NHS Digital Data Release Register - reformatted

NHS England (quarry House) projects

952 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.

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

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

Legal basis: Health and Social Care Act 2012 - s261(5)(d)

Purposes: No (Agency/Public Body)

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

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

Opt outs honoured: Anonymised - ICO Code Compliant (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(5)(d)

Purposes: Yes (Agency/Public Body)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-11-17 — 2022-11-16

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)

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.

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

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

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

Purposes: No (Agency/Public Body)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-05-07 — 2023-05-06 2021.06 — 2022.12.

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.

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

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 (Agency/Public Body)

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.

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

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)

Purposes: No (Agency/Public Body)

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

When:DSA runs 2021-05-07 — 2023-05-06 2018.06 — 2022.07.

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)

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.



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

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)

Purposes: No (Agency/Public Body)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-05-07 — 2023-05-06 2021.06 — 2022.06.

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)

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.

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

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 - 'Other dissemination of information'

Purposes: No (Agency/Public Body)

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

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

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.

SMI Comprehensive Physical Health Checks (PHSMI) GPES Extract — DARS-NIC-433629-H3M0G

Opt outs honoured: No - Statutory exemption to flow confidential data without consent, Anonymised - ICO Code Compliant (Statutory exemption to flow confidential data without consent)

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)

Purposes: No (Agency/Public Body)

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

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)

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)

Purposes: No (Agency/Public Body)

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)

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

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

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(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)

Purposes: No (Agency/Public Body)

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)

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) — DARS-NIC-192305-X3T0Y

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

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

Purposes: No (Agency/Public Body)

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

When:DSA runs 2020-06-01 — 2020-08-31 2019.10 — 2021.05.

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

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: Yes

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

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 2018-12-03 — 2021-12-02 2019.09 — 2021.05.

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

Data-controller type: 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-204559-J4H7T

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 — 2021.05.

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

Data-controller type: 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

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 Non-Sensitive

When:DSA runs 2019-01-02 — 2020-01-01 2019.09 — 2021.05.

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

Data-controller type: 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

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

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

Purposes: No (Agency/Public Body, Network)

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

When:DSA runs 2019-01-02 — 2020-01-01 2019.09 — 2021.05.

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

Data-controller type: 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.


Access to HES via NHS Digital online portal - NIC-09042-L9M1K — DARS-NIC-18798-V2J6C

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, 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)

Purposes: No (Agency/Public Body)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-12-01 — 2020-03-31 2017.09 — 2021.05.

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.

Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204571-R1F4T

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

Purposes: No (Network)

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

When:DSA runs 2019-03-07 — 2021-03-06 2019.09 — 2021.02.

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.

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

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 — 2020.11.

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

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

Sublicensing allowed: No

Datasets:

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

Objectives:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Expected Benefits:

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

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

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

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

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


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

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

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

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

Outputs:

Outputs fall into the following categories:

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

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

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

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

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

Processing:

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

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

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

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

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

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

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

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

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

NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)

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

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

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


DATA MINIMISATION

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

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

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

All access to data is auditable by NHS Digital.

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

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 (Agency/Public Body, Network)

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

When:DSA runs 2019-01-02 — 2020-01-01 2019.09 — 2020.11.

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.


Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204544-H5L0S

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 — 2019.12.

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.

National Cancer Waiting Times Monitoring Data Set (NCWTMDS) with derivation of deprivation age and gender — DARS-NIC-266008-T3S9D

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).

Diagnostic Imaging Data — DARS-NIC-15336-S8W9K

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

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(2)(b)(ii)

Purposes: No (Agency/Public Body)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-02-10 — 2022-02-09 2017.09 — 2018.05.

Access method: Ongoing

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Diagnostic Imaging Dataset
  2. Diagnostic Imaging Data Set (DID)

Objectives:

The primary purpose of the flow is for production of Official Statistics, answering Parliamentary Questions (PQs) and media queries, which are the current responsibility of NHS England as subject matter experts.

In addition, NHS England will use the data for jointly assessing and addressing data quality problems with HSCIC.

Access to pseudonymised record level DID data will also enable NHS England:

• To perform better analysis of cancer pathways by indicating where, what and when imaging takes place in the pathway

• To allow Public Health England to calculate more accurate estimates of the distribution of individual radiation dose estimates from medical exposures

• To enable analysis of demographic and geographic variation in access to diagnostic imaging tests

• To provide detailed national data on trends and patterns in NHS imaging to demonstrate how expensive equipment and trained workforce are deployed and support capacity planning

• To discontinue the existing annual KH12 dataset and reduce burden on providers

• To understand and influence issues around delays in access and turnaround times for tests (including analysis of median periods and distributions)

• To provide more detailed national data than is otherwise available on test type (modality), body site of test and patient demographics, which can reveal the impact of initiatives to improve outcomes for patients by influencing the type, timing and number of tests

• To allow benchmarking in the rate of provision of diagnostic tests overall and in GPs’ direct access to tests, to encourage increased use of tests leading to earlier diagnosis and hence improved outcomes

• To inform accreditation processes for imaging departments through the UK Imaging Services Accreditation Scheme and the assessment of imaging services by the Care Quality Commission.

• To inform work on development of accurate tariffs for all diagnostic imaging tests

Yielded Benefits:

NHS England has continued to utilise Diagnostic Imaging Data to: - Monitor and improve diagnostic imaging services, by measuring access to imaging services - Improve cancer survival rates by reducing referral to treatment times and diagnosing cancers earlier - Reduce unnecessary exposure to radiation by monitoring compliance with clinical guidelines Benefits achieved to date - The reported measures for nine key modalities including X-ray, Ultrasound, CT and MRI scans. This provides more information on NHS provision of these services than any other resource and is the only source of national information on some modalities. - The trends and patterns of provision demonstrate where there is scope for improving the early of diagnosis of cancer, in particular highlighting the share of referrals made by GPs. - The published Diagnostic Imaging Data statistics have also been used by third parties such as CQC (to help with Ionising Radiation (Medical Exposure) Regulations compliance), PHE (Population radiation exposure) and NHS Improvement, giving essential information to support their work.

Expected Benefits:

NHS England will utilise DID data to continuously:

• Monitor and improve diagnostic imaging services, by measuring access to imaging services
• Improve cancer survival rates by reducing referral to treatment times and diagnosing cancers earlier
• Reduce unnecessary exposure to radiation by monitoring compliance with clinical guidelines

Benefits achieved to date

The reported measures for nine key modalities including X-ray, Ultrasound, CT and MRI scans. This provides more information on NHS provision of these services than any other resource and is the only source of national information on some modalities.

The trends and patterns of provision demonstrate where there is scope for improving the early of diagnosis of cancer, in particular highlighting the share of referrals made by GPs.

Outputs:

Aggregated data is produced on a monthly basis, using accumulated annual figures, with small numbers suppressed in line with the HES analysis guide. This is published as an official statistic, conforming to National Statistics protocols on a public website https://www.england.nhs.uk/statistics/statistical-work-areas/diagnostic-imaging-dataset/

In additional to production of the official statistics, NHS England will use the DID data to produce ad-hoc reports and analyses for the purposes outlined in the objective for processing section.

All outputs will be aggregated with small numbers suppressed in line with the HES analysis guide. No third party will have access to any record level DID data.

Outputs already produced

Official statistics from the Diagnostic Imaging Dataset (DID) have been published by NHS England (previously Dept of Health) monthly since 2012-13. In addition, annual reports and additional analyses have been published for 2012-13 to 2014-15.

Key statistics include:
• Number of diagnostic tests performed
• Period from referral to test
• Period from test to the test report being issued

These measures are reported for nine key modalities including X-ray, Ultrasound, CT and MRI scans.

In addition, data are published for a subset of tests that are particularly used to identify or discount a diagnosis of cancer.

These statistics are published for England and by Provider on a monthly basis and additionally by Commissioner on an annual basis. They are accompanied by information on data quality, coverage and completeness. Additional annual analyses include:

• Annual reports incorporating maps and additional analysis by age, sex, referral source and Provider
• Annual technical reports that further explain and describe the data collected
• Standardised imaging rates by CCG, showing the variation in provision
• Supplementary information on other modalities
• A comparison of 2013-14 DID imaging activity with other data sources: DM01 and KH12.

In addition to the material published on the NHS England web pages, NHS England produce ad hoc analyses to respond to queries raised by our clinical or policy contacts and others via the contact address did@dh.gsi.gov.uk.

Examples of the outputs and associated benefits of these analyses include:

• Rates of CT virtual Colonoscopy and Barium enema, which were compared with endoscopy rates (from HES) to show areas of best practice
• Cardiac imaging comparisons, showing relative proportions of CT and MRI activity
• Analysis by day of the week, to inform the debate around 7-day services
• Evaluation with CRUK of ‘Be Clear on Cancer’ initiatives such as for ‘Blood in pee’ and Lung cancer, by demonstrating increased diagnostic activity in periods and areas of the publicity campaigns
• Usage of individual NICIP or SNOMED CT codes, to review changes in coding practice
• Additional analysis to compare DID waiting times with DM01, to investigate delays around diagnostics
• Contributions for consideration or use in the Diagnostic Atlas of Variation published by Rightcare at http://www.rightcare.nhs.uk/index.php/atlas/diagnostics-the-nhs-atlas-of-variation-in-diagnostics-services/
• Data quality analyses, to work together with HSCIC to improve the completeness and usability of DID.

Processing:

NHS England currently hold peudonymised DID data from April 2012 onward . The DID data received within this agreement will be added to the DID data already held by NHS England which is used to create monthly and annual Official Statistics publications.

DID data will be provided to NHS England on a monthly basis. Each new months’ data is appended to the existing dataset until all files for a financial year have been published. Data is added to the database on 4th of each month and a report is normally published around the third Thursday of the month.

NHS England do not hold any identifiable DID data. NHS England will not link DID data to any other data set.

All individuals with access to the record level data are employees of NHS England and no third party will have have access to the record level DID data.

Project 24 — NIC-107814-Z0J1Q

Opt outs honoured: N ()

Legal basis: Health and Social Care Act 2012

Purposes: ()

Sensitive: Sensitive

When:2017.12 — 2018.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Improving Access to Psychological Therapies Data Set
  2. Mental Health Services Data Set
  3. SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
  4. Mental Health Minimum Data Set
  5. Mental Health and Learning Disabilities Data Set
  6. Local Provider Data - Emergency Care
  7. SUS for Commissioners
  8. Ambulance-Local Provider Flows

Objectives:

Objective for processing:
Generic objectives applicable to all requested data sets
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. To engage the Health Foundation to provide their analytical expertise to the Health Data Lab project
5. There is a requirement to link all datasets available on the tNR in order to fully understand patient pathways. This enables better planning of patients care to realise improvements and efficiencies. This will be possible through the creation of a consistent pseudonym applicable to all datasets.
In summary, to better understand the relationship between physical and mental health, NHS England intend to link SUS, Mental Health (MHMDS, MHLDDS, MHSDS), IAPT and 111 pseudonymised record level data for commissioning purposes to ensure commissioners can understand full patient pathways for their patients and plan their care. This is an area where the evidence is currently relatively weak, for example NHS England cannot currently answer questions such as whether patients with MH issues are more likely to be admitted or readmitted to hospital, or whether they have longer stays, and therefore linking data is an important requirement.

Objectives applicable to specific data sets
Mental Health (MHSDS, MHLDDS, MHMDS): Despite previous initiatives such as the 2011 mental health strategy, challenges with system-wide implementation coupled with an increase in people using mental health services has led to inadequate provision and worsening outcomes in recent years, including a rise in the number of people taking their own lives. NHS England and the Department of Health published Future in Mind in 2015, which articulated a clear consensus about the way in which NHS England can make it easier for children and young people to access high quality mental health care when they need it. The 2016 Five Year Forward View for Mental Health report from the Mental Health Taskforce builds on this strategy and sets out the start of a ten-year journey for the transformation which clearly states the role that NHS England has to play.
The Mental Health data is crucial in monitoring progress against the Five Year Forward View. In particular, it will help:
• Understand current patient pathways, what care is available now and what level of referrals to mental health services are anticipated to ensure 70,000 additional children and young people each year will receive evidence-based treatment.
• Ensure that there will be the right number of CAMHS T4 beds in the right place reducing the number of inappropriate out of area placements.
• Support at least 30,000 additional women each year to access evidence-based specialist perinatal mental health treatment.
• Ensure that appropriate services are being commissioned to reduce the premature mortality of people living with severe mental illness (SMI); and 280,000 more people having their physical health needs met by increasing early detection and expanding access to evidence-based physical care assessment and intervention each year.
• Ensure people with SMI can access evidence based Individual Placements and Support (IPS)
• Ensuring that at least 60% of people with first episode psychosis starting treatment with a NICE-recommended package of care with a specialist early intervention in psychosis (EIP) service within two weeks of referral.
• Support a comprehensive programme of work to increase access to high quality care that prevents avoidable admissions and supports recovery for people who have severe mental health problems and significant risk or safety issues in the least restrictive setting as close to home as possible.
• Improve the quality of services commissioned, the case-mix of patients in treatment, population needs, the differences in success of treatment and care at practice, CCG, provider level and other geographies (e.g. regions) as well as the impact on other parts of the healthcare system, e.g. A&E.
• Improve outcomes and tackle inequalities of people with MH problems.
• Provide insight into suicide by looking at those with prior mental health problems, the severity and length of the problems and how many of those committing suicide also had wider physical health problems to help reduce the number of people taking their own by lives.
• Enable the robust quality and performance planning and monitoring at a local and national level.
• Make availability of home treatment visible in every part of England as an alternative to hospital
• Check provision of all-age mental health liaison services to meet the national commitment that at least 50% will meet the service standard
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.
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.

IAPT: 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).
The use of IAPT data will support the following priorities for service development:
• Expanding services so that at least 1.5m adults access care each year by 2020/21. This means that IAPT services nationally will move from seeing around 15% of all people with anxiety and depression each year to 25%, and all areas will have more IAPT services.
• Focusing on people with long term conditions. Two thirds of people with a common mental health problem also have a long term physical health problem, greatly increasing the cost of their care by an average of 45% more than those without a mental health problem. By integrating IAPT services with physical health services the NHS can provide better support to this group of people and achieve better outcomes.
• Supporting people to find or stay in work. Good work contributes to good mental health, and IAPT services can better contribute to improved employment outcomes.
• Improving quality and people’s experience of services. Improving the numbers of people who recover, reducing geographic variation between services, and reducing inequalities in access and outcomes for particular population groups are all important aspects of the development of IAPT services.
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 better understand the relationship between physical and mental health, NHS England intend to link SUS, Mental Health data and IAPT record level data that has been pseudonymised using a consistent pseudonym which has been derived for commissioning purposes. This is an area where the evidence is currently relatively weak. Linking SUS, Mental Health and IAPT 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 MH issues are at a higher risk of particular outcomes (e.g. admissions, readmissions, increased lengths of stay).Therefore linking data is an important requirement.

IAPT Pilot Data: 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 planned to release substantial savings across local health economies.
In order 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. They need to identify cost savings / reductions in expected activity from the system as a result of integrated treatment of co-morbid physical and mental health problems, showing that they are realisable in practice. Therapists will be co-located within long term conditions / medically unexplained symptoms (MUS) care pathways as part of multidisciplinary teams.
Sites will be providing integrated psychological therapies in a range of settings: general practice, integrated care teams, community specialist care teams such as Diabetes or Respiratory, outpatients’ teams and community hubs. New and existing therapists will be co-located in general practice and form the first of the ‘3000 mental health therapists’ committed to in the General Practice Forward View.
NHS England is supporting Early Implementer pilot sites to deliver new Integrated IAPT services. The first wave of these sites are listed in Appendix A.
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.
Additional data not captured in the IAPT Minimum Dataset is required in order to assess the impact of the Integrated IAPT Early Implementer services on patient outcomes and use of health services. Please see Appendix B for a list of data items being requested from the IAPT pilot data set. The additional measures are a modest extension of the existing IAPT dataset. The main change is simply an expansion of the list of disorder specific measures to match the expanded number of conditions being treated. In addition, there will be a short measure of self-reported healthcare utilisation to support the analysis of healthcare utilisation and savings.
This information is needed to ascertain what the key components of successful interventions are, and the population groups they work best with. The use of the additional pilot data will support the following priorities for IAPT expansion:
• Measuring changes in healthcare utilisation – showing the savings that can be realised by creating Integrated IAPT services. In addition to self-report measures of healthcare utilisation, it is important to link the IAPT MDS (plus the additional measures) to secondary healthcare datasets (SUS), including Inpatient dataset, Outpatient dataset, A+E dataset, and the Critical Care dataset, in order to identify savings elsewhere in the system.
• Measuring outcomes from services accurately for people with long term conditions – using the additional outcome measures to understand how services support people with long term conditions and how this links to healthcare utilisation.
• Understanding how integrated services can best be implemented – understanding variation in access, outcomes and treatment in different sites.
Analysis of these dimensions will be vital in informing the future roll-out of integrated IAPT services. Roll out is estimated to cost around £157 million in 18/19, £233m in 19/20, and £308m in 20/21, which is due to be funded from CCG baselines. Delivering new integrated services is expected to deliver substantial savings (£26m in 17/18, £122m in 18/19, £236m in 19/20, £364m in 20/21), with services quickly becoming self-sustaining.
NHS England have contracted a team at Imperial College to undertake an evaluation of the pilot who have substantial experience in the use of routine data for evaluation of healthcare interventions.

111 Data: The 111 data is 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. It is essential that a national view of services is available to NHS England’s analysts. NHS England has a duty to ensure health services are provided in an integrated way. When exercising its functions, NHS England must do so with a view to securing that health services are provided in an integrated way where it considers that doing so would:
(a) Improve the quality of services, including outcomes;
(b) Reduce inequalities in access;
(c) Reduce inequalities in outcomes.

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 in pseudonymised, record level form
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.
Specific purposes for this data include:

1. Proactive assurance of CCG-commissioned 111 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. Data quality analysis and data quality management, to ensure data processing has been carried out effectively
3. Better understanding of the effectiveness of changes to the operating model for urgent and emergency care (UEC), such as increasing the level of clinical input within 111 services as triage and sign-posting of patients that contact the service; to do this, NHS England will need to be able to understand the pathways that patients follow post contact with the 111 service in order to provide an evidence base for changes to these services.
4. Identification of quality differences nationally between different providers and opportunities to improve the efficiency of 111 services.

The proposed approach is the provision of a single national system, white-labelled and provided locally to CCGs. The RAIDR-111 dashboard is an innovative BI 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, as per the CCG’s DSA.

North of England DSCRO 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 will be shared with Arden and GEM DSCRO in order to have the consistent pseudonym applied and subsequent upload to the tNR. 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 tNR 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.

Expected Benefits:

Expected measurable benefits to health and/or social care including target date:

General benefits applicable to all requested data sets
1. Analysis and reporting will help ensure that NHS England meets its statutory duties (as outlined above) to commission effective and efficient services in line with NHS England’s Five Year Forward View.
2. tNR 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. Enable NHS England to make better use of existing data, without compromising data security and by using data that is pseudonymised to mitigate the risk of compromising patient privacy.
7. Reduced resources whilst delivering robust assessment of national programmes.
8. 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.
9. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
10. Enables monitoring of:
a. CCG outcome indicators.
b. Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
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. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
11. 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.

Additional benefits applicable to specific data sets
Data set specific benefits, in addition to those listed above, include the following.
Mental Health (MHMDS, MHLDDS, MHSDS) data will also support:
12. Increased access to Mental Health and IAPT data are 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 us 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 the Data Controller (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).

111 data will also support:
13. A reduction in unnecessary use of A&E.
14. An increase in referrals to alternatives to A&E.
15. Improvement to performance of A&E waiting times

IAPT Pilot data will also support:
16. The IAPT Early Implementers pilot aims to measure healthcare utilisation as well as the mental and physical health benefits gained from the new services. NHS England aims to measure the impact of Integrated IAPT on treatment outcomes. Locally collected and nationally specified information to supplement the utilisation data will need to be included as necessary, for instance mental health outcomes, perception of physical health, and patient experience.

17. Service users and care providers will both benefit from the pilot, as it will allow NHS England to understand how Integrated IAPT co-located in and integrated with physical health services affects individuals’ mental and physical health, their healthcare utilisation, and their experience with IAPT. It will be possible to explore how characteristics of Integrated IAPT service models correlate with health care utilisation (e.g. measuring the outcomes for different service set ups – size of service, extent of integration with physical healthcare etc.) and understand how the characteristics of people accessing Integrated IAPT correlate with health care utilisation. It will be possible to understand which aspects of the service implementation contributed to changes in outcomes and to enable learning. This will help to inform the future commissioning and funding of Integrated IAPT services.
18. The benefits for patients in particular will be better access to psychological therapy for patients with physical long-term conditions and those with persistent medically unexplained symptoms, resulting from integrated services in physical healthcare pathways, specifically trained staff, and condition specific outcome measures. This will support IAPT services to reach the required 25% access rate set out in the Mental Health Five Year Forward View and to appropriately measure patient outcomes including recovery rates. This in turn will help to break down artificial barriers between physical and mental healthcare, and pave the way for further implementation of integrated healthcare services nationally.

Outputs:

Specific outputs expected, including target date:
General outputs applicable to all requested data sets
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 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 down to individual GP Practice level.
22. Produce GP Practice level dashboard reports, including high flyers.

Additional outputs applicable to specific data sets
Outputs applicable to specific data sets include the following.

SUS will also support:
23. Gap and reconciliation analyses between monthly activity returns versus SUS/CDS data.
24. Gap and reconciliation analyses between aggregate contract monitoring reports submitted to DSCROs versus SUS/CDS.

Mental Health (MHMDS, MHLDDS, MHSDS) data will also support:
25. A Mental Health Five Year Forward View (5YFV) dashboard; delivered in response to the recommendation in the 5YFV. NHS England recently published a first version of this dashboard, which will allow us to hold national and local bodies to account for implementing the 5YFV strategy. The dashboard is structured around the core elements of the MH programme as set out in the 5YFV implementation plan, and include perinatal mental health, children and young people’s mental health and elements across the common, crisis and secure adult mental health pathway including health and justice and suicide prevention. NHS England require improved Mental Health/IAPT data to further develop some of the indicators in the dashboard.
26. To use the Mental Health data to support contract payment and clinical case management (and develop a reliance in this data flow akin to acute services and their use of SUS data).
27. Regular monitoring reports of commissioners (inpatient services) to meet NHS England’s statutory duties and to demonstrate the delivery of NHS England’s Learning Disability Programme by cross-referencing relevant activity with Assuring Transformation data, due to end in 2018
28. To support ongoing updates to the Mental Health Quality Dashboard using quality measures derived from the MHMDS and MHLDDS. (The current dashboard is under review to focus the measures further on quality and utilising the dataset will enable a wider availability of measures as well as robust data. The dashboard can be used by QSG, commissioners and providers for benchmarking and identifying areas for service improvement as well as to inform commissioning decisions.)
29. To support the development of Clinical Services Quality Measures (CSQMs) that provide an at-a-glance indication of how well services are performing. They have been/will be developed as composite measures for Psychosis and Dementia specifically as a series of metrics that, for example, will allow for comparisons between services such as units within hospitals; providing better information for patients clinicians and citizens. Supressed numbers currently available in the published reports do not allow annual aggregation to be input into the composites. The measures will be developed according to statistical principles and will be assured by clinical and technical experts. (NHS England is involving patients, the public, service providers and clinicians in the development of these measures with aggregate – service level information to be available via NHS Choices and My NHS.)

111 data will also support:
30. A single national system, white-labelled and provided locally to CCGs by each CSU through their local BI portal, from April 2017
31. Reporting and analysis to support the proactive assurance of CCG-commissioned 111 services – including contract management, performance management, needs and inequalities analysis, benchmarking, service review and development, planning, budgets and allocations and general commissioning assurance activities, from April 2017
32. Data quality analysis and data quality management, to ensure data processing has been carried out effectively, from April 2017

IAPT pilot data will also support:
33. The provision of an Interim Report by October 2017, and a final report in 2018, by Imperial College on the IAPT Early Implementers programme. These reports will identify patient outcomes in these services, uptake rates of patients accessing the new Integrated IAPT services, the profile of patients being offered the services and those using them. It will also help identify groups that are under or over-represented and give insight into patient experience of the new services. Crucially, by analysing healthcare utilisation using the linked SUS/IAPT/IAPT pilot dataset, these reports will include an indication of whether the Integrated IAPT Early Implementers services have resulted in savings in the health system as well as the observable changes in healthcare utilisation. Only aggregated data summaries e.g. by patient cohorts will be produced and included in the reports. The aggregate IAPT reports produced by Imperial College will adhere to NHS Digitals disclosure control rules before being shared outside the organisation. For data from the Mental Health data sets, and any Mental Health data linked to SUS, the following disclosure control rules will be applied:
- National level figures only may be presented unrounded, without small number suppression;
- Suppress all numbers between 0 and 5;
- Round all other numbers to the nearest 5;
- Percentages can be calculated based on unrounded values, but need to be rounded to the nearest integer in any outputs;
- In addition for Learning Disability data in Mental Health, the England level data also must apply the suppression of all numbers between 0 and 5, and rounding of other numbers to the nearest 5.
34. Analysis in detail of the mental and physical health outcomes being obtained by people using integrated services, and how service features influence outcomes. This analysis will support commissioners in implementation of integrated services across the NHS.

The target commencement date for the above outputs is December 2016 for existing data sets and March 2017 for the 111 data, as agreed in previous applications (references can be found in the summary section. For IAPT Pilot data this refers to the approval for data to flow to NHS England and not the collection which has already commenced. The aim is to monitor changes on a monthly basis going forward.

Processing:

Processing activities:
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, 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. 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 LSOA level* (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).

AGEM CSU (in capacity of tNR host)
Activities: Data will flow to AGEM DSCRO for pseudonymisation. The pseudonymised dataset will then flow to other data processors, as listed below, to undertake processing activities on behalf of NHS England for a specific project(s) under Service Level Agreements.
• Data linkage between the data sets being requested in this application will be undertaken on pseudonymised record level data held within the tNR by NHS England data analysts operating under strictly controlled conditions and any inadvertent or malicious re-identification of data subjects will be recorded and reported in line with the NHS England’s incident (disciplinary) management process and appropriate action taken. A national feed of identifiable commissioning datasets (SUS, MHMDS, MHLLDS, MHSDS, IAPT and IAPT Pilot data) will be transferred from NHS Digital to Data Services for Commissioners Regional Office (DSCRO) AGEM who will complete data quality checks, pseudonymisation and validation of the data.
• The DSCRO will apply the same pseudonymisation key to all NHS England required datasets in order to enable linkage by the AGEM CSU Data Processor (within the tNR).
• DSCRO AGEM, in addition, also send a copy of identifiable SUS data to DSCRO North England. DSCRO North England collate all 111 data from all other DSCROs into a central processing area, link the 111 data with SUS data and transfer the data to DSCRO AGEM.
• DSCRO AGEM securely transfer the following pseudonymised data (anonymised in accordance with the DSfC Anonymisation Requirements for Data used for Commissioning Purposes and in line with the ICO Anonymisation Code of Practice) to Arden and GEM CSU who act as NHS England’s main data processor:
- SUS
- Mental Health (MHMDS, MHLDDS, MHSDS)
- IAPT
- IAPT Pilot data
- Linked SUS and 111
The data will be stored on a repository server within Arden and GEM CSU, known as the temporary national repository (tNR).
In addition, an extract of linked SUS and 111 data will be shared with SCW CSU for specific additional processing, as detailed below.
The IAPT pilot data will also be stored securely and logically separated from other tNR data sets and will only be made available to up to 5 NHS England analysts and up to 3 Data Services for Commissioners data management specialists who will be responsible for its processing or undertaking analysis to meet the statutory duties listed in this application. Any linkage with other datasets held on the tNR will only be permitted for purposes outlined in this agreement and users will be required to log any such linkage and the reasons for it. In addition, an anonymised extract of linked SUS, IAPT and IAPT pilot data will be shared with Imperial College London for specific processing, as detailed below.
• The data will be processed in the tNR on behalf of NHS England (as recipient data controller) to meet the reporting requirements, by adding value to the data (e.g. adding a tariff and grouper) to support integrated patient care analysis.
• Under strict access controls, NHS England’s analysts (including those based within CSUs) will use remote access arrangements to query the pseudonymised record level data which is held within the tNR in order for them to analyse the data. The data can be accessed remotely from multiple locations in England using secure VPN or the N3 network, depending on where NHS Analysts are based. Access is secured via two personal user IDs and passwords; one to login in the terminal services server giving access to the Arden GEM network domain and then a further login into the SQL Server environment where the user is given read-only access to the data. Further information surrounding tNR access management can be found at the end of this section.

North England CSU (in capacity of urgent care dashboard host)
In order to provide a national view of all UEC activity on behalf of NHS England to all CCGs, in addition to the transfer of linked SUS and 111 data from DSCRO North England to DSCRO AGEM, DSCRO North England also transfer the linked SUS and 111 data to North England Commissioning Support Unit (NECS) for further processing and in order to upload the data to the dashboard tool. The data flow sequence and arrangements are specified below:
Activities:
• North England DSCRO consolidate all 111 data collected by the other DSCROs into a central processing area.
• AGEM DSCRO will supply a relevant extract of NHS England’s SUS data to North England DSCRO.
• North England DSCRO link the 111 and SUS data to create a purpose-specific linked data set and flow the linked data to AGEM for upload to the tNR in pseudonymised form.
• North England DSCRO also submit a pseudonymised extract to NHS England’s nominated CSU data processor – North East Commissioning Support (NECS).
• NECS will further process the pseudonymised patient level data so that each CCG in the country is able to receive the 111 data relating to their patients only (as per local DSAs) and upload to the dashboard.
• CCGs will also have the ability to see aggregate reports from the dashboard tool for the whole of England and their STP footprint which will enable them to benchmark their service providers and validate and analyse this across wider health economies in line with the statutory duties under the Health and Social Care Act 2012.
Please note that the individual (209) CCG DSAs will be updated and approved by IGARD to capture the use of NECS for this processing, prior to NECS enabling CCG access to pseudonymised, record level SUS and 111 data. (NECS will work upon instruction from NHSE as Data Controller.)

South, Central & West CSU (in capacity of National analytical support for 111)
Activities:
South Central West Commissioning Support Unit (SCW) will be provided with an anonymised 111 Minimum Dataset, linked with the anonymised SUS dataset for the period 2015/16, 2016/2017 and current 2017/18 up to 31st December 2017 for the delivery of the agreed SLA with NHS England.
Data analysis will only take place on patient-level data where it has been pseudonymised and will include analysis of 111 and SUS data. SCW will produce four reports from the data (three interim and final).
Data processing activities will include general completeness checks; validation will have taken place before the data is provided. SCW will then look at the changes in flow of patients through the 111 services and into onward providers where available and relevant. The key links will be with patients disposed from 111 to Emergency Departments. This analysis relies on matched 111 and accident and emergency data.
The second stage of the analysis will look at patterns before and after the increase in clinical resource into Clinical Assessment Service (CAS). SCW intend to determine impact by comparing the differences in the change from this analysis and, by use of other nationally available comparators (ethnicity, deprivation, geography etc.), estimate impact of the intervention.
The national 111 dataset should be available from 1st May 2017 and released on an on-going monthly basis. Access is limited to those substantive employees with authorised user accounts used for identification and authentication.

The Health Foundation
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.

Activities: 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.
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

Datasets: The Health Foundation will receive the following data flows:
• SUS
• Mental Health (MHSDS, MHLDDS, MHMDS)
• IAPT

Imperial College London
In order 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.

Activities:
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 contract, which includes access to full anonymised IAPT and SUS datasets for 2013/14, 2014/15, and 2016/17, plus current data up until 31st March 2018.
They 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 patient-level data where it has been pseudonymised and would include analysis of IAPT (incl. pilot data) and SUS data and 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.
Imperial intend to analyse changes in healthcare utilisation as follows:
1. By using matching techniques to identify the controls for the treated patients (hence the need for 3 years data prior). We will possibly use machine learning techniques to enable us to exploit the rich data in SUS on patient comorbidities and diagnoses.
2. Then comparing the healthcare utilisation of the treated group using data from SUS on inpatient, outpatient and A and E attendances pre- and post-reform.
3. Undertaking a similar analysis for the control sample.
4. Comparing the differences in the change for the treated and control groups and use this as an estimate of the impact of the policy. Imperial will disaggregate by type of utilisation and also by patient groups and by other dimensions which are important (for example, measures of SES).

Timescales: An initial extract of the above historic datasets will be provided to Imperial College on approval of the application. Subsequent releases will be based on the requirements of the project and adhere to DSA and DPA conditions. For this it will be crucial that the pseudonym remains the same for the duration of this programme, so new monthly extracts can be linked to historical extracts.
Imperial College’s security arrangements are outlined in the attached Data Security Policy, which includes role based access controls, a secure server environment, and log in security. Only three individuals who are directly working on this analysis will be able to access the data. Access is limited to those employees with authorised user accounts used for identification and authentication.

tNR Access Management
NHS England will limit the amount of pseudonymised data which is made available to analysts. Where access to the tNR is required by internal users (based within NHSE and CSUs), a robust user registration process is in place, which involves:
• Sign-off by the analyst’s lead manager to ensure that all users have a suitable level of knowledge about SQL Server and tNR processed data.
• Submission of an access request application, outlining the purposes for which they require access.
• The IAO of the tNR assessing the request to ensure that it is in line with the agreed purposes included in the data sharing agreement.
Once access to data on the tNR is granted, according to the role and user requirements, access is secured by using 2 factor authentication, via VPN and on the N3 network.
As recipient data controller, NHS England are responsible for and will ensure that the use of the data is in line with the NHS Digital data sharing framework contract and data sharing agreement and will take all steps necessary to minimise the risk of inadvertent or malicious re-identification. NHS England believe that the wider benefits of using the data to meet its statutory duties to ensure that patients receive the most appropriate care outweigh the extremely low risk of re-identification from the processing activities required.
Access is limited to those substantive employees with authorised user accounts used for identification and authentication.
*a LSOA is a small geographical area typically covering about 1500 people

Assuring Transformation — DARS-NIC-389823-P1P6B

Opt outs honoured: No - Assuring Transformation is disclosed under the following approval: Enhanced Quality Assurance Process Data flow - CAG 8-02 a-c/2014, No - data flow is not identifiable, Identifiable, Anonymised - ICO Code Compliant (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012, Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(7), 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 (Agency/Public Body)

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

When:DSA runs 2019-04-01 — 2020-03-31 2017.06 — 2017.05.

Access method: Ongoing, Monthly, One-Off

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: Yes

Datasets:

  1. Monthly Subscription Assuring Transformation
  2. Assuring Transformation (Identifiable)
  3. Assuring Transformation (Pseudo)
  4. Assuring Transformation (Pseudo)

Objectives:

Use monthly and weekly Assuring Transformation (AT) data to derive performance and quality indicators for Learning Disability services, in order to drive improvements in the services and to identify where good/poor practice is taking place. Analysis will be carried out by NHS England analysts. The analysts will use the fully identifiable data set to produce useful analysis for operational managers and LD Programme staff. The analysis they produce will not include identifiable information.

(b) Use timely operational management information, to allow NHS England to monitor and manage delivery of Transforming Care improvements to care for inpatients with a learning disability, behaviour which challenges or an autism spectrum disorder. Unsuppressed small numbers are included in this data set to ensure that commissioners are carrying out their duties in relation to discharging people with a learning disability who are placed inappropriately in hospital. Each CCG is likely to have small numbers in each category and it is important to be able to track if they have reduced their number from e.g. three to two, which unsuppressed numbers do not allow. The operational management report cannot be used for its intended purpose of monitoring commissioner CCG-level activity unless it is populated with unsuppressed data.

NHS Digital will be supplying operational management information reports to NHS England on a frequent weekly basis. NHS England will not be doing any processing, but will be using the reports as produced by NHS Digital to manage CCG performance.

The new data fields in the AT data set give further insight into delivery of improvements, specifically the Care & Treatment Review process which is used to identify patients suitable for discharge and the barriers currently preventing discharge. Including the new AT fields in the extracts and reports sent to NHS England will facilitate targeted work to discharge patients who have been identified as ready to be discharged from inpatient care.

(c) Use information on the location of services and the number of patients using these services to effectively plan and deliver transformational change, reducing the reliance on inpatient care for people with learning disability and/or autism. Planning and delivery will be carried out by Transforming Care Partnerships (TCPs) - CCGs, specialised commissioners and local authorities working together to ensure appropriate and effective services are put in place for this vulnerable group of people. TCPs are responsible for the delivery of the transformation of services, reducing the reliance on inpatient care and using local services to help people live in the community. This will ensure people with learning disability and/or autism receive effective and appropriate care close to their homes.

To be able to plan and deliver these new services, TCPs need to have reliable detailed data about the people currently in hospital who originate from their CCGs / local authorities. This will allow them to put appropriate services in place for when patients leave hospital, and to ensure the appropriate provider capacity is available for those people that do still require hospital care.

No TCP would see another TCP's unsuppressed data.

Yielded Benefits:

The data has provided operational managers with the evidence base through which to drive improvements in services and patient experience, to reduce the reliance on inpatient care and to manage the safe discharge of inpatients to the community. Commissioners have been able to monitor progress against planned trajectories for reductions in inpatient numbers and take prompt action when performance has fallen below expectation. AT data has been used as the baseline to monitor performance against the new Care and Treatment Review (CTR) Policy which took effect from 1 April 2017, helping to reduce the number of people going into these hospitals as well as to improve the quality of care people receive in hospital. Transforming Care Partnerships (TCPs) have been able to sue the data to effectively plan and commission appropriate services, and to reduce the reliance on inpatient care. More effective commissioning of any required inpatient services will save the NHS money, reducing the need for spot-purchasing of care and lengthy block contracts with providers. NHS England has been able to monitor patients at commissioner level, and identify blockages which are preventing patients being discharged. NHS England has also been able to carry out specific pieces of analysis, such as detailed work on the u-18 age group.

Expected Benefits:

The data gives insight at organisational (provider/commissioner) level, the benefits are that operational managers will have an evidence base through which to drive improvements in services and patient experience. As soon as this evidence base is available actions can be taken to begin these improvements. Without this evidence base targeted work to improve services and patient experience cannot take place. The data enables performance management of trajectories to reduce inpatient numbers.

The information will be used day-to-day, to reduce the reliance on inpatient care and to manage the safe discharge of current inpatients to the community. Benefits will flow immediately as NHS England national and regional managers are able to take immediate action when necessary. Commissioners are developing trajectories for inpatient numbers to March 2017 and these reports will help manage delivery of these trajectories.

As well as an in-year delivery target commissioners are developing three-year (2016/17 - 2018/19) transformation plans in line with the published national transformation plan Building the Right Support. Operational management data is important for helping manage delivery of these plans, to ensure any deviation from trajectory is identified early and can be acted on. Detailed information is required by TCPs to plan and commission effectively.

The additional request to share detailed data with TCPs will allow TCPs to effectively plan and commission appropriate services, and to reduce the reliance on inpatient care. It will enable patients to be moved from inappropriate inpatient facilities to community care which is closer to home and more appropriate to each individual's needs, improving their quality of life. More effective commissioning of any required inpatient services will save the NHS money, reducing the need for spot-purchasing of care and lengthy block contracts with providers.

The data already received by NHS England has allowed them to carry out detailed analysis to support delivery of the Transforming Care programme, in particular the objective of reducing the reliance on inpatient care. NHS England has been able to monitor patients at commissioner level, and identify blockages which are preventing patients being discharged. NHS England have been able to carry out specific pieces of analysis, such as detailed work on the u-18 age group – this has contributed to the reduction in the number of u-18 patients.

Changes to the contents of the data set in 2015 included the ‘CCG of origin’ field which has enabled NHS England to map patients whose care is specialised-commissioned by NHS England (over half the inpatient total) to be mapped to their home CCG. This is vital to the process of planning services – without this information local Transforming Care Partnerships (TCPs) do not understand the total number of inpatients that they need to be planning services for. Using this information TCPs have been able to develop 3-year transformation plans. Amending the agreement to allow NHS England to share unsuppressed data with TCPs will allow TCPs to properly and accurately complete these plans, giving them a full understanding of their inpatient numbers and the services these patients are using.

Outputs:

(a) Outputs are aggregated commissioner-level analysis, used for internal management purposes. The monthly data and analysis allow local operational managers to ensure commissioners are delivering national performance indicators, and to intervene when they are not.

(b) The operational MI outputs will only be available to operational managers within NHS England. No other organisations will have access to this data. This information will not be used or shared outside NHS England. [Note that this is a weekly output - section 9 of this template does not include 'weekly' as an option in the Frequency table]

Analysis will not be published in journals or be used in relation to clinical trials, nor used for direct marketing. Performance dashboards and other analysis will be used internally and with commissioners once the Management Information has been published by NHS Digital. These will be in aggregated form only. NHS Digitals’ guidance on suppression of small numbers will be followed.

(c) Aggregate, unsuppressed TCP-level reports showing the numbers of patients at each provider site, the number of patients at each level of ward security and the numbers of patients in hospital split by length-of-stay groups. This will be used to plan services and identify services which will be decommissioned as services are transformed and bed numbers are reduced.

Processing:

Data will not be stored, processed or in any other way accessible by a third party. Data is stored in the secure storage that was set up when NHS England managed this data collection themselves.

(a) Monthly data will be analysed to produce aggregate level reports, to allow operational managers to work with challenged organisations to improve delivery and performance against key national indicators. Patient level data will be accessible only to those named individuals that have been given access to the secure data storage, and will only be accessed in the safe haven environment set up for this purpose.

(b) NHS Digital supplies operational management information reports to NHS England on a weekly basis. NHS England does not carry out any processing, but ensures the operational MI reports are provided to the named operational managers, who use the reports generated as produced by NHS Digital to manage CCG performance.

(c) NHS England will supply data to TCPs to allow them to plan and deliver transformational change to services for people with learning disabilities and/or autism. To allow them to effectively plan and deliver these services they need access to unsuppressed data showing the number of patients originating from the TCP at each hospital site. The data supplied to each TCP will only include information for patients originating from that TCP, and will not include NHS number, date of birth or home postcode.

Project 26 — CASEMIX_NHSE

Opt outs honoured: No - data flow is not identifiable ()

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

Purposes: ()

Sensitive: Non Sensitive

When:2017.06 — 2017.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Episode and Spell level grouper results; underlying patient level data.

Objectives:

To inform the decision making process for determination of the scope and structure of the future Grouper Products