NHS Digital Data Release Register - reformatted

NHS Calderdale CCG projects

• GDPPR COVID-19 – CCG - Pseudo
• DSfC - NHS Calderdale CCG; RS, IV & Comm.
• DSfC - NHS Calderdale, GH & NK CCGs - STP - Comm
• Project 4
• Project 5
• Project 6
• Project 7
• Project 8
• Project 9
• Project 10

1475 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).

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🚩 NHS Calderdale CCG was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Calderdale 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.

GDPPR COVID-19 – CCG - Pseudo — DARS-NIC-384582-F4X9R

Type of data: information not disclosed for TRE projects

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

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

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

Sensitive: Sensitive

When:DSA runs 2020-07-01 — 2021-03-31 2021.01 — 2021.05.

Access method: One-Off, Frequent Adhoc Flow

Data-controller type: NHS CALDERDALE CCG, NHS WEST YORKSHIRE ICB - 02T

Sublicensing allowed: No

Datasets:

1. GPES Data for Pandemic Planning and Research (COVID-19)
2. COVID-19 Ethnic Category Data Set
3. COVID-19 Vaccination Status
4. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)

Objectives:

NHS Digital has been provided with the necessary powers to support the Secretary of State’s response to COVID-19 under the COVID-19 Public Health Directions 2020 (COVID-19 Directions) and support various COVID-19 purposes, the data shared under this agreement can be used for these specified purposes except where they would require the reidentification of individuals.

GPES data for pandemic planning and research (GDPPR COVID 19)
To support the response to the outbreak, NHS Digital has been legally directed to collect and analyse healthcare information about patients from their GP record for the duration of the COVID-19 emergency period under the COVID-19 Directions.
The data which NHS Digital has collected and is providing under this agreement includes coded health data, which is held in a patient’s GP record, such as details of:
• diagnoses and findings
• medications and other prescribed items
• investigations, tests and results
• treatments and outcomes
• vaccinations and immunisations

Details of any sensitive SNOMED codes included in the GDPPR data set can be found in the Reference Data and GDPPR COVID 19 user guides hosted on the NHS Digital website. SNOMED codes are included in GDPPR data.
There are no free text record entries in the data.

The Controller will use the pseudonymised GDPPR COVID 19 data to provide intelligence to support their local response to the COVID-19 emergency. The data is analysed so that health care provision can be planned to support the needs of the population within the CCG area for the COVID-19 purposes.

Such uses of the data include but are not limited to:

• Analysis of missed appointments - Analysis of local missed/delayed referrals due to the COVID-19 crisis to estimate the potential impact and to estimate when ‘normal’ health and care services may resume, linked to Paragraph 2.2.3 of the COVID-19 Directions.

• Patient risk stratification and predictive modelling - to highlight patients at risk of requiring hospital admission due to COVID-19, computed using algorithms executed against linked de-identified data, and identification of future service delivery models linked to Paragraph 2.2.2 of the COVID-19 Directions. As with all risk stratification, this would lead to the identification of the characteristics of a cohort that could subsequently, and separately, be used to identify individuals for intervention. However the identification of individuals will not be done as part of this data sharing agreement, and the data shared under this agreement will not be reidentified.

• Resource Allocation - In order to assess system wide impact of COVID-19, the GDPPR COVID 19 data will allow reallocation of resources to the worst hit localities using their expertise in scenario planning, clinical impact and assessment of workforce needs, linked to Paragraph 2.2.4 of the COVID-19 Directions:

The data may only be linked by the Data Controller or their respective Data Processor, to other pseudonymised datasets which it holds under a current data sharing agreement only where such data is provided for the purposes of general commissioning by NHS Digital. The Health Service Control of Patient Information Regulations (COPI) will also apply to any data linked to the GDPPR data.
The linked data may only be used for purposes stipulated within this agreement and may only be held and used whilst both data sharing agreements are live and in date. Using the linked data for any other purposes, including non-COVID-19 purposes would be considered a breach of this agreement. Reidentification of individuals is not permitted under this DSA.

LEGAL BASIS FOR PROCESSING DATA:
Legal Basis for NHS Digital to Disseminate the Data:
NHS Digital is able to disseminate data with the Recipients for the agreed purposes under a notice issued to NHS Digital by the Secretary of State for Health and Social Care under Regulation 3(4) of the Health Service Control of Patient Information Regulations (COPI) dated 17 March 2020 (the NHSD COPI Notice).
The Recipients are health organisations covered by Regulation 3(3) of COPI and the agreed purposes (paragraphs 2.2.2-2.2.4 of the COVID-19 Directions, as stated below in section 5a) for which the disseminated data is being shared are covered by Regulation 3(1) of COPI.

Under the Health and Social Care Act, NHS Digital is relying on section 261(5)(d) – necessary or expedient to share the disseminated data with the Recipients for the agreed purposes.


Legal Basis for Processing:
The Recipients are able to receive and process the disseminated data under a notice issued to the Recipients by the Secretary of State for Health and Social Care under Regulation 3(4) of COPI dated 20th March (the Recipient COPI Notice section 2).

The Secretary of State has issued notices under the Health Service Control of Patient Information Regulations 2002 requiring the following organisations to process information:

Health organisations

“Health Organisations” defined below under Regulation 3(3) of COPI includes CCGs for the reasons explained below. These are clinically led statutory NHS bodies responsible for the planning and commissioning of health care services for their local area

The Secretary of State for Health and Social Care has issued NHS Digital with a Notice under Regulation 3(4) of the National Health Service (Control of Patient Information Regulations) 2002 (COPI) to require NHS Digital to share confidential patient information with organisations permitted to process confidential information under Regulation 3(3) of COPI. These include:

• persons employed or engaged for the purposes of the health service

Under Section 26 of the Health and Social Care Act 2012, CCG’s have a duty to provide and manage health services for the population.

Regulation 7 of COPI includes certain limitations. The request has considered these limitations, considering data minimisation, access controls and technical and organisational measures.

Under GDPR, the Recipients can rely on Article 6(1)(c) – Legal Obligation to receive and process the Disclosed Data from NHS Digital for the Agreed Purposes under the Recipient COPI Notice. As this is health information and therefore special category personal data the Recipients can also rely on Article 9(2)(h) – preventative or occupational medicine and para 6 of Schedule 1 DPA – statutory purpose.

Expected Benefits:

• Manage demand and capacity
• Reallocation of resources
• Bring in additional workforce support
• Assists commissioners to make better decisions to support patients
• Identifying COVID-19 trends and risks to public health
• Enables CCGs to provide guidance and develop policies to respond to the outbreak
• Controlling and helping to prevent the spread of the virus

Outputs:

• Operational planning to predict likely demand on primary, community and acute service for vulnerable patients due to the impact of COVID-19
• Analysis of resource allocation
• Investigating and monitoring the effects of COVID-19
• Patient Stratification in relation to COVID-19, such as:
o Patients at highest risk of admission
o Frail and elderly
o Patients that are currently in hospital
o Patients with prescriptions related to COVID-19
o Patients recently Discharged from hospital
For avoidance of doubt these are pseudonymised patient cohorts, not identifiable.

Processing:

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

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

All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake.

Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement.

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

The Recipients will take all required security measures to protect the disseminated data and they will not generate copies of their cuts of the disseminated data unless this is strictly necessary. Where this is necessary, the Recipients will keep a log of all copies of the disseminated data and who is controlling them and ensure these are updated and destroyed securely.

Onward sharing of patient level data is not permitted under this agreement. Only aggregated reports with small number suppression can be shared externally.

The data disseminated will only be used for COVID-19 GDPPR purposes as described in this DSA, any other purpose is excluded.

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.

AUDIT
All access to data is auditable by NHS Digital in accordance with the Data Sharing Framework Contract and NHS Digital terms.
Under the Local Audit and Accountability Act 2014, section 35, Secretary of State has power to audit all data that has flowed, including under COPI.

DATA MINIMISATION:
Data Minimisation in relation to the data sets listed within the application are listed below:

• Patients who are normally registered and/or resident within the CCG region (including historical activity where the patient was previously registered or resident in another commissioner area).
and/or
• Patients treated by a provider where the CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy.
and/or
• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of the CCG.

The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
- GDPPR COVID 19 Data
Pseudonymisation is completed within the DSCRO and is then disseminated as follows:
1. Pseudonymised GDPPR COVID 19 data is securely transferred from the DSCRO to the Data Controller / Processor
2. Aggregation of required data will be completed by the Controller (or the Processor as instructed by the Controller).
3. Patient level data may not be shared by the Controller (or any of its processors).

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DSfC - NHS Calderdale CCG; RS, IV & Comm. — DARS-NIC-90651-Q8W4T

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - data flow is not identifiable, Yes - patient objections upheld, Anonymised - ICO Code Compliant, Identifiable (Section 251, Mixture of confidential data flow(s) with consent and flow(s) with support under 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), Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

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

Sensitive: Sensitive

When:DSA runs 2019-03-23 — 2022-03-22 2018.06 — 2021.05.

Access method: Frequent adhoc flow, Frequent Adhoc Flow, One-Off

Data-controller type: NHS CALDERDALE CCG, NHS WEST YORKSHIRE ICB - 02T

Sublicensing allowed: No

Datasets:

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

Objectives:

This is a new application for the following purposes:
Invoice Validation
As an approved Controlled Environment for Finance (CEfF), North of England Commissioning Support Unit 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) (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 General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by eMBED.

Commissioning
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.
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 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 eMBED Health Consortium and The Health Informatics Service.

Yielded Benefits:

Yielded benefits include 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 Commissioning 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. Enables monitoring of: a. CCG outcome indicators. b. Financial and Non-financial validation of activity. c. Checking frequent or multiple attendances to improve early intervention and avoid admissions. e. Commissioning and performance management. f. Understanding the care of patients in nursing homes. Expected measurable benefits to health and/or social care including target date: In addition to the existing benefits listed within individual Data Sharing Agreements, the below benefits will be included: • Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed • Insight to understand the numerous factors that play a role in the outcome for both data sets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice. • Births and Mortality data provide some of the best sources of information about the health of the commissioning region, they will provide indicators of health problems, and provide patterns of risk within the commissioner’s region. It also supports valuable bench-marking for evaluating progress in future years.

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
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:

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.

The Health Informatics Service
THIS provides a range of data management functions and outputs as specified by the CCG. Outputs include the provision of pseudonymised data to allow it to be viewed and interrogated, as well as aggregate level reports. These outputs can take the form of data held in a secure data warehouse or files e.g. database, CSV, Excel files.
The warehousing of data uses a robust and tested platform, i.e. the warehouse (HPS database) has been developed over circa 20 years to reflect commissioner/CCG requirements and is in a THIS IT environment, so is secure.
Utilising THIS data management also provides the following benefits:
• Utilising local knowledge and expertise on data flows that are specific to the CCG in particular data flowing from Calderdale and Huddersfield NHS Trust
• Making efficient use of existing processes that are well established and tailored to the CCG requirements
• Providing the resource / capacity required to process data flows for the CCG

The aggregate outputs fall into the following areas:
• Studying variation and trends over time
• Monitoring of healthcare contract activity plans
• Performance monitoring
• Quality monitoring

The categories of outputs to the CCG includes:

• 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/anonymised in context level.
o Contract Data Quality reporting at anonymised in context record level.
• “Deep dive” analysis of hospital activity at aggregate level.
Specific examples of report outputs include:

Commissioner Reporting
- Summary by Provider View – Plan and Actuals Year to Date (YTD)
- Summary by Patient Outcome Data (POD) view - Plan and Actuals YTD
- Summary by Provider View – Activity and Finance Variance by POD
- Planned Care by Provider View – Activity and Finance Variance by POD
- Planned Care by POD View – Activity, Finance Plan and Actuals YTD
- Provider Reporting
- Readmissions analysis
- Production of aggregate reports for CCGs Business Intelligence
- Production of project / programme level dashboards
- Monitoring of acute / community services
- Budget reporting

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. Access is limited to those substantive employees with authorised user accounts used for identification and authentication.

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.

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.

No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.
The DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.


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 Commissioning Support Unit.
3. 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. 
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 Commissioning Support Unit 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
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 Health Consortium 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 Health Consortium.
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. Access to the Risk Stratification system that eMBED Health Consortium hosts is limited to those substantive employees with authorised user accounts used for identification and authentication.
7. Once eMBED Health Consortium has completed the processing, the CCG can access the online system via a secure N3 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)
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
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 – 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 for the addition of derived fields.
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.
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.
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 2 – The Health Informatics Service
1) Pseudonymised SUS only is securely transferred from the DSCRO to North of England Commissioning Support Unit for the addition of derived fields.
2) North of England Commissioning Support Unit then pass the processed, pseudonymised data to both The Health Informatics Service
3) The Health Informatics Service apply business rules, pricing and create additional categorical fields.
4) The Health Informatics Service securely transfer the Pseudonymised data to eMBED Health Consortium to flow directly to the CCG.
5) 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.
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 can be shared.

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DSfC - NHS Calderdale, GH & NK CCGs - STP - Comm — DARS-NIC-192032-K0J3X

Type of data: information not disclosed for TRE projects

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

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

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

Sensitive: Sensitive

When:DSA runs 2019-09-01 — 2022-08-31 2018.10 — 2021.03.

Access method: Frequent Adhoc Flow, One-Off

Data-controller type: NHS CALDERDALE CCG, NHS KIRKLEES CCG, NHS WEST YORKSHIRE ICB - 02T, NHS WEST YORKSHIRE ICB - X2C4Y

Sublicensing allowed: No

Datasets:

1. Acute-Local Provider Flows
2. Ambulance-Local Provider Flows
3. Children and Young People Health
4. Community Services Data Set
5. Community-Local Provider Flows
6. Demand for Service-Local Provider Flows
7. Diagnostic Imaging Dataset
8. Diagnostic Services-Local Provider Flows
9. Emergency Care-Local Provider Flows
10. Experience, Quality and Outcomes-Local Provider Flows
11. Improving Access to Psychological Therapies Data Set
12. Maternity Services Data Set
13. Mental Health and Learning Disabilities Data Set
14. Mental Health Minimum Data Set
15. Mental Health Services Data Set
16. Mental Health-Local Provider Flows
17. National Cancer Waiting Times Monitoring DataSet (CWT)
18. Other Not Elsewhere Classified (NEC)-Local Provider Flows
19. Population Data-Local Provider Flows
20. Primary Care Services-Local Provider Flows
21. Public Health and Screening Services-Local Provider Flows
22. SUS for Commissioners
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:

Commissioning
The NHS and local councils have come together in 44 areas covering all of England to develop proposals to improve health and care. They have formed new partnerships – known as sustainability and transformation partnerships – to plan jointly for the next few years.

Sustainability and transformation partnerships build on collaborative work that began under the NHS Shared Planning Guidance for 2016/17 – 2020/21, to support implementation of the Five Year Forward View. They are supported by six national health and care bodies: NHS England; NHS Improvement; the Care Quality Commission (CQC); Health Education England (HEE); Public Health England (PHE) and the National Institute for Health and Care Excellence (NICE).

The CCGs are part of the West Yorkshire and Harrogate Transformation Partnership. The STP is responsible for implementing large parts of the 5 year forward view from NHS England. The STP is implementing several initiatives:

- Putting the patient at the heart of the health system
- Working across organisational boundaries to deliver care and including social care, Public Health, providers and GPs as well as CCGs
- Reviewing patient pathways to improve patient experience whilst reducing costs e.g. reduce the number of standard tests a patient may have and only have the ones they need
- Planning the demand and capacity across the healthcare system across 3 CCGs to ensure we have the right buildings, services and staff to cope with demand whilst reducing the impact on costs
- Working to prevent or capture conditions early as they are cheaper to treat
- Introduce initiatives to change behaviours e.g. move more care into the community
- Patient pathway planning for the above


To ensure the patient is at the heart of care, the STP is focussing on where services are required across the geographical region. This assists to ensure delivery of care in the right place for patients who may move and change services across CCGs.

The CCGs will work proactively and collaboratively with the other CCGs in the STP to redesign services across boundaries to integrate services. Collaborative sharing is required for CCGs to understand these requirements.

The CCGs will 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 STP 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)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)

The pseudonymised data is required to for the following purposes:
 Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Quality Outcomes for the patients and 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 CCGs area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by North of England Commissioning Support Unit, eMBED Health Consortium and The Health Informatics Service.


The eMBED Health Consortium is made up of 4 partners:
• Kier
• Dr Foster
• BDO
• Engine

Only two of the organisations process and store data. BDO and Engine do not process, store or have access to any data.

Kier make up over 90% of the consortium. Staff from Kier are segregated from the rest of Kier to work on the eMBED contract. Kier process pseudonymised data for the purpose of commissioning.

Dr Foster received pseudonymised data (for the purpose of commissioning), directly from Kier, to conduct further Business Intelligence processing and to produce further reports on behalf of the CCG.

eMBED are not a legal entity, although they do have an IG Toolkit. Kier and Dr Foster are the relevant legal entities hosting the eMBED Health Consortium.

Yielded Benefits:

Expected Benefits:

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. CCGS outcome indicators.
b. Financial and Non-financial validation of activity.
c. Successful delivery of integrated care within the CCGS.
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 CCGS 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.
14. Reviewing current service provision
a. Cost-benefit analysis and service impact assessments to underpin service transformation across health economy
b. Service planning and re-design (development of NMoC and integrated care pathways, new partnerships, working with new providers etc.)
c. Impact analysis for different models or productivity measures, efficiency and experience
d. Service and pathway review
e. Service utilisation review
15. Ensuring compliance with evidence and guidance
a. Testing approaches with evidence and compliance with guidance.
16. Monitoring outcomes
a. Analysis of variation in outcomes across population group
17. Understanding how services impact across the health economy
a. Service evaluation
b. Programme reviews
c. Analysis of productivity, outcomes, experience, plan, targets and actuals
d. Assessing value for money and efficiency gains
e. Understanding impact of services on health inequalities
18. Understanding how services impact on the health of the population and patient cohorts
a. Measuring and assessing improvement in service provision, patient experience & outcomes and the cost to achieve this
b. Propensity matching and scoring
c. Triple aim analysis
19. Understanding future drivers for change across health economy
a. Forecasting health and care needs for population and population cohorts across STPs
b. Identifying changes in disease trends and prevalence
c. Efficiencies that can be gained from procuring services across wider footprints, from new innovations
d. Predictive modelling
20. Delivering services that meet changing needs of population
a. Analysis to support policy development
b. Ethical and equality impact assessments
c. Implementation of NMOC
d. What do next years contracts need to include?
e. Workforce planning
21. Maximising services and outcomes within financial envelopes across health economy
a. What-if analysis
b. Cost-benefit analysis
c. Health economics analysis
d. Scenario planning and modelling
e. Investment and disinvestment in services analysis
f. Opportunity analysis

Outputs:

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 CCGS 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 CCGS 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:
a. Patients at highest risk of admission
b. Most expensive patients (top 15%)
c. Frail and elderly
d. Patients that are currently in hospital
e. Patients with most referrals to secondary care
f. Patients with most emergency activity
g. Patients with most expensive prescriptions
h. Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Profiling population health and wider determinants to identify and target those most in need
a. Understanding population profile and demographics
b. Identify patient cohorts with specific needs or who may benefit from interventions
c. Identifying disease prevalence. health and care needs for population cohorts
d. Contributing to Joint Strategic Needs Assessment (JSNA)
e. Geographical mapping and analysis
14. Identifying and managing preventable and existing conditions
a. Identifying types of individuals and population cohorts at risk of non-elective re-admission
b. Risk stratification to identify populations suitable for case management
c. Risk profiling and predictive modelling
d. Risk stratification for planning services for population cohorts
e. Identification of disease incidence and diagnosis stratification
15. Reducing health inequalities
a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs
b. Socio-demographic analysis
16. Managing demand
a. Waiting times analysis
b. Service demand and supply modelling
c. Understanding cross-border and overseas visitor
d. Winter planning
e. Emergency preparedness, business continuity, recovery and contingency planning
17. Care co-ordination and planning
a. Planning packages of care
b. Service planning
c. Planning care co-ordination
18. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
a. Patient pathway analysis across health and care
b. Outcomes & experience analysis
c. Analysis to support services to react to terror situations
d. Analysis to identify vulnerable patients with potential safeguarding issues
e. Understanding equity of care and unwarranted variation
f. Modelling patient flow
g. Tracking patient pathways
h. Monitoring to support New Models of Care (NMOC), Accountable Care Organisations (ACO), Sustainable Transformation Partnerships (STP)
i. Identifying duplications in care
j. Identifying gaps in care, missed diagnoses and triple fail events
k. Analysing individual and aggregated timelines
19. Undertaking budget planning, management and reporting
a. Tracking financial performance against plans
b. Budget reporting
c. Tariff development
d. Developing and monitoring capitated budgets
e. Developing and monitoring individual-level budgets
f. Future budget planning and forecasting
g. Paying for care of overseas visitors and cross-border flow
20. Monitoring the value for money
a. Service-level costing & comparisons
b. Identification of cost pressures
c. Cost benefit analysis
d. Equity of spend across services and population cohorts
e. Finance impact assessment
21. Comparing population groups, peers, national and international best practice
a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice
b. Benchmarking against other parts of the country
c. Identifying unwarranted variations
22. Comparing expected levels
a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations
23. Comparing local targets & plan
a. Monitoring of local variation in productivity, cost, outcomes, quality and experience
b. Local performance dashboards by service provider, commissioner, geography, NMOC, STPs
24. Monitoring activity and cost compliance against contract and agreed plans
a. Contract monitoring
b. Contract reconciliation and challenge
c. Invoice validation
25. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
a. Performance dashboards
b. CQUIN reporting
c. Clinical audit
d. Patient experience surveys
e. Demand, supply, outcome & experience analysis
f. Monitoring cross-border flows and overseas visitor activity
26. Improving provider data quality
a. Coding audit
b. Data quality validation and review
c. Checking validity of patient identity and commissioner assignment

Processing:

Data must only be used as stipulated within this Data Sharing Agreement.

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

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

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

Patient level data will not be shared outside of the CCGS unless it is for the purpose of Direct Care, where it may be shared only with those 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)

Segregation
Where the Data Processor and/or the Data Controllers 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 Minimisation:
Data Minimisation in relation to the data sets listed within section 3 are listed below. This also includes the purpose on which they would be applied -

For the purpose of Commissioning:
• Patients who are normally registered and/or resident within the commissioner (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where the commissioner is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy – this is only for commissioning and relates to both national and local flows.
and/or
• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of the commissioner - this is only for commissioning and relates to both national and local flows.

The above relates to data requested only (Table 3B). Data currently held (Table 3A) will have the following Data Minimisation:
• CCG of residence and/or registration.

For clarity, any access by Pulsant, Telecity, Yeadon Community Health Centre, Huddersfield Royal Infirmary, Calderdale Royal Hospital and Telstra 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.

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. Community Services Data Set (CSDS)
10. Diagnostic Imaging Data Set (DIDS)
11. National Cancer Waiting Times Monitoring Data Set (CWT)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:

Data Processor 1 & 2 – North of England Commissioning Support Unit & eMBED
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), Community Services Data Set (CSDS). Diagnostic Imaging data (DIDS) and National Cancer Waiting Times Monitoring Data Set (CWT) 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 and the CCG.
3. eMBED add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning (CSU).
b. Check recorded activity against contracts or invoices and facilitate discussions with providers (CSU).
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 then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data 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
6. Aggregation of required data for CCGS management use will be completed by North of England Commissioning Support Unit, Embed 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.

Data Processor 3 The Health Informatics Service
1. Pseudonymised SUS+ 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 The Health Informatics Service.
3. The Health Informatics Service apply business rules, pricing and create additional categorical fields.
4. The Health Informatics Service securely transfer the Pseudonymised data to eMBED to flow directly to the CCG.
5. Aggregation of required data for CCG management use will be completed by The Health Informatics Service 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 can be shared.

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Project 4 — DARS-NIC-83772-T4M1V

Type of data: information not disclosed for TRE projects

Opt outs honoured: N (Section 251)

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

Purposes: ()

Sensitive: Sensitive

When:2018.06 — 2018.09.

Access method: Frequent adhoc flow

Data-controller type:

Sublicensing allowed:

Datasets:

1. Ambulance-Local Provider Flows

Objectives:

Process 1

As part of the vision to introduce new care models that can provide care closer to home, it is critical that Calderdale CCG establish an effective framework to identify and prioritise areas that require transformation. This framework will underpin the approach to securing improved health outcomes for the local population from services that can deliver high quality as well as making the best use of resources.
To achieve this, NECS will support Calderdale CCG to undertake a population segmentation exercise. The population segmentation exercise will include the total registered population of Calderdale and a framework for commissioners to understand the range and scale of health needs and the patterns in the use of health and care resources.
Population segmentation is recognised method to support system transformation. For a comprehensive and robust population exercise to be undertaken, the CCG require pseudonymised SUS data to be linked with GP data.
This analysis will enable the health and care system within the Calderdale region to proceed with the development of new models of care and transform the way the system currently operates, providing a greater focus on the prevention of ill health and empowering individuals and communities to maintain their independence and maximise their health and wellbeing. The analysis will also provide a platform for the health and care system to track progress over time and inform the development of new payment mechanisms associated with new models of care being introduced.

Process 2
Both the Meeting The Challenge (MTC) and Right Care Right Time Right Place (RCRTRP) have both conducted analyses of the potential impact of reconfiguration on the flow of patients, attendances, admissions and bed numbers of the potential changes to service provision proposed in the respective programmes.
This piece of work is to revisit the previous reconfiguration of service provision and model the potential aggregate impact of the two programmes combined. This will include impact on patient flows: attendances, admissions and estimated bed numbers at both Dewsbury and District Hospital (DDH) and Calderdale Royal Hospital (CRH)
Outputs from the project will include a report which will be presented to the Trusts and CCGs outlining the findings of the study, including methodology, calculations and mapping.

No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties named in the Data Sharing Agreement and will only be used for the purposes laid out in the application/agreement. The data to be released from the NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.

Expected Benefits:

Process 1
The principle benefits to health and/or social care include:
• NEEDS - Provide a framework to understand population by need
• Patient Benefit – the availability of an integrated dataset will enable the system to design services and new models of care tailored to meet the specific needs of patient cohorts

• UTILISATION – summarise the patterns in the use of health and care resources and the associated costs
• Patient Benefit – understanding patterns in the use of resources and quantifying its use will allow the system to focus the development of new care models on the needs of the local population, in particular those patients multiple comorbidities who are currently dependent upon episodic unplanned care
• PRIORITISATION - Provide the system with a mechanism to prioritise areas for transformation and the introduction of new care models across the health and care system
• Patient Benefit – using integrated data sets will enable the identification of patient cohorts with most need and will enable the system to develop the appropriate interventions and models of care that can anticipate and meet patient requirements

• BASELINES - Ability to quantify activity and costs to the system, providing baselines and trend analysis
• Patients Benefit – provide the system with the capability to demonstrate the impact on reducing the reliance on episodic unplanned care

• OUTCOMES – provides baselines to track improvements in health outcomes
• Patient Benefit – provide the system with the ability to demonstrate the impact on patients quality of life and their health status as well as the shift from a reliance upon episodic unplanned care to care in the community and closer to home

• NEW MODELS OF CARE – provide a vehicle to support integrated approaches to transformation and the capability to monitor the subsequent impact on health outcomes and resource utilisation
• Patient Benefit – will support the system to develop non hospital based services so that people can maintain their independence as well as their health and wellbeing

• PROVISION – enable clinicians and front line staff to target interventions on specific client groups and provide personalised care
• Patient Benefit – enable the system to develop and align an integrated workforce to meet the multiple needs of the local population, in particular high users of unplanned services

• NEW PAYMENT MODELS – provide the intelligence to inform the development of new payment models linked to the development of new care models
• Patient Benefit – will inform the system to enable funding and investment to follow the needs of patient. The introduction of new payment models will support the shift from the current funding patterns that remunerate activity based payment associated high cost acute care to services that are located in the community and closer to home that recognise and reward improved outcomes

Process 2
• Ability to demonstrate the aggregate impact on the public, as a result of the proposed changes outlined in both the RCRTRP and MTC programs.
• Benefit to the patient: Consideration of the aggregate capacity issues in relation to the number of beds required across both Trust areas to ensure that the proposed changes provide a system that can deliver improved Quality of Care outcomes (including patient experience) meet patients’ care needs and will result in improved outcomes.

• Required to support work with transport providers and patients to: reach agreement on the impact for the public, in terms of potential increased travel time as a result of the proposed changes, for those travelling by Public Transport and private vehicles; understand the Equality implications of these changes; and identify potential mitigations.
• Benefit to the patient: People are worried that the impact of additional travelling time will affect their ability to access care and visit people in hospital. This work will enable us to quantify that impact so that we can then work with transport providers, local transport commissioners and patients to consider the impact and how we could address/mitigate the issues in a way that works, taking account of existing public and patient transport, resulting in improved patient experience.

• Ability to demonstrate the potential impact on Yorkshire Ambulance service in relation to additional demand and support subsequent commissioning of Ambulance Services
• Benefit to the patient: Ensuring that we understand the impact of additional demand/travel time for the Ambulance service ensures that the ambulance service is able to meet this demand and that patient is taken to the correct place to receive care which will ensure access to the correct clinical resources, a better chance of recovery, improved patient experience, improved patient outcomes and a potential impact on mortality.

• Aggregate the impact on the flow of patients: attendance, admissions and estimated bed numbers at neighbouring Trusts, particularly Dewsbury District Hospital, Huddersfield Royal Infirmary and Calderdale Royal Hospital.
• Benefit to the patient: Understanding the capacity implications of the changes will ensure timely access to care, by clinicians who can meet their needs, resulting in shorter lengths of stay in hospital and improved outcomes for patients

• Provide a model to test impact on A&E attendances and Inpatient admissions of both programs.
• Benefit to patient: Understanding the changes to the flow of patients as a result of the proposed changes will ensure that access to care does not deteriorate (particularly in relation to wait times for Emergency care and access to timely planned care) resulting in improved outcomes and patient experience and a shorter time in hospital.

• As a result of the above, enable the completion of the Full Business Case and Equality and Health Inequality Impact Assessment for the RCRTRP Programme.
• Benefit to Patient: Consideration of Equality Issues for patients with protected characteristics enables mitigation to put in place to address these needs. Consideration of Health Inequality issues ensures that potential inequality of access in relation to proposed service changes and current usage by local demographic is identified and mitigation put in place. The overall benefit is to ensure that the proposals would not have any unlawful consequences for people who live or work in our communities

• Provide a detailed response to the Joint Health Scrutiny committee on their recommendations regarding the impact on the public and the Yorkshire Ambulance Service.
• Benefit to the patient: This is a product of the above requirements and benefits in order to enable independent scrutiny and assurance that the proposed changes are in the best interests of the local health economy.

Outputs:

Process 1
NECS will support Calderdale CCG to undertake a population segmentation exercise of the registered practice population of Calderdale and provide the mechanism to understand range and type of health needs in the population and patterns in the utilisation and cost of health and care resources.
Key outputs from the population segmentation exercise will include:
• Summary of the population by age and health need
• Summary on the utilisation of health and care resources across the population
• Framework to identify and prioritise where new care models should be developed
• Baseline to understand to track progress overtime – health improvement, utilisation of services, costs associated with activity
Process 2
NECS will support Calderdale CCG Right Care, Right Time, Right Place (RCRTRP) & Meeting the Challenge (MTC) programs to undertake patient travel analysis (non-ambulance) and the impact on the public, in terms of potential increased travel time as a result of the proposed changes outlined in both the RCRTRP and MTC programmes. And impact on the flow of patients: attendance, admissions and estimated bed numbers at both DDH and CRH as a result of the proposed changes outlined in both the RCRTRP and MTC programmes.
A report will be presented to the Trusts and CCGs outlining the findings of the study, including methodology, calculations and mapping.

Processing:

Process 1
1. North of England Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository.
2. Data quality management and pseudonymisation of data is completed by the DSCRO using the Open Pseudonymiser tool. The pseudonymised data is then passed securely to North of England CSU BI team for analysis.
3. North of England CSU data team process extracts of GP data sourced from practices across Calderdale and apply the same Open Pseudonymiser algorithm/key to the data as used by the DSCRO.
4. The North of England CSU BI team receives the Pseudonymised data for the addition of derived fields, linkage of data sets and analysis to support the purpose outlined above. Linkage will take place between, SUS and the GP population extract.
5. Aggregation of required data for CCG management use will be completed by the CSU.
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 disclosure control applied can be shared where contractual arrangements are in place

Process 2
1. North of England Data Services for Commissioners Regional Office (DSCRO) receives flows of local provider data from the Trusts.
2. The DSCRO will derive travel distances and times using the patient postcode submitted by the provider well as postcodes of the hospitals in the area. The output will include a series of derived data items (both travel time and distance) for the different hospitals for each patient record. The postcode will not be output, just the derived times/distances.
3. Data quality management and pseudonymisation of data is completed by the DSCRO. The pseudonymised data is then passed securely to North of England CSU employees within the BI team for analysis.
4. The North of England CSU BI team receives the Pseudonymised data who undertake analysis to support the purpose outlined above.
5. Aggregation of required data for CCG management use will be completed by the CSU.
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 disclosure control applied can be shared where contractual arrangements are in place.

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Project 5 — NIC-83772-T4M1V

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:2017.06 — 2017.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

1. SUS Accident & Emergency data
2. SUS Admitted Patient Care data
3. SUS Outpatient data
4. Local Provider Data - Acute
5. Local Provider Data - Ambulance
6. Local Provider Data - Demand for Service
7. Local Provider Data - Diagnostic Services
8. Local Provider Data - Emergency Care
9. Local Provider Data - Mental Health
10. Local Provider Data - Other not elsewhere classified
11. Local Provider Data - Community
12. SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)

Objectives:

Process 1

As part of the vision to introduce new care models that can provide care closer to home, it is critical that Calderdale CCG establish an effective framework to identify and prioritise areas that require transformation. This framework will underpin the approach to securing improved health outcomes for the local population from services that can deliver high quality as well as making the best use of resources.
To achieve this, NECS will support Calderdale CCG to undertake a population segmentation exercise. The population segmentation exercise will include the total registered population of Calderdale and a framework for commissioners to understand the range and scale of health needs and the patterns in the use of health and care resources.
Population segmentation is recognised method to support system transformation. For a comprehensive and robust population exercise to be undertaken, the CCG require pseudonymised SUS data to be linked with GP data.
This analysis will enable the health and care system within the Calderdale region to proceed with the development of new models of care and transform the way the system currently operates, providing a greater focus on the prevention of ill health and empowering individuals and communities to maintain their independence and maximise their health and wellbeing. The analysis will also provide a platform for the health and care system to track progress over time and inform the development of new payment mechanisms associated with new models of care being introduced.

Process 2
Both the Meeting The Challenge (MTC) and Right Care Right Time Right Place (RCRTRP) have both conducted analyses of the potential impact of reconfiguration on the flow of patients, attendances, admissions and bed numbers of the potential changes to service provision proposed in the respective programmes.
This piece of work is to revisit the previous reconfiguration of service provision and model the potential aggregate impact of the two programmes combined. This will include impact on patient flows: attendances, admissions and estimated bed numbers at both Dewsbury and District Hospital (DDH) and Calderdale Royal Hospital (CRH)
Outputs from the project will include a report which will be presented to the Trusts and CCGs outlining the findings of the study, including methodology, calculations and mapping.

Expected Benefits:

Process 1
The principle benefits to health and/or social care include:
• NEEDS - Provide a framework to understand population by need
• Patient Benefit – the availability of an integrated dataset will enable the system to design services and new models of care tailored to meet the specific needs of patient cohorts

• UTILISATION – summarise the patterns in the use of health and care resources and the associated costs
• Patient Benefit – understanding patterns in the use of resources and quantifying its use will allow the system to focus the development of new care models on the needs of the local population, in particular those patients multiple comorbidities who are currently dependent upon episodic unplanned care
• PRIORITISATION - Provide the system with a mechanism to prioritise areas for transformation and the introduction of new care models across the health and care system
• Patient Benefit – using integrated data sets will enable the identification of patient cohorts with most need and will enable the system to develop the appropriate interventions and models of care that can anticipate and meet patient requirements

• BASELINES - Ability to quantify activity and costs to the system, providing baselines and trend analysis
• Patients Benefit – provide the system with the capability to demonstrate the impact on reducing the reliance on episodic unplanned care

• OUTCOMES – provides baselines to track improvements in health outcomes
• Patient Benefit – provide the system with the ability to demonstrate the impact on patients quality of life and their health status as well as the shift from a reliance upon episodic unplanned care to care in the community and closer to home

• NEW MODELS OF CARE – provide a vehicle to support integrated approaches to transformation and the capability to monitor the subsequent impact on health outcomes and resource utilisation
• Patient Benefit – will support the system to develop non hospital based services so that people can maintain their independence as well as their health and wellbeing

• PROVISION – enable clinicians and front line staff to target interventions on specific client groups and provide personalised care
• Patient Benefit – enable the system to develop and align an integrated workforce to meet the multiple needs of the local population, in particular high users of unplanned services

• NEW PAYMENT MODELS – provide the intelligence to inform the development of new payment models linked to the development of new care models
• Patient Benefit – will inform the system to enable funding and investment to follow the needs of patient. The introduction of new payment models will support the shift from the current funding patterns that remunerate activity based payment associated high cost acute care to services that are located in the community and closer to home that recognise and reward improved outcomes

Process 2
• Ability to demonstrate the aggregate impact on the public, as a result of the proposed changes outlined in both the RCRTRP and MTC programs.
• Benefit to the patient: Consideration of the aggregate capacity issues in relation to the number of beds required across both Trust areas to ensure that the proposed changes provide a system that can deliver improved Quality of Care outcomes (including patient experience) meet patients’ care needs and will result in improved outcomes.

• Required to support work with transport providers and patients to: reach agreement on the impact for the public, in terms of potential increased travel time as a result of the proposed changes, for those travelling by Public Transport and private vehicles; understand the Equality implications of these changes; and identify potential mitigations.
• Benefit to the patient: People are worried that the impact of additional travelling time will affect their ability to access care and visit people in hospital. This work will enable us to quantify that impact so that we can then work with transport providers, local transport commissioners and patients to consider the impact and how we could address/mitigate the issues in a way that works, taking account of existing public and patient transport, resulting in improved patient experience.

• Ability to demonstrate the potential impact on Yorkshire Ambulance service in relation to additional demand and support subsequent commissioning of Ambulance Services
• Benefit to the patient: Ensuring that we understand the impact of additional demand/travel time for the Ambulance service ensures that the ambulance service is able to meet this demand and that patient is taken to the correct place to receive care which will ensure access to the correct clinical resources, a better chance of recovery, improved patient experience, improved patient outcomes and a potential impact on mortality.

• Aggregate the impact on the flow of patients: attendance, admissions and estimated bed numbers at neighbouring Trusts, particularly Dewsbury District Hospital, Huddersfield Royal Infirmary and Calderdale Royal Hospital.
• Benefit to the patient: Understanding the capacity implications of the changes will ensure timely access to care, by clinicians who can meet their needs, resulting in shorter lengths of stay in hospital and improved outcomes for patients

• Provide a model to test impact on A&E attendances and Inpatient admissions of both programs.
• Benefit to patient: Understanding the changes to the flow of patients as a result of the proposed changes will ensure that access to care does not deteriorate (particularly in relation to wait times for Emergency care and access to timely planned care) resulting in improved outcomes and patient experience and a shorter time in hospital.

• As a result of the above, enable the completion of the Full Business Case and Equality and Health Inequality Impact Assessment for the RCRTRP Programme.
• Benefit to Patient: Consideration of Equality Issues for patients with protected characteristics enables mitigation to put in place to address these needs. Consideration of Health Inequality issues ensures that potential inequality of access in relation to proposed service changes and current usage by local demographic is identified and mitigation put in place. The overall benefit is to ensure that the proposals would not have any unlawful consequences for people who live or work in our communities

• Provide a detailed response to the Joint Health Scrutiny committee on their recommendations regarding the impact on the public and the Yorkshire Ambulance Service.
• Benefit to the patient: This is a product of the above requirements and benefits in order to enable independent scrutiny and assurance that the proposed changes are in the best interests of the local health economy.

Outputs:

Process 1
NECS will support Calderdale CCG to undertake a population segmentation exercise of the registered practice population of Calderdale and provide the mechanism to understand range and type of health needs in the population and patterns in the utilisation and cost of health and care resources.
Key outputs from the population segmentation exercise will include:
• Summary of the population by age and health need
• Summary on the utilisation of health and care resources across the population
• Framework to identify and prioritise where new care models should be developed
• Baseline to understand to track progress overtime – health improvement, utilisation of services, costs associated with activity
Process 2
NECS will support Calderdale CCG Right Care, Right Time, Right Place (RCRTRP) & Meeting the Challenge (MTC) programs to undertake patient travel analysis (non-ambulance) and the impact on the public, in terms of potential increased travel time as a result of the proposed changes outlined in both the RCRTRP and MTC programmes. And impact on the flow of patients: attendance, admissions and estimated bed numbers at both DDH and CRH as a result of the proposed changes outlined in both the RCRTRP and MTC programmes.
A report will be presented to the Trusts and CCGs outlining the findings of the study, including methodology, calculations and mapping.

Processing:

Process 1
1. North of England Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository.
2. Data quality management and pseudonymisation of data is completed by the DSCRO using the Open Pseudonymiser tool. The pseudonymised data is then passed securely to North of England CSU BI team for analysis.
3. North of England CSU data team process extracts of GP data sourced from practices across Calderdale and apply the same Open Pseudonymiser algorithm/key to the data as used by the DSCRO.
4. The North of England CSU BI team receives the Pseudonymised data for the addition of derived fields, linkage of data sets and analysis to support the purpose outlined above. Linkage will take place between, SUS and the GP population extract.
5. Aggregation of required data for CCG management use will be completed by the CSU.
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 disclosure control applied can be shared where contractual arrangements are in place

Process 2
1. North of England Data Services for Commissioners Regional Office (DSCRO) receives flows of local provider data from the Trusts.
2. The DSCRO will derive travel distances and times using the patient postcode submitted by the provider well as postcodes of the hospitals in the area. The output will include a series of derived data items (both travel time and distance) for the different hospitals for each patient record. The postcode will not be output, just the derived times/distances.
3. Data quality management and pseudonymisation of data is completed by the DSCRO. The pseudonymised data is then passed securely to North of England CSU employees within the BI team for analysis.
4. The North of England CSU BI team receives the Pseudonymised data who undertake analysis to support the purpose outlined above.
5. Aggregation of required data for CCG management use will be completed by the CSU.
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 disclosure control applied can be shared where contractual arrangements are in place.

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Project 6 — NIC-90651-Q8W4T

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

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 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.

The Health Informatics Service
THIS provides a range of data management functions and outputs as specified by the CCG. Outputs include the provision of pseudonymised data to allow it to be viewed and interrogated, as well as aggregate level reports. These outputs can take the form of data held in a secure data warehouse or files e.g. database, CSV, Excel files.
The warehousing of data uses a robust and tested platform, i.e. the warehouse (HPS database) has been developed over circa 20 years to reflect commissioner/CCG requirements and is in a THIS IT environment, so is secure.
Utilising THIS data management also provides the following benefits:
• Utilising local knowledge and expertise on data flows that are specific to the CCG in particular data flowing from Calderdale and Huddersfield NHS Trust
• Making efficient use of existing processes that are well established and tailored to the CCG requirements
• Providing the resource / capacity required to process data flows for the CCG

The aggregate outputs fall into the following areas:
• Studying variation and trends over time
• Monitoring of healthcare contract activity plans
• Performance monitoring
• Quality monitoring

The categories of outputs to the CCG includes:

• 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/anonymised in context level.
o Contract Data Quality reporting at anonymised in context record level.
• “Deep dive” analysis of hospital activity at aggregate level.
Specific examples of report outputs include:

Commissioner Reporting
- Summary by Provider View – Plan and Actuals Year to Date (YTD)
- Summary by Patient Outcome Data (POD) view - Plan and Actuals YTD
- Summary by Provider View – Activity and Finance Variance by POD
- Planned Care by Provider View – Activity and Finance Variance by POD
- Planned Care by POD View – Activity, Finance Plan and Actuals YTD
- Provider Reporting
- Readmissions analysis
- Production of aggregate reports for CCGs Business Intelligence
- Production of project / programme level dashboards
- Monitoring of acute / community services
- Budget reporting

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
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
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.

The Health Informatics Service
1. Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository.
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 the Health Informatics Service. Data will only be processed by substantive employees of the data controller and processors The Health Informatics Service apply business rules, pricing and create additional categorical fields.
4. The Health Informatics Service securely transfer the Pseudonymised data to eMBED to flow directly to the CCG.
5. 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.
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.

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 transfers the processed, pseudonymised and linked data to eMBED and the CCG. Data will only be processed by substantive employees of the data controller and processors
4. a) The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning.
b) 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 includes 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 the CSU 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.

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Project 7 — NIC-60454-Q4L6Z

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), The Health Informatics Service (THIS) and eMBED Health Consortium, for ongoing provision in line with the NHS England Lead Provider Framework (LPF).

Data Processor 1 - NECS is the commissioning support unit working with the CCG.
Data Processor 2 - THIS is hosted by Calderdale and Huddersfield Foundation NHS Trust and is a data processor, sub-contracted by NECS, to provide support to the CCG which is an ongoing arrangement
The Health Informatics Service ensure the addition of derived fields and the data is processed so that it can be stored in a structured format in secure data warehouses to allow the data to be viewed and interrogated. Data at pseudonymised level is flowed to eMBED and directly to the CCG, by providing secure access to the relevant data warehouses to allow them to view and extract their data, or via secure email or secure file transfer.
They provide a very bespoke service to the CCGs they cover, including the following:
• Provision of the most up to date hospital submissions so CCG
• Frozen contracting views, i.e. in line with PbR timescales and rules for commissioning
• Implementation of any local data flows agreed between the CCGs and providers
• Supply the CHFT local data feeds which aren’t provided by other data processers
• transform the data as required and ensure that the CCG receives a personal and supportive service

Data Processor 3 - 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.


No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from the NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.

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:
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 (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository.
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 (apart from that highlighted in point 9) 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.

The Health Informatics Service
1. Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository.
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 the Health Informatics Service. The Health Informatics Service apply business rules, pricing and create additional categorical fields. No linkage occurs.
4. The Health Informatics Service securely transfer the Pseudonymised data to eMBED to flow directly to the CCG.
5. Aggregation of required data for CCG management use will be completed by the CSU, 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 where contractual arrangements are in place.

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Project 8 — NIC-21942-Y4Q6H

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 9 — NIC-56504-D8K6T

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:

As an approved Controlled Environment for Finance (CEfF), the data processor 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.

No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from the NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.

Expected Benefits:

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

Outputs:

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

Processing:

North of England DSCRO (part of NHS Digital) will apply Type 2 objections (from 14th October 2016 onwards) before any identifiable data leaves the DSCRO.
1. SUS Data is obtained from the SUS Repository to North of England DSCRO.
2. North of England 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. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the national 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. 
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 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.

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Project 10 — NIC-22515-W6S8Y

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 GP practice.

Expected Benefits:

To provide risk profiling, calculated on activity data from secondary and primary care. As part of the risk stratification processing activity detailed above, the GP have access to the eMBED CPM web-tool for reports which presents to them their registered patients and associated risk score.
The GP can access the eMBED CPM web-tool which is a secure portal at any time which will support multi-disciplinary team discussions around ongoing patient care, enhanced service requirements and supporting patient care.
The GP can copy and paste the NHS number presented in the eMBED CPM web-tool to any other program including the practice clinical system, in order to perform the key aspects of this risk stratification role.
There are two outputs available in the eMBED CPM web-tool, these are:
• Identifiable Reports – containing a record for each patient with NHS number, name and unique identifier Patient ID which is added to each record during data processing.

Non-Identifiable Reports – NHS number and name are removed but the record still contains the unique identifier patient ID. The GP practice authorises the access to the eMBED CPM web-tool, the level of access and which view is available.
Aggregated outputs are available to the CCG on request via eMBED.
No data will be shared with any other third party organisations.

Outputs:

To provide risk profiling, calculated on activity data from secondary and primary care. As part of the risk stratification processing activity detailed above, the GP have access to the eMBED CPM web-tool for reports which presents to them their registered patients and associated risk score.
The GP can access the eMBED CPM web-tool which is a secure portal at any time which will support multi-disciplinary team discussions around ongoing patient care, enhanced service requirements and supporting patient care.
The GP can copy and paste the NHS number presented in the eMBED CPM web-tool to any other program including the practice clinical system, in order to perform the key aspects of this risk stratification role.
There are two outputs available in the eMBED CPM web-tool, these are:
• Identifiable Reports – containing a record for each patient with NHS number, name and unique identifier Patient ID which is added to each record during data processing.

Non-Identifiable Reports – NHS number and name are removed but the record still contains the unique identifier patient ID. The GP practice authorises the access to the eMBED CPM web-tool, the level of access and which view is available.
Aggregated outputs are available to the CCG on request via eMBED.
No data will be shared with any other third party organisations.

Processing:

Processing of SUS Data for the purposes of Risk Stratification includes landing, processing, staging and publication.
1. Landing
Prior to the release of SUS data by DSCRO Yorkshire, Type 2 objections will be applied and the relevant patients data redacted. DSCRO Yorkshire securely transfer the SUS data identifiable at the level of NHS number. Data is landed and processed in an access restricted data centre located at eMBED.
Only named individuals have access to process the data. All users undertake regular IG training, in line with IGT & ISO 27001:2013 requirements.
2. Processing
Data is processed on a monthly basis.
2.1. Data is extracted from primary care systems and downloaded to a secure storage area within eMBED, it is then processed to exclude data for patient objections and sensitive conditions
2.2. Cleaning and quality checks are carried out and documented.
2.3. SUS and primary care data are linked.
2.4. Creation of Risk Stratification dataset.
2.5. Risk Stratification dataset processed through CPM Risk Stratification Algorithm to produce a Risk Stratified scoring dataset.

3. Staging
Data is landed to a secure staging area for final quality checks before forwarding to the live server.
4. Publication
Outputs are available to GP practice for their own patients only via the eMBED CPM web-portal. Access to the eMBED CPM web-portal is via username and password. All usage of its tools is audited this is controlled by the practices.
There are two outputs available, these are:
• Identifiable Reports – containing a record for each patient with NHS number, name and unique identifier Patient ID which is added to each record during data processing.

• Non-Identifiable Reports – NHS number and name are removed but the record still contains the unique identifier patient ID. (The Patient ID is generated during the loading and processing and are used in referencing the different tables so no one knows these numbers.)
Data identifiable at the level of NHS number is only available to named individuals within the GP Practices who have a legitimate relationship with the patient.
The web-portal is accessed by the GP using a username and password.
The GP have direct access to any underlying patient level SUS data where they can see all aspects of the inpatient and outpatient activity.
The GP also has access to the diagnosis data from both SUS data and the primary care data.

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