NHS Digital Data Release Register - reformatted

NHS Southport And Formby CCG projects

1019 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).


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

DSfC - NHS Southport and Formby CCG; Comm. — NIC-130735-P4Q6M

Opt outs honoured: No - data flow is not identifiable, Yes - patient objections upheld (Excuses: Does not include the flow of confidential data)

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

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

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

When:DSA runs 2019-07 – 2022-06 2017.12 — 2021.05.

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

Data-controller type: NHS SOUTHPORT AND FORMBY CCG, NHS CHESHIRE AND MERSEYSIDE ICB - 01V

Sublicensing allowed: No

Datasets:

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

Type of data: Anonymised - ICO Code Compliant, Identifiable

Objectives:

Objective for processing:
This is a new application for the following purposes:
Commissioning
To use pseudonymised data to provide intelligence to support commissioning of health services. The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Diagnostic Imaging Data Set (DIDS)
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by -
- Arden and Greater East Midlands Commissioning Support Unit
- Midlands and Lancashire Commissioning Support Unit
- Advancing Quality Alliance (AQuA)
- The Academic Health Sciences Network

Yielded Benefits:

Expected Benefits:

Expected measurable benefits to health and/or social care, including target date(s):
Commissioning
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.

Outputs:

Specific outputs expected, including target date(s):
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.

Processing:

Processing activities:
Data must only be used as stipulated within this Data Sharing Agreement.
Data Processors must only act upon specific instructions from the Data Controller.
Data can only be stored at the addresses listed under storage addresses.
The Data Controller and any Data Processor will only have access to records of patients of residence and registration within the CCG. Access is limited to those substantive employees with authorised user accounts used for identification and authentication.
Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data.
No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.

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 – Arden and Greater East Midlands 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) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to Arden and Greater East Midlands Commissioning Support Unit.
2) Arden and Greater East Midlands Commissioning Support Unit add derived fields, link data and provide analysis.
3) Allowed linkage is between the data sets contained within point 1.
4) Arden and Greater East Midlands Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
5) Aggregation of required data for CCG management use will be completed by Arden and Greater East Midlands Commissioning Support Unit 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.

Data Processor 2 – Midlands and Lancashire 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) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to Midlands and Lancashire Commissioning Support Unit.
2) Midlands and Lancashire Commissioning Support Unit add derived fields, link data and provide analysis.
3) Allowed linkage is between the data sets contained within point 1.
4) Midlands and Lancashire Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
5) Aggregation of required data for CCG management use will be completed by Midlands and Lancashire Commissioning Support Unit 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

Data Processor 3 – Advancing Quality Alliance (AQuA) via Arden and Greater East Midlands Commissioning Support
1) Pseudonymised SUS, Local Provider data and Mental Health data (MHSDS, MHMDS, MHLDDS) only is securely transferred from the DSCRO to Arden and Greater East Midlands Commissioning Support.
2) Arden and Greater East Midlands Commissioning Support add derived fields, link data and provide analysis.
3) Allowed linkage is between the data sets contained within point 1.
1. Arden and Greater East Midlands Commissioning Support then pass the processed, pseudonymised and linked data to Advancing Quality Alliance (AQuA). Advancing Quality Alliance (AQuA) provide support for a range of quality improvement programmes including the NW Advancing Quality Programme. Advancing Quality Alliance (AQuA) identifies cohorts of patients within specific disease groups for further analysis to help drive quality improvements across the region.
4) Aggregation of required data for CCG management use will be completed by Advancing Quality Alliance (AQuA).
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

Data Processor 4 – The Academic Health Sciences Network via Arden and Greater East Midlands Commissioning Support
1) Pseudonymised SUS only is securely transferred from the DSCRO to Arden and Greater East Midlands Commissioning Support.
2) Arden and Greater East Midlands Commissioning Support add derived fields, link data and provide analysis.
3) Allowed linkage is between the data sets contained within point 1.
4) Arden and Greater East Midlands Commissioning Support then pass the processed, pseudonymised and linked data to The Academic Health Sciences Network. The Academic Health Sciences Network analyse the data to look at processes rather than patients, for example, A&E performance, process times, bed days as well as ‘deep dives’ to support clinical reviews for CCGs.
5) Aggregation of required data for CCG management use will be completed by The Academic Health Sciences Network.
6) Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared

Project 2 — NIC-197584-N4S9C

Opt outs honoured: No - data flow is not identifiable, Yes - patient objections upheld (Excuses: Does not include the flow of confidential data)

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 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. Other Not Elsewhere Classified (NEC)-Local Provider Flows
  18. Population Data-Local Provider Flows
  19. Primary Care Services-Local Provider Flows
  20. Public Health and Screening Services-Local Provider Flows
  21. SUS for Commissioners

Type of data:

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 CCG commissions services from a range of providers covering a wide array of services.
The CCG is part of the Cheshire and Merseyside Health and Care Partnership. This body is responsible for implementing large parts of the 5 year forward view from NHS England. The HCP is implementing several initiatives:

1. Putting the patient at the heart of the health system
2. Working across organisational boundaries to deliver care and including social care, public Health, providers and GPs as well as CCGs
3. Reviewing patient pathways to improve patient experience whilst reducing costs e.g. reduce the number of standard tests a patient may have and only have the ones they need
4. Planning the demand and capacity across the healthcare system across 6 CCGs to ensure we have the right buildings, services and staff to cope with demand whilst reducing the impact on costs
5. Working to prevent or capture conditions early as they are cheaper to treat
6. Introduce initiatives to change behaviours e.g. move more care into the community
7. Patient pathway planning for the above

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

This amendment is for NHS Southport and Formby CCG and KPMG 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 pseudonymised datasets. This work is key in developing a service change proposal for Southport and Ormskirk Acute Services Sustainability. The service change proposal will set out the options and next steps for how each organisation will agree and implement a clinically sustainable, operationally practical and financially affordable solution for their hospitals. Southport and Ormskirk Acute Services Sustainability is one of 5 collaborations feeding into the Cheshire and Merseyside Acute Sustainability and Cheshire and Merseyside Place Based Care Systems programmes. The work is led by Cheshire & Merseyside Health Partnership supported by KPMG, the NHS Transformation Unit (TU), and members include all Acute, Community, Mental Health providers, Clinical Commissioning Groups, NHS England and Local Authorities from the Cheshire & Merseyside area. The Service Change proposal must contain key elements to be considered by NHS England nationally (as per the requirements of the NHS England’s guidance - Planning, Assuring and Delivering Service Change for Patients, November 2015). Pertinent elements to this DARS amendment include:
• Analysis of the full range of potential service changes that can achieve the desired improvement in quality and outcomes;
• The development of a range of options based on the above analysis;
• An assessment against legal duties and obligations including the Public Sector Equality Duty11 (PSED) and the duty to have regard to the need to reduce inequalities;
• Any potential financial implications (capital spend, transactional or transitional funds, savings, core costs etc.) which may impact on the range of options taken forward;
• Analysis of demographic and other factors likely to influence future demand for the service;

To complete these elements above, detailed information is required:
Finance, activity and capacity modelling
Net Present Value (NPV) analysis and support with assumptions
What are the current patient flows and how do they change with each option proposed?
What does the preferred option look like at system cost level and an individual provider level?
Is there a knock-on impact on neighbouring providers?
Is the preferred option affordable?

Processing for this activity will be conducted by KPMG LLP.

Expected Benefits:

Commissioning
Sharing this data is crucial to producing a service change proposal for Southport and Ormskirk Acute Services Sustainability. The service change proposal will set out the options and next steps for how each organisation will agree and implement a clinically sustainable, operationally practical and financially affordable solution for their hospitals:
• Impacts will be identified over a five year forecast period
• Finance impacts will cover both Southport & Ormskirk and the wider Cheshire & Merseyside footprint
• Capacity requirements will include beds, theatres and staffing (by site for S&O)
• Knock on impacts will include activity, capacity and finance for other C&M providers, and activity only for out of area providers

Outputs:

Commissioning
SUS Data sets: A&E, Inpatients, Outpatients
CCG: 01V NHS Southport & Formby CCG
Time Period: 2015/16, 2016/17, 2017/18 financial years

Processing:

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

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

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

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

Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data.
All access to data is managed under Roles-Based Access Controls
No patient level data will be linked other than as specifically detailed within this agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.
NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)
1) North West Data Services for Commissioning Regional Office (DSCRO) receive a national feed of data for NHS Southport and Formby CCG from SUS
2) Data quality management of data is completed by the DSCRO and the data is then passed to Arden and GEM CSU for the addition of derived fields, linkage of relevant data sets and analysis.
3) Arden and GEM CSU then pass the processed, pseudonymised data to NHS Southport and Formby CCG. An extract of SUS data will be made, using only fields relevant to the project (see below, specific outputs) and securely transferred (via SFTP) to KPMG
4) KPMG will use the data to see patient journeys for pathway re-design and de-commissioning. Data will be fed into modelling tools with clinically approved assumptions allowing commissioners and providers (working under the Southport and Ormskirk Acute Services Sustainability group, a sub group of the Cheshire & Merseyside Health Partnership Acute Sustainability programme) understand a baseline ‘do nothing’ position, and model a number of options for clinical review (as detailed above) and ultimately contribute to the service change proposal
4) Patient level data will not be shared outside of the CCG other than to KPMG Health and only for the specified project they have been commissioned to undertake. Any other data shared externally will consist of aggregated reports only

DSfC - NHS Southport & Formby CCG, RS — NIC-47139-R5G3C

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

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

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

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

When:DSA runs 2019-07 – 2022-07 2017.06 — 2017.05.

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

Data-controller type: NHS SOUTHPORT AND FORMBY CCG, NHS CHESHIRE AND MERSEYSIDE ICB - 01V

Sublicensing allowed: No

AGD/predecessor discussions: igardminutes-22ndoctober2020final.pdf, IGARD_Minutes_20.04.17.pdf, IGARD Minutes - 26 January 2023 final.pdf, IGARD Minutes - 26 August 2021 final.pdf, IGARD Minutes - 29 July 2021 - FINAL.pdf, igard-minutes---6-aug-2020-final.pdf, igardminutes-21stjanuary2021final.pdf, igardminutes-14thjanuary2021final.pdf

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 - Public Health & Screening services
  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. SUS (Accident & Emergency, Inpatient and Outpatient data)
  24. 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

Type of data: Identifiable

Objectives:

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

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.

Pseudonymised – Mental Health, MSDS, 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 the HSCIC will not be national data, but only that data relating to the specific locality of interest of the applicant.

Yielded Benefits:

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.

Expected Benefits:

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

Pseudonymised – SUS and Local Flows
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, 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) flows.
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
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.

Pseudonymised – MHSDS, MHMDS, MHLDDS, MSDS, 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 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC) flows.
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:

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 risk stratification presents pseudonymised data to the GPs. GPs are able to re-identify information only for their own patients for the purpose of direct care.
2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
3. Record level output will be available for commissioners pseudonymised at patient level and aggregated at patient level.
Pseudonymised – SUS and Local Flows
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of acute / community / mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports include high flyers.

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

Processing:

Prior to the release of identifiable data by North West DSCRO, Type 2 objections will be applied and the relevant patient’s data redacted.
Risk Stratification
Data Processor 1 – Arden & GEM CSU:
1. SUS Data is sent from the SUS Repository to North West Data Services for Commissioners Regional Office (DSCRO) to the data processor.
2. SUS data identifiable at the level of NHS number regarding hospital admissions, A&E attendances and outpatient attendances is delivered securely from North West DSCRO to the data processor.
3. Data quality management and standardisation of data is completed by North West DSCRO and the data identifiable at the level of NHS number is transferred securely to Arden & GEM CSU, who hold the SUS data within the secure Data Centre on N3.
4. Identifiable GP Data is securely sent from the GP system to Arden & GEM CSU.
5. SUS data is linked to GP data in the risk stratification tool by the data processor.
6. Arden & GEM CSU who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
7. Once Arden & GEM CSU has completed the processing, the data is passed to the CCG in pseudonymised form at patient level and as aggregated reports.

Data Processor 2 – Midlands & Lancashire CSU:
1. SUS Data is sent from the SUS Repository to North West Data Services for Commissioners Regional Office (DSCRO) to the data processor.
2. SUS data identifiable at the level of NHS number regarding hospital admissions, A&E attendances and outpatient attendances is delivered securely from North West DSCRO to the data processor.
3. Data quality management and standardisation of data is completed by North West DSCRO and the data identifiable at the level of NHS number is transferred securely to Arden & GEM CSU, who hold the SUS data within the secure Data Centre on N3.
4. Identifiable GP Data is securely sent from the GP system to Arden & GEM CSU.
5. SUS data is linked to GP data in the risk stratification tool by the data processor.
6. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The risk stratification presents pseudonymised data to the GPs. GPs are able to re-identify information only for their own patients for the purpose of direct care.
7. Arden & GEM CSU who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
8. Data identifiable at the level of NHS number is transferred securely to Midlands & Lancashire CSU who apply the data to the BI tool to analyse and produce reports.
9. Once Midlands & Lancashire CSU has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level and aggregated reports.
10. 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.

Pseudonymised – SUS and Local Flows
Data Processor 1 – Arden & GEM CSU:
1. North West Data Services for Commissioners Regional Office (DSCRO) receives a flow of SUS identifiable data for the CCG from the SUS Repository. North West DSCRO also receives 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 Arden & GEM CSU for the addition of derived fields, linkage of data sets and analysis.
3. Arden & GEM CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4. Patient level data will not be shared outside of the CCG 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.
Data Processor 2 – Midlands & Lancashire CSU:
1. North West Data Services for Commissioners Regional Office (DSCRO) receives a flow of SUS identifiable data for the CCG from the SUS Repository. North West DSCRO also receives identifiable local provider data for the CCG directly from Providers.
2. The identifiable SUS data and identifiable local provider flow data is securely transferred from North West DSCRO to Central Midlands DSCRO.
3. Data quality management and pseudonymisation of data is completed by Central Midlands DSCRO and the pseudonymised data is then passed securely to Midland & Lancashire CSU for the addition of derived fields, linkage of data sets and analysis.
5. Midland & Lancashire CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide.
Data Processor 3 - AQuA
1. North West Data Services for Commissioners Regional Office (DSCRO) receives a flow of SUS identifiable data for the CCG from the SUS Repository. North West DSCRO also receives identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by North West DSCRO and the pseudonymised data is then passed securely to Arden & GEM CSU for the addition of derived fields, linkage of data sets and analysis.
3. Arden & GEM CSU then passes the pseudonymised data securely to AQuA to provide support for a range of quality improvement programmes including the NW Advancing Quality Programme. AQuA identifies cohorts of patients within specific disease groups for further analysis to help drive quality improvements across the region.
4. AQuA produces aggregate reports only with small number suppression in line with the HES analysis guide. Only aggregate reports are sent to the CCG.
Data Processor 4 – Academic Health Sciences Network (Utilisation Management Team)
1. North West Data Services for Commissioners Regional Office (DSCRO) receives a flow of SUS identifiable data for the CCG from the SUS Repository. North West DSCRO also receives identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by North West DSCRO and the pseudonymised data is then passed securely to Arden & GEM CSU for the addition of derived fields, linkage of data sets and analysis.
3. Arden & GEM CSU then passes the pseudonymised data securely to the Academic Health Service (Utilisation Management Team) (AHSN UMT)
4. The AHSN UMT receives pseudonymised SUS data for Greater Manchester patients. They analyse the data to look at processes rather than patients, for example, A&E performance, process times, bed days as well as ‘deep dives’ to support clinical reviews for CCGs.
AHSN UMT produces aggregate reports only with small number suppression in line with the HES analysis guide. Only aggregate reports are sent to the CCG.
Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS
Data Processor 1 – Arden & GEM CSU:
1. North West Data Services for Commissioners Regional Office (DSCRO) receives a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS) and Maternity (MSDS). North West DSCRO also receive a flow of pseudonymised patient level data for each CCG for Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes
2. The pseudonymised data is securely transferred from North West DSCRO to Central Midlands DSCRO.
3. Data quality management and pseudonymisation of data is completed by Central Midlands DSCRO and the pseudonymised data is then passed securely to Arden & GEM CSU for the addition of derived fields, linkage of data sets and analysis.
4. Arden & GEM CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
5. The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning
6. Aggregation of required data for CCG management use can be completed by the CSU or the CCG
7. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide.
Data Processor 2 – Midlands & Lancashire CSU:
1. North West Data Services for Commissioners Regional Office (DSCRO) receives a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS) and Maternity (MSDS). North West DSCRO also receive a flow of pseudonymised patient level data for each CCG for Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes
2. The identifiable SUS data and identifiable local provider flow data is securely transferred from North West DSCRO to Central Midlands DSCRO.
3. Data quality management and pseudonymisation of data is completed by Central Midlands DSCRO and the pseudonymised data is then passed securely to Midland & Lancashire CSU for the addition of derived fields, linkage of data sets and analysis.
4. Midland & Lancashire CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
5. Aggregation of required data for CCG management use can be completed by the CSU or the CCG
6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide.
Data Processor 3 - Advancing Quality Alliance (AQuA)
1. North West Data Services for Commissioners Regional Office (DSCRO) receives a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS).
2. Data quality management and pseudonymisation of data is completed by North West DSCRO and the pseudonymised data is then passed securely to Arden & GEM CSU for the addition of derived fields, linkage of data sets and analysis.
3. Arden & GEM CSU then passes the pseudonymised data securely to Advancing Quality Alliance (AQuA).
4. AQuA receives pseudonymised SUS data for Greater Manchester patients. They analyse the data to look at processes rather than patients, for example, A&E performance, process times, bed days as well as ‘deep dives’ to support clinical reviews for CCGs.
5. AQuA produces aggregate reports only with small number suppression in line with the HES analysis guide. Only aggregate reports are sent to the CCG.