NHS Digital Data Release Register - reformatted

NHS Scarborough And Ryedale Ccg projects

• Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System (partially via "system access")
• DSfC - NHS Scarborough and Ryedale CCG: RS, IV & Comm.
• Project 3
• Project 4
• Project 5
• Project 6

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

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

Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204531-P5L8G

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location, Network)

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

When:DSA runs 2019-11-01 — 2020-10-31 2019.11 — 2024.09.

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 EAST RIDING OF YORKSHIRE CCG, NHS HUMBER AND NORTH YORKSHIRE ICB - 02Y

Sublicensing allowed: No

Datasets:

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

Objectives:

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.


Humber, Coast and Vale Cancer Alliance

NHS East Riding of Yorkshire Clinical Commissioning Group (the CA's Hosting organisation) will directly access the Cancer Waiting Times System on behalf of Humber, Coast and Vale Cancer Alliance across Humber, Coast and Vale. Humber, Coast and Vale Cancer Alliance is hosted by NHS East Riding of Yorkshire Clinical Commissioning Group a population of 1.4 million people.

NHS East Riding of Yorkshire Clinical Commissioning Group hosts Humber, Coast and Vale Cancer Alliance.

NHS East Riding of Yorkshire Clinical Commissioning Group works with health organisations across Humber, Coast and Vale including 3 acute providers, 6 clinical commissioning groups, no community providers and 6 hospices.

Acute Providers

Hull and East Yorkshire Hospitals NHS Trust (RWA)
Northern Lincolnshire and Goole Hospitals NHS Foundation Trust (RJL)
York Teaching Hospitals NHS Foundation Trust (RCB)

Clinical Commissioning Groups

NHS East Riding of Yorkshire Clinical Commissioning Group (02Y)
NHS Hull Clinical Commissioning Group (03F)
NHS North East Lincolnshire Clinical Commissioning Group (03H)
NHS North Lincolnshire Clinical Commissioning Group (03K)
NHS Scarborough & Ryedale Clinical Commissioning Group (03M)
NHS Vale of York Clinical Commissioning Group (03Q)

Hospices

Andy’s Children’s Hospice, Barton-upon-Humber
Dove House Hospice, Hull
Lindsey Lodge, Scunthorpe
Saint Catherine's Hospice, Scarborough
St Andrew's Hospice, Grimsby
St Leonards Hospice, York


Data access

The CWT system provides the lead organisations 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 Humber, Coast and Vale Cancer Patients.

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

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

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

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

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

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

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

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

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

Purpose One - Aggregate local reports
Generation of routine Cancer Waiting Times reports at Provider (Trust) or CCG level. Lead organisations will access a summary of the totals for the Providers (Trust) and 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 (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. 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.

While the Cancer Alliance works together to decide on areas of interest, the lead organisation decides, independently, how to support these decisions via the use of the CWT data.

Yielded Benefits:

The CA has used data available from NHS England's (NHSE) Statistical Work Areas; information received from Cancer Alliance Data, Evidence and Analysis Service (CADEAS) and other public websites such as Fingertips to create a variety of products such as: o Cancer Performance Dashboard o Diagnostics Waiting Times and Activity for Diagnostic Tests and Procedures Dashboard o 2 Week Wait Conversion Rates These products have been used to assist the Cancer Alliance to provide performance insights for all trusts and CCGs; analysis of individual trusts’ performance against each indicator down to the individual tumour or treatment type; performance management information to guide conversations with NHS England, CCGs, individual trusts and the CA’s Programme Executive Board; System Board; Systems Performance Assurance and Monitoring Group etc. In addition, these products and other analysis has been used to information: o Bids for Transformational funding:  Cancer Champions Programme (CCP) was developed in North East Lincolnshire and is being rolled out to all areas within Humber Coast & Vale (HCV). The CCP is designed to inform local populations, so they can identify symptoms and when and how to access services. The aim is to achieve an 11% increase in individuals acting on symptoms. The programme focuses on 12 cancers and includes awareness and understanding of the 3 screening programmes. Training is delivered within traditionally hard to reach communities\local businesses, health organisations, local councils and voluntary groups. The target to achieve 400 cancer champions has been reached 4 months ahead of schedule due to the popularity of the courses. The aim is to reach 800 champions in high risk communities by March 2019.  Diagnostics Work Programme – Decisions have/will be made about the future shape of diagnostics services (radiology, pathology, endoscopy) and action plans will be developed to deliver the necessary changes to enable delivery of the future model across HCV. This will include decisions about what equipment is required and where it should be placed for greatest impact and a strategy for diagnostics workforce development, recruitment and retention. We will also adopt standardise processes to remove unwarranted variation in practice and patient experience. All patients across HCV, both cancer and non-cancer, will benefit from an improved diagnostics services in terms of more timely diagnosis and access to treatment and reduced anxiety caused by waiting for a diagnosis. The ambition is for all diagnostic tests to be done and reported in accordance with national standards including CWT standards and pathway specific requirements. Outputs of the programme to date are a completed capacity and demand exercise across HCV which is informing priorities and development of the future model, on a strategic and collaborative basis. Work to commence delivery of digital pathology services and a networked approach to radiology reporting are also underway. o Bids for funding 62 Day Recovery Funding to improve the 62 day operation standard e.g. CA received £780k to provide additional services such as:  Colorectal Straight to Test – Funding (£214k) to appoint CNS’s to triage referrals and send patient straight to test where appropriate. It is expected 500 patients will be seen between Nov 18 and Mar 19.  Endoscopy activity - 17 weekend sessions to provide 400 additional colonoscopy procedures. 25 Follow Up clinics to progress patients requiring treatment. For a period of 3 months an additional 50 lists equating to 250 surveillance patients which would free up 10 FT slots per week internally; total of 120 FT slots - impact would be to reduce the endoscopy diagnostic part of the pathway by 4 days;  Imaging and Reporting Capacity – Additional 24 MRI slots for 16 weeks (total of 384 slots). This additional MRI capacity would enable FT turnaround times within 2 weeks for all the Trust's cancer sites and would allow specific focus on prostate. Additional 300 CT Scans taken and reported across Humber Coast and Vale footprint o Inform various pathway workshops where the aim of the day was to: Understand and agree the “as is”; Capture what is already ongoing; Identify opportunities to share and collaborate; Identify additional actions/resources required and Agree future ways of working. o Ongoing access to CWT data is essential to support our understanding of patient volumes and achievement against the standards at a tumour site specific level so that we can plan and prioritise service development that will have the biggest impact.

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.

As East Riding of Yorkshire Clinical Commissioning Group is acting as the lead organisation in a Cancer Alliance their access is via the same route as other Cancer Alliances i.e via the Cancer Wait Times (CWT) System. The team doing this processing within the CCG is separate from the commissioning team and would not have access to data provide via the DSCRO route. Additionally any separate agreement that the CCG has to access CWT may include other processors and purposes.

Only the lead organisation, NHS East Riding of Yorkshire Clinical Commissioning Group will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the NHS East Riding of Yorkshire Clinical Commissioning Group server. Role Based Access Control prevents access to data downloads to employees outside of the analytical team responsible for producing outputs; the Humber, Coast and Vale cancer Alliance Core team.

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

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

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

NHS East Riding of Yorkshire Clinical Commissioning Group 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 East Riding of Yorkshire Clinical Commissioning Group 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 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.

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.

For clarity, any access by Telstra, Telecity and Calderdale and Huddersfield NHS Foundation Trust and to data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

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.

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DSfC - NHS Scarborough and Ryedale CCG: RS, IV & Comm. — DARS-NIC-90691-W4B6F

Type of data: information not disclosed for TRE projects

Opt outs honoured: N, Y, No - data flow is not identifiable, Yes - patient objections upheld, Anonymised - ICO Code Compliant, Identifiable (Section 251, Section 251 NHS Act 2006, Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s))

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Section 251 approval is in place for the flow of identifiable data, National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), 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(2)(b)(ii)

Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)

Sensitive: Sensitive

When:DSA runs 2019-03-01 — 2022-02-28 2018.06 — 2020.07.

Access method: Frequent adhoc flow, Frequent Adhoc Flow

Data-controller type: NHS NORTH YORKSHIRE CCG, NHS HUMBER AND NORTH YORKSHIRE ICB - 42D

Sublicensing allowed: No

Datasets:

1. Acute-Local Provider Flows
2. Ambulance-Local Provider Flows
3. Children and Young People Health
4. Community-Local Provider Flows
5. Demand for Service-Local Provider Flows
6. Diagnostic Imaging Dataset
7. Diagnostic Services-Local Provider Flows
8. Emergency Care-Local Provider Flows
9. Experience, Quality and Outcomes-Local Provider Flows
10. Improving Access to Psychological Therapies Data Set
11. Maternity Services Data Set
12. Mental Health and Learning Disabilities Data Set
13. Mental Health Minimum Data Set
14. Mental Health Services Data Set
15. Mental Health-Local Provider Flows
16. National Cancer Waiting Times Monitoring DataSet (CWT)
17. Other Not Elsewhere Classified (NEC)-Local Provider Flows
18. Population Data-Local Provider Flows
19. Primary Care Services-Local Provider Flows
20. Public Health and Screening Services-Local Provider Flows
21. SUS for Commissioners
22. Community Services Data Set
23. Civil Registration - Births
24. Civil Registration - Deaths
25. National Diabetes Audit
26. Patient Reported Outcome Measures
27. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
28. Improving Access to Psychological Therapies Data Set_v1.5
29. Civil Registrations of Death
30. Community Services Data Set (CSDS)
31. Diagnostic Imaging Data Set (DID)
32. Improving Access to Psychological Therapies (IAPT) v1.5
33. Mental Health and Learning Disabilities Data Set (MHLDDS)
34. Mental Health Minimum Data Set (MHMDS)
35. Mental Health Services Data Set (MHSDS)
36. Patient Reported Outcome Measures (PROMs)

Objectives:

Invoice Validation
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so they are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets and will not be used further.
The legal basis for this to occur is under Section 251 of NHS Act 2006.
Invoice Validation with be conducted by North of England CSU
The CCG are advised by North of England CSU whether payment for invoices can be made or not.

Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
The legal basis for this to occur is under Section 251 of NHS Act 2006 (CAG 7-04(a)).
Risk Stratification will be conducted by eMBED

Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Diagnostic Imaging Data Set (DIDS)
The pseudonymised data is required to for the following purposes:
§ Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
§ Data Quality and Validation – allowing data quality checks on the submitted data
§ Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
§ Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
§ Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
§ Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
§ Service redesign
§ Health Needs Assessment – identification of underlying disease prevalence within the local population
§ Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models

The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by North of England CSU, Scarborough and Ryedale CCG (Partnership Commissioning Unit) & eMBED

Yielded Benefits:

Expected Benefits:

Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care

Risk Stratification
Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised:
1. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services thus allowing early intervention.
3. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
4. Supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework by allowing for more targeted intervention in primary care.
5. Better understanding of local population characteristics through analysis of their health and healthcare outcomes
All of the above lead to improved patient experience through more effective commissioning of services.

Commissioning
1. 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.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Financial and 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.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.

Outputs:

Invoice Validation
1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events

Risk Stratification
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
3. Record level output will be available for commissioners (of the CCG), pseudonymised at patient level.
4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
5. The CCG will be able to target specific patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions. The CCG will also be able to:
o Stratify populations based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost
o Plan work for commissioning services and contracts
o Set up capitated budgets
o Identify health determinants of risk of admission to hospital, or other adverse care outcomes.

Commissioning
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of acute / community / mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports include high flyers.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o Most expensive patients (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community

Data Processor 3 –Scarborough and Ryedale CCG (Partnership Commissioning Unit)
The PCU produces a number of reports which provide a summary (aggregated with small numbers suppressed) which are shared back to the CCG, the following are a list of these:

IAPT Dataset

Mandated national contract KPIs:
Completion of IAPT Minimum Data Set outcome data
IAPT Access Times – 6 & 18 wk (finished treatment)

Local CCG and NHSE information and KPIs:
Number of Referrals
Number Entering Treatment
Monthly Prevalence rate
Number completing treatment
Number moving to recovery
Number not at caseness
Monthly Recovery rate
Reliable Improvement rate
IAPT Access Times – 6 & 18 wk (entering treatment)
Waiting times for treatment and those still waiting
Clearance times

Local CCG monitoring:
Appointments, cancellations and DNA rate analysis
Data Quality
Referral rates and activity by GP Practice and Age band


Mental Health Dataset

Mandated national contract KPIs :
Completion of valid NHS number field
Completion of Ethnic coding
Under 16 bed days on Adult wards (Never event)

Local CCG and NHSE information and KPIs:
Gatekeeping admissions
7 day follow-up hospital discharges
EIP access rates
Eating disorders

Local CCG monitoring:
Referral rates by GP Practice and Age band
CPA monitoring inc settled accommodation and employment
CPA reviews within 12 months, step up/down etc
Bed days, admissions and discharges
Delayed discharges
Detentions
LD/ MH/CAMHS ward stays
Bed locality (distance out of area)
Contacts and DNA rates
Cluster monitoring and red rules
Data quality

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.

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

The Data Controller and any Data Processor will only have access to records of patients of residence and registration within the CCG.

Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data.
All access to data is managed under Roles-Based Access Controls
No patient level data will be linked other than as specifically detailed within this agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality and that data required by the applicant.
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 DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data for the purpose of risk stratification leaves the DSCRO.
CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools.

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.

All access to data is auditable by NHS Digital.

Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors.

Invoice Validation

1. Identifiable SUS+ Data is obtained from the SUS+ Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the North of England CSU.
3. The CSU carry out the following processing activities within the CEfF for invoice validation purposes:
a. Validating that the Clinical Commissioning Group is responsible for payment for the care of the individual by using SUS+ and/or backing flow data.
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance. 
4. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between North of England CSU CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.

Risk Stratification

On 20th July 2017, North of England CSU ceased to deliver risk stratification. eMBED is the sole Data Processor for Risk Stratification.
1. Identifiable SUS+ data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to eMBED ,who hold the SUS+ data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to eMBED.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once eMBED has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.

Commissioning
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS+
2. Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Demand for Service
e. Diagnostic Service
f. Emergency Care
g. Experience, Quality and Outcomes
h. Mental Health
i. Other Not Elsewhere Classified
j. Population Data
k. Primary Care Services
l. Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Maternity Services Data Set (MSDS)
7. Improving Access to Psychological Therapy (IAPT)
8. Child and Young People Health Service (CYPHS)
9. Diagnostic Imaging Data Set (DIDS)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:

Data Processor 1 and 2 – North of England Commissioning Support Unit and eMBED Health Consortium
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to North of England Commissioning Support Unit.
2. North of England Commissioning Support Unit then pass the processed, pseudonymised data to both eMBED Health Consortium and the CCG.
3. eMBED Health Consortium add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
4. Allowed linkage is between the data sets contained within point 1.
5. eMBED Health Consortium then pass the processed, pseudonymised and linked data to the CCG.
6. The CCG analyse the data received from eMBED Health Consortium and North of England Commissioning Support Unit to see patient journeys for pathways or service design, re-design and de-commissioning.
7. Aggregation of required data for CCG management use will be completed by North of England Commissioning Support Unit, eMBED Health Consortium or the CCG as instructed by the CCG.
8. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.
9. The CCG securely transfer Pseudonymised data back to the provider to:
a) confirm how patients are reported in SUS, and how the commissioner can reliably group these patients into categories for points of delivery;
b) allow for granular data validation whereby a commissioner may query the SUS record, and need to pass it back to the provider for checking; and
c) to allow the provider to undertake further analysis of a cohort of their patients as requested and specified by the commissioner.

The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider.

Data Processor 3 –Scarborough and Ryedale CCG Partnership Commissioning Unit

1. North of England and Yorkshire Data Services for Commissioners Regional Office (DSCRO) receives a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) for commissioning purposes and only is securely transferred from the DSCRO to North of England CSU
2. North of England CSU add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
3. Allowed linkage is between the data sets contained within point 1.
4. North of England CSU then pass the processed, pseudonymised and linked data to the Partnership Commissioning Unit (PCU), hosted by Scarborough and Ryedale CCG.
5. The PCU utilises the data for monitoring for the CCGs supported by the PCU against their contracts and national standards. They also monitor the provider data against NHS England reports and NHS Digital data to be able to, challenge and areas of issue/mistake by using the data sets and monitor data quality. Analysis is provided on lower level practice reporting and monitoring, age profiling, early intervention reporting, and unify submission commissioner return, seven day follow ups and crisis gate keeping. There is no linkage with SUS data other what is stated above within the application which takes place to give a complete patient pathway analysis. Only substantive employees have access to the data.
6. Aggregation of required data for CCG management use will be completed by North of England CSU or the CCG as instructed by the CCG.
7. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.

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Project 3 — NIC-90691-W4B6F

Type of data: information not disclosed for TRE projects

Opt outs honoured: N, Y

Legal basis: Health and Social Care Act 2012, Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Sensitive

When:2017.06 — 2017.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

1. Local Provider Data - Acute
2. Local Provider Data - Ambulance
3. Local Provider Data - Community
4. Local Provider Data - Demand for Service
5. Local Provider Data - Diagnostic Services
6. Local Provider Data - Emergency Care
7. Local Provider Data - Experience Quality and Outcomes
8. Local Provider Data - Mental Health
9. Local Provider Data - Other not elsewhere classified
10. Local Provider Data - Population Data
11. Local Provider Data - Primary Care
12. Mental Health and Learning Disabilities Data Set
13. Mental Health Minimum Data Set
14. Mental Health Services Data Set
15. SUS Accident & Emergency data
16. SUS Admitted Patient Care data
17. SUS Outpatient data
18. Children and Young People's Health Services Data Set
19. Improving Access to Psychological Therapies Data Set
20. Maternity Services Dataset
21. SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)

Objectives:

Invoice Validation
As an approved Controlled Environment for Finance (CEfF), North of England CSU receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (c)/2013, to undertake invoice validation on behalf of the CCG. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. The CCG are advised by the CSU whether payment for invoices can be made or not.

Risk Stratification
To use SUS data identifiable at the level of NHS number according to S.251 CAG 7-04(a)/2013 (and Primary Care Data) for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users. Risk Stratification enables GPs to better target intervention in Primary Care.

Commissioning (Pseudonymised) – SUS and Local Flows
To use pseudonymised data to provide intelligence to support commissioning of health services. The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.

Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS
To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services :
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Diagnostic Imaging Data Set (DIDS)
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.

Expected Benefits:

Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care

Risk Stratification
Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised:
1. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
3. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
4. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
5. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
All of the above lead to improved patient experience through more effective commissioning of services.


Commissioning (Pseudonymised) – SUS and Local Flows
1. 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.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows.
4. Commissioning cycle support for grouping and re-costing previous activity.
5. 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.
j. Service Transformation Projects (STP)

6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.

Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS
1. 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.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. 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.
4. Commissioning cycle support for grouping and re-costing previous activity.
5. 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.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.

Outputs:

Invoice Validation
1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events

Risk Stratification
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
3. Record level output will be available for commissioners pseudonymised at patient level and aggregate with small number suppression.
4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.

Commissioning (Pseudonymised) – SUS and Local Flows
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals POD.
e. Planned care by POD view – activity, finance plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of acute / community / mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports include frequent flyers.
9. Mortality
10. Quality
11. Service utilisation reporting
12. Patient safety indicators
13. Production of reports and dash boards to support service redesign and pathway changes

Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports include frequent flyers.

Data Processor 3 –Scarborough and Ryedale CCG (Partnership Commissioning Unit)
The PCU produces a number of reports which provide a summary (aggregated with small numbers suppressed) which are shared back to the CCG, the following are a list of these:

IAPT Dataset

Mandated national contract KPIs:
Completion of IAPT Minimum Data Set outcome data
IAPT Access Times – 6 & 18 wk (finished treatment)

Local CCG and NHSE information and KPIs:
Number of Referrals
Number Entering Treatment
Monthly Prevalence rate
Number completing treatment
Number moving to recovery
Number not at caseness
Monthly Recovery rate
Reliable Improvement rate
IAPT Access Times – 6 & 18 wk (entering treatment)
Waiting times for treatment and those still waiting
Clearance times

Local CCG monitoring:
Appointments, cancellations and DNA rate analysis
Data Quality
Referral rates and activity by GP Practice and Age band


Mental Health Dataset

Mandated national contract KPIs :
Completion of valid NHS number field
Completion of Ethnic coding
Under 16 bed days on Adult wards (Never event)

Local CCG and NHSE information and KPIs:
Gatekeeping admissions
7 day follow-up hospital discharges
EIP access rates
Eating disorders

Local CCG monitoring:
Referral rates by GP Practice and Age band
CPA monitoring inc settled accommodation and employment
CPA reviews within 12 months, step up/down etc
Bed days, admissions and discharges
Delayed discharges
Detentions
LD/ MH/CAMHS ward stays
Bed locality (distance out of area)
Contacts and DNA rates
Cluster monitoring and red rules
Data quality

Processing:

Invoice Validation

SUS Data is obtained from the SUS Repository to DSCRO.
1. DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the North of England CSU.
2. The CSU carry out the following processing activities within the CEfF for invoice validation purposes:
a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the SUS data flow to validate the corresponding record in the backing data flow
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance. 
3. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between the CSU CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.



Risk Stratification
Data Processor 1 - North England CSU
1. Identifiable SUS data is obtained from the SUS Repository to Yorkshire Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by DSCRO and the data identifiable at the level of NHS number is transferred securely to North of England CSU, who hold the SUS data within the secure NECS network storage.
3. Identifiable GP Data is securely sent from the GP system to North of England CSU.
4. SUS data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier derived from SUS available to GPs is the NHS numbers of their own patients. Any further identification of the patients is derived from the GP data sourced from their own systems.
6. North of England CSU who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
7. Once North of England CSU has completed the processing, the CCG can access the online system via a secure network connection to access the data pseudonymised at patient level.
On or before 20th July 2017, this data processor will cease to deliver risks stratification, at which point a data destruction certificate will be completed. eMBED will the sole Data Processor for Risk Stratification. eMBED will run adjacently to NECS until NECS ceases.

Data Processor 2 - eMBED
1. Identifiable SUS data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to eMBED, who hold the SUS data within eMBED secure storage.
3. Identifiable GP Data is securely sent from the GP system to eMBED.
4. SUS data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier derived from SUS available to GPs is the NHS number of their own patients. Any further identification of the patients is derived from the GP data sourced from their own systems.
6. eMBED who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
7. Once eMBED has completed the processing, the CCG can access the online system via a secure network connection to access the data pseudonymised at patient level.

Commissioning (Pseudonymised) – SUS and Local Flows
Data Processor 2 - eMBED
1. Yorkshire Data Services for Commissioners Regional Office / North England Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. Yorkshire / North of England DSCRO also obtains identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North of England CSU for the addition of derived fields and analysis.
3. North of England CSU then pass the processed, pseudonymised data to both eMBED and the CCG.
4. eMBED receives the Pseudonymised data for the addition of derived fields, linkage of data sets and analysis. Linked data is limited to the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning:

- SUS data and Local Provider data at pseudonymised level
- Mental Health (MHSDS, MHLDDS, MHMDS) with SUS
- Improving Access to Psychological Therapies (IAPT) with SUS
- Diagnostic Imaging Dataset (DIDs) with SUS
- Maternity (MSDS) with SUS
- Children and Young People’s Health Services (CYPHS) with Local provider data
- Mental Health (MHSDS, MHLDDS, MHMDS) with Local provider data
- Improving Access to Psychological Therapies (IAPT) with Local provider data
- Diagnostic Imaging Dataset (DIDs) with Local provider data
- Maternity (MSDS) with Local provider data
- Children and Young People’s Health Services (CYPHS) with Local provider data

5. eMBED securely transfer pseudonymised outputs for management use by the CCG.
6. The CCG receive Pseudonymised data from both North of England CSU and eMBED. The CCG then analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
7. Aggregation of required data for CCG management use will be completed by the North of England CSU, eMBED or the CCG as instructed by the CCG.
8. data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared.
9. The CCG securely transfer Pseudonymised data back to the provider to:
a) confirm how patients are reported in SUS, and how the commissioner can reliably group these patients into categories for points of delivery;
b) allow for granular data validation whereby a commissioner may query the SUS record, and need to pass it back to the provider for checking; and
c) to allow the provider to undertake further analysis of a cohort of their patients as requested and specified by the commissioner.

The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider.

Commissioning (Pseudonymised) – Mental Health, MSDS, IAPT, CYPHS and DIDS
1. North of England Data Services for Commissioners Regional Office (DSCRO) and Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtain a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, and MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management, minimisation and pseudonymisation of data is completed by North of England and DSCRO and the pseudonymised data is then passed securely to North of England CSU.
3. North of England CSU then securely transfer the processed, pseudonymised and linked data to eMBED.
4. eMBED receives the data from North of England CSU and carries out further data processing, addition of derived fields, linkage to other data sets and analysis. Linked data would include the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning:
- Mental Health (MHSDS, MHLDDS, MHMDS) with IAPT
- Mental Health (MHSDS, MHLDDS, MHMDS) with SUS
- Improving Access to Psychological Therapies (IAPT) with SUS
- Diagnostic Imaging Dataset (DIDs) with SUS
- Maternity (MSDS) with SUS
- Children and Young People’s Health Services (CYPHS) with SUS
5. Aggregation of required data for CCG management use is completed by eMBED or the CCG as instructed by the CCG.
6. Data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared.

Data Processor 3 –Scarborough and Ryedale CCG (Partnership Commissioning Unit)
1. North of England and Yorkshire Data Services for Commissioners Regional Office (DSCRO) receives a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) for commissioning purposes.
2. Data quality management and pseudonymisation of data is completed by DSCRO and the pseudonymised data is then passed securely to North of England CSU for the addition of derived fields, linkage of data sets and analysis.
3. North of England CSU then passes the processed, pseudonymised and linked data to the Partnership Commissioning Unit (PCU), hosted by Scarborough and Ryedale CCG.
4. The PCU utilises the data for monitoring for the CCGs supported by the PCU against their contracts and national standards. They also monitor the provider data against NHS England reports and NHS Digital data to be able to, challenge and areas of issue/mistake by using the data sets and monitor data quality.
Analysis is provided on lower level practice reporting and monitoring, age profiling, early intervention reporting, and unify submission commissioner return, seven day follow ups and crisis gate keeping.
There is no linkage with SUS data other what is stated above within the application which takes place to give a complete patient pathway analysis. Only substantive employees have access to the data.
5. Aggregated reports only with small number suppression in line with the HES analysis guide are shared with the CCG from the PCU.

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Project 4 — NIC-21865-P5N6D

Type of data: information not disclosed for TRE projects

Opt outs honoured: N

Legal basis: Health and Social Care Act 2012

Purposes: ()

Sensitive: Sensitive

When:2016.12 — 2017.02.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

1. Mental Health Minimum Data Set
2. Mental Health and Learning Disabilities Data Set
3. Mental Health Services Data Set
4. Improving Access to Psychological Therapies Data Set
5. Children and Young People's Health Services Data Set

Objectives:

To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services:
• Mental Health Minimum Data Set (MHMDS)
• Mental Health Learning Disability Data Set (MHLDDS)
• Mental Health Services Data Set (MHSDS)
• Improving Access to Psychological Therapy (IAPT)
• Children and Young People’s Health (CYPHS)

The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.

Expected Benefits:

1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, Integrated Care and pathways.
a. Analysis to support full business cases.
b. Development of business models.
c. Monitoring In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. 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.

Outputs:

As a result of the aforementioned processing activities, eMBED will provide a number of outputs which are securely provided to the CCGs in the appropriate format at pseudonymised level.
Where datasets have been linked, the CCG will receive the outputs of analysis instead of the direct data, however it may also be necessary to provide linked data at row level to CCGs (pseudonymised record level data).
eMBED will provide aggregated reports only with small number suppression to CCG’s stakeholders e.g. GP practices, Local Authorities. Where such data is provided there are safeguards in place to ensure that the receiving organisation has recognised the required safety controls required, i.e. signed agreements from the receiving organisation regarding compliance with data protection and the agreed use of the data.
eMBED will flow outputs, mostly in the form of reports to the CCG stakeholders. CCGs may also provide their stakeholders with the anonymised outputs. The anonymisation will be achieved by aggregating records and using small number suppression in line with HES analysis guidance.
eMBED provides a range of Business Intelligence functions and outputs as specified by the CCG. These outputs can be presented in a variety of different ways to a variety of different users, from highly aggregated graphical “dashboards” to very low-level tabular analysis, and everything in between with the opportunity to drill-down into the detail. Provision of aggregated reports only with small number suppression data to CCG stakeholders allows for analysis at an appropriate level, revealing potentially useful but previously unrecognised commissioning insights/trends whilst mitigating against the risk of re-identification of individuals
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports including high flyers.
The PCU produces a number of reports which provide a summary (not patient level data) which are shared back to the CCG, the following are a list of these:
IAPT Dataset

Mandated national contract KPIs:
Completion of IAPT Minimum Data Set outcome data
IAPT Access Times – 6 & 18 wk (finished treatment)

Local CCG and NHSE information and KPIs:
Number of Referrals
Number Entering Treatment
Monthly Prevalence rate
Number completing treatment
Number moving to recovery
Number not at caseness
Monthly Recovery rate
Reliable Improvement rate
IAPT Access Times – 6 & 18 wk (entering treatment)
Waiting times for treatment and those still waiting
Clearance times


Local CCG monitoring:
Appointments, cancellations and DNA rate analysis
Data Quality
Referral rates and activity by GP Practice and Age band

Mental Health Dataset

Mandated national contract KPIs :
Completion of valid NHS number field
Completion of Ethnic coding
Under 16 bed days on Adult wards (Never event)

Local CCG and NHSE information and KPIs:
Gatekeeping admissions
7 day follow-up hospital discharges
EIP access rates
Eating disorders

Local CCG monitoring:
Referral rates by GP Practice and Age band
CPA monitoring inc settled accommodation and employment
CPA reviews within 12 months, step up/down etc
Bed days, admissions and discharges
Delayed discharges
Detentions
LD/ MH/CAMHS ward stays
Bed locality (distance out of area)
Contacts and DNA rates
Cluster monitoring and red rules
Data quality

The PCU will also share aggregated reports only with small number suppression back to the provider.
The PCU shares aggregated reports only with small number suppression outputs with NHS England for national reporting and to support any issues that need rising in relation to data quality.

Processing:

1. North of England Data Services for Commissioners Regional Office (DSCRO) and Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtain a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, and MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management, minimisation and pseudonymisation of data is completed by North of England and Yorkshire DSCRO and the pseudonymised data is then passed securely to North of England CSU.
3. North of England CSU then securely transfer the processed, pseudonymised and linked data to eMBED.
4. eMBED receives the data from North of England CSU and carries out further data processing, addition of derived fields, linkage to other data sets and analysis. Linked data would include the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning:
• Mental Health (MHSDS, MHLDDS, MHMDS) with IAPT
• Mental Health (MHSDS, MHLDDS, MHMDS) with SUS
• Improving Access to Psychological Therapies (IAPT) with SUS
• Diagnostic Imaging Dataset (DIDs) with SUS
• Maternity (MSDS) with SUS
• Children and Young People’s Health Services (CYPHS) with SUS
5. Aggregation of required data for CCG management use is completed by eMBED or the CCG as instructed by the CCG.
6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared.

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Project 5 — NIC-36253-D9W8D

Type of data: information not disclosed for TRE projects

Opt outs honoured: Y

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

Purposes: ()

Sensitive: Sensitive

When:2016.12 — 2017.02.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

1. SUS (Accident & Emergency, Inpatient and Outpatient data)

Objectives:

To utilise SUS data identifiable at the level of NHS number to provide risk stratification information to the CCG and GP practice.

Expected Benefits:

Risk Stratification promotes improved case management in primary care which is expected to lead to the following benefits being realised :
1. Improved planning by better understanding the patient flows through the healthcare system, thus allowing GPs and clinicians to design appropriate pathways to improve patient flow and identify plans to address these.

2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved via the mapping of frequent users of emergency services and the early intervention of appropriate care.

3. Improved access to services by identifying which services may be in demand but have poor access and from this identify areas where improvement is required.

4. Potentially reduce premature mortality by more targeted intervention in primary care, which supports the commissioner to meet its requirement to reduce premature mortality in line with the CCG Outcome Framework.

It is expected that all of the aforementioned will lead to improved patient experience through more effective direct patient care services.

Outputs:

To provide risk profiling, calculated on activity data from secondary, urgent and primary care. As part of the risk stratification processing activity detailed above, the GP practice has access to the RAIDR tool for reports which present to them their registered patients and associated risk score.
The only identifier to be provided to the GP practice is the NHS number of their registered patient (for their own patients only).
The GP practice can access the RAIDR tool, which is a secure portal, at any time which will support MDT (multi-disciplinary team) discussions around ongoing patient care.
The GP practice can copy and paste the NHS number presented in the secure web-portal to any other program including the practice clinical system.
CCG staff who have been granted access to the RAIDR tool can only access aggregate output / reports.
No record-level SUS is provided to any other organisation.

Processing:

Processing of SUS Data for the purposes of Risk Stratification includes landing, processing, staging and publication.
1. Landing
A local flow of identifiable urgent care data is submitted from healthcare providers to DSCRO North of England. DSCRO North of England transfer the local provider urgent care data identifiable at the level of NHS number to NECS using a secure file transfer process and the urgent care data is landed in secure NECS network storage.
Prior to the release of SUS data by DSCRO North England, Type 2 objections will be applied and the relevant patients data redacted. DSCRO North of England securely transfer SUS data identifiable at the level of NHS number to North of England Commissioning Support Unit (NECS). This is done by landing the SUS data in secure NECS network storage. Data is landed and processed in an access restricted server at NECS.
Primary care data identifiable at the level of NHS number is extracted from GP clinical systems and downloaded to secure NECS network storage – all patient objections are handled at the point of data extraction with no identifiable data flowing where patients have a relevant dissent code (these include both type 1 and 2 as well as local system codes).
Only named individuals have access to process the data. All users undertake regular IG training, in line with IGT requirements.
2. Processing (ETL)
Data is processed on a monthly basis, which follows NECS ETL (Extract, Transform and Load) process as follows.
2.1. Cleaning and quality checks are carried out on the data.
2.2. The primary care, and SUS & urgent care local provider data are combined using NHS number to link the data and the data is processed to create a risk stratification data set
2.3. The urgent care data is linked to primary care data to calculate a risk score for each admission/attendance.

3. Staging
Data is landed to a secure NECS staging area for final quality checks.
4. Publication
Outputs are available to the CCG and the GP practice via the RAIDR tool which has a secure web-portal for accessing the data. All usage of its tools is audited.
Access to the RAIDR tool is via individual usernames and passwords.
Data identifiable at the level of NHS number is only available to named individuals within the GP practice who have a legitimate relationship with the patient or where an individual working within a GP practice has the authorisation of a senior individual - such as senior partner or business manager within the practice - to access data identifiable at the level of NHS number for the purposes of conducting Risk Stratification for case finding. This is only applies where there is a legitimate relationship with the patient for direct patient care. (For example, staff such as community/practice nurses who work as part of a multi-disciplinary team with the GPs.)
The CCG has an aggregated view only of Risk Stratification data based on their related GP practices. No record-level SUS data identifiable at the level of NHS number is provided to any other organisation.

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Project 6 — NIC-60449-S4F7K

Type of data: information not disclosed for TRE projects

Opt outs honoured: N

Legal basis: Health and Social Care Act 2012

Purposes: ()

Sensitive: Sensitive

When:2016.12 — 2017.02.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

1. SUS (Accident & Emergency, Inpatient and Outpatient data)
2. Local Provider Data - Acute, Ambulance, Community, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Mental Health, Other not elsewhere classified, Population Data, Primary Care

Objectives:

SUS and Local Provider Data - The CCG recognises that good information and intelligence is crucial for the commissioning of high quality and safe services leading to better outcomes for the populations they serve. This application supports this objective.
This arrangement was previously agreed to facilitate the transfer of Commissioning Support Services, from Yorkshire & Humber Commissioning Support Unit (Y&H CSU), who previously held ASH status and served the CCGs, to North England CSU (NECS), and eMBED Health Consortium, for ongoing provision in line with the NHS England Lead Provider Framework (LPF).

Data Processor 1 - NECS is a commissioning support unit that had been working with the CCG for some time.
Data Processor 2 - eMBED was appointed in March 2016 to continue the operations of the Yorkshire and Humber CSU; Kier Business Services Limited, with additional Business Intelligence work carried out under contract by Dr Foster Ltd.
Kier Business Services are the prime partner for the LPF within the eMBED Health Consortium. Both organisations (Kier Business Services and Dr Foster Ltd) are a legal entity in their own right. Dr Foster Ltd are subcontracted to Kier Business Services for the delivery of eMBED Health Consortium services.

Expected Benefits:

1. 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.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. 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.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.

Outputs:

1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of acute / community / mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports include high flyers.
9. Monitoring of hospital activity against planned levels where an established contract exists between a provider and a commissioner inclusive of:
o Overall contract reporting of actual vs plan for activity and value at aggregate level
o Reconciliation reports between local hospital data, and SUS records at aggregate level.
o Contract Data Quality reporting at anonymised in context record level.
10. QIPP scheme analysis at aggregate level
11. Monitoring of SUS based CCG Outcome Framework indicators at aggregate level with small number suppression.
12. “Deep dive” analysis of hospital activity at aggregate level.
13. Cross CCG benchmarking at aggregate level.
14. Provision of aggregate reports with small number suppression activity data to CCGs’ stakeholders e.g. Health and Wellbeing Boards where the CCG have agreed to this

Processing:

1. Yorkshire Data Services for Commissioners Regional Office / North England Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. Yorkshire / North England DSCRO also obtains identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North of England CSU for the addition of derived fields and analysis.
3. North of England CSU then pass the processed, pseudonymised data to both eMBED and the CCG.
4. eMBED receives the Pseudonymised data for the addition of derived fields, linkage of data sets and analysis. Linked data is limited to the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning:

- SUS data and Local Provider data at pseudonymised level
- Mental Health (MHSDS, MHLDDS, MHMDS) with SUS
- Improving Access to Psychological Therapies (IAPT) with SUS
- Diagnostic Imaging Dataset (DIDs) with SUS
- Maternity (MSDS) with SUS
- Children and Young People’s Health Services (CYPHS) with Local provider data
- Mental Health (MHSDS, MHLDDS, MHMDS) with Local provider data
- Improving Access to Psychological Therapies (IAPT) with Local provider data
- Diagnostic Imaging Dataset (DIDs) with Local provider data
- Maternity (MSDS) with Local provider data
- Children and Young People’s Health Services (CYPHS) with Local provider data

5. eMBED securely transfer pseudonymised outputs for management use by the CCG.
6. The CCG receive Pseudonymised data from both North of England CSU and eMBED. The CCG then analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
7. Aggregation of required data for CCG management use will be completed by the CSU, eMBED or the CCG as instructed by the CCG.
8. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared where contractual arrangements are in place.
9. The CCG securely transfer Pseudonymised data back to the provider to:
a) confirm how patients are reported in SUS, and how the commissioner can reliably group these patients into categories for points of delivery;
b) allow for granular data validation whereby a commissioner may query the SUS record, and need to pass it back to the provider for checking; and
c) to allow the provider to undertake further analysis of a cohort of their patients as requested and specified by the commissioner.
The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider.

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