NHS Digital Data Release Register - reformatted

NHS Birmingham And Solihull Ccg

🚩 NHS Birmingham And Solihull Ccg received multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Birmingham And Solihull Ccg may not have compared the two datasets, but the identifiers are consistent between datasets for the same recipient, and NHS Digital does not know what their recipients actually do.

Project 1 — NIC-41134-T4K0J

Opt outs honoured: N, Y

Sensitive: Sensitive

When: 2016/12 — 2018/05.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012, Section 251 approval is in place for the flow of identifiable data

Categories: Anonymised - ICO code compliant, Identifiable

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, Primary Care, Public Health & Screening services
  • Mental Health Services Data Set
  • Mental Health Minimum Data Set
  • Mental Health and Learning Disabilities Data Set
  • Improving Access to Psychological Therapies Data Set
  • Children and Young People's Health Services Data Set
  • Local Provider Data - Acute
  • Local Provider Data - Ambulance
  • Local Provider Data - Community
  • Local Provider Data - Diagnostic Services
  • Local Provider Data - Emergency Care
  • Local Provider Data - Mental Health
  • Local Provider Data - Primary Care
  • SUS Accident & Emergency data
  • SUS Admitted Patient Care data
  • SUS Outpatient data
  • Local Provider Data - Demand for Service
  • Local Provider Data - Demand For service
  • Local Provider Data - Other not elsewhere classified
  • Local Provider Data - Population 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

Objectives:

Invoice Validation As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number to undertake invoice validation on behalf of the CCG. In order to support commissioning of patient care by validating non-contracted activity in the CCG, this data is required for the purpose of invoice validation. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. Risk Stratification This is an application to use SUS data identifiable at the level of NHS number 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. Pseudonymised – SUS and Local Flows Application for the CCG 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. Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS Application for the CCG to use MHSDS, MHMDS, MHLDDS, MSDS, IAPT, CYPHS and DIDs linked and pseudonymised data to provide intelligence to support commissioning of health services. The linked, 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.

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 misapproproation of public funds to ensure the on-going 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. Pseudonymised – SUS and Local Flows 1) Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management and pathways. 2) Health economic modelling using: a) Analysis on provider performance against 18 weeks wait targets b) Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients c) Analysis of outcome measures for differential treatments, accounting for the full patient pathway d) Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC) flows 3) Commissioning cycle support for grouping and re-costing previous activity 4) Enables monitoring of: a) CCG outcome indicators b) Non-financial validation of patient level data c) Successful delivery of integrated care within the CCG d) Checking frequent or multiple attendances to improve early intervention and avoid admissions e) Commissioning and performance management 5) Feedback to NHS service providers on data quality at an aggregate level Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS 1) Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management and pathways. 2) Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3) Health economic modelling using: (a) Analysis on provider performance. (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.

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 with no identifiers 3) Record level output will be available for commissioners in anonymised or pseudonymised format. 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. 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 acute / community / mental health quality matrix. 6) Clinical coding reviews / audits. 7) Budget reporting down to individual GP Practice level.

Processing:

Central Midlands DSCRO will apply Type 2 objections (from 1st October 2016 onwards) before any identifiable data leaves the DSCRO. Invoice Validation 1) Central and Midlands DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the Arden and GEM CSU (Data Processor 2). 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) by using the derived commissioner field in SUS and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow b) Once the backing information is received, this will be checked against system access and reports provided by the HSCIC to confirm the payments are: - In line with Payment by Results tariffs - are in relation to a patient registered with a CCG GP or resident within the CCG area. - The health care provided should be paid by the CCG in line with CCG guidance.  3) The CCG are notified of that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between Arden and GEM CSU and the provider meaning that no data needs to be sent to the CCG. The CCG only receives notification to pay. Risk Stratification 1) SUS data identifiable at the level of NHS number regarding hospital admissions, A&E attendances and outpatient attendances is delivered securely from Central and Midlands Data Services for Commissioners Regional Office (DSCRO) to the data processor. 2) 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 Midlands and Lancashire CSU (Data Processor 1), who hold the SUS data within the secure Data Centre on N3. 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 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. 5) Midlands and Lancashire 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. 6) Once Midlands and Lancashire CSU has completed the processing, the CCG can dial in to the online system via N3 connection to access the data anonymised at patient level. Pseudonymised – SUS and Local Flows 1) Central and Midlands Data Services for Commissioners Regional Office (DSCRO) receives a flow of SUS identifiable data for the CCG from the SUS Repository. Central and Midlands DSCRO also receives identifiable local provider data for the CCG directly from Providers. 2) Data quality management of data is completed by the DSCRO and the identifiable data is then passed securely to North England CSU for the addition of derived fields, linkage of data sets and analysis. 3) Midlands and Lancashire CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 4) Patient level data will not be shared outside of the CCG. External aggregated reports only. Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS 1) Central and Midlands Data Services for Commissioning Regional Office (DSCRO) will receive a flow of pseudonymised patient level data for each CCG for Mental Health (MHSDS, MHMDS, MHLDDS), Improving Access to Psychological Therapies (IAPT), Maternity (MSDS), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes 2) Data quality management of data is completed by the DSCRO and the pseudonymised data is then passed securely to Midlands and Lancashire CSU for the addition of derived fields, linkage of data sets and analysis. Linkage is not with other datasets just between the data contained within the dataset itself. 3) Midlands and Lancashire CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 4) The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning 5) The CCG completes aggregation of required data for CCG management use – disclosing any outputs at the appropriate level. 6) Patient level data will not be shared outside of the CCG. External aggregated reports only with small numbers suppressed with HSCIC guidance.


Project 2 — NIC-41097-Y5P2Y

Opt outs honoured: Y, N

Sensitive: Sensitive

When: 2016/12 — 2018/05.

Repeats: Ongoing

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012

Categories: Identifiable, Anonymised - ICO code compliant

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, Primary Care
  • Mental Health Services Data Set
  • Mental Health Minimum Data Set
  • Mental Health and Learning Disabilities Data Set
  • Improving Access to Psychological Therapies Data Set
  • Children and Young People's Health Services Data Set
  • Local Provider Data - Acute
  • Local Provider Data - Ambulance
  • Local Provider Data - Community
  • Local Provider Data - Diagnostic Services
  • Local Provider Data - Emergency Care
  • Local Provider Data - Mental Health
  • Local Provider Data - Primary Care
  • SUS Accident & Emergency data
  • SUS Admitted Patient Care data
  • SUS Outpatient data
  • Local Provider Data - Demand For service
  • 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

Objectives:

Invoice Validation As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number to undertake invoice validation on behalf of the CCG. In order to support commissioning of patient care by validating non-contracted activity in the CCG, this data is required for the purpose of invoice validation. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. Risk Stratification This is an application to use SUS data identifiable at the level of NHS number 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. Pseudonymised – SUS and Local Flows Application for the CCG 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. Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS Application for the CCG to use MHSDS, MHMDS, MHLDDS, MSDS, IAPT, CYPHS and DIDs linked and pseudonymised data to provide intelligence to support commissioning of health services. The linked, 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.

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 misapproproation of public funds to ensure the on-going 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. Pseudonymised – SUS and Local Flows 1) Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management and pathways. 2) Health economic modelling using: a) Analysis on provider performance against 18 weeks wait targets b) Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients c) Analysis of outcome measures for differential treatments, accounting for the full patient pathway d) Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC) flows 3) Commissioning cycle support for grouping and re-costing previous activity 4) Enables monitoring of: a) CCG outcome indicators b) Non-financial validation of patient level data c) Successful delivery of integrated care within the CCG d) Checking frequent or multiple attendances to improve early intervention and avoid admissions e) Commissioning and performance management 5) Feedback to NHS service providers on data quality at an aggregate level Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS 1) Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management and pathways. 2) Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3) Health economic modelling using: (a) Analysis on provider performance. (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.

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 with no identifiers 3) Record level output will be available for commissioners in anonymised or pseudonymised format. 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. 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 acute / community / mental health quality matrix. 6) Clinical coding reviews / audits. 7) Budget reporting down to individual GP Practice level.

Processing:

Central Midlands DSCRO will apply Type 2 objections (from 1st October 2016 onwards) before any identifiable data leaves the DSCRO. Invoice Validation 1) Central and Midlands DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the Arden and GEM CSU (Data Processor 2). 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) by using the derived commissioner field in SUS and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow b) Once the backing information is received, this will be checked against system access and reports provided by the HSCIC to confirm the payments are: - In line with Payment by Results tariffs - are in relation to a patient registered with a CCG GP or resident within the CCG area. - The health care provided should be paid by the CCG in line with CCG guidance.  3) The CCG are notified of that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between Arden and GEM CSU and the provider meaning that no data needs to be sent to the CCG. The CCG only receives notification to pay. Risk Stratification 1) SUS data identifiable at the level of NHS number regarding hospital admissions, A&E attendances and outpatient attendances is delivered securely from Central and Midlands Data Services for Commissioners Regional Office (DSCRO) to the data processor. 2) 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 Midlands and Lancashire CSU (Data Processor 1), who hold the SUS data within the secure Data Centre on N3. 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 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. 5) Midlands and Lancashire 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. 6) Once Midlands and Lancashire CSU has completed the processing, the CCG can dial in to the online system via N3 connection to access the data anonymised at patient level. Pseudonymised – SUS and Local Flows 1) Central and Midlands Data Services for Commissioners Regional Office (DSCRO) receives a flow of SUS identifiable data for the CCG from the SUS Repository. Central and Midlands DSCRO also receives identifiable local provider data for the CCG directly from Providers. 2) Data quality management of data is completed by the DSCRO and the identifiable data is then passed securely to North England CSU for the addition of derived fields, linkage of data sets and analysis. 3) Midlands and Lancashire CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 4) Patient level data will not be shared outside of the CCG. External aggregated reports only. Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS 1) Central and Midlands Data Services for Commissioning Regional Office (DSCRO) will receive a flow of pseudonymised patient level data for each CCG for Mental Health (MHSDS, MHMDS, MHLDDS), Improving Access to Psychological Therapies (IAPT), Maternity (MSDS), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes 2) Data quality management of data is completed by the DSCRO and the pseudonymised data is then passed securely to Midlands and Lancashire CSU for the addition of derived fields, linkage of data sets and analysis. Linkage is not with other datasets just between the data contained within the dataset itself. 3) Midlands and Lancashire CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 4) The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning 5) The CCG completes aggregation of required data for CCG management use – disclosing any outputs at the appropriate level. 6) Patient level data will not be shared outside of the CCG. External aggregated reports only with small numbers suppressed with HSCIC guidance.


Project 3 — NIC-41087-X6Y1L

Opt outs honoured: Y, N

Sensitive: Sensitive

When: 2016/12 — 2018/05.

Repeats: Ongoing

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012

Categories: Identifiable, Anonymised - ICO code compliant

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, Primary Care
  • Mental Health Services Data Set
  • Mental Health Minimum Data Set
  • Mental Health and Learning Disabilities Data Set
  • Improving Access to Psychological Therapies Data Set
  • Children and Young People's Health Services Data Set
  • Local Provider Data - Acute
  • Local Provider Data - Ambulance
  • Local Provider Data - Community
  • Local Provider Data - Diagnostic Services
  • Local Provider Data - Emergency Care
  • Local Provider Data - Mental Health
  • Local Provider Data - Primary Care
  • SUS Accident & Emergency data
  • SUS Admitted Patient Care data
  • SUS Outpatient data
  • Local Provider Data - Demand For service
  • 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

Objectives:

Invoice Validation As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number to undertake invoice validation on behalf of the CCG. In order to support commissioning of patient care by validating non-contracted activity in the CCG, this data is required for the purpose of invoice validation. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. Risk Stratification This is an application to use SUS data identifiable at the level of NHS number 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. Pseudonymised – SUS and Local Flows Application for the CCG 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. Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS Application for the CCG to use MHSDS, MHMDS, MHLDDS, MSDS, IAPT, CYPHS and DIDs linked and pseudonymised data to provide intelligence to support commissioning of health services. The linked, 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.

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 misapproproation of public funds to ensure the on-going 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. Pseudonymised – SUS and Local Flows 1) Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management and pathways. 2) Health economic modelling using: a) Analysis on provider performance against 18 weeks wait targets b) Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients c) Analysis of outcome measures for differential treatments, accounting for the full patient pathway d) Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC) flows 3) Commissioning cycle support for grouping and re-costing previous activity 4) Enables monitoring of: a) CCG outcome indicators b) Non-financial validation of patient level data c) Successful delivery of integrated care within the CCG d) Checking frequent or multiple attendances to improve early intervention and avoid admissions e) Commissioning and performance management 5) Feedback to NHS service providers on data quality at an aggregate level Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS 1) Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management and pathways. 2) Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3) Health economic modelling using: (a) Analysis on provider performance. (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.

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 with no identifiers 3) Record level output will be available for commissioners in anonymised or pseudonymised format. 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. 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 acute / community / mental health quality matrix. 6) Clinical coding reviews / audits. 7) Budget reporting down to individual GP Practice level.

Processing:

Central Midlands DSCRO will apply Type 2 objections (from 1st October 2016 onwards) before any identifiable data leaves the DSCRO. Invoice Validation 1) Central and Midlands DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the Arden and GEM CSU (Data Processor 2). 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) by using the derived commissioner field in SUS and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow b) Once the backing information is received, this will be checked against system access and reports provided by the HSCIC to confirm the payments are: - In line with Payment by Results tariffs - are in relation to a patient registered with a CCG GP or resident within the CCG area. - The health care provided should be paid by the CCG in line with CCG guidance.  3) The CCG are notified of that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between Arden and GEM CSU and the provider meaning that no data needs to be sent to the CCG. The CCG only receives notification to pay. Risk Stratification 1) SUS data identifiable at the level of NHS number regarding hospital admissions, A&E attendances and outpatient attendances is delivered securely from Central and Midlands Data Services for Commissioners Regional Office (DSCRO) to the data processor. 2) 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 Midlands and Lancashire CSU (Data Processor 1), who hold the SUS data within the secure Data Centre on N3. 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 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. 5) Midlands and Lancashire 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. 6) Once Midlands and Lancashire CSU has completed the processing, the CCG can dial in to the online system via N3 connection to access the data anonymised at patient level. Pseudonymised – SUS and Local Flows 1) Central and Midlands Data Services for Commissioners Regional Office (DSCRO) receives a flow of SUS identifiable data for the CCG from the SUS Repository. Central and Midlands DSCRO also receives identifiable local provider data for the CCG directly from Providers. 2) Data quality management of data is completed by the DSCRO and the identifiable data is then passed securely to North England CSU for the addition of derived fields, linkage of data sets and analysis. 3) Midlands and Lancashire CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 4) Patient level data will not be shared outside of the CCG. External aggregated reports only. Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS 1) Central and Midlands Data Services for Commissioning Regional Office (DSCRO) will receive a flow of pseudonymised patient level data for each CCG for Mental Health (MHSDS, MHMDS, MHLDDS), Improving Access to Psychological Therapies (IAPT), Maternity (MSDS), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes 2) Data quality management of data is completed by the DSCRO and the pseudonymised data is then passed securely to Midlands and Lancashire CSU for the addition of derived fields, linkage of data sets and analysis. Linkage is not with other datasets just between the data contained within the dataset itself. 3) Midlands and Lancashire CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 4) The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning 5) The CCG completes aggregation of required data for CCG management use – disclosing any outputs at the appropriate level. 6) Patient level data will not be shared outside of the CCG. External aggregated reports only with small numbers suppressed with HSCIC guidance.


Project 4 — DARS-NIC-387358-H3Z2J

Opt outs honoured: No - Statutory exemption to flow confidential data without consent (Statutory exemption to flow confidential data without consent)

Sensitive: Sensitive

When: 2021/01 — 2021/05.

Repeats: One-Off, Frequent Adhoc Flow

Legal basis: CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002

Categories: Anonymised - ICO code compliant

Datasets:

  • GPES Data for Pandemic Planning and Research (COVID-19)

Objectives:

NHS Digital has been provided with the necessary powers to support the Secretary of State’s response to COVID-19 under the COVID-19 Public Health Directions 2020 (COVID-19 Directions) and support various COVID-19 purposes, including those set out below, through: • establishing and operating information systems to collect and analyse data in connection with COVID-19 for COVID-19 purposes, and • developing and operating information and communication systems to deliver services in connection with COVID-19 for COVID-19 purposes, Such COVID-19 purposes include the following: a) Paragraph 2.2.2 of the COVID-19 Directions: identifying and understanding information about patients or potential patients with or at risk of COVID-19 , information about incidents of patient exposure to COVID-19 and the management of patients with or at risk of COVID-19 including: locating, contacting, screening, flagging and monitoring such patients and collecting information about and providing services in relation to testing, diagnosis, self-isolation, fitness to work, treatment, medical and social interventions and recovery from COVID-19 b) Paragraph 2.2.3 of the COVID-19 Directions: understanding information about patient access to health services and adult social care services as a direct or indirect result of COVID-19 and the availability and capacity of those services c) Paragraph 2.2.4 of the COVID-19 Directions: monitoring and managing the response to COVID-19 by health and social care bodies and the Government including providing information to the public about COVID-19 and its effectiveness and information about capacity, medicines, equipment, supplies, services and the workforce within the health services and adult social care services GPES data for pandemic planning and research (GDPPR COVID 19)) To support the response to the outbreak, NHS Digital has been legally directed to collect and analyse healthcare information about patients from their GP record for the duration of the COVID-19 emergency period under the above COVID-19 Directions. The data which NHS Digital has collected and is providing under this agreement includes coded health data, which is held in a patients GP record such as details of: • diagnoses and findings • medications and other prescribed items • investigations, tests and results • treatments and outcomes • vaccinations and immunisations Details of any sensitive SNOMED codes can be found in the Reference Data and GDPPR COVID 19 user guides hosted on the NHS Digital website. SNOMED codes are included in GDPPR data. There are no free text record entries in the data. The Controller will use the pseudonymised GDPPR COVID 19 data to provide intelligence to support their local response to the COVID-19 emergency. The data is analysed so that health care provision can be planned to support the needs of the population within the CCG area for the COVID-19 purposes set out above. Such uses cases of the data include but are not limited to: • Analysis of missed appointments - Analysis of local missed/delayed referrals due to the COVID-19 crisis to estimate the potential impact to come and estimate of when ‘normal’ health and care services may resume, linked to Paragraph 2.2.3 of the COVID-19 Directions. • Patient risk stratification and predictive modelling - to highlight patients at risk of requiring hospital admission due to COVID-19, computed using algorithms executed against linked de-identified data, and identification of future service delivery models linked to Paragraph 2.2.2 of the COVID-19 Directions. As with all risk stratification, this would lead to the reidentification of a cohort of patients specifically at risk. • Resource Allocation - In order to assess system wide impact of COVID-19, the GDPPR COVID 19 data will allow reallocation of resources to the worst hit localities using their expertise in scenario planning, clinical impact and assessment of workforce needs, linked to Paragraph 2.2.4 of the COVID-19 Directions: The data may be only be linked by the Recipient to other datasets which it holds under a current data sharing agreement (where such data is provided for the purposes of commissioning) with NHS Digital. Reidentification of individuals is not permitted under this DSA. The linked data may only be used for purposes stipulated within this agreement, and may only be held and used whilst both data sharing agreements are live and in date. Using the linked data for any other purposes, including non-COVID-19 purposes would be considered a breach of this agreement. LEGAL BASIS FOR PROCESSING DATA: Legal Basis for NHS Digital to Disseminate the Data: NHS Digital is able to disseminate data with the Recipients for the agreed purposes under a notice issued to NHS Digital by the Secretary of State for Health and Social Care under Regulation 3(4) of the Health Service Control of Patient Information Regulations (COPI) dated 17 March 2020 (the NHSD COPI Notice). The Recipients are health organisations covered by Regulation 3(3) of COPI and the agreed purposes (paragraphs 2.2.2-2.2.4 of the COVID-19 Directions, as stated below in section 5a) for which the disseminated data is being shared are covered by Regulation 3(1) of COPI. Under the Health and Social Care Act, NHS Digital is relying on section 261(5)(d) – necessary or expedient to share the disseminated data with the Recipients for the agreed purposes. Legal Basis for Processing: The Recipients are able to receive and process the disseminated data under a notice issued to the Recipients by the Secretary of State for Health and Social Care under Regulation 3(4) of COPI dated 20th March (the Recipient COPI Notice section 2). The Secretary of State has issued notices under the Health Service Control of Patient Information Regulations 2002 requiring the following organisations to process information: Health organisations “Health Organisations” defined below under Regulation 3(3) of COPI includes CCGs for the reasons explained below. These are clinically led statutory NHS bodies responsible for the planning and commissioning of health care services for their local area The Secretary of State for Health and Social Care has issued NHS Digital with a Notice under Regulation 3(4) of the National Health Service (Control of Patient Information Regulations) 2002 (COPI) to require NHS Digital to share confidential patient information with organisations permitted to process confidential information under Regulation 3(3) of COPI. These include: • persons employed or engaged for the purposes of the health service Under Section 26 of the Health and Social Care Act 2012, CCG’s have a duty to provide and manage health services for the population. Under GDPR, the Recipients can rely on Article 6(1)(c) – Legal Obligation to receive and process the Disclosed Data from NHS Digital for the Agreed Purposes under the Recipient COPI Notice. As this is health information and therefore special category personal data the Recipients can also rely on Article 9(2)(h) – preventative or occupational medicine and para 6 of Schedule 1 DPA – statutory purpose.

Expected Benefits:

• Manage demand and capacity • Reallocation of resources • Bring in additional workforce support • Assists commissioners to make better decisions to support patients • Identifying COVID-19 trends and risks to public health • Enables CCG’s to provide guidance and develop policies to respond to the outbreak • Controlling and helping to prevent the spread of the virus

Outputs:

• Operational planning to predict likely demand on primary, community and acute service for vulnerable patients • Analysis of resource allocation • Investigating and monitoring the effects of COVID-19 • Patient Stratification, such as: o Patients at highest risk of admission o Frail and elderly o Patients that are currently in hospital o Patients with prescriptions related to COVID-19 o Patients recently Discharged from hospital

Processing:

PROCESSING CONDITIONS: Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital. Data Processors must only act upon specific instructions from the Data Controller. All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake. Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. 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 i.e.: employees, agents and contractors of the Data Recipient who may have access to that data). The Recipients will keep their cut of the electronic disseminated data in an encrypted form and take all required security measures to protect the disseminated data and they will not generate copies of their cuts of the disseminated data unless this is strictly necessary. Where this is necessary, the Recipients will keep a log of all copies of the disseminated data and who is controlling them and ensure these are updated and destroyed securely. Onward sharing is not permitted under this agreement. The data disseminated will only be used for COVID-19 GDPPR purposes as described in this DSA, any other purpose is excluded. 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. AUDIT All access to data is auditable by NHS Digital in accordance with the Data Sharing Framework Contract and NHS Digital terms. Under the Local Audit and Accountability Act 2014, section 35, Secretary of State has power to audit all data that has flowed, including under COPI. DATA MINIMISATION: Data Minimisation in relation to the data sets listed within the application are listed below: • Patients who are normally registered and/or resident within the CCG region (including historical activity where the patient was previously registered or resident in another commissioner). and/or • Patients treated by a provider where the CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy. and/or • Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of the CCG. The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets: - GDPPR COVID 19 Data Pseudonymisation is completed within the DSCRO and is then disseminated as follows: 1. Pseudonymised GDPPR COVID 19 data is securely transferred from the DSCRO to the Data Controller / Processor 2. Aggregation of required data will be completed by the Controller (or the Processor as instructed by the Controller). 3. Patient level data may not be shared by the Controller (or any of its processors).


Project 5 — DARS-NIC-360432-Z1Q8K

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

Sensitive: Sensitive

When: 2021/03 — 2021/05.

Repeats: One-Off, Frequent Adhoc Flow

Legal basis: Health and Social Care Act 2012 - s261(5)(d)

Categories: Anonymised - ICO code compliant

Datasets:

  • Acute-Local Provider Flows
  • Ambulance-Local Provider Flows
  • Children and Young People Health
  • Civil Registration - Births
  • Civil Registration - Deaths
  • Community Services Data Set
  • Community-Local Provider Flows
  • Demand for Service-Local Provider Flows
  • Diagnostic Imaging Dataset
  • Diagnostic Services-Local Provider Flows
  • Emergency Care-Local Provider Flows
  • e-Referral Service for Commissioning
  • Experience, Quality and Outcomes-Local Provider Flows
  • Improving Access to Psychological Therapies Data Set
  • Maternity Services Data Set
  • Mental Health and Learning Disabilities Data Set
  • Mental Health Minimum Data Set
  • Mental Health Services Data Set
  • Mental Health-Local Provider Flows
  • National Cancer Waiting Times Monitoring DataSet (CWT)
  • National Diabetes Audit
  • Other Not Elsewhere Classified (NEC)-Local Provider Flows
  • Patient Reported Outcome Measures
  • Personal Demographic Service
  • Population Data-Local Provider Flows
  • Primary Care Services-Local Provider Flows
  • Public Health and Screening Services-Local Provider Flows
  • Summary Hospital-level Mortality Indicator
  • SUS for Commissioners

Objectives:

The data accessed through this NHS Digital agreement will be used by the Clinical Commissioning Group and Local Authorities in the fulfilment of statutory duties of commissioners and public health functions. For commissioners, these duties under section 26 of the 2012 Health & Social Care Act include duties for Clinical Commissioning Groups (CCGs) to: - (14Q) Exercising functions effectively, efficiently, and economically. - (14R) Secure continuous improvement in the quality of services provided to individuals for or in connection with the prevention, diagnosis or treatment of illness, and securing continuous improvement in the outcomes that are achieved from the provision of the services. - (14T) Reduce inequalities between patients with respect to their ability to access health services and reduce inequalities between patients with respect to the outcomes achieved by the provision of health services. - (14Z1) Exercise its functions with a view to securing that the provision of health services is integrated with the provision of health-related services or social care services. For local authorities, these duties will include fulfilment of its public health function, specifically to support and improve: - Provision of the duty under 2013 Regulations statutory ‘core offer’ public health advice and support provided to local NHS commissioners, and support commissioners in their duty under section 26 of the Health & Social Care Act 2012 to obtain advice appropriate for enabling CCGs to appropriately discharge its functions for the prevention, diagnosis or treatment of illness, and the protection of public health. - Support the duty of the local authority under section 12 of the Health and Social Care Act 2012 to take appropriate steps to improve the health of the population. - Support the duty of the local authority under sections 192 and 193 of the 2012 Act to consult on and publish Joint Strategic Needs Assessments (JSNAs) and Joint Health and Wellbeing Strategies (JHWSs) produced in collaboration with NHS and voluntary sector partners on the Health and Wellbeing Board. - Conduct health impact assessments, assessing the potential impacts on health and the wider social economic and environmental determinants of health of Local Authority and CCG strategic plans, policies and services. - The capability of the local public health intelligence service to undertake comparative longitudinal analyses of patterns of and variations in the incidence and prevalence of disease and risks to public health; demand and access to treatment and preventative care services’ variations in health outcomes between groups in the population; the level of integration between local health and care services; the local associations between causal risk factors and health status and outcomes. The CCGs and Local Authorities commission services from a range of providers covering a wide array of health and care functions. Each of the data flow categories requested supports the commissioned activity of one or more providers. Pseudonymised (containing both clinical and financial information) data will be utilised to provide intelligence to support the commissioning of these health and care services, to ensure that adequate services are commissioned to meet patient need within the CCG area, and that these services are designed in such a way as to maximise opportunities for improving efficiency, efficacy, reducing inequalities, and improving outcomes. The data controllers under this agreement are; CCG: NHS Birmingham and Solihull CCG Local Authority: Birmingham City Council and Solihull Metropolitan Borough Council. The data controllers also process data The data processors under this agreement are Midlands and Lancashire Commissioning Support Unit - process data for the purpose of commissioning Microsoft Limited - Provide cloud services for Midlands and Lancashire Commissioning Support Unit LIMA Networks Limited - Provide IT Infrastructure for Midlands and Lancashire Commissioning Support Unit No other organisations are involved in the project. Legal Basis for Processing Data: Data accessed under this Agreement will be processed in accordance with GDPR Article 6(1)(e) (processing is necessary for the performance of a task in the public interest or in the exercise of official authority vested in the controller) and Article 9(2)(h) (processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services on the basis of Union or Member State law or pursuant to contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3 of the Article). The following pseudonymised datasets are required to provide this support for the commissioning of health services: - Secondary Uses Service (SUS+) - Local Provider Flows o Acute o Ambulance o Community o Demand for Service o Diagnostic Service o Emergency Care o Experience, Quality and Outcomes o Mental Health o Other Not Elsewhere Classified o Population Data o Primary Care Services o Public Health Screening - Mental Health Minimum Data Set (MHMDS) - Mental Health Learning Disability Data Set (MHLDDS) - Mental Health Services Data Set (MHSDS) - Maternity Services Data Set (MSDS) - Improving Access to Psychological Therapy (IAPT) - Child and Young People Health Service (CYPHS) - Community Services Data Set (CSDS) - Diagnostic Imaging Data Set (DIDS) - National Cancer Waiting Times Monitoring Data Set (CWT) - Civil Registries Data (CRD) (Births) - Civil Registries Data (CRD) (Deaths) - National Diabetes Audit (NDA) - Patient Reported Outcome Measures (PROMs) - e-Referral Service (eRS) - Personal Demographics Service (PDS) - Summary Hospital-level Mortality Indicator (SHMI) The pseudonymised data is required to for the following purposes:  Population health management: • Understanding the interdependency of care services • Targeting care more effectively • Using value as the redesign principle  Data Quality and Validation – allowing data quality checks on the submitted data  Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them  Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs  Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated  Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another  Service redesign  Health Needs Assessment – identification of underlying disease prevalence within the local population  Patient stratification and predictive modelling - to highlight cohorts of patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models  Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.  Support measuring the health, mortality or care needs of the total local population

Expected Benefits:

Commissioning and Service Improvement Analyses - 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. - Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. - 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). - Commissioning cycle support for grouping and re-costing previous activity. - Enables monitoring of: a. CCG outcome indicators. b. Financial and Non-financial validation of activity. c. Successful delivery of integrated care within the CCG. d. Checking frequent or multiple attendances to improve early intervention and avoid admissions. e. Case management. f. Care service planning. g. Commissioning and performance management. h. List size verification by GP practices. i. Understanding the care of patients in nursing homes. - Feedback to NHS service providers on data quality at an aggregate and individual record level only on data initially provided by the service providers. - 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. - 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. - 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. - 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. - Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics. - Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts. - Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities. - Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed. - Insight to understand the numerous factors that play a role in the outcome for multiple datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice. - Provision of indicators of health problems, and patterns of risk within the commissioning region. - Support of benchmarking for evaluating progress in future years. - Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people. - Assists commissioners to make better decisions to support patients - Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die. - Clinical - understand reasons why patients are dying, what additional support services can be put in to support. - Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust. - Manage demand - understanding the quantity of assessments required enable the ability improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.

Outputs:

Commissioning and Service Improvement Analyses - 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. - Readmissions analysis. - Production of aggregate reports for CCG Business Intelligence. - Production of project / programme level dashboards. - Monitoring of acute / community / mental health quality matrix. - Clinical coding reviews / audits. - Budget reporting down to individual GP Practice level. - GP Practice level dashboard reports. - Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports. - Data Quality and Validation measures allowing data quality checks on the submitted data. - Contract Management and Modelling. - Patient Stratification, such as: a. Patients at highest risk of admission b. High cost activity uses (top 15%) c. Frail and elderly d. Patients that are currently in hospital e. Patients with most referrals to secondary care f. Patients with most emergency activity g. Patients with most expensive prescriptions h. Patients recently moving from one care setting to another i. Discharged from hospital j. Discharged from community - Joint Strategic Needs Assessment - Joint Health & Wellbeing Strategy - The annual report of the Director of Public Health. - Reports commissioned by the Health and Wellbeing Board. - Public health and wider Local Authority health and wellbeing commissioning strategies and plans. - Public health advice to NHS commissioners. - Responses to licensing applications and other statutory Local Authority functions requiring public health input. - Local health profiles. - Health impact assessments and equity audits; and, among other outputs. - Responses to internal and external requests for information and intelligence on the health and wellbeing of the population. The outputs listed will support both the CCG and the local authorities to fulfil their statutory duties. This joint application will allow collaboration where these statutory duties overlap All outputs are directly and indirectly related to commissioning

Processing:

Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital. Data Processors must only act upon specific instructions from the Data Controller. Data can only be stored at the addresses listed under storage addresses. All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role. Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released 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. 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). Onward Sharing Patient level data will not be shared outside of the CCG and local authorities 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. Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set. 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 Minimisation Data Minimisation in relation to the data sets listed within the application are listed below. This also includes the purpose on which they would be applied - For the purpose of Commissioning: - Patients who are normally registered and/or resident within the NHS Birmingham and Solihull CCG (including historical activity where the patient was previously registered or resident in another commissioner). and/or - Patients treated by a provider where NHS Birmingham and Solihull CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy this is only for commissioning and relates to both national and local flows. and/or - Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of NHS Birmingham and Solihull CCG - this is only for commissioning and relates to both national and local flows. There is no other mechanism to achieve the same result. Both CCG and Local Authority teams will require access to record-level, linkable (within the boundaries of the NHSD agreement) datasets to be able to fulfil statutory obligations around commissioning, commissioning support and health and wellbeing analyses. Microsoft Limited provide Cloud Services for NHS Midlands and Lancashire Commissioning Support Unit and do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data. Lima Networks LTD supply IT infrastructure for NHS Midlands and Lancashire Commissioning Support Unit and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. Data will be stored within a single platform hosted by NHS Midlands and Lancashire Commissioning Support Unit, and will be accessed by Birmingham and Solihull CCG, Solihull MBC and Birmingham CC using this platform exclusively, and will not be re-hosted in any other platform outside of this environment. This includes granting of access to the database[s] containing the data. The majority of locations belong to the CSU who host the data. The additional locations specified within this Agreement are to allow the data from the system to be extracted if necessary. In addition to the dissemination of Cancer Waiting Times Data via the DSCRO, the CCG is able to access reports held within the CWT system in NHS Digital directly. Access within the CCG is limited to those with a need to process the data for the purposes described in this agreement. A CCG user will be able to access the provider extracts from the portal for any provider where at least 1 patient for whom they are the registered CCG for that individuals GP practice appears in that setting Although a CCG user may have access to pseudonymised patient information not related to that CCG, users should only process and analyse data for which they have a legitimate relationship (as described within Data Minimisation). The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets: 1. SUS+ 2. Local Provider Flows (received directly from providers) a. Acute b. Ambulance c. Community d. Demand for Service e. Diagnostic Service f. Emergency Care g. Experience, Quality and Outcomes h. Mental Health i. Other Not Elsewhere Classified j. Population Data k. Primary Care Services l. Public Health Screening 3. Mental Health Minimum Data Set (MHMDS) 4. Mental Health Learning Disability Data Set (MHLDDS) 5. Mental Health Services Data Set (MHSDS) 6. Maternity Services Data Set (MSDS) 7. Improving Access to Psychological Therapy (IAPT) 8. Child and Young People Health Service (CYPHS) 9. Community Services Data Set (CSDS) 10. Diagnostic Imaging Data Set (DIDS) 11. National Cancer Waiting Times Monitoring Data Set (CWT) 12. Civil Registries Data (CRD) (Births) 13. Civil Registries Data (CRD) (Deaths) 14. National Diabetes Audit (NDA) 15. Patient Reported Outcome Measures (PROMs) 16. e-Referral Service (eRS) 17. Personal Demographics Service (PDS) 18. Summary Hospital-level Mortality Indicator (SHMI) Data Processor 1 NHS Midlands and Lancashire Commissioning Support Unit 1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit (NDA), Patient Reported Outcome Measures (PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS) and Summary Hospital-level Mortality Indicator (SHMI) data only is securely transferred from the DSCRO to NHS Midlands and Lancashire Commissioning Support Unit. 2. NHS Midlands and Lancashire Commissioning Support Unit add derived fields by using existing data, link data and provide analysis to: a. See patient journeys for pathways or service design, re-design and de-commissioning. b. Check recorded activity against contracts or invoices and facilitate discussions with providers. c. Undertake population health management d. Undertake data quality and validation checks e. Thoroughly investigate the needs of the population f. Understand cohorts of residents who are at risk g. Conduct Health Needs Assessments 3. Allowed linkage is between the data sets contained within point 1. No other data linkage will take place. 4. NHS Midlands and Lancashire Commissioning Support Unit then pass the processed, pseudonymised and linked data to the Data Controllers. 5. Aggregation of required data will be completed by NHS Midlands and Lancashire Commissioning Support Unit or the Data Controllers. 6. Patient level data will not be shared outside of the Data Controllers / Processors and will only be shared within the Data Controllers / Processors on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set. There is no requirement for the analytical teams (either CCG or local authority) to re-identify patients, but in the cases of the development of risk stratification or other similar primary use tools, the data controllers may need the facility to provide identifiable results back to direct healthcare professionals or local authority direct care staff only for the purpose of direct care. All re-id requests will be processed and authorised by the DSCRO on a case by case basis. National data opt outs are not applied in these cases as they are for the purposes of direct care. An example of a request for the re-id of patients for direct care may be; A&E High Attendance usage Practices can filter data to show for example the number of A&E attendances in a given period for each patient. The Practice would then look into these patients to review their care and try and reduce A&E attendances and/or sign post the patients to community services/MH Services. An outcome of this is earlier intervention in the patient(s) care thus potentially reducing future costs and minimising future risk. Risk Stratification-type re-IDs Practices can re-ID a list of patients with a high number of medications (ingredient count) and review the medication for these patients. This can help address the risk of polypharmacy which is recognised as an adverse risk factor for patient safety. A by-product of such reviews may be to reduce costs of medication.


Project 6 — DARS-NIC-186883-L6C8Y

Opt outs honoured: N, Y, No - data flow is not identifiable, Yes - patient objections upheld (Section 251, Section 251 NHS Act 2006, Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s))

Sensitive: Sensitive

When: 2018/06 — 2021/05.

Repeats: Frequent adhoc flow, Frequent Adhoc Flow, One-Off

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Section 251 approval is in place for the flow of identifiable data, National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Categories: Anonymised - ICO code compliant, Identifiable

Datasets:

  • Acute-Local Provider Flows
  • Ambulance-Local Provider Flows
  • Children and Young People Health
  • Community-Local Provider Flows
  • Demand for Service-Local Provider Flows
  • Diagnostic Imaging Dataset
  • Diagnostic Services-Local Provider Flows
  • Emergency Care-Local Provider Flows
  • Experience, Quality and Outcomes-Local Provider Flows
  • Improving Access to Psychological Therapies Data Set
  • Maternity Services Data Set
  • Mental Health and Learning Disabilities Data Set
  • Mental Health Minimum Data Set
  • Mental Health Services Data Set
  • Mental Health-Local Provider Flows
  • National Cancer Waiting Times Monitoring DataSet (CWT)
  • Other Not Elsewhere Classified (NEC)-Local Provider Flows
  • Population Data-Local Provider Flows
  • Primary Care Services-Local Provider Flows
  • Public Health and Screening Services-Local Provider Flows
  • SUS for Commissioners
  • Community Services Data Set
  • Civil Registration - Births
  • Civil Registration - Deaths
  • National Diabetes Audit
  • Patient Reported Outcome Measures
  • e-Referral Service for Commissioning
  • Personal Demographic Service
  • Summary Hospital-level Mortality Indicator

Objectives:

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. The legal basis is as follows: For dissemination - Section 251 of NHS Act 2006 CAG 7-07(a-c) - Section 261(7) of Health and Social Care Act 2012. GDPR: - Article 6(1)(e) - Article 9(2)(h) - Article 9(3) - Section 11 Data Protection Act 2018 Invoice Validation with be conducted by NHS Arden and Greater East Midlands Commissioning Support Unit. The CCG are advised by NHS Arden and Greater East Midlands Commissioning Support Unit whether payment for invoices can be made or not. Risk Stratification Risk stratification is a tool for identifying and predicting which patients are at high risk or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes. To conduct risk stratification Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care. The legal basis is as follows: For dissemination - Section 251 of NHS Act 2006 CAG 7-04(a) - Section 261(7) of Health and Social Care Act 2012. GDPR: - Article 6(1)(e) - Article 9(2)(h) - Article 9(3) - Section 11 Data Protection Act 2018 Risk Stratification will be conducted by NHS Midlands and Lancashire Commissioning Support Unit. Commissioning To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area. The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers. The following pseudonymised datasets are required to provide intelligence to support commissioning of health services: - Secondary Uses Service (SUS+) - Local Provider Flows o Acute o Ambulance o Community o Demand for Service o Diagnostic Service o Emergency Care o Experience, Quality and Outcomes o Mental Health o Other Not Elsewhere Classified o Population Data o Primary Care Services o Public Health Screening - Mental Health Minimum Data Set (MHMDS) - Mental Health Learning Disability Data Set (MHLDDS) - Mental Health Services Data Set (MHSDS) - Maternity Services Data Set (MSDS) - Improving Access to Psychological Therapy (IAPT) - Child and Young People Health Service (CYPHS) - Diagnostic Imaging Data Set (DIDS) - Community Services Dataset (CSDS) - National Cancer Waiting Times Dataset (NCWT) The pseudonymised data is required to for the following purposes: § Population health management: • Understanding the interdependency of care services • Targeting care more effectively • Using value as the redesign principle § Data Quality and Validation – allowing data quality checks on the submitted data § Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them § Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs § Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated § Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another § Service redesign § Health Needs Assessment – identification of underlying disease prevalence within the local population § Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. The legal basis is as follows: For dissemination - Section 261(1) of Health and Social Care Act 2012 - Section 261(2)(b)(ii) of Health and Social Care Act 2012 - GDPR: - Article 6(1)(e) - Article 9(2)(h) - Article 9(3) - Section 11 Data Protection Act 2018 Processing for commissioning will be conducted by NHS Midlands and Lancashire Commissioning Support Unit, and Arden and GEM CSU

Yielded Benefits:

n/a

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 thus allowing early intervention. 3. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required. 4. Supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework by allowing for more targeted intervention in primary care. 5. Better understanding of local population characteristics through analysis of their health and healthcare outcomes All of the above lead to improved patient experience through more effective commissioning of services. Commissioning 1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways. a. Analysis to support full business cases. b. Develop business models. c. Monitor In year projects. 2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3. Health economic modelling using: a. Analysis on provider performance against 18 weeks wait targets. b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients. c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway. d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC). 4. Commissioning cycle support for grouping and re-costing previous activity. 5. Enables monitoring of: a. CCG outcome indicators. b. Financial and Non-financial validation of activity. c. Successful delivery of integrated care within the CCG. d. Checking frequent or multiple attendances to improve early intervention and avoid admissions. e. Case management. f. Care service planning. g. Commissioning and performance management. h. List size verification by GP practices. i. Understanding the care of patients in nursing homes. 6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers. 7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these. 8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care. 9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required. 10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework. 11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics. 12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts 13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.

Outputs:

Invoice Validation 1. Addressing poor data quality issues 2. Production of reports for business intelligence 3. Budget reporting 4. Validation of invoices for non-contracted events 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. 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. 5. The CCG will be able to target specific patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions. The CCG will also be able to: o Stratify populations based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost o Plan work for commissioning services and contracts o Set up capitated budgets o Identify health determinants of risk of admission to hospital, or other adverse care outcomes. Commissioning 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of acute / community / mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include high flyers. 9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports 10. Data Quality and Validation measures allowing data quality checks on the submitted data 11. Contract Management and Modelling 12. Patient Stratification, such as: o Patients at highest risk of admission o Most expensive patients (top 15%) o Frail and elderly o Patients that are currently in hospital o Patients with most referrals to secondary care o Patients with most emergency activity o Patients with most expensive prescriptions o Patients recently moving from one care setting to another i. Discharged from hospital ii. Discharged from community

Processing:

Data must only be used as stipulated within this Data Sharing Agreement. Data Processors must only act upon specific instructions from the Data Controller. Data can only be stored at the addresses listed under storage addresses. Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data. All access to data is managed under Roles-Based Access Controls No patient level data will be linked other than as specifically detailed within this agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality and that data required by the applicant. NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data) The DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO. CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools. 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 DSCRO and from the providers – it does not flow through any other processors. Invoice Validation 1. Identifiable SUS+ Data is obtained from the SUS+ Repository to the Data Services for Commissioners Regional Office (DSCRO). 2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the NHS Arden and Greater East Midlands Commissioning Support Unit. 3. NHS Arden and Greater East Midlands Commissioning Support Unit carry out the following processing activities within the CEfF for invoice validation purposes: a. Validating that the Clinical Commissioning Group is responsible for payment for the care of the individual by using SUS+ and/or backing flow data. b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are: i. In line with Payment by Results tariffs ii. are in relation to a patient registered with a CCG GP or resident within the CCG area. iii. The health care provided should be paid by the CCG in line with CCG guidance.  4. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between NHS Arden and Greater East Midlands Commissioning Support Unit 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 1. Identifiable SUS+ data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO). 2. 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 NHS Midlands and Lancashire Commissioning Support Unit, who hold the SUS+ data within the secure Data Centre on N3. 3. Identifiable GP Data is securely sent from the GP system to NHS Midlands and Lancashire Commissioning Support Unit. 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 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. 6. Once NHS Midlands and Lancashire Commissioning Support Unit has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level. Commissioning Data Processor 1 – NHS Midlands and Lancashire Commissioning Support Unit 1.Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS) and Diagnostic Imaging data (DIDS) Community Services Dataset (CSDS) and National Cancer Waiting Times (NCWT) only is securely transferred from the DSCRO to NHS Midlands and Lancashire Commissioning Support Unit. 2. NHS Midlands and Lancashire Commissioning Support Unitadd derived fields, link data and provide analysis to: a. See patient journeys for pathways or service design, re-design and de-commissioning. b. Check recorded activity against contracts or invoices and facilitate discussions with providers. c. Undertake population health management d. Undertake data quality and validation checks e. Thoroughly investigate the needs of the population f. Understand cohorts of residents who are at risk g. Conduct Health Needs Assessments 3. Allowed linkage is between the data sets contained within point 1. 4. NHS Midlands and Lancashire Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG. 5. Aggregation of required data for CCG management use will be completed by NHS Midlands and Lancashire Commissioning Support Unit or the CCG as instructed by the CCG. 6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set. Data Processor 2 – Arden and GEM Commissioning Support Unit 1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS) and Diagnostic Imaging data (DIDS) Community Services Dataset (CSDS) and National Cancer Waiting Times (NCWT) only is securely transferred from the DSCRO to NHS Arden and GEM Commissioning Support Unit. 2. NHS Arden and GEM Commissioning Support Unit add derived fields, link data and provide analysis to: a. See patient journeys for pathways or service design, re-design and de-commissioning. b. Check recorded activity against contracts or invoices and facilitate discussions with providers. c. Undertake population health management d. Undertake data quality and validation checks e. Thoroughly investigate the needs of the population f. Understand cohorts of residents who are at risk g. Conduct Health Needs Assessments 3. Allowed linkage is between the data sets contained within point 1. 4. NHS Arden and GEM Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG. 5. Aggregation of required data for CCG management use will be completed by NHS Arden and GEM Commissioning Support Unit or the CCG as instructed by the CCG. 6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.


Project 7 — DARS-NIC-134833-S0M1M

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

Sensitive: Sensitive

When: 2018/06 — 2019/04.

Repeats: Frequent adhoc flow, Frequent Adhoc Flow

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

Categories: Anonymised - ICO code compliant

Datasets:

  • Acute-Local Provider Flows
  • Ambulance-Local Provider Flows
  • Children and Young People Health
  • Community Services Data Set
  • Community-Local Provider Flows
  • Demand for Service-Local Provider Flows
  • Diagnostic Imaging Dataset
  • Diagnostic Services-Local Provider Flows
  • Emergency Care-Local Provider Flows
  • Experience, Quality and Outcomes-Local Provider Flows
  • Improving Access to Psychological Therapies Data Set
  • Maternity Services Data Set
  • Mental Health and Learning Disabilities Data Set
  • Mental Health Minimum Data Set
  • Mental Health Services Data Set
  • Mental Health-Local Provider Flows
  • National Cancer Waiting Times Monitoring DataSet (CWT)
  • Other Not Elsewhere Classified (NEC)-Local Provider Flows
  • Population Data-Local Provider Flows
  • Primary Care Services-Local Provider Flows
  • Public Health and Screening Services-Local Provider Flows
  • SUS for Commissioners

Objectives:

Commissioning To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area. The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers. The following pseudonymised datasets are required to provide intelligence to support commissioning of health services: - Secondary Uses Service (SUS+) - Local Provider Flows o Acute o Ambulance o Community o Demand for Service o Diagnostic Service o Emergency Care o Experience, Quality and Outcomes o Mental Health o Other Not Elsewhere Classified o Population Data o Primary Care Services o Public Health Screening - Mental Health Minimum Data Set (MHMDS) - Mental Health Learning Disability Data Set (MHLDDS) - Mental Health Services Data Set (MHSDS) - Maternity Services Data Set (MSDS) - Improving Access to Psychological Therapy (IAPT) - Child and Young People Health Service (CYPHS) - Community Services Data Set (CSDS) - Diagnostic Imaging Data Set (DIDS) - National Cancer Waiting Times Monitoring Data Set (CWT) The pseudonymised data is required to for the following purposes: § Population health management: • Understanding the interdependency of care services • Targeting care more effectively • Using value as the redesign principle § Data Quality and Validation – allowing data quality checks on the submitted data § Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them § Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs § Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated § Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another § Service redesign § Health Needs Assessment – identification of underlying disease prevalence within the local population § Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. Processing for commissioning will be conducted by Arden and Greater East Midlands Commissioning Support Unit. The CCG have engaged the services of Arden and GEMCSU to undertake specialist business intelligence analysis – Specialist Strategic Service Improvement (SSSI). This is totally separate specialist analysis that supports the CCG in health care provision and health profiling of the population within the CCG areas. This is additional to the processing and analysis done by MLCSU. This specialist analysis significantly complements the analysis undertaken by MLCSU in their core business intelligence service to the CCGs.

Yielded Benefits:

Any future application for extension or renewal beyond 31/05/2019 should include detail of any outputs produced or benefits achieved through use of DSfC Data

Expected Benefits:

Commissioning 1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways. a. Analysis to support full business cases. b. Develop business models. c. Monitor In year projects. 2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3. Health economic modelling using: a. Analysis on provider performance against 18 weeks wait targets. b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients. c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway. d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC). 4. Commissioning cycle support for grouping and re-costing previous activity. 5. Enables monitoring of: a. CCG outcome indicators. b. Financial and Non-financial validation of activity. c. Successful delivery of integrated care within the CCG. d. Checking frequent or multiple attendances to improve early intervention and avoid admissions. e. Case management. f. Care service planning. g. Commissioning and performance management. h. List size verification by GP practices. i. Understanding the care of patients in nursing homes. 6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers. 7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these. 8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care. 9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required. 10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework. 11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics. 12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts 13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.

Outputs:

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

Processing:

Data must only be used as stipulated within this Data Sharing Agreement. Data Processors must only act upon specific instructions from the Data Controller. Data can only be stored at the addresses listed under storage addresses. 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. Commissioning The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets: 1. SUS+ 2. Local Provider Flows (received directly from providers) a. Acute b. Ambulance c. Community d. Demand for Service e. Diagnostic Service f. Emergency Care g. Experience, Quality and Outcomes h. Mental Health i. Other Not Elsewhere Classified j. Population Data k. Primary Care Services l. Public Health Screening 3. Mental Health Minimum Data Set (MHMDS) 4. Mental Health Learning Disability Data Set (MHLDDS) 5. Mental Health Services Data Set (MHSDS) 6. Maternity Services Data Set (MSDS) 7. Improving Access to Psychological Therapy (IAPT) 8. Child and Young People Health Service (CYPHS) 9. Community Services Data Set (CSDS) 10. Diagnostic Imaging Data Set (DIDS) 11. National Cancer Waiting Times Monitoring Data Set (CWT) Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows: Data Processor 1 – Arden and Greater East Midlands Commissioning Support Unit 1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS). Diagnostic Imaging data (DIDS) and National Cancer Waiting Times Monitoring Data Set (CWT) only is securely transferred from the DSCRO to Arden and Greater East Midlands Commissioning Support Unit. 2. Arden and Greater East Midlands Commissioning Support Unit add derived fields, link data and provide analysis to: a. See patient journeys for pathways or service design, re-design and de-commissioning . b. Check recorded activity against contracts or invoices and facilitate discussions with providers c. Undertake population health management d. Undertake data quality and validation checks e. Thoroughly investigate the needs of the population f. Understand cohorts of residents who are at risk g. Conduct Health Needs Assessments 3. Allowed linkage is between the data sets contained within point 1. 4. Arden and Greater East Midlands Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG. 5. Aggregation of required data for CCG management use will be completed by Arden and Greater East Midlands Commissioning Support Unit or the CCG as instructed by the CCG. 6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.