NHS Digital Data Release Register - reformatted

NHS Gloucestershire CCG projects

1555 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).


🚩 NHS Gloucestershire CCG was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Gloucestershire 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-391600-Q4Y2J

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 2020-09-01 — 2021-03-31 2021.01 — 2021.05.

Access method: One-Off, Frequent Adhoc Flow

Data-controller type: NHS GLOUCESTERSHIRE CCG, NHS GLOUCESTERSHIRE ICB - 11M

Sublicensing allowed: No

Datasets:

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

Objectives:

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

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

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

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

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

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

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

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

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

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

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


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

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

Health organisations

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

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

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

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

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

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

Expected Benefits:

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

Outputs:

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

Processing:

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

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

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

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

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

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

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

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

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

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

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

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

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


DSfC - NHS Gloucestershire CCG / Gloucestershire County Council - Population Health — DARS-NIC-343158-Z2L4D

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

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

Sensitive: Sensitive

When:DSA runs 2020-04-23 — 2023-04-22 2020.06 — 2021.05.

Access method: Frequent Adhoc Flow, One-Off

Data-controller type: GLOUCESTERSHIRE COUNTY COUNCIL, NHS GLOUCESTERSHIRE CCG, GLOUCESTERSHIRE COUNTY COUNCIL, NHS GLOUCESTERSHIRE ICB - 11M

Sublicensing allowed: No

Datasets:

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

Objectives:

COMMISSIONING
Population Health
To use pseudonymised data to provide intelligence to support the commissioning of health and care services. The data (containing both clinical and financial information) is analysed so that health and care provision can be planned to support the needs of the population within the Gloucestershire area.
The CCG and Local authority 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.

Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM project.

NHS Gloucestershire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England.

Optum is a leading health services and innovation company dedicated to helping make the health system work better for everyone. Optum has been involved in the UK healthcare arena since 2002 helping clinicians deliver high quality, cost-effective healthcare and improve the lives and wellbeing of patients.

Optum is an accredited supplier on the The Health Systems Support (HSS) (NHS England.

The following pseudonymised datasets are required to provide intelligence to support commissioning of health and care services:
- Secondary Uses Service (SUS+)
- 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)


The pseudonymised data is required for the following purposes:
1. Improving Mental Health: including improving dementia care and a renewed focus on mental health and wellbeing, additional support for regular users of health and care services.
2. Focusing on proactive care in partnership with local communities: including building capacity in primary, community and VCSE care, reducing demand for acute services and improving end of life care.
3. Improving population health: including rapid delivery of place based integrated working through Integrated Locality Partnerships and a focus on wellbeing and prevention & self-care. Increasingly we will work to influence the wider determinants of health including loneliness and isolation whilst also improving or use and application of population health management.
4. Focus on enabling conditions including
a. fostering a culture of engagement and co-creation
b. continuing existing enabling programmes of workforce, estates and digital
c. maturing the system approach to allocation of resources to ensure investments are used to create greatest improvement
d. ensuring effective governance that facilitates shared decision making

Processing for population health will be conducted by South, Central and West Commissioning Support Unit.

General Commissioning

The CCG also receives the following datasets to conduct their general commissioning activities

- Secondary Uses Service (SUS+)
- 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)


This application allows the linkage of these data sets to the local provider flow datasets, GP data and Social Care data the CCG receives on DARS-NIC-343042-X5T7Y. The same pseudo code will be applied by the DSCRO in order to enable this linkage. The linked data will only be made available to the CCG and not the Council.

Processing for this will be conducted by South Central and West Commissioning Support Unit and Optum Health Solutions (for CCG Only).

The CCG may be alerted to patients through the commissioning processing who would benefit from further support and is able to use other datasets held under other DSAs to identify individuals through this process.

Whilst this agreement covers the purpose of commissioning there are references tor risk stratification. This is relevant as when the CCG are using the data for commissioning purposes they may flag that there is a patient or group of patients presenting a risk. Whilst risk stratification is not the primary purpose this agreement would not prohibit any flagging of at risk groups. The CCG has approval to access the same data under a different agreement for Risk Stratification NIC- 3422229 and if it were not having this separate agreement with the Council Risk Stratification and Commissioning would sit under the same agreement with the CCG.

Expected Benefits:

Population Health Analytics to enable:
1. Understanding of cohorts of people who are at risk of becoming new users of services / users of some of the more expensive services, to better understand and manage those needs.
2. 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. this benefit applies only to the CCG.
3. Services and contracts to be better aligned with populations and their needs.
4. Evaluation of the impact of health and care services, including the effectiveness of changes to services and technology
5. To assess the cost effectiveness of the local health and care economy.
6. Thoroughly investigating the needs of the population and segments of the population, to ensure most appropriate services are available for individuals when and where they need them.
7. Monitoring population health and care interactions to understand where there may be unmet need for cohorts of patients or individuals, or where the provision of care may be being duplicated, allowing commissioners to identify priorities and plans to address these
8. Supporting the development of the Joint Strategic Needs Assessment (JSNA).
9. Population projections
10. Predictive modelling - used at cohort level to identify future service delivery requirements and models.
11. Modelling activity across all data sets to understand how services interact with each other, and how cohorts or individuals interact with a range of services to understand how changes in one service may affect flow through another
Benefits:
1. By having a more comprehensive understanding of the health and care system, through linked data, services and contracts can be better aligned to population needs.
2. More robust evaluation of the impact of health and care services
3. Improvements the cost effectiveness of the local health and care economy
4. An enhanced evidence base to ensure most appropriate services are available for individuals when and where they need them
5. By understand where there may be unmet need for cohorts of patients across health AND care, the system will be better able to respond
6. Better understanding of health inequalities and therefore better able to address them
7. Better understanding of the wider determinants of health
8. Aligned population projects across health and care

Outputs:

Population Health Analytics to enable:
1. Understanding of cohorts of people who are at risk of becoming new users of services / users of some of the more expensive services, to better understand and manage those needs.
2. 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.
3. Services and contracts to be better aligned with populations and their needs.
4. Evaluation of the impact of health and care services, including the effectiveness of changes to services and technology
5. To assess and improve the cost effectiveness of the local health and care economy.
6. Thoroughly investigating the needs of the population and segments of the population, to ensure most appropriate services are available for individuals when and where they need them.
7. Monitoring population health and care interactions to understand where there may be unmet need for cohorts of patients or individuals, or where the provision of care may be being duplicated, allowing commissioners to identify priorities and plans to address these
8. Supporting the development of the Joint Strategic Needs Assessment (JSNA).
9. Population projections
10. Predictive modelling - used at cohort level to identify future service delivery requirements and models.
11. Modelling activity across all data sets to understand how services interact with each other, and how cohorts or individuals interact with a range of services to understand how changes in one service may affect flow through another
12. Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project. The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.

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 Controllers.

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 only be linked to datatsets specifically detailed within this Data Sharing Agreement and those listed in DARS agreement DARS-NIC-343042-X5T7Y
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).

Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set.

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.

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 Gloucestershire CCG region (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
- Patients treated by a provider where NHS Gloucestershire 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 Gloucestershire CCG.
and/or
- The population for which Gloucestershire County Council has responsibility for.

University Hospitals Bristol 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.

Black Box Software
- The Black Box is a software process with very limited access, restricted to only those who administer it.
- It is a set of logic that is hidden from users. It generates a re-pseudonymised output from the data that users enter.
- The purpose of the Black Box is to map the data such that the resulting pseudonymisation is the same as that used at the DSCRO.
- The Black Box works by calling upon a mapping table from the DSCRO and re-pseudonymising by switching the
pseudonym. No data is persisted in the Black Box.
The Black Box is held within a private part of South Central and West Commissioning Support Unit secure network and physically located at the storage address within the DARS application/agreement with the same underlying security controls.)

DATA LINKAGE
This DARS application is linked in association with the DARS application NIC-343042-X5T7Y-v0.3 and therefore the same pseudo key to be applied to all data releases in both applications.

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)
5. Maternity Services Data Set (MSDS)
6. Improving Access to Psychological Therapy (IAPT)
7. Child and Young People Health Service (CYPHS)
8. Community Services Data Set (CSDS)
9. Diagnostic Imaging Data Set (DIDS)
10. National Cancer Waiting Times Monitoring Data Set (CWT)
11. Civil Registries Data (CRD) (Births)
12. Civil Registries Data (CRD) (Deaths)
13. National Diabetes Audit (NDA)
14. Patient Reported Outcome Measures (PROMs)

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

Population Health - South, Central and West Commissioning Support Unit (CCG and Local Authority)

Pseudonymised SUS+, 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) and Patient Reported Outcome Measures (PROMs) only is held until points 2-8 are completed.
2. South, Central and West Commissioning Support Unit receives GP data. GP Data is received as follows:
- Identifiable GP data is submitted to South Central and West Commissioning Support Unit.
- The identifiable data lands in a ring-fenced area for GP data only.
- The GP data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.
- There is a Data Processing Agreement in place between the GP and South Central and West Commissioning Support Unit.
A specific named role within South Central and West Commissioning Support Unit acts on behalf of the GP.
- This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.
- Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted.
- South Central and West Commissioning Support Unit are then sent the pseudonymised GP data with the pseudo
algorithm specific to them.
3. South, Central and West Commissioning Support Unit also receive a flow of social care data. Social Care data is received in the following way:
- Identifiable:
- Identifiable social care data is submitted to South Central and West Commissioning Support Unit.
- The identifiable data lands in a ring-fenced area for social care data only within South Central and West Commissioning Support Unit.
- The social care data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.
- There is a Data Processing Agreement in place between the Local Authority and South Central and West Commissioning Support Unit. A specific named role, this role will be separate from any other roles that may lead to a conflict within South Central and West Commissioning Support Unit acts on behalf of the provider.
- This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.
- Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted.
- South Central and West Commissioning Support Unit are then sent the pseudonymised social care data with the pseudo algorithm specific to them.
4. Once the pseudonymised GP data and social care data is received, South, Central and West Commissioning Support Unit make a request to the DSCRO.
5. The DSCRO check the dates of the key generation
6. The DSCRO then send a mapping table to South, Central and West Commissioning Support Unit
7. South, Central and West Commissioning Support Unit then overwrite the organisation specific keys with the DSCRO key.
8. The mapping table is then deleted.
9. The DSCRO pass the Pseudonymised SUS+, 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) and Patient Reported Outcome Measures (PROMs) to South, Central and West Commissioning Support Unit for the addition of derived fields.
10. South, Central and West Commissioning Support Unit then pass the data to the CCG and Local Authority
11. GP and Social care data is then linked to the data sets listed within point 9. Only data listed within this data sharing agreement for the purpose of commissioning may be linked - data sets in point 9 and point 10

General Commissioning - South Central and West Commissioning Support Unit (CCG Only)
1. Pseudonymised SUS+, 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) and Patient Reported Outcome Measures (PROMs) only is securely transferred from the DSCRO to South Central and West Commissioning Support Unit.
2. South Central and West Commissioning Support Unit add derived fields by using existing data and link data to Local Provider data (received on application DARS-NIC-343042-X5T7Y) GP data and Social care 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. South Central and West Commissioning Support Uni then pass the processed, pseudonymised and linked data to the CCG.
4. Aggregation of required data for CCG management use will be completed by South Central and West Commissioning Support Uni or the CCG as instructed by the CCG.
5. 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

Optum Health Solutions (CCG only)
Commissioning - Data Processor: Optum Health Solutions (UK) Ltd
1. Pseudonymised SUS is securely transferred from Gloucestershire CCG to Optum Health Solutions (UK) Ltd. The data is decoupled from the other national datasets and sent as individual data flows
2. Optum Health Solutions link data to Local Provider data, GP data and Social care data received through application DARS-NIC-343042-X5T7Y and provide analysis to::
- Whole population segmentation to assess population health needs
- Prospective risk scoring for individuals to indicate the likelihood of future adverse events
- Predictive modelling to determine individuals at risk and an understanding of the drivers of risk
- Longitudinal analysis of intersegmental drift 􀍴􀀃identifying individuals who move between complexity classifications and the drivers of these transitions
- The production of individual-level theographs to identify gaps in care
3. GP and Social Care datasets are needed for the processing carried out by Optum to enhance the population health analytics beyond SUS and LPF's which contain only secondary care activity
4. Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the CCG.
5. Aggregated of required data for CCG management use will be completed by Optum Health Solutions (UK) Ltd 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.
7. Optum Health Solutions (UK) Ltd will only be in receipt of data and only be permitted to act as Data Processors for the period specified in the contract with NHS Gloucestershire CCG


DSfC - NHS Gloucestershire CCG - Comm — DARS-NIC-343042-X5T7Y

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 2020-01-16 — 2023-01-15 2020.03 — 2021.05.

Access method: Frequent Adhoc Flow, One-Off

Data-controller type: NHS GLOUCESTERSHIRE CCG, NHS GLOUCESTERSHIRE ICB - 11M

Sublicensing allowed: No

Datasets:

  1. Acute-Local Provider Flows
  2. Ambulance-Local Provider Flows
  3. Community-Local Provider Flows
  4. Demand for Service-Local Provider Flows
  5. Diagnostic Services-Local Provider Flows
  6. Emergency Care-Local Provider Flows
  7. Experience, Quality and Outcomes-Local Provider Flows
  8. Mental Health-Local Provider Flows
  9. Other Not Elsewhere Classified (NEC)-Local Provider Flows
  10. Population Data-Local Provider Flows
  11. Primary Care Services-Local Provider Flows
  12. Public Health and Screening Services-Local Provider Flows

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:
- 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

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 highlight 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 South, Central and West Commissioning Support Unit and Optum Health Solutions

This application allows the linkage of these data sets to the National datasets (Pseudonymised SUS+, 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) and Patient Reported Outcome Measures (PROMs)) the CCG receives on DARS-NIC-343158-Z2L4D. The same pseudo code will be applied by the DSCRO in order to enable this linkage.

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 readmission's, 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 bench-marking for evaluating progress in future years.

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 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:
- Patients at highest risk of admission
- Most expensive patients (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.

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 only be linked to datatsets specifically detailed within this Data Sharing Agreement and those listed in DARS agreement DARS-NIC-343158-Z2L4D
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:
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.Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set.

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

University Hospitals Bristol 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.

Black Box Software
- The Black Box is a software process with very limited access, restricted to only those who administer it.
- It is a set of logic that is hidden from users. It generates a re-pseudonymised output from the data that users enter.
- The purpose of the Black Box is to map the data such that the resulting pseudonymisation is the same as that used at the DSCRO.
- The Black Box works by calling upon a mapping table from the DSCRO and re-pseudonymising by switching the
pseudonym. No data is persisted in the Black Box.
The Black Box is held within a private part of South Central and West Commissioning Support Unit secure network and physically located at the storage address within the DARS application/agreement with the same underlying security controls.

DATA LINKAGE
This DARS application is linked in association with the DARS application NIC-343158-Z2L4D and therefore the same pseudo key to be applied to all data releases in both applications

The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:

1. 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

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

Data Processor - South, Central and West Commissioning Support Unit

1. Local Provider data only is held until points 2-8 are completed.
2. South, Central and West Commissioning Support Unit receives GP data (See GP Data section below for how this is received)
3. South, Central and West Commissioning Support Unit also receive a flow of social care data. (See Social Care Data section below for how this is received)
4. Once the pseudonymised GP data and social care data is received, South, Central and West Commissioning Support Unit make a request to the DSCRO.
5. The DSCRO check the dates of the key generation.
6. The DSCRO then send a mapping table to South, Central and West Commissioning Support Unit
7. South, Central and West Commissioning Support Unit then overwrite the organisation specific keys with the DSCRO key.
8. The mapping table is then deleted.
9. The DSCRO pass the local provider data securely to South, Central and West Commissioning Support Unit for the addition of derived fields.
10. South, Central and West Commissioning Support Unit then pass the data to the CCG.
11. GP and Social care data is then linked to the data sets listed within point 9. Data is also linked with Pseudonymised SUS+, 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) and Patient Reported Outcome Measures (PROMs) received on application DARS-NIC-343158-Z2L4D
12. The CCG analyse the data to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
13. The CCG pass Pseudonymised SUS, Local Provider Data, GP Primary Care data and Social Care data to Data Processor 4
- Optum Health Solutions (UK) Ltd.
14. Optum Health Solutions (UK) Ltd analyse the data and pass the data to the CCG.
15. Aggregation of required data for CCG management use will be completed by South, Central and West Commissioning
Support Unit as instructed by the CCG.
16. 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.

GP DATA
GP Data is received as follows
- Identifiable GP data is submitted to South Central and West Commissioning Support Unit.
- The identifiable data lands in a ring-fenced area for GP data only.
- The GP data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.
- There is a Data Processing Agreement in place between the GP and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the GP.
- This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.
- Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted.
- South Central and West Commissioning Support Unit are then sent the pseudonymised GP data with the pseudo
algorithm specific to them.

SOCIAL CARE DATA
Social Care data is received in one of the following 2 ways:
- Pseudonymised:
- Social Care data is pseudonymised within the provider using a pseudonymisation tool, different to that used by the DSCRO. The provider requests a pseudonymisation key from the DSCRO. The key can only be used once. The key is specific to the Local Authority and to that specific date.
- The pseudonymised data lands in a ring-fenced area for social care data only within South Central and West
Commissioning Support Unit.
- There is a Data Processing Agreement in place between the Provider and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the Provider.
- This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.
- The data is then passed into the non-ring fenced area with the pseudo algorithm specific to them.
- Identifiable:
- Identifiable social care data is submitted to South Central and West Commissioning Support Unit.
- The identifiable data lands in a ring-fenced area for social care data only within South Central and West Commissioning Support Unit.
- The social care data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.
- There is a Data Processing Agreement in place between the Local Authority and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the provider.
- This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.
- Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted.
- South Central and West Commissioning Support Unit are then sent the pseudonymised social care data with the pseudo algorithm specific to them.

Commissioning - Data Processor: Optum Health Solutions (UK) Ltd
1. Local Provider Data, GP Primary Care data and Social Care data is securely transferred from Gloucestershire CCG to Optum Health Solutions (UK) Ltd. The data is decoupled from the other national datasets and sent as individual data flows
2. Optum Health Solutions (UK) Ltd provide analysis to:
- Whole population segmentation to assess population health needs
- Prospective risk scoring for individuals to indicate the likelihood of future adverse events
- Predictive modelling to determine individuals at risk and an understanding of the drivers of risk
- Longitudinal analysis of intersegmental drift 􀍴􀀃identifying individuals who move between complexity classifications and the drivers of these transitions
- The production of individual-level theographs to identify gaps in care
3. Allowed linkage is between the datasets contained within point (1) above and pseudonymised SUS+ data received from application DARS-NIC-343158-Z2L4D. GP and Social Care datasets are needed for the processing carried out by Optum to enhance the population health analytics beyond SUS and LPF's which contain only secondary care activity
4. Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the CCG.
5. Aggregated of required data for CCG management use will be completed by Optum Health Solutions (UK) Ltd 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.
7. Optum Health Solutions (UK) Ltd will only be in receipt of data and only be permitted to act as Data Processors for the period specified in the contract with NHS Gloucestershire CCG


DSfC - NHS Gloucestershire CCG - RS & IV — DARS-NIC-342229-X7K0T

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Identifiable (Section 251 NHS Act 2006)

Legal basis: National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

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

Sensitive: Sensitive

When:DSA runs 2019-12-01 — 2022-11-30 2020.01 — 2021.05.

Access method: Frequent Adhoc Flow, One-Off

Data-controller type: NHS GLOUCESTERSHIRE CCG, NHS GLOUCESTERSHIRE ICB - 11M

Sublicensing allowed: No

Datasets:

  1. SUS for Commissioners
  2. Personal Demographic Service

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 CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation with be conducted by the 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.
Risk Stratification will be conducted by South, Central and West Commissioning Support Unit and Sollis Partnership Ltd.

Expected Benefits:

INVOICE VALIDATION
The invoice validation process supports the ongoing delivery of patient care across the NHS and the CCG region by:
1. Ensuring that activity is fully financially validated.
2. Ensuring that service providers are accurately paid for the patients treatment.
3. Enabling services to be planned, commissioned, managed, and subjected to financial control.
4. Enabling commissioners to confirm that they are paying appropriately for treatment of patients for whom they
are responsible.
5. Fulfilling commissioners duties to fiscal probity and scrutiny.
6. Ensuring full financial accountability for relevant organisations.
7. Ensuring robust commissioning and performance management.
8. Ensuring commissioning objectives do not compromise patient confidentiality.
9. Ensuring the avoidance of misappropriation of public funds.

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.

Outputs:

INVOICE VALIDATION
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient􀍛s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.

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. 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.

CCGs will be able to:
3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions.
4. Reduce hospital readmissions and targeting clinical interventions to high risk patients.
5. Identify patients at risk of deterioration and providing effective care.
6. Reduce in the difference in the quality of care between those with the best and worst outcomes.
7. Re-design care to reduce admissions.
8. Set up capitated budgets - budgets based on care provided to the specific population.
9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly.
11. Health needs assessments - identifying numbers of patients with specific health conditions or combination of
conditions.
12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost.
13. Production of Theographs - a visual timeline of a patients encounters with hospital providers.
14. Analyse based on specific diseases
In addition:
- The risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
- Record level output (pseudonymised) will be available for commissioners (of the CCG), pseudonymised at patient level.
Onward sharing of this data is not permitted.

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)

The DSCRO (part of NHS Digital) will apply National Opt-outs before any identifiable data leaves the DSCRO only for the purpose of Risk Stratification.

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.

(RS) The only identifier available in the data set is the NHS numbers. Any further identification of the patients will only be completed by the patient's clinician on their own systems for the purpose of direct care with a legitimate relationship.

ONWARD SHARING:
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.

Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set.

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 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.

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 Risk Stratification:
- Patients who are normally registered and/or resident within the Gloucestershire CCG region (including historical activity where the patient was previously registered or resident in another commissioner

For the purpose of Invoice Validation:
- Patients who are resident and/or registered within the CCG region.

University Hospitals Bristol 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.

Invoice Validation Data Processor(s) - NHS Gloucestershire 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 also receive backing data from the provider.
4. The CEfF conduct the following processing activities for invoice validation purposes:
a. Validating that the Clinical Commissioning Group are responsible for payment for the care of the individual by using SUS+ and/or provider backing flow data.
b. Once the provider backing information is received, it 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.
5. 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 - Data Processor(s) - South, Central and West Commissioning Support Unit and The Sollis
Partnership Ltd
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 South, Central and West Commissioning Support Unit, hosted, Sollis Partnership Ltd managed, processing area within the secure Data Centre.
3. Identifiable GP Data is securely sent from the GP system to South, Central and West Commissioning Support Unit hosted, Sollis Partnership Ltd managed, processing area within the secure Data Centre.
4. SUS+ data is linked to GP data in the risk stratification tool by Sollis Partnership Ltd within the South, Central and West Commissioning Support Unit hosted, Sollis Partnership Ltd managed, processing area
5. The Sollis Partnership Ltd access the risk stratification tool via remote role-based access controls and manage the risk stratification.
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. Once the Sollis Partnership Ltd has completed the processing within the South, Central and West Commissioning
Support Unit environment, 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.
8. A pseudonymised version of the risk stratification database will be securely transferred from the South, Central and West Commissioning Support Unit to the CCG data warehouse undertaken by the South, Central and West Commissioning Support Unit.

No data is stored at Sollis Partnership Ltd addresses. Sollis Partnership Ltd employees have remote access from the address provided to a secure area at South Central and West Commissioning Support Unit to identifiable data supplied by the DSCRO for the purpose of Risk Stratification only. Data is not taken from the secure server and is worked on within the CSU environment remotely.


DSfC - NHS Gloucestershire CCG - Comm, RS & IV — DARS-NIC-182332-B2F4M

Type of data: information not disclosed for TRE projects

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

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

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

Sensitive: Sensitive

When:DSA runs 2019-08-13 — 2022-08-12 2018.06 — 2021.05.

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

Data-controller type: NHS GLOUCESTERSHIRE CCG, NHS GLOUCESTERSHIRE ICB - 11M

Sublicensing allowed: No

Datasets:

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

Objectives:

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.
Invoice Validation with be conducted by the 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.
Risk Stratification will be conducted by South, Central and West Commissioning Support Unit and Sollis Partnership Ltd.

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)
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
• Ensuring we do what we should
§ 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 South, Central and West Commissioning Support Unit

Yielded Benefits:

Expected Benefits:

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

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

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

Outputs:

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

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

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

Processing:

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

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

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

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

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

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 for the purpose of Risk Stratification 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 Gloucestershire CCG is a Data Controller who also processes data.

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 CCG and from the providers – it does not flow through any other processors.


Black Box Software
- The Black Box is a software process with very limited access, restricted to only those who administer it.
- It is a set of logic that is hidden from users. It generates a re-pseudonymised output from the data that users enter.
- The purpose of the Black Box is to map the data such that the resulting pseudonymisation is the same as that used at the DSCRO.
- The Black Box works by calling upon a mapping table from the DSCRO and re-pseudonymising by switching the pseudonym. No data is persisted in the Black Box.
The Black Box is held within a private part of South Central and West Commissioning Support Unit secure network and physically located at the storage address within the DARS application/agreement with the same underlying security controls.)


Invoice Validation – Data Processor 3 – NHS Gloucestershire CCG
1. 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 – Data Processors 1 and 2 - South, Central and West Commissioning Support Unit and the Sollis Partnership Ltd
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 South, Central and West Commissioning Support Unit, hosted, Sollis Partnership Ltd managed, processing area within the secure Data Centre on N3.

3. Identifiable GP Data is securely sent from the GP system to South, Central and West Commissioning Support Unit hosted, Sollis Partnership Ltd managed, processing area within the secure Data Centre on N3.

4. SUS+ data is linked to GP data in the risk stratification tool by Sollis Partnership Ltd within the South, Central and West Commissioning Support Unit hosted, Sollis Partnership Ltd managed, processing area

5. The Sollis Partnership Ltd access the risk stratification tool via remote role-based access controls and manage the risk stratification.

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. Once the Sollis Partnership Ltd has completed the processing within the South, Central and West Commissioning Support Unit environment, 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.

8. A pseudonymised version of the risk stratification database will be securely transferred from the South, Central and West Commissioning Support Unit to the CCG data warehouse undertaken by the South, Central and West Commissioning Support Unit.

No data is stored at Sollis Partnership Ltd addresses. Sollis Partnership Ltd employees have remote access (via) N3 from the address provided to a secure area at South Central and West Commissioning Support Unit to identifiable data (with type 2 objections applied) supplied by the DSCRO for the purpose of Risk Stratification only. Data is not taken from the secure server and is worked on within the CSU environment remotely.



Commissioning – Data Processor 1 - South, Central and West Commissioning Support Unit
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)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:

Data Processor 1 - South, Central and West 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) and Diagnostic Imaging data (DIDS) only is held until points 2 – 8 are completed.

2. South, Central and West Commissioning Support Unit receives GP data. GP Data is received as follows:
o Identifiable GP data is submitted to South Central and West Commissioning Support Unit.
o The identifiable data lands in a ring-fenced area for GP data only.
o The GP data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.
o There is a Data Processing Agreement in place between the GP and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the GP.
o This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.
o Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted.
o South Central and West Commissioning Support Unit are then sent the pseudonymised GP data with the pseudo algorithm specific to them.

3. South, Central and West Commissioning Support Unit also receive a flow of social care data. Social Care data is received in one of the following 2 ways:
o Pseudonymised:
§ Social Care data is pseudonymised within the provider using a pseudonymisation tool, different to that used by the DSCRO. The provider requests a pseudonymisation key from the DSCRO. The key can only be used once. The key is specific to the Local Authority and to that specific date.
§ The pseudonymised data lands in a ring-fenced area for social care data only.
§ There is a Data Processing Agreement in place between the Provider and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the Provider.
§ This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.
§ The data is then passed into the non-ringfenced area with the pseudo algorithm specific to them.
o Identifiable:
§ Identifiable social care data is submitted to South Central and West Commissioning Support Unit.
§ The identifiable data lands in a ring-fenced area for social care data only.
§ The social care data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.
§ There is a Data Processing Agreement in place between the Local Authority and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the provider.
§ This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.
§ Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted.
§ South Central and West Commissioning Support Unit are then sent the pseudonymised social care data with the pseudo algorithm specific to them.

4. Once the pseudonymised GP data and social care data is received, South, Central and West Commissioning Support Unit make a request to the DSCRO.

5. The DSCRO check the dates of the key generation (Point 2d and 3aii/3biv).

6. The DSCRO then send a mapping table to South, Central and West Commissioning Support Unit

7. South, Central and West Commissioning Support Unit then overwrite the organisation specific keys with the DSCRO key.

8. The mapping table is then deleted.

9. The DSCRO 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), Community Services Data Set (CSDS) and Diagnostic Imaging (DIDS) securely to South, Central and West Commissioning Support Unit for the addition of derived fields, linkage of data sets and analysis

10. GP and Social care data is then linked to the data sets listed within point 9. Only data listed within this data sharing agreement for the purpose of commissioning may be linked - data sets in point 9 and point 10

11. South, Central and West Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments

12. Aggregation of required data for CCG management use will be completed by South, Central and West Commissioning Support Unit as instructed by the CCG.

13. 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.


Project 6 — DARS-NIC-49737-S2P1V

Type of data: information not disclosed for TRE projects

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

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:

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

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 the CCG.
The CCG are advised by the CEfF whether payment for invoices can be made or not.

Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides a forecast of future demand by identifying high risk 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 the CCG.

Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Diagnostic Imaging Data Set (DIDS)


The pseudonymised data is required to for the following purposes:
 Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
• Ensuring we do what we should
 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 the CCG.

Expected Benefits:


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

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

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

Outputs:


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

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

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

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)

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
1. 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. Checking the individual is registered to the Clinical Commissioning Group (CCG) by using the derived commissioner field in SUS 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. 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
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 the CCG, who hold the SUS data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to the CCG.
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 the CCG has completed the processing, access is available through the online system via a secure N3 connection to access the data pseudonymised at patient level.

Commissioning
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS
2. Local Provider Flows (received directly from providers)
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Maternity Services Data Set (MSDS)
7. Improving Access to Psychological Therapy (IAPT)
8. Child and Young People Health Service (CYPHS)
9. Diagnostic Imaging Data Set (DIDS)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor 1 – The CCG
1) Pseudonymised SUS, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to the CCG.
2) The CCG add derived fields, link data and 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
3) Allowed linkage is between the data sets contained within point 1.
4) Aggregation of required data for CCG management use will be completed by the CCG.
5) 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 7 — NIC-49737-S2P1V

Type of data: information not disclosed for TRE projects

Opt outs honoured: N, Y ()

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

Purposes: ()

Sensitive: Sensitive

When:2017.06 — 2017.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Children and Young People's Health Services Data Set
  2. Improving Access to Psychological Therapies Data Set
  3. Local Provider Data - Acute
  4. Local Provider Data - Ambulance
  5. Local Provider Data - Community
  6. Local Provider Data - Demand for Service
  7. Local Provider Data - Diagnostic Services
  8. Local Provider Data - Emergency Care
  9. Local Provider Data - Experience Quality and Outcomes
  10. Local Provider Data - Mental Health
  11. Local Provider Data - Other not elsewhere classified
  12. Local Provider Data - Population Data
  13. Local Provider Data - Primary Care
  14. Mental Health and Learning Disabilities Data Set
  15. Mental Health Minimum Data Set
  16. Mental Health Services Data Set
  17. SUS Accident & Emergency data
  18. SUS Admitted Patient Care data
  19. SUS Outpatient data
  20. Maternity Services Dataset
  21. SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
  22. SUS for Commissioners
  23. Public Health and Screening Services-Local Provider Flows
  24. Primary Care Services-Local Provider Flows
  25. Population Data-Local Provider Flows
  26. Other Not Elsewhere Classified (NEC)-Local Provider Flows
  27. Mental Health-Local Provider Flows
  28. Maternity Services Data Set
  29. Experience, Quality and Outcomes-Local Provider Flows
  30. Emergency Care-Local Provider Flows
  31. Diagnostic Services-Local Provider Flows
  32. Diagnostic Imaging Dataset
  33. Demand for Service-Local Provider Flows
  34. Community-Local Provider Flows
  35. Children and Young People Health
  36. Ambulance-Local Provider Flows
  37. Acute-Local Provider Flows
  38. SUS (Accident & Emergency, Inpatient and Outpatient data)
  39. Local Provider Data - Acute, Ambulance, Community, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Mental Health, Other not elsewhere classified, Population Data, Primary Care

Objectives:

Invoice Validation
As an approved Controlled Environment for Finance (CEfF), the CCG receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (b)/2013. The data is required for the purpose of invoice validation. The NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF.

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

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

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

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 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 misappropriation of public funds to ensure the ongoing delivery of patient care

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

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

Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, Integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.

Outputs:

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

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

Commissioning (Pseudonymised) – SUS and Local Flows
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals 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.

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

Processing:

Central Southern DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.
The CCG and any Data Processor will only have access to records of its own CCG. Access is limited to those administrative staff with authorised user accounts used for identification and authentication.

Invoice Validation
1. SUS Data is sent from the SUS Repository to Central Southern DSCRO
2. Central Southern 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. Checking the individual is registered to the 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 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 the CCG GP or resident within the CCG area via the NHS Digital Spine System
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
1. Identifiable SUS data is sent from the SUS Repository to Central Southern Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by Central Southern DSCRO and the data identifiable at the level of NHS number is transferred securely to the CCG, who hold the SUS data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to the CCG.
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. The CCG who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
7. Once the CCG has completed the processing, access is available through the online system via a secure N3 connection to access the data pseudonymised at patient level

Commissioning (Pseudonymised) – SUS and Local Flows
1. Central Southern Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. Central Southern DSCRO also obtains identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to the CCG for the addition of derived fields, linkage of data sets and analysis. Allowed linkage is between SUS data sets and local flows.
3. Aggregation of required data for CCG management use will be completed by the CCG.
4. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared where contractual arrangements are in place.

Commissioning (Pseudonymised) – Mental Health, MSDS, IAPT, CYPHS and DIDS
1. Central Southern Data Services for Commissioners Regional Office (DSCRO) obtains a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management and pseudonymisation of data is completed by Central Southern DSCRO and the pseudonymised data is then passed securely to the CCG for the addition of derived fields and analysis.
3. The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning.
4. Aggregation of required data for CCG management use will be completed by the CSU or the CCG as instructed by the CCG
5. 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 where contractual arrangements are in place.