NHS Digital Data Release Register - reformatted

NHS Kirklees CCG

🚩 NHS Kirklees CCG received multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Kirklees 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 — DARS-NIC-90698-W7X6Y

Opt outs honoured: N, Y, No - data flow is not identifiable (Section 251, Does not include the flow of confidential data)

Sensitive: Sensitive

When: 2018/06 — 2021/03.

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

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
  • 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
  • National Cancer Waiting Times Monitoring DataSet (CWT)
  • Civil Registration - Births
  • Civil Registration - Deaths
  • National Diabetes Audit
  • Patient Reported Outcome Measures

Objectives:

Risk Stratification To use SUS data identifiable at the level of NHS number according to S.251 CAG 7-04(a) (and Primary Care Data) for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users. Risk Stratification enables General Practitioners (GPs) to better target intervention in Primary Care. Risk Stratification will be conducted by eMBED. Commissioning To use pseudonymised data to provide intelligence to support commissioning of health services. The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers. 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) 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 eMBED Health Consortium, The Health Informatics Service and PI Care and Health Ltd.

Yielded Benefits:

Yielded benefits include 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. Enables monitoring of: a. CCG outcome indicators. b. Financial and Non-financial validation of activity. c. Checking frequent or multiple attendances to improve early intervention and avoid admissions. e. Commissioning and performance management.

Expected Benefits:

Risk Stratification Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised: 1. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these. 2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care. 3. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required. 4. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework. 5. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics. All of the above lead to improved patient experience through more effective commissioning of services. 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. 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. Data Processor 4 - PI Benchmark The Integrated Commissioning Executive for Kirklees (which includes the local authority and both NHS Greater Huddersfield CCG and NHS North Kirklees CCG) wanted to better appreciate the potential and impact of how Better Care Fund monies were being utilised, and whether there were more effective ways to analyse or target the work. PI Care and Health were selected for this work based on their existing work in this field, their clarity in defining the detail of what could be done and how, their engagement and attitude, ability to deliver and price.

Outputs:

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 is derived from the GP data sourced from their own systems. 2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk. 3. Record level output will be available for commissioners (of the CCG), pseudonymised at patient level and aggregate with small number suppression. 4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient. Commissioning 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. The Health Informatics Service THIS provides a range of data management functions and outputs as specified by the CCG. Outputs include the provision of pseudonymised data to allow it to be viewed and interrogated, as well as aggregate level reports. These outputs can take the form of data held in a secure data warehouse or files e.g. database, CSV, Excel files. The warehousing of data uses a robust and tested platform, i.e. the warehouse (HPS database) has been developed over circa 20 years to reflect commissioner/CCG requirements and is in a THIS IT environment, so is secure. Utilising THIS data management also provides the following benefits: • Utilising local knowledge and expertise on data flows that are specific to the CCG in particular data flowing from Calderdale and Huddersfield NHS Trust • Making efficient use of existing processes that are well established and tailored to the CCG requirements • Providing the resource / capacity required to process data flows for the CCG The aggregate outputs fall into the following areas: • Studying variation and trends over time • Monitoring of healthcare contract activity plans • Performance monitoring • Quality monitoring The categories of outputs to the CCG includes: • Monitoring of hospital activity against planned levels where an established contract exists between a provider and a commissioner inclusive of: o Overall contract reporting of actual vs plan for activity and value at aggregate level o Reconciliation reports between local hospital data, and SUS records at aggregate/anonymised in context level. o Contract Data Quality reporting at anonymised in context record level. • “Deep dive” analysis of hospital activity at aggregate level. Specific examples of report outputs include: Commissioner Reporting - Summary by Provider View – Plan and Actuals Year to Date (YTD) - Summary by Patient Outcome Data (POD) view - Plan and Actuals YTD - Summary by Provider View – Activity and Finance Variance by POD - Planned Care by Provider View – Activity and Finance Variance by POD - Planned Care by POD View – Activity, Finance Plan and Actuals YTD - Provider Reporting - Readmissions analysis - Production of aggregate reports for CCGs Business Intelligence - Production of project / Programme level dashboards - Monitoring of acute / community services - Budget reporting

Processing:

Processing activities: Data must only be used as stipulated within this Data Sharing Agreement. Data Processors must only act upon specific instructions from the Data Controller. Data can only be stored at the addresses listed under storage addresses. The Data Controller and any Data Processor will only have access to records of patients of residence and registration within the CCG. Access is limited to those substantive employees with authorised user accounts used for identification and authentication. 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. 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. No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant. The DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO. Risk Stratification On or before 20th July 2017, one of these data processors will be instructed to cease delivery of risk stratification, at which point a data destruction certificate will also be requested from that data processor. Notification will be made in writing to both Data Processors of the decision to cease or continue service, NHS Digital will sent a copy The data destruction certificate will also be shared with NHS Digital. From the 21st of July 2017 there will be only one Data Processor for Risk Stratification for North Kirklees. eMBED and NECS will run adjacently to one another until the 20th of July 2017 or until notified A data destruction certificate for the previous risk stratification data processor will be provided Data Processor 1 - North England CSU (NECS) 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 North of England Commissioning Support Unit hold the SUS data within the secure Data Centre on N3. 3. Identifiable GP Data is securely sent from the GP system to North of England 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. Access to the Risk Stratification system that North of England Commissioning Support Unit hosts is limited to those substantive employees with authorised user accounts used for identification and authentication. 7. Once North of England Commissioning Support Unit has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level. Data Processor 2 - eMBED 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 eMBED Health Consortium who hold the SUS data within the secure Data Centre on N3. 3. Identifiable GP Data is securely sent from the GP system to eMBED Health Consortium. 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. Access to the Risk Stratification system that eMBED Health Consortium hosts is limited to those substantive employees with authorised user accounts used for identification and authentication. 7. Once eMBED Health Consortium has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level. Commissioning The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets: 1. SUS 2. Local Provider Flows (received directly from providers) 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 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. Diagnostic Imaging Data Set (DIDS) Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows: Data Processor 1 – eMBED Health Consortium 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) only is securely transferred from the DSCRO to North of England Commissioning Support Unit for the addition of derived fields. 2) North of England Commissioning Support Unit then pass the processed, pseudonymised data to both eMBED Health Consortium and the CCG. 3) eMBED Health Consortium add derived fields, link data and provide analysis. 4) Allowed linkage is between the data sets contained within point 1. 5) eMBED Health Consortium then pass the processed, pseudonymised and linked data to the CCG. 6) The CCG analyse the data received from eMBED Health Consortium and North of England Commissioning Support Unit to see patient journeys for pathways or service design, re-design and de-commissioning. 7) Aggregation of required data for CCG management use will be completed by North of England Commissioning Support Unit, eMBED Health Consortium or the CCG as instructed by the CCG. 8) Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared. 9) The CCG securely transfer Pseudonymised data back to the provider to: a) confirm how patients are reported in SUS, and how the commissioner can reliably group these patients into categories for points of delivery; b) allow for granular data validation whereby a commissioner may query the SUS record, and need to pass it back to the provider for checking; and c) to allow the provider to undertake further analysis of a cohort of their patients as requested and specified by the commissioner. The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider. Data Processor 3 – The Health Informatics Service 1) Pseudonymised SUS only is securely transferred from the DSCRO to North of England Commissioning Support Unit for the addition of derived fields. 2) North of England Commissioning Support Unit then pass the processed, pseudonymised data to both The Health Informatics Service 3) The Health Informatics Service apply business rules, pricing and create additional categorical fields. 4) The Health Informatics Service securely transfer the Pseudonymised data to eMBED Health Consortium to flow directly to the CCG. 5) Aggregation of required data for CCG management use will be completed by North of England Commissioning Support Unit, eMBED Health Consortium 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. Data Processor 4 - PI Benchmark 1. SUS, pseudonymised using the University of Nottingham open pseudonymiser tool is transferred from the DSCRO to PI Care and Health Ltd. The University of Nottingham open pseudonymiser tool is a standalone windows desktop application which creates a digest of one or more columns of a CSV file, using a shared key (SALT file) controlled by the DSCRO. 2. Data quality management of social care data is completed by Kirklees Council. The social care data is then pseudonymised using University of Nottingham open pseudonymiser tool. Pseudonymised Social Care Data will be sent to PI Care and Health Ltd direct from Kirklees Council via secure FTP. 3. The pseudonymisation key cannot be used to re-identify data as the tool does not allow for this to happen, it only allows for one way pseudonymisation. 4. PI Care and Health Ltd then link the data using the common pseudo link, which is undertaken within a controlled environment by a named member of staff, who then produce online reports using CareTrak data analysis tool to provide Greater Huddersfield CCG with a range of high level commissioning intelligence based on integrated pathways of care in Kirklees. Access to these reports is based on user access controls, as follows: - Access to the commissioning intelligence at pseudonymised level is accessible by 2 named members of staff in the CCG (based on a super user access licence for CareTrak) - Access to aggregate commissioning intelligence (anonymised) is available to up to 3 additional users across the CCG (standard user licence) - External aggregated reports only with small number suppression can be shared. Access to the CareTrak system, both on a super user and standard user approach is governed via respective organisation employee code of practice, data protection policies and information governance protocols. Additionally, super users conform to a specific information access agreement which mitigates the risk of how the pseudo data can be handled and used. The Integrated Commissioning Executive for Kirklees (which includes the local authority and both NHS Greater Huddersfield CCG and NHS North Kirklees CCG) wanted to better appreciate the potential and impact of how Better Care Fund monies were being utilised, and whether there were more effective ways to analyse or target the work. PI Care and Health were selected for this work based on their existing work in this field, their clarity in defining the detail of what could be done and how, their engagement and attitude, ability to deliver and price.


Project 2 — DARS-NIC-90661-W2S5Q

Opt outs honoured: N, Y, No - data flow is not identifiable, Yes - patient objections upheld (Section 251, Section 251 NHS Act 2006)

Sensitive: Sensitive

When: 2018/06 — 2021/03.

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(7)

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
  • 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
  • National Cancer Waiting Times Monitoring DataSet (CWT)
  • Civil Registration - Births
  • Civil Registration - Deaths
  • National Diabetes Audit
  • Patient Reported Outcome Measures

Objectives:

Invoice Validation As an approved Controlled Environment for Finance (CEfF), North of England CSU receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (c)/2013, to undertake invoice validation on behalf of the CCG. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. The CCG are advised by the CSU whether payment for invoices can be made or not. Risk Stratification To use SUS data identifiable at the level of NHS number according to S.251 CAG 7-04(a)/2013 (and Primary Care Data) for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. Commissioning (Pseudonymised) – SUS and Local Flows To use pseudonymised data to provide intelligence to support commissioning of health services. The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers. Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services : - Mental Health Minimum Data Set (MHMDS) - Mental Health Learning Disability Data Set (MHLDDS) - Mental Health Services Data Set (MHSDS) - Maternity Services Data Set (MSDS) - Improving Access to Psychological Therapy (IAPT) - Child and Young People Health Service (CYPHS) - Diagnostic Imaging Data Set (DIDS) The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.

Expected Benefits:

Invoice Validation 1. Financial validation of activity 2. CCG Budget control 3. Commissioning and performance management 4. Meeting commissioning objectives without compromising patient confidentiality 5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care Risk Stratification Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised: 1. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these. 2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care. 3. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required. 4. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework. 5. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics. All of the above lead to improved patient experience through more effective commissioning of services. Commissioning (Pseudonymised) – SUS and Local Flows 1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways. a. Analysis to support full business cases. b. Develop business models. c. Monitor In year projects. 2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3. Health economic modelling using: a. Analysis on provider performance against 18 weeks wait targets. b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients. c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway. d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows. 4. Commissioning cycle support for grouping and re-costing previous activity. 5. Enables monitoring of: a. CCG outcome indicators. b. Non-financial validation of activity. c. Successful delivery of integrated care within the CCG. d. Checking frequent or multiple attendances to improve early intervention and avoid admissions. e. Case management. f. Care service planning. g. Commissioning and performance management. h. List size verification by GP practices. i. Understanding the care of patients in nursing homes. j. Service Transformation Projects (STP) 6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers. Commissioning (Pseudonymised) – SUS and Local Flows Data Processor 4 PI Benchmark The Integrated Commissioning Executive for Kirklees (which includes the local authority and both NHS Greater Huddersfield CCG and NHS North Kirklees CCG) wanted to better appreciate the potential and impact of how Better Care Fund monies were being utilised, and whether there were more effective ways to analyse or target the work. PI Care and Health were selected for this work based on their existing work in this field, their clarity in defining the detail of what could be done and how, their engagement and attitude, ability to deliver and price. Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS 1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, Integrated care and pathways. a. Analysis to support full business cases. b. Develop business models. c. Monitor In year projects. 2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3. Health economic modelling using: a. Analysis on provider performance against targets. b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients. c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway. 4. Commissioning cycle support for grouping and re-costing previous activity. 5. Enables monitoring of: a. CCG outcome indicators. b. Non-financial validation of activity. c. Successful delivery of integrated care within the CCG. d. Checking frequent or multiple attendances to improve early intervention and avoid admissions. e. Case management. f. Care service planning. g. Commissioning and performance management. h. List size verification by GP practices. i. Understanding the care of patients in nursing homes. 6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.

Outputs:

Invoice Validation 1. Addressing poor data quality issues 2. Production of reports for business intelligence 3. Budget reporting 4. Validation of invoices for non-contracted events Risk Stratification 1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients is derived from the GP data sourced from their own systems. 2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk. 3. Record level output will be available for commissioners (of the CCG), pseudonymised at patient level and aggregate with small number suppression. 4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient. Commissioning (Pseudonymised) – SUS and Local Flows 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals POD. e. Planned care by POD view – activity, finance plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of acute / community / mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include frequent flyers. 9. Mortality 10. Quality 11. Service utilisation reporting 12. Patient safety indicators 13. Production of reports and dash boards to support service redesign and pathway changes Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include frequent flyers. The Health Informatics Service THIS provides a range of data management functions and outputs as specified by the CCG. Outputs include the provision of pseudonymised data to allow it to be viewed and interrogated, as well as aggregate level reports. These outputs can take the form of data held in a secure data warehouse or files e.g. database, CSV, Excel files. The warehousing of data uses a robust and tested platform, i.e. the warehouse (HPS database) has been developed over circa 20 years to reflect commissioner/CCG requirements and is in a THIS IT environment, so is secure. Utilising THIS data management also provides the following benefits: • Utilising local knowledge and expertise on data flows that are specific to the CCG in particular data flowing from Calderdale and Huddersfield NHS Trust • Making efficient use of existing processes that are well established and tailored to the CCG requirements • Providing the resource / capacity required to process data flows for the CCG The aggregate outputs fall into the following areas: • Studying variation and trends over time • Monitoring of healthcare contract activity plans • Performance monitoring • Quality monitoring The categories of outputs to the CCG includes: • Monitoring of hospital activity against planned levels where an established contract exists between a provider and a commissioner inclusive of: o Overall contract reporting of actual vs plan for activity and value at aggregate level o Reconciliation reports between local hospital data, and SUS records at aggregate/anonymised in context level. o Contract Data Quality reporting at anonymised in context record level. • “Deep dive” analysis of hospital activity at aggregate level. Specific examples of report outputs include: Commissioner Reporting - Summary by Provider View – Plan and Actuals Year to Date (YTD) - Summary by Patient Outcome Data (POD) view - Plan and Actuals YTD - Summary by Provider View – Activity and Finance Variance by POD - Planned Care by Provider View – Activity and Finance Variance by POD - Planned Care by POD View – Activity, Finance Plan and Actuals YTD - Provider Reporting - Readmissions analysis - Production of aggregate reports for CCGs Business Intelligence - Production of project / Programme level dashboards - Monitoring of acute / community services - Budget reporting

Processing:

The DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO. The CCG and any Data Processor will only have access to records of its own CCG. Access is limited to those administrative staff with authorised user accounts used for identification and authentication. 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. Invoice Validation SUS Data is obtained from the SUS Repository to DSCRO. 1. DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the North of England CSU. 2. The CSU carry out the following processing activities within the CEfF for invoice validation purposes: a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the SUS data flow to validate the corresponding record in the backing data flow b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are: i. In line with Payment by Results tariffs ii. are in relation to a patient registered with a CCG GP or resident within the CCG area. iii. The health care provided should be paid by the CCG in line with CCG guidance.  3. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between the CSU CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc. Risk Stratification On or before 20th July 2017, one of these data processors will be instructed to cease delivery of risk stratification, at which point a data destruction certificate will also be requested from that data processor. Notification will be made in writing to both Data Processors of the decision to cease or continue service, NHS Digital will be sent a copy The data destruction certificate will also be shared with NHS Digital From the 21st of July 2017 there will be only one Data Processor for Risk Stratification for Greater Huddersfield. eMBED and NECS will run adjacently to one another until the 20th of July 2017 or until notified A data destruction certificate for the previous risk stratification data processor will be provided Data Processor 1- North England CSU (NECS) 1. Identifiable SUS data is obtained from the SUS Repository to Yorkshire Data Services for Commissioners Regional Office (DSCRO). 2. Data quality management and standardisation of data is completed by DSCRO and the data identifiable at the level of NHS number is transferred securely to North of England CSU, who hold the SUS data within the secure NECS network storage. 3. Identifiable GP Data is securely sent from the GP system to North of England CSU. 4. SUS data is linked to GP data in the risk stratification tool by the data processor. 5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier derived from SUS available to GPs is the NHS numbers of their own patients. Any further identification of the patients is derived from the GP data sourced from their own systems. 6. North of England CSU who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication. 7. Once North of England CSU has completed the processing, the CCG can access the online system via a secure network connection to access the data pseudonymised at patient level. Data Processor 2 eMBED 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 eMBED, who hold the SUS data within eMBED secure storage. 3. Identifiable GP Data is securely sent from the GP system to eMBED. 4. SUS data is linked to GP data in the risk stratification tool by the data processor. 5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier derived from SUS available to GPs is the NHS number of their own patients. Any further identification of the patients is derived from the GP data sourced from their own systems. 6. eMBED who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication. 7. Once eMBED has completed the processing, the CCG can access the online system via a secure network connection to access the data pseudonymised at patient level. Commissioning (Pseudonymised) – SUS and Local Flows Data Processor 2 eMBED 1. Yorkshire Data Services for Commissioners Regional Office / North England Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. Yorkshire / North of England DSCRO also obtains identifiable local provider data for the CCG directly from Providers. 2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North of England CSU for the addition of derived fields and analysis. 3. North of England CSU then pass the processed, pseudonymised data to both eMBED and the CCG. 4. eMBED receives the Pseudonymised data for the addition of derived fields, linkage of data sets and analysis. Linked data is limited to the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning: - SUS data and Local Provider data at pseudonymised level - Mental Health (MHSDS, MHLDDS, MHMDS) with SUS - Improving Access to Psychological Therapies (IAPT) with SUS - Diagnostic Imaging Dataset (DIDs) with SUS - Maternity (MSDS) with SUS - Children and Young People’s Health Services (CYPHS) with Local provider data - Mental Health (MHSDS, MHLDDS, MHMDS) with Local provider data - Improving Access to Psychological Therapies (IAPT) with Local provider data - Diagnostic Imaging Dataset (DIDs) with Local provider data - Maternity (MSDS) with Local provider data - Children and Young People’s Health Services (CYPHS) with Local provider data 5. eMBED securely transfer pseudonymised outputs for management use by the CCG. 6. The CCG receive Pseudonymised data from both North of England CSU and eMBED. The CCG then analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 7. Aggregation of required data for CCG management use will be completed by the North of England CSU, eMBED or the CCG as instructed by the CCG. 8. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared. 9. The CCG securely transfer Pseudonymised data back to the provider to: a) confirm how patients are reported in SUS, and how the commissioner can reliably group these patients into categories for points of delivery; b) allow for granular data validation whereby a commissioner may query the SUS record, and need to pass it back to the provider for checking; and c) to allow the provider to undertake further analysis of a cohort of their patients as requested and specified by the commissioner. The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider. Data Processor 3 The Health Informatics Service 1. Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. 2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North of England CSU for the addition of derived fields and analysis. 3. North of England CSU then pass the processed, pseudonymised data to the Health Informatics Service. The Health Informatics Service apply business rules, pricing and create additional categorical fields. 4. The Health Informatics Service securely transfer the Pseudonymised data to eMBED to flow directly to the CCG. 5. Aggregation of required data for CCG management use will be completed by the North of England CSU, eMBED or the CCG as instructed by the CCG. 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. 7. Data Processor 4 PI Benchmark 1. Yorkshire Data Services for Commissioners Regional Office (DSCRO) receive a flow of identifiable SUS data for Greater Huddersfield CCG from SUS. 2. Data quality management of data is completed by the DSCRO. The SUS data is then pseudonymised using University of Nottingham open pseudonymiser tool - a standalone windows desktop application which creates a digest of one or more columns of a CSV file, using a shared key (SALT file) controlled by Yorkshire Data Services for Commissioners Regional Office 3. The completed pseudonymised file is then passed to PI Limited (PI Care and Health) via secure FTP. 4. Data quality management of social care data is completed by Kirklees Council. The social care data is then pseudonymised using University of Nottingham open pseudonymiser tool. Pseudonymised Social Care Data will be sent to PI Limited (PI Care and Health) direct from Kirklees Council via secure FTP. 5. The pseudonymisation key cannot be used to re-identify data as the tool does not allow for this to happen, it only allows for one way pseudonymisation. 6. PI Limited (PI Care and Health) then link the data using the common pseudo link, which is undertaken within a controlled environment by a named member of staff, who then produce online reports using CareTrak data analysis tool to provide Greater Huddersfield CCG with a range of high level commissioning intelligence based on integrated pathways of care in Kirklees. Access to these reports is based on user access controls, as follows: - Access to the commissioning intelligence at pseudonymised level is accessible by 2 named members of staff in the CCG (based on a super user access licence for CareTrak) - Access to aggregate commissioning intelligence (anonymised) is available to up to 3 additional users across the CCG (standard user licence) - External aggregated reports only with small number suppression can be shared. Access to the CareTrak system, both on a super user and standard user approach is governed via respective organisation employee code of practice, data protection policies and information governance protocols. Additionally, super users conform to a specific information access agreement which mitigates the risk of how the pseudo data can be handled and used. The Integrated Commissioning Executive for Kirklees (which includes the local authority and both NHS Greater Huddersfield CCG and NHS North Kirklees CCG) wanted to better appreciate the potential and impact of how Better Care Fund monies were being utilised, and whether there were more effective ways to analyse or target the work. PI Care and Health were selected for this work based on their existing work in this field, their clarity in defining the detail of what could be done and how, their engagement and attitude, ability to deliver and price. Commissioning (Pseudonymised) – Mental Health, MSDS, IAPT, CYPHS and DIDS 1. North of England Data Services for Commissioners Regional Office (DSCRO) and Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtain a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS and MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes. 2. Data quality management, minimisation and pseudonymisation of data is completed by North of England and DSCRO and the pseudonymised data is then passed securely to North of England CSU. 3. North of England CSU then securely transfers the processed, pseudonymised and linked data to eMBED and the CCG. 4. a) The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning. b) eMBED receives the data from North of England CSU and carries out further data processing, addition of derived fields, linkage to other data sets and analysis. Linked data includes the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning: - Mental Health (MHSDS, MHLDDS, MHMDS) with IAPT - Mental Health (MHSDS, MHLDDS, MHMDS) with SUS - Improving Access to Psychological Therapies (IAPT) with SUS - Diagnostic Imaging Dataset (DIDs) with SUS - Maternity (MSDS) with SUS - Children and Young People’s Health Services (CYPHS) with SUS 5. Aggregation of required data for CCG management use is completed by the CSU or the CCG as instructed by the CCG. 6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared.


Project 3 — DARS-NIC-434767-Z4P3N

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

Sensitive: Sensitive

When: 2021/03 — 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, the data shared under this agreement can be used for these specified purposes except where they would require the reidentification of individuals. 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 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 patient’s 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 included in the GDPPR data set 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. Such uses 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 and to estimate 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 identification of the characteristics of a cohort that could subsequently, and separately, be used to identify individuals for intervention. However the identification of individuals will not be done as part of this data sharing agreement, and the data shared under this agreement will not be reidentified. • 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 only be linked by the Data Controller or their respective Data Processor, to other pseudonymised datasets which it holds under a current data sharing agreement only where such data is provided for the purposes of general commissioning by NHS Digital. The Health Service Control of Patient Information Regulations (COPI) will also apply to any data linked to the GDPPR data. 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. Reidentification of individuals is not permitted under this DSA. 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. Regulation 7 of COPI includes certain limitations. The request has considered these limitations, considering data minimisation, access controls and technical and organisational measures. 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 CCGs 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 due to the impact of COVID-19 • Analysis of resource allocation • Investigating and monitoring the effects of COVID-19 • Patient Stratification in relation to COVID-19, 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 For avoidance of doubt these are pseudonymised patient cohorts, not identifiable.

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 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 of patient level data is not permitted under this agreement. Only aggregated reports with small number suppression can be shared externally. 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 area). 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 4 — DARS-NIC-422221-W0P7K

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

Sensitive: Sensitive

When: 2021/03 — 2021/05.

Repeats: One-Off, Frequent Adhoc Flow

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information', National Health Service Act 2006 - s251 - 'Control of patient information'.

Categories: Anonymised - ICO code compliant, Identifiable

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
  • Medicines dispensed in Primary Care (NHSBSA data)
  • 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:

INVOICE VALIDATION Invoice validation is part of a process by which providers of care or services get paid for the work they do. Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is 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 (data from providers) and will not be used further. The CCG are advised by the appointed CEfF, North of England Commissioning Support Unit (NECS), whether payment for invoices can be made or not. Invoice Validation will be conducted by NHS North of England Commissioning Support Unit RISK STRATIFICATION Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) 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 both individual and groups of vulnerable 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. Risk Stratification will be conducted by NHS North of England 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) - 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) - Medicines Dispensed in Primary Care (NHSBSA Data) 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.  Provide intelligence about the safety and effectiveness of medicines. 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 Calderdale & Huddersfield NHS Foundation Trust hosting The Health Informatics Service, PI Care and Health Ltd (PI Limited) and NHS North of England Commissioning Support Unit (NECSU).

Expected Benefits:

INVOICE VALIDATION The invoice validation process supports the ongoing delivery of patient care across the NHS and the CCG region by: 1. Ensuring that activity is fully financially validated. 2. Ensuring that service providers are accurately paid for the patients treatment. 3. Enabling services to be planned, commissioned, managed, and subjected to financial control. 4. Enabling commissioners to confirm that they are paying appropriately for treatment of patients for whom they are responsible. 5. Fulfilling commissioners duties to fiscal probity and scrutiny. 6. Ensuring full financial accountability for relevant organisations. 7. Ensuring robust commissioning and performance management. 8. Ensuring commissioning objectives do not compromise patient confidentiality. 9. Ensuring the avoidance of misappropriation of public funds. 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 and health outcomes 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. 14. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed. 15. Insight to understand the numerous factors that play a role in the outcome for both 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. 16. Provision of indicators of health problems, and patterns of risk within the commissioning region. 17. Support of benchmarking for evaluating progress in future years. 18. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people. 19. Assists commissioners to make better decisions to support patients and drive changes in health care 20. Allows comparisons of providers performance to assist improvement in services – increase the quality 21. Allow analysis of health care provision to 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. 22. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one). 23. Monitoring of entire population, as a pose to only those that engage with services 24. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice. 25. Monitor the quality and safety of the delivery of healthcare services. 26. Allow focused commissioning support based on factual data rather than assumed and projected sources 27. Understand admissions linked to overprescribing. 28. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.

Outputs:

INVOICE VALIDATION 1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes. 2. Outputs from the CEfF will enable accurate production of budget reports, which will: a. Assist in addressing poor quality data issues b. Assist in business intelligence 3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s. 4. Budget control of the CCG. 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. 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. CCGs will be able to: 3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions. 4. Reduce hospital readmissions and targeting clinical interventions to high risk patients. 5. Identify patients at risk of deterioration and providing effective care. 6. Reduce in the difference in the quality of care between those with the best and worst outcomes. 7. Re-design care to reduce admissions. 8. Set up capitated budgets – budgets based on care provided to the specific population. 9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes. 10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly. 11. Health needs assessments – identifying numbers of patients with specific health conditions or combination of conditions. 12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost. 13. Production of Theographs – a visual timeline of a patients encounters with hospital providers. 14. Analyse based on specific diseases In addition: - The risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk. - Record level output (pseudonymised) will be available for commissioners (of the CCG), pseudonymised at patient level. Onward sharing of this data is not permitted. 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. 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 High cost activity uses (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 13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services. 14. 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. 15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support. 16. Understanding where patient 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. 17. Removal of patients from Risk Stratification reports. 18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity. 19. Manage demand, by understanding the quantity of assessments required CCGs are able to 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. 20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters. 21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals. 22. Allow Commissioners to better protect or improve the public health of the total local patient population 23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population 24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline. 25. Investigate mortality outcomes for trusts. 26. Identify medication prescribing trends and their effectiveness. 27. Linking prescribing habits to entry points into the health and social care system 28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy) The Health Informatics Service (THIS) THIS provides a range of data management functions and outputs as specified by the CCG. Outputs include the provision of pseudonymised data to allow it to be viewed and interrogated, as well as aggregate level reports. These outputs can take the form of data held in a secure data warehouse or files e.g. database, CSV, Excel files. The warehousing of data uses a robust and tested platform, i.e. the warehouse (HPS database) has been developed over circa 20 years to reflect commissioner/CCG requirements and is in a THIS IT environment, so is secure. Utilising THIS data management also provides the following benefits: • Utilising local knowledge and expertise on data flows that are specific to the CCG in particular data flowing from Calderdale and Huddersfield NHS Trust • Making efficient use of existing processes that are well established and tailored to the CCG requirements • Providing the resource / capacity required to process data flows for the CCG The aggregate outputs fall into the following areas: • Studying variation and trends over time • Monitoring of healthcare contract activity plans • Performance monitoring • Quality monitoring The categories of outputs to the CCG includes: • Monitoring of hospital activity against planned levels where an established contract exists between a provider and a commissioner inclusive of: o Overall contract reporting of actual vs plan for activity and value at aggregate level o Reconciliation reports between local hospital data, and SUS records at aggregate/anonymised in context level. o Contract Data Quality reporting at anonymised in context record level. • “Deep dive” analysis of hospital activity at aggregate level.

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. 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 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. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/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 ie: employees, agents and contractors of the Data Recipient who may have access to that data) The DSCRO (part of NHS Digital) will apply National Opt-outs before any identifiable data leaves the DSCRO only for the purpose of Risk Stratification. 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. The identifier available in the data set is the NHS numbers. Any further identification of the patients will only be completed by the patient’s clinician on their own systems for the purpose of direct care with a legitimate relationship. ONWARD SHARING: 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. 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. Where the Data Processor and/or the Data Controller hold identifiable data with opt outs applied and identifiable data with opt outs not applied, 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. 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 Kirklees CCG region (including historical activity where the patient was previously registered or resident in another commissioner). and/or • Patients treated by a provider where NHS Kirklees 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 Kirklees CCG - this is only for commissioning and relates to both national and local flows. For the purpose of Risk Stratification: • Patients who are normally registered and/or resident within the NHS Kirklees CCG region (including historical activity where the patient was previously registered or resident in another commissioner For the purpose of Invoice Validation: • Patients who are resident and/or registered within the CCG region. This includes data that was previously under a different organisation name but has now merged into this CCG 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). Equinix, Pulsant and IT Professional Services Ltd 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 Calderdale and Huddersfield NHS Foundation trust (hosting The Health Informatics Service) supply IT infrastructure 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. This includes granting of access to the database[s] containing the data. INVOICE VALIDATION NHS North of England CSU 1. Identifiable SUS+  Data is obtained by the Data Services for Commissioners Regional Office (DSCRO). 2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the NHS North of England CSU 3. The CEfF also receive backing data from the provider. 4. NHS North of England CSU carry out the following processing activities within the CEfF for invoice validation purposes: a. Validating that the Clinical Commissioning Group are responsible for payment for the care of the individual by using SUS+  and/or provider backing flow data. b. Once the provider 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. 5. 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 North of England CSU CEfF team and the provider, meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc. RISK STRATIFICATION NHS North of England CSU 1. Identifiable SUS+  data is transferred 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 , who securely hold the SUS+ data 3. Identifiable GP Data is securely sent from the GP system to NHS North of England CSU 4. SUS+ data is linked to GP data in the risk stratification tool by the data processor. 5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier 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. Once NHS North of England CSU has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level 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) 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) 19. Medicines Dispensed in Primary Care (NHSBSA Data) Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows: Data Processor 1 – North of England 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), Summary Hospital-level Mortality Indicator (SHMI) and Medicines Dispensed in Primary Care (NHSBSA Data) data only is securely transferred from the DSCRO to North of England Commissioning Support Unit 2. North of England 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. 4. North of England 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 North of England 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 - PI Care and Health Ltd (PI Limited) Data quality management and pseudonymisation is completed within the DSCRO. Pseudonymisation for this flow is done using the Nottingham Open Pseudonymisation Tool. The University of Nottingham open pseudonymiser tool is a standalone windows desktop application which creates a digest of one or more columns of a CSV file, using a shared key (SALT file) controlled by the DSCRO. 1. Pseudonymised SUS+ only is securely transferred from the DSCRO to PI Limited. 2. Data quality management of social care data is is completed by Kikrlees Council. The social care pseudonymised using University of Nottingham open pseudonymiser tool at Kirklees Council. The pseudonymised Social Care Data is sent to PI Limited from Kirklees Council via secure FTP. 3. The pseudonymisation key cannot be used to re-identify data as the tool does not allow for this to happen, it only allows for one way pseudonymisation. 4. PI Limited (PI Care and Health) then link the data using the common pseudo link, which is undertaken within a controlled environment by a named member of staff, who then produce online reports using CareTrak data analysis tool to provide NHS Kirklees CCG with a range of high level commissioning intelligence based on integrated pathways of care in Kirklees. Access to these reports is based on user access controls, as follows: - Access to the commissioning intelligence at pseudonymised level is accessible by 2 named members of staff in the CCG (based on a super user access licence for CareTrak) - Access to aggregate commissioning intelligence (anonymised) is available to up to 3 additional users across the CCG (standard user licence) - External aggregated reports only with small number suppression can be shared. Access to the CareTrak system, both on a super user and standard user approach is governed via respective organisation employee code of practice, data protection policies and information governance protocols. Additionally, super users conform to a specific information access agreement which mitigates the risk of how the pseudo data can be handled and used. The Integrated Commissioning Executive for Kirklees (which includes the local authority and NHS Kirklees CCG ) wanted to better appreciate the potential and impact of how Better Care Fund monies were being utilised, and whether there were more effective ways to analyse or target the work. PI Care and Health were selected for this work based on their existing work in this field, their clarity in defining the detail of what could be done and how, their engagement and attitude, ability to deliver and price.


Project 5 — DARS-NIC-241634-Z3F2L

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

Sensitive: Non Sensitive

When: 2019/03 — 2021/03.

Repeats: Frequent Adhoc Flow, Ongoing

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
  • Community-Local Provider Flows
  • SUS for Commissioners
  • Diagnostic Services-Local Provider Flows
  • Emergency Care-Local Provider Flows

Objectives:

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 Diagnostic Service o Emergency Care 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 Kier Business Services Limited and Dr Foster Limited (Hosting the eMBED Health Consortium), NHS North Kirklees CCG, North of England Commissioning Support Unit, NHS Wakefield CCG.

Expected Benefits:

1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways. a. Analysis to support full business cases. b. Develop business models. c. Monitor In year projects. 2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3. Health economic modelling using: a. Analysis on provider performance against 18 weeks wait targets. b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients. c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway. d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC). 4. Commissioning cycle support for grouping and re-costing previous activity. 5. Enables monitoring of: a. CCG outcome indicators. b. 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:

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 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. Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data. All access to data is managed under Roles-Based Access Controls. No patient level data will be linked other than as specifically detailed within this agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality and that data required by the applicant. NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data) Segregation Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked. All access to data is auditable by NHS Digital. Data Minimisation Data Minimisation in relation to the data sets listed within section 3 are listed below. This also includes the purpose on which they would be applied - • Patients who are normally registered and/or resident within Wakefield CCG and North Kirklees CCG (including historical activity where the patient was previously registered or resident in another commissioner). and/or • Patients treated by a provider where Wakefield CCG and North Kirklees CCG are 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 Wakefield CCG and North Kirklees CCG - this is only for commissioning and relates to both national and local flows. Calderdale and Huddersfield NHS Foundation Trust supply IT infrastructure 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. This includes granting of access to the database[s] containing the data. Telecity, Yeadon Community Health Centre, Telstra, Pulsant, BDO and Engine 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. 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. Diagnostic Service e. Emergency Care Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows: 1. Pseudonymised SUS+ and Local Provider data only is securely transferred from the DSCRO to North of England Commissioning Support Unit. 2. North of England Commissioning Support Unit add derived fields. 3. North of England Commissioning Support Unit pass the pseudonymised data to Kier Business Services Limited (Hosting the eMBED Health Consortium) (to point 6). 4. North of England Commissioning Support Unit analyse the data 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 6. Kier Business Services Limited (Hosting the eMBED Health Consortium) analyse the data and then pass the data to Dr Foster Limited (Hosting the eMBED Health Consortium). Kier Business Services Limited and Dr Foster Limited (Hosting the eMBED Health Consortium) 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 7. Allowed linkage is between the data sets contained within point 1. 8. The eMBED Health Consortium then pass the processed, pseudonymised and linked data to the CCG. 9. Aggregation of required data for CCG management use will be completed by North of England Commissioning Support Unit, Kier Business Services Limited and Dr Foster Limited (Hosting the eMBED Health Consortium) or the CCG as instructed by the CCG. 10. 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. 11. The CCG receive outputs from both North of England Commissioning Support Unit and eMBED Health Consortium (Hosted by the Kier Group and Dr Foster) to enable comparators. 12. The CCG securely transfer pseudonymised data back to the provider to: a) confirm how patients are reported in SUS, and how the commissioner can reliably group these patients into categories for points of delivery; b) allow for granular data validation whereby a commissioner may query the SUS record, and need to pass it back to the provider for checking; and c) to allow the provider to undertake further analysis of a cohort of their patients as requested and specified by the commissioner. The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider.


Project 6 — DARS-NIC-191964-Y3Z1L

Opt outs honoured: Yes - patient objections upheld (Section 251, Section 251 NHS Act 2006)

Sensitive: Sensitive, and Non Sensitive

When: 2019/01 — 2021/03.

Repeats: Frequent Adhoc Flow, One-Off

Legal basis: National Health Service Act 2006 - s251 - 'Control of patient information'.

Categories: Identifiable

Datasets:

  • SUS for Commissioners

Objectives:

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 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 a forecast of future demand by identifying high risk 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. Risk Stratification will be conducted by North of England Commissioning Support Unit (NECS).

Expected Benefits:

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.

Outputs:

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. 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.

Processing:

Data must only be used as stipulated within this Data Sharing Agreement. Data Processors must only act upon specific instructions from the Data Controller. Data can only be stored at the addresses listed under storage addresses. The Data Controller and any Data Processor will only have access to records of patients of residence and registration within the CCG. Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data. All access to data is managed under Roles-Based Access Controls 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. 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 of interest of the applicant. The DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO. 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 audited For the purpose of Risk Stratification: • Patients who are normally registered and/or resident within the commissioner (including historical activity where the patient was previously registered or resident in another commissioner The above relates to data requested only (Table 3B). Data currently held (Table 3A) will have the following Data Minimisation: • CCG of residence and/or registration. For clarity, any access by Pulsant, Huddersfield Royal Infirmary, Calderdale Royal Hospital or Yeadon Community Health Centre to 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. Risk Stratification Data Processor 1 – North of England Commissioning Support Unit 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 North of England 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 North of England 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. 6. Once North of England 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


Project 7 — DARS-NIC-159523-F1C1P

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

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)

Categories: Anonymised - ICO code compliant

Datasets:

  • SUS for Commissioners

Objectives:

The purpose of this data flow is to enable the Integrated Commissioning Exec –ICE (Kirklees Council, NHS North Kirklees CCG and NHS Greater Huddersfield CCG) to understand how services, and the trajectory of service users interact around social care provision and hospital utilisation (by linking pseudonymised social care data with pseudonymised SUS data).

Yielded Benefits:

The complexity of initiating integrated working, the related internal (to Kirklees as a locality) political landscape, and information governance have in their various ways complicated how the intended work was addressed. Ultimately meaning that there are no immediate benefits, but it has provided us with the insight, means and understanding of how we can move forward in a meaningful way

Expected Benefits:

1. Improved performance against national Better Care Fund metrics 2. Reduction in A&E attendances (especially for elderly persons) 3. Reduction in emergency hospital admissions (especially for elderly persons) 4. Accurate evaluation of local Better Care Fund schemes 5. Accurate evaluation of system transformation of Intermediate Care 6. Improved experience of service users 7. Improved health outcomes 8. Improved social care outcomes 9. Improved productivity thorough streamlining and integration of services.

Outputs:

Reports, analyses and dashboards to support the integration of health and social care including: 1. Falls 2. Better Care Fund national metrics 3. Better Care Fund local schemes 4. Intermediate Care

Processing:

Data must only be used as stipulated within this Data Sharing Agreement. Data Processors must only act upon specific instructions from the Data Controller. Data can only be stored at the addresses listed under storage addresses. The Data Controller and any Data Processor will only have access to records of patients of residence and registration within North Kirklees CCG and Greater Huddersfield CCG. Patient level data will not be shared outside of the Local Authority 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. 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 of interest of 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 audited The Data Services for Commissioners Regional Office (DSCRO) obtains the following data set: 1. SUS+ Data quality management and pseudonymisation is completed within the DSCRO using the Nottingham Open Pseudonymiser tool and is then disseminated as follows: Data Processor – PI Limited 1) Pseudonymised SUS+ is securely transferred from the DSCRO to PI Limited. 2) Kirklees Metropolitan Council pseudonymise social care data using the Nottingham Open Pseudonymiser tool. 3) Kirklees Metropolitan Council then securely transfer the pseudonymised social care data to PI Limited. 4) PI Ltd link the SUS+ data and Social Care and load the data into the CareTrak Business Intelligence Tool 5) Data will only be shared within the Council 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.