NHS Digital Data Release Register - reformatted
NHS Greater Manchester ICB - 01y projects
87 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).
DSfC - NHS Tameside and Glossop CCG - IV — NIC-180025-W6S0Z
Opt outs honoured: Yes - patient objections upheld, No - DSfC for Invoice Validation Purposes (Excuses: Section 251, Section 251 NHS Act 2006)
Legal basis: National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive
When:DSA runs 2019-02 – 2022-02 2018.10 — 2021.05.
Access method: Frequent Adhoc Flow, One-Off
Data-controller type: NHS TAMESIDE AND GLOSSOP CCG, NHS GREATER MANCHESTER ICB - 01Y
Sublicensing allowed: No
AGD/predecessor discussions: igard-minutes-14th-february-2019-final.pdf
Datasets:
- SUS for Commissioners
Type of data: Identifiable
Objectives:
Invoice Validation
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so they are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets and will not be used further.
Invoice Validation with be conducted by NHS Tameside and Glossop CCG
The CCG are advised by their inhouse team whether payment for invoices can be made or not
Yielded Benefits:
Expected Benefits:
Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care
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
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 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.
Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the CCG and from the providers – it does not flow through any other processors.
Invoice Validation
1. Identifiable SUS+ Data is obtained from the SUS+ Repository by the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) located in the CCG.
3. The CEfF conduct the following processing activities for invoice validation purposes:
a. Validating that the Clinical Commissioning Group is responsible for payment for the care of the individual by using SUS+ and/or backing flow data.
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. In relation to a patient registered with the CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
4. The CCG are notified by the CEfF that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved
DSfC - NHS Tameside & Glossop CCG, RS, Comm. — NIC-47189-W3X0L
Opt outs honoured: N, Y, No - data flow is not identifiable, Yes - patient objections upheld (Excuses: Does not include the flow of confidential data, Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s))
Legal basis: Health and Social Care Act 2012, Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(7), Health and Social Care Act 2012 s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 s261(2)(b)(ii)
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive
When:DSA runs 2019-05 – 2022-04 2017.06 — 2017.05.
Access method: Ongoing, Frequent Adhoc Flow, One-Off
Data-controller type: NHS TAMESIDE AND GLOSSOP CCG, NHS GREATER MANCHESTER ICB - 01Y
Sublicensing allowed: No
AGD/predecessor discussions: 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:
- Children and Young People's Health Services Data Set
- Improving Access to Psychological Therapies Data Set
- Local Provider Data - Acute
- Local Provider Data - Ambulance
- Local Provider Data - Community
- Local Provider Data - Demand for Service
- Local Provider Data - Diagnostic Services
- Local Provider Data - Emergency Care
- Local Provider Data - Experience Quality and Outcomes
- Local Provider Data - Mental Health
- Local Provider Data - Other not elsewhere classified
- Local Provider Data - Population Data
- Local Provider Data - Public Health & Screening services
- Mental Health and Learning Disabilities Data Set
- Mental Health Minimum Data Set
- Mental Health Services Data Set
- SUS Accident & Emergency data
- SUS Admitted Patient Care data
- SUS Outpatient data
- Maternity Services Dataset
- SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
- SUS for Commissioners
- Public Health and Screening Services-Local Provider Flows
- Primary Care Services-Local Provider Flows
- Population Data-Local Provider Flows
- Other Not Elsewhere Classified (NEC)-Local Provider Flows
- Mental Health-Local Provider Flows
- Maternity Services Data Set
- Experience, Quality and Outcomes-Local Provider Flows
- Emergency Care-Local Provider Flows
- Diagnostic Services-Local Provider Flows
- Diagnostic Imaging Dataset
- Demand for Service-Local Provider Flows
- Community-Local Provider Flows
- Children and Young People Health
- Ambulance-Local Provider Flows
- Acute-Local Provider Flows
- Community Services Data Set
- National Cancer Waiting Times Monitoring DataSet (CWT)
- Civil Registration - Births
- Civil Registration - Deaths
- SUS (Accident & Emergency, Inpatient and Outpatient data)
- Local Provider Data - Acute, Ambulance, Community, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Mental Health, Other not elsewhere classified, Population Data, Primary Care
- e-Referral Service for Commissioning
- Medicines dispensed in Primary Care (NHSBSA data)
- National Diabetes Audit
- Patient Reported Outcome Measures
- Personal Demographic Service
- Summary Hospital-level Mortality Indicator
- National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
- Improving Access to Psychological Therapies Data Set_v1.5
- Civil Registrations of Death
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DID)
- Improving Access to Psychological Therapies (IAPT) v1.5
- Mental Health and Learning Disabilities Data Set (MHLDDS)
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Services Data Set (MHSDS)
- Patient Reported Outcome Measures (PROMs)
- Summary Hospital-level Mortality Indicator (SHMI)
Type of data: Anonymised - ICO Code Compliant, 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, Maternity, IAPT, CYPHS and DIDS
To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services :
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Diagnostic Imaging Data Set (DIDS)
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from the HSCIC will not be national data, but only that data relating to the specific locality of interest of the applicant.
Yielded Benefits:
N/A
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).
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 – 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 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:
Risk Stratification
1. 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 reports.
Pseudonymised – SUS and Local Flows
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of acute / community / mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports include high flyers.
Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of 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:
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
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.
Pseudonymised – SUS and Local Flows
Data Processor 2 – GMSS (via DP1):
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 Greater Manchester Shared Services (GMSS).
4. GMSS analyse the data to see patient journeys for pathway or service design, re-design and de-commissioning.
5. GMSS then pass the processed pseudonymised data to 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 4 – AQuA (via DP1):
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 5 – Academic Health Sciences Network (Utilisation Management Team) (SUS Only) (via DP1)::
1. North West Data Services for Commissioners Regional Office (DSCRO) receives a flow of SUS identifiable data for the CCG from the SUS Repository.
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 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 receive 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. 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.
NHS Bury CCG, NHS Heywood, Middleton and Rochdale CCG, NHS North Manchester CCG and NHS Oldham CCG have a collaborative information sharing agreement in place to share pseudonymised SLAM and SLAM Backup data between these CCGs only. SLAM data is included under Local Flows and is available under the Health and Social Care Act 2012.
Pseudonymised – Mental Health and IAPT
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 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
1. 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.
2. 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.
3. The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning
4. Aggregation of required data for CCG management use can be completed by the CSU or 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.
Data Processor 2 – GMSS (via DP1):
Greater Manchester Shared Services (GMSS) have taken BI services in house and are now hosted by Oldham CCG. AGEM CSU flow data to a small team within GMSS. Access to the data is restricted to this team who access and manage the data. These BI services were previously provided by North West CSU.
GMSS deliver a range of services including;
• effective use of resources;
• data quality;
• information governance;
• market management;
• provider contract & performance management;
To enable GMSS to support these services a team within the GMSS have controlled access to SUS data at a pseudonymised level. Access to the data is controlled by AGEM CSU using users’ roles to ensure only appropriate users gain access to pseudonymised data. Data can then be used for reporting to support the range of services being offered to CCGs, and CCGs receive aggregate level reports from GMSS. GMSS staff are separate from Oldham CCG staff and accordingly have separate functions and roles.
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) North West DSCRO also receive a flow of pseudonymised patient level data for each CCG for Improving Access to Psychological Therapies (IAPT) for commissioning purposes
2. The pseudonymised data is securely transferred from North West DSCRO 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 Greater Manchester Shared Services (GMSS)
4. GMSS analyse and conduct the BI function and then send the Pseudonymised data 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.
Data Processor 4 - Advancing Quality Alliance (AQuA) (via DP1):
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.