysis has to be undertaken at the most appropriate level for action to be taken and performance to be benchmarked; thus allowing patients to experience improvements to the system. For Cancer, this is specific tumour site level which is only possible with unsuppressed data. Introducing small number suppression would result in these reports having no practical use and leave Cancer Alliances without a way in which they can understand variation in performance between providers and improve the system. Cancer Alliances have already been provided with access to unsuppressed data in their data sharing agreements held directly between NHS Digital and each lead organisation responsible for employing the Cancer Alliance users of the system. Currently, the CWT national system does not provide full coverage of the data requested by Cancer Alliances in their data sharing agreements with NHS Digital. Only a limited amount of aggregate reports and record level data is available directly in the CWT system. NHS England are working with the development team to rectify this issue but based on competing policy priorities and finite financial resources it is likely that this development will not be fully realised. Therefore, NHS England’s Cancer Alliance, Data, Evidence and Analysis Service (CADEAS) will be required to provide Alliances with aggregate data for monthly and quarterly performance management and monitoring use within the NHS. This may include small numbers. This temporary arrangement includes only those Cancer Alliances that do not yet have the required data via the Cancer Waiting Times Dataset. Three Cancer Alliances do not yet have an active Data Sharing Agreement with NHS Digital for the Cancer Waiting Times Dataset. These Cancer Alliances do not have the expertise and/or resources to complete a DSA application process during the current Covid-19 crisis and ‘restore’ period. NHS England will work with these Cancer Alliances to provide support to ensure that DSAs with NHS Digital are active from 18th June 2022. As such, a temporary sub-licensing measure is in place for this application to allow access to aggregate reports which may include small numbers as detailed. In addition to the current restrictions in the CWT system, there is a longer term requirement for aggregate reports to be shared as detailed in section 5c. Specific Outputs Expected. These outputs are based on analysis conducted nationally and provide information for Cancer Alliances to enable further local analyses to be carried out and to understand and assure local performance. It would not be an efficient use of NHS resources for all Cancer Alliances to conduct the same level of data manipulation and presentation of outputs where initial data manipulation has already been conducted by the CADEAS team. Risk of disclosure is minimised as the dataset does not include patient demographics that may allow users to identify an individual e.g. there are no age, ethnic categories or geographic breakdowns based on patient postcode. Examples of this type of analysis include: - a) Comparison of performance by tumour site for each standard (nationally, and at Sustainability and Transformation Partnership (STP), regional, Alliance, Clinical Commissioning Group (CCG) and provider levels) b) National comparisons of trends in volumes of cases included for each standard c) Treatment modality comparisons at tumour site level d) Analysis of length of the whole pathway and phases of the pathway at various points along the distributions e.g. median, 75th, 85th and 95th percentiles. 3. Regional teams and Directors of Commissioning Operations teams will use aggregate data for the purpose of performance management and supporting the system to meet operational standards. 4. Access to ad-hoc sub-reports, specifically the breast screening cohort which is a sub-set of the data extracts required to produce monthly, quarterly and annual Official Statistics. The output will be used to inform policy decisions for the Director of the Cancer Programme team. The data is needed to conduct trend analysis on the specific cohort of patients who were identified as having missed a scheduled routine breast screening invitation. As part of the service response programme NHS England needs to be able to conduct analysis on those patients who, having been offered a screen, do go on to be diagnosed with a malignancy. This includes 62 day wait from referral from a cancer screening service to first treatment patients, as well as subsequent treatment activity and outcomes. Failure to understand the full scope and impact of the screening invitation errors could lead to reputational risk to the organisation and Public Health England at a later date. The data cannot be used for any other purpose than that stated above. The data will not be shared with any third party except in the form of aggregated outputs with small numbers suppressed in line with appropriate disclosure controls, such as Official Statistics; however aggregate report outputs containing small numbers may be shared with regional NHS England teams and Cancer Alliances as detailed above. Small numbers may be included in the aggregate data reports and are essential for analyses carried out, for example, to understand performance at provider level on a specific tumour site such as prostate and to benchmark performance against other similar providers. Suppressing small numbers would limit the utility of the reports and make performance and improvement discussions more challenging if both sides are not looking at the same numbers. Data will only ever be used for purposes relating to healthcare or the promotion of health in line with the requirements of the Health and Social Care Act 2012 as amended by the Care Act 2014. Any record level data extracted from the system will not be processed outside of the analytics teams employed by NHS England, with only aggregate data to be shared. The GDPR lawful basis for NHS England to process this data is under Article 6(1)(e) 'task in the public interest', and Article 9(2)(h) ‘Health or social care purposes'. (Agency/Public Body, internal NHS transfer)

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

When:DSA runs 2020-06-01 — 2020-08-31 2019.10 — 2023.01.

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: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: Yes, No

Datasets:

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

Objectives:

The National Cancer Waiting Times Monitoring DataSet (NCWTMDS) is a national, patient level data collection by NHS Digital, under a Direction from NHS England (NHSE). The data are used for monitoring times taken to diagnose and treat patients with cancer and ensure these are in line with the expectations and rights of patients in the NHS Constitution.

The NHS Digital NCWTMDS online system allows NHS providers to record data derived from patient care activity. This data can be used to:
•monitor cancer waiting times targets
•plan service improvements

As a patient moves through the stages of their treatment pathway, data on referrals, treatments and diagnosis are derived from care records locally.

The NCWTMDS provides the data used to publish the official cancer 62 day treatment target which is one of the key national statistics used to monitor the performance of the NHS. After collection, the cancer waiting times data can also be queried by NHS organisations, cancer networks and the Department of Health to provide reports and feedback on the progress towards meeting these targets.

The NCWTMDS System will provide for NHS England online access to:

1. Record level patient data (anonymised, without a record ID or pseudonym)
2. Aggregate data (pre-defined tabulations, without disclosure control i.e. small number suppression)

Some organisations accessing the NCWTMDS system are permitted to download data containing the identifier NHS number, or containing a pseudonymised record identifier; however under this agreement NHS England will not be permitted to have access to that level of data, and can only access record level anonymised data (with no pseudonymised ID) and aggregate data.

NHS England previously had access to the dataset via Open Exeter, from Spring 2018 the dataset will be accessed via the new Cancer Waiting Times System and NHS Digital iView tool https://www.digital.nhs.uk/tools-for-accessing-data/iView-and-iViewPlus

NHS England requires access to the system for the following purpose(s):

1. The national analytics team will use record level data to produce monthly and quarterly Official Statistics.
2. Regional teams and the Commissioning Operations Directorate will use aggregate data for the purpose of performance management.

The data cannot be used for any other purpose than that stated above. The data will not be shared with any third party. Data will only ever be used for purposes relating to healthcare or the promotion of health in line with the requirements of the Health and Social Care Act 2012 as amended by the Care Act 2014. Any record level data extracted from the system will not be processed outside of the analytics team, with only aggregate data to be shared with other NHS England teams.

This agreement supercedes any previous data sharing agreements in place to access this dataset via Open Exeter.

Yielded Benefits:

• Publication of monthly and quarterly Official Statistics which allows health organisations to assess performance and benchmark, identifying outliers and policy developments required. • Provision of transformation funding and National Cancer Programme projects, consisting of more than £250m, is provided to Cancer Alliances based on CWT Official Statistics performance as a benchmark for how ready the local system is to make changes and produce benefits from funding. • National timed pathways which promote best practice for patient care and faster diagnosis of cancer and non-cancer patients have been developed based on performance of tumour groups identified in the Official Statistics. • Local NHS England teams analyse performance and initiate improvement work locally, and identify outliers which have resulted in performance improvement and improved patient care / experience.

Expected Benefits:

Enabling analysis of the Cancer Waiting Times data on a system wide basis will provide insight to focus service improvements on most effective areas to improve performance. In particular you would expect that access to the data be essential to delivery of the Cancer Waiting Times 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
• 28 day referral to diagnosis - TBC

Outputs:

NHS England use NCWTMDS data on an ongoing basis for performance management purposes and for the production of national and official statistics. Statistical reports are published on a monthly and quarterly basis, and are available via the NHS England website: https://www.england.nhs.uk/statistics/statistical-work-areas/cancer-waiting-times/

Monthly statistical reports are issued alongside a press release to increase impact and aid interpretation.

All outputs will contain only data that is compliant with the relevant disclosure control rules including suppression and rounding.

Additional outputs consist of:
• Analysis to support delivery of Cancer Waiting Times standard and identify variation, including discussions to improve patient pathways and target funding / new NHS England Cancer Programme projects
• Comparative Cancer Waiting Times performance at tumour group for Cancer Alliances, Trusts and CCGs
• Analysis of Cancer Waiting Times performance by treatment to inform discussions.
• Identifying variation which may impact cancer patient’s outcomes or patient experience in order to support national policy discussions

Processing:

This application is for online permissions to access the record level NCWTMDS via the NHS Digital system and iView tool. The system can only be accessed by approved users via an N3 connection.

NHS England's national analytics team require access to record level data so that this can be analysed to produce Official Statistics on cancer waiting times. These statistics are published on a monthly and quarterly basis and report the number of people who attended outpatient appointments within two weeks of an urgent referral by their GP for suspected cancer or breast symptoms and, for patients with cancer, on the numbers who started treatment within 31 and 62 days for each organisation. Record level data is required to calculate medians and complete other statistical analysis that cannot be derived from pre-aggregated data alone. NHS England’s Regional analytics teams and Directors of Commissioning Operations analytics teams require access to aggregate record level data so that this can be analysed to produce regional reports on cancer waiting times on a monthly and quarterly basis, which allows them to assess performance and identify regional outliers.

Users wishing to access the system will require authorisation from the NHS England SIRO or IAO before access will be granted by NHS Digital; this is managed via a Data Users Certificate (DUC) form that is completed by each organisation accessing the system. NHS England is responsible for ensuring that only individuals with a legitimate need to access the data are approved as users. NHS England users are granted the permission to locally download record level extracts from the system and such downloads must be stored and processed securely on NHS England servers. No patient identifiable data is provided, and records should not be linked to any other source.

Data will only be accessed by individuals within NHS England who have authorisation from the SIRO or IAO to access the data for the purposes described, all of whom are personnel working under appropriate supervision on behalf of NHS England. Following completion of the analysis any record level data will be securely destroyed. Users are not permitted to upload data into the system. The data will not be used for commercial use. The data will not be linked with any record level data and there will be no requirement nor attempt to re-identify individuals from the data.

The raw data will not be made available to any third parties except in the form of aggregated outputs with small numbers suppressed in line with appropriate disclosure controls, such as Official Statistics.

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).

Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204575-V7X8H

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

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), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, 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. This agreement is for the Wessex Cancer Alliance to access Cancer Waiting Times data. The purpose for which the data is processed under this agreement is determined by the cancer alliance. However as the Cancer Alliance is not a legal entity, as staff are substantially employed by NHS England, who are therefore the lead organisation, and the data controller who processes data. In this agreement therefore, all references to accessing patient level data refer to the legal entity – NHS England (listed as a processor) are also part of the legal entity NHS England and are permitted to process the data. 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 The NHS Oversight Framework, including, importantly, in the 62 day wait from referral to first treatment standard. 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. Wessex Cancer Alliance NHS England will directly access the Cancer Waiting Times System on behalf of Wessex Cancer Alliance. The data is processed under the following articles: 6(1)e, as the Cancer Alliance is tasked with improving the delivery of the health and care system and have the public interest at heart; and article 9(2)h as the cancer alliance is tasked with the management of health and social care systems. The Cancer Alliance works with health organisations including the acute providers and ICB's listed below- Acute Providers •Dorset Country Hospital NHS Foundation Trust; Hampshire Hospitals NHS Foundation Trust; Isle of Wight NHS Trust; Portsmouth Hospitals Trust; University Hospitals Dorset NHS Foundation Trust; University Hospital Southampton NHS Foundation Trust ICBs • NHS Dorset Integrated Care Board and NHS Hampshire, Southampton and Isle of Wight Integrated Care Board Community Providers • Southern Health NHS Foundation Trust; Solent NHS Trust; Dorset Healthcare University NHS Foundation Trust Hospices • Earl Mountbatten; Rowans; Countess Mountbatten; Oakhaven; St Michaels; Countess of Brecknock; Lewis Manning; Forest Holme; Joseph Weld; Macmillan Unit, Christchurch Hospital. 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' ICB of responsibility. This Cancer Alliance is limited to Wessex Cancer Alliance Cancer Patients. A) Aggregate reports including small numbers Aggregate data is available in the form of reports at Provider (Trust) and ICB level. Small numbers may be included in the aggregate data reports and are essential for analyses carried out by lead organisations. 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 and allowed action to be taken to improve patient care. Investigating breaches Lead organisations 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/ICB 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. 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 ICB level and other health hierarchies. Lead organisations will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements. Lead organisations 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 ICB level. Lead organisations will access a summary of the totals for the Providers (Trust) and the ICB that are treating cancer patients where they have a commissioning responsibility for that patient (based on the ICB 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 ICBs 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 clinical audit purposes. The two broad purposes for this would be; 1) To support local clinical 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. (Network, internal NHS transfer)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2018-12-03 — 2021-12-02 2019.09 — 2023.01.

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: NHS ENGLAND (QUARRY HOUSE)

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 Wessex 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 NHS England. NHS England 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 - NHS England.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.


Wessex Cancer Alliance

NHS England will directly access the Cancer Waiting Times System on behalf of Wessex Cancer Alliance across Wessex (Dorset ICS and Hampshire and Isle of Wight STP). Wessex Cancer Alliance is hosted by NHS England and covers a population of approximately 2.8 million people.

NHS England works with health organisations across Wessex including 7 acute providers, 8 clinical commissioning groups, 3 community providers and 10 hospices.

Acute Providers

•Dorset Country Hospital NHS Foundation Trust; Hampshire Hospitals NHS Foundation Trust; Isle of Wight NHS Trust; Poole Hospital NHS Foundation Trust; Portsmouth Hospitals Trust; Royal Bournemouth and Christchurch Hospitals NHS Foundation Trust; University Hospital Southampton NHS Foundation Trust

CCGs
• Dorset CCG, Fareham & Gosport CCG, Isle of Wight CCG, North Hampshire CCG, Portsmouth CCG, South Eastern Hampshire CCG, Southampton City CCG, West Hampshire CCG

Community Providers

• Southern Health NHS Foundation Trust; Solent NHS Trust; Dorset Healthcare University NHS Foundation Trust

Hospices

• Earl Mountbatten; Rowans; Countess Mountbatten; Oakhaven; St Michaels; Countess of Brecknock; Lewis Manning; Forest Holme; Joseph Weld; Macmillan Unit, Christchurch Hospital.

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

NHS England 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 Wessex 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

NHS England 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.

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.

NHS England will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements.

NHS England 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. Lead organisations 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 (Acute Providers, CCGs, Community Providers & Hospices) 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 (Acute Providers, CCGs, Community Providers & Hospices) responsible for direct patient care for that patient. This will be for local clinical audit purposes.

The two broad purposes for this would be;

1) To support local clinical 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. Local Clinical 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.

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 lead organisation NHS England will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the NHS England 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 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).

NHS England 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 NHS England 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 NHS mail (nhs.net)
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 South East, NHS South West and the National Cancer Team within NHS England. 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.

Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204571-R1F4T

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

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 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(2)(b)(ii), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, This agreement is for the East of England - North Cancer Alliance to access Cancer Waiting Times data. The purpose for which the data is processed under this agreement is determined by the cancer alliance. However the Cancer Alliance is not a legal entity. The Cancer Alliance staff are substantially employed by NHS England and therefore as the lead organisation are the data controller. Under this Data Sharing Agreement NHS England are the sole data controller who will processes the data. Within NHS England are seven regions who support local systems to provide more joined up and sustainable care for patients. The regional teams are responsible for the quality, financial and operational performance of all NHS organisations in their region, drawing on the expertise and support of our corporate teams to improve services for patients and support local transformation. 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 Taskforces 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. 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. Cancer alliances are also created to drive improvement in cancer outcomes. Align with the improvement trajectory set for cancer survival (also part of CCG IAF), cancer alliances are set to deliver the Faster Diagnostic Standards (FDS) from April 2021 (delayed from April 2020). FDS is part of CWT dataset, referring to the duration between urgent GP referral to patients being told whether they have a cancer diagnosis or not. The National Cancer Programme has confirmed that FDS, along with 62-day wait, will be key metrics within the 10 year NHS Plan that Cancer Alliances will be held accountable to. Thus without access to the data as outlined in this request, the Cancer Alliance will not be able to deliver work programme as outlined by the National Cancer Programme. The Cancer Alliance will directly access the Cancer Waiting Times System on behalf of alliance member trusts and CCGs The Cancer Alliance works with health organisations across the East of England region including the acute providers and CCG's listed below- Acute Providers •Basildon and Thurrock University Hospital Trust Bedford Hospital Cambridge University Hospital Colchester Hospital East and North Herts NHS Trust Hinchingbrooke Health Care Trust Ipswich Hospital James Paget University Hospital Trust Luton and Dunstable University Trust Mid Essex Hospital Norfolk and Norwich University Hospital Papworth Hospital Peterborough and Stamford Hospital Southend University Hospital Queen Elizabeth Hospital Kings Lynn The Princess Alexandra Hospital West Herts Hospital West Suffolk Hospital Milton Keynes University Hospital Bedfordshire Hospital Trust East Suffolk and North East Essex Foundation Trust Mid and South Essex Trust North West Anglia Foundation Trust Clinical Commissioning Groups (CCGs) • Basildon and Brentwood CCG • Bedfordshire CCG • Cambridgeshire and Peterborough CCG • Castle Point and Rochford CCG • East and North Hertfordshire CCG • Great Yarmouth & Waveney CCG • Herts Valleys CCG • Ipswich and East Suffolk CCG • Luton CCG • Mid Essex CCG • North East Essex CCG • North Norfolk CCG • Norwich CCG • South Norfolk CCG • Southend CCG • Thurrock CCG • West Essex CCG • West Norfolk CCG • Norfolk and Waveney CCG • West Suffolk CCG Data access The CWT system provides the Data Controller / Processor 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 organisation will only access patient records which fall within the Cancer Alliances' footprint of responsibility based on the patients' CCG of responsibility. 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 The Data Controller routinely monitors 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 Approved users 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. The Cancer Alliance will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements. The Cancer Alliance'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. Lead organisations 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 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 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. 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 c. 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. (Network, internal NHS transfer)

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

When:DSA runs 2019-03-07 — 2021-03-06 2019.09 — 2023.01.

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: NHS ENGLAND (QUARRY HOUSE)

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 East of England 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 NHS England. NHS England 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 - NHS England.

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.


East of England Cancer Alliance

NHS England will directly access the Cancer Waiting Times System on behalf of East of England Cancer Alliance across Cambridgeshire, Bedfordshire, Hertfordshire, Essex, Norfolk, Suffolk and Milton Keynes. East of England Cancer Alliance is hosted by NHS England East and covers a population of 6.3 million people.

NHS England works with health organisations across England

Acute Providers

•Basildon and Thurrock University Hospital Trust
Bedford Hospital
Cambridge University Hospital
Colchester Hospital
East and North Herts NHS Trust
Hinchingbrooke Health Care Trust
Ipswich Hospital
James Paget University Hospital Trust
Luton and Dunstable University Trust
Mid Essex Hospital
Norfolk and Norwich University Hospital
Papworth Hospital
Peterborough and Stamford Hospital
Southend University Hospital
Queen Elizabeth Hospital Kings Lynn
The Princess Alexandra Hospital
West Herts Hospital
West Suffolk Hospital
Milton Keynes University Hospital


CCGs
• Basildon and Brentwood CCG
• Bedfordshire CCG
• Cambridgeshire and Peterborough CCG
• Castle Point and Rochford CCG
• East and North Hertfordshire CCG
• Great Yarmouth & Waveney CCG
• Herts Valleys CCG
• Ipswich and East Suffolk CCG
• Luton CCG
• Mid Essex CCG
• North East Essex CCG
• North Norfolk CCG
• Norwich CCG
• South Norfolk CCG
• Southend CCG
• Thurrock CCG
• West Essex CCG
• West Norfolk CCG
• West Suffolk CCG


Community Providers

Cambridgeshire Community Services
East Coast Community Healthcare
Hertfordshire Community NHS Trust
Norfolk Community Health and Care NHS Trust
South Essex Partnership University NHS Foundation Trust
Suffolk Community Healthcare

Hospices
Arthur Rank
Bedford Day care Hospice
East Anglia Childrens Hospice
Fair Haven Hospice
Farleigh Hospice
Garden House Hospice
Hospice of St Francis
Isobel Hospice
Keech Hospice Care for Adults
Keen Hospice Care for children
Little Havens Childrens Hospice
Peace Hospice Care
Rennie Grove Hospice Care

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 East of England 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
Lead organisations 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.

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.

Lead organisations will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements.

Lead organisations 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. Lead organisations will access a summary of the totals for the Providers (Trust) and CCGs that are treating cancer patients where they have a commissioning responsibility for that patient (based on the CCGs they are aligned to). This analysis would then be shared with the providers and commissioners and used to inform service improvement by providing bench-marked 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 (Acute Providers, CCGs, Community Providers & Hospices) responsible for direct patient care for that patient. This will be for local clinical audit purposes.

The two broad purposes for this would be;

1) To support local Clinical 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.

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 lead organisation NHS England will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the NHS England 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 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).

NHS England 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 NHS England 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 CCGs that are treating cancer patients where they have a commissioning responsibility for that patient (based on the CCGs 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: NHS mail (nhs.net)
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 Improvement, Public Health England, and also with East of England Cancer Alliance's constituent STPs, CCGs and hospital trusts. 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.

Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204559-J4H7T

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)

Purposes: No (Agency/Public Body, Network)

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

When:DSA runs 2019-01-02 — 2020-01-01 2019.09 — 2023.01.

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: NHS ENGLAND (QUARRY HOUSE)

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 Lancashire and South Cumbria 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 NHS England. NHS England 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 - NHS England.

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.

NHS England will directly access the Cancer Waiting Times System for the Lancashire & South Cumbria Cancer Alliance region, which covers a population of 1.7 million people.

Lancashire and South Cumbria Cancer Alliance works with health organisations across Lancashire and South Cumbria including 4 acute providers, 8 clinical commissioning groups.

Acute Providers

RXL Blackpool
RXR East Lancashire
RXN Lancashire Teaching
RTX Morecambe Bay

CCGs

00Q NHS Blackburn with Darwen CCG
00R NHS Blackpool CCG
00X NHS Chorley and South Ribble CCG
01A NHS East Lancashire CCG
02M NHS Fylde & Wyre CCG
01E NHS Greater Preston CCG
01K NHS Morecambe Bay CCG
02G NHS West Lancashire CCG

Data access

The CWT system provides one organisation (the lead organisation - in this case NHS England) 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

NHS England 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 Lancashire & South Cumbria 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
NHS England 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
NHS England 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.

NHS England will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements.

NHS England'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. Lead organisations 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 Lancashire and South Cumbria Cancer Alliance previously include:- · Produced Cancer Waiting Times Reports each month which look at performance by tumour type – helps with pathway work per cancer type · Also breach reasons we have used to identify issues with trusts such as capacity issues and also looking at demand in terms of 2 week wait referrals · Trends over time to see seasonal differences

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 NHS England will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the NHS England 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 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).

NHS England 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 Lancashire & South Cumbria Cancer Alliance 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 will be using the cloud with multiple layers of security.
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 NSSGs, Boards and those within the Alliance who requires data. 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 NHS England in fulfilment of their public health function.

The Cancer Alliance 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.

Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204557-F0N1T

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

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), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, This agreement is for the Thames Valley 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 NHS England. NHS England 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 - NHS England. 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. Thames Valley Cancer Alliance NHS England will directly access the Cancer Waiting Times System for the Thames Valley Cancer Alliance region, which covers a population of 2.3 million people. Thames Valley Cancer Alliance works with health organisations across Thames Valley including [6] acute providers and [6] clinical commissioning groups. Acute Providers RD8 - Milton Keynes General NHS Trust, RTH - Oxford University Hospitals NHS Foundation Trust RXQ - Buckinghamshire Healthcare NHS Trust, RN3 - Great Western Hospitals NHS Foundation Trust RDU - Frimley Health Hospital NHS Trust RHW - Royal Berkshire NHS Foundation Trust CCGs 04F NHS Milton Keynes CCG 10Q NHS Oxfordshire CCG 14Y NHS Buckinghamshire CCG 15A NHS Berkshire West CCG 15D NHS East Berkshire CCG 12D NHS Swindon CCG Data access The CWT system provides one organisation (NHS England) 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 NHS England 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 Thames Valley 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 Lead organisations 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. NHS England will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements. NHS England'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. Lead organisations 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. Dashboard: Thames Valley Cancer Alliance (TVCA) along with its stakeholder organisations, Oxford University Hospitals NHS Foundation Trust, Royal Berkshire NHS Foundation Trust, Buckinghamshire Healthcare NHS Trust, Great Western Hospitals NHS Foundation Trust, Milton Keynes University Hospitals NHS Foundation Trust and Frimley Health NHS Foundation Trust agreed to form a partnership to ensure safe delivery of cancer services. In recognition that during the current covid-19 pandemic, cancer systems across Thames Valley will be under significant pressure to continue to deliver safe care to all patients, Thames Valley Cancer Alliance developed a pan alliance prioritisation plan covering the agreed process and governance for managing cancer services through the COVID-19 response. With the on-going COVID-19 response there is a need for more visibility of real time data to enable proactive management and tracking of all cancer patients within the Cancer Alliance area; currently each Trusts’ Cancer Patient Tracking List (PTL) is growing due to the changes being made in the management of treatment for cancer patients and there is manual tracking of patients increasing the risk of patients being missed. Draper & Dash Ltd Access to data: TVCA have contracted Draper and Dash Ltd (D&D) to develop and deliver their Cancer Waits module / dashboard to the Alliance and each Trust as shown above. D&D will be given access to aggregated data via Secure File Transfer Environment used by the Cancer Alliance following submission by each of the Trust's data. Following automated aggregation of the data for Cancer Alliance use, D&D will also have access to this view of the data for the purposes of producing the outputs below. The D&D dashboard will provide the trust with the targeted overview needed to restore and recover cancer services during the COVID-19 pandemic and address bottlenecks in patient flow, enable granular insights and assess performance targets within the cancer domain. The dashboard will provide retrospective visibility of data however in some instances including the PTL section, a near real time patient level tracking will be available. The aim of adding Draper and Dash is to enable their services including but not limited to cancer waits module/dashboard specification gathering, business rules and data transformation, front end development and hosting for the Trusts clinical, operational and executive reporting. (Agency/Public Body, Network, internal NHS transfer)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-01-02 — 2020-01-01 2019.09 — 2023.01.

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: NHS ENGLAND (QUARRY HOUSE)

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 Thames Valley 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 NHS England. NHS England 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 - NHS England.

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.

Thames Valley Cancer Alliance

NHS England will directly access the Cancer Waiting Times System for the Thames Valley Cancer Alliance region, which covers a population of 2.3 million people.

Thames Valley Cancer Alliance works with health organisations across Thames Valley including [6] acute providers and [6] clinical commissioning groups.

Acute Providers
RD8 - Milton Keynes General NHS Trust,
RTH - Oxford University Hospitals NHS Foundation Trust
RXQ - Buckinghamshire Healthcare NHS Trust,
RN3 - Great Western Hosptials NHS Foundation Trust
RDU - Frimley Health Hospital NHS Trust
RHW - Royal Berkshire NHS Foundation Trust

CCGs
04F NHS Milton Keynes CCG
10Q NHS Oxfordshire CCG
14Y NHS Buckinghamshire CCG
15A NHS Berkshire West CCG
15D NHS East Berkshire CCG
12D NHS Swindon CCG

Data access

The CWT system provides one organisation (NHS England) 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

NHS England 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 Thames Valley 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
Lead organisations 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.

NHS England will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements.

NHS England'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. Lead organisations 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 Thames Valley Cancer Alliance previously include:- 1) The inter-trusts referral analysis – to identify the gap and breaches by tumour sites and between trusts. This helps to improve the patient pathway. 2) Tumour sites specific pathway analysis: Prostate cancer – to analyse and identify the gap and breaches e.g. understand 14 days, 31 days and 62 days gaps, treatment modality and inter-Trust issue.

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 NHS England will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the NHS England 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 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).

NHS England 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 Thames Valley Cancer Alliance 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 the Cloud (Shared drive within Cancer Alliance).

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, Providers and CCGs within Thames Valley. 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 NHS England 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.

Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204550-N7M4D

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

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), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, This agreement is for the Kent and Medway Cancer Alliance to access Cancer Waiting Times data. The purpose for which the data is processed under this agreement is determined by the cancer alliance. However, the Cancer Alliance is not a legal entity - its staff (and those accessing the Cancer Waiting Times data) are substantively employed by NHS England 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 -NHS England. This agreement follows a National Cancer Waiting Times Monitoring Dataset - Cancer Alliance specific template. 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 The NHS Oversight Framework, including, importantly, in the 62 day wait from referral to first treatment standard. 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. Kent and Medway Cancer Alliance NHS England will directly access the Cancer Waiting Times System on behalf of Kent and Medway Cancer Alliance. The data is processed under the following articles: 6(1)e, as the Cancer Alliance is tasked with improving the delivery of the health and care system and have the public interest at heart; and article 9(2)h as the cancer alliance is tasked with the management of health and social care systems. The Cancer Alliance works with the following health organisations: Acute Providers: Maidstone and Tunbridge Wells Medway Maritime Foundation Trust Dartford and Gravesham NHS Trust East Kent Hospitals Foundation Trust ICBs: Kent & Medway ICB Community Providers: Virgin Care Hospices Heat of Kent Hospice Hospice in the Weald Demelza House Pilgrims Hospice 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' ICB of responsibility. This Cancer Alliance is limited to Kent and Medway Cancer Patients. A) Aggregate reports including small numbers Aggregate data is available in the form of reports at Provider (Trust) and ICB level. Small numbers may be included in the aggregate data reports and are essential for analyses carried out by lead organisations. 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 and allowed action to be taken to improve patient care. Investigating breaches Lead organisations 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/ICB 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. 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 ICB level and other health hierarchies. Lead organisations will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements. Lead organisations 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 ICB level. Lead organisations will access a summary of the totals for the Providers (Trust) and the ICB that are treating cancer patients where they have a commissioning responsibility for that patient (based on the ICB 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 ICBs 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 clinical audit purposes. The two broad purposes for this would be; 1) To support local clinical 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. (Agency/Public Body, Network, internal NHS transfer)

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

When:DSA runs 2019-01-02 — 2020-01-01 2019.09 — 2023.01.

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: NHS ENGLAND (QUARRY HOUSE)

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 Kent and Medway 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 NHS England. NHS England 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 - NHS England.

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.

Kent and Medway Cancer Alliance

NHS England will directly access the Cancer Waiting Times System for the Kent and Medway Cancer Alliance region, which covers a population of 1.8 million people.

Kent and Medway Cancer Alliance works with health organisations across South, East of England including 4 acute providers, 8 clinical commissioning groups, 1 community providers and 4 hospices.

Acute Providers

Maidstone and Tunbridge Wells
Medway Maritime Foundation Trust
Dartford and Gravesham NHS Trust
East Kent Hospitals Foundation Trust

CCGs
South Kent Coast
Canterbury and Coastal
Ashford
Thanet
West Kent
Medway
Swale
Dartford Gravesham and Swanley

Community Providers
Virgin Care

Hospices
Heat of Kent Hospice
Hospice in the Weald
Demelza House
Pilgrims Hospice

Data access

The CWT system provides one organisation (NHS England) representing the 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

NHS England 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 of England 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 NHS England.

Investigating breaches
NHS England will 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
NHS England 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 NHS England 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.

NHS England will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements.

NHS England’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. NHS England 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 NHS England will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the NHS England 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 NHS England’s Senior Information Risk Officer (SIRO), and where there is a valid Data Sharing Agreement between NHS England 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).
NHS England 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 Alliance 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 email.

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 [National Cancer Programme Team or other NHSE / NHSI colleagues regionally or nationally. 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 NHS England 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.


Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204544-H5L0S

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)

Purposes: No (Network)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-01-17 — 2020-01-16 2019.09 — 2023.01.

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: NHS ENGLAND (QUARRY HOUSE)

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 Peninsula Cancer Alliance and Somerset, Wiltshire, Avon and Gloucestershire 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 NHS England. NHS England 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 - NHS England.

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.


Peninsula Cancer Alliance and Somerset, Wiltshire, Avon and Gloucestershire Cancer Alliance

NHS England will directly access the Cancer Waiting Times System on behalf of Peninsula Cancer Alliance and Somerset, Wiltshire, Avon and Gloucestershire Cancer Alliance across South West England. Peninsula Cancer Alliance and Somerset, Wiltshire, Avon and Gloucestershire Cancer Alliance are hosted by NHS England and collectively cover a population of 4.7 million people.

The Peninsula Cancer Alliance and Somerset, Wiltshire, Avon and Gloucestershire Cancer Alliance works with health organisations across South West England including 13 acute providers, 8 clinical commissioning groups.

Acute Providers
Gloucestershire Hospitals NHS Foundation Trust
North Bristol NHS Trust
Royal United Hospitals Bath NHS Foundation Trust
Salisbury NHS Foundation Trust
University Hospitals Bristol NHS Foundation Trust
Weston Area Health NHS Trust
Northern Devon Healthcare NHS Trust
University Hospitals Plymouth NHS Trust
Royal Cornwall Hospitals NHS Trust
Royal Devon and Exeter NHS Foundation Trust
Taunton and Somerset NHS Foundation Trust
Torbay and South Devon NHS Foundation Trust
Yeovil District Hospital NHS Foundation Trust

CCGs
Bath and North East Somerset
Gloucestershire
Bristol, North Somerset and South Gloucestershire
Wiltshire
Kernow
Somerset
Northern, Eastern and Western Devon
South Devon and Torbay

Data access

The CWT system provides one organisation (NHS England ) 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

NHS England 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 the 8 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 NHS England.

Investigating breaches
NHS England 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
NHS England 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 NHS England 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.

NHS England will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements.

NHS England 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. NHS England 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 NHS England will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the NHS England 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 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).

NHS England 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 Peninsula Cancer Alliance and Somerset, Wiltshire, Avon and Gloucestershire Cancer Alliance 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 NHS Mail.
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 CCGs 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 NHS England 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.

Access to HES via NHS Digital online portal - NIC-09042-L9M1K — DARS-NIC-18798-V2J6C

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

Legal basis: Health and Social Care Act 2012, 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(5)(d), Health and Social Care Act 2012 – s261(2)(b)(ii), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, NHS England has a wide spectrum of responsibilities to support Health and Social care within England, and access to the NHS England Portal is required to support this for the following areas; - commissioning - policy - finance - economic development - research and analysis The above, all assist NHS England in its aim to create the culture and conditions for health and care services and staff to deliver the highest standard of care and ensure that valuable public resources are used effectively to get the best outcomes for individuals, communities and society for now and for future generations. In order to fulfil these responsibilities, the NHS England Portal access allows NHS England to download data from NHS England Portal. NHS England are processing the data being accessed under this agreement as part of the public task under Article 6(1)(e) and 9(2)(h) of the UK GDPR. Article 6(1)(e) Task in the public interest: processing is necessary for the performance of a task in the public interest or in the exercise of official authority vested in the controller. Public Authority: NHS England is a public authority. The Data Protection Act 2018 defines 'public authority' as that defined under the Freedom of Information (FOI) Act 2000. The FOI Act was amended by the Health and Social Care Act 2012 schedule 5 paragraph 99(b) to include the NHS Commissioning Board (also known as NHS England) as a named public authority. - Basis in law: The Health and Social Care Act 2012 section 23 13E(1) states that the NHS Commissioning Board 'must exercise its functions with a view to securing continuous improvement in the quality of services provided to individuals for or in connection with— (a)the prevention, diagnosis or treatment of illness, or (b)the protection or improvement of public health.' Public Task: Section 8 of the Data Protection Act 2018 clarifies that “In Article 6(1) of the GDPR (lawfulness of processing), the reference in point (e) to processing of personal data that is necessary for the performance of a task carried out in the public interest or in the exercise of the controller’s official authority includes processing of personal data that is necessary for… (d) the exercise of a function of the Crown, a Minister of the Crown or a government department. The UK government department responsible for the NHS is the Department of Health, headed by the Secretary of State for Health. Necessity: Throughout the application process, the necessity of the processing for the performance of the task has been assessed. This included but was not limited to ensuring appropriate minimisation of the data to ensure that only the minimum amount of data required are processed. During the application process it has been considered whether the information that the processing aims to determine is already available from other sources or whether the task could be performed using publicly available data or data from alternative sources than NHS England. Consideration has been given to whether the volume of data being requested is proportionate to the expected benefit and, through examination of the expected benefits consideration has been given to whether the task is itself necessary. Therefore, we are satisfied that this request is appropriate, necessary and proportionate for the performance of the task described in the Purpose statement and that there is no other reasonable means for the data processor to achieve their purpose that is less intrusive to the data subjects. Article 9(2)(h) Processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services on the basis of Union or Member State law or pursuant to contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3. The data are requested for reasons of management of Health and Social Care Systems and Services - meeting the conditions in the DPA 2018 Schedule 1 Part 1, schedule 2(2)(f). The conditions and safeguards in DPA 2018 section 11(1) – stating that “For the purposes of Article 9(2)(h) of the GDPR (processing for health or social care purposes etc), the circumstances in which the processing of personal data is carried out subject to the conditions and safeguards referred to in Article 9(3) of the GDPR (obligation of secrecy) include circumstances in which it is carried out— (b) by another person who in the circumstances owes a duty of confidentiality under an enactment or rule of law.” NHS England meets this condition because NHS England is subject to a duty to promote a comprehensive health service, designed to secure the improvement in the physical and mental health of people in England and the prevention, diagnoses and treatment of illness, which it discharges alongside the Secretary of State, except for that part of the health service that is delivered in pursuit of public health functions of the Secretary of State or local authorities. (NHS Act 2006, S1H (2)) and NHS England assists Secretary of State in providing health services and exercising public health functions. Section 12 empowers the Secretary of State to make arrangements with any person or body to provide, or assist in providing, anything that the Secretary of State has a duty or power to provide, or arrange for the provision of, under section 2A or 2B or Schedule 1 of the 2006 Act, as amended (the Secretary of State’s duty as to the protection of public health and the improvement of public health respectively). (NHS Act 2006, S12, HSCA 2012, s22). As part of the standard Data Access Request Service application process: - the applicant’s technical and organisational measures to safeguard the data have been assessed and meets NHS England’s acceptance criteria; - the requested data has been assessed as proportionate to the aim pursued; - respect to the essence of the right to data protection has been assessed (e.g. security assurance, data retention, controls and processing activities, etc.); - measures to protect the rights and freedoms of data subjects have been assessed including transparency (fair processing) publishing subject’s rights to withdraw consent and/or have their data erased or rectified, etc. - The data required by NHS England is not intrusive. - The data required is pseudonymised by NHS England to minimise the risk of identification. Data will only ever be used for purposes relating to healthcare or the promotion of health in line with the requirements of the Health and Social Care Act 2012 as amended by the Care Act 2014. NHS England Portal users are based across the organisation and their access is from the secure NHS England environment. They help NHS England to oversee the delivery of NHS funded services and the continuous improvements to the quality of treatment and care by using HES data to inform, target, strategise, monitor, benchmark, cross-check and plan services. An ongoing example is the planning of endoscopy services to meet demand. Using tailored HES data with sufficient stable data years (pre-Covid) to build a robust time series, it is possible to anticipate future demand based on population demographics and other factors. This is helping to ensure that sufficient capacity is in place, as elective recovery from Covid continues, and that further enhancements to screening programs are achievable. Another example is the redesign of urgent and emergency care (UEC) services to cope with the increasing demand on A&E departments and emergency admissions. Some of this analysis will be for internal management purposes and key outputs will be published in various forms (see examples below). NHS England access to record level data is necessary to devise appropriate aggregations e.g. of activity relating to diseases or groups of operations, to calculate statistics such as median length of stay, to break down total counts to understand their components and to analyse connected activity such as A&E attendance and emergency admission. Any record level data extracted from the system will not be processed outside of the analytics team. Only registered NHS England Portal users who form the analytics team will have access to record level data downloaded from the NHS England Portal system. Following completion of the analysis the record level data will be securely destroyed. Ongoing requirements - HES data is used in various projects, e.g. maternity data – http://maternitydashboard.tvscn.nhs.uk/ , the public face is information from HES, and is refreshed on a quarterly. Without the HES data, NHS England can’t compare the local and national data, in order to improve the data quality and service within Maternity. - Other projects include cancer surgical review, community hospitals admission, Cardiovascular disease (CVD) e.g Primary Percutaneous coronary intervention; - Most projects are using data to benchmark and understand services within each area. This helps with the strategic decision making e.g. redesigning the services. Justification for the volume of data This data is used for various different projects. Having such a broad amount of data available allows the Data Controller to quickly respond to different requests to full-fill their commissioning responsibilities without having to change the data sharing agreement. Whilst access does not include any of the identifiable or sensitive data, a full range of non-identifiable fields may be needed for different purposes. (Agency/Public Body, internal NHS transfer)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-12-01 — 2020-03-31 2017.09 — 2023.01.

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

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Accident and Emergency
  3. Hospital Episode Statistics Outpatients
  4. Hospital Episode Statistics Critical Care
  5. Emergency Care Data Set (ECDS)
  6. Hospital Episode Statistics Accident and Emergency (HES A and E)
  7. Hospital Episode Statistics Admitted Patient Care (HES APC)
  8. Hospital Episode Statistics Critical Care (HES Critical Care)
  9. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

NHS England supports across a wide spectrum of responsibilities to support Health and Social care within England access to HDIS is required to support this for the following areas;
- commissioning
- policy
- finance
- economic development
- research and analysis

The above all assist NHS England in its aim to create the culture and conditions for health and care services and staff to deliver the highest standard of care and ensure that valuable public resources are used effectively to get the best outcomes for individuals, communities and society for now and for future generations.

Data will only ever be used for purposes relating to healthcare or the promotion of health in line with the requirements of the Health and Social Care Act 2012 as amended by the Care Act 2014.

HDIS users are based across the organisation and their access is from the secure NHS England environment. They help NHS England to oversee the delivery of NHS funded services and the continuous improvements to the quality of treatment and care by using HES data to inform, target, strategies, monitor, benchmark, cross-check and plan services.

An example is the £2.1 billion Sustainability and Transformation fund set up to stabilise NHS finances, in tandem with higher rates of efficiency growth, and to provide funding for transition to more effective models of care. Many of this fund’s uses impact on hospital care and require good evidence and understanding of hospital activity – at a local level but within a national context as provided by HES.

Another example is the redesign of urgent and emergency care (UEC) services to cope with the increasing demand on A&E departments and emergency admissions. A specific part of that is the development of new indicators to monitor UEC effectiveness due in October 2016. Some of this analysis will be for internal management purposes and key outputs will be published in various forms (see examples below).

NHS England access to record level data is necessary to devise appropriate aggregations eg of activity relating to diseases or groups of operations, to calculate statistics such as median length of stay, to break down total counts to understand their components and to analyse connected activity such as A&E attendance and emergency admission.

Any record level data extracted from the system will not be processed outside of the analytics team. Only registered HDIS users who form the analytics team, will have access to record level data downloaded from the HDIS system. Following completion of the analysis the record level data will be securely destroyed.

Yielded Benefits:

Public examples of earlier work drawing on HES outputs that have benefitted patients and Health communities include: • The route map for Urgent and Emergency Care that includes the piloting of outcome metrics to demonstrate improvements for patients: https://www.england.nhs.uk/wp-content/uploads/2015/11/item5-board-20-11-15.pdf. Without these outcome metrics, there is no measure of success for the initiatives implemented. • Publishing a breach rate for mixed sex accommodation that uses HES data in combination with NHS England data: http://www.england.nhs.uk/statistics/statistical-work-areas/mixed-sex-accommodation/. Without this breach rate there would be no accountability and patients would continue to suffer the problems of mixed sex wards. • Tools helping the NHS (and the public) to review and address variation such as the Diagnostic Atlas of Variation: http://www.rightcare.nhs.uk/index.php/atlas/diagnostics-the-nhs-atlas-of-variation-in-diagnostics-services/. Without these tools, local health communities may invest in services that do not provide maximum benefit for patients. • The latest stages of the NHS cancer strategy that include work on improving diagnostic test capacity (drawing on HES analysis): https://www.england.nhs.uk/wp-content/uploads/2016/05/cancer-strategy.pdf. Without this information, there may be insufficient resource put in place to meet demand for cancer diagnostics, leading to worse outcomes. • The Mental Health Five Year Forward View (MH FYFV) dashboard brings together key data from across mental health services to measure the performance of the NHS in delivering plans and includes metrics based on HES (see https://www.england.nhs.uk/mental-health/taskforce/imp/mh-dashboard/). Without this, there would be no transparency in progress towards putting mental health care on a level footing with physical illness. • The allocation model for children’s mental health is being updated with statistics relating to hospital activity in this area. HES provides evidence to allow allocations to be fair and targeted.

Expected Benefits:

NHS England has an objective to allow everyone to have greater control of their health and wellbeing, support individuals to live longer, healthier lives by the provision of high quality health and care services that are compassionate, inclusive and constantly-improving. The vision for that was set out in the NHS Five Year Forward View, published in 2014. NHS England's effectiveness in achieving this is summarised in their Annual Report:

https://www.england.nhs.uk/wp-content/uploads/2016/07/nhse-annual-rep-201516.pdf

Public examples of earlier work drawing on HES outputs that have benefitted patients and Health communities include:

• The route map for Urgent and Emergency Care that includes the piloting of outcome metrics to demonstrate improvements for patients: https://www.england.nhs.uk/wp-content/uploads/2015/11/item5-board-20-11-15.pdf. Without these outcome metrics, there is no measure of success for the initiatives implemented.

• Publishing a breach rate for mixed sex accommodation that uses HES data in combination with NHS England data: http://www.england.nhs.uk/statistics/statistical-work-areas/mixed-sex-accommodation/. Without this breach rate there would be no accountability and patients would continue to suffer the problems of mixed sex wards.

• Tools helping the NHS (and the public) to review and address variation such as the Diagnostic Atlas of Variation: http://www.rightcare.nhs.uk/index.php/atlas/diagnostics-the-nhs-atlas-of-variation-in-diagnostics-services/. Without these tools, local health communities may invest in services that do not provide maximum benefit for patients.

• The latest stages of the NHS cancer strategy that include work on improving diagnostic test capacity (drawing on HES analysis): https://www.england.nhs.uk/wp-content/uploads/2016/05/cancer-strategy.pdf. Without this information, there may be insufficient resource put in place to meet demand for cancer diagnostics, leading to worse outcomes.

Outputs:

NHS England use HES data on an ongoing basis for management purposes, for internal review, for information and tools to support the commissioning and provision of NHS services and in publications relevant to NHS England business plan and the objectives of NHS England mandate.

The following examples illustrate the ongoing use of the HES data and outputs expected in the coming year:
• Enumerating activity for specialised commissioning;
• Reviewing trends in diagnostic testing to improve early cancer detection;
• Validating the claims of New Care Model vanguards to improve eg emergency admission rates and bed days or A&E attendance for children and young people;
• Supporting the Maternity Transformation Programme (currently being launched) to deliver safer, more personalised care;
• Contributing to the Right Care Commissioning for Value packs to help CCGs do efficient and effective commissioning;
• Informing the Congenital Heart Disease Review to secure the best outcomes for patients;
• Providing baselines for the CCG Improvement and Assessment Framework for performance monitoring;
• Producing hospital related indicators for the Primary Care Dashboard for GP Practices;
• Refining the formula for the Mental health tariff;
• Developing system wide indicators for Urgent and Emergency Care Networks, to implement from 2017.

In addition, NHS England users will analyse HES data to contribute to many other workstreams and handle briefing requests on an ad hoc basis. Each item is separately commissioned and target dates are set during the programme.

Examples of external-facing uses of the data are given in the benefits section below. Recent examples of internal and unpublished briefing, tools and analysis are as follows.

• Internal analysis paper investigating the appropriate metric for calculating bed-days;
• High-level briefing on trends in the use of the independent sector by the NHS;
• Dashboard showing variations in endoscopy provision across England;
• Briefing paper assessing evidence for the impact of a New Care Models vanguard.

The data are used for internal purposes such as briefing and specialised commissioning, for advising NHS organisations such as Trusts and CCGs or for wider publication such as in the examples below. The data are not used for commercial use. Small numbers are suppressed in line with the HES Analysis Guide.

Processing:

NHS England users access HDIS via a secure portal from encrypted laptops and desktops based in a number of locations. These are encrypted by Bitlocker to the AES-256 standard These devices have the VMware software necessary to access HDIS, but not HDIS itself, which remains always in the NHS Digital remote environment. Access is not possible without additionally having a user id, password and RSA token. NHS Digital grant NHS England the ability to carry out analysis on HES data using the SAS Enterprise Guide analytical tool. Data are viewed and analysed remotely via this secure means.

NHS England users also have the ability to locally download record level results, outputs and extracts from the HDIS system. Such downloads are stored and processed securely on NHS England servers (or equivalent for Strategic Clinical Network users who are legally part of NHS England). These are generally in the form of tables for further analysis, aggregation, standardisation and computation or for inclusion in briefing, documents, models and tools. Record level extracts are only required for small numbers of cases where further manipulation is required eg to understand how episodes relate to the same spell, pathway or patient. No patient identifiable data are provided and records are not linked to any other source.

The data are not used for commercial use. For all outputs small numbers are suppressed in line with the HES Analysis Guide. Any unsuppressed tables are stored and, where necessary, shared securely with colleagues involved in the analysis of results and the unsuppressed data will not be shared with third parties.

The data will be processed for the purposes described in this document. Most tables extracted from HDIS are aggregated to CCG, Hospital provider or national level, but further breakdowns may be required eg to build geographies based on Local Authority District or GP practices. HES data may be analysed at aggregate level with other data sources, especially resident or GP registered populations to create activity rates.

NHS England have 30 analyst users who are part of the agreed 50 licenses (together with DH, no DH users have access to the HDIS system under the terms of this agreement) that are covered by the GIA arrangement.

NHS Improvement - National Clinical Improvement Programme (NCIP) — DARS-NIC-213403-P3R8Q

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

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), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, NHS Improvement (NHSI) launched on 1 April 2016 and was the operational name for the organisation that brought together Monitor and the NHS Trust Development Authority (TDA) plus a number of other teams. NHSI and TDA merged with NHS England in July 2022. This amended Agreement covers the provision of data from NHS England Data Access Request Services (DARS) to NHS England (NHSE) as sole controller. (Previously Monitor and NHS TDA) NHSE are an operational partner in delivery of the Portal to the NHS. Article 6(1)(e) is being used as the GDPR legal basis for processing. NHS England is a public authority. The Data Protection Act 2018 s7(1)(a) defines public bodies for the purpose of the GDPR as a public authority as defined by the Freedom of Information Act 2000. The FOI Act 2000 Part 1, section 3 (1)(a)(i) specifies that a public authority means any body which is listed in Schedule 1. Schedule 1 of the FOI Act 2000 lists special health authorities as public authorities; (NHS England is a statutory body under the Health and Social Care Act 2012. GDPR Article 9(2)(h) is also being relied upon: Processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services on the basis of Union or Member State law or pursuant to contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3. -The data are required for the purpose of commissioning. -The data required by the data controllers is the least intrusive to the data subject possible to be able to conduct their functions. -The data required for commissioning purposes is pseudonymised by NHS Digital to minimise the risk of identification. As such, NHSE is responsible, among other things, for the oversight of NHS trusts, NHS foundation trusts and independent providers. NHSE requires access to the following data sets as part of this request; *Hospital Episode Statistics (HES) including Consultant code *Patient Reported Outcome Measures (PROMS) *HES- Civil registration of deaths linked data *SUS PbR *DIDS *Theatre data set (discovery collection) Only data for care and treatment in English hospitals is required under this Agreement. NCIP is keen to use the civil registration of death data to measure mortality following procedures. The key data fields for this purpose are date of death and cause of death. The NCIP programme is a quality improvement tool allowing consultants to ‘drill down’ into mortality within 90 days of procedure as part of regular review of their own practice and outcomes. One of the key clinical quality metrics is death following surgical procedures. The programme uses HES data to calculate a number of clinical quality indicators, including in-hospital mortality. PROMS data is necessary to support ongoing discovery for improving consultant performance. DIDS data is necessary to support ongoing discovery for improving consultant attribution. SUS PbR is necessary to provide additional patient outcomes detail for both inpatients and outpatients which supports the overall purpose of the quality improvement tool. The data years requested are required to provide trend data, for example, five or ten year survival statistics, or consultant/ procedure improvements from a point in time when practice/ pathway is changed. NHSE will ensure that suitable controls are in place such that the data is used by the trust solely in line with the purposes set out within the agreement. . The National Consultant Information Programme (NCIP) delivers a secure online portal platform. Consultants will use the platform for the purposes of supporting improvements in the clinical quality of healthcare services provided by the NHS in England in order to bring about improvements in clinical outcomes for persons in receipt of such services. In particular in support of personal development; in particular, professional appraisal. NCIP operates under the statutory improvement functions of NHSE, which is a central part of the NHS Long Term Plan. The NCIP product will feature a series of activity-specific dashboards and metrics. Those with access will be able to drill through the dashboards to the underlying pseudonymised record level data. Consultants and speciality grade doctors will have access to dashboards that describe their personal activity and the unit level activity of their designated organisation (where the designated organisation is an NHS Trust). A Consultant’s or speciality grade doctor’s access to the product will be subject to the approval of the Medical Director (or persons working on their behalf) at their NHS Designated Organisation. Specific to the theatre data set discovery this data is being collected under a Mandatory Request to NHS England DARS. The request is for NHS England DARS to establish and operate an information system for the collection and analysis of theatre data from between five and seven NHS Foundation Trusts (discovery sites) in support of the NCIP. The purpose of requesting NHSE DARS to establish the NCIP Theatre Data Set Discovery Information System is to enable NHSE to assess the potential of theatre data to enhance the attribution of surgical activity to consultants, as recorded in Hospital Episode Statistics (HES) Admitted Patient Care (APC) data, and to explore potential other uses of the data (e.g. unit-level productivity measurement) with a view to developing a national theatre data set. Inaccurate attribution of existing activity data to consultants is a risk to the success of NCIP. The data will be collected in a form which identifies individual patients and associated information about their health care. This will therefore be patient level data sourced from local theatre systems within NHS trusts. The data will be disseminated to NHSE once it has been collected by NHSE DARS as part of the data set discovery project. The flow of data will be limited by the duration of the Discovery project; i.e. the Discovery project will not support an on-going flow of theatre data. This information is necessary to enable data linkage to HES APC data at procedure level and for NHSE to share the relevant activity data with the consultants concerned. The collection also identifies the surgeons and anaesthetists involved. Clinicians will be identified in Theatre data using a combination of GMC number, local identifier and name. There are no intended publications of the Theatre Data Set Discovery collection. The data sourced from NHSE DARS under this agreement will also be used by the NCIP development team for validation and development of NCIP algorithms. This will involve a trust consultant (involved in the development of NCIP) sharing with NHSE analysts a sub-set of trust held data related to a specific procedure, this will be cross referenced to HES data and any inaccuracies shared back with the consultant who is directly involved in the delivery of the patient’s direct care. This will generally include aggregate level figures with small numbers suppressed but could include a set of procedure codes. This activity is critical to developing accurate content, be it aggregations of activity or metrics that are applied to those activities. (Agency/Public Body, internal NHS transfer)

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

When:DSA runs 2019-04-04 — 2020-04-03 2020.06 — 2021.05.

Access method: One-Off, Ongoing

Data-controller type: MONITOR, NHS TRUST DEVELOPMENT AUTHORITY, NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: Yes, No

Datasets:

  1. NCIP Theatre Data Set Discovery Project
  2. NCIP Theatre Data Set Discovery Project Bridging File
  3. Secondary Uses Service Payment By Results Outpatients
  4. Secondary Uses Service Payment By Results Episodes
  5. Secondary Uses Service Payment By Results Accident & Emergency
  6. Secondary Uses Service Payment By Results Spells
  7. Bridge file: Hospital Episode Statistics to Diagnostic Imaging Dataset
  8. Civil Registration (Deaths) - Secondary Care Cut
  9. Diagnostic Imaging Dataset
  10. Hospital Episode Statistics Accident and Emergency
  11. Hospital Episode Statistics Admitted Patient Care
  12. Hospital Episode Statistics Critical Care
  13. Hospital Episode Statistics Outpatients
  14. Patient Reported Outcome Measures (Linkable to HES)
  15. Secondary Uses Service Payment By Results Accident & Emergency
  16. Civil Registrations of Death - Secondary Care Cut
  17. Diagnostic Imaging Data Set (DID)
  18. Hospital Episode Statistics Accident and Emergency (HES A and E)
  19. Hospital Episode Statistics Admitted Patient Care (HES APC)
  20. Hospital Episode Statistics Critical Care (HES Critical Care)
  21. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

NHS Improvement (NHSI) was launched on 1 April 2016 and is the operational name for the organisation that brings together Monitor and the NHS Trust Development Authority (TDA) plus a number of other teams.

NHS Improvement operates as a single organisation, with a joint board and single leadership and operating model although the TDA and Monitor continue to exist as distinct legal entities with their continuing statutory functions, legal powers and staff.

This application seeks to request data for both the TDA and Monitor as joint Data controllers.

The TDA is a Special Health Authority established by Article 2 of the TDA (Establishment and Constitution) Order 2012. The NHS TDA is also made up of the Patient Safety, the National Reporting and Learning System, the Advancing Change and the Intensive Support Teams. Under the NHS DA (Directions and Miscellaneous Amendments etc.) Regulations 2016 it has a general power to take such steps as it considers necessary and appropriate to assist and support persons providing NHS services to ensure continuous improvement in the quality of the provision and the financial sustainability of NHS services.

Monitor is a statutory body. Under the Health and Social Care Act 2012. It has a duty when exercising its functions to protect and promote patient interests by promoting economic, efficient and effective health care services whilst maintaining or improving quality. Monitor must co-operate with Special Health Authorities including the NHS TDA.

Monitor and the NHS Trust Development Authority (TDA) have come together under the operational name NHS Improvement, combining the functions and responsibilities of the two statutory bodies in a single integrated organisation.

Article 6(1)(e) is being used as the GDPR legal basis for processing.
Monitor, The TDA and NHSE are public authorities. The Data Protection Act 2018 s7(1)(a) defines ‘public bodies’ for the purpose of the GDPR as “a public authority as defined by the Freedom of Information Act 2000”. The FOI Act 2000 Part 1, section 3 (1)(a)(i) specifies that a public authority means any body which is listed in Schedule 1. Schedule 1 of the FOI Act 2000 lists special health authorities as public authorities (TDA) and Monitor is a statutory body. Under the Health and Social Care Act 2012.

Article 9(2)(j) is also being used as 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).


As such, NHS Improvement is responsible, among other things, for the oversight of NHS trusts, NHS foundation trusts and independent providers.

Monitor require access to the following data sets as part of this request;

*Hospital Episode Statistics (HES) including Consultant code
*Patient Reported Outcome Measures (PROMS)
*ONS-HES linked data
*Civil registration of deaths data
*Theatre data set (discovery collection)

The National Clinical Improvement Programme (NCIP) aims to support clinicians with learning and continuous self-development with respect to the services they deliver. The programme will provide both team and clinical-level activity and metrics about the whole of a clinician's practice, and links to relevant service delivery research and other evidence, delivered through a secure online portal hosted by NHS Improvement. NCIP will be a digital product that NHS consultants and speciality grade doctors in England will use to source their personal and unit-level outcome data in the context of national benchmarks. This information will support quality improvement activities, with the ultimate aim of delivering improved patient care.

NCIP is a Getting It Right First Time (GIRFT) Programme, operating under the statutory improvement functions of NHS Improvement, which is a central part of the NHS Long Term Plan. The NCIP product will feature a series of activity-specific dashboards and metrics. Those with access will be able to drill through the dashboards to the underlying pseudonymised record level data. Consultants and speciality grade doctors will have access to dashboards that describe their personal activity and the unit level activity of their designated organisation (where the designated organisation is an NHS Trust). A Consultant’s or speciality grade doctor’s access to the product will be subject to the approval of the Medical Director (or persons working on their behalf) at their NHS Designated Organisation.

Specific to the theatre data set discovery this data is being collected under a Mandatory Request to NHS Digital. The request is for NHS Digital to establish and operate an information system for the collection and analysis of theatre data from between five and seven NHS Foundation Trusts (discovery sites) in support of the NCIP.

The purpose of requesting NHS Digital to establish the NCIP Theatre Data Set Discovery Information System is to enable NHSI/E to assess the potential of theatre data to enhance the attribution of surgical activity to consultants, as recorded in Hospital Episode Statistics (HES) Admitted Patient Care (APC) data, and to explore potential other uses of the data (e.g. unit-level productivity measurement) with a view to developing a national theatre data set.

Inaccurate attribution of existing activity data to consultants is a risk to the success of NCIP.

The data will be collected in a form which identifies individual patients and associated information about their health care. This will therefore be patient level data sourced from local theatre systems within NHS trusts. The data will be disseminated to NHSI once it has been collected by NHSD as part of the data set discovery project. The flow of data will be limited by the duration of the Discovery project; i.e. the Discovery project will not support an on-going flow of theatre data.

This information is necessary to enable data linkage to HES APC data at procedure level and for NHSI to share the relevant activity data with the consultants concerned. The collection also identifies the surgeons and anaesthetists involved. Clinicians will be identified in Theatre data using a combination of GMC number, local identifier and name.

There are no intended publications of the Theatre Data Set Discovery collection.

The data sourced from NHS Digital under this agreement will also be used by the NCIP development team for validation and development of NCIP algorithms. This will involve a trust consultant (involved in the development of NCIP) sharing with NHSI analysts a sub set of trust held data related to a specific procedure, this will be cross referenced to HES data and any inaccuracies shared back with the consultant who is directly involved in the delivery of the patient’s direct care. This will generally include aggregate level figures with small numbers suppressed but could include a set of procedure codes. This activity is critical to developing accurate content, be it aggregations of activity or metrics that are applied to those activities.

Yielded Benefits:

There are currently no yielded benefits due to the sub-license being in place for less than 12 months.

Expected Benefits:

The benefits that the NCIP product will provide is to improve patient care through learning generated from the provision of individual and unit level activity and outcomes data to NHS consultants and speciality grade doctors in England. The product will provide data to individual consultants and speciality grade doctors for personal development, professional appraisal and improvements/learning. Support the Responsible Officer to discharge statutory duties for having oversight of a Consultant’s and speciality grade doctor whole practice. Ensure trust Medical Director has a view of all activity within their trust and identity areas of required improvements.





Outputs:

Example outputs that will form part of the core functions set out in the purpose section are:

Developing the Carter Model Hospital, GIRFT and NCIP product.

Developing the Carter Programme and the Model Hospital dashboard and metrics in a nationally available online information system, with a series of themed compartments which present key performance metrics for different area across the hospital, community services, mental health services and ambulance services.

Enabling providers to compare performance against their peers and national benchmarks and identify areas where they need to improve and develop products to help support service improvements and operational productivity.

Providing Consultant and speciality grade doctor level activity data to individual Consultants and speciality grade doctors. The rationale of sharing at this level is to support Consultant and speciality grade doctor appraisals and clinical improvements/outcomes.

Processing:

The NCIP product will be securely provided over the web, where users will require username and password to access. All patient level pseudonymised HES data will be held within NHSI secure servers, whereas aggregate activity data (e.g. number of procedures, number of re admission within 30 days) at consultant and speciality grade doctor level will be held in the Azure Cloud under contract with NHSI. Only Aggregated data with small number suppression will be held in the Azure Cloud.

Data presented via the NCIP product will include pseudonymised record level data as well as aggregate data (without small numbers suppression in line with the exception agreed for GIRFT). Access to data held in the NCIP product will be provided in accordance with sign up to terms of conditions of use for accessing NCIP (flow down NHSD requirements) and under a sub licence arrangement with trusts.

Access levels of data will be in accordance with the sub licence each Trust signs up to;
Consultants and speciality grade doctors will have access to Trust level dashboards (where their Designated Body is the subject) in addition to their personal dashboards, where the Consultant and speciality grade doctor is the subject. Consultants and speciality grade doctors will not be able to access other Consultants and speciality grade doctor dashboards.

Consultants and speciality grade doctors will be able to access pseudonymised patient data related to the numerator and denominator values displayed in their own Consultant and speciality grade doctor dashboards.

Consultants and speciality grade doctors will be able to access pseudonymised patient data related to the numerator and denominator values displayed in the Unit level dashboards to which they have access. Consultants and speciality grade doctors will not be able to identify other consultants and speciality grade doctors in the dashboards. Consultants and speciality grade doctors will be able to identify other consultants and speciality grade doctor in the pseudonymised patient data only where there are other episodes in index spells attributed to the consultant and speciality grade doctor in question.

For the purpose of this agreement Consultants and Specialty Doctors are defined as; A senior medical practitioner who is appointed to their role by an NHS Trust. A Medical Practitioner is;

“Medical Practitioner” means a person who-
- is included in the register of medical practitioners referred to in section 2 of the Medical Act 1983;
- holds a licence to practise under that Act; and
- is employed or otherwise engaged by the Trust to provide healthcare services under the NHS.

GIRFT (including NCIP) and Model Hospital are keen to use the civil registration of death data to measure mortality following procedures.

The key data fields for this purpose are date of death and cause of death. The GIRFT and Model
Hospital programmes aim to improve cost efficiency of NHS services through reducing variation in cost and clinical quality.

One of the key clinical quality metrics is death following surgical procedures. The programmes currently use HES data to calculate a number of clinical quality indicators, including in-hospital mortality. NHSI plan to switch from monitoring in hospital mortality to mortality (in any setting) over the next few months NHS Improvement will ensure that suitable controls are in place such that the data is used by the trust solely in line with the purposes set out within the agreement.

Monitor will not use data for any commercial purpose. Monitor will retain the Intellectual Property Rights to any works derived from or including the production of the National Tariff, PLICS, GIRFT data packs, NCIP product and Model Hospital Dashboard outputs.

For clarity, Monitor and NHS TDA will act as joint data controllers in common.

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). Flow down terms of the DSFC will be included in the sub licence for NCIP.

Under the Sub licence arrangements which this agreement will permit NHS trusts will have access to the following data;

Consultants and speciality grade doctors will access to NCIP Product with role based access controls (RBAC) under a sub licencing arrangement.

*HES pseudonymised patient level- including Consultant code
*Patient Reported Outcome Measures (PROMS)
*HES-Civil registration data
*Sus PBR
*DIDS
*PLICS
*Theatres data

Only data for care and treatment in English hospitals is provided under this agreement.

DSfC - NHS England - Comm — DARS-NIC-212898-X4C9W

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

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), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, NHS England commission secondary care activity for members of the Armed Forces and their families. As per the Armed Forces covenant, there are certain obligations which must be met for these patients e.g. priority treatment times. Contracts are held between NHS England and a total of 46 providers who deliver care for Armed Forces and as such the contracts are commissioned and monitored by using SUS and local provider flows. Similarly, patients within the Justice system who require secondary care, receive care from their local hospitals and the contracts for this care are commissioned and monitored by NHS England. These services and responsibilities are referred to as Direct Commissioning and are covered by statute. NHS England’s statutory functions are defined in the 2012 Health and Social Care Act and the Mandate from the Department of Health which must be published annually. A copy of the 2018/19 mandate can be found here: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/691998/nhse-mandate-2018-19.pdf The mandate sets NHS England seven objectives and these at the highest level are: 1. Through better commissioning, improve local and national health outcomes, particularly by addressing poor outcomes and inequalities. 2. To help create the safest, highest quality health and care service. 3. To balance the NHS budget and improve efficiency and productivity. 4. To lead a step change in the NHS in preventing ill health and supporting people to live healthier lives. 5. To maintain and improve performance against core standards. 6. To improve out-of-hospital care. 7. To support research, innovation and growth and to support the Government’s implementation of EU Exit in regard to health and care NHS England will use 3 Commissioning Support Units as data processors to support the Direct Commissioning BI Service as below: - North of England Commissioning Support Unit - Arden and Greater East Midlands Commissioning Support Unit - North East London Commissioning Support Unit The data will be processed by Regional Teams across England in much the same way, for the similar purposes and benefits as commissioning data is processed for any CCG. There are 5 Regional Teams located across the 3 Commissioning Support Units. 3 data processors are being utilised due to the geographical spread of national data and due to the NHS Digital-NHS England Area Team/Commissioning Hub legitimate relationship mappings currently in place. (It is not practical to deliver the service from a single NHS Digital DSCRO and single CSU, due to the level of consolidation that would be required, but the 3 CSUs can cover the whole of England.) Each data processor is assigned to specific regions, as follows: North Regional Team - North of England CSU Midlands and East Regional Team - Arden and GEM CSU London Regional Team - North & East London CSU South East Regional Team - Arden and GEM CSU South West Regional Team - Arden and GEM CSU The data processors are responsible for processing and linking the SUS+ data, Local Provider Flows, Mental Health (MHMDS, MHLDDS, MHSDS), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), National Cancer Waiting Times Monitoring Data Set (CWT) and Diagnostic Imaging data (DIDS), for the addition of derived fields, linkage of relevant data sets and analysis, contracting monitoring, reconciliation and invoice validation*, for their own regions and will work to support the relevant NHS England Regional BI Teams. *The term "invoice validation" is used to enable the data controller to use the data to check recorded activity against contracts or invoices and to facilitate discussions with providers using pseudonymised data. There is no identifiable data being requested and therefore no reliance on Section 251 support (CAG 2-03 or CAG 7-07(a-c)) and a Controlled Environment for Finance is not used. Invoice Validation is part of commissioning and has only been separated as a purpose when reliant on the specific Section 251 support (CAG 7-07(a-c)) As this is pseudonymised data, a separate purpose is not required – pseudonymised data will be used for commissioning, of which the invoice validation is part of. The level of data requested is pseudonymised and anonymised in accordance with the ICO Anonymisation Code of Practice, to be used for the purposes outlined in this application/agreement. (Commissioning Support Unit (CSU), internal NHS transfer)

Sensitive: Sensitive

When:DSA runs 2019-09-01 — 2022-08-31 2020.02 — 2021.05.

Access method: Frequent Adhoc Flow, One-Off

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Acute-Local Provider Flows
  2. Ambulance-Local Provider Flows
  3. Children and Young People Health
  4. Community Services Data Set
  5. Community-Local Provider Flows
  6. Demand for Service-Local Provider Flows
  7. Diagnostic Imaging Dataset
  8. Diagnostic Services-Local Provider Flows
  9. Emergency Care-Local Provider Flows
  10. Experience, Quality and Outcomes-Local Provider Flows
  11. Mental Health and Learning Disabilities Data Set
  12. Mental Health Minimum Data Set
  13. Mental Health Services Data Set
  14. Mental Health-Local Provider Flows
  15. National Cancer Waiting Times Monitoring DataSet (CWT)
  16. Other Not Elsewhere Classified (NEC)-Local Provider Flows
  17. Population Data-Local Provider Flows
  18. Primary Care Services-Local Provider Flows
  19. Public Health and Screening Services-Local Provider Flows
  20. SUS for Commissioners
  21. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
  22. Community Services Data Set (CSDS)
  23. Diagnostic Imaging Data Set (DID)
  24. Mental Health and Learning Disabilities Data Set (MHLDDS)
  25. Mental Health Minimum Data Set (MHMDS)
  26. Mental Health Services Data Set (MHSDS)

Objectives:

NHS England commission secondary care activity for members of the Armed Forces and their families. As per the Armed Forces covenant, there are certain obligations which must be met for these patients e.g. priority treatment times. Contracts are held between NHS England and a total of 46 providers who deliver care for Armed Forces and as such the contracts are commissioned and monitored by using SUS and local provider flows. Similarly, patients within the Justice system who require secondary care, receive care from their local hospitals and the contracts for this care are commissioned and monitored by NHS England.

These services and responsibilities are referred to as Direct Commissioning and are covered by statute. NHS England’s statutory functions are defined in the 2012 Health and Social Care Act and the Mandate from the Department of Health which must be published annually. A copy of the 2018/19 mandate can be found here:

https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/691998/nhse-mandate-2018-19.pdf

The mandate sets NHS England seven objectives and these at the highest level are:

1. Through better commissioning, improve local and national health outcomes, particularly by addressing poor outcomes and inequalities.
2. To help create the safest, highest quality health and care service.
3. To balance the NHS budget and improve efficiency and productivity.
4. To lead a step change in the NHS in preventing ill health and supporting people to live healthier lives.
5. To maintain and improve performance against core standards.
6. To improve out-of-hospital care.
7. To support research, innovation and growth and to support the Government’s implementation of EU Exit in regard to health and care


NHS England will use 3 Commissioning Support Units as data processors to support the Direct Commissioning BI Service as below:
- North of England Commissioning Support Unit
- Arden and Greater East Midlands Commissioning Support Unit
- North East London Commissioning Support Unit

The data will be processed by Regional Teams across England in much the same way, for the similar purposes and benefits as commissioning data is processed for any CCG. There are 5 Regional Teams located across the 3 Commissioning Support Units.

3 data processors are being utilised due to the geographical spread of national data and due to the NHS Digital-NHS England Area Team/Commissioning Hub legitimate relationship mappings currently in place. (It is not practical to deliver the service from a single NHS Digital DSCRO and single CSU, due to the level of consolidation that would be required, but the 3 CSUs can cover the whole of England.) Each data processor is assigned to specific regions, as follows:

North Regional Team - North of England CSU
Midlands and East Regional Team - Arden and GEM CSU
London Regional Team - North & East London CSU
South East Regional Team - Arden and GEM CSU
South West Regional Team - Arden and GEM CSU

The data processors are responsible for processing and linking the SUS+ data, Local Provider Flows, Mental Health (MHMDS, MHLDDS, MHSDS), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), National Cancer Waiting Times Monitoring Data Set (CWT) and Diagnostic Imaging data (DIDS), for the addition of derived fields, linkage of relevant data sets and analysis, contracting monitoring, reconciliation and invoice validation*, for their own regions and will work to support the relevant NHS England Regional BI Teams.

*The term "invoice validation" is used to enable the data controller to use the data to check recorded activity against contracts or invoices and to facilitate discussions with providers using pseudonymised data. There is no identifiable data being requested and therefore no reliance on Section 251 support (CAG 2-03 or CAG 7-07(a-c)) and a Controlled Environment for Finance is not used.
Invoice Validation is part of commissioning and has only been separated as a purpose when reliant on the specific Section 251 support (CAG 7-07(a-c))
As this is pseudonymised data, a separate purpose is not required – pseudonymised data will be used for commissioning, of which the invoice validation is part of.


The level of data requested is pseudonymised and anonymised in accordance with the ICO Anonymisation Code of Practice, to be used for the purposes outlined in this application/agreement.

Yielded Benefits:

Expected Benefits:

1. Supporting the annual objectives as set by the Department of Health
2. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
3. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
4. Health economic modelling using:
a. Analysis on provider performance against wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
5. Commissioning cycle support for grouping and re-costing previous activity.
6. Enables monitoring of:
a. Outcome indicators.
b. Financial and Non-financial validation of activity.
c. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
d. Case management.
e. Care service planning.
f. Commissioning and performance management.
7. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
8. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
10. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
11. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
12. Financial validation of activity, budget control and the avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care.
13. Reviewing current service provision:
a. Cost-benefit analysisand service impact assessments to underpin service transformation
b. Service planning and re-design
c. Impact analysis fordidfferent odels of productivity measures, efficiency and expereience
d. Service and pathway review
e. Service utilisation review
14. Ensuring compliance and testing of approaches with evidence and guidance.
15. Monitoring outcomes and anlaysis of variations
16. Understanding how services impact across the health economy
a. Service evaluation
b. Programme reviews
c. Analysis or productivity, outcomes, experience, plan targets and actuals
d. Assessing value for money and efficiency gains
e. Understanding impact on services on health inequalities
17. Understanding how services impact on the health of the population and patient cohorts
a. Measuring and assessing improvement in service provision, patient experience and outcomes and the cost to achieve this
b. Propensity matching and scoring
c. Triple aim analysis
18. Understanding future drivers for change
a. Forecasting health needs
b. Identifying changes in disease trends and prevalence
c. Efficiencies that can be gained for procuring services across wider footprints and from new innovations
19. Delivering services that meet changing needs of the population
a. Analysis to support policy development
b. Ethnical and equality impact assessments
c. What do next year’s contracts need to include
d. Workforce planning
20. Maximising services and outcomes within financial envelopes across health economy
a. What-if analysis
b. Cost-benefit analysis
c. Health economics analysis
d. Scenario planning and modelling
e. Investment and disinvestment ins services analysis
f. Opportunity analysis
21. Analysis of productivity, outcomes, experience, plan targets and actuals

Outputs:

1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis
3. Waiting list/time analysis
4. Reconciliation of patient level and aggregate contract monitoring information with the agreed list of NHS England commissioned drugs to identify any instances of drugs or devices not listed on the NHS England commissioned list of drugs and devices.
5. Reporting on provider progress against contractual QIPP and CQUIN schemes.
6. Reporting on contract performance against programmes for Public Health
7. Reporting on commissioned provider activity against actual activity
8. Reporting on key performance indicators for Health and Justice services:
9. Reporting on commissioned activity against agreed clinical thresholds
10. Reporting on and investigation of any significant swings in reported service performance from the previous months reporting.
11. Aggregate reports to illustrate the level of reconciliation reported between commissioning data set flows and associated Aggregate Inpatient and Outpatient contract monitoring at Specialised Service Code level and Point of Delivery.
12. Aggregate reports to illustrate the level of reconciliation reported between commissioning data sets and associated Aggregate Inpatient, Outpatient and A & E contract monitoring to indicate the match achieved at Main specialty / treatment function code level and Point of Delivery.
13. Aggregate reports to illustrate the level of reconciliation reported between commissioning data sets and associated patient level Inpatient and outpatient contract monitoring, to indicate the match achieved at Specialised Service Code level and Point of Delivery.
14. Aggregate reports to illustrate the level of reconciliation reported between aggregate data flows and associated patient level monitoring for non-standard datasets (e.g. local flows)., to match achieved at service level and Point of Delivery.
15. Patient level reporting to illustrate instances where a Provider has charged a sub-region for a drug on the list of Cancer drugs which are expected to be funded centrally as part of the Cancer Drug Fund.
16. Aggregate performance report for each provider contract including clinical service, contractual activity plan and cost, actual activity and cost, variance from plan (for both activity and finance) and projected forecast outturn (for both activity and finance).
17. Aggregate performance reports by service to show the performance by each provider contract including clinical service, contractual activity plan and cost, actual activity and cost, variance from plan and projected forecast outturn.
18. Trend analysis of the public health programme data.
19. Reporting on performance and quality KPIs.
20. Benchmarking reports of secondary dental commissioning activities
21. Trend analysis for services within a provider but also the trend of services (irrespective of provider)
22. Financial validation checks and challenges for contracted and non-contracted activity
23. Data Quality and Validation measures and monitoring against agreed data quality improvement plans.
24. Budget reporting
25. Contract Management and Modelling
26. Project/ programme level dashboards

Processing:

PROCESSING CONDITIONS:
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.

Data Processors must only act upon specific instructions from the Data Controller.

Data can only be stored at the addresses listed under storage addresses.

All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake.

Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement.

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)

ONWARD SHARING:
Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data.

Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set.

SEGREGATION:
Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked.

Where the Data Processor and/or the Data Controller hold identifiable data with opt outs applied and identifiable data with opt outs not applied, the data will be held separately so data cannot be linked.

All access to data is auditable by NHS Digital.


DATA MINIMISATION

NHS England is responsible for commissioning activities as per the NHS Act 2006 as amended by the Health and Social Care Act 2012. This gave NHS England, statutory responsibilities to directly undertake the commissioning of the following services:

• Prescribed Specialised Services
• Secondary Care Dental
• Armed Forces
• Health in Justice
• Public Health

Only data related to the above directly commissioned services will be disseminated by NHS Digital. The purpose of the direct commissioning BI service is to support only those services which are commissioned by NHS England. The data is proactively managed to ensure any data which is utilised for commissioning and monitoring of provider contracts only covers areas where there is a clear need to do so.

NHS Midlands and Lancashire Commissioning Support Unit and Greater Manchester Shared Services (hosted by NHS Oldham CCG) supply IT infrastructure for Arden and GEM Commissioning Support Unit and are therefore listed as data processors. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Interxion, Ilkeston Community Hospital (Part of Derbyshire Community Health Services NHS Foundation Trust) and Pulsant do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Direct commissioning activities are undertaken by 5 NHS Regional Teams. Each Regional Team will only get the direct commissioning data relating to their Regional Team – see table below.

The 5 Regional Teams are supported by 3 CSUs (data processors). The 3 data processors will only receive direct commissioning data for the regions which they support, as shown below:
NHS Regional Team Supporting CSU (Data Processor)
North Regional Team North of England CSU
Midlands and East Regional Team Arden and GEM CSU
London Regional Team North and East London CSU
South East Regional Team Arden and GEM CSU
South West Regional Team Arden and GEM CSU


The relevant Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS+
2. Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Demand for Service
e. Diagnostic Service
f. Emergency Care
g. Experience, Quality and Outcomes
h. Mental Health
i. Other Not Elsewhere Classified
j. Population Data
k. Primary Care Services
l. Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Diagnostic Imaging Data Set (DIDS)
7. National Cancer Waiting Times (CWT)
8. Children and Young People's Health Service (CYPHS)
9. Community Services Data Set (CSDS)
Data quality management and pseudonymisation (anonymised in accordance with the ICO Anonymisation Code of Practice) is completed within the DSCRO data is then disseminated as follows:

1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), National Cancer Waiting Times Monitoring Data Set (CWT) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to
a. North of England Commissioning Support Unit
b. Arden and Greater East Midlands Commissioning Support Unit
c. North East London Commissioning Support Unit
Each Commissioning Support Unit will only receive data relating to the regions processing the data:
- North of England Commissioning Support Unit:
o North
- Arden and Greater East Midlands Commissioning Support Unit
o Midlands and East
o South East
o South West
- North East London Commissioning Support Unit
o London
2. The Commissioning Support Units then add derived field and link data. They then provide analysis to:
a. Check recorded activity against contracts or invoices and facilitate discussions with providers.
b. Undertake contracting monitoring
c. Undertake data quality and validation checks
3. Allowed linkage is between the data sets listed in this application.
4. Each Commissioning Support Unit then passes the processed pseudonymised data and business intelligence reports to NHS England Regional Teams, who analyse the data to see patient journeys for pathway or service design, re-design and to support general commissioning and de-commissioning of services.
5. Patient level data will not be shared outside of the data controller (apart from with the data processors listed in this application/agreement) and will only be shared within the data controller and data processors on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.

SMI Comprehensive Physical Health Checks (PHSMI) GPES Extract — DARS-NIC-433629-H3M0G

Type of data: Pseudonymised

Opt outs honoured: No - Statutory exemption to flow confidential data without consent, Anonymised - ICO Code Compliant (Statutory exemption to flow confidential data without consent, Flow to de-identified environment - no analysis on confidential patient information)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 - s261(5)(d), Health and Social Care Act 2012 – s261(2)(a), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, NHS England wish to continue to use the Physical Health Checks for people with Severe Mental Illness (PHSMI) data which was collected via the General Practice Extraction Service (GPES) in order to monitor the delivery of the NHS Long Term Plan ambition to ensure that 390 thousand people with Severe Mental Illness (SMI) have their physical health needs met by receiving a comprehensive physical health check (PHSMI) and follow-up intervention. The previous version of the Agreement required an initial full year extract of the data and thereafter an extract on a quarterly basis to monitor delivery of the PHSMI programme No further data is required in this agreement other than extension to the Data Sharing Agreement to enable NHS England to continue to use the PHSMI data in order to monitor the delivery of health checks and interventions for people with SMI over the lifetime of the NHS Long Term Plan. The lawful basis for processing personal data are Articles 6.1(e) “where 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” and 9.2(j) “where the processing of personal data is necessary for archiving purposes, scientific or historical research purposes or statistical purposes in the public interest”. The aim of the extract is to track delivery of PHSMI and reduce the levels of premature mortality for people living with severe mental illness by increasing early detection and expanding access to evidence-based physical care assessment and intervention each year This data is anticipated tol help clinicians understand how well they are performing in the diagnosis and management of six elements of the PHSMI. The extract will consist of routinely recorded GP data covering alcohol consumption, blood lipids, blood glucose, smoking, BMI and blood pressure. In summary, the extraction is needed because the data is anticipated to: • help monitor health outcomes to understand whether delivery of physical health checks and follow-up interventions lead to improvements in physical health indicators in people with SMI over time, including whether any given patient retains improvements in subsequent annual health check cycles • inform whether current policy and practice exacerbate or reduce health inequalities, including an insight into which patient cohorts are accessing health checks and interventions, and whether these have the same impact in different cohorts • review whether different risk factors (for example SMI diagnosis, demographics, socioeconomic status, or frequency of contacts with primary and secondary care) can be utilised to inform risk stratification of physical health checks and determine the style or frequency of checks appropriate for various patient cohorts • assess and address local inequalities in access to and uptake of physical health checks and interventions, informing a targeted approach to improve service provision on national and local levels • help understand the impact of health checks on healthcare utilisation and the subsequent cost effectiveness of delivery. The data collection links to ICS's’ Statutory functions, responsibilities and commitments to, alongside other bodies, improve and integrate services providing physical healthcare, reduce health inequalities and reduce premature mortality across people with SMI, in line with the relevant legislation including the Public Sector Equality Duty, the Equality Act 2010, and the Health and Social Care Act 2012. Data outputs from the audit will be targeted for use by health care economies including practices, primary care networks and ICSs. Information will also be generated to inform national policy and improvement work. Outputs will show variation in diagnosis and treatment across areas, provide new information on the occurrence and co- existence of co-morbidities and allow for the assessment of characteristics of those receiving health checks (including age, ethnicity and deprivation). The adoption of the business rule set for PHSMI at individual practice level will facilitate detailed case finding and quality improvement work within practices., NHS England wish to continue to use the Physical Health Checks for people with Severe Mental Illness (PHSMI) data which was collected via the General Practice Extraction Service (GPES) in order to monitor the delivery of the NHS Long Term Plan ambition to ensure that 390 thousand people with Severe Mental Illness (SMI) have their physical health needs met by receiving a comprehensive physical health check (PHSMI) and follow-up intervention by 2023/24 and beyond. Further data is required in this agreement to enable NHS England to continue to use the PHSMI data in order to monitor the delivery of health checks and interventions for people with SMI over the lifetime of the NHS Long Term Plan. The lawful basis for processing personal data are Articles 6.1(e) “where 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” and 9.2(j) “where the processing of personal data is necessary for archiving purposes, scientific or historical research purposes or statistical purposes in the public interest”. The aim of the extract is to track delivery of PHSMI and reduce the levels of premature mortality for people living with severe mental illness by increasing early detection and expanding access to evidence-based physical care assessment and intervention each year. This data is anticipated to help clinicians understand how well they are performing in the diagnosis and management of six elements of the PHSMI. The extract will consist of routinely recorded GP data covering alcohol consumption, blood lipids, blood glucose, smoking, BMI and blood pressure. In summary, the extraction is needed because the data is anticipated to: • help monitor health outcomes to understand whether delivery of physical health checks and follow-up interventions lead to improvements in physical health indicators in people with SMI over time, including whether any given patient retains improvements in subsequent annual health check cycles • inform whether current policy and practice exacerbate or reduce health inequalities, including an insight into which patient cohorts are accessing health checks and interventions, and whether these have the same impact in different cohorts • review whether different risk factors (for example SMI diagnosis, demographics, socioeconomic status, or frequency of contacts with primary and secondary care) can be utilised to inform risk stratification of physical health checks and determine the style or frequency of checks appropriate for various patient cohorts • assess and address local inequalities in access to and uptake of physical health checks and interventions, informing a targeted approach to improve service provision on national and local levels • help understand the impact of health checks on healthcare utilisation and the subsequent cost effectiveness of delivery. The data collection links to ICS's’ Statutory functions, responsibilities and commitments to, alongside other bodies, improve and integrate services providing physical healthcare, reduce health inequalities and reduce premature mortality across people with SMI, in line with the relevant legislation including the Public Sector Equality Duty, the Equality Act 2010, and the Health and Social Care Act 2012. Data outputs from the PHSMI audit will be targeted for use by health care economies including practices, primary care networks and ICSs. Information will also be generated to inform national policy and improvement work. Outputs will show variation in diagnosis and treatment across areas, provide new information on the occurrence and co- existence of co-morbidities and allow for the assessment of characteristics of those receiving health checks (including age, gender, ethnicity and deprivation). The adoption of the business rule set for PHSMI at individual practice level will facilitate detailed case finding and quality improvement work within practices. (Agency/Public Body, internal NHS transfer)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2021-04-19 — 2022-04-18 2021.04 — 2021.05.

Access method: Ongoing

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Physical Health Checks for people with Severe Mental Illness (PHSMI)

Objectives:

NHS England and NHS Improvement (NHSE/I) wish to use the General Practice Extraction Service (GPES) to extract General Practice data in order to monitor the delivery of the NHS Long Term Plan ambition to ensure that 390K people with Severe Mental Illness (SMI) have their physical health needs met by receiving a comprehensive physical health check (PHSMI) and follow-up intervention. NHSE/I require an initial full-year extract of data and thereafter an extract on a quarterly basis to monitor delivery of the PHSMI programme.

The aim of the GPES extract is to track delivery of PHSMI and reduce the levels of premature mortality for people living with severe mental illness by increasing early detection and expanding access to evidence-based physical care assessment and intervention each year.

This data will be extracted by NHS Digital via GPES and will help clinicians to understand how well they are performing in the diagnosis and management of six elements of the PHSMI. The extract will consist of routinely recorded GP data covering alcohol consumption, blood lipids, blood glucose, smoking, BMI and blood pressure. In summary, the extraction is needed because the data will:

• help monitor health outcomes to understand whether delivery of physical health checks and follow-up interventions lead to improvements in physical health indicators in people with SMI over time, including whether any given patient retains improvements in subsequent annual health check cycles
• inform whether current policy and practice exacerbate or reduce health inequalities, including an insight into which patient cohorts are accessing health checks and interventions, and whether these have the same impact in different cohorts
• review whether different risk factors (for example SMI diagnosis, demographics, socioeconomic status, or frequency of contacts with primary and secondary care) can be utilised to inform risk stratification of physical health checks and determine the style or frequency of checks appropriate for various patient cohorts
• assess and address local inequalities in access to and uptake of physical health checks and interventions, informing a targeted approach to improve service provision on national and local levels
• help understand the impact of health checks on healthcare utilisation and the subsequent cost effectiveness of delivery.

The data collection links to CCGs’ Statutory functions, responsibilities and commitments to, alongside other bodies, improve and integrate services providing physical healthcare, reduce health inequalities and reduce premature mortality across people with SMI, in line with the relevant legislation including the Public Sector Equality Duty, the Equality Act 2010, and the Health and Social Care Act 2012.

Data outputs from the audit will be targeted for use by health care economies including practices, primary care networks and CCGs. Information will also be generated to inform national policy and improvement work.

Outputs will show variation in diagnosis and treatment across areas, provide new information on the occurrence and co- existence of co-morbidities and allow for the assessment of characteristics of those receiving health checks (including age, ethnicity and deprivation). The adoption of the business rule set for PHSMI at individual practice level will facilitate detailed case finding and quality improvement work within practices.

In the future NHSE might want to link the PHSMI primary care general practice data with other datasets including (MHSDS), the secondary care Hospital Episode Statistics (HES) data and mortality data, in order to track the monitoring and evaluation of national programme delivery across the life course and care pathway, and to determine impact on outcomes and health inequalities. This will be subject to a further DARS application.

Expected Benefits:

The NHS Long Term Plan has identified physical health checks for patients with severe mental illness as a priority, with the potential to prevent premature mortality of up to 15-20 years

Routine data collection is the essential starting point for this ambition. Without real time data, the health system will have no indication of the scale of the problem or the opportunity for improvement for patients and populations. It is the only way to systematically identify individuals whose high-risk conditions are sub-optimally managed, either through non-diagnosis, under treatment or over treatment. NICE have produced guidance on improving the physical health for people with serious mental illness (https://www.nice.org.uk/sharedlearning/improving-physical-health-for-people-with-serious-mental-illness-smi ) Data will help to focus and optimise the programme locally and nationally. This data will allow the provision of comprehensive locally specific and nationwide information related to PHSMI and associated interventions. This will help to highlight opportunities for broader professionally led quality improvement activity associated with the delivery of the NHS Long Term Plan.

In summary, the extraction is needed because the data from the audit will support:
• The monitoring and evaluation of national access targets from the NHS Long Term Plan
• Local quality improvement activity
• Measurement of the impact on population outcomes

This data will provide information on a national and local level that has not previously been available. The extract will allow analysis of primary care data beyond that currently published as part of the Quality and Outcomes Framework enabling the reporting of familiar indicators but with greater detail which will be available to inform improvements in service delivery and to reduce inequalities. For example, the extract will include data and information around SMI health checks broken down by age group which will enable Primary Care Networks to be able to optimise care. Other novel analyses will include a review of the extent to which comorbidities occur within the SMI population.

Outputs:

The first report will be published in the summer 2021. This report will focus on national data. Information will also be released at lower geographies which will show variation between Regions and ICSs, future considerations regarding releasing data at lower-level geographies (PCNs and practice level) will be made following assessment of the robustness of the data at these levels. The format for this has yet to be finalised but will ultimately form a dashboard.

All outputs will be anonymous and will not report on individual patients and no output will contain any personal identifiable data. Data will be published only in aggregate form with small numbers suppressed in line with the HES analysis guide to ensure that no individual can be identified in any output. Information will be released in different formats for different audiences and will include written reports, slide sets, dashboards and briefings/infographics.
Specifically:
- An Interactive dashboard: including national and localised findings. Localised findings will be available at different healthcare geographies.

Outputs from the data collection will be designed to inform a number of different audiences, including but not limited to:
- Providers of primary care;
- Commissioners;
- Policy makers in government and NHS England;

In the future NHSE might want to link the PHSMI primary care general practice data with other datasets including (MHSDS), the secondary care Hospital Episode Statistics (HES) data and mortality data, in order to track the monitoring and evaluation of national programme delivery across the life course and care pathway, and to determine impact on outcomes and health inequalities. This will be subject to a further DARS application.

Processing:

Personal and special category data will be collected from all participating GP Practices in England as an initial full-year extract of data and thereafter an extract on a quarterly basis. The first extract is scheduled to take place in the second half of the 2020-21 financial year and will cover the previous financial year of 2019-20. GP IT System Suppliers will extract data already held in GP Practice patient record systems and transfer this data to NHS Digital using the established General Practice Extraction Service (GPES) tool.

NHS Digital has been directed by NHS England under section 254 of the Health and Social Care Act 2012 (2012 Act) to establish and operate a system for the collection and analysis of the information specified for this service.

All GP Practices in England are legally required to share data with NHS Digital for this purpose under section 259(1)(a) and
(5) of the 2012 Act.

The legal basis for the transfer of data is given in the 'SMI Physical Health Checks Directions 2020' signed on 13th October 2020 which includes section 259(1)(a) of the Health and Social Care Act 2012 (the 2012 Act), a Data Provision Notice will be served in accordance with the procedure published as part of the NHS Digital duty under section 259(8) on the following persons:
• General Practices in England, covering the four core GP system suppliers (GPSS):
o TPP
o EMIS
o Cegedim Health Solutions
o Eva Health Technologies

Once the data is collected from GPSS, validation on the file structure and contents is carried out before files are accepted by NHS Digital’s GP Data Collector system. The data is then processed by the Data Management Service (DMS) to create a data asset. The processing involves loading the files from GPSS into a secure database and linking to corporate reference data to provide additional demographic information. The data is stored separately and only the pseudonymised view is made available to people. Data quality will be checked against the standard six data quality characteristics, which are coverage, completeness, validity, default, integrity and timeliness, as per the requirements of NHSE/I.

Many of the SNOMED CT codes used to specify the data items listed are also used in the Quality and Outcomes and Framework (QOF) and other payment extractions and therefore the data quality of these codes is expected to be high. For other SNOMED CT codes that are not used in payment extractions, the data quality may not be as high. Analysis conducted by NHSE/I will determine this. Other non-coded information will be validated against standard NHS Digital protocols. For example: patient NHS Number will be validated against the Modulus 11 algorithm and GP practice code will be validated against reference data held by NHS Digital.

Under section 259(5) of the 2012 Act, the organisation types specified in the above Scope must comply with the Form, Manner and Period of the data collection requirements.

In line with the national data opt-out operational policy guidance, national data opt-outs will not apply to the collection. However, Type 1 objections will be upheld in collecting this data from General Practices and therefore the data for those patients who have registered a Type 1 objection with their GP will not be collected. The Type 1 objection prevents an individual’s personal identifiable confidential information from being shared outside of their GP Practice except when it is being used for the purposes of their direct care.

Data flow and access: NHS Digital to NHSE/I, in summary:

a) NHS Digital will send psuedonymised data to NHSE/I via Message Exchange for Social Care and Health (MESH)
b) Data will not be stored or processed by a third party. Data will be stored in a secure NHS England network folder with named access to only a small number of analysts.

Data processing will only be carried out by substantive employees of NHS England who have been appropriately trained in data protection and confidentiality (as required in mandatory training for all NHSE employees).

Data Requirement
All fields in the dataset are required so that NHSE/I can provide analytical support to the ongoing monitoring of the
PHSMI programme. This would not be possible without the full amount of data. PHSMI GPES is a national collection so national data is required in order to assess geographical trends and identify any geographical and demographic variation in PHSMI.

Data Analysis
The data will be used to create indicators which can be used to describe, measure and summarise. This information will be reported at different geographies and by different descriptors to show variation and identify opportunities for improvement in care and outcomes. Data will be published only in aggregate form with small numbers suppressed in line with the HES analysis guide to ensure that no individual can be identified in any output. Information will be released in different formats for different audiences and will include written reports, slide sets, dashboards and briefings/infographics.

All organisations party to this agreement must comply with the data sharing framework contract requirements, including those regarding the use (and purposes of that use) by "personnel" (as defined within the data sharing framework contract
i.e. employees, agents and contractors of the data recipient who may have access to that data).

There will be no attempts made to re-identify individuals involved in this project as there is no requirement to do so.

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. There will be no requirement nor attempt to re-identify individuals from the data.

GDPPR COVID-19 – NHS England Application — DARS-NIC-384608-C9B4L

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Statutory exemption to flow confidential data without consent, Flow to de-identified environment - no analysis on confidential patient information)

Legal basis: CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002, Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 - s261(5)(d), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, (Agency/Public Body, internal NHS transfer)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2020-07-16 — 2021-03-31 2020.09 — 2021.05.

Access method: One-Off, Frequent Adhoc Flow

Data-controller type: MONITOR, NHS ENGLAND (QUARRY HOUSE), NHS TRUST DEVELOPMENT AUTHORITY, NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. GPES Data for Pandemic Planning and Research (COVID-19)
  2. Civil Registration - Deaths
  3. COVID-19 Second Generation Surveillance System
  4. Medicines dispensed in Primary Care (NHSBSA data)
  5. NHS Pathways Data Set
  6. Shielded Patient List
  7. SUS for Commissioners
  8. COVID-19 Ethnic Category Data Set
  9. Covid-19 UK Non-hospital Antigen Testing Results (pillar 2)
  10. Electronic Prescribing and Medicines Administration (EPMA) data in Secondary Care for COVID-19
  11. COVID-19 Hospitalization in England Surveillance System
  12. COVID-19 ICNARC Case Mix Programme for Adult Critical Care
  13. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
  14. Civil Registrations of Death
  15. COVID-19 Second Generation Surveillance System (SGSS)
  16. COVID-19 Electronic Prescribing and Medicines Administration (ePMA) in Secondary Care
  17. COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)
  18. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Objectives:

NHS England, also known as the ‘National Commissioning Board’ leads the National Health Service (NHS) in England. NHS England are responsible for the budget, planning, delivery and day-to-day operation of the commissioning side of the NHS in England as set out in the Health and Social Care Act 2012.

NHS England has responsibility for a wide range of purposes and hold Statutory Duties, including commissioning specialised services, paying for primary care, public health services, offender healthcare and specific services for the armed forces. NHS England is also legally required to undertake a range of non-commissioning functions, including oversight of Clinical Commissioning Group (CCG) and new care models assurance, reviewing major service changes, development of policy and financial allocations.

NHS England’s statutory duties are set out in the NHS Act 2006 and by the Health and Social Care Act 2012 amendments. To enable NHS England to assess the value, quality and effectiveness of the services it commissions, the Health and Social Care Act 2012 (Section 254) empowers NHS England to direct NHS Digital to collect the data it requires. NHS Digital are required to process confidential patient-level data, transform it into an agreed anonymised format which NHS England can legally receive and safely use without impacting the privacy of service users.

The legal bases underpinning some of NHS England’s statutory commissioning and population health management duties are set out below:

Legal Basis
Ref Statute
A1 DUTY: Eliminate discrimination, harassment and victimisation and advance equality of opportunity
A2 DUTY: Have regard to impact on services in certain areas
A3 DUTY: Payment of sums
A4 DUTY: Performance of functions outside England
A5 DUTY: Prevent people from being drawn into terrorism
A6 DUTY: Process data for the prevention or detection of crime
A7 DUTY: Provide integrated services to improve outcomes and reduce inequalities
A8 DUTY: Safeguard and promote the welfare of children
A9 DUTY: Securing continuous improvement in quality of services provided to individuals
A10 DUTY: To arrange the provision of health services in England
A11 DUTY: To collect and analyse information relating to safety of services
A12 DUTY: To commission secondary dental, armed forces and health and justice health services
A13 DUTY: To consider the economic, social and environmental benefits to be achieved through commissioning
A14 DUTY: To ensure health services are provided in an integrated way
A15 DUTY: To exercise functions relating to primary dental services
A16 DUTY: To exercise relevant public health functions
A17 DUTY: To improve quality of services
A18 DUTY: To monitor and improve the quality of care
A19 DUTY: To pay CCGs to meet their expenditure
A20 DUTY: To promote a comprehensive health service
A21 DUTY: To provide certain specified services
A22 DUTY: To provide high secure psychiatric services
A23 DUTY: To provide pharmaceutical services
A24 DUTY: To provide primary medical services
A25 DUTY: To provide primary ophthalmic services
A26 DUTY: To provide secondary community ambulance mental health services or facilities
A27 DUTY: To put and keep in place arrangements to monitor and improve the quality of health care
A28 DUTY: To secure continuous improvement in the quality of services
A29 DUTY: Understand impact of commissioning decisions on provision of services to Welsh and Scottish residents
A30 POWER: Produce documents to support counter fraud and security management functions
A31 POWER: Reimbursement for pharmaceutical remuneration
A32 POWER: To assist SoS in providing health services and exercising public health functions
A33 POWER: To commission certain health services as requested by SoS
A34 POWER: To conduct research
A35 POWER: To make payments to CCGs in respect of quality of services
A36 POWER: To pay for community services
A37 POWER: To scrutinise or review areas of the health service with local authorities
A38 REGULATION: To ensure buying decisions are fair and improve quality and efficiency of healthcare services
A39 REGULATION: To enter into prescribed arrangements between NHSE, CCGs, providers and local authorities
A40 SECONDARY LEGISLATION: Carry out financial duties
A41 SECONDARY LEGISLATION: To provide community dental, health and justice, armed forces and specialised services

In order for NHS England to discharge its statutory duties, all elements of the contracting cycle, from assessing population health needs, through service planning and contract management, to service evaluation and redesign, requires access to high quality data within the appropriate legal framework. As part of its duties, NHS England also has responsibilities to respond to major incidents.

In general data access is required for the purposes of commissioning and underpinning system activities within the NHS England demographic area, including reducing health inequalities, identifying and managing preventable and existing conditions, managing demand, monitoring pathway compliance, comparison to peers, monitoring outcomes, understanding how services impact across the health economy and designing the future healthcare system.

With the pandemic of COVID-19, which began in the United Kingdom back in January 2020, NHSX, NHS England and NHS Improvement have been tasked with leading the national data response to COVID-19. This required a Data Store (specific for COVID-19 data) to be created that ensures data can be used effectively to support the national response to protecting citizens against the COVID-19 virus. This response also includes the recovery and restoration of health services as the need for COVID-19 specific services reduce.

The NHS COVID-19 Data Store has been established under the provisions of the COPI (Control of Patient Information) notices issued by the Secretary of State for Health and Social Care using powers available to him under regulation 3 of the Health Service (Control of Patient Information) Regulations 2002, and is designed to support a range of activities, including:

● Understanding COVID-19 and impact to provision of NHS services and patient outcomes;
● Identifying and understanding information about patients or potential patients with or at risk of COVID-19;
● Delivering services to patients, clinicians, the health services;
● Planning in relation to COVID-19.

These powers give NHS England, an organisation which falls under regulation 3(3) of the COPI regulations, powers delegated by the Secretary of State to require the disclosure of confidential patient information.

The COVID-19 Data Store is a strictly controlled central point that brings together all data necessary to provide NHS England and NHS improvement analysts only, with the most comprehensive datasets related to COVID-19. There is however a requirement to ensure that all necessary data sets, required to support the national response are acquired, as this will provide a full picture of how the pandemic is impacting all areas of the National Health Service. One area of the service NHS England does not currently have data for, is Primary Care – specifically the GPES (General Practice Extraction Service) Data for Pandemic Planning and Research (GDPPR) data.

Data stored within the data store, including GDPPR, all share a common pseudo key. This means that GDPPR is linkable, however it must only be linked for purposes listed under this DSA.

The Data Protection Impact Assessment (DPIA) and Privacy Notice for the use of NHS COVID-19 data can be found at https://www.england.nhs.uk/ourwork/tsd/data-info/

NHS England requires pseudonymised GDPPR data under Regulation 3 the Control of Patient Information Regulations 2002 (COPI) Notice which was issued by the Secretary of State for Health in March 2020. The GDPPR data will be used to provide intelligence to support NHS England in their response to the COVID-19 pandemic as set out in the COPI notice and shown below:

NHS England and NHS Improvement is required to process confidential patient information in the manner set out below for purposes set out in Regulation 3(1) of COPI (insofar as those purposes relate to the current outbreak of COVID-19).

NHS England and NHS Improvement (under the legal entities of Monitor and NHS Trust Development Authority (TRA)) are joint data controllers in this agreement.

The data will be analysed so that health care provision can be planned to support the needs of the population for the COVID-19 purposes and to better understand and plan the impacts on NHS Services and patient outcomes.

Such uses cases of the data include but are not limited to:
• To help plan, monitor and manage the national response to the COVID-19 pandemic, which will help save lives.
• NHS England will be monitoring and managing jointly with PHE;
(i) outbreaks of communicable disease to anticipate downstream impacts to NHS services and patient outcomes;
(ii) incidents of exposure to communicable disease;
(iii) the delivery, efficacy and safety of immunisation programmes;
(iv) adverse reactions to vaccines and medicines;
(v) risks of infection acquired from food or the environment (including water supplies);
(vi) the giving of information to persons about the diagnosis of communicable disease and risks of acquiring such disease.
• Provide comprehensive national pictures of COVID-19 care and outcomes in England (at National, Regional and Sub regional levels) which included understanding COVID-19 and risks to public health, trends in COVID-19 and risks, and controlling and preventing the spread of COVID-19 and its impact on NHS Services and patient outcomes.
• Understand the scope and scale of variation of COVID-19 identification, diagnoses, hospitalisation, treatments, deaths across the national, regional and sub-regional areas.
• Identifying and understanding information about patients or potential patients with or at risk of COVID-19 (for example Obese or Diabetic patients).
• Delivering through NHS services including primary care to patients, the provision of information, fit notes, immunisations, and vaccinations (including school vaccinations).
• Understand both the effectiveness of the NHS 111 First Programme in reducing the risk of nosocomial transmission of COVID-19 in Emergency Departments (EDs) and the potential impact the programme may have on the wider UEC (Urgent and Emergency Care) system and primary care.
• Understanding impacts of patient access to health services for example reviewing the referrals rates to Cancer services a direct or indirect result of COVID-19 and the availability and capacity of those services or that care.
• Review and plan restoration of Health care services and providing funding where necessary to bring services back online, where COVID-19 has had an impact.

Research Ethics Committee (REC) approval is not appropriate under these conditions, as the data will be used to support analysis for policy, guidance and operational management of the NHS.

Poor management and control of COVID-19 will be associated with higher risk of hospitalisations (therefore increased demand and reduced capacity within hospitals) as well as death and long-term health complications of patients. Those who are from a minority ethnic background as well as those patients that have underlying health conditions are more vulnerable to adverse health outcomes from COVID-19.

To support these patients, NHS England will be looking to perform a system level risk stratification. This means NHS England will need to know the overall population and be able to understand the cohorts of patients that are more susceptible to COVID-19. This will be done nationally using Population Segmentation – identifying groups of patients based on diagnoses, ethnicity etc, where there is no requirement to re-identify patients. It is therefore not the same as ‘patient level risk stratification’ as known to be done within GP Practices, where re-identification of patients is needed for the provision of direct care.

Looking at the Primary care system as a whole, the 111 First programme is anticipating an increase in the use of NHS 111 so it is important to understand how any increase in 111 demand impacts on demand for primary care services and the wider urgent and emergency care (UEC) system.

Below is a specific example of how the data will be used and linked. There are other use case examples in a separate document provided alongside this application. These are:
• Use Case 01 – 111 First Programme Evaluation
• Use Case 02 – Public health screening
• Use Case 03 – Flu Vaccination Programme
• Use Case 04 – Mortality increased risk in patients that are overweight
• Use Case 05 – Vaccinations & Immunisations
• Use Case 06 – Restoration of Health Care Services

Data will only be linked with other COVID-19 data where the analysis required has gone through an approval process. This ensures that it is clearly in line with the purposes of NHS England and the COPI Notice.

Access to both GPES and 111 Pathways data, will allow robust analysis to be conducted to inform decision making and development of improved models of care in the UEC system and mitigate the risk of other parts of the health services becoming overburdened with additional demand. It would not be statistically valid to undertake the analysis only using an extract of the GPES data for the cohort who presented at 111, as this would not provide a robust comparison with baseline activities.

The GDPPR data will be used for specific bespoke use cases such as the one illustrated above, it would not be feasible to utilise the Trusted Research Environment (TRE), and therefore a direct feed from NHS Digital to NHS England is required, in order for the Organisation to perform the additional duties in supporting with the COVID-19 efforts.

Under GDPR, NHS England can rely on Article 6(1)(c) – Legal Obligation to receive and process the Disseminated data from NHS Digital for the Agreed Purposes under the Recipient COPI Notice. As this is health information and therefore special category personal data the Recipients can also rely on Article 9(2)(h) – processing is necessary for the purposes of preventative or occupational medicine and 9(2)(i) – processing is necessary for reasons of public interest in the area of public health.

With regard to the application of the Type 1 and national data opt outs to data processed under the COPI notice, our view is that as the COPI notice places a legal requirement on organisations to process Confidential Patient Information (CPI), opt outs will not apply to any data accessed by virtue of the notice. In any case, as set out in NHS Digital’s National Data Opt-Out operational policy guidance CPI processed under regulation 3 of the COPI regulations is not subject to the national data opt- out.

The data received by the Joint Data Controllers is pseudonymised data which is processed under strict controls and therefore meets the ICO Anonymisation Code of Practice.

Expected Benefits:

• Reduce deaths associated with COVID-19
• Support primary care to increase capacity and to meet heightened demand as a result of a left shift based on 111 first
• Reallocation of resources and correctly allocate resources in line with demand
• Bring in additional workforce support
• Assists commissioners in making decisions to better support patients
• Identifying COVID-19 trends and risks to public health
• Increase resilience in supply chain for PPE based on localised demand from primary care
• Enables NHS England to provide guidance and develop policies to respond to the outbreak
• Controlling and helping to prevent the spread of the virus
• NHS England can share a common understanding of activity levels across the system in regard to COVID-19.
• Better activity data will also enable a more robust national planning process and improve the allocation of resources across the system. This will support the response to the pandemic but also the recovery of services.

Outputs:

Any outputs to 3rd parties not included as a Data Controller/Processor in this application/agreement must be aggregated
(with small number suppression applied in line with NHS Digital requirements).

Within 1 week of NHS England receiving the data from NHS Digital, it will be able to use the dataset to provide analysis that starts to respond to the following:

• Support the NHS response to COVID-19
• Analyse the spread of COVID-19 diagnoses geographically and demographically, to identify any trends. Appointment activity will also be analysed to better understand use of non-face to face consultation trends and potential differences across geographical areas.
• Operational planning to predict likely demand on primary, community and acute service for vulnerable patients.
• Analysis of resource allocation.
• Diagnosing and monitoring the effects of COVID-19 at a National, Regional and sub regional level.
• Ensuring NHS England has adequate data to inform that interventions and measures put in place to reduce the transmission of COVID-19 are being effective and impactful.
• Analyse factors that result in increased service utilisation for COVID-19 patients.
• Start building modelling and forecasting tools for COVID-19 from Primary care perspective. Learning from and predicting likely patient pathways in order to influence early interventions and other alternatives for patients.

Processing:

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

The bespoke Use cases as highlighted in Section 5a, it would not be feasible to utilise the Trusted Research Environment (TRE), and therefore a direct feed from NHS Digital to NHS England is required.

Data Processors must only act upon specific instructions from the Joint Data Controllers.

The COVID Data Store consists of different areas for processing, and one of those is the Palantir Foundry platform. The GDPPR data will not be processed by Palantir or ingested into the Foundry platform. Palantir Foundry Platform are not involved with the dataset, storage or other form of processing under this application

Under the terms of the DSA, this data can only be accessed by NHSE and NHSI employees and can not be onwardly shared (which for the avoidance of doubt, includes extracts and/or access to online systems within or outside of NHSE and NHSI).

All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake.

Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement.

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

The Joint Data Controllers will keep their cut of the electronic Disseminated data in an encrypted form and take all required security measures to protect the Disseminated data and they will not generate copies of their cuts of the Disseminated data unless this is strictly necessary. Where this is necessary, the Joint Data Controllers will keep a log of all copies of the Disseminated data and who is controlling them and ensure these are updated and destroyed securely.

The GDPPR data will only be processed by the Joint Data Controllers teams under strict access controls. It will not be disseminated outside of the Joint Data Controller's boundaries and will only be linked with other COVID-19 data where the analysis required has gone through an approval process which demonstrates that it is clearly in line with the purposes outlined in section 5a.

There will be no Sub-licencing and the GDPPR data will not be shared outside of NHS England.

SEGREGATION:
Where the Data Processor and/or the Joint Data Controllers hold both identifiable and pseudonymised data, the GDPPR data will be held separately so data cannot be linked without appropriate authorisation with pre-approved justification.

AUDIT:
all processing and use of data provided under this DSA (including derivatives of the data) is auditable by NHS Digital in accordance with the Data Sharing Framework Contract and NHS Digital terms.

Under the Local Audit and Accountability Act 2014, section 35, Secretary of State has power to audit all data that has flowed, including under COPI.

Microsoft Limited provide IT infrastructure and are therefore listed as data processors. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
- GDPPR Data
Pseudonymisation is completed within the DSCRO (GEM DSCRO / NW DSCRO) and is then disseminated as follows:
1. Pseudonymised GDPPR data is securely transferred from the DSCRO to the Joint Data Controllers / Processor
2. Allowed linkage is between the data sets contained within point 1.
3. Aggregation of required data will be completed by the Joint Data Controllers (or the Processor as instructed by NHS England).

Any further reports sent beyond the joint data controllers and processors as stipulated in this agreement will contain aggregate data only, and will be subject to the disclosure controls of the relevant datasets as NHS Digital and ONS guidance: https://www.ons.gov.uk/methodology/methodologytopicsandstatisticalconcepts/disclosurecontrol/healthstatistics

Analysis within the Joint Data Controllers:
The Joint Data Controllers may at any time require any of its Commissioning Support Units (CSUs) to undertake activities on its behalf for specific project(s) under a Service Level Agreement. All NHS CSUs are therefore listed below and operate as NHS England teams rather than separate legal data processors. This does not mean that all of NHS England CSU’s will access GDPPR data. This DSA will be updated to add further datasets already provided by NHS Digital and therefore including all NHS England processing teams ensures transparency:

• Arden and Greater East Midlands Commissioning Support Unit (AGEM CSU)
• NHS North of England Commissioning Support Unit (NECS)
• NHS North & East London Commissioning Support Unit (NEL CSU)
• NHS South, Central & West Commissioning Support Unit (SCW CSU)
• NHS Midlands and Lancashire Commissioning Support Unit

When the NHS England CSU teams are undertaking analysis they are prohibited from sharing anything other than anonymous data with any third parties. In this instance, “anonymous data” means data that is aggregated (with small numbers suppressed in line with NHS Digital guidance).

Processing activities undertaken only take place on pseudonymised patient-level data and would include:
• Data quality checks
• Data validation
• Generation of ad-hoc analysis and reports to support specific projects

A lead CSU will be nominated for each project. This approach ensures that the Joint Data Controllers can flexibly meet demand across the NHS system.
AGEM CSU is the only identified NHS England CSU team processing the GDPPR dataset.

NHS England - Pilot Ambulance Data Set for commissioning purposes — DARS-NIC-427822-X5G6N

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(5)(d), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; Health and Social Care Act 2012 - s261(5)(d)

Purposes: No (Agency/Public Body)

Sensitive: Sensitive

When:DSA runs 2021-02-01 — 2022-03-31 2021.01 — 2021.05.

Access method: One-Off, Frequent Adhoc Flow

Data-controller type: MONITOR, NHS ENGLAND (QUARRY HOUSE), NHS TRUST DEVELOPMENT AUTHORITY

Sublicensing allowed: No

Datasets:

  1. Ambulance Data Set (Pilot)

Objectives:

NHS England and NHS Improvement have directed NHS Digital to pilot the collection and analysis of Ambulance Service data in England with a view to improving the quality and consistency of this data as laid out in the Ambulance Services Data Set Discovery Directions 2020; https://digital.nhs.uk/about-nhs-digital/corporate-information-and-documents/directions-and-data-provision-notices/nhs-england-directions/ambulance-services-data-set-discovery-directions-2020

This Ambulance Service pilot data set is required by NHS England and NHS Improvement to contribute to the assessment of the pilot collection.

The NHS Long-Term Plan 2019 sets out a commitment to develop an ambulance data set to: “…bring together data from all ambulance services nationally in order to follow and understand patient journeys from the ambulance service into other urgent and emergency healthcare settings”. The Ambulance Data Set project seeks to deliver that long-term plan commitment. The project is owned by NHS England and NHS Improvement, operating with the authority of the Urgent and Emergency Care Transformation programme under the title of the ‘Joint Ambulance Improvement Programme’

Additionally, in response to the significant demand for Ambulance Services and data to support pandemic research and planning, NHS England and NHS Improvement have statutory responsibilities to continue to improve quality of health care services at all times, and requires data to do this.

Expected Benefits:

As the data being shared is from a pilot for a proposed Data Collection the benefits are in the potential of what could be delivered by the end product data set. This future data set will enable NHS England and NHS Improvement to improve the commissioning of services involved in Emergency Care leading to better outcomes for users of the related services.

Outputs:

Testing and evaluation reports of the Pilot Ambulance Data Set.

Processing:

Processing Conditions
Data must only be used as stipulated within this Data Sharing Agreement.

Data Processors must only act upon specific instructions from the Data Controller.

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

No record level data will be linked other than as detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement.

All access to data (by data controllers and data processors) is managed under Role and task-Based Access Controls. Users can only access data authorised by their role, for a task they are undertaking.

Pre-publication data:
• Where unpublished management information/data have been supplied, the following additional ‘conditions of use’ are applicable to reduce the risk of a breach of the Code of Practice for Statistics which may damage the public trust in Official Statistics. Unpublished management information includes data which has been supplied in advance of release of the data as an Official Statistic.
o Access to unpublished management information will be kept to a minimum. A record of which groups of people have access to this data should be maintained by the IAO of the NCDR. Unpublished management information will be under separate access to ensure that only those who can access the data prior to publication can do so and that purposes linked to access to the data are recorded. It is expected that access will only be for staff in NHS E/I Teams and Direct Commissioning (Arden and Greater East Midlands Commissioning Support Unit).
o There cannot be any public use of unpublished management information which could undermine the official statistics and thus breach the Code of Practice for Statistics. This includes any public statement that prejudges or pre-empts the contents of any subsequent statistical release, or any ad hoc or selective comments on, or reporting of, unpublished data.
o Access to unpublished management information has been granted for managerial, operational, commissioning or other appropriate decision-making purposes. You must not share or discuss the data, or any results or documents based on it, with anyone else or use it for any other purpose.
o Unpublished management information may be discussed between other people who have access to the information and with the relevant NHS Digital production team
o Any results or documents produced should show that the data are pre-publication restricted.
o All users of unpublished management information must abide by these ‘conditions of use’.
o Any accidental or wrongful release of the data must be reported immediately to NHS Digital. Wrongful release includes indications of content, including descriptions such as “favourable” or “unfavourable”. If in doubt you should consult the NHS Digital production team in the first instance who can advise.
o Any breach in these ‘conditions of use’ may result in removal of access to unpublished management information.

Data Processor Specific Conditions
Microsoft Limited provide Cloud Services for Arden and GEM Commissioning Support Unit and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

NHS Midlands and Lancashire Commissioning Support Unit and Greater Manchester Shared Services (hosted by Salford Royal NHS Foundation Trust) supply IT infrastructure for Arden and GEM Commissioning Support Unit and are therefore listed as data processors. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Ilkeston Community Hospital (Part of Derbyshire Community Health Services NHS Foundation Trust) and Wrightington, Wigan and Leigh NHS Foundation Trust do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Data processor 1&2 - NHS England and NHS Improvement
NHS England and NHS Improvement will be provided access to analyse a pseudonymised version of the pilot Ambulance Data Set via the NHS Digital Data Access Environment (DAE).

The project team will analyse the data on DAE in line with the purposes listed above only.

Once the data has been analysed it will be destroyed in line with NHS Digital's Data destruction policy.

Only registered DAE users will have access to record level data downloaded from the system. Following completion of the analysis the record level data will be securely destroyed

Data processor 3 - NHS Arden and Greater East Midlands Commissioning Support Unit
The pilot ambulance dataset is also made available through Arden and Greater East Midlands DSCRO as follows:

1. The pilot dataset is pseudonymised at the Arden and Greater East Midlands DSCRO.

2. The pseudonymised extract of the dataset is securely sent from the Arden and Greater East Midlands DSCRO to NHS Arden and Greater East Midlands Commissioning Support Unit.

3. The data is then processed by NHS Arden and Greater East Midlands Commissioning Support Unit for the purposes set out in this Agreement only.

NHS England - DSfC - NCDR amendment 2019 — DARS-NIC-139035-X4B7K

Type of data: Pseudonymised

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261(5)(d); 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(5)(d), Health and Social Care Act 2012 - s261(5)(d); Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii), NHS England De-Identified Data Analytics and Publication Directions 2023

Purposes: No, (Agency/Public Body, internal NHS transfer)

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

When:DSA runs 2019-04-01 — 2022-03-31 2020.02 — 2021.05.

Access method: Frequent Adhoc Flow, One-Off, Ongoing

Data-controller type: NHS ENGLAND (QUARRY HOUSE), MONITOR, NHS ENGLAND (QUARRY HOUSE), NHS TRUST DEVELOPMENT AUTHORITY

Sublicensing allowed: No

Datasets:

  1. Acute-Local Provider Flows
  2. Ambulance-Local Provider Flows
  3. Assuring Transformation (Pseudo)
  4. Children and Young People Health
  5. Civil Registration - Deaths
  6. Clinical Registries for Commissioning
  7. Community Services Data Set
  8. Community-Local Provider Flows
  9. Demand for Service-Local Provider Flows
  10. Diagnostic Imaging Dataset
  11. Diagnostic Services-Local Provider Flows
  12. Emergency Care-Local Provider Flows
  13. Experience, Quality and Outcomes-Local Provider Flows
  14. Improving Access to Psychological Therapies Data Set
  15. Maternity Services Data Set
  16. Mental Health and Learning Disabilities Data Set
  17. Mental Health Minimum Data Set
  18. Mental Health Services Data Set
  19. Mental Health-Local Provider Flows
  20. National Cancer Waiting Times Monitoring DataSet (CWT)
  21. National Diabetes Audit
  22. Other Not Elsewhere Classified (NEC)-Local Provider Flows
  23. Patient Reported Outcome Measures
  24. Population Data-Local Provider Flows
  25. SUS for Commissioners
  26. Civil Registration - Births
  27. e-Referral Service for Commissioning
  28. Summary Hospital-level Mortality Indicator
  29. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
  30. Medicines dispensed in Primary Care (NHSBSA data)
  31. Improving Access to Psychological Therapies Data Set_v1.5
  32. Alcohol Dependence
  33. Ambulance Data
  34. Tobacco Dependence
  35. Continuing Healthcare Dataset
  36. Emergency Care Data Set (ECDS)
  37. Hospital Episode Statistics Accident and Emergency
  38. Hospital Episode Statistics Admitted Patient Care
  39. Hospital Episode Statistics Critical Care
  40. Hospital Episode Statistics Outpatients
  41. Ambulance Data Set (Pilot)
  42. Civil Registrations of Death
  43. Community Services Data Set (CSDS)
  44. Diagnostic Imaging Data Set (DID)
  45. Improving Access to Psychological Therapies (IAPT) v1.5
  46. Mental Health and Learning Disabilities Data Set (MHLDDS)
  47. Mental Health Minimum Data Set (MHMDS)
  48. Mental Health Services Data Set (MHSDS)
  49. Patient Reported Outcome Measures (PROMs)
  50. Summary Hospital-level Mortality Indicator (SHMI)
  51. Hospital Episode Statistics Accident and Emergency (HES A and E)
  52. Hospital Episode Statistics Admitted Patient Care (HES APC)
  53. Hospital Episode Statistics Critical Care (HES Critical Care)
  54. Hospital Episode Statistics Outpatients (HES OP)
  55. Ambulance Data Set
  56. Adult Social Care
  57. Cardiovascular Disease Prevention Audit (CVD Prevent Audit)
  58. Linked-Patient Level Costing Integrated Data Set (Linked-PLCINTDS)_NHSI

Objectives:

NHS England will carry out analysis on a variety of pseudonymised datasets. This collection of datasets has been referred to as the “temporary National Repository” (tNR), and is now known as the National Commissioning Data Repository (NCDR).

The requested datasets are required to ensure that NHS England can meet its statutory duties (as per NHS Act 2006 and the Health and Social Care Act 2012 s13N,s23) and to meet the requirements of the Five Year Forward View. The objective for processing can be summarized as the provision of an ad-hoc and routine analysis and reporting service to support the work of NHS England (NHSE) in the following responsibility areas:

1. Proactive management of commissioned services – including contract management, performance management, needs and inequalities analysis, benchmarking, service review and development, planning, budgets and allocations and general commissioning assurance activities
2. Analysis and reporting to support QIPP (Quality, Innovation, Productivity and Prevention) programme activities
3. Data quality analysis and data quality management, to ensure data processing has been carried out effectively
4. Advanced analytics to support evaluation of service transformation.

In general access to and linkage of the data into NCDR has permitted NHS England to carry out proactive management of commissioned services, which includes contract management, performance management, needs and inequalities analysis, benchmarking, service reviews as well as development, planning, budgets and allocations and general commissioning assurance activities. An example of this is where service reviews in terms of access have taken place and the findings showed that the uptake was low due to location of the service. With the analysis and intelligence gained from using the data, the service has been relocated to a more accessible place. Future access and analysis of the data will confirm the anticipated benefits that the service is reaching and is accessible by more people.

Analysis and reporting to support QIPP (Quality, Innovation, Productivity and Prevention) programme activities, have also been supported by developing and using dashboards to support decision making at all levels within NHS England. The dashboards have been a valuable resource of information to demonstrate areas of innovation and improvement and share best practice.

Access to the data, has helped drive understanding of Data quality analysis and data quality management. NHS England have been able to identify the gaps of coverage and quality in certain areas; for example, feeding back to NHS Digital of missing data items from the MHSDS data set. Working jointly to understand the issues have helped resolve some of these data concerns, from both commissioner and provider prospectives.

To better understand the relationship between physical and mental health, NHS England will link physical and mental health record level data. This is an area where the evidence is currently relatively weak. Linking this data will ensure commissioners can understand full patient pathways for their patients and plan their care, for example NHS England cannot currently answer questions such as whether patients with mental health issues are at a higher risk of particular outcomes (e.g. hospital admissions, re-admissions, increased lengths of stay).

It is anticipated that NHS England will develop this resource and request additional datasets from NHS Digital. Any additional datasets will only be included in this agreement subject to application to NHS Digital. The reasons for needing the datasets included in this agreement are as follows:


SUS (A&E, OP, APC, and ECDS):
SUS data is used extensively in local, regional and national performance management, in the development of national policies (e.g. A&E plan, demand and capacity modelling for elective care) and in resource and activity planning.
SUS will also contribute to:

1. Effective performance and contract management of the health and care system
2. Reducing the burden on Local Providers through eventual cessation of daily sitreps (situation report showing patient flow through A&E to help identify and make improvements to systems) which will be replaced by ECDS daily flows


Mental Health (MHMDS, MHLDDS, MHSDS) and Assuring Transformation (AT):
The 2016 Five Year Forward View for Mental Health report from the Mental Health Taskforce sets out the start of a ten-year journey for the transformation of mental health services. The Mental Health data is crucial in monitoring progress against the Five Year Forward View.

MHSDS data has also been expanded to include extensive information on people with learning disability and/or autism. The annual learning disability provider census, which ran from 2013-15 has been stood down, and all relevant content is now included within MHSDS. In addition, the content of the commissioner-based Assuring Transformation (AT) data collection has been included within MHSDS, with a goal to stand down AT when MHSDS data quality and completeness reach acceptable levels. Both the census and AT cover only inpatient care. There is currently no other data set which gives details of specialist community and outpatient services used by people with learning disability and/or autism. This is a high-profile policy area and it is important that NHS England can monitor the quality and completeness of Mental Health data, so that this data can become the single, definitive source of information about people with learning disability and/or autism using NHS-funded services. Access to patient-level data will also allow more detailed modelling and segmentations than is available through published data.

NHS England therefore needs to be able to monitor the quality and completeness of Mental Health data, so that the data can become the single, definitive source of information about people with learning disability and/or autism using NHS-funded services. As there is a requirement for further segmentation beyond the existing Data Quality reporting by NHS Digital, patient-level data is required. This is also true for other elements of Mental Health data (e.g. early intervention in psychosis) where NHS England have set-up aggregate data collections from providers until the quality of MHSDS can be improved. This increases burden and causes confusion.

Detailed patient-level data is also required to compare Assuring Transformation and MHSDS inpatient data. This is necessary to identify under- and over-reporting in MHSDS (compared to AT) and to identify where patient records are inconsistent across the two data sets. Assuring Transformation is currently being used to monitor inpatient trajectories as part of the three-year national transformation plan ‘Building the right support’. If the monitoring data set switches to MHSDS before the end of this three-year period, NHS England needs to have absolute confidence that the two data sets are comparable and compatible.

The need for increased access to Mental Health and IAPT data is widespread given the relative lack of evidence (as compared to measuring physical health), despite £34 billion being spent each year on mental health (source: MH FYFV). The data will allow NHS England to better monitor (for example by looking at local variation or the links with physical health) progress against some of the priority actions identified in the MH FYFV, such as waiting time standards for early intervention in psychosis. Data access will facilitate the development of new standards e.g. on eating disorders or out of area placements (where patient-level data will allow us to monitor the impact of various thresholds). To monitor progress against policy programmes NHS England need high quality data, and access to Mental Health and IAPT will allow NHS England to assist in driving up quality, and cease the aggregate data collections which are currently in place (so reducing burden on providers and administrative costs).


Improving Access to Psychological Therapies (IAPT) (including additional payment data, and wave 1+2 pilot sites):

The Improving Access to Psychological Therapies (IAPT) programme began in 2008 and has transformed treatment of adult anxiety disorders and depression in England. Over 900,000 people now access IAPT services each year, and the Five Year Forward View for Mental Health committed to expanding services further alongside improving quality. IAPT services provide evidence based treatments for people with anxiety and depression (implementing NICE guidelines).

In addition, there is a strong policy need to understand the linkage between physical and mental health. Physical and mental health are closely linked – people with severe and prolonged mental illness are at risk of dying on average 15 to 20 years earlier than other people – one of the greatest health inequalities in England. Two thirds of these deaths are from avoidable physical illnesses, including heart disease and cancer, many caused by smoking. In addition, people with long term physical illnesses suffer more complications if they also develop mental health problems.

To measure the impact of new integrated IAPT services and inform future rollout, NHS England has commissioned Imperial College to analyse the impact of Integrated IAPT services. This will include analysis on outcomes and healthcare utilisation, with the aim of collecting evidence to build a strong case for commissioners to support implementation across the NHS.
Additionally, IAPT payment data is requested to aid the testing and implementation of a currency model for IAPT services that is predicated upon the delivery of outcomes and quality metrics related to treatment that are currently captured within the IAPT dataset.

Other benefits include enabling the principle of the money following the patient, which is a key enabler of the policy of attaining parity between mental health and physical health. This can only be achieved by an appropriate balance of resources.

The Five Year Forward View for Mental Health and Implementing the Five Year Forward View for Mental Health include commitments to expand Improving Access to Psychological Therapies (IAPT) services to meet 25% of need by 2020/21. Most of the expansion will be in ‘Integrated IAPT’ services, co-located in and integrated with physical health services, and focused on people with anxiety/depression in the context of long-term physical health problems and/or people with distressing and persistent medically unexplained symptoms (MUS). The expansion is expected to deliver quality improvements across local health economies that would enable better planning of resources so they are utilised more effectively.

To support the development of integrated IAPT services, pilots are being supported as Integrated IAPT Early Implementers in 2016/17 and in 2017/18. Early Implementers will work collaboratively to design and implement high quality new services, and modify clinical pathways.

It is anticipated that with a more joined up approach there will be an improvement in access to services for patients who need treatment of co-morbid physical and mental health problems. The aim is to ensure that patients have the access they need as and when required with a more streamlined care pathway. Therapists will be co-located within long term conditions / medically unexplained symptoms (MUS) care pathways as part of multidisciplinary teams.

NHS England is supporting Early Implementer pilot sites to deliver new Integrated IAPT services. To understand how Integrated IAPT services can be implemented and their effects, NHS England have commissioned an analysis of the impact of ’Integrated IAPT’ services on health outcomes and healthcare utilisation. The aim of this work is to collect evidence to build a strong case for commissioners to support a further rollout of Integrated IAPT and to understand new ways of working.

Analysis of these dimensions will be vital in informing the future roll-out of integrated IAPT services, and the IAPT data included in this agreement is required to carry out this analysis.

To measure the impact of new integrated IAPT services and inform future rollout, NHS England has commissioned Imperial College to analyse the impact of Integrated IAPT services. This will include analysis on outcomes and healthcare utilisation, with the aim of collecting evidence to build a strong case for commissioners to support implementation across the NHS.


Local 111 Data:
44 lead CCGs already have a contract in place for 111 services and there are currently different models for how 111 services are commissioned and integrated within a locality. By collecting 111 data centrally at a national level, local best practice can be identified through benchmarking and provide the evidence to better understand the most effective model for integration of the various services associated with urgent and emergency care. In order to do this, NHS England requires CCGs to continue to collect data from their local services and provide specific metrics for Urgent & Emergency Care (UEC) so that this is also available in the national UEC Dashboard that North of England Commissioning Support Unit will collate for NHS England nationally. These metrics are aggregated (small numbers suppressed in line with NHS Digital requirements).

The national UEC Dashboard will enable both CCGs and NHS England to have a consistent way of reviewing UEC services, which will be captured in all CCG DSAs (in addition to this NHS England agreement). It will also provide a consistent method for pathway analysis, so that CCGs can compare and contrast their performance with other UEC models across the country. Linkage through to their own local reporting will further allow them to better understand their local pathways.

The proposed approach is the provision of a single national system, white-labelled and provided locally to CCGs. The RAIDR-111 dashboard is a tool specifically developed by NECS to support the UEC system. RAIDR-111 will deliver a single yet comprehensive view of the Integrated Urgent Care system nationally, meeting the needs of many differing audiences – NHSE, STPs, A&E Delivery Boards, and CCGs. The dashboard needs to combine 111 call outcome data with the linked secondary care SUS pseudonymised record level data, showing A&E attendance and treatment received. The dashboard provides a single version of the truth accessible and drillable at national, regional, STP, and CCG level – all able to be aggregated up and down, at the fingertips of the users. These metrics are aggregated (small numbers suppressed in line with NHS Digital requirements).

NHS Digital will link the local 111 data with a number of fields from national SUS data in order to generate the dataset required to populate the urgent care dashboard. This linked 111/SUS data set have the consistent pseudonym applied and subsequent upload to the NCDR. This will enable the urgent care dashboard to be populated, which will allow NHS England to understand and benchmark urgent care patient flows and service provision.
Further linkage with other NCDR data sets is needed in order to fully understand the activities, pathways and outcomes of patients that enter the system via the 111 service. These data sets will include wider SUS data (APC, OP, A&E), IAPT and the mental health data sets (MHMDS, MHLDDS, MHSDS).

South Central & West CSU (SCW) have also been commissioned to undertake work on behalf of NHS England in relation to the 111 data. SCW will utilise the data to assess whether increasing the proportion of 111 calls handled by a clinician reduces the proportion of callers that subsequently attend A&E as well as understanding the impact on ambulance dispositions and GP dispositions.

The data will be used to understand the impact on the whole Integrated Emergency Care system of an increase in the resources in the Clinical Assessment Service (CAS) of 111. The data will be used to show any change in disposition of the patients within the 111 system and any impact that it has on the wider system of urgent care service providers.
In order for the evaluation to effectively establish the activity, disposition and impact changes SCW will require national data. This will enable changes in services as a result of wider factors (such as demographics, seasonality and national drivers such as the recommendations coming out of the Next Steps on the Five Year Forward View) to be taken into account.


Community (CYPHS, CSDS – Community Services Data Set (replacing CYPHS)):
NHS England requires access to community data to enable the comparison of outcomes from community healthcare services and ensure that these services are commissioned in a way that improves the health of the population and reduces inequalities.

NHS England also requires community data to support allocations analysis in order to adhere to statutory duties around allocation of budgets for commissioning NHS services, and in doing so adhering to the principle of ensuring equal access for equal need. Although NHS England has statistical models to predict the need for different health services across the country to inform the allocations process, there is currently no model for community services due to a lack of robust data at the national level.

The CYPHS dataset will be undergoing the removal of the age restriction making it an all ages dataset (CSDS). There will also be additional development of this dataset resulting in a new specification.


Maternity Services Data Set (MSDS) including currency extract:
NHS England requires access to maternity data to enable the comparison of outcomes from maternity healthcare services and ensure that these services are commissioned in a way that improves the health of the population and reduces inequalities. This data is required to ensure NHS England can satisfy its statutory responsibility to assure maternity services that are commissioned, changed or redesigned by CCGs and support the development of relevant health and care policies and financial allocations.

NHS England also requires national maternity data in order to refresh the allocation formula to inform the next allocations round. Access to maternity patient level data will support the work will enable NHS England to further develop currencies for maternity services.


Diagnostic Imaging Dataset (DID):
National DID data is required by NHS England to understand the quality of care and patient outcomes. NHS England commission all specialised services activity for two diagnostic tests - PET-CT and Cardiac MRI, and therefore requires access to the relevant data for effective commissioning of these.

Furthermore, the dataset provides a more complete picture of all imaging activity including those performed at mobile/independent sector diagnostic units and is therefore more complete than local commissioning flows that are currently received. It will be used alongside other data sources (such as SUS) to undertake specific commissioning activities, including creation of commissioning dashboards, analysis of imaging activity and improving the understanding of diagnostic services by diagnostic modality.

NHS England has been granted access to a subset of test DIDs data, which contains over 100 million records. Access to this data facilitated an understanding of the distribution of the time between a test being requested and actually carried out by type of test, provider, by some patient characteristics and over time. This is key to deepening the understanding of what characteristics are associated with the longest delays; particularly with respect to cancer diagnoses, the early detection of which is a key objective in the NHS Long Term Plan. Access to the full dataset on a regular basis will significantly improve understanding of the elective patient pathway from initial outpatient to final treatment. This access will also increase visibility of which parts of the care pathways need improvement where delays often occur (for example), and support improvement programmes which analyse diagnostic waiting times to identify demographic variability of service, inequality in treatment provision and variation in treatment outcomes in relation to length of time between referral and diagnosis.

The DID dataset is expected to be completed by all providers of NHS services, and as such covers independent sector providers for PET CT etc. which NHS England’s existing data flows might not cover. It also captures all imaging performed at mobile diagnostic units and therefore is likely to be more complete than current commissioning flows. Release of DID data will allow NHS England to investigate these underlying concerns around coverage and where the gaps are.

The DID data would be linked with patient level monitoring received as part of the commissioning process, as well as costing flows such as the local price information, in order to understand the cost of the service. The data would also be linked with SUS.
NHS England will be primarily focusing on cardiac MRI and PET CT as these services are commissioned centrally irrespective of whether the patient would traditionally be paid for by CCG or NHS England.

Access will also enable line by line reconciliation with patient level flows, following which NHS England could consider turning off the local data flow, in favour of DID, which would release significant burden on trusts.


Cancer Waiting times (CWT):
NHS England requires access to CWT data so it can be used to monitor times taken to diagnose and treat patients with cancer across the country, and ensuring that wait times are in line with the expectations and rights of patients in the NHS Constitution. The CWT data is also needed to enable the comparison of cancer waiting times from NHS Providers, to understand the scope and scale of variation across the national, regional and sub-regional areas.

The data will be used to:

• Monitor cancer waiting times targets at national and regional levels.
• Identify variances in waiting times across the country and focus on improving the services and reducing inequalities.
• Produce monthly and quarterly Official Statistics.
• Regional teams and the Commissioning Operations Directorate will use aggregate data for the purpose of performance
• management.
• investigate these underlying concerns around coverage and where the gaps are.
• Review and plan service improvements

Comparison of performance by tumour type aggregate reports will provide insight into how adjustments and general operation of the CWT dataset and guidance rules apply in the system, and whether policy decisions need to be made to amend the dataset and rules to reflect changing performance or volumes within CWT.

The overall aim of this type of additional analysis would be to support improvements to cancer patients survival and experience. The NHS Long Term Plan set out a number of ambitions to be met by 2028 including increasing the proportions of patients staged 1 or 2 from around half now to three-quarters. Achieving this means that from 2028, 55,000 more people each year will survive their cancer for at least five year after diagnosis. For these, improvements to ensure optimal diagnostic and treatment pathways and nationally agreed processes are key, and require NHS England policy teams to be able to analyse the Cancer Waiting Times dataset to identify improvements.

The CWT historical data will required to provide baselines of previous cancer waiting times going back at least 6 years. This will allow retrospective analyses to confirm that interventions put in place to reduce the cancer waiting times, have brought the length of time patients have to wait for a confirmed diagnosis down. Access to data will also identify the quality of the data provided and where focus can be prioritised to support the local healthcare systems.

The NHS England requirement for the CWT data will also need to be used with other datasets included in this Data Sharing Agreement such as SUS, Civil Registration of Deaths and Diagnostic Imaging data. This will be used to understand how local systems are working effectively, such that cancer is diagnosed and treated quicker and cancer survival rates are increasing at a National, Regional and sub-regional level.


Civil Registration of Deaths (CR Deaths):
Mortality is one of the measures of patient outcomes, particularly when that death is at a young age or from a cause that may have been prevented by a healthcare intervention.
There is a Secretary of State ambition to reduce the rate of stillbirths and neonatal deaths by 50% by 2025, for which the maternity transformation programme has been set up to achieve this ambition. To support this ambition there is a requirement to understand the factors that contribute to still births and neonatal deaths.

By having access to the Civil Registration of Deaths data, NHS England will be able to understand the drivers and patterns of mortality as well as premature mortality. This would help inform of the NHS treatments that those patients have received.

As part of the Long Term Plan, access to this data would also permit analyses that would not be possible from the ONS publications, for example to identify the still birth rate for women from a BAME background who live in the most deprived areas. This would highlight where service provision is not adequate and allow focus and interventions to be put in place with a view to reduce the levels of still births.

From access to this data NHS England, would be able to understand reasons why patients are dying at a National, Regional and sub-regional level and identify what additional support services could be put in place to prevent many of these deaths. Part of the analyses would also show where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
NHS England requires the data to feed into the Clinical Pathway dashboard which contain measures:
• Mortality rate from serious emergency conditions (7 days)
• Mortality rate from serious emergency conditions (30 days)
• Case fatality rate from serious emergency conditions

These measures help validate programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working, or did the patient die.

The dashboard provides guidance to make Urgent Emergency Care (UEC) systems aware of issues relating to patient outcomes and clinical effectiveness. This will inform long term strategic planning and monitor change to improve the quality of UEC.

The NHS England requirement for the CR Deaths data will also need to be used with other datasets included in this Data Sharing Agreement such as SUS, Maternity. This will be used to understand how local systems are working effectively, such that Services and interventions put in place to prevent people from dying early are effective and living longer at a National, Regional and sub-regional level.


Patient Reported Outcome Measures (PROMs)
NHS England requires access to Patient Reported Outcome Measures data to enable the comparison of outcomes from healthcare services. This data assesses the quality of care delivered to NHS patients from the patient perspective.

The data will be used to understand variation and drivers in outcomes as reported by patients, and to explore how they differ in relation to patients undergoing the same set of procedures (hip replacements, knee replacements, groin hernia, varicose veins) within NHS providers. The data will also permit viewing patient outcomes at a National, Regional and sub-regional levels. It will provide NHS England details of the quality of care provided country wide, and focus on where progress can be made to ensure that these services are commissioned in a way that improves the health of the population and reduces inequalities.

NHS England will require at least the last 6 years of data to start building the retrospective views of the data, and baseline how patients outcomes have changed historically.

PROMs data will also be used alongside a number of fields from the National SUS data in order to develop a dataset that will be used to generate a further analyses and insight that ensures NHS England can satisfy its statutory duties part of which includes a responsibility to consider the economic, social and environmental benefits to be achieved through commissioning.


National Diabetes Audit data (NDA):
NHS England requires access to the National Diabetes Audit data to;
• assess local practice against National Institute for Health and Care Excellence (NICE guidelines
• compare care and care outcomes with similar services and organisations
• identify gaps or shortfalls that are priorities for improvement
• identify and share best practice
• provide comprehensive national pictures of diabetes care and outcomes in England

NHS England has a statutory duty (under the Health and Social Care Act (2012)) to conduct an annual assessment of every CCG in England. The NDA data will be used to produce the Clinical Commissioning Group Improvement and Assessment Framework (CCGIAF) ratings for indicator 103b. Indicator 103b evaluates newly diagnosed people with diabetes (diagnosed less than a year) attend a structured education course. NHS England monitors the Clinical Commissioning Groups to ensure that the number of diabetes patients attending structured education are increasing.

Poor management can be associated with higher risk of the microvascular complications of diabetes (eye disease and blindness; kidney disease and kidney failure; foot disease, foot ulceration and amputation) and higher risk of cardiovascular disease (heart attack, angina, heart failure, stroke, and amputation). As such, NICE recommends that newly diagnosed diabetes patients are attend a structured education course within 12-months of diagnosis in order to improve understanding, empowerment and self-management of diabetes.

Whilst diabetes care process delivery and treatment target achievement are recommended in order to both monitor for the onset of diabetes complications and to minimise the risk of onset of diabetes complications, structured education is recommended to support self-management in order to achieve the same goals, as well as to achieve better understanding of the disease and better quality of life with diabetes.

The National Diabetes Audit data will also be required to monitor progress on the Transformation Funding provided to the Diabetes programme.
The Diabetes Transformation Funding was allocated to CCGs who had successfully bid for funding during 2017/18 to fund four separate workstreams for an initial two-year period as follows:
• Increase the treatment target attainment among CCGs and reduce the variation between CCGs to improve outcomes for patients with diabetes and reduce complications
• Increase attendance at structured education and thus improve self-management and treatment target attainment
• Establish or expand Multi-disciplinary footcare teams to provide a dedicated service improving outcomes, reduce the length of stay and the number of amputations
• Implement or increase the Diabetes inpatient specialist nurse provision to provide support and education to inpatients with diabetes to reduce the complications and provide training

NHS England will require this data to be fed into a reporting dashboard for the Diabetes Transformation Programme Board, that is to be updated on a regular basis with data from NDA, National SUS, National Diabetes Inpatient Audit data (NaDIA).

NHS England will require at least the last 10 years of data to start building the retrospective views of the data, and baseline how delivery of diabetes care has changed historically.


Clinical Registry Data:
NHS England requires access to data collected within Clinical Registries, Databases and Audits. Part of NHS England’s responsibility oversees the budget, planning, delivery and day-to-day operation of the commissioning side of the NHS in England as set out in the Health and Social Care Act 2012.

Every year NHS England recommissions, commissions or procures health services from health service providers. It is a complex process, involving the assessment and understanding of a population’s health needs, the planning of services to meet those needs and securing services on a limited budget, then monitoring the services procured. When a service is procured, this is done through a contract. The contract – is referring t

Yielded Benefits:

NHS England would not have been able to meet some of its statutory duties (as per NHS Act 2006 and the Health and Social Care Act 2012 s13N, s23) and to meet the requirements of the Five Year Forward View, without access to SUS data. Yielded benefits have been partially met with the SUS data. Access has enabled NHS England to check the quality and efficiency of the health services that are commissioned and to plan for the future needs of patients. Reports and dashboards have been created to demonstrate management of commissioned services, including contract management, performance management, inequalities analysis, benchmarking, service review and development, planning, budgets and allocations and general commissioning assurance activities. Access to Mental health and IAPT data has allowed NHS England to better monitor (for example by looking at local variation or the links with physical health) progress against some of the priority actions identified in the Mental Health Five Year Forward View, such as waiting time standards for early intervention in psychosis. NHS England through accessing the data provided, have been able to develop insight and understanding of the services commissioned and ultimately view how this organisation can better support and improve the care and quality patients receive, as well as the ambition set out to help people live longer. There is a continuing requirement for NHS England to have access the data so that all objectives, purposes, outputs and benefits can continue to be realised. For data received only very recently from NHS Digital, including; • Assuring Transformation • Community Services Data Set • Childrens’ and Young Peoples’ Health Services • Maternity Services Data Set – including currency data • Diagnostic Imaging Data set • Improved Access to Psychological Therapy (IAPT) Pilot data The yielded benefits for these data sets cannot to be demonstrated yet, as there has not been enough time to develop understanding of these data sets.

Expected Benefits:

1. Analysis and reporting will help NHS England to commission effective and efficient services in line with NHS England’s Five Year Forward View.
2. NCDR to act as a proving ground for the Commissioner Assignment Methodology (CAM) and to convert the CAM methodology to a system algorithm. Benefits expected from commencement of provider implementation of the CAM include:
a. Equitable distribution of resources
b. More accurate identification of commissioners
c. Improved performance data from providers for monitoring contract performance
d. Consistency of approach makes national analyses easier and more accurate
e. Efficient local processes for providers
3. Support analysis of development and monitoring outcomes for new models of care.
4. Developing improved methodology for calculation of commissioner budget allocations.
5. Provides robust findings on which complex changes to care are most effective, enabling large transformation programmes to improve the effectiveness of their interventions. For example, SUS data has been used extensively (monitoring trends in acuity of cases, investigating the characteristics of attenders, understanding the relationship between attendances and admissions, etc.) in the development of the recent A&E Plan.
6. Reduced resources whilst delivering robust assessment of national programmes.
7. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
8. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
9. Enables monitoring of:
a. Outcome indicators.
b. Non-financial validation of activity.
c. Successful delivery of integrated care within the NHS.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. Understanding the care of patients in nursing homes.
10. There have already been significant benefits realised from the use of activity data derived from SUS. NHS England now share a common understanding of activity levels across the system, which has enabled better local and regional performance management, as well as the development of national policies e.g. new demand and capacity plans for elective care. Better activity data has also enabled a more robust national planning process, and so improved the allocation of funds across the system.


Clinical Registry Data:
1. Review the data quality and coverage of the hospitals providing data and provide feedback to improving the collections both in quality and ensuring all provider who should be supplying data are doing so. This will ensure that the care for patients is recorded accurately, which will also have a positive impact on understanding the patients’ care pathway whilst observing potential gaps in care and what interventions can be put in place to further support patient outcomes. Once interventions have been put in place NHS England will be able to monitor the impacts and ensure that the improvements to care and outcomes are being delivered.
2. Clinical Registry data is also required to underpin the strategic planning, purchasing, future models and the evaluation of specialised services for which NHS England also has a national responsibility. The budget for Specialised Commissioning alone is estimated to be £16 Billion (in 2018/2019). From access to the Clinical Registry data NHS England can ensure that payments made to providers are accurate against agreed contract values, avoiding potential overpayments.
3. To support and encourage good standards of quality care, the Clinical Registry data will be used to develop additional policy, guidance and Best Practice Tariffs as top-up payments for Trusts, encouraging better delivery of care. This can be measured by reviewing the number of providers that have met the qualifying criteria, over time.

Outputs:

Any outputs to 3rd parties not included as Data Controller/Processor in this application/agreement must be aggregated (with small number suppression applied in line with NHS Digital requirements).

All datasets will be used to:
1. Allow NHS England to meet its ongoing statutory duties under the NHS Act 2006 and the Health and Social Care Act 2012 s13N, s23. Specifically – ‘to exercise its functions ensuring that health services are provided in an integrated way where this would improve quality and outcome of services and reduce inequalities’.
2. Realise data quality improvements initiatives including reports to ensure that NHS England data processing has been carried out correctly (e.g. expected volume of specialised activity service line codes derived).
3. Provide an aggregate activity and finance report which will be used to populate an NHS England integrated activity and finance report for the monthly NHS England Executive Group Meeting. This has now been introduced (the benefits from this, and related SUS analyses included in the following section).
4. Analyse the impact of changes to NHS commissioning business rules (e.g. tariff changes, commissioner assignment, specialised services identification rules, HRG grouping).
5. Facilitate proactive management of NHS England directly commissioned services using pseudonymised or aggregate data (with small number suppression) only. (This is dependent on the analysis requirement as to whether the output used is pseudonymised or aggregate data.)
6. Enhance statistical analysis to facilitate proactive management of transformation programmes by local health systems on behalf of NHS England.
7. Monitor and analyse outpatient and community services; alternatives to inpatient care.
8. Monitor and analyse of new patient care pathways introduced to support the transformation of services for people with learning disability and/or autism. Access to data will specifically allow:
- Analysis of inpatient services and activity for people with learning disability and/or autism
- Analysis of outpatient and community services and activity for people with learning disability and/or autism
- Analysis of patient pathways as patients move between services
9. Analyse factors that result in high service usage.
10. Analyse the usefulness of diagnosis coding. Analysis will firstly focus on an understanding of the completeness and quality of coding in the dataset to provide a basis for any further analysis. NHS England would like to understand the completeness and validity of this data item, as well as identifying any geographical trends or particular providers which show problems with coding completeness. Access to the data would enable further discussion of coding practices in providers for casemix complexity. The intelligence can be shared through commissioning routes to help drive up coding completeness and accuracy to make any subsequent analysis more meaningful.
11. Analyse the spread of diagnoses geographically and demographically, to identify any trends as well as diagnoses recorded over time (given a robust starting point for coding accuracy and completeness). Admissions and readmissions and activity could also be analysed by diagnosis to better understand these trends and potential differences in provider models to inform commissioning decisions and service improvement.
12. Provide intelligence to commissioners to support the reduction of unnecessary restraint and potentially abusive restraint. An analysis of restraint to identify any trends or outliers across providers, CCGs and sub-regions. The analysis will also include the frequency of restraint per patient and by ward type. This will highlight any areas for concern in the use of restraint to inform further discussions with commissioners. As the restraint type is added to the MHSDS in v2.0 this will provide further insight and areas for focus in discussions with commissioners. The aim of this is to provide intelligence to commissioners to support the reduction of unnecessary restraint and potentially abusive restraint.
13. Achieve the service improvements required, in association with the findings from the report “The commissioning of specialised services in the NHS” by the National Audit Office (NAO), whereby the findings suggested that NHS England does not have sufficient information to drive service improvement in specialised commissioning.
14. Undertake health economic modelling using:
a. Analysis on provider performance against targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
15. Provide commissioning cycle support for grouping and re-costing previous activity.
16. Undertake commissioner reporting, including:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
17. Produce aggregate reports for CCG Business Intelligence.
18. Produce project / programme level dashboards.
19. Monitor acute / community / mental health quality matrix.
20. Facilitate clinical coding reviews / audits.
21. Undertake budget reporting with drill down capability to various levels.
22. Dashboards that are produced can cover all levels of the NHS – National, Regional and Sub-regional. The aim is to highlight trends of areas where in some cases NHSE are able to the levels of frequency of attendees accessing services.
23. NHS England is creating a population health management dashboard which will give each combined local health economy an aggregated (with small numbers suppressed) view of national data, facilitating benchmarking. This will inform NHS England about the relative performance of these emerging combined health and social care resources, facilitating information exchange and assurance that the new model of operation is being effective and meeting its objectives.
24. Any outputs produced from processing IAPT data must comply with the IAPT Disclosure Controls i.e.: o In order to prevent suppressed numbers from being calculated through differencing other published numbers from totals, all sub-national counts have been rounded to the nearest 5. o Sub-national rates (percentages) are rounded to the nearest whole percent to prevent disclosure. National rates are rounded to one decimal place.


Clinical Registry Data:
1. Routine reports and dashboards (where small numbers appear, these will be suppressed in line with NHS Digital guidance) so that all levels of NHS England (national, regional and sub regional) can access the views, analyses and insight. The intelligence gathered will be made available to drive improvement, efficiency as well as recognising ‘model hospital behaviours’ in specialist fields.
2. Produce analysis of variation and trends at National, Regional and Sub regional levels, not just from a provider view, but from a commissioning prospective as well.
3. Produce analysis of variation and drivers in outcomes as reported by each disease specific Registry, and to explore how they differ in relation to patients undergoing the same set of procedures and treatments in NHS providers.
4. Inform decisions of what can be done to reduce the variation and improve the care given to patients.

The specific Clinical Registry datasets included in this Data Sharing Agreement at the time of approval are:
- TARN, Trauma Audit and Research Network
- UK Renal Registry
- UK ROC, UK Rehabilitation Outcomes Collaborative
- NHFD, National Hip Fracture Database
- PICANet, Paediatric Intensive Care Audit Network
- BSR, British Spine Registry
Other clinical registry datasets may be added to this list, subject to approval from NHS Digital, including review and recommendation by the IGARD (independent expert group advising NHS Digital on the release of data).

Processing:

Data must only be used as stipulated within this Data Sharing Agreement.

Data Processors must only act upon specific instructions from the Data Controller.

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

No record level data will be linked other than as detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement.

All access to data (by data controllers and data processors) is managed under Role and task-Based Access Controls. Users can only access data authorised by their role, for a task they are undertaking.

Generic processing activities applied to multiple requested data sets
Data will only be shared with or processed by the parties listed in this application and will only be used for the purposes stipulated. Any further reports sent beyond the data controller and processors as stipulated in this agreement will contain aggregate data only with small number suppression, and will be subject to the disclosure controls of the relevant datasets. As part of the monitoring and evaluating of the transformation programmes, it will be necessary for the processed data to be enhanced by linking in publicly available contextual information on aggregate level (with small number suppression). Examples of publicly available data include GP patient survey result aggregated to GP practice level (source: https://gp-patient.co.uk/surveys-and-reports), measures of deprivation aggregated at Lower Super Output Area (LSOA) level (a small geographical area typically covering about 1500 people).
- source: https://data.gov.uk/dataset/english-indices-of-deprivation-2015-lsoa-level) and disease prevalence, again geographically aggregated (source: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases).


The following pseudonymised datasets are provided by NHS Digital to NHS England:
- SUS (including ECDS)
- Local Provider Flows (including 111 data)
- Mental Health Services Data Set (MHSDS) (including pre-publication data)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Minimum Data Set (MHMDS)
- Assuring Transformation (AT)
- Improving Access to Psychological Therapies (IAPT) (including additional payment data and pre-publication data)
- Improving Access to Psychological Therapies (IAPT) (including Long term conditions wave 1 and 2 - 22 and 61 providers respectively supplying pilot data)
- Children and Young Peoples Health Services (CYPHS)
- Community Services Data Set (CSDS)
- Maternity Services Data Set (MSDS) (including currency extract)
- Diagnostic Imaging Data Set (DID)
- Cancer Waiting Times (CWT)
- Civil Registration Deaths
- Patient Reported Outcome Measures (PROMS)
- National Diabetes Audit (NDA)
- Clinical Registries for commissioning

There are 3 key activities which are undertaken with this data:
1. Data Management (Data Quality, Data Linkage, and creation of data subsets)
2. Analysis within NHS England
3. Analysis outside NHS England

Pre-publication data:
• Where unpublished management information/ data have been supplied, the following additional ‘conditions of use’ are applicable to reduce the risk of a breach of the Code of Practice for Statistics which may damage the public trust in Official Statistics. Unpublished management information includes data which has been supplied in advance of release of the data as an Official Statistic.
o Access to unpublished management information will be kept to a minimum. A record of which groups of people have access to this data should be maintained by the IAO of the NCDR. Unpublished management information will be under separate access to ensure that only those who can access the data prior to publication can do so and that purposes linked to access to the data are recorded. It is expected that access will only be for staff in NHS England Teams and Direct Commissioning (Arden and Greater East Midlands Commissioning Support Unit).
o There cannot be any public use of unpublished management information which could undermine the official statistics and thus breach the Code of Practice for Statistics. This includes any public statement that prejudges or pre-empts the contents of any subsequent statistical release, or any ad hoc or selective comments on, or reporting of, unpublished data.
o Access to unpublished management information has been granted for managerial, operational, commissioning or other appropriate decision-making purposes. You must not share or discuss the data, or any results or documents based on it, with anyone else or use it for any other purpose.
o Unpublished management information may be discussed between other people who have access to the information and with the relevant NHS Digital production team
o Any results or documents produced should show that the data are pre-publication restricted.
o All users of unpublished management information must abide by these ‘conditions of use’.
o Any accidental or wrongful release of the data must be reported immediately to NHS Digital. Wrongful release includes indications of content, including descriptions such as “favourable” or “unfavourable”. If in doubt you should consult the NHS Digital production team in the first instance who can advise.
o Any breach in these ‘conditions of use’ may result in removal of access to unpublished management information.


1) Data Management (Data Quality, Data Linkage, and creation of data subsets):
This activity is carried out solely by Arden and Greater East Midlands Commissioning Support Unit.
The datasets within the NCDR undergo processing to ensure data quality, to meet the reporting requirements, and to add value to the data (e.g. adding a tariff and grouper) to support integrated patient care analysis.

In order to be able to link the various datasets, a “Master Patient Index” (MPI) is used. This MPI contains only pseudonymised data, and is created by NHS Digital outside of this agreement (under a Data Processing Agreement) using identifiable data from the NHAIS (GP registration) system. The MPI data can be used to link the pseudonymised datasets, as the same pseudonymisation key is used for the production of all the datasets and the MPI. The MPI also contains demographic data to enhance the analysis, by facilitating segmentation of the population (e.g. by segmenting postcodes and neighbourhoods into 6 Categories, 18 Groups and 62 types).

Linkage is only permitted between the datasets listed above.

Due to the inherent risks of access to large amounts of data, the MPI is available only to a very small number of people (less than 10). When any MPI data is to be shared outside this small group, the data undergoes a second encryption process using a purpose-specific pseudonym in order to minimise the risk of re-identification. Each request for linkage must be considered by the NCDR Change Advisory Board and authorised by the NCDR IAO before any data is made available to NHS England analysts.
Where data is needed for analysis, a purpose-specific data mart (a minimised dataset) is created and is made available only to those analysts demonstrating legitimate purposes and (subject to their use being documented and audited).

Risk of re-identification
A Privacy Impact Assessment has been undertaken within NHS England in reference to the MPI and risk is within acceptable tolerance levels.
Further mitigations have been developed to address increased risk or re-identification through linkage and are being rolled out. These include the assignment of a unique pseudonym for each purpose and a more rigid application of data minimisation.



2) Analysis within NHS England:
NHS England may at any time require any of its Commissioning Support Units (CSUs) to undertake activities on its behalf for a specific project(s) under a Service Level Agreement. All NHS CSUs are therefore listed below as data processors:
• Arden and Greater East Midlands Commissioning Support Unit (AGEM CSU)
• NHS North of England Commissioning Support Unit (NECS)
• NHS North & East London Commissioning Support Unit (NEL CSU)
• NHS South, Central & West Commissioning Support Unit (SCW CSU)
• Midlands and Lancashire Commissioning Support Unit
The CSUs undertaking analysis are prohibited from sharing anything other than anonymous data with any 3rd parties. In this instance, “anonymous data” means data that is aggregated (with small numbers suppressed in line with NHS Digital requirements).
Processing activities would only take place on pseudonymised patient-level data and would include:
• Data quality checks
• Data validation
• Generation of ad-hoc analysis and reports to support specific projects
A lead CSU will be nominated for each project.
This approach ensures that NHS England can flexibly meet demand across the NHS system.

3) Analysis outside NHS England:
External organisations sometimes provide assistance to NHS England. Each external organisation is included here explicitly, and their data processing is limited to the purpose specified. Any additional organisations or purposes are prohibited.


The Health Foundation - The Improvement Analytics Programme
The Health Foundation has partnered with NHS England to deliver the Improvement Analytics Unit (IAU), which exists to support all NHS England’s major transformation programmes. The IAU will utilise data to help build a body of knowledge about which interventions and major new initiatives in the English NHS are successfully improving patient care and share that learning more widely. The unit supports delivery of NHS England’s commitment in the Five Year Forward View to evaluating the impact of major national programmes (such as the new care models). The IAU will expand NHS operational research and statistical methods to promote more rigorous ways of answering high impact questions in health services redesign.

The Health Foundation will undertake analysis on de-identified patient level data only, which will be provided via NHS England’s contracted data processor for the NCDR.

Specifically, it will provide the NHS with the capability of rapidly testing interventions in health and social care system, so that changes can be implemented to the system as rapidly as possible to improve patient care.

More widely, the programme supports the development of strong and effective local health systems with the capacity and capability to meet the needs of local communities and to respond to emerging priorities for the NHS.

The services agreed with NHS England and The Health Foundation covers in the main, evaluation of the major programmes as set out in the 5 year Forward view and will use a range of approaches to establishing counterfactuals, including through constructing matched controls. This will require development of an Improvement Analytics Unit which provides access to patient level data, and incorporates sophisticated statistical and analytical approaches to the evaluation. The Improvement Analytics Unit is an NHS England initiative which will be run jointly with The Health Foundation during phase 1. An objective of the programme is knowledge transfer of complex statistical techniques from THF to NHS England and their use on the NHS England SAS service.

The processing being undertaken will support NHS England to meet its statutory functions outlined in the Health and Social Care Act 2012 covering in the main, direct commissioning and as part of their assurance role (to ensure commissioning is equitable).

The Health Foundation (THF) will only be provided with access to or given extracts of the specific commissioning data they require in order to undertake their activities set out within the SLA or data processing agreement.
The datasets required for this work are:
- SUS (including ECDS)
- Mental Health (MHMDS, MHLDDS, and MHSDS)
- IAPT
- Community (CYPHS, CSDS)
- Maternity
Processing activities would only take place on patient-level data where it has been pseudonymised and would include:
• Data quality checks
• Data validation
• Generation of ad-hoc analysis and reports to support specific projects


Imperial College London – Integrated IAPT Early Implementers
Imperial College will only be provided with extracts of the specific commissioning data they require in order to undertake their activities set out within the Data Processing Agreement,
The datasets required for this work are:
- SUS (including ECDS)
- IAPT
- IAPT Pilot

Imperial College London will use the data to analyse the performance of Integrated IAPT in terms of healthcare utilisation - including recovery, access, demographics, waiting times, as well as patient experience.

Data analysis would only take place on pseudonymised patient-level data and would include analysis of IAPT (incl. pilot data) and SUS data and the production of three reports (interim, draft, and final).

Data processing activities will include general data quality checks and validation of the pilot data. Imperial will then produce a treated on the treated (TT) analysis - comparing those who were treated in an Integrated IAPT service to those who are as similar as possible but were not treated, looking to find a counterfactual for each treated person, which can reasonably proxy their outcomes had they been treated in terms of secondary health care utilisation.
This analysis relies on matched IAPT data with SUS inpatients, outpatients and accident and emergency data. To find a suitable control group for those treated within Integrated IAPT services Imperial will use a matching algorithm with machine learning, which will include a number of SUS variables relating to the individuals visit to hospital (procedure details, diagnosis details etc.) in the matching process, along with their key demographics (age, gender, characteristics of their area of residence including socio-economic status etc.).

The second stage of the analysis then relies on standard regression analysis. Having data for 3 years prior to the intervention will ensure there are large enough samples to find appropriate controls for matching with those who have been treated in an Integrated IAPT service. This will allow us to test whether the treated and control sites are statistically similar, in that they show common trends in outcomes before the intervention. It is standard to look at this over a number of years: 3 years is generally the minimum that would be required.


In terms of data flowing to both The Health Foundation and Imperial College London, the process is as follows;

Data sets approved by NHS Digital are made available through Arden and Greater East Midlands DSCRO. The DSCRO accesses clear patient level data and makes any identifiable data items within non- identifiable. This is done by either removing data items that are not permitted to be seen (e.g. Names, addresses etc), or in the case of patient identifiers, these are pseudonymised in line with NHS Digital guidance.

Once the data is pseudonymised, the DSCRO then flows the datasets to NCDR, which is hosted by Arden and Greater East Midlands Commissioning Support Unit (AGEM CSU). At this point NHS England analytical staff are able to access the pseudonymised data within the NCDR, for which they have permission to do so.

AGEM CSU (NHS England’s contracted data processor for the NCDR) are able to flow the specified requested data to named organisations (The Health Foundation and Imperial College London) using Secure Electronic File Transfer (SEFT) accounts.

This transfer mechanism ensures that data can only be accessed by named individuals (within The Health Foundation or Imperial College London), securely and is also password protected, to enhance security.


Clinical Registry Data:
There are different sources of the data, dependent on where the clinical registry data is held. The majority of the sources of Clinical Registry data are held within an NHS environment, but not all, for example; UK ROC which is hosted by Kings College London, or TARN data (Trauma Audit Research Network) which is controlled by the University of Manchester.

Clinical Registry data is submitted to and collected by NHS Digital under the Data Services for Commissioners Directions 2015. The Directions are published by NHS England in exercise of its powers under Section 254(1) of the Health and Social Care Act 2012 to direct NHS Digital to establish information systems.

The rationale for the Directions is to establish Data Services for Commissioners (DSfC): a service to cleanse, link, and
de-identify commissioning data, as appropriate; and disseminate the resultant data and reports to commissioners
who require them to perform their functions, having current contracts with respective providers, or legitimate
interest the data.

The NHS England Directions for DSfC provides the legal basis for flow of personal confidential data into NHS Digital.
Prior to dissemination to NHS England, all Patient Confidential Data is pseudonymised by NHS Digital (via DSCRO) and the data will flow to NHS England via Arden and Greater East Midlands Commissioning Support Unit who host the NHSE National Commissioning Data Repository (NCDR), in line with the agreed DSfC Anonymisation Specification.

Once the data is made available, Data Management (including Data Quality, Data Linkage, and creation of data subsets), is carried out solely by NHS England teams which may include an NHS England Commissioning Support Unit. The Clinical Registry datasets within the NCDR undergo processing to ensure data quality, to meet the reporting requirements, and to add value to the data (e.g. adding a tariff and grouper) to support integrated patient care analysis.

Processing activities only take place on pseudonymised patient-level data and include:
- Data quality checks
- Data validation
- Generation of ad-hoc analysis and reports to support specific projects

The NHS England NCDR has strict access controls in place and therefore access to the Clinical Registry data held on NHS England’s NCDR is restricted, to ensure that when Clinical Registry data is required, clear justification is provided. All requests are logged and auditable. All users to the NCDR go through an access control process (previously shared with NHS Digital) and purpose specific data sets are created when analysis needs to be undertaken on data held within the NCDR.

As previously mentioned, Clinical Registry data will (in some cases not all) also be linked and used alongside a number of fields from other Nationally collected datasets (named above, e.g. SUS), in order to develop subsets that will be project specific and used to generate a further analyses, insight and questions about the health of the population, in terms of why is there variations in the provision of care and what interventions can be developed to improve the inequalities identified. There will be also a need for cross referencing records to ensure that payment is not duplicated, activity is costed appropriately and invoiced correctly by responsible organisations.

National Cancer Waiting Times Monitoring Data Set (NCWTMDS) with derivation of deprivation age and gender — DARS-NIC-266008-T3S9D

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

Purposes: No (Agency/Public Body)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-03-01 — 2020-02-29 2019.03 — 2019.03.

Access method: One-Off

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

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

Objectives:

The National Cancer Waiting Times Monitoring DataSet (NCWTMDS) is a national, patient level data collection by NHS Digital, under a Direction from NHS England (NHSE). The data are used for monitoring times taken to diagnose and treat patients with cancer and ensure these are in line with the expectations and rights of patients in the NHS Constitution.
As a patient moves through the stages of their treatment pathway, data on referrals, treatments and diagnosis are derived from care records locally.

The NCWTMDS provides the data used to publish the official cancer 62 day treatment target which is one of the key national statistics used to monitor the performance of the NHS. After collection, the cancer waiting times data can also be queried by NHS organisations, cancer networks and the Department of Health to provide reports and feedback on the progress towards meeting these targets.

The NHS Long term plan states:
"For all major conditions, the quality of care and the outcomes for patients are now measurably better than a decade ago. Childbirth is the safest it has ever been, cancer survival is at an all-time high, deaths from cardiovascular disease have halved since 1990, and male suicide is at a 31-year low. But there is good evidence to suggest that over the next decade the NHS should be doing even better. Partly that’s because there’s currently too much variation in service quality between clinical teams and between different parts of the country. Partly we’ll need to improve by tackling previously unmet need – for example in young people’s mental health services. And partly we’ll be able to do better because the worldwide frontier of medical possibility will continue to advance."

NHS England require additional information to understand variation in cancer standard achievement and ultimately cancer outcomes.

In addition to the access granted under DARS-NIC-192305-X3T0Y-v3.2 NHS England requires access NCWTMDS for the following purpose(s):
1. The Operations and Information directorate require NCWTMDS linked to deprivation data to allow understanding of associations between deprivation and cancer waiting times
2. The Operations and Information directorate require NCWTMDS linked to age and gender to understand whether standardising for these factors influences overall outcome achievement.

The data cannot be used for any other purpose than that stated above. The data will not be shared with any third party. Data will only ever be used for purposes relating to healthcare or the promotion of health in line with the requirements of the Health and Social Care Act 2012 as amended by the Care Act 2014. Any record level data extracted from the system will not be processed outside of the analytics team, with only aggregate data to be shared with other NHS England teams.

Expected Benefits:

This additional analysis will allow NHS England to better understand the impact of deprivation on access and effectiveness of cancer pathways and to assess the value of routinely adding additional derivations to the NCWTMDS. The additional requested data attributes LSOA and IMD_Rank will be used to understand how deprived an area of residence is, and the additional fields Gender and Age will test the impact of standardisation i.e. to test if degree of inequality varies by age and gender.

Enabling analysis of the Cancer Waiting Times data on a system wide basis will provide insight to focus service improvements on most effective areas to improve performance. In particular you would expect that access to the data be essential to delivery of the Cancer Waiting Times 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
• 28 day referral to diagnosis - TBC

Outputs:

NHS England will use this data for the specific purpose of understanding whether there is an association between deprivation, age and gender and cancer waiting times. This is a one-off piece of analysis for internal purposes and will be used to understand the value of further work in this area. Additional work and any routine derivation of deprivation, age and gender will need subsequent amendments or new data sharing agreements to be put in place.

All outputs will contain only data that is compliant with the relevant disclosure control rules including suppression and rounding.

Processing:

Data will only be accessed by individuals within NHS England who have authorisation from the SIRO or IAO to access the data for the purposes described, all of whom are personnel working under appropriate supervision on behalf of NHS England. Following completion of the analysis any record level data will be securely destroyed. The data will not be used for commercial use. The data will not be linked with any record level data and there will be no requirement nor attempt to re-identify individuals from the data.

The raw data will not be made available to any third parties except in the form of aggregated outputs with small numbers suppressed in line with appropriate disclosure controls, such as Official Statistics.

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).

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

Type of data: Identifiable

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

Legal basis: Health and Social Care Act 2012, Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012), , Other-Health and Social Care Act 2012 - s261(2)(b)(ii), Health and Social Care Act 2012 - s261(5)(d)

Purposes: No, The National Institute for Cardiovascular Outcomes Research (NICOR) now hosted at NHS Arden and Greater East Midlands CSU (Arden and GEM) has received Hospital Episode Statistics (HES) Admitted Patient Care (APC) and Civil Registration mortality (ONS) data for use in an audit of patients who have undergone one of three procedures: - Percutaneous mitral valve leaflet repair (a type of cardiac surgery) for mitral regurgitation (heart valve leakage) using MitraClip; - Left Atrial Appendage Occlusion (LAAO)(a heart treatment strategy to reduce the risk of blood clots); and - Patent Foramen Ovale Closure (PFOC)(‘hole in the heart’) procedures. This data needs to be retained for archiving purposes. No further processing of the data will occur under this version of the agreement. This data must be retained for a minimum of six years, as determined by the NHS England Record Management Team based on their statutory requirements. This Agreement permits processing of the data for the purpose of secure storage and back up. This Agreement permits the necessary processing of the data for the purposes of permanently destroying, deleting or erasing the data once it is no longer required for the purpose for which it was collected. Once destroyed/deleted or erased, NICOR must confirm destruction to NHS Digital. If any further data processing is required in addition to the above purposes or if the data needs to be moved to a different organisation, a further amendment request must be submitted to NHS Digital before data is accessed. The data was originally disseminated for the purpose of a key deliverable to provide Newcastle Upon Tyne Hospitals NHS Foundation Trust (NUTH) with a pseudonymised linked clinical PFOC, MitraClip and LAAO raw data with ONS and HES data extract. ONS and HES linked data are required from NHS Digital to allow analysis of future clinical events rates after the initial treatment (principally rates of strokes/cerebrovascular events and death). Pseudonymised HES APC and ONS data were provided against the cohort of approximately 1965 patients who have received either of the procedures Mitraclip, LAAO and PFOC. This cohort of patients represents all patients treated with these procedures in the NHS nationally. NICOR are required by NHS England to retain this linked ONS and HES data for each registry for a period of six years. In April 2013, NHS England became responsible for directly commissioning specialised services and published a clinical commissioning policy statement which stated that percutaneous mitral valve leaflet repair for mitral regurgitation using MitraClip, LAAO and PFOC procedures would not be routinely funded as the current evidence base had been of insufficient quality. NHS England developed ‘Commissioning through Evaluation’ (CtE) to support the commissioning of clinical activity around an evaluation programme to add to the current evidence base for designated technologies. The overall aim was to provide a clinical and economic evaluation of the MitraClip and the other two procedures. Funding was provided for a limited number of high-risk patients as determined by an appropriately constituted Multi-disciplinary Team (MDT) process. Prior to 2013 service provision was unstructured and delivered by providers who attempted to establish services through negotiation with local specialised commissioners. The majority of procedures were commissioned through individual funding requests or by individual Trusts funding treatments by other means. In April 2013 NHS England became responsible for commissioning specialised services. Howeve