NHS Digital Data Release Register - reformatted

NHS Greater Manchester Icb - 01w projects

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


DSfC - Stockport CCG / Council Application - Comm — DARS-NIC-580883-G7N1K

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

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

Purposes: No (Sub ICB Location)

Sensitive: Sensitive

When:DSA runs 2022-01-05 — 2024-11-12

Access method: Frequent Adhoc Flow

Data-controller type: NHS GREATER MANCHESTER ICB - 01W, STOCKPORT METROPOLITAN BOROUGH COUNCIL

Sublicensing allowed: No

Datasets:

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

Objectives:

One of the key changes under the new Health and Social Care bill is the creation of 42 Integrated Care Systems (ICS) constituted of new legal entities which replace CCGs. As this agreement is coming into existence shortly prior to the expected date of this change, it is understood that it is likely there will need to be a new, closely related agreement put in place well before the end date stated here.

COMMISSIONING
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG and Local Authority 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 Local Authority commissions social care and some other health services and requires access to the same data as the CCG in order to work more collaboratively.

The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
• Secondary Uses Service (SUS+)
• Local Provider Flows
• Acute
• Ambulance
• Community
• Demand for Service
• Diagnostic Service
• Emergency Care
• Experience, Quality and Outcomes
• Mental Health
• Other Not Elsewhere Classified
• Population Data
• Primary Care Services
• 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)
• Civil Registries Data (CRD) (Births)
• Civil Registries Data (CRD) (Deaths)
• National Diabetes Audit (NDA)
• Patient Reported Outcome Measures (PROMs)
• e-Referral Service (eRS)
• Personal Demographics Service (PDS)
• Summary Hospital-level Mortality Indicator (SHMI)
• Medicines Dispensed in Primary Care (NHSBSA Data)
• Adult Social Care Data

Processing of the Medicines Dispensed in Primary Care (NHSBSA Data) dataset is only permitted to provide intelligence about the safety and effectiveness of medicines, as specified by the NHS Business Services Authority (NHSBSA) Medicines Data Directions 2019.

The pseudonymised data is required to for the following purposes:
• Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• 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
• To understand the demand 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 highlight cohorts of 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
• Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
• Support measuring the health, mortality or care needs of the total local population.
• Provide intelligence about the safety and effectiveness of medicines.
• Allow analysis of patient pathways across healthcare and social care.

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 and local authority area based on the full analysis of multiple pseudonymised datasets.

Processing for commissioning will be conducted by Arden and GEM Commissioning Support Unit.

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. CCG outcome indicators.
b. Financial and Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
14. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed.
15. Insight to understand the numerous factors that play a role in the outcome for both datasets. 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.
16. Provision of indicators of health problems, and patterns of risk within the commissioning region.
17. Support of benchmarking for evaluating progress in future years.
18. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people.
19. Assists commissioners to make better decisions to support patients and drive changes in health care
20. Allows comparisons of providers performance to assist improvement in services – increase the quality
21. Allow analysis of health care provision to 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.
22. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one).
23. Monitoring of entire population, as a pose to only those that engage with services
24. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice.
25. Monitor the quality and safety of the delivery of healthcare services.
26. Allow focused commissioning support based on factual data rather than assumed and projected sources
27. Understand admissions linked to overprescribing.
28. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.
29. Developing, through evaluation of person-level data, more effective prevention strategies and interventions across a pathway or care setting involving adult social care
30. Designing and implementing new payment models across health and adult social care
31. Understanding current and future population needs and resource utilisation for local strategic planning and commissioning purposes including for health, social care and public health needs.

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 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.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
• Patients at highest risk of admission
• High cost activity uses (top 15%)
• Frail and elderly
• Patients that are currently in hospital
• Patients with most referrals to secondary care
• Patients with most emergency activity
• Patients with most expensive prescriptions
• Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.
20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals.
22. Allow Commissioners to better protect or improve the public health of the total local patient population
23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts.
26. Identify medication prescribing trends and their effectiveness.
27. Linking prescribing habits to entry points into the health and social care system
28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
29. Monitoring, at a population level, particular cohorts of service users and designing analytical models which support more effective interventions in health and adult social care
30. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care

Processing:

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

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

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

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

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

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

ONWARD SHARING:
There is no requirement for the analytical teams to re-identify patients, but in the development of cohorts of patients considered to be at risk, the data controllers may need the facility to provide identifiable results back to direct healthcare professionals or local authority direct care staff only for the purpose of direct care. Additionally clinicians, made aware of a number of cases that they believe would need intervention may request re-identification for that direct care purpose.

These instances of re-identification will generally be carried out as programmes of work or, rarely, on an individual/small group basis. All re-id requests will be processed and authorised by the DSCRO on a case by case basis. National data opt outs are not applied in these cases as they are for the purposes of direct care which follows the legal basis of implied consent.

The following are typical (generic) examples of instances where a CCG might want to use the re-identification process:

A&E High Attendance usage

The CCG can filter data to show for example the number of A&E attendances in a given period for each patient. The CCG can then flag to the relevant GP of the patient any patients that require intervention. An outcome of this is earlier intervention in the patient(s) care thus potentially reducing future costs and minimising future risk.

Polypharmacy re-IDs

CCG's can request re-ID of a list of patients to be sent to the relevant GP with a high number of medications (ingredient count) and review the medication for these patients. This can help address the risk of polypharmacy which is recognised as an adverse risk factor for patient safety. A by-product of such reviews may be to reduce costs of medication.

The Re-identification process for direct care is as follows:

1. The CCG identifies a patient cohort to be re-identified for the purpose of direct care.

2. The CCG sends a re-id request to the DSCRO. This may be done through the CCG or CSU’s Business Intelligence (BI) Tool, or through a manual form.

3. The DSCRO assesses as to whether the request passes the specified re-identification process checks. Checks include if the requester is authorised to access identifiable data, if the number of patients in the cohort is appropriate, and that the request does not seem inappropriate or outside of expected parameters, including for example around timings and the requestor’s relationship with patients in the data. These checks are carried out either by DSCRO staff using pre-approved information (timing’s, requester’s identity etc) or via an automated system. For automated systems, steps 1 -3 wouldn’t apply in most cases as it would be the direct care professional who identifies the cohort and as long as they are an approved re-id user and have gone through security checks initially, they will be able to re-id without more further checks.

4. If successful/approved, the DSCRO re-identifies the relevant data item(s) for the appropriate patients and returns the identifiable fields to Health or care professional(s) with a legitimate relationship to the patient. The CCG does not see the identifiable record.

5. DSCROs retain an audit trail of all re-id requests

6. National Data opt outs are not applied for the purpose of direct care

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

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

All access to data is auditable by NHS Digital.

DATA MINIMISATION:
Data Minimisation in relation to the data sets listed within the application 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 NHS Stockport CCG and Stockport Metropolitan Borough Council Local Authority region (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where NHS Stockport CCG 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 NHS Stockport CCG - this is only for commissioning and relates to both national and local flows.

In addition to the dissemination of Cancer Waiting Times Data via the DSCRO, the CCG & Local Authority is able to access reports held within the CWT system in NHS Digital directly. Access within the CCG & Local Authority is limited to those with a need to process the data for the purposes described in this agreement.

A user will be able to access the provider extracts from the portal for any provider where at least 1 patient for whom they are the registered CCG for that individuals GP practice appears in that setting

Although a user may have access to pseudonymised patient information not related to them, users should only process and analyse data for which they have a legitimate relationship (as described within Data Minimisation).

Microsoft Limited provide Cloud Services for Arden and GEM Commissioning Support Unit and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data

NHS Midlands and Lancashire Commissioning Support Unit and Greater Manchester Shared Services (hosted by Salford Royal NHS Foundation Trust) supply IT infrastructure for Arden and GEM Commissioning Support Unit and are therefore listed as data processors. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Ilkeston Community Hospital (Part of Derbyshire Community Health Services NHS Foundation Trust) and Wrightington, Wigan and Leigh NHS Foundation Trust do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

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)
12. Civil Registries Data (CRD) (Births)
13. Civil Registries Data (CRD) (Deaths)
14. National Diabetes Audit (NDA)
15. Patient Reported Outcome Measures (PROMs)
16. e-Referral Service (eRS)
17. Personal Demographics Service (PDS)
18. Summary Hospital-level Mortality Indicator (SHMI)
19. Medicines Dispensed in Primary Care (NHSBSA Data)
20. Adult Social Care Data

Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:

Data Processor 1 – Arden and GEM Commissioning Support Unit
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), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit (NDA), Patient Reported Outcome Measures (PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI), Medicines Dispensed in Primary Care (NHSBSA Data) and Adult Social Care data only is securely transferred from the DSCRO to Arden and GEM Commissioning Support Unit.
2. Arden and GEM Commissioning Support Unit add derived fields by using existing data, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
3. Allowed linkage is between the data sets contained within point 1.
4. Arden and GEM Commissioning Support Unit then pass the processed, pseudonymised and linked data to the Data Controllers.
5. Aggregation of required data for management use will be completed by Arden and GEM Commissioning Support Unit or the Data Controller.
6. Patient level data will not be shared outside of the Data Controller and will only be shared within 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.


DSfC - NHS Stockport CCG - RS, IV & COMM — DARS-NIC-110660-G9W6M

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

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Section 251 approval is in place for the flow of identifiable data, National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(2)(b)(ii)

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

Sensitive: Sensitive

When:DSA runs 2019-08-10 — 2022-08-09 2018.06 — 2021.05.

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

Data-controller type: NHS STOCKPORT CCG, NHS GREATER MANCHESTER ICB - 01W

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. e-Referral Service for Commissioning
  29. Medicines dispensed in Primary Care (NHSBSA data)
  30. Personal Demographic Service
  31. Summary Hospital-level Mortality Indicator
  32. Improving Access to Psychological Therapies Data Set_v1.5

Objectives:

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



Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
The legal basis for this to occur is under Section 251 of NHS Act 2006 (CAG 7-04(a)).
Risk Stratification will be conducted by Arden and Greater East Midlands Commissioning Support Unit and North of England Commissioning Support Unit (NECS)
Arden and Greater East Midlands Commissioning Support Unit:
The Risk Stratification is done using the Kings Fund Combine Predictive Model and the data are made available to the CCG as extracts, which can be analysed using local tools. GP practices are able to view identifiable data. The Risk Stratification data from AGEM CSU will be sent to the CCG through the same mechanism as other datasets received directly from AGEM data management. All data will therefore be presented/accessed using the same tools enabling consistent use, comparisons and linkage of data at the appropriate level. As AGEM provide a data management service, data are typically provided as data extracts (or by providing access to such data), enabling more complex, bespoke analysis. * Data Processor North of England Com missioning Support Unit:
The NECS Risk Stratification data are presented to GPs through a Business Intelligence (BI) Tool ‘RAIDR’, and the same tool is also used to present the data to the CCG as interactive reports. All data/reports from NECS are provided in a consistent manner through this same mechanism; the RAIDR BI Tool. RAIDR typically presents reports derived from data extracts through a more user-friendly interface, allowing users to undertake some analysis and report presentation. The CCG can only view aggregate reports but practice users can see identifiable data for their patients.


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

The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by:
- Arden and GEM CSU
- Greater Manchester Shared Services
- Salford Royal Foundation Trust Hosting:
i) Advancing Quality Alliance (AQuA)
ii) Greater Manchester Academic Health Science Network
- Outcomes Based Healthcare
- North of England Commissioning Support Unit (for Local Provider Flows and Sus pseudonymised from 01/04/13 onwards only.)

Yielded Benefits:

Expected Benefits:

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

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



Commissioning
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Financial and Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
14. New commissioning and service delivery models delivered via joint health and social care teams reducing duplication
15. Reduction in variation of outcomes and quality of care through increased understanding of primary and secondary care interaction. E.g. if cancer treatment outcomes are poor in one area does the GP data indicate a delayed referral?
16. A complete understanding of service utilisation to aid capacity/demand planning across health and social care
17. Early warning of likely pressures in the wider health and system following increased activity in primary and social care giving other providers a chance to plan and react

Outputs:

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

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

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


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.

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

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

All access to data is auditable by NHS Digital.

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


Invoice Validation – Stockport CCG
1. Identifiable SUS+ Data is obtained from the SUS+ Repository by 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) located in the CCG.
3. The CEfF conduct the following processing activities for invoice validation purposes:
a. Validating that the Clinical Commissioning Group is responsible for payment for the care of the individual by using SUS+ and/or backing flow data.
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. In relation to a patient registered with the 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 by the CEfF that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved

Risk Stratification - Arden and GEM CSU
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 Arden and GEM CSU, who hold the SUS+ data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to Arden and GEM CSU.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Arden and GEM CSU has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level and aggregate with small number suppression

Risk Stratification – North of England CSU
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 Arden and GEM CSU, who hold the SUS+ data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to Arden and GEM CSU.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Arden and GEM CSU has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level and aggregate with small number suppression



Commissioning
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS+
2. Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Demand for Service
e. Diagnostic Service
f. Emergency Care
g. Experience, Quality and Outcomes
h. Mental Health
i. Other Not Elsewhere Classified
j. Population Data
k. Primary Care Services
l. Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Maternity Services Data Set (MSDS)
7. Improving Access to Psychological Therapy (IAPT)
8. Child and Young People Health Service (CYPHS)
9. Diagnostic Imaging Data Set (DIDS)
10. Community Services Data Set (CSDS)
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 – Arden and GEM CSU
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 Arden and GEM CSU.
2. Arden and GEM CSU add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
3. Allowed linkage is between the data sets contained within point 1.
4. Arden and GEM CSU then pass the processed, pseudonymised and linked data to the CCG.
5. Aggregation of required data for CCG management use will be completed by Arden and GEM CSU 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 as set out within NHS Digital guidance applicable to each data set.

Data Processor – Greater Manchester Shared Services
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS) and Improving Access to Psychological Therapies data (IAPT) only is securely transferred from the DSCRO to Arden and GEM CSU.
2. Arden and GEM CSU add derived fields, link data and provide analysis
3. Allowed linkage is between the data sets contained within point 1.
4. Arden and GEM CSU then pass the processed, pseudonymised and linked data to the Greater Manchester Shared Services hosted by NHS Oldham CCG.
5. Greater Manchester Shared Services provide analysis to see patient journeys for pathways or service design, re-design and de-commissioning.
6. Greater Manchester Shared Services then pass the processed, pseudonymised and linked data to NHS Stockport CCG.
7. Aggregation of required data for CCG management use will be completed by Greater Manchester Shared Services or the CCG as instructed by the CCG.
8. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.


Data Processor – Advancing Quality Alliance (AQuA)
1. Pseudonymised SUS+, Local Provider data and Mental Health data (MHSDS, MHMDS, MHLDDS) only is securely transferred from the DSCRO to Arden and GEM CSU.
2. Arden and GEM CSU add derived fields, link data and provide analysis
3. Allowed linkage is between the data sets contained within point 1.
4. Arden and GEM CSU then pass the processed, pseudonymised and linked data to the Advancing Quality Alliance.
5. Advancing Quality Alliance provide support for a range of quality improvement programmes including the NW Advancing Quality Programme. AQuA identifies cohorts of patients within specific disease groups for further analysis to help drive quality improvements across the region.
6. Advancing Quality Alliance produces aggregate reports only with small number suppression. Only aggregate reports are sent to the CCG.

Data Processor – Greater Manchester The Academic Health Sciences Network (Utilisation Management Team)
1. Pseudonymised SUS+ only is securely transferred from the DSCRO to Arden and GEM CSU.
2. Arden and GEM CSU add derived fields, link data and provide analysis
3. Allowed linkage is between the data sets contained within point 1.
4. Arden and GEM CSU then pass the processed, pseudonymised and linked data to the Academic Health Sciences Network.
5. Academic Health Sciences Network analyse the data to look at processes rather than patients, for example, A&E performance, process times, bed days as well as ‘deep dives’ to support clinical reviews for CCGs.
6. Academic Health Sciences Network produces aggregate reports only with small number suppression. Only aggregate reports are sent to the CCG.


Data Processor - Outcomes Based Healthcare

The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS+
Data quality management and pseudonymisation is completed within the DSCRO using an ‘Encryption Key’ that is specific to the Stockport Together (ST) project and is then disseminated as follows:
1) Pseudonymised SUS data is securely transferred from the DSCRO to the CCG.
2) The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
3) The CCG then pass the pseudonymised data to Outcomes Based Healthcare via secure FTP.

Primary Care Data
4) Identifiable GP Data is securely sent from the GP systems to Arden and Greater East Midlands Commissioning Support Unit, which acts as data processor on behalf of the GP practices.
5) Arden and Greater East Midlands Commissioning Support Unit process the data to meet the requirements specified, in order to provide baseline and monitoring data for the Stockport Together Outcomes Framework. This includes addition of derived fields.
6) The data is pseudonymised by Arden and Greater East Midlands Commissioning Support Unit (acting on behalf of the GP practices) using the ‘Encryption Key’ which is specific to the ST project, provided by the DSCRO.
7) Arden and Greater East Midlands Commissioning Support Unit then pass the pseudonymised primary care data in consistently pseudonymised form at patient level to the CCG via secure FTP.
8) The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. The CCG then pass the pseudonymised data to Outcomes Based Healthcare via secure FTP.

Social Care Data
9) Data quality management of Adult Social Care data is completed by Stockport Metropolitan Borough Council.
10) The Social Care data is pseudonymised at source using the ST specific ‘Encryption Key’, provided by the DSCRO. This consistently pseudonymised data is securely passed to the CCG using the ST shared area of the local secure network.
11) The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. The CCG then pass the pseudonymised data to Outcomes Based Healthcare via secure FTP.


12) Outcomes Based Healthcare will undertake linkage of the pseudonymised data sets (SUS, GP Data and Social Care Data only), using the consistent pseudonym to make the link.
13) Linkage is done within a controlled environment by named members of staff.
14) Outcomes Based Healthcare will make available on-line reports to the CCG to provide high level intelligence, based on a holistic view of care across the Stockport health and care system.
15) Access to commissioning intelligence at pseudonymised record level will be available to 2 named members of staff in the CCG.
16) Access to aggregate commissioning intelligence reports with small number suppression only will be available to a range of other named users in the Stockport Together partner organisations.

The data will be used to analytically understand patient journeys for pathway and service re-design. Access to commissioning intelligence is governed by the organisation employee code of practice, data protection policies and information governance protocols. Additionally, access to the record level data will conform to a specific information access agreement which governs how the data will be handled and used. Outcomes Based Healthcare will be responsible for linking the data but will not have access to the pseudonymisation tool, which allows data to be pseudonymised using the Encryption key. The Encryption key will only be shared by the DSCRO with named individuals in the GP practices (or their data processors) and Stockport Metropolitan Borough Council (Adult Social Care). This is to enable the GP data and the Adult Social Care data to be pseudonymised at source. The key cannot be used to re-identify data as it only allows for one-way pseudonymisation. Access to the pseudonymised data is provided to Outcome Based Healthcare and the CCG only and will only be used for the purposes specified. The data will not be transferred, shared or otherwise made available to any third party. Re-identification can only occur for GPs who have a legitimate relationship with the patient and only for the purpose of direct care.

Data Processor - North of England Commissioning Support Unit
1. Pseudonymised SUS+ and Local Provider data only from 01/04/13 onwards is securely transferred from the DSCRO to NoECSU.
2. NoECSU add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
3. Allowed linkage is between the data sets contained within point 1.
4. NoECSU then pass the processed, pseudonymised and linked data to the CCG.
5. Aggregation of required data for CCG management use will be completed by NoECSU 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 as set out within NHS Digital guidance applicable to each data set.