NHS Digital Data Release Register - reformatted

NHS Sunderland CCG projects

GDPPR COVID-19 CCG - Pseudo
DSfC - NHS Sunderland CCG - Comm
DSfC - NHS Sunderland CCG IV RS Comm
Project 4
Project 5

1196 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).

🚩 NHS Sunderland CCG was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Sunderland 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-404711-R1R3R

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 2020-09-23 — 2021-03-31 2021.01 — 2021.05.

Access method: One-Off, Frequent Adhoc Flow

Data-controller type: NHS SUNDERLAND CCG, NHS NORTH EAST AND NORTH CUMBRIA ICB - 00P

Sublicensing allowed: No

Datasets:

GPES Data for Pandemic Planning and Research (COVID-19)
COVID-19 Ethnic Category Data Set
COVID-19 Vaccination Status
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).

DSfC - NHS Sunderland CCG - Comm — DARS-NIC-250326-W3F1B

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 2019-11-01 — 2022-10-31 2019.02 — 2021.05.

Access method: Frequent Adhoc Flow, One-Off

Data-controller type: NHS SUNDERLAND CCG, NHS NORTH EAST AND NORTH CUMBRIA ICB - 00P

Sublicensing allowed: No

Datasets:

Mental Health and Learning Disabilities Data Set
Mental Health Minimum Data Set
Mental Health Services Data Set
SUS for Commissioners
Civil Registration - Births
Civil Registration - Deaths
Civil Registrations of Death
Mental Health and Learning Disabilities Data Set (MHLDDS)
Mental Health Minimum Data Set (MHMDS)
Mental Health Services Data Set (MHSDS)

Objectives:

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+)
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
The pseudonymised data is required to for the following purposes:
 Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
 Data Quality and Validation – allowing data quality checks on the submitted data
 Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
 Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
 Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
 Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
 Service redesign
 Health Needs Assessment – identification of underlying disease prevalence within the local population
 Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models

The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by North of England Commissioning Support Unit & Outcomes Based Healthcare Ltd. Outcomes Based Healthcare Ltd use Cloud based processing and therefore will use both Microsoft Azure and Google Clouds as processing locations.

Yielded Benefits:

1. Population segmentation now being used to feed into commissioning decisions and service transformation and monitoring impact. 2. System wide outcome measures in place and data used to continuously develop the outcomes framework across the system

Expected Benefits:

1. Population segmentation and outcome measurement across the entire population produces data that looks at the end results of care, burden of disease and complications, and their severity, as well as system activity metrics, and a better understanding of the population through grouping people by need. Including analysis showing impact of deprivation on outcomes and quality of care
2. Outcomes data across the entire population will support decision making around service transformation, integrated care, care planning, care coordination, and service delivery, with the focus on improving the outcomes
3. Outcomes data supports quality process improvement within care pathways
4. Access to stakeholders across the entire health system, including commissioners and providers to have a single, transparent view of outcomes data
5. Refocuses health system providers (including health and social care providers) to work in a more integrated way to reduce the burden of disease
6. Enables commissioners and providers to compare whether their longer-term targets and improvement trajectories set for each outcome, have been met. Whilst allowing providers to focus their efforts on improving these outcomes, for specific population groups, over a period of years

Outputs:

Outcomes Platform access via secure login (available to named individuals in the CCG and CCG commissioned providers only)
a. Aggregated monthly values for each outcome (with small number suppression, including any values under 5) using NHS Digital guidance.
i. This enables the CCG and providers to visualise baselines using historical data for each outcome, and set improvement trajectories
ii. Monitoring of outcomes on a monthly basis
b. Filtering of outcomes data by age bands, deprivation centiles, and other variables
c. Statistical process control for each outcome measure
d. Population segment insights related to outcomes
e. Information schedule describing the outcomes to be monitored, the technical description, and annual baseline data for each outcome.

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 and using the Cloud storage listed.

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).

Access by the CCG to aggregated commissioning intelligence is governed by the organisation employee code of practice, data protection policies and information governance protocols.

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 including data held in Cloud storage.

Data Minimisation
Data Minimisation in relation to the data sets listed within the agreement are listed below. This also includes the purpose on which they would be applied -

• Patients who are normally registered and/or resident within Sunderland CCG (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where Sunderland 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 Sunderland CCG - this is only for commissioning and relates to both national and local flows.

For clarity, any access by Pulsant Data Centre 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. Mental Health Minimum Data Set (MHMDS)
3. Mental Health Learning Disability Data Set (MHLDDS)
4. Mental Health Services Data Set (MHSDS)
Data quality management and pseudonymisation is completed within the DSCRO using the University of Nottingham Open Pseudonymiser Tool and is then disseminated as follows:

Data Processor 1 & 2 – North of England Commissioning Support Unit & Outcomes Based Healthcare Ltd
1. Pseudonymised SUS+, Mental Health data (MHSDS, MHMDS, MHLDDS only is securely transferred from the DSCRO to North of England Commissioning Support Unit.
2. North of England Commissioning Support Unit sends pseudonymised data via secure FTP to Outcomes Based Healthcare Ltd.
3. GP data is pseudonymised at source within each GP practice using the University of Nottingham Open Pseudonymiser Tool.
4. GP data is linked with the data listed in point 1.
5. Based on a data specification specific to the CCG’s requirements, pseudonymised data flows via secure FTP to Outcomes Based Healthcare Ltd. The data specification includes:
• Pseudonymised identifier
• LSOA (lower super output area)
• Read coded data for specific medical conditions
• Current medication data for specific medical conditions
6. Outcomes Based Healthcare Ltd provide aggregate intelligence reporting and dashboards to the CCG with aggregate population-level data (with small number suppression). Data analysis will include:
a. Data quality and validation checks
b. Population segmentation analytics for each segment including intelligence on outcomes, hospital activity, cost, lifestyle/risk factors, deprivation and other patient demographic information.

Outcomes Based Healthcare Ltd will not have access to the pseudonymisation tool or encryption key used for the SUS, Mental Health and GP data. Outcomes Based Healthcare Ltd will not re-identify the data.

DSfC - NHS Sunderland CCG IV RS Comm — DARS-NIC-36892-P3B3F

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - consent provided by participants of research studYes - patient objections upheld, No - data flow is not identifiable, Anonymised - ICO Code Compliant, Identifiable (Section 251, Mixed, 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), National Health Service Act 2006 - s251 - 'Control of patient 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(7), Health and Social Care Act 2012 s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 s261(2)(b)(ii)

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

Sensitive: Sensitive, and Non Sensitive

When:DSA runs 2019-10-01 — 2022-09-30 2018.06 — 2021.05.

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

Data-controller type: NHS SUNDERLAND CCG, NHS NORTH EAST AND NORTH CUMBRIA ICB - 00P

Sublicensing allowed: No

Datasets:

Acute-Local Provider Flows
Children and Young People Health
Demand for Service-Local Provider Flows
Improving Access to Psychological Therapies Data Set
Mental Health and Learning Disabilities Data Set
Mental Health Services Data Set
Other Not Elsewhere Classified (NEC)-Local Provider Flows
Ambulance-Local Provider Flows
Community Services Data Set
Community-Local Provider Flows
Diagnostic Imaging Dataset
Diagnostic Services-Local Provider Flows
Emergency Care-Local Provider Flows
Experience, Quality and Outcomes-Local Provider Flows
Maternity Services Data Set
Mental Health Minimum Data Set
Mental Health-Local Provider Flows
National Cancer Waiting Times Monitoring DataSet (CWT)
Population Data-Local Provider Flows
Primary Care Services-Local Provider Flows
Public Health and Screening Services-Local Provider Flows
SUS for Commissioners
Civil Registration - Births
Civil Registration - Deaths
National Diabetes Audit
Patient Reported Outcome Measures
e-Referral Service for Commissioning
Personal Demographic Service
Summary Hospital-level Mortality Indicator
National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
Improving Access to Psychological Therapies Data Set_v1.5
Adult Social Care
Medicines dispensed in Primary Care (NHSBSA data)
Civil Registrations of Death
Community Services Data Set (CSDS)
Diagnostic Imaging Data Set (DID)
Improving Access to Psychological Therapies (IAPT) v1.5
Mental Health and Learning Disabilities Data Set (MHLDDS)
Mental Health Minimum Data Set (MHMDS)
Mental Health Services Data Set (MHSDS)
Patient Reported Outcome Measures (PROMs)
Summary Hospital-level Mortality Indicator (SHMI)

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) (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 North of England CSU

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 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 North of England CSU

Yielded Benefits:

Invoices validated as per agreed timescales and specification. Reports used to feed into CCG budget management processes and performance/contract management. Risk stratification used for population health management purposes and commissioning of servicess.

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.
Specific outputs expected, including target date:
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

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 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 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 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
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 North of England 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 North of England CSU.
4. SUS data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier 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 North of England CSU hosts is limited to those substantive employees with authorised user accounts used for identification and authentication.
7. Once North of England CSU has completed the processing, the CCG can access the online system via a secure 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 Learning Disability Data Set (MHLDDS)
4. Mental Health Services Data Set (MHSDS)
5. Maternity Services Data Set (MSDS)
6. Improving Access to Psychological Therapy (IAPT)
7. Child and Young People Health Service (CYPHS)
8. Diagnostic Imaging Data Set (DIDS)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor 1 – North of England CSU
1) Pseudonymised SUS, Local Provider data, Mental Health data (MHSDS, 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 CSU.
2) North of England CSU add derived fields, link data and provide analysis.
3) Allowed linkage is between the data sets contained within point 1.
4) North of England CSU then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
5) Aggregation of required data for CCG management use will be completed by North of England 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.

Project 4 — DARS-NIC-134663-P4Z4Z

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - data flow is not identifiable, Yes - patient objections upheld (Section 251)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: ()

Sensitive: Sensitive

When:2018.10 — 2019.04.

Access method: Frequent Adhoc Flow

Data-controller type:

Sublicensing allowed:

Datasets:

Acute-Local Provider Flows
Ambulance-Local Provider Flows
Children and Young People Health
Community Services Data Set
Community-Local Provider Flows
Demand for Service-Local Provider Flows
Diagnostic Imaging Dataset
Diagnostic Services-Local Provider Flows
Emergency Care-Local Provider Flows
Experience, Quality and Outcomes-Local Provider Flows
Improving Access to Psychological Therapies Data Set
Maternity Services Data Set
Mental Health and Learning Disabilities Data Set
Mental Health Minimum Data Set
Mental Health Services Data Set
Mental Health-Local Provider Flows
Other Not Elsewhere Classified (NEC)-Local Provider Flows
Population Data-Local Provider Flows
Primary Care Services-Local Provider Flows
Public Health and Screening Services-Local Provider Flows
SUS for Commissioners

Objectives:

Invoice Validation
As an approved Controlled Environment for Finance (CEfF), North of England Commissioning Support Unit (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) (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 North of England Commissioning Support Unit (CSU)

Commissioning - Data Processor 1 - North of England Commissioning Support Unit
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)
- Community Services Data Set (CSDS)
- 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 North of England Commissioning Support Unit (CSU)

In addition, North of England Commissioning Support Unit also receive pseudonymised GP data, Social Care data and Consented Data. This is pseudonymised either at source or within North of England Commissioning Support Unit. This pseudonymisation tool is different to that held within the DSCRO. Also, each data source will use a variation of this tool so there is no linkage between these data until a common pseudonym has been applied via the DSCRO.

Commissioning - Data Processor 2 - Outcomes Based Healthcare (OBH)
OBH will use pseudonymised data, to support the measurement of outcomes. This includes development of outcomes, and baselining and monitoring of individual outcomes on the Outcomes Framework, as well as providing detailed analysis relating to those outcomes, on behalf of the CCG. This will enable near real-time outcome measurement for specific population segments, where the entire population is accounted for:

- 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)

Yielded Benefits:

N/A

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.
d. Pooled health and social care budget reporting
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types and patient groups
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 and social care.
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. New commissioning and service delivery models delivered via joint health and social care teams reducing duplication
8. 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?
9. A complete understanding of service utilisation to aid capacity/demand planning across health and social care
10. 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.

Data Processor 2 – Outcomes Based Healthcare (OBH)

Outcomes are often described as those things that matter to people, and are typically the end results of care across complete care pathways. Access to a population-level view of segmented and specific outcome measures that cover the whole population, in near real-time is essential for any health and care system. It is also an essential enabler supporting quality process improvement within care pathways.

Outcomes measured using existing clinical and administrative data typically measure the reduction in illness, disease and complications, and their severity, in addition to system activity metrics.

Measuring outcomes aims to refocus providers (including health and social care providers) to work together to reduce the burden of disease. By setting longer-term targets and improvement trajectories for each outcome, providers can focus their efforts on improving these outcomes, for specific population groups, over a period of years.

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. All of the above segmented in to population groups
10. Analysis across health and social care by patient (outputs aggregated) providing a greater understand of service interdependencies and opportunities for a single service delivery model where overlap may exist currently
11. Variation reporting between primary and secondary care (e.g. where one care setting suggests the patient has a condition but the other does not potentially leading to inappropriate treatment)
12. Delayed transfers of care analysis

1. Outcomes Platform access via secure login (available to named individuals in the CCG and CCG commissioned providers only) provided until March 2019
a. Aggregated monthly values for each outcome (with small number suppression, including any values under 5).
i. This enables the CCG and providers to visualise baselines using historical data for each outcome, and set improvement trajectories
ii. Monitoring of outcomes on a monthly basis until March 2019
b. Filtering of outcomes data by age bands, deprivation centiles, and other variables
c. Statistical process control for each outcome measure
d. Population segment insights related to outcomes
e. Information schedule describing the outcomes to be monitored, the technical description, and annual baseline data for each outcome.
2. Access by the CCG to aggregated commissioning intelligence is governed by the organisation employee code of practice, data protection policies and information governance protocols.

Data Processor 2 – Outcomes Based Healthcare (OBH)
1. Outcomes Platform access via secure login (available to named individuals in the CCG and CCG commissioned providers only) provided until March 2019
a. Aggregated monthly values for each outcome (with small number suppression, including any values under 5).
i. This enables the CCG and providers to visualise baselines using historical data for each outcome, and set improvement trajectories
ii. Monitoring of outcomes on a monthly basis until March 2019
b. Filtering of outcomes data by age bands, deprivation centiles, and other variables
c. Statistical process control for each outcome measure
d. Population segment insights related to outcomes
e. Information schedule describing the outcomes to be monitored, the technical description, and annual baseline data for each outcome.
2. Access by the CCG to aggregated commissioning intelligence is governed by the organisation employee code of practice, data protection policies and information governance protocols.

Processing:

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

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

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

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

Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data.

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 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 of interest of the applicant.
The DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.
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)
NHS Digital will not be involved with the pseudonymisation of Social Care Data and GP data referred to in this agreement.

NHS Digital is not involved in the processing of personal data once released from NHS Digital.

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 audited

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
Identifiable SUS Data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
1. 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 (CSU).
2. The CSU carry out the following processing activities within the CEfF for invoice validation purposes:
o 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
o 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:
- In line with Payment by Results tariffs
- are in relation to a patient registered with a CCG GP or resident within the CCG area.
- 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 North of England CSU CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.

Risk Stratification
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 North of England Commissioning Support Unit (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 North of England CSU.
4. SUS data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier 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 North of England CSU 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. Community Services Data Set (CSDS)
10. Diagnostic Imaging Data Set (DIDS)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor 1 – North of England Commissioning Support Unit (CSU)
1. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then held until completion of points 2 – 7.
2. North of England Commissioning Support Unit also receive GP Data. It is received as follows:
o Identifiable GP data is submitted to the CSU.
o The data lands in a ring-fenced area for GP data only.
o There is a Data Processing Agreement in place between the GP and the CSU. A specific named individual within the CSU acts on behalf on the GP. This person has been issued with a black box.
o The individual requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once. The key is specific to that GP and the pseudonymisation request. The individual does not have access to the data once it has been passed on to the CSU.
o The GP data is then pseudonymised using the black box and DSCRO issued key – the clear data is then deleted from the ring-fenced area.
o The CSU are then sent the pseudo GP data with the pseudo key specific to them.
3. North of England Commissioning Support Unit receive a flow of social care data. Social Care data is received in one of the following 2 ways:
o Pseudonymised:
- The social care organisation is issued with their own black box solution.
- The social care organisation requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once and is specific to that date.
- The social care organisation submits the pseudonymised social care data to the CSU with the pseudo algorithm specific to them
o Identifiable:
- Identifiable Social Care data is submitted to North of England Commissioning Support Unit
- The data lands in a ring-fenced area for GP data only.
- There is a Data Processing Agreement in place between the Local Authority and North of England Commissioning Support Unit A specific named individual within North of England Commissioning Support Unit on behalf on the Local Authority. This person has been issued with a black box.
 The individual requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once. The key is specific to the Local Authority and to that specific date.
- Before North of England Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted.
- North of England Commissioning Support Unit are then sent the pseudonymised GP data with the pseudo algorithm specific to them.
4. North of England Commissioning Support Unit receive a flow of consented data. It is received as follows:
o Identifiable consented data is submitted to the CSU.
o The data lands in a ring-fenced area for consented data only.
o There is a Data Processing Agreement in place between the CCG and the CSU. A specific named individual within the CSU acts on behalf on the CCG. This person has been issued with a black box.
o The individual requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once. The key is specific to the CCG and the pseudonymisation request. The individual does not have access to the data once it has been passed on to the CSU.
o The consented data is then pseudonymised using the black box and DSCRO issued key – the clear data is then deleted from the ring-fenced area.
o The CSU are then sent the pseudo consented data with the pseudo key specific to them.
5. Once the pseudonymised GP data, social care data and consented data is received, the CSU make a request to the DSCRO.
6. The DSCRO then send a mapping table to the CSU
7. The CSU then overwrite the organisation specific keys with the DSCRO key.
8. The mapping table is then deleted.
9. The DSCRO then pass the pseudonymised SUS, local provider data, Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) securely to North of England CSU for the addition of derived fields, linkage of data sets and analysis.
10. Social care, GP and Consented data is then linked to the data sets listed within point 9 in the CSU. utilising algorithms and analysis
11. North of England Commissioning Support provide analysis to:
o See patient journeys for pathways or service design, re-design and de-commissioning.
o Check recorded activity against contracts or invoices and facilitate discussions with providers.
o Undertake population health management
o Undertake data quality and validation checks
o Thoroughly investigate the needs of the population
o Understand cohorts of residents who are at risk
o Conduct Health Needs Assessments
12. North of England Commissioning Support also apply an risk stratification algorithm to the pseudonymised SUS+, Local Provider flows and GP data.
13. Aggregation of required data for CCG management use will be completed by the CSU as instructed by the CCG.
14. Patient level data will not be shared outside of the Data Processor/Controller and will only be shared within the Data Processors on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.

Data Processor 2 – Outcomes Based Healthcare (OBH)
1. North of England Commissioning Support sends pseudonymised SUS, Mental Health, Social Care, and GP data, based on data specification that includes only that information required for the outcomes selected by the CCG, for linking via secure FTP to OBH.
2. OBH provide analysis to the CCG through the online Outcomes Platform tool:
a. data quality and validation checks
b. population segmentation analytics
c. understand patient journeys for pathway and service re-design, as well as recording the end results of care through outcome measurement
d. statistical process control
e. aggregate commissioning intelligence reports with small number suppression to named users in the CCG and providers commissioned by the CCG

OBH will not have access to the pseudonymisation tool, which allows data to be pseudonymised using the Encryption key, therefore is unable to re-identify the data.

Project 5 — NIC-36892-P3B3F

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:

Local Provider Data - Acute
Local Provider Data - Ambulance
Local Provider Data - Community
Local Provider Data - Demand for Service
Local Provider Data - Diagnostic Services
Local Provider Data - Emergency Care
Local Provider Data - Experience Quality and Outcomes
Local Provider Data - Public Health & Screening services
Local Provider Data - Mental Health
Local Provider Data - Other not elsewhere classified
Local Provider Data - Population Data
Local Provider Data - Primary Care
Mental Health and Learning Disabilities Data Set
Mental Health Minimum Data Set
Mental Health Services Data Set
SUS Accident & Emergency data
SUS Admitted Patient Care data
SUS Outpatient data
Children and Young People's Health Services Data Set
Improving Access to Psychological Therapies Data Set
Maternity Services Dataset
SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
SUS for Commissioners
Public Health and Screening Services-Local Provider Flows
Primary Care Services-Local Provider Flows
Population Data-Local Provider Flows
Other Not Elsewhere Classified (NEC)-Local Provider Flows
Mental Health-Local Provider Flows
Maternity Services Data Set
Experience, Quality and Outcomes-Local Provider Flows
Emergency Care-Local Provider Flows
Diagnostic Services-Local Provider Flows
Diagnostic Imaging Dataset
Demand for Service-Local Provider Flows
Community-Local Provider Flows
Children and Young People Health
Ambulance-Local Provider Flows
Acute-Local Provider Flows
SUS (Accident & Emergency, Inpatient and Outpatient data)
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, Public Health & Screening services

Objectives:

Invoice Validation
As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number to undertake invoice validation on behalf of the CCG. In order to support commissioning of patient care by validating non-contracted activity in the CCG, this data is required for the purpose of invoice validation. 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
This is an application to use SUS data identifiable at the level of NHS number 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.

Pseudonymised – SUS and Local Flows
Application for the CCG 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 commission activity of one or more providers. Equally the underpinning categories such as “experience, quality and outcomes” are applicable to all commissioned services and support the flows of data evidencing the quality of patient care.

Data is generally requested for a 5 year period – this is to ensure any commissioning decisions based on analysis produced from the data supplied are robust and supported by clear evidence. Utilising only 1, 2 or 3 years of data is not sufficient to ensure long term patient trends are reflected. For example a couple of back to back mild winters would skew the true trend of increased COPD admissions during the winter period.

The above applies to all the locally requested datasets as well as SUS as a complete picture of health services is required to underpinned major commissioning decisions. E.g. closing a community hospital would require analysis of acute services, ambulance journeys, diagnostic services, clinical screening, the impact primary care, patient experience and outcomes. A understanding of the population and demand for services would also be needed.

Without a complete and comprehensive understanding of all local health services decisions cannot be made that stand up to significant public, political and media scrutiny.

SUS data is requested for a longer period as due a particular requirement of the NHS standard contract commissioners are required to manage emergency admissions back to a threshold level set on 2008 activity. Each year 2008/09 SUS data is re-processed to reflect local commissioning arrangements, new national guidance/tariffs and a threshold figure recalculated. A record level dataset is required to complete this task.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
Application for the CCG to use MHSDS, MHMDS, MHLDDS, MSDS, IAPT, CYPHS and DIDs linked and pseudonymised data to provide intelligence to support commissioning of health services. The linked, 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.

Data is generally requested for a 5 year period – this is to ensure any commissioning decisions based on analysis produced from the data supplied are robust and supported by clear evidence. Utilising only 1, 2 or 3 years of data is not sufficient to ensure long term patient trends are reflected.

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 HSCIC will not be national data, but only that data relating to the specific locality of interest of the applicant.

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 misapproproation of public funds to ensure the on-going 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.
Pseudonymised – SUS and Local Flows
1) Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management and pathways.
2) 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) flows
3) Commissioning cycle support for grouping and re-costing previous activity
4) Enables monitoring of:
a) CCG outcome indicators
b) Non-financial validation of patient level data
c) Successful delivery of integrated care within the CCG
d) Checking frequent or multiple attendances to improve early intervention and avoid admissions
e) Commissioning and performance management
5) Feedback to NHS service providers on data quality at an aggregate level

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
1) Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management and pathways.
2) Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3) Health economic modelling using:
(a) Analysis on provider performance.
(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.

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 with no identifiers

3) Record level output will be available for commissioners in anonymised or pseudonymised format.

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.

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 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.

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 acute / community / mental health quality matrix.
6) Clinical coding reviews / audits.
7) Budget reporting down to individual GP Practice level.

Processing:

Invoice Validation
1) SUS Data is sent from the SUS Repository to North England DSCRO. Prior to the release of SUS data by North England DSCRO Type 2 objections will be applied and the relevant patients data redacted.

2) DSCRO North England pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the North of England CSU (Data Processor 1).

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) by using the derived commissioner field in SUS 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 to confirm the payments are:
- In line with Payment by Results tariffs
- are in relation to a patient registered with a CCG GP or resident within the CCG area.
- 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 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) SUS Data is sent from the SUS Repository to North England DSCRO. Prior to the release of SUS data by North England DSCRO Type 2 objections will be applied and the relevant patients data redacted.

2) SUS data identifiable at the level of NHS number regarding hospital admissions, A&E attendances and outpatient attendances is delivered securely from Data Services for Commissioners Regional Office (DSCRO) North England to the data processor.
4) 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 North of England CSU (Data Processor 1), who hold the SUS data within the secure Data Centre on N3.
5) SUS data is linked to GP data in the risk stratification tool by the data processor.
6) 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.
7) North of England CSU who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
8) Once North of England CSU has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level.

Pseudonymised – SUS and Local Flows
1) North England Data Services for Commissioners Regional Office (DSCRO) receives a flow of SUS identifiable data for the CCG from the SUS Repository. North England DSCRO also receives identifiable local provider data for the CCG directly from Providers.
2) Data quality management of data is completed by the DSCRO and the pseudonymised data is then passed securely to North England CSU for the addition of derived fields, linkage of data sets and analysis.
3) North of England CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4) Patient level data will not be shared outside of the CCG. External aggregated reports only.

Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS
1) North England Data Services for Commissioning Regional Office (DSCRO) will receive a flow of pseudonymised patient level data for each CCG for Mental Health (MHSDS, MHMDS, MHLDDS), Improving Access to Psychological Therapies (IAPT), Maternity (MSDS), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes
2) Data quality management of data is completed by the DSCRO and the pseudonymised data is then passed securely to North England CSU for the addition of derived fields, linkage of data sets and analysis. Linkage is not with other datasets just between the data contained within the dataset itself.
3) North of England CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4) The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning
5) The CCG completes aggregation of required data for CCG management use – disclosing any outputs at the appropriate level.
6) Patient level data will not be shared outside of the CCG. External aggregated reports only.

NHS Digital Data Release Register - reformatted

NHS Sunderland CCG projects

GDPPR COVID-19  CCG - Pseudo — DARS-NIC-404711-R1R3R

DSfC - NHS Sunderland CCG - Comm — DARS-NIC-250326-W3F1B

DSfC - NHS Sunderland CCG IV RS Comm — DARS-NIC-36892-P3B3F

Project 4 — DARS-NIC-134663-P4Z4Z

Project 5 — NIC-36892-P3B3F

GDPPR COVID-19 CCG - Pseudo — DARS-NIC-404711-R1R3R