NHS Digital Data Release Register - reformatted
NHS Leeds North Ccg projects
76 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).
🚩 NHS Leeds North Ccg was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Leeds North 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 — NIC-90673-L0Q4M
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:2017.12 — 2018.05.
Access method: Ongoing
Data-controller type:
Sublicensing allowed:
Datasets:
- SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
- Improving Access to Psychological Therapies Data Set
- Mental Health Minimum Data Set
- Mental Health and Learning Disabilities Data Set
- Maternity Services Dataset
- Mental Health Services 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 - Mental Health
- Local Provider Data - Other not elsewhere classified
- 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
Objectives:
Objective for processing:
This is a new application for the following purposes:
Invoice Validation
As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (c)/2013, to undertake invoice validation on behalf of the CCG. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. The CCG are advised by the CSU whether payment for invoices can be made or not.
Risk Stratification
To use SUS data identifiable at the level of NHS number according to S.251 CAG 7-04(a)/2013 (and Primary Care Data) for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users. Risk Stratification enables GPs to better target intervention in Primary Care.
Commissioning (Pseudonymised) – SUS and Local Flows
To use pseudonymised data to provide intelligence to support commissioning of health services. The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS
To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services :
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Diagnostic Imaging Data Set (DIDS)
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.
Expected Benefits:
Expected measurable benefits to health and/or social care including target date:
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.
j. Service Transformation Projects (STP)
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, Integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
Outputs:
Specific outputs expected, including target date:
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 and aggregate with small number suppression.
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 POD.
e. Planned care by POD view – activity, finance 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 frequent flyers.
9. Mortality
10. Quality
11. Service utilisation reporting
12. Patient safety indicators
13. Production of reports and dash boards to support service redesign and pathway changes
Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports include frequent flyers.
Processing:
Processing activities:
The DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.
The CCG and any Data Processor will only have access to records of its own CCG. Access is limited to those administrative staff with authorised user accounts used for identification and authentication.
Invoice Validation
SUS Data is obtained from the SUS Repository to DSCRO.
1. DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the North of England CSU.
2. 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 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.
3. 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 the 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.
Risk Stratification
Data Processor 1 - North England CSU
1. Identifiable SUS data is obtained from the SUS Repository to Yorkshire Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by DSCRO and the data identifiable at the level of NHS number is transferred securely to North of England CSU, who hold the SUS data within the secure NECS network storage.
3. Identifiable GP Data is securely sent from the GP system to North of England CSU.
4. SUS data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier derived from SUS available to GPs is the NHS numbers of their own patients. Any further identification of the patients is derived from the GP data sourced from their own systems.
6. North of England 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 North of England CSU has completed the processing, the CCG can access the online system via a secure network connection to access the data pseudonymised at patient level.
On or before 20th July 2017, this data processor will cease to deliver risks stratification, at which point a data destruction certificate will be completed.
eMBED
Identifiable SUS data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
1. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to eMBED, who hold the SUS data within eMBED secure storage.
2. Identifiable GP Data is securely sent from the GP system to eMBED.
3. SUS data is linked to GP data in the risk stratification tool by the data processor.
4. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier derived from SUS available to GPs is the NHS number of their own patients. Any further identification of the patients is derived from the GP data sourced from their own systems.
5. eMBED 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 eMBED has completed the processing, the CCG can access the online system via a secure network connection to access the data pseudonymised at patient level.
Commissioning (Pseudonymised) – SUS and Local Flows
Data Processor 2 - eMBED
1. Yorkshire Data Services for Commissioners Regional Office / North England Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. Yorkshire / North of England 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 of England CSU for the addition of derived fields and analysis.
3. North of England CSU then pass the processed, pseudonymised data to both eMBED and the CCG.
4. eMBED receives the Pseudonymised data for the addition of derived fields, linkage of data sets and analysis. Linked data is limited to the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning:
- SUS data and Local Provider data at pseudonymised level
- Mental Health (MHSDS, MHLDDS, MHMDS) with SUS
- Improving Access to Psychological Therapies (IAPT) with SUS
- Diagnostic Imaging Dataset (DIDs) with SUS
- Maternity (MSDS) with SUS
- Children and Young People’s Health Services (CYPHS) with Local provider data
- Mental Health (MHSDS, MHLDDS, MHMDS) with Local provider data
- Improving Access to Psychological Therapies (IAPT) with Local provider data
- Diagnostic Imaging Dataset (DIDs) with Local provider data
- Maternity (MSDS) with Local provider data
- Children and Young People’s Health Services (CYPHS) with Local provider data
5. eMBED securely transfer pseudonymised outputs for management use by the CCG.
6. The CCG receive Pseudonymised data from both North of England CSU and eMBED. The CCG then analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
7. Aggregation of required data for CCG management use will be completed by the North of England CSU, eMBED or the CCG as instructed by the CCG.
8. 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.
9. The CCG securely transfer Pseudonymised data back to the provider to:
a) confirm how patients are reported in SUS, and how the commissioner can reliably group these patients into categories for points of delivery;
b) allow for granular data validation whereby a commissioner may query the SUS record, and need to pass it back to the provider for checking; and
c) to allow the provider to undertake further analysis of a cohort of their patients as requested and specified by the commissioner.
The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider.
Commissioning (Pseudonymised) – Mental Health, MSDS, IAPT, CYPHS and DIDS
1. North of England Data Services for Commissioners Regional Office (DSCRO) and Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtain a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS and MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management, minimisation and pseudonymisation of data is completed by North of England and DSCRO and the pseudonymised data is then passed securely to North of England CSU.
3. North of England CSU then securely transfers the processed, pseudonymised and linked data to eMBED and the CCG.
4. a) The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning.
b) eMBED receives the data from North of England CSU and carries out further data processing, addition of derived fields, linkage to other data sets and analysis. Linked data includes the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning:
- Mental Health (MHSDS, MHLDDS, MHMDS) with IAPT
- Mental Health (MHSDS, MHLDDS, MHMDS) with SUS
- Improving Access to Psychological Therapies (IAPT) with SUS
- Diagnostic Imaging Dataset (DIDs) with SUS
- Maternity (MSDS) with SUS
- Children and Young People’s Health Services (CYPHS) with SUS
5. Aggregation of required data for CCG management use is completed by the 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 in line with the HES analysis guide can be shared.
Project 2 — NIC-90673-L0Q4N
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:
- 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 - Public Health & Screening services
- Local Provider Data - Mental Health
- Local Provider Data - Other not elsewhere classified
- Local Provider Data - Population Data
- Local Provider Data - Primary Care
- 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
Objectives:
Invoice Validation
As an approved Controlled Environment for Finance (CEfF), North of England CSU receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (c)/2013, to undertake invoice validation on behalf of the CCG. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. The CCG are advised by the CSU whether payment for invoices can be made or not.
Risk Stratification
To use SUS data identifiable at the level of NHS number according to S.251 CAG 7-04(a)/2013 (and Primary Care Data) for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users. Risk Stratification enables GPs to better target intervention in Primary Care.
Commissioning (Pseudonymised) – SUS and Local Flows
To use pseudonymised data to provide intelligence to support commissioning of health services. The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS
To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services :
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Diagnostic Imaging Data Set (DIDS)
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
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.
j. Service Transformation Projects (STP)
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, Integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
Outputs:
Invoice Validation
1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events
Risk Stratification
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
3. Record level output will be available for commissioners (of the CCG), pseudonymised at patient level and aggregate with small number suppression.
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 POD.
e. Planned care by POD view – activity, finance 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 frequent flyers.
9. Mortality
10. Quality
11. Service utilisation reporting
12. Patient safety indicators
13. Production of reports and dash boards to support service redesign and pathway changes
Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports include frequent flyers.
Processing:
Invoice Validation
SUS Data is obtained from the SUS Repository to DSCRO.
1. DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the North of England CSU.
2. 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 SUS data flow to validate the corresponding record in the backing data flow
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with 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.
3. 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 the 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.
Risk Stratification
Data Processor 1 - North England CSU
1. Identifiable SUS data is obtained from the SUS Repository to Yorkshire Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by DSCRO and the data identifiable at the level of NHS number is transferred securely to North of England CSU, who hold the SUS data within the secure NECS network storage.
3. Identifiable GP Data is securely sent from the GP system to North of England CSU.
4. SUS data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier derived from SUS available to GPs is the NHS numbers of their own patients. Any further identification of the patients is derived from the GP data sourced from their own systems.
6. North of England 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 North of England CSU has completed the processing, the CCG can access the online system via a secure network connection to access the data pseudonymised at patient level.
On or before 20th July 2017, this data processor will cease to deliver risks stratification, at which point a data destruction certificate will be completed. eMBED will the sole Data Processor for Risk Stratification. eMBED will run adjacently to NECS until NECS ceases.
eMBED
Identifiable SUS data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
1. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to eMBED, who hold the SUS data within eMBED secure storage.
2. Identifiable GP Data is securely sent from the GP system to eMBED.
3. SUS data is linked to GP data in the risk stratification tool by the data processor.
4. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier derived from SUS available to GPs is the NHS number of their own patients. Any further identification of the patients is derived from the GP data sourced from their own systems.
5. eMBED 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 eMBED has completed the processing, the CCG can access the online system via a secure network connection to access the data pseudonymised at patient level.
Commissioning (Pseudonymised) – SUS and Local Flows
Data Processor 2 - eMBED
1. Yorkshire Data Services for Commissioners Regional Office / North England Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. Yorkshire / North of England 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 of England CSU for the addition of derived fields and analysis.
3. North of England CSU then pass the processed, pseudonymised data to both eMBED and the CCG.
4. eMBED receives the Pseudonymised data for the addition of derived fields, linkage of data sets and analysis. Linked data is limited to the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning:
- SUS data and Local Provider data at pseudonymised level
- Mental Health (MHSDS, MHLDDS, MHMDS) with SUS
- Improving Access to Psychological Therapies (IAPT) with SUS
- Diagnostic Imaging Dataset (DIDs) with SUS
- Maternity (MSDS) with SUS
- Children and Young People’s Health Services (CYPHS) with Local provider data
- Mental Health (MHSDS, MHLDDS, MHMDS) with Local provider data
- Improving Access to Psychological Therapies (IAPT) with Local provider data
- Diagnostic Imaging Dataset (DIDs) with Local provider data
- Maternity (MSDS) with Local provider data
- Children and Young People’s Health Services (CYPHS) with Local provider data
5. eMBED securely transfer pseudonymised outputs for management use by the CCG.
6. The CCG receive Pseudonymised data from both North of England CSU and eMBED. The CCG then analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
7. Aggregation of required data for CCG management use will be completed by the North of England CSU, eMBED or the CCG as instructed by the CCG.
8. 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.
9. The CCG securely transfer Pseudonymised data back to the provider to:
a) confirm how patients are reported in SUS, and how the commissioner can reliably group these patients into categories for points of delivery;
b) allow for granular data validation whereby a commissioner may query the SUS record, and need to pass it back to the provider for checking; and
c) to allow the provider to undertake further analysis of a cohort of their patients as requested and specified by the commissioner.
The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider.
Commissioning (Pseudonymised) – Mental Health, MSDS, IAPT, CYPHS and DIDS
1. North of England Data Services for Commissioners Regional Office (DSCRO) and Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtain a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS and MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management, minimisation and pseudonymisation of data is completed by North of England and DSCRO and the pseudonymised data is then passed securely to North of England CSU.
3. North of England CSU then securely transfers the processed, pseudonymised and linked data to eMBED and the CCG.
4. a) The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning.
b) eMBED receives the data from North of England CSU and carries out further data processing, addition of derived fields, linkage to other data sets and analysis. Linked data includes the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning:
- Mental Health (MHSDS, MHLDDS, MHMDS) with IAPT
- Mental Health (MHSDS, MHLDDS, MHMDS) with SUS
- Improving Access to Psychological Therapies (IAPT) with SUS
- Diagnostic Imaging Dataset (DIDs) with SUS
- Maternity (MSDS) with SUS
- Children and Young People’s Health Services (CYPHS) with SUS
5. Aggregation of required data for CCG management use is completed by the 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.
Project 3 — NIC-21947-H6Q3R
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:
- Mental Health Minimum Data Set
- Mental Health and Learning Disabilities Data Set
- Mental Health Services Data Set
- Improving Access to Psychological Therapies Data Set
- Children and Young People's Health Services Data Set
Objectives:
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)
• Improving Access to Psychological Therapy (IAPT)
• Children and Young People’s Health (CYPHS)
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.
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. Development of business models.
c. Monitoring 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.
Outputs:
As a result of the aforementioned processing activities, eMBED will provide a number of outputs which are securely provided to the CCGs in the appropriate format at pseudonymised level.
Where datasets have been linked, the CCG will receive the outputs of analysis instead of the direct data, however it may also be necessary to provide linked data at row level to CCGs (pseudonymised record level data).
eMBED will provide aggregated reports only with small number suppression to CCG’s stakeholders e.g. GP practices, Local Authorities. Where such data is provided there are safeguards in place to ensure that the receiving organisation has recognised the required safety controls required, i.e. signed agreements from the receiving organisation regarding compliance with data protection and the agreed use of the data.
eMBED will flow outputs, mostly in the form of reports to the CCG stakeholders. CCGs may also provide their stakeholders with the anonymised outputs. The anonymisation will be achieved by aggregating records and using small number suppression in line with HES analysis guidance.
eMBED provides a range of Business Intelligence functions and outputs as specified by the CCG. These outputs can be presented in a variety of different ways to a variety of different users, from highly aggregated graphical “dashboards” to very low-level tabular analysis, and everything in between with the opportunity to drill-down into the detail. Provision of aggregated reports only with small number suppression data to CCG stakeholders allows for analysis at an appropriate level, revealing potentially useful but previously unrecognised commissioning insights/trends whilst mitigating against the risk of re-identification of individuals
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 including high flyers.
The PCU produces a number of reports which provide a summary (not patient level data) which are shared back to the CCG, the following are a list of these:
IAPT Dataset
Mandated national contract KPIs:
Completion of IAPT Minimum Data Set outcome data
IAPT Access Times – 6 & 18 wk (finished treatment)
Local CCG and NHSE information and KPIs:
Number of Referrals
Number Entering Treatment
Monthly Prevalence rate
Number completing treatment
Number moving to recovery
Number not at caseness
Monthly Recovery rate
Reliable Improvement rate
IAPT Access Times – 6 & 18 wk (entering treatment)
Waiting times for treatment and those still waiting
Clearance times
Local CCG monitoring:
Appointments, cancellations and DNA rate analysis
Data Quality
Referral rates and activity by GP Practice and Age band
Mental Health Dataset
Mandated national contract KPIs :
Completion of valid NHS number field
Completion of Ethnic coding
Under 16 bed days on Adult wards (Never event)
Local CCG and NHSE information and KPIs:
Gatekeeping admissions
7 day follow-up hospital discharges
EIP access rates
Eating disorders
Local CCG monitoring:
Referral rates by GP Practice and Age band
CPA monitoring inc settled accommodation and employment
CPA reviews within 12 months, step up/down etc
Bed days, admissions and discharges
Delayed discharges
Detentions
LD/ MH/CAMHS ward stays
Bed locality (distance out of area)
Contacts and DNA rates
Cluster monitoring and red rules
Data quality
The PCU will also share aggregated reports only with small number suppression back to the provider.
The PCU shares aggregated reports only with small number suppression outputs with NHS England for national reporting and to support any issues that need rising in relation to data quality.
Processing:
1. North of England Data Services for Commissioners Regional Office (DSCRO) and Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtain a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, and MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management, minimisation and pseudonymisation of data is completed by North of England and Yorkshire DSCRO and the pseudonymised data is then passed securely to North of England CSU.
3. North of England CSU then securely transfer the processed, pseudonymised and linked data to eMBED.
4. eMBED receives the data from North of England CSU and carries out further data processing, addition of derived fields, linkage to other data sets and analysis. Linked data would include the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning:
• Mental Health (MHSDS, MHLDDS, MHMDS) with IAPT
• Mental Health (MHSDS, MHLDDS, MHMDS) with SUS
• Improving Access to Psychological Therapies (IAPT) with SUS
• Diagnostic Imaging Dataset (DIDs) with SUS
• Maternity (MSDS) with SUS
• Children and Young People’s Health Services (CYPHS) with SUS
5. Aggregation of required data for CCG management use is completed by eMBED 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 in line with the HES analysis guide can be shared.
Project 4 — NIC-56510-Z9Z0V
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:
- SUS (Accident & Emergency, Inpatient and Outpatient data)
Objectives:
As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (c)/2013, to undertake invoice validation on behalf of the CCG. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. The CCG are advised by the CSU whether payment for invoices can be made or not.
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 NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.
Expected Benefits:
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
Outputs:
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:
North of England DSCRO (part of NHS Digital) will apply Type 2 objections (from 14th October 2016 onwards) before any identifiable data leaves the DSCRO.
1. SUS Data is obtained from the SUS Repository to North of England DSCRO.
2. North of England DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the North of England 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 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 the 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.
Project 5 — NIC-60430-F1Q3B
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:
- 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, Public Health & Screening services
Objectives:
SUS and Local Provider Data - The CCG recognises that good information and intelligence is crucial for the commissioning of high quality and safe services leading to better outcomes for the populations they serve. This application supports this objective.
This arrangement was previously agreed to facilitate the transfer of Commissioning Support Services, from Yorkshire & Humber Commissioning Support Unit (Y&H CSU), who previously held ASH status and served the CCGs, to North England CSU (NECS), and eMBED Health Consortium, for ongoing provision in line with the NHS England Lead Provider Framework (LPF).
Data Processor 1 - NECS is a commissioning support unit that had been working with the CCG for some time.
Data Processor 2 - eMBED was appointed in March 2016 to continue the operations of the Yorkshire and Humber CSU; Kier Business Services Limited, with additional Business Intelligence work carried out under contract by Dr Foster Ltd.
Kier Business Services are the prime partner for the LPF within the eMBED Health Consortium. Both organisations (Kier Business Services and Dr Foster Ltd) are a legal entity in their own right. Dr Foster Ltd are subcontracted to Kier Business Services for the delivery of eMBED Health Consortium services.
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.
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:
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. Monitoring of hospital activity against planned levels where an established contract exists between a provider and a commissioner inclusive of:
o Overall contract reporting of actual vs plan for activity and value at aggregate level
o Reconciliation reports between local hospital data, and SUS records at aggregate level.
o Contract Data Quality reporting at anonymised in context record level.
10. QIPP scheme analysis at aggregate level
11. Monitoring of SUS based CCG Outcome Framework indicators at aggregate level with small number suppression.
12. “Deep dive” analysis of hospital activity at aggregate level.
13. Cross CCG benchmarking at aggregate level.
14. Provision of aggregate reports with small number suppression activity data to CCGs’ stakeholders e.g. Health and Wellbeing Boards where the CCG have agreed to this
Processing:
1. Yorkshire Data Services for Commissioners Regional Office / North England Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. Yorkshire / North England 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 of England CSU for the addition of derived fields and analysis.
3. North of England CSU then pass the processed, pseudonymised data to both eMBED and the CCG.
4. eMBED receives the Pseudonymised data for the addition of derived fields, linkage of data sets and analysis. Linked data is limited to the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning:
- SUS data and Local Provider data at pseudonymised level
- Mental Health (MHSDS, MHLDDS, MHMDS) with SUS
- Improving Access to Psychological Therapies (IAPT) with SUS
- Diagnostic Imaging Dataset (DIDs) with SUS
- Maternity (MSDS) with SUS
- Children and Young People’s Health Services (CYPHS) with Local provider data
- Mental Health (MHSDS, MHLDDS, MHMDS) with Local provider data
- Improving Access to Psychological Therapies (IAPT) with Local provider data
- Diagnostic Imaging Dataset (DIDs) with Local provider data
- Maternity (MSDS) with Local provider data
- Children and Young People’s Health Services (CYPHS) with Local provider data
5. eMBED securely transfer pseudonymised outputs for management use by the CCG.
6. The CCG receive Pseudonymised data from both North of England CSU and eMBED. The CCG then analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
7. Aggregation of required data for CCG management use will be completed by the CSU, eMBED or the CCG as instructed by the CCG.
8. 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.
9. The CCG securely transfer Pseudonymised data back to the provider to:
a) confirm how patients are reported in SUS, and how the commissioner can reliably group these patients into categories for points of delivery;
b) allow for granular data validation whereby a commissioner may query the SUS record, and need to pass it back to the provider for checking; and
c) to allow the provider to undertake further analysis of a cohort of their patients as requested and specified by the commissioner.
The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider.
Project 6 — NIC-22520-J3P7F
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:2016.12 — 2017.02.
Access method: Ongoing
Data-controller type:
Sublicensing allowed:
Datasets:
- SUS (Accident & Emergency, Inpatient and Outpatient data)
Objectives:
To utilise SUS data identifiable at the level of NHS number to provide risk stratification information to the CCG and GP practice.
Expected Benefits:
Risk Stratification promotes improved case management in primary care which is expected to lead to the following benefits being realised :
1. Improved planning by better understanding the patient flows through the healthcare system, thus allowing GPs and clinicians to design appropriate pathways to improve patient flow and identify plans to address these.
2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved via the mapping of frequent users of emergency services and the 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 reduce premature mortality by more targeted intervention in primary care, which supports the commissioner to meet its requirement to reduce premature mortality in line with the CCG Outcome Framework.
It is expected that all of the aforementioned will lead to improved patient experience through more effective direct patient care services.
Outputs:
PROCESS 1:
To provide risk profiling, calculated on activity data from secondary and primary care. As part of the risk stratification processing activity detailed above, the GP practice has access to the RAIDR tool for reports which present to them their registered patients and associated risk score.
The only identifier to be provided to the GP practice is the NHS number of their registered patient.
The GP practice can access the RAIDR tool, which is a secure portal, at any time which will support MDT (multi-disciplinary team) discussions around ongoing patient care, and enhanced service requirements.
The GP practice can copy and paste the NHS number presented in the secure web-portal to any other program including the practice clinical system.
CCG staff who have been granted access to the RAIDR tool can only access aggregate output / reports.
No record-level data will be shared with any other third party organisations.
PROCESS 2:
To provide risk profiling, calculated on activity data from secondary and primary care, community and mental health data. As part of the risk stratification processing activity detailed above, the GP practice has access to the secure web-portal for reports which present to them their registered patients and associated risk score.
The GP practice can access the secure web-portal at any time to support MDT (multi-disciplinary team) discussions around ongoing patient care, and enhanced service requirements.
The GP practice can copy and paste the NHS number presented in the secure web-portal to any other program including the practice clinical system.
There are two views of the data available, pseudonymised and identifiable at the level of NHS number. The data identifiable at the level of NHS number is only available to the GP practice who has a legitimate relationship with the patient. GP practice access to the data is authorised by the GP practice Caldicott Guardians.
The CCG can access a pseudonymised view of the data only.
No record-level data will be shared with any other third party organisations.
Processing:
The data processor agrees to process data only for the purposes of risk stratification.
There are two processes for risk stratification, each using different methodologies to process the data and calculate the risk scores for each patient. These are both recognised methodologies that each contribute data for risk stratification, and by using both methodologies this enables the GP practice and the CCG to obtain a wider range of data to inform risk stratification.
Processing activities:
The two processes are described below:
PROCESS 1:
Process 1 uses an algorithm known as the Combined Predictive Model (CPM) to calculate the risk score for each patient using primary and secondary care data identifiable at the level of NHS number.
Processing of SUS Data for the purposes of Risk Stratification includes landing, processing, staging and publication.
1. Landing
Prior to the release of SUS data by DSCRO Yorkshire, Type 2 objections will be applied and the relevant patients data redacted. DSCRO Yorkshire securely transfer SUS data identifiable at the level of NHS number to North of England Commissioning Support Unit (NECS). This is done by landing the SUS data in secure NECS network storage. Data is landed and processed in an access restricted server at NECS.
Primary care data identifiable at the level of NHS number is extracted from GP clinical systems and downloaded to secure NECS network storage.
Only named individuals have access to process the data. All users undertake regular IG training, in line with IGT requirements.
2. Processing (ETL)
Data is processed on a monthly basis, which follows NECS ETL (Extract, Transform and Load) process as follows.
2.1. Cleaning and quality checks are carried out on the data.
2.2. The primary care and SUS data are combined using NHS number to link the data and the data is processed to create a risk stratification data set
3. Staging
Data is landed to a secure NECS staging area for final quality checks.
4. Publication
Outputs are available to the CCG and the GP practice (for their own patients only) via the RAIDR tool which has a secure web-portal for accessing the data. All usage of the tool is audited.
Access to the RAIDR tool is via individual usernames and passwords.
Data identifiable at the level of NHS number is only available to named individuals within the GP practice who have a legitimate relationship with the patient or where an individual working within a GP practice has the authorisation of a senior individual - such as senior partner or business manager within the practice - to access data for the purposes of conducting Risk Stratification for case finding. This also only applies where there is a legitimate relationship with the patient for direct patient care. (For example, staff such as community/practice nurses who work as part of a multi-disciplinary team with the GPs.)
The CCG has an aggregated view only of Risk Stratification data based on their related GP practices.
No record-level SUS data identifiable at the level of NHS number or local provider data identifiable at the level of NHS number is provided to any other organisation.
PROCESS 2:
Process 2 uses the John Hopkins Adjusted Clinical Groups (ACG) algorithm using primary, secondary, community and mental health data identifiable at the level of NHS number and provides the risk score for each patient and additional information on the predicted costs of treatment. (The use of the risk stratification tool to provide a picture of predicted costs of service provision fits within the scope of risk stratification to be used by clinical commissioners to target specific patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions. The analysis of predicted costs enables specific patient groups to be targeted by providing clinical commissioners with an understanding of the likely service and resource requirements for specific groups / cohorts of patients. The predicted costs also support an understanding of the reduction in costs relating to reduced hospital admissions, which is a stated aim of risk stratification.)
Processing of SUS Data for the purposes of Risk Stratification includes landing, processing, staging and publication.
1. Landing
Prior to the release of SUS data by DSCRO Yorkshire, Type 2 objections will be applied and the relevant patients data redacted. DSCRO Yorkshire securely transfer SUS data identifiable at the level of NHS number to North of England Commissioning Support Unit (NECS). This is done by landing the SUS data in secure NECS network storage.
Primary care data extracts from GP clinical systems are downloaded and transferred to NECS by landing the data in secure NECS network storage.
Only named individuals have access to process the data. All users undertake regular IG training, in line with IGT requirements.
2. Processing
Data is processed on a monthly basis.
2.1 Cleaning and quality checks are carried out on the primary care data.
2.2 The primary care, community and mental health data is then combined with SUS data using NHS numbers to link the data.
2.3 The combined dataset is processed to produce the calculated risk scores for each patient.
3. Staging
Data is landed to a secure NECS staging area for final quality checks before the data is loaded for publication.
4. Publication
The data is loaded and published using the NECS SQL BI stack, which includes storage of the data in the NECS secure network storage and a secure web-portal for making the data available to the GP practice.
4.1. GP practice access to data (for their own patients only):
Data identifiable at the level of NHS number is presented via the secure web-portal to the GP practice who has a legitimate relationship with the patient.
Data identifiable at the level of NHS number is only available to named individuals within the GP practice who have a legitimate relationship with the patient.
The web-portal is accessed by the GP practice using a username and password.
The GP practice has access to SUS data identifiable at the level of NHS number to see aspects of the inpatient and outpatient activity via the secure web-portal.
All usage of the secure web-portal is audited and access rights are granted by the Caldicott Guardians at the GP practice.
4.2. CCG access to data:
The CCG can access a pseudonymised view of the data only.
Please see Appendix for lists of which GP practices use each process.