NHS Digital Data Release Register - reformatted

NHS Tower Hamlets Ccg projects

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


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

Project 1 — DARS-NIC-95867-F5F0L

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - data flow is not identifiable (Does not include the flow of confidential data)

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

Purposes: ()

Sensitive: Sensitive

When:2019.01 — 2019.04.

Access method: Frequent Adhoc Flow

Data-controller type:

Sublicensing allowed:

Datasets:

  1. 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 pseudonymised.

Invoice Validation will be conducted by NHS North East London CSU
The CCG are advised by NHS North East London CSU whether payment for invoices can be made or not.

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

The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.


Processing for commissioning will be conducted by North East London CSU & Queen Mary University

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

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

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

Processing:

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

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

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

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

All access to data is managed under Roles-Based Access Controls

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

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

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

All access to data is auditable by NHS Digital.

Invoice Validation
1. Pseudonymised SUS+ Data is obtained from the SUS+ Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the North East London CSU.
3. North East London CSU carry out the following processing activities within the CEfF 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. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance. 
4. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between North East London CSU CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.

Commissioning
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS+
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor 1 – North East London CSU
1. Pseudonymised SUS+ only is securely transferred from the DSCRO to North East London CSU.
2. North East London CSU add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
3. Allowed linkage is between the data sets contained within point 1.
4. North East London CSU then pass the processed, pseudonymised and linked data to the CCG.
5. Aggregation of required data for CCG management use will be completed by North East London CSU or the CCG as instructed by the CCG.
6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.

Data Processor 2 – Queen Mary University of London
1. Data Services for Commissioners Regional Office (DSCRO) North East London obtains a flow of SUS identifiable data for the CCG from the SUS Repository.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North East London CSU.
3. North East London CSU then pass the processed, pseudonymised SUS data to The Clinical Effectiveness Group within Queen Mary University of London (Data Processor 2).
4. Queen Mary University of London process the data on behalf of the CCG to evaluate clinical outcomes and recommend best practice with regard to long term conditions and other health priorities within the area and securely transfer the pseudonymised patient level output to 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 in line with the HES analysis guide can be shared where contractual arrangements are in place.


Project 2 — NIC-95867-F5F0L

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. Local Provider Data - Public Health & Screening services
  21. Maternity Services Dataset
  22. SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
  23. SUS for Commissioners
  24. Public Health and Screening Services-Local Provider Flows
  25. Primary Care Services-Local Provider Flows
  26. Population Data-Local Provider Flows
  27. Other Not Elsewhere Classified (NEC)-Local Provider Flows
  28. Mental Health-Local Provider Flows
  29. Maternity Services Data Set
  30. Experience, Quality and Outcomes-Local Provider Flows
  31. Emergency Care-Local Provider Flows
  32. Diagnostic Services-Local Provider Flows
  33. Diagnostic Imaging Dataset
  34. Demand for Service-Local Provider Flows
  35. Community-Local Provider Flows
  36. Children and Young People Health
  37. Ambulance-Local Provider Flows
  38. Acute-Local Provider Flows

Objectives:

Invoice Validation

As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data anonymised in line with the ICO Code of Practice and using the local identifiers to undertake invoice validation on behalf of the CCG. The CCG are advised by the CSU whether payment for invoices can be made or not.


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 primarily using Pseudonymised data.
For the purposes of direct care, GPs have the ability to access SUS data identifiable at the level of NHS number under S.251 CAG 7-04(a)/2013 following explicit action that initiates a re-identification.

Commissioning (Pseudonymised) – SUS, Local Flows, 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 Services (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.

Commissioning (Pseudonymised) – SUS
To use pseudonymised data to provide intelligence to support commissioning of health services, using Queen Mary University of London as Data Processor. 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 SUS data.
The CCGs commission services from a range of providers covering a wide array of services. The SUS data flow requested supports the commissioned activity of one or more providers.

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.
Data may only be used for the purposes outlined within the Data Sharing Agreement and must not be used for any other purpose.

Expected Benefits:

Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care
Risk Stratification
Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised:
1. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
3. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
4. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
5. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
All of the above lead to improved patient experience through more effective commissioning of services.

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

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. In the first instance, GPs have access to pseudonymised patient level data of their own patients however they also have the ability to access NHS number of their patients following explicit action that initiates a re-identification of the pseudonymised NHS number. 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) SUS, Local Flows, 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:

The CCG and any Data Processor will only have access to records of its own CCG. Access is limited to substantive employees with authorised user accounts used for identification and authentication on a need to know basis only.
Invoice Validation
CEfF (a) - Newham CCG and Tower Hamlets CCG:
1. SUS Data is obtained from the SUS Repository to North East London Data Services for Commissioners Regional Office (DSCRO).
2. North East London DSCRO de-identifies the data and pushes a one-way data flow of SUS data anonymised in line with the ICO Code of Practice and using the local identifiers into the Controlled Environment for Finance (CEfF) in the North East London CSU.
3. The CSU carry out the following processing activities within the CEfF for invoice validation purposes:
a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by the HSCIC to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
Identifiable data supplied by the provider will only flow when SUS data is not available for a particular service. The identifiable data cannot be used to re-identify the Pseudonymised SUS data provided for invoice validation.
4. The CCG are notified that the invoice has been validated and can be paid.
5. Any discrepancies or non-validated invoices are investigated and resolved between the CSU CEfF team and the provider using the local patient ID and local event ID. The local identifiers must only be used for the purpose of contract monitoring to ensure sound financial management, challenge of costs or data between commissioner and provider and the prevention and possible investigation of any fraudulent or potentially fraudulent acts.
6. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.

CEfF (b) – City and Hackney CCG only:
1. SUS Data is obtained from the SUS Repository by DSCRO North East London.
2. DSCRO North East London 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 the HSCIC 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.
iii. The health care provided should be paid by the CCG in line with CCG guidance. 
4. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved

Risk Stratification
1. Identifiable SUS data is obtained from the SUS Repository by North East London Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management, standardisation and pseudonymisation of the data is completed by North East London DSCRO and the pseudonymised record level data is transferred securely to North East London CSU, who hold the SUS data within the secure Data Centre on N3.
3. GP Data identifiable at the level of NHS number is securely sent from the GP system to North East London CSU.
4. North East London CSU pseudonymises the GP data using the same pseudo ID as SUS, but without requiring the NHS Number to be stored within the CSU. The pseudonymisation process uses a lookup table containing a salted NHS Number hash and Pseudo Id only (it does not contain NHS Number).
5. The lookup table consists of hash values for all possible NHS Numbers and their pseudonyms. The NHS Number hash is calculated by adding a salt (a secret string of characters) to the NHS Number and applying a cryptographic hash function to get the final hash value. Each NHS Number has a unique hash value. The hash function is non-reversible, i.e. for given the hash value it is not possible to mathematically calculate the input value.
6. The lookup table will only be used to pseudonymise GP Data for the purpose of Risk Stratification
7. The pseudonymised GP and SUS data is loaded into the risk stratification tool where the data is linked.
8. 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 GPs access the pseudonymised NHS number of their own patients however, following an explicit action, they also have the ability to access the NHS Number of those patients for the purpose of direct care. The GP request for the re-identification of a pseudonymised NHS Number is passed to the North East London DSCRO which returns the NHS Number.
Any further identification of the patients will be completed by the GP on their own systems, using the revealed NHS Numbers.
9. North East London 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.
10. Once North East London CSU has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level.

Commissioning (Pseudonymised) SUS
Data Processor 1 – NEL CSU
1. North East London Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. North East London DSCRO also obtains identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North East London CSU for the addition of derived fields, linkage of data sets and analysis. Allowed linkage is between SUS data sets and local flows.
3. North East London CSU then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
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 in line with the HES analysis guide can be shared where contractual arrangements are in place.

Data Processor 2 – Queen Mary University of London
1. Data Services for Commissioners Regional Office (DSCRO) North East London obtains a flow of SUS identifiable data for the CCG from the SUS Repository.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North East London CSU.
3. North East London CSU then pass the processed, pseudonymised SUS data to The Clinical Effectiveness Group within Queen Mary University of London (Data Processor 2).
4. Queen Mary University of London process the data on behalf of the CCG to evaluate clinical outcomes and recommend best practice with regard to long term conditions and other health priorities within the area and securely transfer the pseudonymised patient level output to 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 in line with the HES analysis guide can be shared where contractual arrangements are in place.

Commissioning (Pseudonymised) – SUS, Local Flows, Mental Health, MSDS, IAPT, CYPHS and DIDS
1. Data Services for Commissioners Regional Office (DSCRO) North East London obtains a flow of SUS identifiable data for the CCG from the SUS Repository and identifiable local provider data directly from Providers.
2. Data Services for Commissioners Regional Office (DSCRO) North East London 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.
3. Data quality management and pseudonymisation of data is completed by DSCRO North East London and the pseudonymised data is then passed securely to North East London CSU for the addition of derived fields, linkage and analysis.
4. North East London CSU then pass the processed, pseudonymised and linked data to the CCG.
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 will be completed by the CSU or the CCG as instructed by the CCG
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.


Project 3 — NIC-55701-V2H8K

Type of data: information not disclosed for TRE projects

Opt outs honoured: N ()

Legal basis: Health and Social Care Act 2012

Purposes: ()

Sensitive: Sensitive

When:2016.12 — 2017.02.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. SUS (Accident & Emergency, Inpatient and Outpatient data)
  2. Local Provider Data - Acute, Ambulance, Community, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Mental Health, Other not elsewhere classified, Population Data, Primary Care
  3. Mental Health Minimum Data Set
  4. Mental Health and Learning Disabilities Data Set
  5. Mental Health Services Data Set
  6. Improving Access to Psychological Therapies Data Set
  7. Children and Young People's Health Services Data Set

Objectives:

Invoice Validation
As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data anonymised in line with the ICO Code of Practice and using the local identifiers to undertake invoice validation on behalf of the CCG. The CCG are advised by the CSU whether payment for invoices can be made or not.

Commissioning (Pseudonymised) – SUS, Local Flows, 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 Services (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.

Commissioning (Pseudonymised) – SUS
To use pseudonymised data to provide intelligence to support commissioning of health services, using Queen Mary University of London as Data Processor. 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 SUS data.
The CCGs commission services from a range of providers covering a wide array of services. The SUS data flow requested supports the commissioned activity of one or more providers.

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.
Data may only be used for the purposes outlined within the Data Sharing Agreement and must not be used for any other purpose.

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

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

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

Commissioning (Pseudonymised) – SUS and Local Flows
Para 3d)
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) SUS, Local Flows, 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:

North East London DSCRO 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 substantive employees with authorised user accounts used for identification and authentication on a need to know basis only.
Invoice Validation
1. SUS Data is obtained from the SUS Repository to North East London Data Services for Commissioners Regional Office (DSCRO).
2. North East London DSCRO de-identifies the data and pushes a one-way data flow of SUS data anonymised in line with the ICO Code of Practice and using the local identifiers into the Controlled Environment for Finance (CEfF) in the North East London CSU.
3. The CSU carry out the following processing activities within the CEfF for invoice validation purposes:
a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by the HSCIC to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
Identifiable data supplied by the provider will only flow when SUS data is not available for a particular service. The identifiable data cannot be used to re-identify the Pseudonymised SUS data provided for invoice validation.
4. The CCG are notified that the invoice has been validated and can be paid.
5. Any discrepancies or non-validated invoices are investigated and resolved between the CSU CEfF team and the provider using the local patient ID and local event ID. The local identifiers must only be used for the purpose of contract monitoring to ensure sound financial management, challenge of costs or data between commissioner and provider and the prevention and possible investigation of any fraudulent or potentially fraudulent acts.
6. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.

Commissioning (Pseudonymised) SUS
Data Processor 1 – NEL CSU
1. North East London Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. North East London DSCRO also obtains identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North East London CSU for the addition of derived fields, linkage of data sets and analysis. Allowed linkage is between SUS data sets and local flows.
3. North East London CSU then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
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 in line with the HES analysis guide can be shared where contractual arrangements are in place.

Data Processor 2 – Queen Mary University of London
1. Data Services for Commissioners Regional Office (DSCRO) North East London obtains a flow of SUS identifiable data for the CCG from the SUS Repository.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North East London CSU.
3. North East London CSU then pass the processed, pseudonymised SUS data to The Clinical Effectiveness Group within Queen Mary University of London (Data Processor 2).
4. Queen Mary University of London process the data on behalf of the CCG to evaluate clinical outcomes and recommend best practice with regard to long term conditions and other health priorities within the area and securely transfer the pseudonymised patient level output to 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 in line with the HES analysis guide can be shared where contractual arrangements are in place.

Commissioning (Pseudonymised) – SUS, Local Flows, Mental Health, MSDS, IAPT, CYPHS and DIDS
1. Data Services for Commissioners Regional Office (DSCRO) North East London obtains a flow of SUS identifiable data for the CCG from the SUS Repository and identifiable local provider data directly from Providers.
2. Data Services for Commissioners Regional Office (DSCRO) North East London 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.
3. Data quality management and pseudonymisation of data is completed by DSCRO North East London and the pseudonymised data is then passed securely to North East London CSU for the addition of derived fields, linkage and analysis.
4. North East London CSU then pass the processed, pseudonymised and linked data to the CCG.
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 will be completed by the CSU or the CCG as instructed by the CCG
7. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared where contractual arrangements are in place.