NHS Digital Data Release Register - reformatted

NHS Camden Ccg projects

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


🚩 NHS Camden Ccg was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Camden 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 Camden CCG; RS. — DARS-NIC-162895-N9K8S

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Section 251, Does not include the flow of confidential data)

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

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

Sensitive: Sensitive

When:DSA runs 2018-12-21 — 2021-12-20 2018.06 — 2020.03.

Access method: Frequent adhoc flow, Frequent Adhoc Flow

Data-controller type: NHS NORTH CENTRAL LONDON CCG, NHS NORTH CENTRAL LONDON ICB - 93C

Sublicensing allowed: No

Datasets:

  1. SUS for Commissioners

Objectives:

This is a new application for the following purposes:

Risk Stratification
This is an application to use SUS data identifiable at the level of pseudonymised/encrypted NHS number for the purpose of Risk Stratification. Camden CCG Risk Stratification provides a forecast of future demand by identifying high risk groups as part of its population health management. This enables commissioners to initiate proactive management plans for cohorts / categories of clinical treatment that are potentially high service users.
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.
No data used for risk stratification will be re-identified under this agreement as this is being used for population health planning element of stratification only.
Reports and outputs are only provided in aggregate formats. These are then used by Camden CCG to support population healthcare management for commissioning purposes which may include sharing of these with GP services and other organisations to support care re-design.

Yielded Benefits:

Expected Benefits:

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.
(b) 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.

Risk Stratification
Risk stratification promotes improved case management in health care and will lead to the following benefits being realised:
1) Improved planning by better understanding population healthcare management flows through the whole 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.

Outputs:

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.
(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.

Risk Stratification
1) As part of the risk stratification processing activity detailed above, no access is available to re-identify any individual patient information.
2) Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk with no identifiers

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

Processing:

• North East London will apply the pseudonumisation algorithm (Mede Tool)
• GP Data will be pseudonymised algorithm (Mede Tool)
• CNWL Community data (Flagging known to particular services) will be pseudonymised at the provider level using the pseudonumisation algorithm.
Risk Stratification
1. Identifiable SUS data is obtained from the SUS Repository to Data Services for Commissioners Regional Office (DSCRO) North East London.
2. Data quality management and standardisation of data is completed by DSCRO North East London and the data identifiable at the level of pseudonymised/encrypted NHS number is transferred securely to Camden CCG, via North East London CSU’s (Data Processor 1) download area, who hold the SUS data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to CCG Risk Stratification tool via the GP managed pseudonymisation server.
4. SUS data is linked to GP data in the risk stratification tool.
5. Camden CCG who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
6. Once the CCG Risk stratification tool has completed the processing, the CCG insights services can access the online system via a secure N3 connection to access the data anonymised at patient level.


Project 2 — NIC-162895-N9K8S?

Type of data: information not disclosed for TRE projects

Opt outs honoured: Y

Legal basis: Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Sensitive

When:2017.12 — 2018.02.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)


Project 3 — NIC-41632-C6X9D

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. Local Provider Data - Acute
  2. Local Provider Data - Ambulance
  3. Local Provider Data - Community
  4. Local Provider Data - Demand for Service
  5. Local Provider Data - Diagnostic Services
  6. Local Provider Data - Emergency Care
  7. Local Provider Data - Experience Quality and Outcomes
  8. Local Provider Data - Mental Health
  9. Local Provider Data - Other not elsewhere classified
  10. Local Provider Data - Population Data
  11. Local Provider Data - Primary Care
  12. Mental Health and Learning Disabilities Data Set
  13. Mental Health Minimum Data Set
  14. Mental Health Services Data Set
  15. SUS Accident & Emergency data
  16. SUS Admitted Patient Care data
  17. SUS Outpatient data
  18. Local Provider Data - Public Health & Screening services
  19. SUS (Accident & Emergency, Inpatient and Outpatient data)
  20. Local Provider Data - Acute, Ambulance, Community, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Mental Health, Other not elsewhere classified, Population Data, Primary Care

Objectives:

Invoice Validation
As an approved Controlled Environment for Finance (CEfF), the 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
This is an application to use SUS data identifiable at the level of NHS number for the purpose of Risk Stratification. Camden CCG Risk Stratification provides a forecast of future demand by identifying high risk groups as part of its population health management. This enables commissioners to initiate proactive management plans for cohorts / categories of clinical treatment that are potentially high service users.

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

Commissioning (Pseudonymised) – Mental Health and Maternity
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)
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.

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

Expected Benefits:

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

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

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

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

Outputs:

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

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

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

Commissioning (Pseudonymised) – Mental Health and Maternity
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 those administrative staff with authorised user accounts used for identification and authentication.
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) using the local identifiers and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. 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.
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.

Risk Stratification
1. Identifiable SUS data is obtained from the SUS Repository to North East London Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by North East London DSCRO and the data identifiable at the level of NHS number is transferred securely to the North East London CSU for landing only.
3. North East London CSU then securely transfer the data to the CCG, who hold the SUS data within the secure Data Centre on N3. Data is deleted once the CCG has received the data.
4. The CCG pseudonymises the identifiable SUS data within the CCG.
5. Identifiable GP Data is securely sent from the GP system to the CCG. The identifiabl;e GP data is pseudonymised within the CCG.
6. Pseudonymised SUS data is linked to GP data in the risk stratification tool by the data processor.
7. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor. GPs are able to access re-identified data only where the toolhighlights 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.
8. The CCG who hosts the risk stratification system that holds SUS data is limited to those substantive employees with authorised user accounts used for identification and authentication.
9. Once the CCG has completed the processing, access is available through the online system via a secure N3 connection to access the data pseudonymised at patient level.

Commissioning (Pseudonymised) – SUS and Local Flows
1. 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 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) – Mental Health and Maternity
1. North East London Data Services for Commissioners Regional Office (DSCRO) obtains a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS) and Maternity (MSDS) for commissioning purposes.
2. Data quality management and pseudonymisation of data is completed by North East London DSCRO and the pseudonymised data is then passed securely to North East London CSU for the addition of derived fields and analysis.
3. North East London CSU then pass the processed, pseudonymised data to the CCG.
4. The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning.
5. Aggregation of required data for CCG management use will be completed 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 where contractual arrangements are in place.